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i

A THESIS FOR THE DEGREE OF MASTER OF SCIENCE

Single Nucleotide Polymorphism Marker Discovery

by Transcriptome Sequencing in Capsicum

고추 전사체를 통한

단일염기다형성 분자마커개발

August 2014

PHILLIP CHOE

MAJOR IN HORTICULTURAL SCIENCE

DEPARTMENT OF PLANT SCIENCE

THE GRADUATE SCHOOL OF SEOUL NAIONAL UNIVERSITY

i



UNDER THE DIRECTION OF DR. BYOUNG-CHEORL KANG

SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL

OF SEOUL NATIONAL UNIVERSITY

BY

PHILLIP CHOE

MAJOR IN HORTICULTURAL SCIENCE


THE GRADUATE SCHOOL OF SEOUL NATIONAL UNIVERSITY

August 2014

APPROVED AS A QUALIFIED DISSERTATION OF PHILLIP CHOE

FOR THE DEGREE OF MASTER OF SCIENCE

BY THE COMMITTEE MEMBERS

CHAIRMAN _____________________________

Jin Hoe Huh, Ph.D.

VICE-CHAIRMAN _____________________________ Byoung-Cheorl Kang, Ph.D.

MEMBER _____________________________

Eun Jin Lee, Ph.D.

i



PHILLIP CHOE


THE GRADUATE SCHOOL OF SEOUL NATIONAL UNIVERSITY

ABSTRACT

Backcross breeding is the method most commonly used to introgress

new traits into elite lines. Conventional backcross breeding requires at least 4-

5 generations to recover the genomic background of the recurrent parent.

ii

Marker-assisted backcrossing (MABC) represents a new breeding approach

that can substantially reduce breeding time and cost. For successful MABC,

highly polymorphic markers with known positions in each chromosome are

essential. Single nucleotide polymorphism (SNP) markers have many

advantages over other marker systems for MABC due to their high abundance

and amenability to genotyping automation. To facilitate MABC in hot pepper

(Capsicum annuum), we utilized expressed sequence tags (ESTs) to develop

SNP markers in this study. For SNP identification, we used Bukang F1-hybrid

pepper ESTs to prepare a reference sequence through de novo assembly. We

performed large-scale transcriptome sequencing of eight accessions using the

Illumina Genome Analyzer (IGA) IIx platform by Solexa, which generated

small sequence fragments of about 90-100 bp. By aligning each contig to the

reference sequence, 58,151 SNPs were identified. After filtering for

polymorphism, segregation ratio, and lack of proximity to other SNPS or

exon/intron boundaries, a total of 1,910 putative SNPs were chosen and

positioned to a pepper linkage map. We further selected 412 SNPs evenly

distributed on each chromosome and primers were designed for high

throughput SNP assays and tested using a genetic diversity panel of 27

Capsicum accessions. The SNP markers clearly distinguished each accession.

These results suggest that the SNP marker set developed in this study will be

valuable for MABC, genetic mapping, and comparative genome analysis.

iii

Key words: Capsicum annuum, expressed sequence tag (EST),

linkage map, marker-assisted breeding (MAB), single

nucleotide polymorphism (SNP), next generation

sequence (NGS)

Student Number: 2009-23245

iv

CONTENTS

ABSTRACT ...................................................................................... i

CONTENTS ....................................................................................... iv

LIST OF TABLES ............................................................................. vii

LIST OF FIGURES ............................................................................ viii

LIST OF ABBREVIATIONS ............................................................ ix

INTRODUCTION ............................................................. 01

LITERATURE REVIEWS .............................................. 04

Molecular marker Developments in the past ............................... 04

Use of molecular marker in Capsicum ........................................ 07

SNP marker discovery ................................................................. 08

EST-derived marker discovery .................................................... 08

SNP discovery in other crops by using ESTs .............................. 09

v

Sequencing technology development .......................................... 10

LITERATURE CITED ..................................................... 14

MATERIALS AND METHODS ..................................... 22

Plant material preparation for eight accessions ........................... 22

RNA extraction for each sample ................................................. 22

Sequencing of transcriptomes for eight accessions ..................... 25

Quality trimming for sequences .................................................. 25

Reference sequence preparation .................................................. 27

Repeat Masking on the reference sequence ................................. 27

Alignment to the reference sequence........................................... 27

SNP calling and filtering ............................................................ 28

Linkage mapping ......................................................................... 28

Polymorphism survey and genetic diversity ................................ 32

vi

RESULTS ........................................................................... 33

Sequencing of hot pepper accessions and quality trimming ....... 34

Alignment of each accession to the reference sequence.............. 35

SNP discovering and SNP filtering ............................................. 37

Development and validation of SNP markers ............................. 39

DISCUSSION .................................................................... 47

REFERENCES .................................................................. 51

ABSTRACT IN KOREAN ............................................... 57

vii

LIST OF TABLES

Table 1. Comparisons of various markers

Table 2. Next generation DNA Sequencing technology

Table 3. Description of Capsicum used in this study

Table 4. Sequencing features of each accession

Table 5. Sequencing information from eight pepper accessions

Table 6. Alignment result of each accession to the reference

Table 7. SNP filtering process

Table 8. The number of SNPs and density in each pepper linkage group

Table 9. Origins of 27 accessions used for polymorphism survey of the SNP

markers

Supplementary Table 1. Detailed information for 412 SNP probes

viii

LIST OF FIGURES

Figure 1. Alignment to the reference and finding SNPs

Figure 2. SNP Selection through filtering process

Figure 3. Overall Process for SNP discovery

Figure 4. Location of 412 SNP markers on pepper linkage map

Figure 5. Polymorphism survey of the 412 SNP markers in cultivars

ix

LIST OF ABBREVIATION

AFLP amplified fragment length polymorphisms

BGI Beijing Genome Institute

BWA Burrows-Wheeler aligner

CCD charge-coupled device

COSII conserved ortholog set II

DEPC diethyl pyrocarbonate

DNA deoxyribonucleic acid

EST expressed sequence tag

GA genome analyzer IIx

HRMA high-resolution melt analysis

KRIBB Korea Research Institute of Bioscience & Biotechnology

LINE long interspersed nuclear element

LTR long terminal repeat

MAB marker assisted breeding

MABC marker assisted backcrossing

x

MAS marker assisted selection

NGS next generation sequencing

NICEM National Instrumentation Center for Environmental Management

PTP Pico Titer Plate

RAPD random amplified polymorphic DNA

RFLP restriction fragment length polymorphisms

RT reverse transcriptase

SNP single nucleotide polymorphism

SOLiD sequencing by oligo ligation and detection

SSR simple sequence repeat

WGS whole genome sequence

1

INTRODUCTION

Hot pepper (Capsicum annuum) is a crop of major economic

importance that is commercially cultivated in China, Korea, the East Indies,

and the United States of America, among many other countries (Shao et al.,

2008). Worldwide production of hot peppers has been estimated to be 14-15

million tons a year (Weiss, 2002). In fact, hot pepper is the vegetable

accounting for the largest planting area in Korea.

In commercial breeding, new traits are commonly introduced into elite

breeding lines using conventional backcross methods, which involve time

consuming efforts to transfer target genes into the genetic background of a

recipient parent. Recently marker-assisted backcrossing (MABC), which is

more efficient and faster than conventional backcrossing, has been generally

accepted as an advanced plant breeding technique (Blum et al., 2002). For the

successful application of MABC, factors to consider include the number of

target genes to be transferred, the genome size of the crop species, and the

availability of a highly saturated map. Among those factors, the availability of

highly polymorphic markers with known positions in each chromosome is

critical (Varshney et al., 2009). Although molecular markers based on

restriction fragment length polymorphism (RFLP), amplified fragment length

polymorphism (AFLP), and random amplified polymorphic DNA (RAPD)

have been developed and used in practical plant breeding (Imelfort et al., 2009;

2

Jung et al., 2010; Kang et al., 2001; Paran et al., 2004; Yoo et al., 2003), such

markers still have limitations for use in MABC due to the difficulty of finding

polymorphisms among breeding lines or of high throughput genotyping.

Recently, single nucleotide polymorphism (SNP) markers have captured

attention because of their potentiality for high-throughput detection and

computerization with automated platforms (Jung et al., 2010; Vignal et al.,

2002; Yi et al., 2006).

SNPs are single-base differences in DNA between accessions. In

plants, SNPs generally occur in populations once every few hundred base

pairs (Metzker, 2005). SNP markers can be developed through several

methods. For example, SNPs can be identified by simply comparing a

candidate sequence to a reference sequence (Nicolai et al., 2012), by whole

genome sequencing (WGS; Goff et al., 2002; The Arabidopsis Genome

Initiative, 2000), or by sequence alignment of expressed sequence tags (ESTs)

to a reference sequence (Kota et al., 2001; Labate and Baldo, 2005; Jones,

2009). For the crops like hot pepper, in which the genome is huge, ESTs have

been adopted as an alternative to WGS and as a substrate for cDNA array-

based expression analyses (Kim et al., 2008; Rudd, 2003). ESTs are a few

hundred base pairs of sequence derived from randomly selected cDNA clones

prepared from specific tissues, and EST sequencing is inexpensive compared

to WGS. These characteristics led us to test whether SNP markers could be

developed from several pepper accessions using ESTs generated with next

generation sequencing (NGS) technology.

3

NGS is a fast and low cost method for the large-scale generation of

reliable and robust transcript sequences and identifying and characterizing

genetic polymorphisms in plants (Imelfort et al, 2009, Metzker, 2010). The

Illumina Genome Analyzer (IGA) used to be the most widely used platform

based on amplified sequencing features generated by bridge PCR (Shendure

and Ji, 2008). Since the IGA reads only short sequences (75-100 base pairs;

Flicek and Birney, 2009), SNPs can be identified by either de novo assembly

of short sequence reads or alignment to the reference. Several factors can

interfere with correct sequence alignment; these include missing calls of

overlapping genotypes (Anney et al., 2008), false discovery of polymorphic

SNPs (Pettersson et al., 2008), homozygote to heterozygote miscalls (Teo et

al., 2007), and allelic dropout (Pompanon et al., 2005).

Here, we describe a process for SNP development from transcriptome

sequencing of peppers. The resulting SNP primers clearly distinguished

between 27 tested Capsicum cultivars, demonstrating that the SNP markers

developed in this study will be useful resources to facilitate MABC in pepper.

4

LITERATURE REVIEW

Molecular marker Developments in the past

Molecular marker is a DNA sequence which can be detected and its

further inheritance can be monitored (Kumar, 2009). With development of

molecular markers, the applications in breeding also have been increased in

terms of selecting, backcrossing, and pyramiding (Collard, 2008). There are

two types of markers classified; One with hybridization-based, such as

restriction fragment length polymorphisms (RFLP) (Botstein, 1980), and the

other with PCR-based, such as random amplified polymorphic DNA (RAPD)

and amplified fragment length polymorphisms (AFLP) (Paran, 1998; VOS,

1995). RFLP is known as the first DNA profiling technic which breaks down

the DNA with restrict enzyme and put those cut-fragment under

electrophoresis (Beckmann, 1983). Although, its high reliability in

determining homozygosis/heterozygosis (Winter & Kahl, 1993), it is time and

labor consuming (Powell, 1996). RAPD method amplifies random segment of

DNA with arbitrary primers. Having advantage of small amount of template

DNA and no sequence data for primer construction, however its drawback is

low reproducibility and non-locus-specificity (Tingey, 1993). AFLP is

believed a transition between RFLP and PCR in terms of selectively

amplifying restriction fragments after breakdown of genomic DNA. The

strength is their abundance in genome, high replicability and not requiring for

5

primer construction sequence data (Mueller & Wolfenbarger, 1999). However,

its requirement for high molecular weight of DNA, difficulty of recognizing

allele, and less reproducibility are considered as main disadvantages (Majer,

1996). Recent year, simple sequence repeat (SSR), which is a simple

combination of 1-6 short motifs, became popular because of their high

genomic abundance and co-dominance of alleles (Morgante et al., 2002).

Despite of all achievement in developing various types of markers, today,

Single Nucleotide Polymorphism (SNP), which is a single base change in a

DNA sequence, becomes promising marker in their highly abundance and less

prone to mutations (Giordano et al. 1999; Vignal, 2002).

Moreover, SNP markers have captured the attentions in recent years

due to their availability for high-throughput detections and computerized with

automated platforms (Mammadov et al. 2012). It is powerfully effective for

genome mapping and identification of candidate genes for Quantitative Trait

Loci (QTL) (Liu and Cordes, 2004). SNPs are widely used in marker assisted

selection (MAS) or marker assisted backcrossing (MABC) in today’s

agriculture as mass finding technologies have been developed in the last few

decades. (Table 1)

6

Table 1. Comparisons of various markers

Features RFLP RAPD AFLP SSR SNP

First introduce (Year) 1974 1990 1995 1992 1994

DNA requirement (µg) 10 0.02 0.5-1.0 0.05 0.05

PCR based No Yes Yes Yes Yes

DNA quality High High Moderate Moderate High

Development cost Low Low Moderate High High

Cost per analysis High Low Moderate Low Low

Reference Grodzicker et al. Williams et al. Vos et al. Akkaya et al. Jordan et al

(1974) (1990) (1995) (1992) (1994)

Reprinted and edited from “Potential of Molecular Markers in Plant Biotechnology” by Kumar et al. 2009. Plant Omics

Journal. 2:141-162.

Reprinted and edited from “Molecular Markers: History, Features and Applications” by Maheswaran. 2004. Advanced Biotech.

Aug:17-24.

7

Use of molecular marker in Capsicum

Over the last decade, molecular markers have become a new wave of

breeding technologies because of their many advantages such as cost and time

savings. Capsicums is the most economical crops undergone marker discovery

and thousands of markers have been placed into a genetic map. First inter-

specific hybrid of Capsicum annuum x Capsicum chinense map was

constructed and later RFLP markers developed in 19 linkage groups (Tanksley,

1988; Prince et al, 1993; Kim et al. 1997). In addition, total 13 linkage groups

were created by inter-specific F2 population of Capsicum annuum x Capsicum

chinense using PCR based markers, mostly AFLP (Livingstone, 1999).

Another map was constructed with 150 RFLP and 430 AFLP markers in 16

linkage groups (Kang, 2001). With all these previously discovered markers,

integrated map was constructed consisting of AFLP, RFLP, and RAPD (Paran,

2004). Recently, SSR marker, which are easy applicable and sensitive in

between species, are widely used (Yi et al, 2006). There has been successful

positioning of orthologous markers between tomato and pepper genomes

using F2 of intra-specific varieties, Capsicum frutescens x Capsicum annuum,

additional conserved ortholog set II (COSII) markers into pepper map (Wu,

2009). Despite of all different types of valuable markers and their discoveries,

SNP marker in Capsicum have become most popular markers because of their

high abundance and easy detection of polymorphism (Jung, 2010).

8

SNP marker discovery

SNPs are single base differences in DNA between accessions (Trick,

2009). In general, the average occurrence in population is once every few

hundred base pairs (Metzker, 2005). Various methods were applied to

discover SNPs in many crops regardless their genomes are completely

sequenced or not. For rice, direct sequencing verified SNPs (Feltus et al.

2004), and sequence/resequence method was used in grapevine (Lijavetzky et

al., 2007), target induced local lesion in genomes (McCallum et al., 2000) and

TaqMan assay (Lee et al., 1999) were applied to detect SNPs. Other

techniques are high-resolution melt analysis (HRMA) (McGlauflin et al., 2010)

and the sequence alignment using expressed sequence tag (EST) database in

barley, tomato, and maize (Kota et al., 2001; Labate and Baldo, 2005; Jones,

2009). EST database mining is an efficient SNP discovery method and first

introduced in human SNP finding (Picoult-Newberg, 1999), but it is limited to

the sufficient ESTs with existing genotype in the database.

EST-derived marker discovery

Sequencing/resequencing methods are limited to when whole genome

sequence is known. Yet, these only have been successful in small genome

plants with whole genome reference, such as rice and Arabidopsis (Yamamoto

et al., 2010; Ossowski et al., 2008). Therefore, in the absence of reference

sequence, de novo assembly can be used as an alternative reference, which is a

9

computerized algorithm that put together small sequences to make a full

length sequence (Ashrafi, 2012). Upon assemble thousands of sequence

fragments to make a long reliable reference, the most widely used and publicly

available in terms of the number of sequences and the total nucleotide count is

EST (Rudd, 2003). ESTs are short single sequences fragments consisting of

few hundred base pair, which are derived by randomly selected cDNA clones

(Hong, 1998). Since, ESTs are abundant in database, and represent portion of

expressed gene, it has been widely used in marker development. For

Capsicum, there are many researches successfully finding markers using ESTs;

1,201 SSRs from 10,232 EST (Yi, 2006), SNPs and SSRs discovery using

Sanger-EST and Illumina sequence assembly (Ashrafi, 2012), and Roche 454

pyrosequencing and de novo assembly of Capsicum annuum ESTs (Nicolai,

2012), and transcriptome profiling with SSRs and SNPs discovery from EST

using 454 pyrosequencing (Lu, 2012).

SNP discovery in other crops by using ESTs

There have been many researches which develop markers from

mining ESTs, because, crop ESTs are public accessible and by assembling

these, we may get big portion of cDNAs. Group of researchers have found 62

SNPs and 12indels in 21 Unigenes of Tomato (Labate and Baldo, 2005). By

deep re-sequencing of a reduced representation library (RRL) and scaffolds in

Soybean, up to 25,047 SNPs have found and among them only 1790 SNPs

10

become as markers (Hyten, 2010). Recently, numbers of SNPs and SSR in the

pepper have been found by using Maor, Early Jalapeno and Criollo de

Morelos (Ashrafi et al. 2012). These great achievements are all for the

improvement and cost down of sequencing technology. In recent days, NGS

techniques are widely applied for SNP marker development because it

produces millions sequence reads in a single run that make sequencing process

relatively fast and cut down the cost (Hayes et al., 2007).

Sequencing technology development

Since, DNA sequencing technology has been developed, tremendous

amount of molecular data have been produced including marker, ESTs and

even whole genome sequence. However, those DNA sequences to date have

mainly relied on various version of Sanger biochemistry (Sanger, 1977). In

Sanger method, DNA is fragmented, cloned and transformed into bacterial

colony. Cycle sequencing reaction follows, generating ddNTP-terminated,

dye-labeled product, which will undergo high resolution electrophoretic

separation in capillaries. As fluorescently labeled fragment move through a

detector, spectrum is used to trace the sequence. Sanger method sequencing is

highly accurate as 99.9% and today the read achieve is up to ~ 1,000bp, but

their high cost with time consuming and labor intensity are the fact which

makes it less favorable (Shendure and Ji, 2008). With technical advancement,

over the last ten years, new methods called NGS have utterly changed the

11

DNA sequencing strategy. NGS do not rely on traditional Sanger method,

which is labeled DNA fragments are physically resolved by electrophoresis

(Richardson, 2010). Among various methods, Roche/454 is known as first

NGS system. It produces relatively long sequences of 200 - 300bp per read

with more than 400,000 reads per run (Bubnoff, 2008). In brief, encapsulated

bead-DNA complex are PCR-amplified to produce beads, which contain

thousands copies of the same template sequence. Those beads are attached to a

pico titer plate (PTP) which eventually undergoes the pyrosequencing reaction

as detecting the generated light (Metzker, 2005). Roche 454 doesn’t directly

read individual bases, but it reads the number of As, Cs, Gs, or Ts at the

current position (Brockman, 2008). Another popular one with short sequence

read of 35-75bp is Solexa, Illumina Genome Analyser II (Imelfort, 2009),

which is based on the concept of sequencing by synthesis technology. Fixed

adapter containing library is denatured and amplified to make clusters

containing thousands of the same DNA fragments. The library splices into

single strands followed by complementation of fluorescent-dye containing

four different kinds of nucleotides (ddATP, ddGTP, ddCTP, ddTTP) and the

signal is detected by charge-coupled device (CCD) camera (Liu, 2012). Later

in 2007, sequencing by oligo ligation and detection (SOLiD) sequencer was

commercialized which sequence by DNA ligase, which takes 5 days to

produce 3 - 4Gb of sequence data with an average read length of 25 - 35bp

(Mardis, 2008). In brief in the system, the fluorescent signals are captured

while the probes are complemented to the template strand followed by

vanishing process by the cleavage (Liu, 2012). HeliScope is unique with its

12

not requiring clonal amplification which led to small amount of materials, and

rather fluorescence detection system is used to directly recognize single DNA

through sequencing by synthesis (Thompson, 2011). It makes average length

of 25bp with high accuracy. Today’s rapid development in bioinformatics and

technology have led tremendous improvement in sequencing DNA and

furthermore mapping, therefore rapid development in practical application

such as MAS and MABC. (Table 2)

13

Table 2. Next generation DNA Sequencing technology

Feature generation By synthesis Cost Paird-end 1 ° error Read length

/megabase /instrument

454 Emulsion PCR Polymerase ~$60 $500,000 Yes Indel 250bp

Solexa Bridge PCR Polymerase ~$2 $430,000 Yes Subst. 36bp

SOLiD Emulsion PCR Ligase ~$2 $591,000 Yes Subst. 35bp

HeliScope Single molecule Polymerase ~$1 $1,350,000 Yes Del 30bp

Note. Cost values are in US dollars.

Reprinted from “Next-generation DNA sequencing” by Jay Shendure & Hanlee Ji. 2008. Nature Biotechnology. 26:1135-1145.

Copyright 2008 by Nature Publishing Group.

14

LITERATURE CITED

Ashrafi H, Hill T, Stoffel K, Kozik A, Yao J, Chin-Wo SR. 2012. De novo

assembly of the pepper transcriptome (Capsicum annuum): a benchmark

for in silico discovery of SNPs, SSRs and candidate genes. BMC

Genomics 13

Beckmann JS, Soller M. 1983. Restriction fragment length polymorphisms in

genetic improvement: methodologies, mapping and costs. Theor Appl

Genet 67:35-43

Botstein D, White RL, Skolnick M, Davis RW. 1980. Construction of a

Genetic Linkage Map in Man Using Restriction Fragment Length

Polymorphisms. Am J Hum Genet 32:314-31

Brockman W, Alvarez P, Young S, Garber M. 2008. Quality scores and SNP

detection in sequencing-by-synthesis systems. Genome Research 18:763-

70

Collard BCY, Mackill DJ. 2008. Marker-assisted selection: an approach for

precision plant breeding in the twenty-first century. Phil. Trans. R. Soc. B

363:557-72

Feltus FA, Wan J, Schulze SR. 2004. An SNP Resource for Rice Genetics and

Breeding Based on Subspecies Indica and Japonica Genome Alignments.

Genome Res. 14:1812-9

15

Giordano M, Oefner PJ, Underhill PA. 1999. Identification by Denaturing

High-Performance Liquid Chromatography of Numerous Polymorphisms

in a candidate Region for Multiple Sclerosis Susceptibility. Genomics

56:247-53

Hayes B, Laerdahl JK, Lien S, Moen T, Berg P. 2007. An extensive resource

of single nucleotide polymorphism markers associated with Atlantic

salmon (Salmo salar) expressed sequence. Aquaculture 265:82-90

Hong S-T, Chung J-E, An G, Kim S-R. 1998. Analysis of 176 Expressed

Sequence Tags Generated from cDNA Clones of Hot Pepper by Single-

pass Sequencing. J. Plant Biol. 41:116-24

Hyten DL, Cannon SB, Song Q, Weeks N, Fickus EW, Shoemaker RC. 2010.

High-throughput SNP discovery through deep resequencing of a reduced

representation library to anchor and orient scaffolds in the soybean whole

genome sequence. BMC Genomics 11

Imelfort M, Duran C, Batley J, Edwards D. 2009. Discovering genetic

polymorphisms in next-generation sequencing data Plant Biotechnology

Journal 7:312-7

Jones E, Chu W-C, Ayele M, Ho J, Bruggeman E, et al. 2009. Development of

single nucleotide polymorphism (SNP) markers for use in commercial

maize (Zea mays L.) germplasm. Mol Breeding 24:165-76

16

Jung J-K, Park S-W, Liu WY, Kang B-C. 2010. Discovery of single

nucleotide polymorphism in Capsicum and SNP markers for cultivar

identification. Euphytica 175:91-107

Kang BC, Nahm SH, Huh JH, Yoo HS, Yu JW, et al. 2001. An interspecific

(Capsicum annuum x C. chinese) F2 linkage map in pepper using RFLP

and AFLP markers. Theor Appl Genet 102:531-9

Kim B-D, Kang BC, Nam SH, Kim BS. 1997. Construction of a Molecular

Linkage Map and Development of a Molecular Breeding Technique. J.

Plant Biol. 40:156-63

Kota R, Varshney RK, Shiel T, Dehmer KJ, Andereas G. 2001. Generation

and comparison of EST-derived SSRs and SNPs in barley (Hordeurn

vulgare L.). Hereditas 135:145 - 51

Kumar P, Gupta VK, Misra AK, Modi DR, B.K. P. 2009. Potential of

Molecular Markers in Plant Biotechnology. Plant Omics Journal 2:141-62

Labate JA, Baldo AM. 2005. Tomato SNP discovery by EST mining and

resequencing. Molecular Breeding 16:343-9

Lee LG, Livak KJ, Mullah B, Graham RJ. 1999. Seven-Color, Homogeneous

Detection of Six PCR Products. BioTechniques 27

17

Lijavetzky D, Cabezas JA, Ibanex A, Rodriguez V. 2007. High throughput

SNP discovery and genotyping in grapevine (Vitis vinifera L.) by

combining a re-sequencing approach and SNPlex technology. BMC

Genomics 8

Liu L, Li Y, Li S, Hu N, He Y, et al. 2012. Comparison ofNext-Generation

Sequencing Systems. Journal of Biomedicine and Biotechnology 2012

Liu ZJ and Cordes JF. 2004 . DNA marker technologies and their applications

in aquaculture genetics. Aquaculture 238:1-37

Livingstone KD, Lackney VK, Blauth JR, van Wijk R, Jahn MK. 1999.

Genome Mapping in Capsicum and the Evolution of Genome Structure in

the Solanaceae. Genetics 152:1183-202

Lu F-H, Cho M-C, Park Y-J. 2012. Transcriptome profiling and molecular

marker discovery in red pepper, Capsicum annuum L. TF68. Mol Biol Rep

39:3327-35

Maheswaran M. 2004. Molecular Markers: History, Features and Application.

Advanced Biotech

Majer D, Mithen R, Lewis BG, Vos P, Oliver RP. 1996. The use of AFLP

fingerprinting for the detection of genetic variation in fungi. Mycol. Res.

100:1107-11

Mammadov Jafar, Aggarwal Rajat, Buyyarapu Ramesh and Kumpatla Siva.

2012. Intern. J of Plant Genomics. 2012:11

18

Mardis ER. 2008. The impact of next-generation sequencing technology on

genetics. Trends in Genetics 24:133-41

McCallum CM, Comai L, Greene EA, Henikoff S. 2000. Targeting Induced

Local Lesions IN Genomes (TILLING) for Plant Functional Genomics.

Plant Physiology 123:439-42

McGlauflin MT, Smith MJ, Wang JT. 2010. High-Resolution Melting

Analysis for the Discovery of Novel Single-Nucleotide Polymorphisms in

Rainbow and Cutthroat Trout for Species Identification. Transactions of

the American Fisheries Society 139

Metzker ML. 2005. Emerging technologies in DNA sequencing. Genome Res.

15:1767-76

Morgante M, Hanafey M, Powell W. 2002. Microsatellites are preferentially

associated with nonrepetitive DNA in plant genomes. Nature Genetics 30

Mueller UG, Wolfenbarger LL. 1999. AFLP genotyping and fingerprinting.

