Almería, 6 de febrero 2019

Jordi Garcia-MasIRTA, Centre de Recerca en Agrigenòmica CSIC-IRTA-UAB-UB

Genómica y mejora genética

- Introducción

- Secuenciación de DNA

- Secuenciación de genomas

- Anotación de genomas

- Descubrimiento de SNPs (GBS, resecuenciación de genomas)

- Genotipado de alto rendimiento

- GWAS, Selección genómica

- Edición génica

El paso de la vida nómada al sedentarismo durante el neolítico (aprox. 10,000 AC) favoreceel desarrollo de la agricultura

Origen de la agricultura

Pintura mural 1200 AC

La domesticación de les especies cultivadas sucede en diversos centros de origen

Domesticación de las especies cultivadas

Gewin, PLoS Biology 2003

Cong et al. Nature Genetics 2008

La domesticación y la selección provocan la pérdida de variabilidad genética

The funnel effect (Tanksley i McCouch 1997)

Tipos de variabilidad

- Intraespecífica: buscamos variabilidad dentro de la misma especie- Especies cercanas compatibles (ex. tomate y género Solanum) - Creación de nueva variación:

1. Inducida: colecciones de mutantes (EMS, rayos X…)2. Transgenes, edición génica

Búsqueda y creación de variabilidad

Domestic and wild tomatoes. L to R: Solanum lycopersicum, and wild relatives S. pimpinellifolium, S. habrochaites and S. pennellii. (Brad Townsley, UC Davis)

The process of Plant Breeding: use of markers

Search and creationof variability

Selection

EvaluationMultiplication &

commercialization

Variability assessmentGenetic distancePedigree validation

Marker-assisted selection

Hybrid purityFingerprintingBreeder’s rights enforcement

CHROMOSOME

Interesting region

Gene of interest

Pathogen inoculation

S R

DNA extraction

PCR

d= 0-2 cM

M2M1 G

Selección asistida por marcadores (MAS)

Uso de marcadores de DNA, estrechamenteligados a un carácter genético, como alternativa al fenotipado del carácter.

Asumimos el fenotipo a partir del genotipo.

Bevan and Uauy 2013

Markers in the genomics era

x

BC1

BC 6-8

P1 P2

Método del retrocruzamiento:selección para un solo marcador

F1

x

BC1

BC2 BC3

P1 P2

Whole genome selection:selección para muchos marcadores

F1

DNA sequencing technologies

- Maxam and Gilbert- Sanger- Next generation sequencing (NGS) 454, SOLID, Illumina- New technologies (single-molecule sequencing)

Maxam and Gilbert sequencing (1976)

- Chemical modificationof DNA and cleavage

- Radioactive labellingof DNA at 5’

- Technically complex

Sanger sequencing (1976)

- Enzymatic method

- Di-deoxynucleotides are used

- Automated

Sanger sequencing evolution

Automatic Sanger sequencing

• Advantages Long reads of aproximatelly 900 bp are obtained

Suitable for small projects

• Disadvantages Low throughput

Expensive

Automatic Sanger sequencing

Next generation sequencing technologies

Nature 437, 376-380 (15 September 2005)

Sanger vs NGS

Shendure and Ji 2008 Nat Biotechnol

Sanger vs NGS

Metzker 2010 Nat Rev Genetics

Clonally amplified templates

Direct detection: (IonTorrent)

pH changes due to release of H+

Fluorescence: (Illumina)

Nitrogenated base labeled

phosphate labeled

Pyrosequencing: (454-Roche)

Released pyrophosphates are transformed into light signal

Sequencing by synthesis and detection

Kahvejian et al 2008 Nat Biotechnol

DNA sequencing applications

Single-molecule templates

Helicos Heliscope and PacBio are new systems that rely in the sequencing of a single molecule: no amplification

Pacific Biosciences real-time sequencing

- Single molecule real-time sequencing (SMRT)- Nanotechnology- Long reads (10 kb), high error rate

• Single molecule

• Real time sequencing

• Polymerase fixed in a plate

• bp lengths 10 kb

• Phospholinked fluorescent Nucleotides

• Well size 70-100 nm (Roche 44 µm)

• 10 million wells

• 100 Gb/h, 15x human genome in 15 min

http://www.youtube.com/watch?v=v8p4ph2MAvI

https://www.youtube.com/watch?v=3UHw22hBpAk

Evolution of DNA sequencing

Genome sequencing

Genome Sequencing

• Genome sequencing: obtaining the order of nucleotides across agenome… but

• Genomes are large (hundreds to thousands of Mb) and DNAsequencing methods can handle only short stretches (hundreds of bp)of DNA at once… so

• Solution: Sequence small pieces and then use computers to assemblethem. Assembly of the reads into sequences represents acomputational problem.