TREE 14

Nicolai M, Pisani C, Bouchet J-P, Vuylsteke M, Palloix A. 2012. Discovery of

a large set of SNP and SSR genetic markers by high-throughput

sequencing of pepper (Capsicum annuum). Genetics and Molecular

Research 11:2295-300

Ossowski S, Schneeberger K, Clark RM. 2008. Sequencing of natural strains

of Arabidopsis thaliana with short reads Genome Research 18:2024-33

19

Paran I, Aftergoot E, Shifriss C. 1998. Variation in Capsicum annuum

revealed by RAPD and AFLP markers. Euphytica 99:167-73

Paran I, van der Voort JR, Lefebvre V, Jahn M, Landry L, et al. 2004. An

integrated genetic linkage map of pepper (Capsicum spp.). Molecular

Breeding 13:251-61

Picoult-Newberg L, Ideker TE, Pohl MG, Taylor SL. 1999. Mining SNPs

From EST Databases. Genome Research 9:167-74

Powell W, Morgante M, Andre C, Hanafey M, Vogel J. 1996. The comparison

of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm

analysis. Molecular Breeding 2:225-38

Prince JP, Pochard E, Tanksley SD. 1993. Construction of a molecular linkage

map of pepper and a comparison of synteny with tomato. Genome 36:404-

17

Richardson P. 2010. Special Issue: Next Generation DNA Sequencing. Genes

1:385-7

Rudd S. 2003. Expressed sequence tags: alternative or complement to whole

genome sequences? TRENDS in Plant Science 8:321-9

Sanger F, Nicklen S, Coulson AR. 1977. DNA sequencing with chain-

terminating inhibitors. Proc. Natl. Acad. Sci. USA 74:5463-7

20

Shendure J, Ji H. 2008. Next-generation DNA sequencing. Nature

Biotechnology 26:1135-45

Tanksley SD, Bernatzky R, Lapitan NL, Prince JP. 1988. Conservation of

gene repertoire but not gene order in pepper and tomato. Proc. Natl. Acad.

Sci. USA 85:6419-23

Thompson JF, Steinmann KE. 2011. Single Molecule Sequencing with a

HeliScope Genetic Analysis System. Curr Protoc Mol Biol.

Tingey SV, del Tufo JP. 1993. Cenetic Analysis with Random Amplified

Polymorphic DNA Markers. Plang Physiol. 101:349-52

Trick M, Meng J, Bancroft L. 2009. Single nucleotide polymorphism (SNP)

discovery in the polyploid Brassica napus using Solexa transcriptome

sequencing. Plant Biotechnology Journal 7:334-46

Vignal Alain, Milan Denis, SanCristobal Magali, Eggen Andre. 2002. A

review on SNP and other types of molecular markers and their use in

animal genetics. EDP Sciences 34:275-305

Von Bubnoff A. 2008. Next-Generation Sequencing: The Race Is On. Cell

132:721-3

Vos P, Hogers R, Bleeker M, Reijans M, Lee Tvd, et al. 1995. AFLP: a new

technique for DNA fingerprinting. Nucleic Acid Research 23

21

Winter P, Kahl G. 1993. Molecular marker technologies for plant

improvement. World Journal of Microbiology & Biotechnology 11:438-48

Wu F, Eannetta NT, Xu Y, Durrett R, Mazourek M, et al. 2009. A COSII

genetic map of the pepper genome provides a detailed picture of synteny

with tomato and new insights into recent chromosome evolution in the

genus Capsicum. Theor Appl Genet 118:1279-93

Yamamoto T, Nagasaki H, Yonemaru, Jun-ichi. 2010. Fine definition of the

pedigree haplotypes of closely related rice cultivars by means ofgenome-

wide discovery of single-nucleotide polymorphisms. BMC Genomics 11

Yi G, Lee JM, Lee S, Choi D, Kim BD. 2006. Exploitation of pepper EST–

SSRs and an SSR-based linkage map. Theor Appl Genet. 114:113-30

22

MATERIALS AND METHODS

Plant material preparation for eight accessions

Jeju (Capsicum annuum), LAM32 (C. annuum), Tean (C. annuum),

CM334 (C. annuum), SNU-001 (C. chinense), Yuwolcho (C. annuum),

PI201234 (C. annuum) and YCM334 (C. annuum) were grown in a growth

chamber with 12 h light at 25°C and 12 h dark at 18°C. Leaf tissues at the

same stage from the eight accessions were collected. Total RNA was isolated

from leaves of each accession with Trizol extraction buffer (Ambion, Carlsbad,

CA, USA) as described in the manufacturer’s protocol and used for

sequencing of transcriptomes. (Table 3)

RNA extraction for each sample

TRIzol reagent from Invitrogen was used for extracting RNA process

as follows the protocol of manufacturer’s instructions. 1 mL of TRIzol reagent

was added on each sample. After 5 minutes of phase separation at the room

temperature, chloroform of 0.2mL were added on followed by centrifuge at

12,000 x g for 15 minutes at 5 degree Celsius. The RNA was precipitated from

the aqueous phase by mixing with 0.5 ml of isopropanol followed by the

sample incubating in the room temperature for 10 minutes and centrifuged at

12,000 x g for 10 minutes at 4 Celsius. By removing the supernatant, the RNA

23

was washed with 75% ethanol. Air dried pallet is dissolved in diethyl

pyrocarbonate (DEPC) treated water.

24

Table 3. Description of Capsicum used in this study

Name Species Origin Genetic-type Sample

Jeju annuum Korea Landrace Leaf

LAM32 annuum India Landrace Leaf

Tean annuum Korea Landrace Leaf

CM334 annuum Mexico Landrace Leaf

SNU-001 chinense Venesula Landrace Leaf

Yuwolcho annuum Korea Landrace Leaf

PI201234 annuum USA Landrace Leaf

YCM334 annuum Taiwan Landrace Leaf

25

Sequencing of transcriptomes for eight accessions

Jeju, LAM32 and Tean were sequenced via GAIIx sequencing with

116-bp single-end reads at the National Instrumentation Center for

Environmental Management (NICEM). CM334 sequencing data of 101-bp

paired-end reads were provided by Dr. Choi from the Plant Genomics

Laboratory at Seoul National University. SNU-001, Yuwolcho, PI201234 and

YCM334 were sequenced with the GAIIx sequencing platform using the 90-

bp paired-end read sequencing method at Beijing Genome Institute (BGI).

(Table 4)

Quality trimming for sequences

The sequence data from each accession were trimmed to reduce the

quality deterioration in the 3’-end and 5’-end regions, which negatively affects

mapping and assembly. Sickle version 1.0 (https://github.com/najoshi/sickle)

was used for quality trimming.

26

Table 4. Sequencing features of each accession

Accessions Species length Single /paired Institute Features

Jeju C. annuum 101bp x1 Single NICEM susceptible

LAM32 C. annuum 101bp x1 Single NICEM cmr2

Tean C. annuum 101bp x1 Single NICEM susceptible

CM334 C. annuum 101bp x2 Paired NICEM Phytophthora

SNU-001 C. chinense 90bp x 2 Paired BGI Capsiate

Yuwolcho C. annuum 90bp x2 Paired BGI M0/L

PI201234 C. annuum 90bp x2 Paired BGI Phytophthora

YCM334 C. annuum 90bp x2 Paired BGI Phytophthora

Each accession is sequenced by Illumina GA IIx from different institute. Features column represents the resistance line

NICEM: National Instrumentation Center for Environmental Management, BGI: Beijing Genomics Institute

27

Reference sequence preparation

The reference sequence, assembled by commercially available CLC

Genomics Workbench software, comprised 31,196 contigs from EST

sequences that were mainly derived from Korean F1 hybrid line Bukang, for

which data are available at the Korea Research Institute of Bioscience &

Biotechnology (KRIBB) (Ashrafi et al., 2012; Kim et al., 2008).

Repeat Masking on the reference sequence

Repeat masking was performed on the reference sequence using the

727 repeat sequence library set up by the Plant Genomics Laboratory at Seoul

National University because of the presence in Capsicum of areas highly

abundant in repeat sequence (Yi et al., 2006). The data were collected by the

RMBlast program, which is mainly used in NCBI for finding matches between

two sequences and attempting to start alignments from these matched places

(Johnson et al., 2008). RepeatMasker from the Institute for Systems Biology

was used to screen DNA sequences for repeats and areas of low complexity.

Alignment to the reference sequence

Sequence alignments to the reference sequence were performed to

find SNPs (McPherson, 2009) using the Burrows-Wheeler Transform

algorithm from Burrows-Wheeler Aligner version 0.5.9rc1, which requires

28

low memory and so is suitable for reducing the analysis time (Li and Durbin,

2009). (Figure 1)

SNP calling and filtering

SNP data were collected using SAMtools software and an in-house

python script with strict criteria (Li et al. 2009). SNPs from sequencing depth

of 25x were filtered in the following order: 1) diallelic SNPs, 2) SNPs found

in more than six accessions, 3) SNPs with high PIC value, 4) SNPs for

Fluidigm probe design (at least 60 bp from any intron-exon junction or

another SNP). (Figure 2)

Linkage mapping

A genetic map was drawn by connecting candidate SNPs after the

filtering process to a hybrid of Capsicum frutescens cv. BG2814-6 x Capsicum

annuum cv. NuMexRNaky RIL population (119 RILs) built at the University

of California, Davis (https://pepchip.genomecenter.ucdavis.edu/). (Figure 3)

https://pepchip.genomecenter.ucdavis.edu/

29

Accession 1

Reference

Accession 2

SNP Figure 1. Alignment to the reference and finding SNPs.

Notes: Each accession is aligned to the reference sequence, and for those which have different single nucleotide

is the candidate for the SNPs.

30

Figure 2. SNP Selection through filtering process.

Note: Filter option 4; adjacent SNPs located within 60bp were discarded

70bp 80bp 30bp 10bp 20bp

Selected Selected Discarded Cu

rren

t p

ipel

ine

New

pip

elin

e

Selected Discarded

31

Figure 3. Overall Process for SNP discovery.

Reference Sequence

NGS on each accession

(EST, de novo assembly)

(Illumina GA IIx)

Repeat Masking

Quality Trimming

(RMBlast, RepeatMasker)

(Sickle version 1.0)

Alignments (BWA)

SNP calling (SAM tools, In-house Script)

Filtering (Customizing Option)

Connecting to the Map (Linkage map by UC Davis)

32

Polymorphism survey and genetic diversity

SNPs positioned in the linkage map were used to design locus-specific

markers for the Fluidigm® EP1TM genotyping system. To validate their

polymorphism and study the application of the SNP markers, 24 different C.

annuum accessionss (CM334, YCM334, Tean, Yuwolcho, ECW, Bukang A

line, Bukang C line, Lam32, Jeju, Dempsey, DRB, Perennial, 9093, ECW30R,

Takanotsume, 35001, 35009, RS202, RS203, RS205, VK-515R, VK515S,

LongSweet, AC2212) and three different C. chinense accessions (PI159236,

Habanero, SNU11-001) were employed. Genomic DNAs of each accessions

were extracted by the hexadecyl trimethyl ammonium bromide (CTAB)

method from young leaf tissues (Yang et al., 2012). Phylogenetic analysis was

carried out using the neighbor-joining method in Darwin5 software

(http://darwin.cirad.fr/darwin, Perrier et al., 2003). Tree construction was

based on the unweighted neighbor-joining method, and bootstraps were

determined from 1,000 replicates.

33

RESULTS

Sequencing of hot pepper accessions and quality trimming

We produced a total of 4.1-4.4 Gb with 36-38 million reads from Jeju,

LAM32 and Tean; a total of 7.1 Gb with 70 million reads from CM334; and a

total of 3.5-3.6 Gb with 39-40 million reads from SNU-001, Yuwolcho,

PI201234, and YCM334 (Table 1). After quality trimming with Sickle version

1.0, the collected data were reduced to 3.6-3.7 Gb with 35-37 million reads of

100-102 bp read length for Jeju, Tean, and LAM32; 5.3 Gb with 67 million

reads averaging 79.5 bp for CM334; and 3.4-3.5 Gb with 39-40 million reads

averaging 87-88 bp for SNU-001, Yuwolcho, PI201234, and YCM334. (Table

5)

34

Table 5. Sequencing information from eight pepper accessions

Cultivar Origin Raw reads Trimmed reads

Bases Reads Read length (bp) Bases Reads Read length (bp)

Jeju Korea 4,341,320,416 37,425,176 116 3,690,172,704 36,990,461 99.8

LAM32 India 4,120,993,728 35,525,808 116 3,596,017,756 35,239,208 102

Tean Korea 4,356,564,208 37,556,588 116 3,708,990,466 37,165,176 99.8

CM334 Mexico 7,111,852,582 70,414,382 101 5,297,351,327 66,591,676 79.5

SNU-001 Venezuela 3,575,010,600 39,722,340 90 3,440,874,878 39,338,990 87.5

Yuwolcho Korea 3,579,091,560 39,767,684 90 3,438,315,513 39,381,505 87.3

PI201234 Germplasm in

USA 3,575,048,220 39,722,758 90 3,493,467,360 39,637,637 88.1

YCM3341 Taiwan 3,525,119,100 39,167,990 90 3,444,541,024 39,081,800 88.1

1 RIL line derived from a cross between Yolo wonder and CM334 in INRA (France)

35

Alignment of each accession to the reference sequence

The total acquired reference sequence of 21,665 kb was de novo

assembled from 31,196 contigs derived from Bukang ESTs, with an average

contig length of 696 bp. There was a total of 1,071 kb of interspersed repeat

elements (5,216 elements). Unclassified repeats accounted for 626 kb of this.

Of the remaining repeat sequence, the largest portion (278 kb) was annotated

as long terminal repeats (LTR), which are composed of several hundred base

pairs. Long interspersed nuclear elements (LINEs), which encode a reverse

transcriptase (RT) and other proteins, accounted for 118 kb. In addition, there

was 49 kb of DNA transposable elements, which tend to have short inverted

repeats at each end. In addition to these interspersed repeat elements, 102 kb

and 103 kb were marked as simple repeat and low complexity regions,

respectively. Therefore, a total of 1,276 kb (5.9%) was masked as repeat

sequences.

The trimmed reads of eight accessions (Table 5) were aligned to the

reference sequence and the range of alignment ratio between each accession

and the reference was 52.6~70.5%. (Table 6)

36

Table 6. Alignment result of each accession to the reference

Trimmed reads Aligned reads Alignment ratio (%)

Jeju 36,990,461 19,465,349 52.62

LAM32 35,239,208 20,122,901 57.10

Tean 37,165,176 20,983,023 56.46

CM334 66,591,676 36,054,433 54.14

SNU-001 39,338,990 24,801,440 63.05

Yuwolcho 39,381,505 26,073,255 66.21

PI201234 39,637,637 27,929,380 70.46

YCM334 39,081,800 25,936,924 66.37

37

SNP discovering and SNP filtering

Sequences with read depth over 25x were used for SNP discovery,

and those that were obviously distinguishable and different among accessions

were defined as SNPs. Based on these criteria, a total of 58,151 SNPs were

identified. From these, SNPs with only two types of genotypes and two alleles

were filtered out. Among the remaining 57,502 SNPs, 33,315 were recognized

as distinguishable in at least six different accessions. In the next step, SNPs

that showed a uniform segregation ratio were chosen. Among the 33,315

SNPs tested, 4,508 segregated 4:4 or 3:5 in the eight accessions. Finally, from

those 4,508 SNPs, 1,910 were selected based on not having any other SNPs

within 60 bp in either direction (Table 7)

38

Table 7. SNP filtering process

Filtering Criteria No. of SNPs remaining No. of filtered SNPs Filtering percentage

(%)

Depth filtering (>25 X) 58,151

Genotype/allele 57,502 649 1.11

No. of distinguishable

accessions 33,315 24,187 42.06

Segregation ratio 4,508 28,807 86.46

Adjacent SNP 1,910 2,598 57.63

Filtering percentage = (No. of SNPs removed by filter ÷ No. of SNPs tested) x 100

39

Development and validation of SNP markers

Among 1,910 SNPs, a total of 1,282 were positioned on the hot pepper map

produced by UC Davis. From these, we further selected 412 SNPs that showed

clear and repeatable polymorphism, and were evenly distributed over a ~3 cM

interval in each chromosome. (Supplementary Table 1) The linkage map

showing the location of the 412 SNPs is presented in Figure 4 and the SNP

number per chromosome is given in Table 8. The entire length of the genetic

map was 1,460.6 cM. There was an average of 34 SNPs in each linkage group,

with the P1_Wild (177.1cM) linkage group including the most SNPs. The P3

linkage group had the density (0.40 SNP/cM). The fewest SNPs mapped to

linkage group P8_Wild. The number of SNPs per cM ranged from 0.16 to

0.40, with an average of 0.28 SNPs per cM. Accordingly, there are averages of

1 SNPs per 3.55-cM interval in the genetic map (Figure 4, Table 8).

To validate the 412 SNP markers, 24 C. annuum and 3 C. chinense

accessions (Table 9) were tested for diversity of pepper genotypes (Figure 5).

Between C. annuum accessions, the average number of SNPs was 143,

ranging from 23 (ECW vs. ECW30R) to 205 (Takanotsume vs. YCM334). By

contrast, between bell-type accessions of C. annuum (9003, Dempsey,

ECW30R, ECW), the average number of SNPs was 51, ranging from 23

(ECW vs. ECW30R) to 69 (DRB vs. ECW). C. chinense accessions showed

an average of 23 SNPs, ranging from 17 (Habanero vs. SNU11-001) to 27

(Habanero vs. PI159236). The SNP number between C. annuum and C.

chinense accessions averaged 179, ranging from 149 (VK-515S vs Habanero)

40

to 209 (Dempsey vs PI159236). Overall, the average SNP number between all

Capsicum accessions was 150, ranging from 17 (Habanero vs SNU11-001) to

209 (Dempsey vs PI159236). Based on the genetic similarity results, a cluster

dendrogram placed the 27 pepper accessions into two main clusters and

clearly differentiated each accession (Figure 5). The first main cluster (I)

comprised 15 different C. annuum accessions (9093, Dempsey, ECW30R,

ECW, DRB, YCM334, RS205, RS203, RS202, Jeju, LongSweet, 35001,

AC2212, CM334, Bukang A). The second cluster (II) consisted of 12 different

accessions including seven C. annuum accessions (35009, Yuwolcho, Tean,

Takanotsume, Bukang C, VK-515R, and VK515S), two wild species of C.

annuum accessions (Perennial and Lam 32) and three C. chinenese accessions

(PI159236, Habanero, and SNU11-001).

41

CAPS_CONTIG.57480.2CAPS_CONTIG.111260.3CAPS_CONTIG.5112.5CAPS_CONTIG.123448.0CAPS_CONTIG.1168218.7KS24033B0710.3CAPS_CONTIG.583111.5CAPS_CONTIG.915512.0CAPS_CONTIG.1251712.6CAPS_CONTIG.104314.1CAPS_CONTIG.601215.1CAPS_CONTIG.520116.6CAPS_CONTIG.454419.8KS24031E12CAPS_CONTIG.2694CAPS_CONTIG.5699

22.4

CAPS_CONTIG.123925.0CAPS_CONTIG.986727.5CAPS_CONTIG.11664CAPS_CONTIG.7601

34.9

CAPS_CONTIG.587936.0CAPS_CONTIG.1105037.6KS08005G0838.7

CAPS_CONTIG.1143247.4CAPS_CONTIG.93747.8CAPS_CONTIG.999550.1KS17031G1252.1CAPS_CONTIG.209855.9CAPS_CONTIG.1021856.5CAPS_CONTIG.254756.7CAPS_CONTIG.112559.8CAPS_CONTIG.750461.7CAPS_CONTIG.756064.5CAPS_CONTIG.976767.0CAPS_CONTIG.1092168.1CAPS_CONTIG.362869.3CAPS_CONTIG.272573.9CAPS_CONTIG.1105875.2KS23001F0676.5CAPS_CONTIG.265677.7CAPS_CONTIG.1018279.1CAPS_CONTIG.10091CAPS_CONTIG.2834

80.4

CAPS_CONTIG.436984.2

CAPS_CONTIG.885590.9CAPS_CONTIG.10653CAPS_CONTIG.1833

92.0






KS13030B11124.9

CAPS_CONTIG.11404129.5ANOK.CO908560130.6

KS24046E02137.4CAPS_CONTIG.11803137.9CAPS_CONTIG.7051139.7CAPS_CONTIG.5625140.1CAPS_CONTIG.10856142.4



CAPS_CONTIG.12116161.5CAPS_CONTIG.7077161.8CAPS_CONTIG.3070162.9

CAPS_CONTIG.4994169.2CAPS_CONTIG.6883170.8



P1_Wild

CAPS_CONTIG.4964CAPS_CONTIG.6936

3.6

CAPS_CONTIG.80704.8

CAPS_CONTIG.242710.0KS01048D1112.4CAPS_CONTIG.729213.5

ANOK.CO77639416.4CAPS_CONTIG.479317.5KS19051F0721.7CAPS_CONTIG.381522.1CAPS_CONTIG.19724.6CAPS_CONTIG.853925.2CAPS_CONTIG.357026.3CAPS_CONTIG.701330.8CAPS_CONTIG.39231.6ACRI.DV64321133.7CAPS_CONTIG.427635.2

CAPS_CONTIG.965549.6KS24056A0951.8CAPS_CONTIG.136752.3CAPS_CONTIG.983154.9CAPS_CONTIG.1067056.2CAPS_CONTIG.34458.9CAPS_CONTIG.479661.1

CAPS_CONTIG.67965.4CAPS_CONTIG.936965.7CAPS_CONTIG.272466.8CAPS_CONTIG.349968.5CAPS_CONTIG.521769.8


CAPS_CONTIG.903880.9CAPS_CONTIG.371081.7CAPS_CONTIG.556183.4CAPS_CONTIG.637284.5KS19047D0485.9



P2


1.9






CAPS_CONTIG.18031.3CAPS_CONTIG.625632.0CAPS_CONTIG.1230533.1KS15046C1135.5CAPS_CONTIG.869836.7CAPS_CONTIG.882837.4CAPS_CONTIG.140639.2CAPS_CONTIG.953742.2CAPS_CONTIG.364042.3CAPS_CONTIG.402243.1CAPS_CONTIG.1173447.3KS24036H0751.6KS10024A0952.1CAPS_CONTIG.46754.8ANOK.CO91034356.3KS11064B0759.3

CAPS_CONTIG.841669.5CAPS_CONTIG.900470.4KS23061E0272.9CAPS_CONTIG.458474.4CAPS_CONTIG.908276.2ANOK.CO90988877.0CAPS_CONTIG.12508CAPS_CONTIG.5830

77.5

KS19014A1182.6CAPS_CONTIG.285883.8CAPS_CONTIG.1154486.7

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CAPS_CONTIG.9424109.6ANOK.CO909129110.4CAPS_CONTIG.730112.8

CAPS_CONTIG.2611118.3CAPS_CONTIG.3343120.4CAPS_CONTIG.6075121.8CAPS_CONTIG.1011123.9KS17053A07125.6CAPS_CONTIG.8564128.0CAPS_CONTIG.8592130.5CAPS_CONTIG.5926131.4KS17054B11132.3CAPS_CONTIG.915133.4


P3

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CAPS_CONTIG.71896.7KS16052G017.3


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CAPS_CONTIG.1221957.2CAPS_CONTIG.695557.7CAPS_CONTIG.459859.8CAPS_CONTIG.602060.7

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77.5


KS21049G0490.4

KS23011E1198.1


KS15022D11106.4




P3

KS14027C043.5



KS21061G1543.8




CAPS_CONTIG.15967.1

CAPS_CONTIG.1008570.4KS20020C0572.5


78.1








KS09094F03115.5




P4


0.0

KS25049K033.9



CAPS_CONTIG.6615.1



KS20005B1143.5




KS12044C0282.1



P5



CAPS_CONTIG.59916.8KS21049K1816.9

KS01057F0623.5



KS17031A1252.6




KS22013D0373.9CAPS_CONTIG.19274.4

KS20039B0481.3

KS07045D1284.5


CAPS_CONTIG.495296.2KS21063P2397.3




P6


22.4


34.9



80.4



92.0






KS13030B11124.9









P1_Wild


3.6

CAPS_CONTIG.80704.8









P2


1.9








77.5


KS21049G0490.4

KS23011E1198.1


KS15022D11106.4




P3

KS14027C043.5



KS21061G1543.8




CAPS_CONTIG.15967.1

CAPS_CONTIG.1008570.4KS20020C0572.5


78.1








KS09094F03115.5




P4


0.0

KS25049K033.9



CAPS_CONTIG.6615.1



KS20005B1143.5




KS12044C0282.1



P5



CAPS_CONTIG.59916.8KS21049K1816.9

KS01057F0623.5



KS17031A1252.6




KS22013D0373.9CAPS_CONTIG.19274.4

KS20039B0481.3

KS07045D1284.5


CAPS_CONTIG.495296.2KS21063P2397.3




P6




KS26033B0338.3

KS01040H0144.5











P7

CAPS_CONTIG.8983.0


KS19059D1124.1

CAPS_CONTIG.83538.8

KS15049B0441.2



P8_Wild

ANOK.CO9118370.6


CAPS_CONTIG.13423.8


33.1


CAPS_CONTIG.1010947.2KS26024E0748.0


58.5






P9

KS10118F020.8CAPS_CONTIG.31472.1


CAPS_CONTIG.662112.2KS20034F0412.8CAPS_CONTIG.484615.8CAPS_CONTIG.445617.1KS23024A0519.5CAPS_CONTIG.53120.4

CAPS_CONTIG.84523.7




KS23026H0547.4CAPS_CONTIG.812647.8KS01034H0748.8CAPS_CONTIG.531949.6CAPS_CONTIG.444851.1CAPS_CONTIG.147353.1KS14023D0353.6CAPS_CONTIG.384754.6CAPS_CONTIG.443156.7KS11062F0259.9


CAPS_CONTIG.909784.9CAPS_CONTIG.569185.9KS24032G1086.0CAPS_CONTIG.116686.9


92.7


P10





CAPS_CONTIG.57525.7



CAPS_CONTIG.1001240.3CAPS_CONTIG.749842.0CAPS_CONTIG.460143.5CAPS_CONTIG.20444.6KS09088C0746.0CAPS_CONTIG.1150847.1CAPS_CONTIG.12022KS20046A12

49.2

ACRI.DV64311851.0CAPS_CONTIG.394854.3

KS12026E0260.0

CAPS_CONTIG.388770.8KS16023G0970.9CAPS_CONTIG.979874.0CAPS_CONTIG.244775.6

CAPS_CONTIG.221581.7KS11073H0182.8CAPS_CONTIG.837284.2CAPS_CONTIG.3318CAPS_CONTIG.7493

85.8


P11

CAPS_CONTIG.17731.2CAPS_CONTIG.74913.2CAPS_CONTIG.125184.3CAPS_CONTIG.79914.7CAPS_CONTIG.113805.6KS16010D029.7KS26064A0911.2

CAPS_CONTIG.88316.8CAPS_CONTIG.534118.9CAPS_CONTIG.862919.5KS22049B0919.7


KS14004H0753.8





CAPS_CONTIG.837484.1CAPS_CONTIG.876186.1CAPS_CONTIG.1237887.4CAPS_CONTIG.560688.1CAPS_CONTIG.631189.1CAPS_CONTIG.1058990.1CAPS_CONTIG.93391.6CAPS_CONTIG.922792.1CAPS_CONTIG.624195.0CAPS_CONTIG.903099.1KS23053A02100.0

KS12037E02106.3

P12




KS26033B0338.3

KS01040H0144.5











P7

CAPS_CONTIG.8983.0


KS19059D1124.1

CAPS_CONTIG.83538.8

KS15049B0441.2



P8_Wild

ANOK.CO9118370.6


CAPS_CONTIG.13423.8


33.1


CAPS_CONTIG.1010947.2KS26024E0748.0


58.5






P9




CAPS_CONTIG.84523.7








92.7


P10





CAPS_CONTIG.57525.7




49.2


KS12026E0260.0



85.8


P11




KS14004H0753.8






KS12037E02106.3

P12

43




KS26033B0338.3

KS01040H0144.5











P7

CAPS_CONTIG.8983.0


KS19059D1124.1

CAPS_CONTIG.83538.8

KS15049B0441.2



P8_Wild

ANOK.CO9118370.6


CAPS_CONTIG.13423.8


33.1


CAPS_CONTIG.1010947.2KS26024E0748.0


58.5






P9




CAPS_CONTIG.84523.7








92.7


P10





CAPS_CONTIG.57525.7




49.2


KS12026E0260.0



85.8


P11




KS14004H0753.8






KS12037E02106.3

P12




KS26033B0338.3

KS01040H0144.5











P7

CAPS_CONTIG.8983.0


KS19059D1124.1

CAPS_CONTIG.83538.8

KS15049B0441.2



P8_Wild

ANOK.CO9118370.6


CAPS_CONTIG.13423.8


33.1


CAPS_CONTIG.1010947.2KS26024E0748.0


58.5






P9




CAPS_CONTIG.84523.7








92.7


P10





CAPS_CONTIG.57525.7




49.2


KS12026E0260.0



85.8


P11




KS14004H0753.8






KS12037E02106.3

P12




KS26033B0338.3

KS01040H0144.5











P7

CAPS_CONTIG.8983.0


KS19059D1124.1

CAPS_CONTIG.83538.8

KS15049B0441.2



P8_Wild

ANOK.CO9118370.6


CAPS_CONTIG.13423.8


33.1


CAPS_CONTIG.1010947.2KS26024E0748.0


58.5






P9




CAPS_CONTIG.84523.7








92.7


P10





CAPS_CONTIG.57525.7




49.2


KS12026E0260.0



85.8


P11




KS14004H0753.8






KS12037E02106.3

P12




KS26033B0338.3

KS01040H0144.5











P7

CAPS_CONTIG.8983.0


KS19059D1124.1

CAPS_CONTIG.83538.8

KS15049B0441.2



P8_Wild

ANOK.CO9118370.6


CAPS_CONTIG.13423.8


33.1


CAPS_CONTIG.1010947.2KS26024E0748.0


58.5






P9




CAPS_CONTIG.84523.7








92.7


P10





CAPS_CONTIG.57525.7




49.2


KS12026E0260.0



85.8


P11




KS14004H0753.8






KS12037E02106.3

P12

Figure 4. Location of 412 SNP markers on pepper linkage map.

44

Table 8. The number of SNPs and density in each pepper linkage group

Chromosome SNPs Size (cM) SNP density (SNP/cM)

P1_Wild 69 177.1 0.39

P2 43 113.8 0.38

P3 57 141.6 0.40

P4 32 144.1 0.22

P5 25 101.6 0.25

P6 36 136.6 0.26

P7 21 104.2 0.20

P8_Wild 8 50.3 0.16

P9 22 110.2 0.20

P10 35 98.0 0.36

P11 33 90.0 0.37

P12 31 106.3 0.29

Total 412 1460.6 0.28

45

Table 9. Origins of 27 accessions used for polymorphism survey of the

SNP markers

Cultivar Origin Cultivar Origin

CM334 Mexico Takanotsume Japan

YCM3341 Taiwan 35001 Indonesia

Tean Korea 35009 Indonesia

Yuwolcho Korea RS202 Indonesia

ECW USA RS203 Indonesia

Bukang A line Korea RS205 Indonesia

Bukang C line Korea VK-515R Indonesia

Lam32 India VK-515S Indonesia

Jeju Korea LongSweet Zambia

Dempsey USA AC2212 USA

DRB USA PI159236 Peru

Perennial India Habanero Mexico

90932 USA SNU11-001 Venezuela

ECW30R USA

1 RIL line derived from a cross between Yolo wonder and CM334 in INRA

(France)

46

Figure 5. Polymorphism survey of the 412 SNP markers in cultivars

SNP numbers are indicated for the comparisons between the

Capsicum accessions indicated on the horizontal and vertical axes.

Blue: SNP number for comparison between C. annuum accessions,

red: SNP number for comparison between C. annuum and C.

chinense, green: SNP number for comparison between C. chinense

accessions.

47

DISCUSSION

Various approaches have been used to find SNPs in hot pepper, such

as targeting sequences using COSII markers (Jung et al., 2010) or PCR using

primers based on BAC sequences (Yang et al., 2009). Recently, ESTs have

been widely used to find SNPs in crop varieties including tomato and barley

because of their abundance and easy accessibility to the data (Kota et al.,

2001; Labate and Baldo, 2005). The present work demonstrates that EST-

derived SNP discovery using NGS is advantageous in hot pepper as well.

We prepared the reference sequence from Bukang ESTs using an

approach similar to that described by Nicoli et al. (2012). However, we

employed different SNP filtering methods to find valuable SNPs more

effectively. By preparing a lengthy reference sequence after de novo assembly,

we generated an alternative to WGS for reference sequence alignment to

identify SNPs. Repeat areas are distributed throughout the genome in hot

pepper. Therefore when preparing a reference sequence, repeat masking

should be performed to find more accurate SNPs. In NGS for Jeju, LAM32,

and Tean, parts of some reads contained low quality data and quality trimming

resulted in small reductions in bases but not read number. However, for

CM334, there was large amount of reduction due to low quality in both bases

and reads. The sequences of SNU-001, Yuwolcho, PI201234, and YCM334

were high quality and did not show no much difference before and after

trimming. Most accessions aligned to the reference with 50-70% of reads

48

alignment. The variations might be due to the different genetic relationships

between the accessions and the reference.

Overall, we identified may SNPs by aligning NGS sequence to the

reference. However, the SNPs were not all equally valuable. Several factors

can lead to false SNP findings, including base calling errors from NGS

(Nielsen et al., 2011), miss-calls including overlapping genotypes (Anney et

al., 2008), and false discovery of polymorphic SNPs that are actually

monomorphic (Pettersson et al., 2008). To address this, we performed quality

filtering of the SNPs. Our in-house SNP filtering process significantly

decreased the SNP numbers: starting from 58,151 SNPs, the SNPs were

filtered down to 1,910. After positioning the SNPs on the genetic linkage map,

developing and testing SNP markers using the Fluidigm® EP1TM genotyping

system, 412 SNP markers were finally selected and validated using 27

Capsicum accessions.

For MABC, background selection focuses on both reduction of donor

segments around target genes and recurrent parent genome recovery.

Successful MABC depends on genome size, population size, marker density in

the map and the use of high throughput marker systems. Recently, Herzog and

Fishch (2013) conducted computer simulations of MABC in genetic models of

sugar beet, rye, sunflower and rapeseed, using the 10% quantile (Q10) value,

the arithmetic mean and the standard deviation of the probability distribution

of the proportion of recipient genome in the entire genome of selected

individuals (as a percentage), for determining every backcross generation to

measure recurrent parent genome recovery. Based on their data, the optimum

49

designs, which minimize the required number of marker data points for target

Q10 values of 96-99% in generation BC2 or BC3 in the model plants,

employed marker densities of 2-20 cM intervals between markers and a

population size of 50-100. In this study, the entire length of the genetic map

covered by the SNP markers was 1,460.6 cM, suggesting that 73-730 markers

(for 2-20 cM intervals) are needed for MABC in pepper. Our marker set

produced an average of 150 SNPs between 27 accessions (corresponding to ~

10 cM intervals), implying that our newly developed SNP markers should be

useful for MABC between 27 accessions. SNP numbers between C. annuum

and C. chinense were much higher than those between accessions from the

same species such as bell types of C. annuum and C. chinense. This result

implies that MABC could be more difficult in closely-related accessions than

in distant accessionss. Despite this, our new SNP markers clearly

distinguished 27 Capsicum accessions.

Among the accessions tested, AC2212 was positioned in the C.

annuum cluster, rather than in the C. chinense cluster. AC2212 was originally

classified as C. chinense based on agronomic information from the Centre for

Genetic Resources, the Netherlands (http://applicaties.wageningenur.nl/

applications/cgngenis/; Wahyuni et al., 2011). However, Wahyuni et al (2013)

reported out that AC2212 likely belongs to C. annuum instead of C. chinense,

based on AFLP marker analysis. This result thus indicates that our newly

developed SNP markers are accurate and can be used for the identification of

diverse Capsicum accessions.

In conclusion, our SNP markers derived from transcriptome sequences

50

will be valuable tools for MABC. In addition, the markers can be used for

genetic mapping, comparative mapping and genetic diversity analyses in

pepper and related species.

51

REFERENCES

Anney, R.J., E. Kenny, C.T. O'Dushlaine, and J. Lasky-Su. 2008. Non-

random error in genotype calling procedures: implications for family-

based and case-control genome-wide association studies. Am. J. Med.

Genet. B. 147B:1379-1386.

The Arabidopsis Genome Initiative. 2000. Analysis of the genome sequence

of the flowering plant Arabidopsis thaliana. Nature 408:796-815.

Ashrafi, H., T. Hill, K. Stoffel, A. Kozik, J. Yao, S.R. Chin-Wo, and A. Van

Deynze. 2012. De novo assembly of the pepper transcriptome (Capsicum

annuum): a benchmark for in silico discovery of SNPs, SSRs and

candidate genes. BMC Genomics 13:571.

Blum, E., K. Liu, M. Mazourek, E.Y. Yoo, M. Jahn, and I. Paran. 2002.

Molecular mapping of the C locus for presence of pungency in Capsicum.

Genome 45:702-705.

Flicek, P. and E. Birney. 2009. Sense from sequence reads: methods for

alignment and assembly. Nat. Methods 6:S6-S12.

Goff, S.A., et al. 2002. A draft sequence of the rice genome (Oryza sativa L.

ssp. japonica). Science 296:92-100.

Herzog, E. and M. Frisch. 2013. Efficient marker-assisted backcross

conversion of seed- parent lines to cytoplasmic male sterility. Plant Breed.

132:33-41.

52

Imelfort, M., C. Duran, J. Batley, and D. Edwards. 2009. Discovering genetic

polymorphisms in next-generation sequencing data. Plant Biotechnol. J.

7:312-317.

Johnson, M., I. Zaretskaya, Y. Raytselis, Y. Merezhuk, S. McGinnis, and T.L.

Madden. 2008. NCBIBLAST: a better web interface. Nucleic Acid Res.

36:W5-W9.

Jones, E., et al. 2009. Development of single nucleotide polymorphism (SNP)

markers for use in commercial maize (Zea mays L.) germplasm. Mol.

Breed. 24:165-176.

Jung, J.K., S.W. Park, W.Y. Liu, and B.C. Kang. 2010. Discovery of single

nucleotide polymorphism in Capsicum and SNP markers for cultivar

identification. Euphytica. 175:91-107.

Kang, B.C., S.H. Nahm, J.H. Huh, H.S. Yoo, J.W. Yu, M.H. Lee, and B.D.

Kim. 2001. An interspecific (Capsicum annuum x C. chinese) F2 linkage

map in pepper using RFLP and AFLP markers. Theor. Appl. Genet.

102:531-539.

Kim, H.J., K.H. Baek, S.W. Lee, J. Kim, B.W. Lee, H.S. Cho, W.T. Kim, D.

Choi, and C.G. Hur. 2008. Pepper EST database: comprehensive in silico

tool for analyzing the chili pepper (Capsicum annuum) transcriptome.

BMC Plant Biology 8:101.

Kota, R., R.K. Varshney, T. Thiel, K.J. Dehmer, and A. Graner. 2001.

Generation and comparison of EST-derived SSRs and SNPs in barley

(Hordeurn vulgare L.). Hereditas 135:145-151.

53

Labate, J.A. and A.M. Baldo. 2005. Tomato SNP discovery by EST mining

and resequencing. Mol. Breed. 16:343-349.

Lee, M.J., B.M. Popkin and S. Kim. 2002. The unique aspects of the nutrition

transition in South Korea: the retention of healthful elements in their

traditional diet. Public Health Nutr. 5:197-203.

Li, H. and R. Durbin. 2009. Fast and accurate short read alignment with

Burrows–Wheeler transform. Bioinformatics 25:1754-1760.

Li, H., et al. 2009. The sequence alignment/map format and SAMtools.

Bioinformatics 25:2078-2079.

McPherson, J.D. 2009. Next-generation gap. Nat. Methods 6:S2-S5.

Metzker, M.L. 2005. Emerging technologies in DNA sequencing. Genome

Res. 15:1767-1776.

Metzker, M.L. 2010. Sequencing technologies - the next generation. Genetics

11:31-46.

Nicolai, M., C. Pisani, J.P. Bouchet, M. Vuylsteke, and A. Palloix. 2012.

Discovery of a large set of SNP and SSR genetic markers by high-

throughput sequencing of pepper (Capsicum annuum). Genet. Mol. Res.

11:2295-2300.

Nielsen, R., J.S. Paul, A. Albrechtsen, and Y.S. Song. 2011. Genotype and

SNP calling from next-generation sequencing data. Nat. Rev. Genet.

12:443-451.

Paran, I., et al. 2004. An integrated genetic linkage map of pepper (Capsicum

spp.). Mol. Breed. 13:251-261.

54

Perrier, X., A. Flori, and F. Bonnot. 2003. Data analysis methods. In: Hamon,

P., M. Seguin, X. Perrier and J.C. Glaszmann. Genetic diversity of

cultivated tropical plants. Gifield Science Publishers. Montpellier, pp. 43-

46.

Pettersson, F., A.P. Morris, M.R. Barnes, and L.R. Cardon. 2008. Goldsurfer2

(Gs2): a comprehensive tool for the analysis and visualization of genome

wide association studies. BMC Bioinformatics 9:138.

Pompanon, F., A. Bonin, E. Bellemain, and P. Taberlet. 2005. Genotyping

errors: causes. Consequences and solutions. Nat. Rev. Genet. 6:847-859.

Rudd, S. 2003. Expressed sequence tags: alternative or complement to whole

genome sequences? Trends Plant Sci. 8:321-329.

Shao, G.C., Z.Y. Zhang, N. Liu, S.E. Yu, and W.G. Xing. 2008. Comparative

effects of deficit irrigation (DI) and partial rootzone drying (PRD) on soil

water distribution, water use, growth and yield in greenhouse grown hot

pepper. Sci. Hortic. 119:11-16.

Shendure, J. and H.L. Ji. 2008. Next-generation DNA sequencing. Nat.

Biotechnol. 26:1135-1145.

Teo, Y.Y., A.E. Fry, T.G. Clark, E.S. Tai, and M. Seielstad. 2007. Data sheet:

Sentrix HumanHap550 genotyping BeadChip. Ann. Hum. Genet. 71:701-

703.

Varshney, R.K., S.N. Nayak, G.D. May, and S.A. Jackson. 2009. Next-

generation sequencing technologies and their implications for crop

genetics and breeding. Trends Biotechnol. 27:522-530.

55

Vignal, A., D. Milan, M. SanCristobal, and A. Eggen. 2002. A review on SNP

and other types of molecular markers and their use in animal genetics.

Genet. Sel. Evol. 34:275-305.

Wahyuni, Y., A.R. Ballester, E. Sudarmonowati, R.J. Bino, and A.G. Bovy.

2011. Metabolite biodiversity in pepper (Capsicum) fruits of thirty-two

diverse cultivars: variation in health-related compounds and implications

for breeding. Phytochemistry 72:1358-1370.

Wahyuni, Y., A.R. Ballester, Y. Tikunov, R.C.H. de Vos, K.T.B. Pelgrom, A.

Maharijaya, E. Sudarmonowati, R.J. Bino, and A.G. Bovy. 2013.

Metabolomics and molecular marker analysis to explore pepper (Capsicum

sp.) biodiversity. Metabolomics 9:130-144.

Weiss, E.A. 2002. World production and trade. CAB International.

Wittenberger, T., H.C. Schaller, and S. Hellebrand. 2001. An expressed

sequence tag (EST) data mining strategy succeeding in the discovery of

new G-protein coupled receptors. J. Mol. Biol. 307:799-813.

Yang, H.B., W.Y. Liu, W.H. Kang, M. Jahn, and B.C. Kang. 2009.

Development of SNP markers linked to the L locus in Capsicum spp. by a

comparative genetic analysis. Mol. Breed. 24:433-446.

Yang, H.B., W.Y. Liu, W.H. Kang, J.H. Kim, H.J. Cho, J.H. Yoo, and B.C.

Kang. 2012. Development and validation of L allele-specific markers in

Capsicum. Mol. Breed. 30:819-829.

Yi, G.B., J.M. Lee, S. Lee, D. Choi, and B.D. Kim. 2006. Exploitation of

pepper EST-SSRs and an SSR-based linkage map. Theor. Appl. Genet.

114:113-130.

56

Yoo, E.Y., S. Kim, Y.H. Kim, C.J. Lee, and B.D. Kim. 2003. Construction of

a deep coverage BAC library from Capsicum annuum, 'CM334'. Theor.

Appl. Genet. 107:540-543.

57

초록

여교배 육종법은 새로운 형질을 Elite 계통에 도입하는데

유용하게 사용되었다. 전통 육종법으로는 반복친의 유전적 배경에

가깝게 만드는데 적어도 4-5 년정도의 시간이 걸린다. 하지만, 마커를

이용한 여교배법은 시간과 비용을 확연하게 줄일 수 있는 방법으로

대두되었다. 마커를 이용한 여교배를 성공적으로 하기위해서는 높은

염기다형성을 보이는 마커의 위치를 각각의 chromosome 내에서 확인할

수 있는 것이 중요하다. 단일염기다형성(Single Nucleotide Polymorphism;

SNP) 마커는 다른 기존의 마커에 비해 대량화, 자동화등의 여러가지

장점을 가진다. 실제 마커를 이용한 여교배육종을 고추에 적용하기

위하여, EST (expressed sequence tags)를 이용하여 SNP marker 를

개발하였다. SNP marker 개발에 이용될 reference를 만들기 위해, 부강 F1

EST 를 assembly 하여 만들고, 90-100bp 의 크기로 sequence 된

염기서열들을 reference와 비교하여 총 58,151 개의 SNP 가 발견되었다.

이러한 SNP 들은 분리비, exon/intron 의 끝부분에서 일정부분이상

떨어진것등의 조건을 가지고 필터링하여, 총 1,910 개의 SNP 가 linkage

mapping 되었다. 그리고 chromosome 내에서 균일하게 분포가되어있는

총 412 개의 SNP 들을 선택하여 primers 를 디자인하여 총 27 개의

고추(Capsicum) 종에 그 genetic diversity를 테스트하였다. 이렇게 개발된

SNP 마커는 확연하게 각각의 종들을 구분하였음을 증명하였다. 따라서

58

최종적으로 본 연구에서 개발된 마커가 실제 MABC 에 유용하게 이용될

수 있음을 제안한다.

주요단어: 고추 (Capsicum), 발현 유전자 단편 (expressed

sequence tag; EST), 연쇄군 지도(linkage map), marker-

assisted breeding (MAB), 단일염기다형성(single

nucleotide polymorphism; SNP), 차세대염기서열분석

(next generation sequence; NGS),

학번: 2009-23245

59

Supplementary Table 1. Detailed information for 412 SNP probes.

Probe name Chromosome Position (cM) Allele Sequence

CAPS_CONTIG.5748 P01 0.184 GA AATCTGAACCAGCCGGTGAATGCGGGTGCCACTGCCAATGAGGAGGTATACAAGATCCTC[G/A]TTTACGATCGCTTTTGTCAAGACATT

TTATCCCCTTTGATCCACGTCAAGGACCTTCGCA

CAPS_CONTIG.11126 P01 0.311 GA TGCGAATGATGCTCAAAATGATAAGGACCGTGGTCAGATCATGGTGGAATTAACCTACAA[G/A]CCATTTAAGGAGGACGAGTTGCCGA

AAGATATTGAAGATAATGATGCAGCACATAAGGTT

CAPS_CONTIG.511 P01 2.504 GT AGAGATTGAGAAAGCGATGAGCGGAATAACATCGGCATCGTTCTTAGCTCGACGTGCGGC[G/T]CAGAGGGAGAGGGTTCGGATCCTCT

ACAGGCGCGCTCTCCGAGACACTCTTAATTGGGCC

CAPS_CONTIG.12344 P01 7.96 AT TCATCCAAAATGTACTTCCTTGCCTTTGTGTTATTGAATAGAGATGGAAAATCTCCGGTT[A/T]CTTGATTACTCAAGGCCCAGTCTTCAA

GTGCCTTTCTTTCTGGAACTGCCACGGCCACTA

CAPS_CONTIG.116821 P01 8.685 GT AGTGTTTGGCCTCATGGCTTAATTTTCAGATGTATCCTAATATTTATTTGCTAGTAATTC[G/T]CCCACGCCCCAGAAGGAAAATTATGTGC

CATAGATAAAAGTTGAACAGGGGAGTGGATGT

KS24033B07 P01 10.251 AT CCTTTAATCCAGGATTTGAAGATTCTAACATCAAATAACAACGTATACACGCATTTTCCG[A/T]GAAAGACTTGCATCAGGATCAGAGTG

CTTTCTTGACTTCCAAAAAGTTGGAACGCTCCTT

CAPS_CONTIG.5831 P01 11.494 CT GCAACTTATCAAACACCATCTCCGTATCCTGCATACCCGCCTCATTCAGCAGCATATCCA[C/T]CCACATCTTATCCTCCTCCTCAACCAAC

TGCTTACCCTCCAGCTTATCCACCACCTTCCG

CAPS_CONTIG.9155 P01 11.998 CA GCTTGTGATAAAACTTTCAACTCCTGTCAATTGCCTATGCTTTTTGGGGCATCTATAAAA[C/A]AAGGCGGAATTGTTTGCCACCAGTTAA

AGACTCCTCTCGCAGTGCAAGATGCAAAGAAGA

CAPS_CONTIG.12517 P01 12.639 CT CCTCCGTTAAGTTTCCGTCTCCGTTTGCTGTTCAGCATGCTAACGTGCGCACTGTGCGGA[C/T]TGTCACTTTGGCGACGGCTTCTAAGC

CGGTGGCTGCTGAGCCGAAGAAGCGTGAACCTAG

CAPS_CONTIG.1043 P01 14.118 AT TGCTGTGCCTCTTGATGCACCATCAGAAAGAACTGCGAGGAAGCCATCTGAGAACGTGAC[A/T]GTTAAAGATGATGGGATCAAAGAG

TCAGCTGATGCCAATGAAGGATCTCACCATCGATCA

CAPS_CONTIG.6012 P01 15.121 CT TCAAGAAAAGCCAGTTAACAATTTCCATTTTCCTCAAACCCTAACTGCAATATCCACTTG[C/T]AGTATCGGGTATGGCAGCCTTGTTGTA

CTACCTAGACGAATGGCCTTCTCATTTAGTACA

CAPS_CONTIG.5201 P01 16.584 GA AACATCTTCCCCTTCTGCAAACAGACTTAAGCTTAAACGCCTTGCACCTGGTCTTGTTGA[G/A]TTATCATCAGTGTCAAAATTGAAAGC

CATGAACGCACGAGGCCACCATTGATCTCCAGGG

60

CAPS_CONTIG.4544 P01 19.83 CT CCTCCCAAGTTTTCCATTCCCTGCTCCATCTGATCCCAATGTTCCTGCAAAAACCACTAC[C/T]CCTTGAAATGCTACAGGGGACTCTGTA

CTATCGACCTCTTACTATGCAATAGTGTTACAA

KS24031E12 P01 22.362 GT TTTCTTCCTTCGCAAAGCCTCTTCTTTCTGTCTTTGGAGCTCTTCCAGTTCTCTATAACG[G/T]TGTTCTTCCTTCATTTGCTGCTCCAAAG

CTTCTCTTCTCTGAGCTTCTTCCACCTTTCGC

CAPS_CONTIG.2694 P01 22.445 AG GAAAACATTACACATGGTCAGTTTGCCTTCACAACAACTGAGGCAGGCAACTACCTAGCATGTTTTTGGGTTGAAGATGGTCATAATGC

AGGA[A/G]GTGGGAGCATAAGTGTTGGCCTTGACTGGAAAACAGGAATTGCTGCCAAGGATTGGGAAACGGTTGCCAGAAAGGAGAA

GATAGAGG

CAPS_CONTIG.5699 P01 22.445 GA TGGCATGCTTGAGAGTTTGTCAAACCCTGCTCAGAAGGAGCAACTTGAAGAACGGATGGC[G/A]CGTATTAAAGAAGACCCATCACTG

AAACCAATCTTGGAAGAGATAGAGAGCGGAGGACCA

CAPS_CONTIG.1239 P01 24.98 CT CAGATCCCTCATCAGCATTGATGACGAAAACAAAGTGATGATGCCTCCACTTATTCAGGA[C/T]ATGGGGAAAGAAATTATTCGTCGAGA

ATCACCAGATGATCCCGAGAGATTGTGTAACTTG

CAPS_CONTIG.9867 P01 27.477 CT ATTACTTTCCACAATTAATGGAGATGGCAGAGAAATTGATTCGTGAGGGTAAAGCCTATG[C/T]GGATGATACACCAAGGGAGCAAATGC

AAAAAGAAAGAAAGGAAGGAATAGAATCAAGGTG

CAPS_CONTIG.11664 P01 34.86 AC CGATATTGCTCCTTCTCTTGTACCCTTTTCGAACCCCATATCTCACCGTTCTCTCATCGG[A/C]GGTAATCATACCTCTGCTCGTTTCTGTTC

TCGGTAACCCCACTTTTCTCCTTTCGAATCC

CAPS_CONTIG.7601 P01 34.86 CT CTTGACATTTGCTTTGAAATCCATCGTTCAGTTGCTCCTCCCCGAGTTTAAGGCTTTATT[C/T]GATAGCACACCTAATGAATTTGATAGCT

TCGCGGATGTACTCAAACTCTATGAAGGAGGA

CAPS_CONTIG.5879 P01 36.013 GT GTAGCTGGCGTCTCTGAAAGGACTATGAGGCATCCGACTGCAATGGCTTCTGTGTTTACT[G/T]CAGTGGATTCTATCAGTAATGAAGTG

GCTGCAATTATTCAATCGCCTGTCTCAGATGATC

CAPS_CONTIG.11050 P01 37.643 AC ATGATCAGCTCTATAACATTAGCAAGGCACCGGTCCCCTGATGGATCAGCACCAGACTTA[A/C]CCCCTCTACTACGGAGGTTAACGTGG

GAAAAGTTAGCTGTAAATCAGCATATCTGCTAGC

KS08005G08 P01 38.663 GT CATGTTCATCTAAGGGTAAACTATGAGGTAGATGTAAGGTAGTTGAAGCAGCTCCAAATT[G/T]TATGGTCTCTATTACTGTGTCAGTCCT

CGTCCTCTTCTTCAGATGCTTCTTTGAGCCACT

CAPS_CONTIG.11432 P01 47.405 GA GCCCTTTGATGCCCCGCTCACTGGAAACTTGAACGATATTACTGATTTCAGATTTGGTTC[G/A]CCTTTCAACTTGGGAGGAAACGATTAT

TCCATGGATGAGCTGACAAAGCAAGATATATCC

CAPS_CONTIG.937 P01 47.789 CT AAGCTAGACTTTGATAAAAGTCAAGTTGTTTACTCAAGTTACTTGCAACTTTCATGGATT[C/T]CTACATTAGATTACTTCAAAAGTGCCA

ACTCTGGGGCAGTATTTGTTTACTTATTTCATA

61

CAPS_CONTIG.9995 P01 50.064 CG TACAGGATGCCTGCATAGCTTTTGCATTCCTTTCCTTAAACTAAGCCTAACCACTGTATT[C/G]TCAACCTCCTCCGTGTCGAATCCCTCTT

TAAACCTACTCTCTAGTGTTTGTCTTTTGTGA

KS17031G12 P01 52.135 GT TTTTCGCTTCTTGTTCCACTTTTCAAGAAAGTCAGAGACTTTGCAGCAAAGAGCAAATGG[G/T]GTTCTGTTTTTAAAGGCTGTAGTGGC

ACTGAGGAGGAGCTAAGTGGAGATTTGTTGCAAA

CAPS_CONTIG.2098 P01 55.851 AT AGGTCCAAATATGAATCAACTGCCCGGAGTTGGACCCAGAAGTATGCCATGGGTTAAGAT[A/T]TTACCTATGAGGGTCTGAATCCTTGT

AAAAATAATTCATGTGTTTGTTCTCTCTACTCTC

CAPS_CONTIG.10218 P01 56.481 AC ATTCATTCATCGTTTTCAAATTAGCAAAGCCTAAGAAGCAATCATGCCGAAGAATAAGGG[A/C]AAGGGAGGAAAGAACAGGAAGAGA

GGAAAGAACGAAGCAGATGATGAGAAGAGAGAGCTA

CAPS_CONTIG.2547 P01 56.72 AG GAAGTCCACCTTCCAGAGGGTCCCATTCTTGAGGTGGCTTCTGCCTTGAGGATTGAAATT[A/G]ATCGTGCTCTTGCTCTACTGCGAGAA

ATTGCGTCAGGGAGAGAACTGAAGAAATTTCTTG

CAPS_CONTIG.1125 P01 59.761 AG TCAACGCGTTAATCACCTACATTTGGCTGCCATTTGGATTTGCTCTTGGAGTTTTTCGCGTATACTTCAATCTCCCTCTTCCAGAGCGCAT