Genome Sequencing: some terminology

Assembly: allocating sequenced fragments of DNA into theircorrect chromosomal positions.Contig: contiguous sequence of DNA created by assemblingoverlapping sequenced fragments of a chromosome.Draft sequence: genome sequence with lower accuracy thana finished sequence.Physical map: a map of the locations of identifiable markersspaced along the chromosomes.Scaffold: a series of contigs that are in the right order but arenot necessarily connected in one continuous stretch ofsequence.Shotgun sequencing: breaking DNA into many small pieces,sequencing the pieces, and assembling the fragments.

Genome sequencing

35

Short fragments of DNA

AC..GC

TT..TCCG..CA

AC..GC

TG..GT TC..CC

GA..GCTG..AC

CT..TG

GT..GC AC..GC AC..GC

AT..ATTT..CC

AA..GC

Short DNA sequences

ACGTGACCGGTACTGGTAACGTACA

CCTACGTGACCGGTACTGGTAACGT

ACGCCTACGTGACCGGTACTGGTAA

CGTATACACGTGACCGGTACTGGTA

ACGTACACCTACGTGACCGGTACTG

GTAACGTACGCCTACGTGACCGGTA

CTGGTAACGTATACCTCT...

Sequenced genome

Genome

break sequence

assemble

Strategies for genome sequencing

- Clone-by-clone (e.g. human)

- Break genome into many long fragments and clone

- Map each long fragment onto the genome and select clones

- Sequence each selected clone with shotgun

- Walking with clone-ends (e.g. rice)

- Break genome into many long fragments and clone

- Start sequencing some clones with shotgun

- Construct map as you go

- Whole Genome Shotgun (e.g. poplar)

One large shotgun pass on the whole genome

Clone-by-clone strategy

• Create a physical map, using hibridization,SNaPshot, or WGP (whole genome profiling) usingmainly BAC libraries.

• Select a minimum tiling path

• shotgun sequence each selected BAC clone

• assemble the individual BACs

BAC clone

mapgenome

Walking strategy

- Build a redundant library of BACs and sequence clone-ends (BES)

- Sequence seed clones

- Walk from seeds with clone-ends to pick clones that extend both sides

- A complex method

genome

BAC clones

Whole-genome shotgun (WGS)strategy

• Randomly ‘shotgun’ the genome and clone in libraries of different insert size (plasmid, cosmid, phage, BAC)

• Sequence each fragment

• Reassemble the reads

• No previous order is needed

Whole Genome Shotgun Sequencing

cut many times at

random

genome

forward-reverse paired

reads

plasmids (2 – 10 Kbp)

cosmids (40 Kbp) known distance

~500 bp~500 bp

Clone-by clone vs whole-genome

Advantages and disadvantages

• Clone-by-clone and walking strategies:

easier assemblies, but a physical map is necessary. Redundancy in clone sequencing.

• Whole-genome shotgun:

No mapping and no redundant sequencing, but repeats are difficult to resolve

Fragment (or read) assembly and repeats are the main problems

• To construct the genome from the reads we find some difficulties:• Incomplete coverage. Leaves contigs separated by gaps

of unknown size.

• Sequencing errors.

• Unknown orientation of contigs

• Repeats: – Complex organisms have repetitive elements

many pieces

to assemble

High coverage:

Assembly: how much sequencing?