TGTTCGTTATAC[A/G]TATGGGATGGTTGGGATCAACCTTGTTATCAAAGGCCCTCGACCACCTGCACCATCACCAGGAACCCCAGGGAA

CCTCTACGCGTGTAATCATCGTTCAGCCCTCGATCCAATTATCATTGCTATTGCACT

CAPS_CONTIG.7504 P01 61.739 GA AGTTTCATTATTACGAACTGCCACAAGTGTGGCTGGGAAGGCCAAGCAGGTATCATCACA[G/A]CAAGAGAATGATCTTGAGGTGGATC

CATGGATTCTTTTAGAGGACGGGGCAGGGTCAAGC

CAPS_CONTIG.7560 P01 64.508 CT GATGACTGGTGAAGTCGCAAATGAAGGTGAGAAAAATCTGAATGTGGAGAAACCCTCCAC[C/T]GAGGAAGAAGCAGGAGATGACAA

GAAGGAAAATCTAGTTGCTGAAGCTGAGGACAAGGAG

CAPS_CONTIG.9767 P01 67.017 CT AGCAAGAGGTGATTGAAACTAGCAAACCCATAGACAACAAATGTAGTAGCAACCAGCAAG[C/T]TTGTGCAGAAGATCAAGAAAAGTT

AGAGAATTGCATGTCCAACACACCCTCCATTGACCA

CAPS_CONTIG.10921 P01 68.138 CT ATGACAAAGGTTCATTCCTGGGCAAACAGAACACAAACAACATGATACAAAACCCATTCG[C/T]GTCTACAGTGTGTTCTTCCCATGTCA

TGAGAAGAGGATACCATGAATAGTTAACACTTGG

CAPS_CONTIG.3628 P01 69.262 CT TAAAATTATTGCATTTGCTTGGGAGCCCAGGGGTCACAGATTCGCTGTCATCCATGGTGA[C/T]AACCCCAGGCCAGATGTCAGTTCCTA

CTCCGTGCGGTCTGGCCCTAACACAGGCCGTGTT

CAPS_CONTIG.2725 P01 73.873 AG CTAAATATGATCATATGATATGTAATCTTTTCGATGAGTTTGAATGACATGTAAGATTTT[A/G]CCTATCTAATACAGTTATGGGGAAATAAG

GGTATAAGCATCTACGATCATTATATCATAT

CAPS_CONTIG.11058 P01 75.211 AG ACTTATCCTATACCTGCTAATGACTCCGTGCAATTTGTGTATTTGTTTTGTAATTTGATT[A/G]CGAAGACTTTCCTTTACGAGCAGAGAAG

GTTGAATGCTGCCTCGGGTGCTTCTGCGGTTG

62

KS23001F06 P01 76.463 GA ACCGAACCCTTTTACGCAATTCCTCTAACTCCCTCTCCATTACATACATTTTCTCCTTCA[G/A]CTCCATGTTTTCCTCCTCCAATCTCTCTA

TATGTTCCTCCACATCATCAACTCTGTAACC

CAPS_CONTIG.2656 P01 77.702 CG GACCAAACAAGGGAACCATCTATTGTAATTGGAGGACATCAATTGGAAGAGAACCTCTTG[C/G]TATTTGACCTTCCAAGAAAGAAAAT

AGGTTTCAGCTCCTCACTCAAGCTTCAACAAACAT

CAPS_CONTIG.10182 P01 79.107 GA GCCTCACCGTTTCCGACCAGGAACTGTGGCTCTAAGAGAAATTAGGAAGTATCAGAAGTC[G/A]ACTGAGTTGTTGATCAGGAAGTTGC

CCTTTCAGAGGCTGGTGAGGGAGATCGCTCAGGAT

CAPS_CONTIG.10091 P01 80.379 CA TCCTATCTGTGAAGGCATAAGCTGTGTTGACATGGAAGTAGCTGTCATTCCAACTTTACC[C/A]ACCCTCGTTTTACACATTGGTAAAGGA

TCTTTACCAGCCAATTTTATATGCAGATTGATT

CAPS_CONTIG.2834 P01 80.379 CT GAAATATGGAATAGTCCATATTCAAATGATAGCTTCCCAATTTATGCTGAAGACATTGATGCTGGT[C/T]CTGATGCATCTCCGTCCACTGC

CATGCTCTCTGAAGTAGCTCAACTTCTGAAGATTACAATAGTGGGAGGATCTATACCTGAACGCAGTGGGGACAAGTTGTATAACACTT

GCTGCGTTTTTGATGCTGATGGAAAGTTGAAAGCTAAGCACAGAAAG

CAPS_CONTIG.4369 P01 84.243 AG TATATACACATGAGTTTCACTTAATCACCACAACAACACAAGTACACAACAATGGCTTCC[A/G]CAACTACACCTTCTACACTAACTCTAT

CTTCCCTTTTCTCACAAGAACTCAACCCCAATT

CAPS_CONTIG.8855 P01 90.878 GA GGGGGAAGAGAGTAAAATTACTTTCATTCTACCCTAATATGCTGGAAATATGGTTTACTT[G/A]TTTCATTAGCAATAAGGCAAGTGTAGT

TTTCAATTGTATTATTGAGTTTGAGTAGACCTA

CAPS_CONTIG.10653 P01 91.976 GA AGCTTATCGTACTGCTGCTGATGCCGCTGCGCGTATACAGGCTGCATTCAGAGAACATTC[G/A]TTCAAAGTACAGACCAAAGCTGTCGA

ATCTTCAAATCCAGAAATAGAAGCACGTAATATA

CAPS_CONTIG.1833 P01 91.976 AG GATGATACAACTTGACTACAATCAAGTATTACTTATAGAGGAAGCATCAAAATACTGTTC[A/G]TCTTTGGGTGCCGAGGTGTTATCGTTT

AATCATCTATGCTTCAGTTCTAAATTATAAAGT

CAPS_CONTIG.10393 P01 96.567 CT TCCACCAGATTATACCCCTGCAAAAACTGAAATAGAGCCTCTGAAGAAAAAGTCTTTGCG[C/T]GTTCCCATGGCCAGACGTGGCACTG

GAAACAAGGGACAAAAGATTCAGATCCTTACTAAT

CAPS_CONTIG.11112 P01 100.366 AT GATGTAGTTCCAAGTTCTCTATGTTAGCAAAACTAGTCACTTTTGTTGGTTCTCTTATGT[A/T]CTCGTTTCACTTTCGTGGTGGTGGTTAT

CGGTTGTGACATAGTCTAAGGGTTTTAGGGGA

CAPS_CONTIG.9297 P01 105.047 CT GTTACGTACTAAGCACAACGTCAGATCCATGCCGGTGAGGAAAGACGACGAAGTTCAGGT[C/T]GTTCGTGGGACCTACAAAGGACGT

GAGGGTAAAGTTGTCCAAGTTTACCGTAAGAAGTGG

CAPS_CONTIG.4534 P01 118.083 CG GATGTTGGATCTGAAAGAGGGTTCAGGAACAGAGGATAACGACACCGAATTACTTGAGAAAGC[C/G]TTGACCGCCGAAACCTCAGAA

GATTGCAGAGAG

63

CAPS_CONTIG.11020 P01 120.758 AT CCAAGGATTCATGACTCACATTTCAGGTGGAAAGGGGACTCCAATGAGACCTGGCCCTAT[A/T]GATGCTTACCTGTTCAGTCTGATTGA

TGAGGACGCGAAAAGTATTCAGCCCGGTAACTTT

KS13030B11 P01 124.856 AG ATGCGGAGGAGGATATCCTCCTCAAGGGTGCTATACATATCCTCCTCAAGGGTACCCTCC[A/G]CAGCATCAGGGGCATACATATCCTCCT

CAAGGGTATCCTCCTGCTGGATATGCTACACAA

CAPS_CONTIG.11404 P01 129.46 AG GTAGAGAATAGAAAGTAGGAAGGGACTCCAAATGCTCTCTTTTGATGGTTTGATATTTTA[A/G]TTTCGTTTTTTTTTGTTGGCTGAAAAT

AATGTTATGACTTATGGTGTATGGGAACAGGGA

ANOK.CO908560 P01 130.572 CT CAATCTAAGGAAGCTTTGGACTTTCATCCCAGAGACAAGTCAGTCAGAGGTGGTACAGTT[C/T]CTGTCTCCATTAAGTTGAAGAAAGG

GGATGCTAACGAACAAGCATTGAACAAGCAAGATG

KS24046E02 P01 137.366 GA AGAGACCTTGCCGGAAGTGTTATCGGCAAACACAGGAGCTGGAACTCACAAGTTCTCACA[G/A]GGTTTGGCAAATGCCTTTGCTTCTC

ATGTGGAGAAACTTGCTGCTCCTTTCAAACAGAGT

CAPS_CONTIG.11803 P01 137.898 GA GGGAGCTGGATGATCTCCAGTTACTTGAGGAGCCGTGGTGGTAACCTCCCAGATCCACCC[G/A]GATGGGCGTTCTGAGGATCATTTGA

AGTCAACATAAGCACAGTTGTCTGCTTATCCTCTT

CAPS_CONTIG.7051 P01 139.713 CT TTACTGATTCAAATTCAAACTAAGTAGATTGGAAGGCAGACTCCCCAAGCTTAGGTACCTAAGTCTATAACAGCAGTGGCATTGCTGAA

TTATTGACAAACACATCCATAGT[C/T]GTCTACATGCTAGTGAGTATTAATTACATGTCAGGAAGAGCTGGAAGGCTTATGTTGATTTTTG

CCAGAATACCTGTACAGGACGATAGTGCTAGCAGCTTCCATGCGCGGCTGTTTTAATAACCGTCACCCTCCGACTAATTCCATGCCATGT

AATATTCTCTCCTGAAGAATAAAGAGTTATCTTCTCATGCACGGCACACAACCTCAAGCAGATAACACCTGTTATTTCACCTTTCTCAGC

ACTGGATGTGCTGCCCGGGCTTTTCTTTACCAGAGAGTCTTCCTCCACTCCATCCCTCAGAATCAAAATCATTCAGAATCATCA

CAPS_CONTIG.5625 P01 140.127 GA TCCATGTCAAAAAATTCCGAAGGTCTCAGAAGTTTGTCCGGGTAATAAAGTGCAACACTG[G/A]AGAAGAAACTGAGGTGCCTCAAGC

TGTAAGGATTTGTTCGGTTGTGCGTAAGATGTGGAA

CAPS_CONTIG.10856 P01 142.4 CA AAGTGCAGAAAACCACTGTCTCGTCCTTCACATTTTAAATAGTTTCTGAATCCAACAGCA[C/A]AATGAAAAACTAAAAAAGAAATCAA

CAAAATACCTAACCTAATCAGAAACATTTCTAACC

CAPS_CONTIG.12740 P01 152.185 GA CACGTTCGTCACGCCCAAAACTCCACTTCTTCCAAGCTGTGCAGGCAAGCTCAAGAACAC[G/A]TCGCCGCCATCAATGCCATAGAACC

CCTTAGCAAGAACCGAAACAGGATGAATCCTTCGT

CAPS_CONTIG.11531 P01 155.039 GA GTATACATTAGGATTCCATCATATTCCATGCCAAGAGGATTTCCCAATAATGCCAACAGT[G/A]TCATCAAGCTTTGAGATAAAGCCAGTT

AATTTCTTTGAGAGCAATCCAATTCTTAATATT

64

CAPS_CONTIG.12116 P01 161.471 GT TTATTGAAAAATACACGACCTGCATTTTCTTTGTTTGCTGTAGTCATGGCTACTGCTGGAGTACTGAGAGTCATCAGTAGATCTGAACAG

AAAGCACCTAATGGCGCTAAAGATTTCTGCAGAGGGACGAATTGAGATTATTGCGCGCGGTTTAGTTTCGAGTGTTGGAGATGCTGATT

ATGCTACCATGAAGCCAAGAAACTCCTTTCTGTTACAGTGTATATCGTTAGCTTTATCTAAAACTGG[G/T]CCATTTTCTTACCAACCTCAT

GTGTTTCTATGCCTCACTACAGCTTTGTTGACTGAAATCTTCCCCTTGCCACACATTTATATCGGAATCCAGGAATCACCTTCTGGCAACT

TGGTGGGATTAGTTCTCAATGAGGTCCAGCAGCATCTAGACAGCATTATTTTTAAGGAAGCAGGGACCATAACTGGTGTCTTTTGCAATC

AATATGTCATGGCTGATGAAGAAAACCGAAGTGCAGTAGAGGATATC

CAPS_CONTIG.7077 P01 161.793 CT CATGCTTAATGAGTCTGTAGTTCCTGACATGGAATCATGTATTTCTTTTGCTGCCCCTTT[C/T]GGTGTTTTCTTGCTAGTATTTTGATAACT

AAGATAAGACAGAGACTGCAACCACGAAACC

CAPS_CONTIG.3070 P01 162.882 CT CTCTTTCTTCAATTTCCTCTGCTTCATCTTCTTCAGAACATTCATCGAAAAATCTAAAAT[C/T]TAGCTCAATTTCTAAGTCGAATCCGATT

CTCCAATTAAGCTTCGCGAAGCATCTACAAAA

CAPS_CONTIG.4994 P01 169.224 GT CTTCTGGCTAGTCAGCTTGGACCCTAGGGTGGAAGAAAAGATACTGGTCGAGCTCTGCAC[G/T]GTCCTTGCAGAGACACGTGGCGAC

GACACGTCAAGGTGGCTGGAAGAGCCACTAGTGTTT

CAPS_CONTIG.6883 P01 170.828 AT TACAGAATCAGCTGTTCGAATCAAGACTGCAGTAGGAAGAGGCGGATACGTAAAGGATAT[A/T]TATGTTAGAGGCATGACAATGAAAA

CAATGAAATACGTATTCTGGATGACAGGCGATTAT

CAPS_CONTIG.7829 P01 173.37 CT ATTGCCACTTTTGTTACCTGGAATGATTGCTATTGTCAAGAATCCTAATAATCCATATTA[C/T]ATGTATTGTGGGATTGTGCAGAGGATTA

CTGATGGCAAAGCTGCTGTGCTTTTTGAAGGT

CAPS_CONTIG.10349 P01 175.942 CG CAGGTACAGTGCAGACCTTACCAGAACTTAGGTAATCTGTCCCATCACAATTTTGCAGCTGTCTTGCCTGGCGACTCAGTT[C/G]CAGGA

ATTGTTGTTGCAAATGGAGTTATAAATTTCTTGAACATCTACAATTCATTACTGGTTGTCAGGCTTGTTTTAACCTGGTTCCCAAATGCTC

CTCCTGCCATTGTCAGTCCCCTCAG

CAPS_CONTIG.4964 P02 3.585 AG GTTACTATTCAGTTTGATATTTGCAGAGAAGGCACTAATCGTGATCTTCGTATTCAAGAC[A/G]CCATTAAGGAAGCTTGTTATAATTGGA

TTAGACCGTGTGAAGAGAGGACGCGGTCCAATT

CAPS_CONTIG.6936 P02 3.585 AG TGGACTTGCTCTGTGAAAATCTAGGACTTGGGCAAGGTTACTTGAAGAAAGTCTTTTATGGCTCAAAGGGTCCTACTTTTGGCACCAAA

GTTAGCAACTACCCACCATGTCCCAAGCCTGATCTGATTAAAGGCCTCAGGGCTCACACAGATGCTGGTGGCATCATCCTTCTATTCCAA

GATGACAAAGTCAGTGGTCTCCAGCTACTCAAAGATGGTAAATGGATTGATGTTCCTCCGATGC[A/G]CCACTCCATTGTCATCAACCTT

GGTGACCAACTTGAGGT

CAPS_CONTIG.8070 P02 4.796 AT TCTCACACAGCTAAAAGAAATAATACAGTTAACCTGAAACTGGTACAGATAAGTATCTGA[A/T]ATAACCAGCAAATCAACCAGGAGTG

GTTCACAATAATTGTGTGACACCAGAGAACATCTA

65

CAPS_CONTIG.2427 P02 9.965 AC TATCCGAAGATCTTACCTACTATCGAAATTTGCCATGCCCTGACACCATATACTTCCAAG[A/C]TCATACTCTTATGCTTCCAAGAACCTGT

GTAGCCAGCGGCCTCATCCTTTCTTCCCTTTT

KS01048D11 P02 12.44 AT CAGCACGGGTGAGGCTTTATCACTAGGTATTGCATACTCAATTTTCTCCCTGCTCACTCG[A/T]GTGACATGGTTAGCTAAAGATGTCATA

TGGCTTGCTGCTGATTCACAGCACGGGGAATAT

CAPS_CONTIG.7292 P02 13.457 CG TATCTGTAGTGGCAGTTGTGTAACCAAGTGGCCCATTTAGGGTGCTCAGAAAAATTCACA[C/G]CTAACACGTGGCAAATGTCATGGTCT

AGAGTAACATCATTACTCTCTAAAAAGAAACTCT

ANOK.CO776394 P02 16.446 AG TCAGAAGTCTAACACCATGTACCCAAAGTTCTCGACTTTCTTCAAAAGAGTCACAATTTC[A/G]TTGGACCAGAAACTGTATCCTGACA

ACCATATTATAATATGGGACTCTGCACGATCTCCT

CAPS_CONTIG.4793 P02 17.482 GA GAGAGGACCTGAGGAAGCTTCAGCTTCTAAATTGAGGAAAAAGAAAACATCACTACAAAA[G/A]GCTCCAGTGTTGCAAAAAGAAGG

CAATAAGGCAAAAAGGATACAAGATTTGCATGCACTG

KS19051F07 P02 21.662 CT ATGAGAAGAGCAGTGGCAAATACGAGAAGAAGGTGTATGTCTTGCCAAAGCACCTCGACGAGAAGGTTGCTGCCCTTCACCTTGGAA

AGCTCGGAGC[C/T]AAGCTCACCAAACTTACCAAGGAACAAGCTGATTACATTAGCGTACCAGTTGAGGGTCCTTACAAGCCAGCTCAC

TACAGGTACTGAGGGGAATAGAAACTGACAGCAGCTGATTACATTATCGCGGCATTCTTGTTTTG

CAPS_CONTIG.3815 P02 22.142 GA GGTTGATAGTTACAATAAACCAATTCCGGCCATTTTGGAGATTCCTTCAAAGGACCATCC[G/A]TATGATCCTGCCCATGATTCTGTTCTAT

CACGAGTGAAGTATCTCTTCTCTACTGAATCA

CAPS_CONTIG.197 P02 24.646 CT GAACAACTGCAGTATTATCTGCACTTTAGTACTCATCGAGTAGTTATTCGACATCGACAC[C/T]TTGGATGAAGCCAAGACATCTTCGAGT

TTTTTATTGTACAATGTTTCCGAGTTGCATATG

CAPS_CONTIG.8539 P02 25.248 CT TCCTCTCTCCCTCTCAACACACAACAATTCCATAACACTTCATAAAAAACAGAGAGTCTT[C/T]CCATGGCAGTTGAAGCGAGACACCT

CAATCTTTTCACTCAACAACAAATCATTTCTAATC

CAPS_CONTIG.3570 P02 26.332 GT CTCAGCTGGCTTTGATCCAGAGATTTCTCGCTGGTGGATTCAGTCTTACAGACCACCAAG[G/T]TTACCAATCCCCACCACGTTGTACAG

ATTCTTATGTCGATGCCATGAAGGATCTCCATCA

CAPS_CONTIG.7013 P02 30.822 AT TTCAGACATTTTCTCATGATATAGACAACTCTAGCAGGATGGAATTGTAAAAGCAAGACT[A/T]GATGTTTCAGAACATAAACTCAGCAC

ACATGAAGTTTCGACTCATTCCAATGACTAGTGA

CAPS_CONTIG.392 P02 31.613 AG CCCTACCAAGATTAACAAGGGAACTGTTGAAATTATCACCCCTGTGGAGCTCATCAAGAA[A/G]GGTGACAAAGTTGGTTCCTCTGAAG

CTGCCCTGCTTGCCAAACTTGGAATTAGGCCCTTC

ACRI.DV643211 P02 33.748 GT TTCTATTAGGAACAGGAGCTCTTGCTCTGAGATGGAAGGTATTCAACAGGAGAAAGAATC[G/T]GGAATTTGGGGTCAGTTGGACAAAA

CACTAGATAACTTGAGAACGACGGTGGATACCAAC

66

CAPS_CONTIG.4276 P02 35.222 GA CAATTGTTGGCTGTCCATGATGCAAGTAGTAATGAGTTACATCATACATAACATAGCCTA[G/A]TAAAGCACCTCCAAACAAAGCAGGAG

CAGCAGTGGGAGTTGCTAGGGATTTGACCAATTT

CAPS_CONTIG.9655 P02 49.555 CA CATATCTTGTATACTACCATGTGGGGCACTTGATGTTATTCGTATTGTTCATGCTAATGG[C/A]AAAGTTGAAGAGATTAGTGGGAGTGTTA

AAGCATCAGAAATCATGAAGATTTACCCTAAA

KS24056A09 P02 51.824 CT GTGGAAAAGACAAATGGAAAGTACAAAGTGCTTGTAGAAGTTTTGCCAGTGGAGCTCTCAGATGCACATGCTGAGCTGGTTATAGTTT

GCGGCGTATTTAGATCTGACGCGTCATGCTTTATGCCTCTAGATCTAAACAGATGTGGAGCAGATGGAAAAAG[C/T]AGTACTATTGAAA

CACCATTTGTGCAAGGACCTTCAGGCAAGGTTACAGTTGAGCTGGATTTTGAAGCAAGTTTAGCCCCCTGCTATATCTCCTTCTATATAA

AGTCACAACTAGTTACTGACATGGAAAGCTCAGAAATCAGAAGCCACAGGAACACGAATTTTGTTGTGCCAGTTGGTTTCAGTTCAGG

GCATCCTTCTCCATTGGGTCTTTCCTTTCTGCCAGATGGATCCTTGAATTTTGCTCTCTTCTCACACAGTGCAAAAAGTGTAGTTTTGTGC

TTGTATGATGACACATCTGCTGAAAAGCCTACCTTAGAGATTGATCTAGATC

CAPS_CONTIG.1367 P02 52.25 AG CCAGAGAGGGAGAGCGATTCTCAAGTATTTTCCGGCGATATTCTCGCCGGAATCAACGCC[A/G]ACTGTTCGAGTTAAACCACCCCATA

CCAAAACCTCAACATATCTCGCTGTTCTTTCTGAT

CAPS_CONTIG.9831 P02 54.916 CT GAATAATTGTAGAATGACAAAGGAAAACGGAGAGAGTCAAGATCACCCTTGTCTCAGCAG[C/T]CAACCTGTTACCATAGATGAAGAA

GAAGTCATTCTTTTCAAGCCCATCACAAGACACAAC

CAPS_CONTIG.10670 P02 56.232 CG TGAAGATGATGATGGAAATGTCAACGCTGTGATTTTCCAGGTGGACTTGTATACAAAACT[C/G]CACAGCATTCCACGTCGTGGAAGTG

CTGCAAATTGGGCAGGTGCCACTACGGTTGAATGA

CAPS_CONTIG.344 P02 58.856 AC CCCATTTTGTTCAAGAACAACTACCTGACGAAGTTAATCCACTTGTGCTCGAATTCCTTA[A/C]TAAGAACAGCAAGCCTCAGTAAGGTC

TCGCTGTTGTTGTTGCTCCGTCTACTAAGAAAAG

CAPS_CONTIG.4796 P02 61.067 CT TTTCTATCTTTACATGGTTTGTCACAGACCACACAAACCTTGTCAACAGCCACGAATTTC[C/T]CTGCACATTTCTTGCAAAAAACATGT

CCACAAGTACTAAGTGCTACAAGTGACAAAGTAT

CAPS_CONTIG.679 P02 65.44 AG TCCTCAAAACCATCTCTTTCTGACTCCTCTGCGCTTTCTTTCCGCTCTGCTGTCAGCCCTTTTCAGCTTCCTAACCATAACTCATCAGGC[

A/G]CTTCAAACCCCTCAAGATCATCATCAGCCGCCACGGTTCGATGCGGTCTCCGTGATCTGCGTGATCGAATTGATTCTGTCAAGAAC

ACACAGAAGATTACTGAGGCTATGAAGCTTGTGGCTGCCGCTAAAGTCAGAAGAGCTCAAGAAGCGGTTGTGGGTGCTAGGCCTTTCT

CCGAGACTTTGGTTGAGGTCCTTTACAACATCAATGAGCAGCTTCAAACAGATGACATTGACGTTCCCCTCACGAAAGTAAGACCTGTC

AAGAAAGTGGCTTTGGTGGTTGTCACCGGTGACCGTGGTCTTTGTGGCGGTTTTAACAACTACATCCTCAAAAAAGCTGAGGCCAGGA

TTAAAGATTTGAAAGCTCTTGGCCTTGATTACGTTGTTATCAGTGTTGGCAAAA

CAPS_CONTIG.9369 P02 65.696 AT TGATCCACCAGAGCATGTCATGCACCGTGCTGAATTTCTCCTTCAGAACGGTTTTGGGGT[A/T]TACAACATATTCAAGAACAACTGTGA

GGATTTCGCAATCTACTGCAAGACCGGTTTGCTA

67

CAPS_CONTIG.2724 P02 66.751 GA CCATTGAGTGATTTTGGGTTTGGGAAAAGGAGCATTTGGGAAGGTGGGGTTGGGTTGTTT[G/A]TTGTTTCGGGTACGGGGTTGTTGGC

ACTAAGTTTGGCTTGGTTGAGAGGGTATCAGTTGC

CAPS_CONTIG.3499 P02 68.524 GA TCACCGGTGGCATTGTCTTGTCTCTTTTTCTTGTTCCTAATTACAGGAACTTTGGCACAA[G/A]ATATTGGTTCAATTGTAACCAGGGACT

TGTTTGAACAGATGCTGAGTTTTAGGAACAACG

CAPS_CONTIG.5217 P02 69.818 CT TAGAGCCCAAGTGACCACAGAGGCTCCTGCTAAAGTTGAGAAGATTTCAAAGAAACAGGA[C/T]GAAGGTGTGGTTGTGAACAAGTTC

AGGCCAAAGGAACCTTACATTGGTAGATGTCTACTC

CAPS_CONTIG.94331 P02 76.842 AG CTGTCCGAGAAATGAGTGTTATTTTGTGCTTAGATTTACATATGGGACAATGTTTCCTCC[A/G]TCGCAGGGGAAACGAGTTATGGGTTGT

GAACTTCATTATCATGGTCGTGAGGAGAATTTT

CAPS_CONTIG.9038 P02 80.882 CT TTGTGCATGGACATTTCCAAGGGTCATTTGCCAAATCATGTAGCTGATGCTGATTCTGAG[C/T]CTGTTGGGCAGCACGAGAAGGAAATG

TCAGGTTGGAGCGTGCTTGATATTGGGACTGGCA

CAPS_CONTIG.3710 P02 81.705 CT TATTACGAAAATACCCAGCTGTGTTTTCAGTGTTTTGGATTGGGCTGTTTCTGGTAAGCC[C/T]GGTGGTTGTTATTTGGATCTTCCTACTG

ATGTGCTTCATCAGACTGTTAGTGAAACTGAA

CAPS_CONTIG.5561 P02 83.405 CT ACAGCTCACACAAGTTGAACTTCAGAATAATCTTCTCACTGGTACATTTCCTGATATTCC[C/T]TCCATATCTTCCAGTCTTGGCCAGATTA

GTCTTTCGAATAACCGACTAACTGGACCTTTG

CAPS_CONTIG.6372 P02 84.488 CG GTCACCTCGTGGACTACCTCCTGAACTGCTGTTTGAGAGTGAAACGAAGGTTGACTTCTG[C/G]AGGACACCTGTGGGAGATGATCCA

AATGGAGGGCTGTTATCCCAAACCTCTGTTGCCAGG

KS19047D04 P02 85.949 GT AAATACTGCTGCGCGCCAACAGCTACAAAGAATACGTGGGATTGCCTCTTTGATGAAGGT[G/T]ATAGAGCCGACGTTTCAATTAACAC

AGATAGTGGTGGCATCCTCTACGTGCATGCTAGTA

CAPS_CONTIG.4895 P02 91.546 CG ATCCACCTGGAAGATTGAATTTGGCAGAGTCCAGAAACAGTAGACCCTCTATGAGGAATC[C/G]AGACTTTGTACCTACCCTTAGAGAG

ACCTCATTGCAGTTCAATTATCCTTCAGCAAATAA

CAPS_CONTIG.1134 P02 91.616 AG CCTTACTTAGAGGAAATCATCATAACCTAAACCTTGTCAAGGATGAGCAAAAATCAATTG[A/G]GGTGAATTTACATAATCAGTTTCCTTC

CAACAGTCTTTCCAGTTTGTGGAAAAATAACGA

CAPS_CONTIG.5328 P02 93.017 GC TGGAGATGTGCATGACTAACTTGGACAAGAAAAAGGCATCCGTATTTTTCAAGACTCAAT[G/C]TAGCACTGCTGCTGAGATGACTGAA

CTTTCAGGCATTCGGAAGATTCTTCCAGAATCAAA

CAPS_CONTIG.3996 P02 94.112 AG GCTGTCCGAGCACACTTGTGTGGCTGGAAATTTATCTATGTTAATGATGTAAGGGCACTTTGTGAGTTACCAGAATCATACGAGGCTTAC

AAAAAACAGCAGCACCGTTGGCATTCTGGTCCTATGCAGCTCTTCAG[A/G]CTATGTCTTCCTACAATCCTGACTTCTAAG

CAPS_CONTIG.6181 P02 97.201 AG CCCGATTCCAGATTCCTCCAGTACAACTCACCACACCCAACCATAACCGACCACACACCA[A/G]TCCTCACCTTCCCATCTACGCGCGTG

ACTACACTGCCATCAGGTCTGCGGGTGGCGACTG

68

CAPS_CONTIG.460 P02 103.03 AG CGAATTTCTTGAACTATGATATTTATGATCTTGAGCTCACCTCCGTTAAGGATAACTCGG[A/G]GCTTAAGAAATTGCTCATGGAAACAAC

GAGCAAATCCATCATTGTCATTGAAGATATTGA

CAPS_CONTIG.12241 P02 104.353 GT TAGGGTTATACTTTAATAAAGTGTTAGTCTGTGTAATCATTTGCTTGTTCTGTAATCAGT[G/T]GTCACTAGAAGCTAAAACATATGTGCAT

GTCCTCTTTGCTTCAAATGGATAGTCATTTTC

CAPS_CONTIG.9821 P02 105.552 CT AGCTCTTGTATTGTATTTAACTTGAAAATTCTCAAAGTGATAGGAAATGTTATCCTTGAA[C/T]GTTTTTTGCTGCATCTGTAGTTTTAGTT

GAACGGGACTTCGTAAGGGCTTGAATTTGTAC

CAPS_CONTIG.4174 P03 1.935 CT AAAGAGAAGTAACTTCTGCTACTGAGTTTTTGGCTTCTGGATCTTCACATATGGGAAAAA[C/T]CCGAACAAGTGCTTGATTTTGGGATT

CCATTCACGTTGCTGAGCACGGCAATACATCAAG

CAPS_CONTIG.5679 P03 1.935 AT AGCTGGAAGAACAACACGAAACT[A/T]GAACTTCCTGCTTGAGCCCATATCGGAGACAAACAGGAGCTGGCTGAAGATGATCCGATGA

ACGTTTATAAGTCTTATGTTTGGATGTTTAAT

CAPS_CONTIG.5880 P03 2.552 CT TGTCTTGCCAAAGCACCTCGACGAGAAGGTTGCTGCCCTTCACCTTGGAAAGCTCGGAGC[C/T]AAGCTCACCAAACTTACCAAGGAA

CAAGCTGATTACATTAGCGTACCAGTTGAGGGTCCT

CAPS_CONTIG.2388 P03 3.592 GA ATTAGTTTGTAATATAATAGTTGAGGCTACTTAAGAGATGATATTGGGGCCCTATTGGTG[G/A]GCAGATCACTTAATATCTAAAAATTGAA

CAAGAATCTAGTTTATTGCATTAGTAACTTCC

CAPS_CONTIG.8242 P03 10.087 AT CTGCTGGTCAAAGTTGGCTGTTTTCAAATTATCCAATTCTCTTGCTGCATAAAGAAGAGC[A/T]ACACCACCGCCTGCAACAATTCCTTC

CTCCACTGCTGCCTTTGTGGCATTCAAAGCATCA

CAPS_CONTIG.11835 P03 10.629 CT GATGGATGTGTGGTGGGGTTTGGTTGAGAGAGATGCACCAGGTGAGTATAATTGGGGTGG[C/T]TATGTTGAGCTTATGGAATGGCGAA

AAAGCATGGATTGAAAGTTCAAGCTGTGATGTCCT

CAPS_CONTIG.5329 P03 16.828 CT AAGAGTTATGGTATCTATTGTTATAGTTCCTCTACTTTAAAAGATGTCAGACAAATTGAC[C/T]GTTAGAAATGGTTCATGAATTTATGTTA

GCTGGTAGATTATTAGATAGGAAATTCGTTAG

CAPS_CONTIG.6934 P03 17.506 GA TGCGAAAGGAATAAGCTCGGTTACTATAATCATTTCTGTTGCAATCTGTTGCTCTTTTTC[G/A]CCAATAAGACTGATTATGTACTTGTACA

AACACTTGTTTTCTTTTTTCACTCATCTGTTC

CAPS_CONTIG.9046 P03 23.758 GA ACCTTAGAACCTTAGTCATCTGTCCTGTTCAAGTATTGAGCAAGTCTGTTGAAATATAAG[G/A]AGACAAGCACTGGTTTGTTCATAGTT

GCTATTCTATTTGTTATGTAACTTTGGTGATGTT

CAPS_CONTIG.12629 P03 26.998 CT TCAATCATCATCATCTGCTTTATCTGCTAATCGTTTAAATCCCGGTCAAAAACCAACTAC[C/T]AGCTGGTGGACCCCACTTTTTGGTTGG

TCCTCTGAACCGGACTACATCGTTGATTCTGGT

CAPS_CONTIG.180 P03 31.286 GA CCATACCATTCCTGTAACTTTTGTAAGTAAATCAGGATATTGGAATTTCATCACAGTGAT[G/A]CGTGAAAATGGTGATGTTAACCTCCAC

AACTGCAACCATCTGTGAAGTTTACCTTCAAAT

69

CAPS_CONTIG.6256 P03 31.961 AG AGCGAAGGTGCTACAGATGAGGAGCGCAGCCGTCTTGAAGTGGTTGGTGAATACCACCTC[A/G]GTGAATTTGTTAACAGGTTTAGACA

CGGTTCACTTGTCATGCGACTGCCAGATTCAGACG

CAPS_CONTIG.12305 P03 33.114 CT GAACTCAAATCTCTGCAACTCTCTCTAATAGAAGAAGATCTAAGCAATCTACAGAACTTT[C/T]TAGAAGAAAATGGAGTGCGTATTCGG

TATGGTGGGAAATGGATTCTCACTAGTAGTAGCT

KS15046C11 P03 35.534 AG TCCTAATCCATTAAACATTTTCTGTGGTGTGATGAATTGACATCATGACTTGTATGTTTA[A/G]TCATTGGATATATGAGTATTTGTATTTATA

ATTGTATTCTCTCCTATTGTCTTCTCAAAA

CAPS_CONTIG.8698 P03 36.724 CT TCTGTTACCGAGGTCCTCAGAAGATCCTCTTGTAATTCATCAATGAAATGATAATAGCAC[C/T]ATAGTATCCAAGTTTCTGGTTAACTTCT

CCATGATGAGATCCCCAAATCTTGTTAGCAAC

CAPS_CONTIG.8828 P03 37.443 CT CTCTTCAGCAAAATCCGGAATCACCAAAACTTAAGCAAGAGTTGCAACACATAGTGTGTA[C/T]ATCCATTTTGTTGTCAATATTTGTTCA

AAGTCCATTGTTAGTGTGTGTTTGTACAATATA

CAPS_CONTIG.1406 P03 39.17 CT AAGGGGACAATTTTACACTGTAAAAATGTTCTGGGTCACCAAGTTTTCTGGATTTTTCGC[C/T]GCTGCAATGGTAATGATTGTGTTATCC

CCTTCTTTACAATCGTTTCCACCTGCTGAAGCT

CAPS_CONTIG.9537 P03 42.2 CT CCAATGCTTCAAACTTGTTTTCAGCTGT[C/T]ACAAATGGCAAATTTGTTTCCTCTGCAACTGCTGCAGCAATTTTTATGTCAAACC

CAPS_CONTIG.3640 P03 42.269 CT TTGATGTTTTCCTTGTGTTTTTTACAGGTAAGATTGTTGGGGTCATCTGTGATTGCTGAT[C/T]GAGGATGCCATCATGCTGTGTTTGAGCA

GCACAGTCCACCGTTGGGGAGTCCTGAGGGCC

CAPS_CONTIG.4022 P03 43.106 CT AAGCATCATCCAAAGCTCTATTAATAGCTCATAGGGCACCAGAAATAGCTCGAGATCTCA[C/T]CAGCGAGGTACAGCGCAATGGTTTAG

CAGACACAGCGAATAACATAGGTAAAGCACTGTA

CAPS_CONTIG.11734 P03 47.281 AG GAGTACATGTTGCTTGTGTTATGCTGTGAGTATATTATTTCAAGATCTTGGAGTAATTCC[A/G]TATGTTTATGAAATTGACCATGATCCTC

AAGGAAAAGAAGTAGAAAATGCCCTAATGAGA

KS24036H07 P03 51.632 CT GAGTGTCAGAATCAACCTCACTTTTGGGAATTTGGCCAAGTTCAGGGTCCAGATATATGT[C/T]CTTTTCCATCTCATCTGTAGCAGTAGA

TGCAACAGGGTTATCCGTATCTCCCTCGTGATA

KS10024A09 P03 52.058 GA CAGCAACACCCAAAAGCTAAGATTAGAAAAGGCATTACAAAAATTGGAGTCCATTTCTTC[G/A]AAGCTTAATTCCAATGCCACTGTCAT

TGTTGCCGACACCATTCCCGTTGACGAAGATGCC

CAPS_CONTIG.467 P03 54.807 CT TCCATTTCCATGCATCAAGGATTCTCTGGCTTTCTTACAAGTTCGCACTATAAGGACTCT[C/T]TGAGAATCCTAAAGTTCATGCTACTATT

GCCTAACTTAAAAGAATACACACAACAAAATA

ANOK.CO910343 P03 56.312 AG ATCCTCCTGGAGTGCAATCTCAGAATAGTGCACCTGCTCCTTCAGTTCCTACTTATGTGT[A/G]TGGCAATTCTGTCACACCTAATGCTCA

ACCTGCATACCCAACATCTTCATACAGTTATCC

70

KS11064B07 P03 59.27 GT GAAAGCTCCTTAGACCTGGTCGTTGTCAACACATGCCTCTACACAAGCATTATAACCACA[G/T]GAGGCTGTTATGTTTCACTTGAACTC

ATAAAAATGTAAATTCTCTATGTATATGGAAGCG

CAPS_CONTIG.8416 P03 69.47 AG GCAAGCAAGCAAGCCTTTGACAGACACATTTCATGCATATTCATGTCACACCCCTTGGAA[A/G]TGGAGACCATTTGGCACAGGCTCAA

GTATCTCTACCGTTGTTTCAGGAGAATGGGGGTTT

CAPS_CONTIG.9004 P03 70.355 GT CTGAGTAGGGAAGATATTGAAAATGCCATACTTGGAGGTCCATAAGGACACCATTTTATG[G/T]GCATATGTTAGTTAGCGTCAGCGCTTC

CATCTGAATTCCAAGCAACTCTAATGGACTAAA

KS23061E02 P03 72.924 AG GAGGTATTTGAGTGCGTACTTCTTGAAGTGCTTTCTGTGCAACTTCTGCGTTTCCACTTA[A/G]TGGTTCATGAAGACTCATCATCACATC

GATTTCATCCGACACAAGTTTAGCTACAGAAAG

CAPS_CONTIG.4584 P03 74.411 AT CCTCGAGGCATCCAAAGGAAGCTTCCCTACATATCTAGGCCGACCATGGAAGATGTACTC[A/T]CGAACAGTATACATGTTATCTAACATG

GGTGATCACATACACCCGCAAGGTTGGCTTGAG

CAPS_CONTIG.9082 P03 76.235 CT GAATCAGCAATTCGTCATGCTCGAGAGGTTGACAGGAAGACAAGAACTTTCTGGAAATGG[C/T]GAAAACAGTGATAATGGACGATCT

GGTACCCGAGCATTTCATGCATTGATGTCTTTATTG

ANOK.CO909888 P03 76.982 CT ACAAAAGACTGCTGGTGGAGGTGGAGAAGGCAGAGGAAGATGCTGTTCTGCAATTGCAAT[C/T]GATGCGCCGGCTCCTTTAACCAGT

GTTTCTGGCATAAGATGGGGCTCAACTATGATCCAA

CAPS_CONTIG.12508 P03 77.516 CT ATCTCTATCAATGTAAATAGACAACAATCACTATCATGCGTGAATTTGAGCATCCAATAG[C/T]ATGTTATTCCCCTGATTGTATAAAACAT

ACATTTCGAATCATTTTCATCAACTGATCCAA

CAPS_CONTIG.5830 P03 77.545 AT TTTCAGGGAAGAAATGGCAGAGCTTTTCTGTTTACTCATGTGATGAATATTGTTGTTGGGGCTAAAGAAGACAGAACTCTCATGACTGG

TCTTCATACTGTTGCTGATATACACTGTGGGGATTGCAATGAGGT[A/T]TTGGGCTGGAAATACGAACGAGCTTATGAGCCTACTCAGAA

GTACAAGGAAGGGAAATTCATACTTGAGAAATCTAAAATCGTTAAAGAGAATTGGTAGTCCACCACCAATTTCATTATTGATTCTTTATC

TTAGTACTTAATGTAAGTAATGCTTATTCTATCTATATCACTCCTTGTACAGAACATGCCAAACTGAAAAAATTGCAAAAGTTCAATTGAA

GATTTCGACTTTTTGTTGT

KS19014A11 P03 82.612 CA GGATATTAACATGAATAGAAAGCTAAATCAAGCAATTCTTTTATGTAAACTGTGTCTAAA[C/A]TATCCTATAAAGTATATGACATTAAACC

GCAAGTCCTGAGAATCCATCTTTATTACGAAC

CAPS_CONTIG.2858 P03 83.837 CA TGGAATTGCCGAATAGCAGTGGTCAGAATCCGATAGCACAGCTGCAGAACAAGTTTAAGG[C/A]GTTGGAGGCCGGCTTCAAACTGTG

GCTATCGAAGCAGTCACTACCTGTTGAAGCTGCTGT

CAPS_CONTIG.11544 P03 86.666 CT GAAGTCCATCAAGAAGAAAGAGAAGGAAACTGTGAAAGAAATCTTATCAACTGCTCACGT[C/T]GTGCTTGCAACTAATATTGGGGCA

GCTGATCCACTAATAAGACGGCTGGATGCATTTGAT

71

KS21049G04 P03 90.387 AT ATGATTTTCACAAGCTTTGGAAGTCATGGGAATATGCTGGCCACAGTTTGTCACAATCAG[A/T]GTGTCAAACTTTTTGGGAGTTCATTG

TGAAGCACTGGAGCTCTCGGACGGAGAACTTCCT

KS23011E11 P03 98.143 GT GCTGATCAGAACTCAAGTTGAAGAAATGTCAAATAAACTAAGCTATGACTAGCCCTAATC[G/T]TTACCCAAAAGATACCCAGTAAGACC

AGCATCTCTTGAGAAATTTTAACCAAACAGGTCA

CAPS_CONTIG.11933 P03 102.723 CT ACACCAGCAGACGTGAAAGAGTACCCTAATTCCTATGTTTTCGTCGTTGATATGCCGGGG[C/T]TGAAATCTGGAGACATCAAAGTGCA

GGTGGAAGAGGAAAATGTGCTGCTTATTAGCGGAG

CAPS_CONTIG.154 P03 103.3 CT AGGTCCAGTTCACGGAGTCTGCTGAATTGAACAAGAATGATAAAGAGAAGAACGATGACG[C/T]GCAAGCTGATGGCTACATCGATCA

GAAGAACAAGAGTTTTCAGATCCACAAATGGAGGAC

KS15022D11 P03 106.435 CT CTAATCACCTATTCAGAAACCACAAATTTGGGTCATCAAAAATCACATCATCTCAAATCT[C/T]CTCCATCTCTCTTCATACCGCAATCGA

CGAGCTCCAAAAAATCACACGCACACTCAAATC

CAPS_CONTIG.9424 P03 109.58 CT TGAAGGAAAAATTAATCACTTCCACCAAGAAAAAAAAGGCAGATGGTTAGAGATGGGTAG[C/T]TTTCCATCATTAAACTAGAGCTATG

CAGAATTAATGACATGTACAGCAAAAAAGAAGAAG

ANOK.CO909129 P03 110.441 GA TAGTGAAGAAACAGAAGAGGAACGGGAAAGGGAACGGGATGATGTCGGGGAAGGATGGAG[G/A]TATGGCGAAAACGATGACGACG

ATGAAGAGACTGAAGAAGATGACTAGGCTTTATTCGTA

CAPS_CONTIG.730 P03 112.831 AG TCTTTCAGCAGCTACTGACCCTTCAACACCATCTGCACTCTTCAGTTTGAGCTTGGCATT[A/G]CTGGTTGTTGGCCCTGCTTGTGTGTAT

CTGGTCCCTGAAGATTACCCTTGGCAAATTGCT

CAPS_CONTIG.2611 P03 118.332 GT ACTTTAAAATCATTCCCCATACAGCTTTCTAATTACAGAGGACCAGTTTCGTTTGAGAAG[G/T]GAAGAAAGCAGGATGGTTTCCTTTTC

CTTCTCTACGTTCTTTGACATGTGGAGTTGGTTC

CAPS_CONTIG.3343 P03 120.406 AT CTGAACAAGGGAACCGGGAAAATCGCTTAAATATGCCCTCCACAGGAGGTGACACTGATG[A/T]TTCCACTAAGAGAGTCATAGATAGT

GCTCATGTTAAGCAGACTCTCGAAACTGATATTGC

CAPS_CONTIG.6075 P03 121.782 AG CTGCTATGGGAAAATGGTGGCGGAGAAAAC[A/G]GCGTGGGATGAGGCAAGGGAAAAAGGAGTGGATTTGGTCGTGATCAACCCAGT

GTTGGTGCTTGGACCACTGCTCCAGCCAACAGTGAATGCAAGTGTTCTTCACATACTAAAGTACCTAACTGGCTCTGCCAAAACATATG

CCAATTCAGTTCAGGCATATGTTCATGTTAAGGATGTTGCACTTGC

CAPS_CONTIG.1011 P03 123.922 GT TAAGAATCCTAAGAGTGGGGAGTTCATTGAGCACCACCTCAAGTTTCCTCCTTCCGTACC[G/T]TCTGACAAACTAACCCATGTTTACAC

TGCTGTGTTGAAACCGGACAATGAAGTTCTGATC

KS17053A07 P03 125.557 CA CAAGTACAAAGGAAGACAGAGGACATTAGTATATTTACCCGCAATCCCGGCAAATATAAG[C/A]TTGCTTAGAGGCCACACGCATGGAG

ATTCTAGGGGCAGTAGCAGGAGCTGCACTGGAGAA

72

CAPS_CONTIG.8564 P03 128.039 GT TCATCGTCGCACCAAAACTTGGAATTGTGCCCGAAAACCTATACTTGGAATGACAAATTA[G/T]ATATAAAAAATCAATGCATACATATAC

AAAAATAAGAAGCAAAACCATAATTTAACCATA

CAPS_CONTIG.8592 P03 130.497 GA TTTCATTCCTTCAGTGTCTTCATCTTCTTAGAAGAATTCAGTTAATTTTATATGCTGACA[G/A]TGCAAATTTAGCGCAATAATTGTCTATTA

GAAGATCCGTCTGAAAAGTAACCACCAGTGT

CAPS_CONTIG.5926 P03 131.387 GA TGATGTTAAGTTGCTTATTTAGCTGTTTTTTTAAATGATTTTGAACCAATGAGGTATTGA[G/A]TATTTTTTGTTGTTATTTTTCTTATTTTGG

TGAAAGAAAGCCCATTTATTATTCAATATC

KS17054B11 P03 132.297 CT CCATTCCTTTAGTCTCCTAGTCCATCTTTCTGTGCTTGCTTTCCGAATAGGTGAATATCT[C/T]GTGAAGAGTTCCAGGAAAGTCAGAAGG

ATTATGCATCTCGAAGGTAAGAATGCCAGAACT

CAPS_CONTIG.915 P03 133.393 AG AGGAGAGTTAGAGAAGGCGCGGCGATGGTGAGGACACAAGGAGATCTATTAGGTAGGGGT[A/G]ATATTGTTGATACAGTTCGTAATGT

GAGGAAAGTGATGGGAGATATTAGGGTTCTATCGA

CAPS_CONTIG.863 P03 139.584 CT GACAAAGAAGAAGGATGTGGGCACTGAGGAAGGAGAAATATTAGATGTTCCTGGCGCCTC[C/T]GTTTCAACAGCAGCTGCTATAGCA

GTTAATGAAAAGGAAAAGGAAGTCACTACTACACCT

CAPS_CONTIG.4313 P03 140.157 CT TGGGTGCTTTACCGACCTCAGAGGCCATCATTCTCCGTTTCAACTCTTCAAGTCTCTCAATTCAATCTCACCTCAACAAAACTCGCTTCC

AAGTTCAATCTCTCCATCGTAGCCCGTAACCCTAACAAAAAAATCTCATTCCTCTACGATCCGATCAACAT[C/T]TCGTTCAATTCCGACG

ATTCTGAGATCGGCTCCGGATCATTACCCGCCTTTACACATGATACAAAAAACACAACGACGTTGAAGACAGTCGTATCAAGTTCAGGA

ACAACTCTCGATGATTCAGTAATTTCCACACTGAGATCTAAGCTGAATAA

KS14027C04 P04 3.461 CT CTTCATTTGGCTGTCATTGGTAATATTCATTCTGAACTCGTGGAGTTACTTATGACTGTCCGTTATATTAATGTCAACACTCGTGATAAGGA

TGGAATGACACCGCTTGATATCCTGAAGCAACGGCCACGTTCTGCTTCATCAGAGCTGCTTACGAAGCAGTTGATCTCTGCCGGGGGGA

TTTTTAGCCATCACGATTATTCTGCGAGGAGAGTTG[C/T]TGCATCCCATTTAAAGATGCAAAATATAAGTAGCAGTCCGGGAACTTCTTT

TAGAATCTCTGACACTGAAATATTCTTATACACGGGCATCGAGCATGCACCAGATTGCAATAGAAAACCTGAGATTAGAAGCTCAACTG

AGCTGAGTCATCGCTGCATGAGTCCCGATACCTACTGCTCTACAAATGACAAGAAACCTGGTTCCGCAAATGATGCAGCCAAAAAGCT

GAAACGCTTCTTCCATTGGCCGAAAATTAAAAAAGGAGATCGTAAGAGGC

CAPS_CONTIG.7189 P04 6.685 AG TGCTAACTCCGGTTCCAAGAAGAAGAGCACTAAGAAGTAAGATCATTCGACTGACATTTC[A/G]CTCGGTCCTCTTACAGCGAACTGTT

ATGATGTATCAATCGAATACAGTTGATGGTTTTTC

KS16052G01 P04 7.269 AT CAGGGACAAAATCAGCAGACGAGCGGATTTAGGCAAGGCCAACAACCGCCATCGCAACAG[A/T]GCTATGGATCTTTGGGGGGCTACC

CACATTTCTACAATTCTCAAGCTGGTATCTCATTAG

CAPS_CONTIG.8001 P04 37.34 AG CAGTATGGTGGTTATTATGGGTATACAGCTGGATATGATGCCGCCGCTGCATATGGTTATGCTCAACCTGCTCAGGATCCAAATCTTTATTA

TGGGGGTTAC[A/G]CTGGGTATGGAAATTACCCTCCACAGCAGCAACCACCACAG

73

CAPS_CONTIG.9633 P04 37.454 CT CAGAGGCTTTTCCTTCTCATTAGGAAGGTTTGATGTAAACAAAAAATGATAATAACTCAA[C/T]TTTTACTTAAAAGACGATGGAGTATCT

GTGAACGCGTCAGCTACTGGCACGCGATAAATC

KS21061G15 P04 43.838 CT CAAAACAATGAAGGTTAAGTTAACAGCGAGAGCGTTTACAACATTAGCTGGAAGATTGTG[C/T]TCTTTGATGTCTCAAGGCTTTTGCA

GCACATCTGCTAAGATGGAACATATTTGTTCTCTC

CAPS_CONTIG.1095 P04 47.896 CT TGCCTTATGGGGGAAGGTCAAGAAGGGAAAGATCGTATTCTCCTTATGAAAGGAACTATG[C/T]TCGTGGTGGCAGATAGGAGGGCATC

TGGTGACCCTACTGACAAGGGAAAACTACTTGTAA

CAPS_CONTIG.4908 P04 53.147 AG ATGCAGATGGAAACCTTCACCCTGATCCCCATTCAACGACCTCTTCTCCAAGAAGCAAGC[A/G]CTAAGCTGCCTCAGTAGCCTGTCAA

GACGTGAATGTAAGCACTCTCTCGAATCTTTCACG

CAPS_CONTIG.12219 P04 57.181 GT GTCGGAGATTCATCGAGTTGAAAAGGGTCAGGGTAATGAATTGGTCAGAAAGAATAGGAT[G/T]GTTGAAAAGCAGAAGATGAAAGAT

GGGAGTTTTTTGCGCAAGAAACCACGATACAATGAA

CAPS_CONTIG.6955 P04 57.747 AT TGATCTGTTCTTTTGAACTGATCAGCATCTTATTCTACACTTATTCTATGCTGCGCGAAT[A/T]ATAGTTGCATCAAACTGCCAACATCATG

CTCAGGGGCCACTGTATTTGGCAGCTTATGCT

CAPS_CONTIG.4598 P04 59.823 CT TGGCTTTCTAGAGGGCTAGATGAAATCTACAGGATACGCTCATTTGACATGGGCAGCGAA[C/T]GCTTTGGGGAGATGCAAGGCCCAGA

TATTCCAAGTGAAGACTGGGGAGCGCTTACATTAC

CAPS_CONTIG.6020 P04 60.656 CG GCATGGCACTGTCTATGCTAATTATGCTGTCGATAGTAGTGATTTGCTGCTTGCGTTTGG[C/G]GTGAGGTTTGATGATAGGGTTACTGGT

AAATTGGAAGCTTTTGCTAGCCGTGCGAAAATT

CAPS_CONTIG.159 P04 67.124 CT CACCACTGAAACCAAAACTGCTGAGGATTATAAGGAAGAGAAAAAACACCACAAGCATCT[C/T]GAACATGTCGGAGAACTCGGTGCC

GTTGCCGCTGGCGCCTTTGCTTTGCATGAGAAGCAC

CAPS_CONTIG.10085 P04 70.423 AC TATTTCACGACCATCTTCTCCAGTAAACGGAAAATTAGGGCGCCTCGCGGTGACAATCTC[A/C]AACATTAACACACCAAAGCTATAAAC

ATCTCCATTAGTTTTCGCCATTGGTGCACCATCA

KS20020C05 P04 72.518 CT AAAATGTCCACGTTCCGAAGGAAACGCAGAAAATCGCCTATGCACCAATTGCTGTGCAGG[C/T]CGTAAGGGTTGCAACTATTACAGCG

CTGACGGGACTTTCATTTGTGAAGGAGAGTCTGAC

CAPS_CONTIG.12621 P04 77.291 GA ATCACAGTTACATTTGCATGAGGCACCAGAGGTCTCATCTGCTCCTGTGAATCATGAAAA[G/A]CCAGTGTACGTGGCGGAAGAGGATT

ACTTGGAAGATTTTCTCGAGATGGATGACCCTCTT

CAPS_CONTIG.10177 P04 78.076 CT AACAGTGACAGCTCTGCGTGATCCAGAATTAAATGAAGCTGGAGTTATCTTATCTTGTGG[C/T]GCTTCTTTGAGTTGGAAAGACGGAA

GGATAGCAACTTTTTACTGTTCGTTTTTAACCAAT

CAPS_CONTIG.6527 P04 78.095 AC AGGAGAGCAAAAGTAGCAGCACTTCTAGAAGTATCGTGTATCTAGTGAAGAAGGCAGAAGACAAGTGGTGGAGCAGACTGAT[A/C]AA

GCAGGAAGGTTTACGTCCAGTGTTTTTGAAAGTTGACTGGGACAAATGGGTTGATGAAGATGAAGAAGATGGTAAAC

74

CAPS_CONTIG.7592 P04 82.27 GT TAGTATGAGGAAAATTCGGGGTAGACACAATGGCTTTCATATGGTAATGGTCTGAAGGCA[G/T]ACACCTGTATGATTTGGAGAACTTGT

GTGGTGATCGGTAAAGAGCTAGCAGGATGACGGC

CAPS_CONTIG.12186 P04 89.549 AG TTCAGGGAGATGAACTGTCATTGCAGAGGGCGTTAAATATGATTCACCGGAATACACATG[A/G]TTATGTTGCTTTGCTTTTCTATGCATC

CTGGTGTCCTTTCTCTAAAAGTTTTAGGCCAAA

CAPS_CONTIG.8288 P04 97.526 CT GAGAAAAGTTGATTCTGCTGCCCTTTGGGAATGTGTTTTGCTTGCCCACATAATTGTTCG[C/T]TGTCTGTGTGAACGATATAAGGCGAG

CTGTTACCTCAGTAGGACCTTTGAAAAGTTTGTA

CAPS_CONTIG.10877 P04 101.527 AG CTCCACACAAAAAATATCTTCTGAAAGAAAAAAAAAAAAGAGAGCATTATACTGTCAATTTCTCTGAATTTTAGCAAAACTA[A/G]TAA

GGAAAAGTCAGTTATCATTATTGTTCATGGCAGAATCAAGTTATGCGACGACTATGGCTAGTAATCCGATTGCTGTAATCGGATCCCAATA

TTGCGCGGCGAACCAGGTTGATCTTGTTATATCTAGGAAGGTCAAGACACTTAGATATGGAGAATTTGTTGTTTCAGATATGAATGGCAA

CTTCATCTTCAAAGTTAAAGGCATAGCTTTTGGATGGCATGATAAGAGAGTTATTCTTGATGCTGCAGACAAGCCCTTAATCACTCTCAA

ACAAAAG

CAPS_CONTIG.4984 P04 107.221 CT AGTTTTCGGAATAACGAAGGACCACAATCCAAGCATGGAAGGGCATGTTTTCCCCAATCC[C/T]GTCGATACTGAAAGCTACATGGTAAT

GTTGTGCTACAAGAATGGGTCACTAGCTCGTGAA

CAPS_CONTIG.7233 P04 110.857 AC CAAGGTATATCATTCCTACTCGTTGGCCTAGACTTGATCGGTGAGCAGGTCGATTAAAAT[A/C]TTTCATTAGCCTAGGGATAATATTAGTT

CAACCGAAAAAGTCAAGTTGGAAACTAGATGC

CAPS_CONTIG.11811 P04 113.159 GT AGATGAAGATGATGAACTTGAAGAAGAGCCAGGTGAAGAGATAGAATCAGCACCGCCGCT[G/T]AATGTTGGTGAAGAGAGGGAAATT

AGCTCAAATGGACTTAAGAAGAAGCTTATTAAACGT

KS09094F03 P04 115.48 GT TGGTGAGAATAAGGCGGAGGAGGAGGAGAAGTTTGTGGAATGGAGGAGGGGATTTGTGGA[G/T]AAATTGGATGGAATTGAGTTGAAT

TTGGAAGGTGTGAAGTTTAAGTTGAAGGTGGATGTT

CAPS_CONTIG.8851 P04 124.702 AC TGAATGTTAAGTAGTTTGCTGTAATCTGTCCAATCATTTTTGTCTTAGATTTTGTAAGCCAATTGTTTATGCTAATTCTTACACGAATAAAT

TGTATAAGCTCCGGGGCTTTACTTCAGCTTACATATGTTTAACGGATGCAGGAGCTGCACAAGGCAATGAAGGGCTTGGGAACGAATGA

TACGACTCTCATTAGGATAATAGTCACGCGAACTGAGATCGACATGCAGTATATAAAAGCAGAGTACCAGAAGAAGCATAAGAAATCTC

TTAATGATGCTGTTCATTCGGAGACTTCTGGTGATTATCGGACCTTTCTTCTCTCTCTTCTGGGGCCTGGTCACTAAATGAAGAGTCTACA

CCATACAGCAGGTGTTATTAGTATGGCATCAGTGTTGAAACCATTGTGTGTAAAGCAGGCAGTTTCTATTGCATGCTAGTTAGTGTTTACT

TAGTTGCCGAGTTTGTTGATTTGGAACAGTGT[A/C]TGTACATGACC

CAPS_CONTIG.7541 P04 125.86 GA GAAGGCTACAACTGAAGTAAATTTCTTGAAGGTGGCAGCAACTTCATTGAAGGCAGAATT[G/A]GAAAAGGAAAAATCAGAACTAGCC

GTGATCCAACAGAGAGAAGGAATGGCATCTGTTGCT

75

CAPS_CONTIG.7773 P04 131.215 GA GAAACGTATGAGAATCTACGAGTTAGGTTCATTGCCTCCTTTTCTACTTGTGTTTGCCGG[G/A]AATATAGCTCCGGTTGATCACAGATGG

AATCAACATGGACTTGGAGGAGACAATTTTCGC

CAPS_CONTIG.7672 P04 132.817 AG GAACTTCTCTCCATTAAAGCAGTTGTTCTCTGATCTTCATATGGGAAGCCACACACATCT[A/G]CGTGCCTTCTCCTCGGCACCAGTTATC

TCTTTGGCAATTGAGAGAGGTTGGAGCGAGTCA

CAPS_CONTIG.9996 P04 133.927 CT TGGAGAACGAGCTTAAGCTGGTCACATTATTCATTAATGAACAATCTCGTTTTGGTTTCC[C/T]GATTATGGTTTTAGCCTTTAGGTACATC

TTTTGTTTGTGCCTGGAATGTTTATCAGTAGA

CAPS_CONTIG.8363 P04 144.06 AT AAAAAAGTATAAGTGTTGATCTGCTACTTACTTCGATATACTCACTAAACTCAGATCTCGAAGTCTCAGCTAAAAAGATGA[A/T]GAAAG

TAGTGCTGAAGTTGGAGTATCTCGATGACAAAGTCAAGCAAAAGGTCATGAAAAAAGTTTCTGTTGTGTACGGG

CAPS_CONTIG.5874 P05 0 GC TGATTTCTCAGTATTTGTACTTGCATCGGATCTTGGTATTGATGCCCGACCCTTTTTGAC[G/C]CGACCCGAAGAAGATACCTGGTATGATT

GCCCTGATCATGATGATGACCACCAAGATTTT

KS26051E10 P05 0 AG TGTGAAAGCTGATAGAGAAGGAGGAAGACCACTCGACATAACTATCACGAAATTGGATGTAAATACCATTACTGCAAATCA[A/G]GGAC

CTGGACGGAACACATTTCTTCCACCTTGTATGTATTATAGTTATTTTGCTTTCGGAGGACCTCAGGGCATTACATCTGCTGAATCATCTGG

TTCTGTACAGG

KS25049K03 P05 3.916 GA GACATGGAGAAGATAAACATTTTCCGTGGCATTTTTAGCAGCTGGATTTTCATAGGCGTC[G/A]TGGTTGCTACAGTTGGTTTCCAAGTTA

TCATCGTCGAGTTCTTAGGCACTTTTGCCAGCA

CAPS_CONTIG.12138 P05 7.286 AG CGAGGACATCGCTCATCTCGAGTGGCTTTCAACGTTCGTGGAGGATTCGTTCTCTTGTGA[A/G]GGTTTGACACTGGGAAAGGAGCATT

GTCGCGTCGACAAGGAGCCATCTGACAGCAAATTC

CAPS_CONTIG.12812 P05 11.274 AA TGGCGATTCCCTTCTTTTTTTATAAACAGGCCAATGATGAGCAAGTGAAGAAAGAGAATG[A/A]ACATATTCATTCCGAACACAATCATC

AGCAAGAGATTTCCGGTAACAAAAAGTTGGCGAT

CAPS_CONTIG.66 P05 15.113 AG TAAAGTAAAGAGTTTCTCTATAACATAAGAAAAGATAATTATCAATCCATACATGATAAGTTGCTACCTAGAACAACAGGCTCTGCACAT

GGCAACATTTTGTACAGTTTTAAGATCTCACTACATTTTTTTTCTTTACACCCTTGTACAGTTACTCTATCTCCACGGCAGGGGCATCAGG

TATGTTTACCATCTGAGCCTCACAGTTAAACCTGCTTATATAGATGTACCTCAAAACTACAATGTACAATGTTACAAACACCACATACATT

TATTTTTAACATGTTCCATCAGCAAGAAAACAAAGACGAGG[A/G]TACTCGTTCTGAGCAAGAAAACAAAGACGAGGATACTCGTTCTA

GCCTCAGTTAGCTGTACAAATTTCCTTCCTACACCATCTAAGAAGCAGCAGAATATGAAGCCAGGACACTGATCCTCCTCTCT

CAPS_CONTIG.9396 P05 31.762 GA CGCTGAAATGGGTATTAAAGATGATCTACTTAGAGGAATTTATCAGTATGGGTTTGAAAA[G/A]CCGTCGGCGATTCAACAACGGGCTGT

TTTGCCGATAATTTCGGGCCGTGATGTGATTGCG

CAPS_CONTIG.10383 P05 32.797 CT AAGAGGAGAAAGGGCATATGACATATTCTCAAGGCTCTTAAAGGAGAGAATTATATGTAT[C/T]AATGGTCCAATTAATGATGCCACTTCT

CATGTTGTTGTTGCTCAGCTTCTTTATCTTGAA

76

CAPS_CONTIG.2744 P05 40.094 GA TTGAACTTCAATGTTATCTGATATCAGTTTGGTGACTGAGTTGACAATGGCTAATGATGC[G/A]TACTCCAATATGGACAGATTTTCTTTCA

TTAGTTTTGTAACTTAAAAGGTGGATCCTTGG

KS20005B11 P05 43.487 GA ATATTGTTTGTGGATATACTAGTGACATGGAAGTTCTGTTTGAATAGATGTTCACTGACC[G/A]ATATGTACCTTGAGCCTTTCCCTTCCCT

TTTTGGTGATTTGCATGCATGTACATATAGTG

CAPS_CONTIG.5102 P05 49.128 AC TGAAAAGCCAGCAGTTTACCGCGAATTCATGTTCAATGACTATATGGGAAGATTCTTTTC[A/C]AAGGAGTTGGATGGGAAGACACTGA

CAAATTACTACAGGATTTCAAATTAAAGATCAGAA

ACRI.CA847609 P05 52.926 CT AGTTTTGTCTGCTAATATCAACCTCCAGCAAAAATCTGATGTTAAACCTTCAGTAAACGT[C/T]GTCTCCAAGAGCCAGAACCATGGGTT

TGTGGCACCTCAAACTCTTAACACTTCAGGACTC

CAPS_CONTIG.8775 P05 54.897 AG AAGAATTCCTGATTTTACCCTTCCAACATCATGCGACCAAAATAGGTTGTGTCATTATTC[A/G]TACTTCTATGCTGATGGTACTTTGGCTG

AGGGTAATCTCGTCCGTGAAAAAATTACATTT

CAPS_CONTIG.6033 P05 62.332 AG AGGGCTCGAATAGCAAGCCCTTAACGGGTGTTGTTTTCGAGCCCTTTGAAGAGGTGAAGA[A/G]AGAGCTTATGCTTGTGCCTACTGGT

CCTCAAAAATCTCTCGCTAGACAAAAGTATACTGA

CAPS_CONTIG.3123 P05 62.771 CG GCAGAGCAAGGTGAACATCACCCCACCTGCATTACAGCTTCCTGGTAGTAGGCTAAAGAC[C/G]TCTTTGAATGCTCGGGACTTGGACT

TGGACATGGATATGCTTGGCTTGGAAAGCATCCGC

CAPS_CONTIG.2117 P05 65.765 AT ATGTCTTGATCGTGTGAAGCTATACCATCTTCTGCTGTACATTGTTATATGCTACATGGT[A/T]CAAACAACAGCCCCGGACAAAGAAAGA

TTGCCATGTTAGCAAGGCTCTTTCAGGTCCAAG

CAPS_CONTIG.12874 P05 68.22 AG GAGGAGGATGGTGTTGCTTGTGTGGAATTCATTGCAGGCAAAGAGGGTCATGTGGACTAC[A/G]ATTTGGTTCCTGGTGTTTGTTACACT

CACCCAGAGGTTGCTTCCGTTGGGAAAACTGAAG

KS24034F11 P05 68.841 AT TGATGCAGTTGTCTCTAGTATCAAGAAAGAGACCACATACAACTACACCGTGCAATCTAA[A/T]CTGAAAACGTCCCCAAGACATGATCT

GATGATGATCTTCACTTGCAAAGTATGTGAAACC

CAPS_CONTIG.8295 P05 70.956 AC ATACTTGAGGCGTTATTTCGGATTCAAGCATGATTTTCTTGGCATAGTTGCAGCTGTGAT[A/C]GTCGCGTTGCCTGTTATGTTTGCCTTGA

CATTTGCATTGTCCATTAAGGCATTCAACTTC

CAPS_CONTIG.3810 P05 73.288 AT GGTATTGAGACTTCAAGCTGGACACAAATACTGTCTCTTGGGTAAGCT[A/T]TCATCAGAGGTTGGATGGAACCATTACGACACTATCAA

GG

CAPS_CONTIG.12684 P05 74.585 CT ATCCTCTTTTGACATGCCTGGGTTCAAGATGTCCGAGATGAAGTACAAGGACTAAACTCG[C/T]AGTATGCATCACAACACTGCTCTCCA

TTTCTCGGTTTGTTTCTTTTGTTTGGATGGAAGA

CAPS_CONTIG.10840 P05 76.638 GT GCTTCCTCAGGCTGTTGAACGAGAAGATAGTTTATGTCGGCAACTTCCTTTTTTTTTTTT[G/T]TTGGTCATTACCAGGCAAAGAGTTTGT

GCTGTTTTTGTATTGAATTTATAGTTGTAGTTT

77

KS12044C02 P05 82.114 AG TTCTCTAGCGACTACTTTTGCTGCTTCTACCGAGGTGGAAGATACTTATGAGCAACCTCA[A/G]GAATCTAAAGTACCAGAAGCGAATAG

AAGAGCTATGGAGAAAGAAACCACATCATACAAC

CAPS_CONTIG.1638 P05 91.698 CG GTAGCTAGAATTGAGGACAGATTAGTCATTCCACCTGGATTCCCTGGCCTTTTTCGACTACCAACAGATTTTCAACTCGAAGCAACTACA

ACAGC[C/G]AACTACCAAGGTTTTCCGTCGAGGTTCAATTCAGCGGACCATTCTCATGAAACTGGCTCATTCC

CAPS_CONTIG.1150 P05 95.453 GT AGCTATGGCGATAAGGAATCGAGTTCAGTTAGCTTCTAATGAGAAGTATTATAATTCTCC[G/T]GCGGAGGCACTTCGGAAGCTTCTAGA

ATCTCCCGGTATTCATCAAGGTCCAGCTTGTTTT

CAPS_CONTIG.6847 P06 1.888 AG CAGTGAAGATTTGCTTCTATCAATCGAGAAATAGAAACTACTGCTGCTGTTTAGATCATA[A/G]TCACCTACCTAAGCATCAGAATTCAGA

ACTGTTGGGCGAAAAATCAACCTTTACGCTTGC

CAPS_CONTIG.2397 P06 3.23 AT ATGTGCAAGTAGGTGTTGAGGCCACTGGTCAATGTGATTCTCATCCGGACGAGAAATTTG[A/T]TCCTTCTGCACTTCCAGTTGTTAGTT

GCATCACCTTTAAGGACATTGTCGGCACAAATGT

CAPS_CONTIG.5585 P06 5.227 CA AGATCTGGAATACGAGTCATTTTTAGCGACAGGAAGACCTGATTTTGAGATAGTATGGCC[C/A]AGTGATGAGTGGAATGCTATTGCTGT

GAATTATACTTCAGGTACAACGTCGAGTCCAAAG

CAPS_CONTIG.12327 P06 12.526 GA ACATCGATTGCATTCTCCAATCTATTTGCCCCCTTTTTCTTTTATTCTGTTGTGGTGAAT[G/A]AGTGATGAAGTTGTATTGCTATTGTTACG

ACAGGTTTTTTGTTCAATTTTCTCACTTTTT

CAPS_CONTIG.599 P06 16.798 AT GGTTCTGCCATTACTGGTCCTATTGGAAAAGAGTGTGCTGATCTATGGCCCAGGATTGCAAGTGCTGCCAACGCCATCGTCTAAGTTTTT

AAATTTGTGTTTTGCTGATAGTTTTCGTTTTGAATTTTTTGGATCTCTGAGTTACCTTTGTCTTGGTAGGAACTATTACTGCA[A/T]CTGGC

TATGAGAATTGTGCTGTACTGCAAAGTTTTTCATCTATGTAGAAGTGCATTACTATTTCAGTTTCTTCATGGTGTTCATGTCAGTTGTTGC

AAATCTGAATTATCTTCTTACAATGTCCTAACACAGACATCATATCGCGGGATTTGAACCTCTATTACCATTTCCTAGCAATGTTGTACAGT

TCCCAGAAACCATTTTTAGATTGCGATAGAGTTACTCGATATGGTATGGATAGCGTACATTTCATTTACCCTCTCCGGACCCCATCAGGTG

GGAATTCACTGGGTAT

KS21049K18 P06 16.87 AG TGCACGATCTGTTTGGCGACCTTTACACAGTCCCAACAGAATGGCATTGTAGGTTATAGC[A/G]TTGGGTCTGACATCCAATCCTTCTAA

GTCATGAAAGAACTTAATGGCTTCGTCGACTTTT

KS01057F06 P06 23.518 CT CGAGTTTCGATTTGTGAAATGGAGGTGGATTCGAGTTCGGTTTGAGGTTTTCTGTCGAGG[C/T]TCTCCATTTGGGTATTTTGGTCTTCTT

TATTACCAACGACGATAACAAGTTCTATTGAGC

CAPS_CONTIG.1354 P06 31.167 CT TAATCTGATAGTATGGCGTGTTTTACATGTGGTTTTGACAGTGTACTGTTTTCATTTAGA[C/T]TATGGGACCTATTACCATGTTATGGAATT

GAATTTGAATGGAAAACTGAGATTTAAAATT

CAPS_CONTIG.11132 P06 46.974 AG TTTGGAGAAATGCTCTTTGTTCCTGAATCGGATAGTCTAAAGGAATGCCCTTCACCAGAA[A/G]AACTAAAACATCGTATTATCATTTCAA

CCAAACCTCCAAAAGAGTACCTTGAAGCCAGTG

78

CAPS_CONTIG.12564 P06 48.781 AT AGGGGTGACTGGAAGGAATTGGAATTTAAAGAGTACAACTTC[A/T]GTGCTAAAGGTCTGCCAGTTGAAGGTGGCCATCTTCATCCATT

GCTCAAGG

CAPS_CONTIG.2137 P06 49.105 GT GAAGACCTGGTATTGGTGCTACTCACTCATCAAGGTTCATTCCTCTGAAGTAATATGGAT[G/T]TTAGGTTATCTTGTGCGCTGTCTGATG

AAGGTCTTGGATTATGTAAGAGTTAAGCTTGGA

KS17031A12 P06 52.616 CT GACAAGCTTTTTCTTTGGAGGCTTACTGGAAAAGTTCCTAACTTAAAAGTTCATCTGTTG[C/T]GAGCTTACCTACTTATATAGAAGAATA

AAGCAATTAATTATAAGTCAAACGCATAAATGT

CAPS_CONTIG.9772 P06 57.221 CT ATAGGCTGCTACCAGAGAGGAGTGCAGAAGAATCAGATTGCCCGATTTCATCCCCCAGTA[C/T]GTCTACAGTACCTAGAGATACTGTTA

AAAGCAAGCAACCTAGGAGAACCCTCAATGTGTC

CAPS_CONTIG.2766 P06 59.238 CT GACATAGCAATTCCATGGATGGGTCTTTTGATACGACGTCGTTTGAGTCTGAATCGGTTT[C/T]GGTTAAGAAGGCTATGGCTCCTGATAA

GCTTGCTGAGCTGTCATTGATTGATCCTAAAAG

CAPS_CONTIG.3229 P06 60.673 CT CCTAGAAGAGTATGAGAAGGTAATGGAAGAGAAGAGGAAAGCCTTATTGGCTCTAAAGCC[C/T]GAGGAAAGAAAGGTCAATTTGGAC

AAAGAGTTTGCATCAATGCAACTTTTATCAAATAAG

CAPS_CONTIG.5548 P06 66.126 GC CAAGCATAACCAATTTCCACTCTTACCGAGTCAACTACACCCAATGCTCTTCCCTACTCG[G/C]ACAACGCATCCACGCGCCACCACATG

TCGTCTGGTCCGCCGTCCGCCGTTTCGAAAAGCC

CAPS_CONTIG.10712 P06 70.167 AG AGATTGAAATAGTGTTGGGCAAGACCGAGAA[A/G]TTTGATGAGTTAATGGCTGCAGAAGCAGAGCAAAATGGGGAAAATGAGGAGC

AGAACTGATTATTACCACATCTGCTCTCTTTCCTGATGATTGAAGTTATCCCAAGCTATACTGCTTTCAGCTGTTGGGTTCTCTATGGTCTT

TGATTAGATCTGTTGGAAAA

KS22013D03 P06 73.863 GT TTGAAGATCGTACGTCTCGAAGGATTCAGATATGGTTATATTTACTGCAATAATAGAGTG[G/T]CGGTGAAAATTCTGCGCACCAAGAAA

GTTGCAAGGCTCAACGGAATTTTTTGACCTCTCA

CAPS_CONTIG.192 P06 74.413 CT TGTTGTAAATTGCAGCTTGTTTAATCCGACACCCTCGTTGTCTGCAATGATTGTGAACCA[C/T]TACAAGCTTCGTGGAAACATCGTTAG

CTACAATCTAGGTGGAATGGGTTGCAGTGCCGGT

KS20039B04 P06 81.292 CT CAAAGAATTGTGTTTCTTGTAATGTTAACAAAAAAGATCTTCTCACCTTCTGTGTTTCTC[C/T]ATCCGTTTCTTCTACTGTTTGTTGCTTG

CTTCAGCTCAATGCCACCTCAGCACGTCCATG

KS07045D12 P06 84.469 AT GGCAGAGCCAGTTACAAAGCCGGCAACAGAGTCAGTACCAGTGGAAGAATCAGGGCCAGT[A/T]ACAGAGAAAACAGAGGAGAAAC

TGATTCCATCGGAAAAGGAAGAAAATCCGGCTCCGGCA

CAPS_CONTIG.5781 P06 87.937 AG ACTTGGCGGACCATAACTTCTGATATTAGTTGCTCTGCCAAGAACCAATACGAGGGAGTT[A/G]CAGAGCCAAACTTACAGATTGTAGG

TTTATGTTTGTTCATACAGTTATAGGTACTTTCCA

79

CAPS_CONTIG.4952 P06 96.175 AT ATTCTTATTGGGAGGTAAATAAATAACTACTCAGCTATTTATGGTCCTCAATATCTTTCA[A/T]ATGAAAACTTTATGTTGGAACCTGACGT

GGGAATGTCAAGTAAACGTTCCTTCTCCTCTT

KS21063P23 P06 97.321 GA ATCACTAGCAGGCCGTCATCTTTACTTGCACTGGGTGTATTCTCGATTAGCTGTGCTCTC[G/A]AGCATCTACAGTGGCATCAATCTTCGA

TGTTTGAAGAACCATAAAAAGGATATGAATATC

KS15031H07 P06 101.806 AG GATACTTGTAGTGTTCAAACAGCTAGACCGCAACTATTACATCAGGAATATGTTGCCTTC[A/G]ATCGACACAAGTACAAGATAACTCTG

CTTGACAACATTGAAGCAAACAGAAAGACACCAC

CAPS_CONTIG.7761 P06 103.102 CT CTTTTCCATTCAATCGACAAAGGCAATGACAATATTTGTGCACTGATGTTATTCAAGAGA[C/T]CTTCAATGTTACAAAGTTGTGTAAGAA

ACTGTACTATACCATCAGAAATTCGTCGACGAG

CAPS_CONTIG.1668 P06 104.727 CT AGGCACCTTGTTTTCATCGCCACATTTACAATAAAAGACGCTCACGCTATACTCTCCCCA[C/T]TACTGATCCATCTTCCTCCTTTACACA

GCTGGCCACTTTACTCCGTTCAATGGCCACTCT

CAPS_CONTIG.11244 P06 106.056 AG AAAGATCATAATATAGCTAAAAGAGAAAGAAAGAAAGAAGAGTACTACTAAAATGGAAACACCAAGGGCTTTTGCAATCCTTGTTCTT

AGACTTTTTACTATGTTGTTGTGTGCAGCTTCAGTGCCACTCATGGTTTCTAACAGCTTCGAACTTAGTGGAGGTGACAA[A/G]ACCAAA

TACAGTGATATTAAGGCCTACAGGT

CAPS_CONTIG.12387 P06 109.388 AT TTTTGGCACTTGGCTGGGTAGACAGTTCAAATGAGCAAATTATATAAGGATGATGTAAAA[A/T]TTCCAAATTCTACCATCTGAAAACAC

TTGATTCTAAAGTATTGAATTTCAAATTTAGCTT

CAPS_CONTIG.11090 P06 110.629 GA TAGCAGCCGCCCACTTGAATCACCAGGAACAAGCAGGGGCAATAGTTTGTGGAGTAGAAC[G/A]GGTGCTCTGCAGACTCAAACCCTT

TCTGCAGCTTCCTCACTTGGACTCTTCTCTGGGTTG

CAPS_CONTIG.8047 P06 111.816 AC TGCATTATTCCCCGTATTTAGTCCTCTGGGTCCCTGTACATTACAATCATACGATGACAT[A/C]AGCTCGTTAATCATCTTTTGCCCGTCTTC

AGGAACTCCTATACCAGATAGATCAAAGGAA

CAPS_CONTIG.5254 P06 114.667 CT GAACAACCAAAGTGGAAGTCGTCATCATCATCATGAATCCCACCAGGTGATACCTTCGTC[C/T]ATGGTGGTTTCCACCACCACGGACTT

GGCCTCTCAGTTGGGCTTCCAGAGGCCGAATTGT

CAPS_CONTIG.12720 P06 120.984 CT ATTTGAGCTTTCTGGTATTCCCCCTGCTCCTCGAGGGGTGCCCCAGATCACGGTTTGCTT[C/T]GACATTGATGCAAATGGTATCTTGAAC

GTCTCTGCTGAGGACAAGACCACTGGACAGAAG

CAPS_CONTIG.10400 P06 121.922 CT CAGCTGACAATGACCCAGTTTATCCAGTTAAAGCAAGTTGAAGAAGGTGCTGGTAAGGCTCCACCACCTGTGCTAGTCCTCCATGGAC

ACTA[C/T]GGTGGATGTGTTGGAGATCTTCCCAGTTATGATGCTTTCACACTTGGGGGACCTTATTCAGTAAGGGGCTACAATATGGGAG

AGATTGGTGCCGCTAGAAATATT

CAPS_CONTIG.771 P06 123.749 GA GTACTAGTTCCTGCATTTTCTCCAAAAGTTACTACTAATACAAGAATTTCACTTCAACGA[G/A]TTGGAATGGTGAGAAATTCCAAATTGT

TTAATTCATTTGTTGCTTCAGTTCAGCCCCTTG

80

CAPS_CONTIG.11261 P06 131.702 CT GATGTTTCAGTCAACTGCTTAATTAGGACCTTTGACTGTTGTGGTTATGACTGGGCCCCT[C/T]GCCAAGATGGTTTTGGACAACAGAGC

TCTTACCACACTTGCTGCTATTTTGATCTACTTG

CAPS_CONTIG.10984 P07 0.783 GC CATCAACAATCTTGCCCATGCATTGATGCTGAAAGGAGCTTTGAACACGGTCATCTTGCC[G/C]GTTATGGATGAATTGATTAAAGCAATA

TGTGAGATGGCCACAACACATTCTTCTGTCCCT

CAPS_CONTIG.3817 P07 1.659 CT TGCTACGCCTTCACCAAAAGCTCCTGCTTCTCCACCTCCTCCTCCCAAAGAAGAGGTTGCCGAGAAACCTGTCACCCCATCAGAGCCA

AAAGTTTCTAAACCCAGTGCGCCTC[C/T]GGCAGATCGCATTTTTGCTAGTCCGCTGGCTAGGAAAATTGCGGAAGATCATAAT

CAPS_CONTIG.1091 P07 4.402 CT GGAAAATCCGAATTCTTATATTCATAGTAATATAGCGGGACTAGTTACGTTGCTCGAGGT[C/T]TGCAAAAATGTACCTATACAACCCGCG

GTTGTATGGGCGAGCTCTAGTTCTGTTTACGGG

CAPS_CONTIG.3597 P07 6.827 GC GGACGAATTATAGTGAACGACCTCAAAGCTAAGGAGCGCGTAATGAAACTGCTGAACCAC[G/C]AGAATGCAGAAGTCACCAAAAACG

CTTTGCTCTGTATCCAAAGGCTTTTCCTAGGTGCCA

CAPS_CONTIG.11582 P07 7.524 CT CTCAGGGTAGTGGTGGCTTCGTGGGTGGCAGGCCTAGTGCCCTCTTGCAAGGTAGTGGTG[C/T]TCCTCCTGCTCGCCCATTGAGCTATG

GTTTTGGCATGGAGCCTGCATCACAGGTTCACGG

CAPS_CONTIG.4411 P07 17.55 GA CATAGGTAAAAATGGCTGGAAATGGAGTATTTGCTGAAATAATTGATGGAGAAGTGTTCA[G/A]ATATTATTGTGAAGGTGAATGGAAAA

AATCAACTTCTGGAAAATCTGTTGCTATTGTTAA

CAPS_CONTIG.9705 P07 31.698 AT TTTTTCTACAAGCTCACACACAATTCTCCATAGATCAACATCTCCAAATCGCGTGAATTTGTTTAATAACTCAAGTTCAGGTGCTTC[A/T]

TCTATAAGGTTTTCACTTGACCGGTCGACGTCACCGAACCGGTCTATCAACCACGTAGTAGTGCAGCAGCAGAACCATAGGATTCATCG

TCATCAAAATCATCATCATCAGAATCAGAAGAAGTCGTGTTTGTGTTCTCCGACTAC

KS26033B03 P07 38.309 GA ATGTGCTTTGCAAGGCGACATTGAACAGGCTCAAAATTATGTGGTACAAGCACTTTCAAC[G/A]AAACCTCAACATCCAGAAGCTATTC

TCACTGCAGTATACGTGGATCTTTTGCGTGGGAAG

KS01040H01 P07 44.497 GA GATAGACAATCTGGTAAACCATCTAGAAAGATTCACCGGCTTAAAGTGCAAATGCAACAG[G/A]CTGAGTCACCTGAAAAAGTAGGTAT

AAATGGTCGTCCAGTTAAAATGGTACCTACAAGTG

CAPS_CONTIG.2024 P07 46.774 AG CCCTTCTTCAGCCGGATCATTTCGAACGGAGTTGATTGAACCCGTTATTAAACCCATGTT[A/G]GATTTTCTCCGGCAAACTGGGTCTTAC

CTTATGGTGAATTGCTACCCCTTTTTTGCATAC

CAPS_CONTIG.6993 P07 52.237 GA CATCCTAGCAAATCCAGCTGCACTTTTGCCTCAGATATTTGGCCAGGCTTTGTATAACCA[G/A]TCCAAATTCTCTGGCCTCCAATTGTCC

CAAGATTTGGAGGGACAACAACATCCTTCAACG

CAPS_CONTIG.10491 P07 57.259 AT CATATCAGGACTTGAAGTCTCCATCCAGACTAGATCAGCGTGGTGAGCGAATGCCCACCC[A/T]CGAACAATTGCAGCCTCTACTGAAC

CCTTAAACCTGTAGAACCCTTCTCTGGTTCTTGGC

81

CAPS_CONTIG.894 P07 61.154 CT ATGTCGTCAGATGGACCAACCCA[C/T]AATGAGTTTGATTTTGAGTTTCTTGGTAACACAACTGGTGAACCATACACTGTTCAAACCAAT

GTATATGTCAATGGTGTTGGTAACAGGGAACAAAGATTGAACCTTTGGTTCGACCCATCTAAGGATTTCCACTCTTATTCCATCTTGTGG

AACCAACGCCAAGTTGT

CAPS_CONTIG.6321 P07 62.115 GA TCCACCGCCGGCTAGTTCAGCCACTAGTGAAGATTCATCCAATGTTCTTACAAATATGTC[G/A]TTGAAGAGAATGCGTGAAACAAATGC

GGATCTTCATTCAGATGTATGAACTTTTTTCAAC

CAPS_CONTIG.11507 P07 73.041 AT TTTGATGGTCATGGTCCACATGGCCATCTCGTTGCTCGCAAAGTAAGGGATGCACTTCCC[A/T]TGAAGCTAGCGTCATTTTTGCAATCAT

TTGACTCGAAGCACAATGGCTCTACTGTGAATT

CAPS_CONTIG.12824 P07 76.529 GT TGCCCTGTTTGCAAGGCTGAAGTCTCAGAAAAAACCTTGATTCCACTCTATGGACGCGGTGGTCAATCTACAAAACCATCCGAAGGAA

AGGCTCCGAATCTTGGCATAGT[G/T]ATCCCACAAAGGCCCCCTAGTCCAAGGTGTGGTGGTCACTTCTTGTTACCAACTACTGATTCAA

ATCCATCCCAGCTACTTCAACGACGAGGTTATCAACAGCAGTCTCAAACACGTCAACCGGCTTATCAGGGTAGCTACATGTCTTCGCCC

ATGCTCAGCCCTGGTGGTGCGACTGCGAATATGTTACAACACTCCATGATTGGAGAAGTAGCCTATGCAAGAATTTTTGGCAACTCATC

AACAACTATGTATACATATCCAAACTCTTATAATCTAGCAATCAGCAGTAGCCCAAGAATGAGAAGGCAATTATCACAGGCTGATAGATC

ACTTGGCAGAAT

CAPS_CONTIG.443 P07 79.926 CT GACTGGTGGATATGTCAATGAAGTTCTACGGGGTGCTTTCATGCCGAATTGCCAAGCCAC[C/T]AAACTGGAAATCCGGTCATTGGGCAA

TCCTATTCTCATACAGGCACCATCTGAAGAGAAG

CAPS_CONTIG.7593 P07 81.718 CT GTTCCCGCTGCCTGAAGAACCATACTACAAAGATGCTGGTCCTGGAGGTCTAATGTTGAG[C/T]GCTGCTGAAATGGAAAAGCTACGCC

TCAAGCAAGAGGAAGAAACTCGATCCAATTGCTTA

CAPS_CONTIG.9567 P07 89.565 GA GCGTAGTTATTATGGAATGTGGAGCATGTGTGTAAGATGGAGACAGTTCGAAGGAGAAGC[G/A]TTGTAGGATCATAGCCAGAGCCATC

TTTGCTTCTATCATGGCGAAATTTTGACCAATGCA

CAPS_CONTIG.8096 P07 101.427 AG TGAAGCCAGTTGTATCAACCAACGTAACAATGCCCGCTGCAGTGGCCAAGGTGTCTCAAC[A/G]ATCTGGGCCAGCACCAAAAAAAGA

TACTGGAAATAATGAGGCTTCTCACGAGGTGTCAGC

CAPS_CONTIG.7411 P07 104.18 CT AGGCTTATTTATGCTGGAAAGCAGCTAGCGGATGA[C/T]AAGACAGCTAAGGATTACAATATTGAAGGCGGTTCTGTTCTTCATCTTGTT

CTTGCTTTGAGGGGTGGTAGTCTTTAGATTGCACCAAATTTGGTTTAATATGTCCAACCATTATCCATGAATTTATCATGACAGTTTCCTTT

TTTTGTTTTCTCTTTACCTTTTCTAATGTAATTTTGGAAGAACCATGAAAACCTGTTAAAGCTGAGATTGGATTGATTTCCCCC

CAPS_CONTIG.898 P08 3.031 GT GCTGTAGGTTCATTAATAGTAAACTGCAGAACAACTCAAACAAGTCCTGTAGGGGCAGCC[G/T]ATGAGAATAAAGATAGCTGCTTAAC

TTGTGGACGAGTTCAGATATGACTATCTAGGTTTT

CAPS_CONTIG.5050 P08 9.18 AG GTCTTGGATTGACAATAACACTGTTTGAAAAAGCCAGCCGAAAGGATGCCTTTTCAACAC[A/G]GAGATGCAGGTATTCAATGGTTCTC

TTGGCAAGGTCCACTTGATTTTATGTGGTTCAAAC

82

ANOK.CO907546 P08 10.686 CT AGCCAAGCTGGCGTCGACCAAAAGGTATTGATTCTAGAGTTAGAAGAAAGTTCAAGGGATGTGTATTGATGCCGAACATTGGATACGG

GTCTGACAAGAAGA[C/T]CCGCCACTATCTTCCCAATGGCTTCAAGAAGTTTGTTGTGCACAATGCAAGTGAGCTTGAGGTTCTAATGAT

GCACAACAG

KS19059D11 P08 24.115 CT CATGCAGAGTGGTAGAGCTACAGAAAAGACTGATGTGTATAGTTTTGGAGTTCTGGTTCT[C/T]GAAGTAATAAGTGGGAAACGGCCCA

CTGATGCATCATTTATTGAGAAGGGCCTCAACATT

CAPS_CONTIG.835 P08 38.781 CT CGGGAACCCGTGGGCATTCCTGTGTTAGATTTTGTTTCGACAACTTTATAAATTGTTGTT[C/T]AGAGTGTAAATTTAGATGTTCTTCTGG

AGTTGTATGCCCTGGGTTTTTGTTGAACTTGTT

KS15049B04 P08 41.179 CT CCTAGCAATGCGTTGGGAAAGCCGATGAAAAGGCATACTTTGGATAAACACAATACCAGGCCC[C/T]GTTAGGACAGCAGTCACCAGAT

TATCATTC

CAPS_CONTIG.8337 P08 43.372 AT TCCATTCAAAAAAACAAGAAGGGAGAAGGGTGACAAGAGGGCCATATACAATACAGATAC[A/T]CTACAACATTATAGCAATAAGTTTT

CCGAAAATAACGGAACAAATTTGCAAGAGCCACCA

CAPS_CONTIG.1476 P08 50.278 CG AGAAAGTGCCATTTTTAAGTGACGATTTGGACTTGGAGTGCGAGGGCAAGGACAAATACAAGTGTGGTTCTAATGTGTTCTGGAAATG

GTGAAGACTTTGTATTCTTAAGCA[C/G]AGTCCTTTCACAAAATGTATCTATTGTGACAGTGAGAAGTAATTTGTTTGATGTTCGTTAAAC

ATCGCATTGATTGCTTTAATTCGTCCATGTTACACTATATATCTGCTAACAATTCTCCAAACTCATACAAGCATTAATGTTATATCTGAAATC

TTCAGCTT

ANOK.CO911837 P09 0.619 AC CAAAGAGATTCAACGATGCAGGAGGTGTGTCAGGTGTGCATGTAGTGGGGCATGCAACCATGCATGTGCATAACGAGGGCGGGCCAAT

GAGGACAGATA[A/C]TAATCCAGAAAATGGAAGAGAGAGATTGAAAAGACATAGAGTTGAAGTGGCAGGACATGTATGGATACCAGAA

ATTTGGGGACAAGAAGAATTATT

CAPS_CONTIG.167 P09 16.655 GC TACTCTTGAAAGTGGCAACCCTTCAATTCCCAACAGGATCACAGAATGCAGATCATATCC[G/C]TTATACAGACTTGTGAGGAAGGAACT

TGGAACTGAACTGTTGACAGGTGAAAGAGTCCGA

CAPS_CONTIG.4086 P09 17.879 CT GAATTGAGTTAGTTGCTCTGCAACATTTATCCTAAACTTGCGCGGACAAATTACTCTCTG[C/T]TTCTGGACTAACGCGAGATGTCAAGT

AAATTAGTTTTCGTAATGTATGTTCTGAAACTGC

CAPS_CONTIG.134 P09 23.799 CT ATTGTTATTCCTCTATATCACTGTCCTTACTGTAATTGGCTACAAGAGCCAAAGTGCCAC[C/T]GACCAATGTGGTGGTGTTGGCATTCTT

GGAATTGCTTGGGCCTTTGGGGGTATGATATTC

CAPS_CONTIG.12056 P09 33.107 CT AGGTATGGCAGATGGTCACGGTTCATCTAGGTCACCGGCAAGTCCGAATGGAGGTGGTAGTCATGAGAGTGGTGGGGACCAGAGTCCT

AGGTCTAATGTACGTGAACAGGACAGGTTTCTACCAATTGCTAA[C/T]ATTAGTCGAATCATGAAGAAGGCACTCCCTGCTAATGGAAAA

ATTGCTAAGGATGCTAAGGAGACTGTTCAGGAATGTGTCTCTGAGTTCATTAGTTTCATCACCAGCGAG

83

CAPS_CONTIG.3893 P09 33.107 CT TGGGGACCAGAGTCCTAGGTCTAATGTACGTGAACAGGACAGGTTTCTACCAATTGCTAA[C/T]ATTAGTCGAATCATGAAGAAGGCAC

TCCCTGCTAATGGAAAAATTGCTAAGGATGCTAAG

CAPS_CONTIG.5964 P09 37.68 AG TGGCCGAAGGATTTGCAGTGAATGTGGAAAGAACTTCAATGTGGCATCTATTGATGTCGC[A/G]GGTGAAAATGGGGCTCCTAGAATCA

CCATGGCTCCACTTAATCCTCCCACACAGTGTATA

CAPS_CONTIG.10109 P09 47.206 AT GCTTATTTCGAATTAGCTTCGGCAACAATAGTTATGGTCCTTTACCTTTGGCAGCTCTAT[A/T]TGATAGATATTGAGTTTTGATATGACGA

AACATTTATTACTGAGCATTGAGTTTTATCTG

KS26024E07 P09 47.957 CT AGCACAATATGTTGTCACAAAGTGGCATCATTTGCAGATTCCAAAAATACAAGTTGCAGG[C/T]TATTATAGAATTATCATGCAGAAACA

AAAACACAGTAAACCAAATAGAAGGCGGCAATAG

CAPS_CONTIG.2383 P09 55.192 AG TATCTGTTTAATCCTGGTGACCTGGACGACTGCATGAACAAACTAGTGCCACTTTTATGC[A/G]ATAGTGAATTGAGAGAAACCATGGGG

AAAGCTGCACGCATCGAAATGGAGAAATACAGCT

CAPS_CONTIG.5919 P09 58.533 CT GAGATGTATTTCACCAAGCTGCTAAGAGCTTAAAAAGCTCTTTCTACTTGATGATTCGTG[C/T]TTTGCTTCTCCCCAAGTGTAGAATGTA

GATTAGGATGCAAAAATTAACTTATGCAGATTT

CAPS_CONTIG.9017 P09 58.533 AG GGATGGAAGAAGGGGACTAAAATAACATTTCCAGAGAAAGGAAACGAGCAACGAGGCATAATTCCATCGGACCTCGTCTTCATAATTG

ATGAGAAGCCGCATGGTGTCTTTAAGAGAGACGGCAATGACCTCATCATCACCCAGAAAATCTCCTTGGTAGAGGCTCTTACTGGATAC

ACTGCACAGATAACAACGCTTGATGGACGGGTTCTAACT[A/G]TACCAATTAATTCAGTCATTAGTCCAAATTATGAAGAAGTTATCAAA

GGAGAAGGTATGCCCATTCCCAAGGAACCTAGCAGAAAAGGAAACTTGAGAGTAAAGTTTAACATCAAGTTCCCCAGCAAACTTACTT

CTGAGCAGAAAGCTGGCATTAAGAGATACTTGACATGATGAATGAACATTAGCT

CAPS_CONTIG.6080 P09 59.142 AT AGCTTAAAACCAGAAGATTACACCGGAGCACGAGGATTAAAGTTGTACATTTTACAATGT[A/T]TTCAGAAAATCTGTTCATAGGAGATT

TAGTCGCCTCTGGATTGTCCGGTGGTATTGCCCT

CAPS_CONTIG.3479 P09 60.744 GA ACCAGGGGGACCTCCCAACATGAGGAATGCACCACCTCCCAACATGGGTGGCATGCAGCA[G/A]CCAAACATGGGTGGGATACACCGG

CAGCAAGGCATTGGGGGGCCACCCCATGCAGGTGGG

CAPS_CONTIG.1539 P09 60.883 GT AGAAGAACAGCTGGAGAAGGCTTTGAAGGGAGCTGATGTTGTCATTATTCCGGCTGGTGT[G/T]CCACGAAAGCCTGGTATGACCCGTG

ATGATTTGTTCAACATTAATGCTGGTATTGTTAAA

CAPS_CONTIG.4367 P09 70.713 AG GGGAGTTAAAGCTGTAGTTGCTAAGAGCTTCGAGAGGATTCACCGTAGCAACTTGGTAGGAATGGGAATTGTGCCTCTATGTTTCAAGG

CTGGTGAGGATGCAGATTCACTTGGATTGACAGGTCATGAGCGATTTACCATTGACCTCCCAGACAAAATTAGTGAGATCCGCCCAGGA

CAAGATGTTACTGTACGAACAGACAC[A/G]GGAAAATCTTTCACATGCGTAGTGCGCTTCGACACTGAGGT

CAPS_CONTIG.1347 P09 72.648 CT ATGACCACGCTATGTGGATCGAAAAGAAAGAAACATCTGGTCAAGATGTCCATGTTTCAT[C/T]GGGGCTCCATGTAAATGAGGAAGAG

AGAGGATCTCTTACACGCACCAATCAAGGGGTTTT

84

CAPS_CONTIG.11818 P09 73.238 GT GCAAAAAGAGTACTAGAAACCAAAGCTTTAAATTCTCAGGATGATTGGCAAAAAGATTAT[G/T]CAATTGAATTGGATTTTCCTGTTGTC

CAAGTAGTTGAGACCAACTTTAATGATGTTCCTG

CAPS_CONTIG.12673 P09 74.705 CT GGTCACTATAAATCCCATTTCCAATATCACCAGCAACAAATTTAGTCCAAGAAATGCCCT[C/T]GAAGTTCCACAAAATCATAACTTTAAC

ACTTCTCTAACACTATCAAGAACACCAAAAGAA

CAPS_CONTIG.6084 P09 87.741 CT AAAAGATGCTGCAATGGGTAAAAAGAGTAAGATCACCAGAGATAGAGACCGTGATGTCAG[C/T]GAAAAAGTGGCTCTTGGGATGGCT

TCTACTGGCACATCAAGAGGAGAGGTCATGTATGAT

CAPS_CONTIG.11337 P09 93.018 GA TTGCCAATTAGGCCATCAAAACAAATTGCAACATCAAAATCAACCAATAAGTTTGTAGTC[G/A]TCAAGGCTTCTGGTTCTTCTTCAATG

AAAGAAAAAGCAGTGGCAGGATTGTCAGCAGGTT

CAPS_CONTIG.7156 P09 100.715 AG AGGTGGGAGCAGCGCTGTCGATGGTCTACATATCGGGAGCGCCGGT[A/G]ATGTTTGTGGGATGTGGTCAGTCCTACACAGACTTGAAG

AAGCTGAATGTCAAGTCCATAGTGAAGACACTCCTCAAATGAATGAGAGCACACAATCTCTCTCTTATCTTTTAATATGTTTGTTTAAGA

AAGTGTGGAAACACTTTTGTGTGTTGCTGCTGCACTTCTG

KS10118F02 P10 0.78 CG CCTGCACCTGCTCCGACCTCAGATGCCTCAGTATTCGTACCAACCGTTTTCGCTTCTCTTGTAGCTCTTGCATTTGAACTTCTCTTCTAGC

TTGTGTGAACATCGACTAATGAAATATAGCTCTTTGTTTGGTCCAACTATATAAGTAGTTTTTTTTGTTTGTTTGTTCGTTTATTTCAACT[C

/G]AGTGTGTTTAGATCATTGAGATTAGAAGGACATTGAGGTTC

CAPS_CONTIG.3147 P10 2.08 AG ATTTGTGCGAGGAAGAGAAGTAGAAGAAGAAAAATGGACGCAGGTGTTGTAGCTGCTACT[A/G]TTCCTGCTGATGGAAGCCTAGAGA

GTAAGGTTCATACTGATGTTATGCTGTTCAACCGCT

CAPS_CONTIG.10411 P10 7.505 AG GCAGTGAAATATGCAGGGCCAATGGATGTAGCAAGACACGTTCTTCGATCTGAAGGAGGC[A/G]TGACAGGTCTCTTCAAGGGCTTGTT

TCCCACCCTGGCACGTGAAGTACCCGGAAATGCTG

CAPS_CONTIG.2441 P10 8.854 CA TATCTAATAACATGCTTGAGAAGCTCTTCCCTTCCTCTGAAGCTCAGTAACTGGTTCTCC[C/A]GAATTCTTGGTTGGTTTACATCTCCTTA

TAAATTCATTTTAACGATAGTGATCCTCATCA

CAPS_CONTIG.6621 P10 12.222 CT AAGTTGGATCAAAAATGATTAGTAAAGAGGAACTGACGCTGTTGCTCGACGGCGTTGATG[C/T]TGATGGAGATGGATGTATTAGCTTAG

ATGAATTCAGTGTTGTCGTCTCCGCTTTTGGAGT

KS20034F04 P10 12.773 GT CAATTGGTGATCGTGGTGAACTCAATGTTCTTATCAATGCATCAAACGGGAAACCTGTTA[G/T]CAAGGGGCGTAAAGTTTAAAAGGGA

ATTCATTCATTTAACAATAACAGTAATAAACATTG

CAPS_CONTIG.4846 P10 15.802 CT GCCCTTTTGCTGGAGCTTCCAGACCCGATGATGCAACTAATAAACAACAGGAGAGCAAGC[C/T]TAAACAAGAGTCTGGAGAAACTGC

AACTGTGTCCCCTAAGTGCCCCTTTGGATATGGTTC

CAPS_CONTIG.4456 P10 17.113 AT CCTTGCAAGATTAAGTGTGCTGACTTGTTCATTTCTTATGAGGAGCAAGGTAATGTTGAC[A/T]TTAGACGTTTAGCTGCCTCAGGCAAT

GAATTGCCATTTTCTGTTATGTTCAAGAAGGCAG

85

KS23024A05 P10 19.53 AG TCAACAGTTAAAAAGCAATAGCAAAGCTCTTTCATCGTTAACAGCGTTCGTCATACAGGA[A/G]CCAAATTCCAAACATGGCAGAGCAA

GCTATTTGAATCAGCTCATAAAAGGTAGGTTCATG

CAPS_CONTIG.531 P10 20.431 GT GACCAATGCTGGTGGTGGTAGTAGTAGTAATGTGAATCAGGGTGTGCAGCAAAATGAGAT[G/T]AGTTATGGTTATGGAGTGAGTCCGG

GGATACTAGGTGGCGCGAATATGAATGGGGTGCCT

CAPS_CONTIG.845 P10 23.669 CT GGGATTACAGTAATTGTGAGGCCATTCTCTGTGGAACTTACCATATATCTCCTATGCCCC[C/T]GATCATAGGATGGGGGTTACAGTTTCAC

ACGGATATTACCCCGTTTGTTTGCAACTTTTC

CAPS_CONTIG.10421 P10 27.385 CT GGAAGTAAACACTTTTGAGTTTAACACAAATCCTTCTCCGATCCATAACCATGTTAATGT[C/T]GTGACTTGAATTTTCTTGTTCTCTAGT

GATGCAAAATAAAGGAAGCATGGCTTTGGGTAA

CAPS_CONTIG.7060 P10 27.581 AG GGGCATGAGCCAGCTGGAGTTGGAAGATGCGGTCCAAGATGATTTGAA[A/G]CGTGCCACTGGAGAATTTGTCAAAGATGAAACCGAT

GCTAATAAACTAAACCGGGTTCTGCAACTAACAGGGTTTAGCGACCCTGTTTATGCTGAAGCATTTGTGACAGTTCATCATTATGATATT

GTCCTGGATGTGACAGTTATTAATAGAACTAAAGAAACCCTCCAGAATTTATGTTTGGAATTGGCAACTATGGGTGATCTTAAACTCGTT

GAGCGTCCACAGAACTATACTCTTGCTCCTGAGTCAAGCAAACAGATAAAAGCAAACATCAAGGTGTCCTC

CAPS_CONTIG.2513 P10 32.766 CT TTTTGTGATGAAATCTTGGAAGGAGAATTTGGGAATTGGTGATGAAGTTTTGCTTTTGAG[C/T]GATGGGAATTTGGAGTTTACTAAGGC

TATTGGATGTGAACTTGATCTTAGTGATAAGCCT

CAPS_CONTIG.12771 P10 36.956 CT TCGTTTTGTGATTGGTGGTCCACATGGAGATGCTGGACTCACTGGCAGAAAAATTATCAT[C/T]GACACTTATGGAGGTTGGGGTGCTCA

CGGTGGAGGTGCCTTCTCAGGGAAAGATCCCACC

KS23026H05 P10 47.383 CT ACAATTCCTCAGCAGCGTTCTCTCTCAACGCGGCCCTTCTTCCCTTCCTTATTCGGAAGA[C/T]GTCAAATGGTTAATCCGACAACACCT

CCTTTCTCTTATCGAAATTCATCCTTCACTTCAA

CAPS_CONTIG.8126 P10 47.812 AT GAAAGACGATAATCCAATTGTTTGTATACATACAACACATACCAAGCAAGCTCAACAGCC[A/T]ATCTCCACTTAAGAGGCAGAATGCAG

TGAACTTTGTGTCTTTGGCAATGCTTCCTCTATA

KS01034H07 P10 48.797 GT TCCGGAACTGGCATTTGAAGAATACGAAACGAGTAAACTGATTAGCAATGAGTTGGAGTC[G/T]TTGGGTATTAAGTATATGTGTGGAGT

AGCTAAGACTGGTTTGGTTGGAACAATTGGATCT

CAPS_CONTIG.5319 P10 49.55 AG TGATCATCCAAAAAAGGGGGAGCCAAGGCAGGGACCTCTTGAATATCAGCTAAGTTGAAA[A/G]TACAGATAACAAACCGCAATCAGT

GGCACCTCAAGTGCAGGTTCAATCATTTGAACTATA

CAPS_CONTIG.4448 P10 51.114 CT CGTGTCATGGTGTTGCCAAACTGCAGTAATTTCTCATCCGGCTGTCGGAGCATTCTTGAC[C/T]CATTGTGGTTGGAACTCAATCTTGGA

AAGCATATGGTGTTCTGTTCCATTCATTTGTTTT

CAPS_CONTIG.1473 P10 53.085 CA CGCTCTTCTCGCTGCTTGGCTATTTCTCTACCTCTTCCGTCCTTCCGATCCTCCTTTGGT[C/A]CTCTTCGGTCGGCAGTTTTCCGAACGG

GAGACGCTTGGTGTTCTAATTATATCTACTGTT

86

KS14023D03 P10 53.622 CG GCATGCTAAGTCTTTGCTCAAGAGATGCATCGACATCCTTGAAAACCTCAAAAAAGAGCA[C/G]AAAGTTTCAAGTTAAATTCATTGATT

ATATTTGGACTACAGGATGCCTTTGCATGGAATG

CAPS_CONTIG.3847 P10 54.601 CA AGCCCCCTCCTTGACAAGTGATTACATGAAAAGATATGAAGGATAAAGATGTGGTTTTTG[C/A]ACCTTCTCATTCCTCTAGGAAGAAGA

CGTGAGAAATAACATTTTGTAGATAAGGTTTGTC

CAPS_CONTIG.4431 P10 56.716 CG AATGATGGGGATACTGCTTTGTCAGTTGTTTACTCTTTAATGTTCGAGATTGAACTGAAT[C/G]TGTCTTTTTTGCGAATAAGTAAGTAGC

ATCTTTTGTTGTTCCTTTGCTGATAATTTTCCT

KS11062F02 P10 59.859 AG GAAAAGATCCTGTTGCCTGTGATCCAGCATATCCTTGTTTCTCC[A/G]TTACACGATTTTCTCTAGGTTTCATTCCAGGGATTTCATCCTTA

ATTGGAGTCATAATCGCATTCTTCATAAGATCCCACACATCCCATCCTAAGACATCGACAGAACCCCTCTTGGCATAGCTCTC

CAPS_CONTIG.10021 P10 73.164 CA TTTAGTTTCATAAATTCCATGTCACTCAAATCCGCAATTCAATTAAACATCCCAGACATA[C/A]TTCACAAACATGGTAAACCTATGACCC

TTGATGAATTAGTCAATGCCATATCAATCAACA

CAPS_CONTIG.7121 P10 75.274 CT CAAGGGAGGAGGATGAAACACTGAGGGTGCTTGTTCTTTAGGGTCCTATAATATATGCTTATTTTATAGTCCTGTTGTGTCATAGTTCGTT

CGATTATCAGTTGGATGTGCGTGTATTGTTCGATTTTGCATCCCAGTGCTATTTCCCTCCCTAACACAGTGAGTTGTTGTTCAGTCCTGTT

TTAGTTGATTGGTCTGTTCTACAGAGGTAGCTTTTAGTTTTCA[C/T]ATGACTGCTGCAGCCAAATGGGAGGATATCAGTTTGTTCGTCCT

CTCAACCTTTATGATCTAAATTTTACCAAATTTTAATA

CAPS_CONTIG.9097 P10 84.88 CT ACCAACAACTGATGTGCAGTGGAGTCTTTGTTCATTTAGTAGCTGGCCTAGGATGGAGAC[C/T]ATTAATTGTATTACTTTGAAATATTGA

ACAAATTTGTTCTTCTATTATAACGGAAGCGTT

CAPS_CONTIG.5691 P10 85.857 AT GGTGTTCGCCAAGGGAGATCCAGGTATTGCAGCTTTGTACGACAAGCTTCTTGTTTCGGA[A/T]GACTTGTGGTCCTTCGGTGAGCTTTT

GCGGTCCAACTACGAGGAGACAAGGACCCTCCTG

KS24032G10 P10 86.021 CT TGTGATCCTCCAGAAGCTGATTGTGCTTTCAGCAATCGATACTACTTACAGTTGGTCAAA[C/T]GTTGGTGGTATAGCGTAAGGGAAAAC

GACGATGCAACATCCTTTGGAGCCATCTCCTACG

CAPS_CONTIG.1166 P10 86.874 CT TGGAGCACCAAACAATCCACCAACGAATTATCAATACAATGGCGGACCAAACAACGGTGG[C/T]GGCATGCCTTACCAAACCGGCCCA

GGGCCAAACCAGAACTATGCCTCAAATCCATCGGGT

CAPS_CONTIG.2972 P10 92.679 AG AAGTGATATCTGGTCATGACAAAGGTAAGATCGGAGAGATCACCGATATTATGAAGCACA[A/G]CAGCAAAGTCGTCGTAAGCGAGATA

AACTTGAAAACCAAACATGTGAAGAGTAGGAGCGA

CAPS_CONTIG.7283 P10 92.679 CT AATTCATCGGGCCACCTTGAAATTCCGATATCCTAGACAACGGGTTAAACCCATTCGTGT[C/T]GCTGTCAAAGTTAGACACCCAGGCGT

TAGTGAATCTATCAGGAGGGATTTTGTACTAATT

CAPS_CONTIG.6055 P10 96.507 GA CCAACTGTATGGAGTAACCCAACAAACACAATAGCAGATCCAGATTGCACCATTTGGAAC[G/A]ATGACCCAAGCCAACTTTGCTACAA

CTGTGATGCATGTAAAGCTGGTTTATTGGGAAATC

87

CAPS_CONTIG.2419 P10 97.441 AG GAGTTAGCACAAGCTGTCCTTGGGAATGACTTAAATAGGCTGCAAGAGCTTCTACGTTTGCGTCATCAGCATAA[A/G]TCAGTGCTACG

GCGTCGTCAAGAGGAGGAGATGG

CAPS_CONTIG.4225 P11 0.874 CT GGCTCATGTTCAGCTAAAGGCTGCCTTGTTTTATGCTGAGGCCTGCTATAGGTATGGTATGGAGCTCCACGAGAAAGAAGAAATTGCAG

AAGAAATTGCGAGGTTGAAGAGTGGGATTAGTGCGTTGGCTGAGGCCAAAAAGTCATCATCAAAGGGAGCAGCACAGCAGCTCTTGG

ATGCAATTAATAAGCTAGAGGCTAATTTAAATCAAAACTTGGCGAGAGCTGTGAAGGAGAATGATAGAGTATACCTCATGAGAGTTCCA

CAAGCCAGTTCTCTGCCTCCTCTTCCAGCATTTGCGATGGTCAAGCCTATGCCAATGAATGATGTTCTGGACGCAAGCAAGGAGAAGAT

GTTTGCGAGTCTTGTTCCTGATAACAGTGCTAAAGCTCTGTCCAGGTACACAGAAATGGTTGATGACGTCATCCGGAC[C/T]CAAGCTG

AGAGATTGCAACAGGGAAGTGAGCTAGCTCGAGTTAAGCTAAGGGAAATGGACTTG

CAPS_CONTIG.3634 P11 3.222 CT TGACGAAGTTAATACAGGTTTCAGCTCAAAAGAGTCCCTGGCCATGAGTTGCAGTGATGC[C/T]AGCTCACCAGGTGAAACTAGAGAGT

TGAAACGCGTTGAACCTGATGTTGGCGATACCTTG

CAPS_CONTIG.5339 P11 4.373 CT CTGCAAGTGGATGAGCATCGAAAGATGCATTAGTATGCTTACTGAAGTGAAGCCTAGCAG[C/T]GACCGTATAGGATCATTGGTGGTTGT

TGGTCTTCTGAATGATTCAAATAAATCCGGGACT

CAPS_CONTIG.9994 P11 5.947 GA CTTAAGTTGAGACAGAATGCTTTCAGTGGGGAGTTCTGGGAGCCAGAAATTGGCAGCTTC[G/A]CTAGACTACAAGTATTGTGGATTGA

GAAGACAGACTTGCAAATCTGGAGGGCTTCAAGTC

CAPS_CONTIG.8503 P11 10.194 AT TGTTGGTGGCTCTTTGACTGATCTAAGTTCCCATTCTGCACAGCCTGGACATCCTGGCTC[A/T]ACATTCCAAAGTGGCCTGCCTTTGTAT

CAACCTGGAGGTAATATAGCACCCTGGGGCCCC

CAPS_CONTIG.6374 P11 13.62 GC CTGTATACGACTACAGACATCGCGGCCACAACGTCAAGGTCCAATTGGCACAATGCTATA[G/C]TACTTGTATACTATTGTCTTAAAAGGG

CAAAGATGCCTCATGAGTTTGTAAATTTTGTCA

CAPS_CONTIG.8053 P11 19.435 AT TGCCGGCCACTGCATTGGTGAAAATCACTCATTCGATTTTTAATATCAATGATGGTGTTA[A/T]TGGGGACAAGCCTCATGGCAAGAAGA

AACTTGTCAGCAAGATTGCATCTCTGCAACAATT

CAPS_CONTIG.9109 P11 20.381 AG CTGCATTCTGCCGCAGTGGGCTTCTCGAAGATGCAAAGGAATTAGCTTCTGAATTTGAAG[A/G]GAAATATGACACATATGATGTAGTTA

TTTTGAATGCGATGCTCTCTGCCTACTGCAGAGC

CAPS_CONTIG.575 P11 25.672 CG GTCTTCTTTTACATTGATCCCGAGTTTGAAAC[C/G]GATCCCAAAATGGATGGCATCAACAATTTGATCCTATCCTACACATTCTTTAAGG

TCTCGGACAAATAAAGAAGCTGTGTTGCTTCCGTACCTTTTGGCCCTCTCCTGGACCTGCACATAGCGGGAGCTTTAATGCACTGGGCT

GCCCTTTTTGCTTCCGTACCTGGGCGTAGTCACCACCGGAGATGTAATTACTACAGAAATAACTTCATTTTCATGGCTGACTAAGGGAAA

GAACAGTGAGGGCTGCCCTTTTTGCTTC

CAPS_CONTIG.2226 P11 29.406 AC TATGCTTCATTTCTAAATACGTTTTGAACTTAGTATTAAACCTTACATGGCTGAAGTTAA[A/C]TAAGGAGCAAGTTCAACTAAATTCCTT

AGATGTTTTACAACTATCATCGGTTCTATGAGC

88

CAPS_CONTIG.5410 P11 31.285 CG TTTGAGACAGCGGAAGCTGGGGATTATATGACTTGCTTCTTTGCTGCTGATCACAAGCCT[C/G]CTCTAACTCTTAATATTGATTTTGACT

GGAAGACTGGTGTAGCTGCTAAGGATTGGACGA

CAPS_CONTIG.11039 P11 34.895 CT AGTATAGGACACCACAAATCTAATCTCAGCACAAAAATTCGCCACACGAGCAATTATTCT[C/T]TCTTTTCTTCTTTTTACCTCTATAAGTA

CTTAGCTAGCCTGATTTACACACCACCACCTT

CAPS_CONTIG.10012 P11 40.275 GT ATCCTCAAATAAAAAAATATAACATTTACATGGGCTTCCTCTTCTTTGTCATCCTCTGCAACTTCCTCCACTTCAAGTAAATCTGGTACGA

CAACCCCCAGAACACCATGGCGACGCTTGTCCATTGCTTTTG[G/T]GACAGCGGATTGCCACTTAATACAGAGGATACTACTATGCTCAC

CAACTTGCGTGTTGTAATGATGGTTGTGTTGGTCAGAAAACCAAATCCACTAATGGTTAGGAAAATGAAGTTCTGGCCCACAGCGCCGC

ATAGACAGTAAAGAAGAATGTCCCATGCTGCCTCTGGATGCTGCTTAC

CAPS_CONTIG.7498 P11 41.954 GA AATTGACTACTATTCGGACATGTTTGGGTTTAGCATTGCAAATTTATTTGCCAAATGACT[G/A]GAGATGAGAGGAGATAATGTCGTAAAA

AGAATGTACTGCAGCACTATGTAGTGTGAATTT

CAPS_CONTIG.4601 P11 43.452 CT GGAGTTTCCTGAAAATATGAGCAGTGTGGCTAATTCTTTGTTTTCTTGCACAATGGCCGG[C/T]GCAAGTTATTTAAGCACTTTATTAGTG

AACGTTTTACATGAAACTACAGGAAGACATGGA

CAPS_CONTIG.204 P11 44.638 GT CTGTGGGATTCTTTCAAACAACTGTTTGCCCTGTCTTGCATCCACGGTTGCACCAGTTGA[G/T]AAGAAACAATCTCTTAGCTCTACTTC

ACCAAGTGCAAGGAAGAAAGCTGCCTTAAAACTT

KS09088C07 P11 46.022 GC GCAATTATTGCTCAACATCCCTCATGAACTAAATTTGTGAATGGCAATGGGTGAACAAGA[G/C]ATTAGAACCACCAACTTCTGTGAGTT

CCTTGTGCATATTTTTGATGATATTTTAGAAGTC

CAPS_CONTIG.11508 P11 47.086 GA AATTCTCTGCTAGAATTCCAGAAAATGCATGTGGAATCATGATCAAAAAAAGTAGCAAGG[G/A]ATATTGGCAAAAGCATGGCAAACCG

GCAAGTCACAAAACGGCAATTATGGACTCCGTTTT

CAPS_CONTIG.12022 P11 49.221 CT ACTGGAGAAGGAAGTGGTGAGGGTGGGGGTTGTACACTGAAGTAACTATGATTAAGAGAT[C/T]ACTTGTTTGATACTGTGTTGCATGT

GTCCAGCAGCATTTCTTCTAGTCTATTACATTATA

KS20046A12 P11 49.221 GA ATTCAATGGCTTAATGATCTGTCTAATTCTACTGGAGTTTTCATCCCTATTGCTTCATTT[G/A]TGTTGGATGTTTTGGAATACAAAATAGTC

GGAGAGCGTGGAAAACCTGGATCTGCTTGCT

ACRI.DV643118 P11 50.974 GT TTGCTAAAGATGCTAAAGTTGGAAATGATAATAGTACCGGTGAAGTAAATGAAACAAGCA[G/T]TGATGCCGGTATCAGCAAACAGACC

TCGGAGAAAGGATCTAAAAAGAAAAAAGGAAAATC

CAPS_CONTIG.3948 P11 54.278 CT TTCGGTCCAGCCCCATAGGGATGGTACTTATCATTACAACTTGGGAAAAGCATTGGCCTC[C/T]CTCAAGGATGAAGGTGTCCTCATAATT

GGTTCTGGATCTGCTACTCACAACTTAAGGGCT

KS12026E02 P11 60.04 CG GATTGTTATCACCCTATAGCTCAAGGTGTTGCTGAGGCTATCCTTGCAAAGCATGCCTGAAGGTTCTGTAAATATGAAACTTG[C/G]TGAC

GCAACTGGAAACTTGACATATACGTCTGTTGCCTTAATCTGGTTGACTGTGCTGGTGCTTTCTCAG

89

CAPS_CONTIG.3887 P11 70.844 CT CGACCGCGAGGCTTCCCGCCACTTGCATGTTCAACGCGGCACCTCAGAGCCAAAGAAAGA[C/T]TGCATTTGTTAGAATGCCATTTTCA

CTCGGTTCTGTAAGGAGCATCTCTAAGTCCTTCGG

KS16023G09 P11 70.946 AC CAAAGGCCAGGAAGCGAGACAAATTCAAAGGAAGGGCTTTATTTCTCTAACTTCAGGTGA[A/C]GGAAAACATATCTGTGCTATAAGTC

CCTGCTTGAAGAAATCTGCACCAAATGACTCGGAT

CAPS_CONTIG.9798 P11 73.951 AT GGAGCACAGCCGCGACAAGAACCCCTTTTAAGATTTTGGAACAGTCACATTCAATATTTT[A/T]ACATCCTGGTATGGCTTGTCACCTTT

GTCGGTCTTCACTTTCTCTATAGCCTGTACAACA

CAPS_CONTIG.2447 P11 75.642 CG CTTAGTAGCGCCCGCACCAGCACCAGCACCAGCAGCATTGTTTATTTCATCGTCTACACA[C/G]AATATAAGTTACATCAAGTACTTTCAC

TGCAACATTTCGGATGGTTATTTCAAGAAAAAT

CAPS_CONTIG.2215 P11 81.657 AG GCAAACGTTCGGAGTTAAATATGATCATCCATGTCAAAGGGCGGAGCATGTAGTAATTCC[A/G]CCGTATGTTTCGCCGGAAAGTGTACG

GAAAACGCTGGCTACCGCGGATGTTAACGGCAAA

KS11073H01 P11 82.845 AT GTAGAATCATAAAGAGAACACAGAGAATGTAGAAGAGAAAAGATATCCCAAAAACACATA[A/T]TAAAACCGTCTCAGCAGATCATCTT

GAAATTCGCTATAAAAAACAGACACGAGAAAGGCA

CAPS_CONTIG.8372 P11 84.206 CT AGAATTGACAGCATTACACGAATGACCAGTTAATAAATGAAAAGGCCAGGCAGTGGACAG[C/T]ATTTTCTTCAGAAGACGCAAAGACT

TTCCATGCAATAGCTTGTTCATACGAAATATGTCG

CAPS_CONTIG.3318 P11 85.768 CT GGAACTCGAGAAGGAGCCTAAGTTCTTGAAGAACGGTGATTCTGGTATGGTTAAGATGAT[C/T]CCCACCAAGCCTATGGTGGTAGAGA

CATTCTCCGATTACCCACCATTGGGACGTTTTGCT

CAPS_CONTIG.7493 P11 85.768 GT AGACTGTTCAATATCCAGTGGAACACCCAGAGAAGTTTGAGAAGTTTGGTATGTCACCTTCGAAAGG[G/T]GTACTTTTCTATGGTCCCC

CAGGATGTGGGAAAACTCTACTTGCCAAGGCAATTGCAAATGAATGTCAAGCCAATTTCATCAGTGTCAAAGGACCTGAACTGCTCAC

CATGTGGTTTGGAGAGAGTGAGGCGAATGTTCGTGAAATTTTCGATAAAGCGAGACAATC

CAPS_CONTIG.7566 P11 88.646 AG ATCGACCAATCATTCAGAAGTAAGAGTGCTGTAATTTTGGAGCCACCACTGGGGAGCTAC[A/G]CTTCTTTTCTCAAAGAGAAGAACGA

GAAGAGAGTCCCAACTTCTGGCAACATTCGAGTAA

CAPS_CONTIG.1773 P12 1.195 AG AATGGCATTAGTGAGTATCATCCTATTAGTTTCGTCGCGAAAGGGGCAAAGAGAAACTTC[A/G]TTTTGTCACCATTGCTTAGCTTTAGA

GATGAATCTTATACTGTGTATTTCAACATTCAAT

CAPS_CONTIG.7491 P12 3.238 CT CGATAACTGATCCAGGAGGGGAAATCAAAATAAGTTTTGGGTATCACTGTAATAACAGCACAGATGATTCTGGCGAGGATTCAGATGGT

GTTGA[C/T]GTACGTCCTGGAAGTAAACTTCGAAGAAACAACAGTTCCTTCTCTTGTCTGTCTGGGGCAGCTCTAAGTGCCAACGCGAC

ACTAGCTAACACAAATATTTGCAATGGATTGTTTGGGGCTGAGATACTGCCAGCACTGGATTCACCTACTTCATTCCGCCGAATACCCTC

TTCTGCGTCGTTGTCAAAGTTGGATTTATTATCATCTTCTTTTCAGAGTGGCTTGTCAAACTTAAGTTGTAGTCCATCCTCTCCGAGTGAG

CTAGCTGAAGACAATTCATCTTCATTGAGGTCCACGAGTGCTCCTTCTAGGTGTGAAAGCTTCCTTAA

90

CAPS_CONTIG.12518 P12 4.303 AG AGAAAATGCCGGTCGCTGGGATGATCATCTAACCCCTGCAGAGAGACGCTACATAGAACA[A/G]AGAGAGAGGATCGACATGCATAAG

ATGGCCAAGACCGCTAATAAATCACATCGTGACCGG

CAPS_CONTIG.7991 P12 4.692 GA TGTTGTTGCTGAATATATTGTGAAGAAAATTCCCATTCCTGTTAGGGATTTCATTTCACC[G/A]CCAAATATGATAGTCATCCGATCATTTG

ATGTTAATAAACCTGGTTTTGAAGTTGATGAT

CAPS_CONTIG.11380 P12 5.597 CT AATAGAAGAGTATGAGGGTGAAGATGAGTCCAGGCCGGAGTTTCTGTGCCCTTTTTGTGG[C/T]GAGGATTTTGATGTTGTTGGCCTTTG

CTGTCATATTGACGAAGACCATGCTGTTGAGGCT

KS16010D02 P12 9.717 AC CAAGGGACTTTTGGTTAAAACACAGCAACAGTCGAAGAAGAAGAACAATTTCACCTATTC[A/C]AGACGTACTATGAGCATTCAGTGTC

TCTCGCAGGAACAGAAATGGACTCATGAAGGTTGC

KS26064A09 P12 11.242 AG AAAAAACATCATATGCATGCAAGCAAACTAATCAACTTGCATCTGGTAAAAGAACCAATG[A/G]TATCTACAAACAAGAATGTTGAGAA

GTAAGGTACTTTCTTTGTCATTTCGAGAATAGCTC

CAPS_CONTIG.883 P12 16.765 CT CGGTGTGGCCAAATCTAACGGTGCTCGTGTGCTGTTGCTGACGGCTCAGCCTGATTCGGT[C/T]AAGATGTGCGCGAGTGTTGTTGCAC

ATATTCCAGCTCAGACTATGGCGGATGATGATGAC

CAPS_CONTIG.5341 P12 18.926 CT CTGCTAGCTATGGGGCCCCTCAAGCTCAAAAGCCTCCTAGTCAGCCAGCTTATGGTCAAC[C/T]GCAGCAGTCTCCTAGTTCACAAGCT

GGTTATGCTCAGCCTCCCCCAGCACAGCCTGGGTA

CAPS_CONTIG.8629 P12 19.498 GT AATTCTGAATATCTTGAAAAGTTGGTCAATCTCAGAGTCGCCCGGAAATAGAGGGTGCTG[G/T]TTCACCATCTCAGCAAATATGCAGCC

AACTGACCAAACATCAACAGGAGTAGAGTAGTGG

KS22049B09 P12 19.726 AC GGATGGTATGTTGAACGAGATCAGGAAAACTCTTACGATCGAGTTAGATGGTTGAATTTG[A/C]TGATTTCGGAGCCTTATTATCTGTTTC

ACTTGCTCGTTTTCTTCACATATATCCCCGTTC

CAPS_CONTIG.5962 P12 31.606 AT AGGTAATTATCAATCTGTTTGTGTAGAGCTCGATGGC[A/T]ACTGGATATATCACCGGTGCTCTATTTTTGCTTGATTATTGGTGATGGTAA

TCTGCAAGTTTGAGGTTGCTAGACAAGGTTCATAGTTTAATTT

CAPS_CONTIG.1278 P12 32.372 AT GAATCTTTCTGTAGTTGGAGCTATTTCTCGTGCAGTTTCTATTCCTTCTGTGTCAGGGCC[A/T]GGATTTTCCGTCTGTGGCTATCACATTG

ATCGCCTGATATCCGACCCTGCTAAAAGTTTG

KS14004H07 P12 53.8 GT AAAGACCGTAGGTCCTGTACCACTGCCCACCAAAAAGAGAATTTACTGTGTCCTCAAATC[G/T]CCACATGTTCACAAAGATGCCAGGT

TCCATTTCGAAATCAGAACTCACCAACGCCTTATT

CAPS_CONTIG.12402 P12 59.33 AG ATGCTGGTGAACTACGATGTTTACGGGGAGAATACTGGGTCATGGACTGCACCGAAAACAGAACGA[A/G]ACGGATTCTGGGAAGGTT

CTGGTTCGGGTGAGGCGGGTCGGGTCACAGGTGGGGTGCCATCCGGGTTGAAACCGGATGTAACGGTGTGTAAAAAAGGAGGATGTG

AGTATAAGACGGTGCAGGAAGCGGTGAATGCTGCACCGGAGAACCAGGAAACGAGGAAGTTTGTGATATTGATCAAATCCGGGTTGTA

TGAGGAGAAA

91

CAPS_CONTIG.10075 P12 68.782 AT ACTGAAACTGGATCAACAGCATGGAAAATCGAGAGTGAGAGTAGCTAGGGTTTGGAAAGA[A/T]GGAGATGGAAAACATCATTTTTCT

GAATGGAGTGTTAACATCAGTCTCCTTTCCAATTGT

CAPS_CONTIG.1344 P12 71.828 CT GACGGAAGATGGGAAGGAAAAGAAGGTAACCTTTGACCTTACACCTTTTAAGCCCATAAA[C/T]GCATCTCTGTACCTATGTGACAACA

AGTTTCACACGGGACCTTTGGGTGAACTGTTGGAA

CAPS_CONTIG.12230 P12 76.415 GA ATGGTAGATAGAAGCACAGGAAGTTTGATAAACATATCAAATTATGGAGAAGAATATAGG[G/A]AGGAGGGAGAAAGTCCGATTAATGTA

TTGTTTCATGGTTATGGTCACTATGACATATTGG

CAPS_CONTIG.182 P12 77.468 GA GGATTAGTTCCCTTAAGTTGGTGCCCTCACAATGCTGGAAAGAGGAGTGATGCTACATTC[G/A]ATTGGGAAAGATCAAGTTTGTTATCT

AACAGAATGAGACTATTTTGTAGTCGGCTGAACA

CAPS_CONTIG.8374 P12 84.083 CT GTACTCTGATCTTCTTAAGGCTCAGGTCCCGGGTAGGGACATTCCAGCTGATGCACTAGATCGTGTAGCTGAAGTTTTACCCCGCTAATT

CAAGTGAAGTGCAGAACACTGCCTTTTTGGGACTTGCTGGACGAGTGTTTGCAGATTGATTCTTTTTATGTTGCAGAGCTTTGTGAAGT

GCAGGCATATG[C/T]ATAGATGGTTGGAAGAAGCTTAACCCGAATGTTCATGGTTTTGGTCAGGGCTGTTAAGACTTATCGTTGTTATTAT

TCTTTTTGTAGTCATATTCTTTAGGGTCCTGCATCATTTTTTGGCAAGCTTTAATTTTCTTCTTGTTCATATGAAGGGCTTTTCTTTAGTTTG

GATGAAATGAATCATGCCTGTAAAATTCTGTATCGAGTAATAAAAGATCTTCGCTTCAAACGCGGAATGTAAGTGGTTCTT

CAPS_CONTIG.8761 P12 86.122 AT TAGGGTAATGGACCTGTATTCAGCTCAATAGTTGTAAACAATGTCTTTTTTCTTCTCAGT[A/T]GCAATATACAAAAGTACATTCTTTGAG

AATGTCGAAAATAGTTCCCTGCATGAATCATCG

CAPS_CONTIG.12378 P12 87.445 CG AAAGTGTGAGCAGATAACTATTTATCCTATAGCAGCGTAAGAGTTGGCCCTATATTTATC[C/G]ATGGAGTGAAGTTGGTGTTTAAATCTG

GATAGAACAGGATACTTGTGATCGACTACTAGA

CAPS_CONTIG.5606 P12 88.124 CT CTATCTAGGTTTCATCTACACTTCTTTTCAAGAAAGGGCTACCTTCATTTCACATGGAAA[C/T]ACAGCTAGGCTCGCCAAGGAGCATGG

GGATATGAAACTAGCACAAATATGTGGTTCAATT

CAPS_CONTIG.6311 P12 89.112 CG CAAACCAAGCAACTCTGACCATCCACGGCCAAATGTTCTTCACCGGTCTGATTTTCAACC[C/G]AGTGGCTTTTCGCCTGATGTTGTTGA

CGACCTAATAAATCTAAACAGTCCTTGAGGAGCA

CAPS_CONTIG.10589 P12 90.061 GT GCATTTAACATGTACTAATATGCCTGTTGAGAAAATTGATCAGGCTCTTGATACTATTAA[G/T]AGTGATGGTATTCAAAATGTTCTTGCAC

TTCGTGGTGATCCACCTCATGGTCAAGATAAG

CAPS_CONTIG.933 P12 91.556 CT TCTAAAAATGGGTAGCAACCAAGCAGTATCATTCCTCACAAACATCGCACGCGCCGCCGT[C/T]GGTCTCGGTATAAGCGCGTCGATACT

CAATTCCTCTCTCTACACCGTCGACGGTGGCGAA

CAPS_CONTIG.9227 P12 92.102 CT TTCTGAACCGTGGGTACTTGTTGTAACCCGTACCTGCACTTTTTCTTCATTATAAAAATC[C/T]TATCTGGGACGCAAATGATCCTGATTTG

TGTTGAAAAAATTCTTCTATCGATTAGCAAAA

92

CAPS_CONTIG.6241 P12 94.968 CT GTAACCTTTTGATCTTCATATCATCGAGTCTACTCAATCGCTGTTCTGCTGCATCTGCTG[C/T]GCGCTCTTAGTTATCCCTACTACTAGTTC

TATGTTTGTACATATATCTTGTAAAATCAAG

CAPS_CONTIG.9030 P12 99.119 CT CTTGGACAAACTCCCAGATGATGCCTTTGTGGTTTACCAAGGTCACCATGGTGATCGTGG[C/T]GTGTATCGTGCCAATGTGATTTTGCC

AGCATCTGCTTTCACAGAGAAAGAAGGAATATAT

KS23053A02 P12 99.977 CT GCTTCTTCTTCTGCTGCTTCTGCCTTCTTCTCCCTTCAACAATACGAGTCAGGCCTCGAG[C/T]TATGTTCACGTCTCTGGCAGTATCAAG

CGTTGCCAGTGCAGCTACCGACTTCGCAACTGA

KS12037E02 P12 106.291 AG GTCTCCATTACCGCAAGTGCGAGGGAAGAGAACTCCAAGGAAGAATTTGAAGTATGGAC[A/G]AAGAGGCCCATCAAAATCTTCTTTG

AGTAGAAGAAGCCTGCTTTTAGGCAAGCCACTGGCGACCTCAAAGACCAAGGTGGACAGTTTAAGCTCAGG

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