Low coverage:

A few pieces

to assemble

a few contigs,

a few gaps

many contigs,

many gaps

Input OutputLander and Waterman,

1988

Main steps to assemble a genome

Now we have NGS sequencingtechnologies

• We can use the above mentioned methods (clone-by clone sequencing or whole-genome shotgun) but instead of using Sanger, we can use 454, Illumina or hybrid approaches

Minimum tilling path (MTP)

BAC library

BAC pooling

Shotgun sequencingand assembly

BAC-to-BAC sequencing strategy

Shotgun sequencingand assembly

Whole genome shotgun sequencing strategy

Timeline of genomic analysis beforethe human genome sequence

2009: Illumina

40-50K$

Secuenciación del genoma humano

2001: Human Genome Project

2.7G$, 11 years

2001: Celera

100M$, 3 years

2007: 454

1M$, 3 months

https://www.genome.gov/27565109/the-cost-of-sequencing-a-human-genome/

Many plant genomes available

The challenge to efficiently manage the

amount of generated data:

bioinformatics

Genome sequence quality is important

Genome annotation

• Annotation: attachment of biological information to sequences

• Genome annotation

Structural: placing functional elements in the genome as ORFs, gene structures, regulatory elements

Functional: attaching biological information to these elements

• Either automated and/or manual

Genome annotation

Cruz et al. GigaScience 2016

https://www6.inra.fr/decodage/layout/set/print/TriAnnot

Pipelines for genome annotation

Sequencing the DHL92 melon genome

Shotgun Paired Ends (3, 8, 20 kb)

Assembly with Newbler 2.5

BAC-end sequences

12 x 6 x

DHL92

Ti

0.06 x (50% paired)

Etiolated plants

nuclei purification

Garcia-Mas et al. PNAS (2012)

- 19.7 % of the assembled genome corresponds to transposon sequences (probably an underestimation)

Garcia-Mas et al. PNAS (2012)www.melonomics.net

A: Physical mapB: ncRNA distribution (orange)C: predicted genes (green)D: transposable elements (blue)E: NBS-LRR genes (brown)F: duplicated blocks

0

10

20

30

40

50

60

70

0 1 2 3 4 5 6 7 8 9 10 11

nu

mb

er

of co

pie

s

million years

- The melon genome has expanded the TE content after the split of the melon/cucumber ancestor 11 My ago. This may, in part, explain the genome size difference between cucumber (350 Mb) and melon (450 Mb) - No recent WGDs were found

Insertion time of melon LTR retrotransposons

- We predicted 27,427 genes in the melon genome,encoding 34,838 transcripts and 32,487 proteins- 69 % of gene predictions are supported bytranscript or protein alignment

Sequencing the DHL92 melon genome

Genome anchoring to chromosomes: pseudomolecules

- F2 map with SNP usingIllumina GoldenGate assay

- 98.2 % of the scaffoldassembly anchored to the 12melon LGs (355 Mb)

Garcia-Mas et al. PNAS (2012); Argyris et al . BMC Genomics (2015)

Number of scaffolds

% assembly

- N90 index is 78 scaffolds.N50 scaffold size is 4.6 Mb

Assignment of chromosomes to the genome sequence

- The karyiotype of “Piel de Sapo” was obtained- FISH allowed assigning each melon chromosome with the corresponding genome assembly- Centromere-specific repetitive sequences identified the putative centromeric regions

Argyris et al. BMC Genomics (2015)

High synteny between melon and cucumber (Cucumis sativus)

Garcia-Mas et al. PNAS (2012)

- The melon genome has expanded in pericentromeric regions, probably due to TEamplification, when compared to cucumber

- Synteny exists among cucurbit genomesbut it is complex after extensive rearrangements. Dysploidy in cucumber2n=2x=14 (Yang et al Plant J 2014)

Guo et al. Nat Genet (2012)

The Tomato Genome Consortium, Nature (2012)

The tomato genome

Improved maize genome sequence

Improved maize genome sequence

Fast de novo genome sequencing

Improved melon genome sequence

(under analysis)

SNP discovery

Method for SNP identification

PrerequisitesCurrent false

discovery rate (%)Specifics, limitations

EST sequence dataLarge number of available EST-sequences

15-50

Dependent on the expression level or need for normalized libraries, difficulties in the discrimination of orthologous from paralogous sequences, low sequence quality

Array analysisUnigene sets based on EST-sequences, array technology

>20Not all SNPs identified, large genomes require complexity reduction

Amplicon resequencing

Unigene sets based on EST-sequences, amplification primers for many individual genes

<5

High reliability but costly, detailed haplotype analysis possible, many lines can be compared, allele frequency data with pools of DNA

No genomic sequence and next-generation sequencing technologies

Novel sequencing technologies, complexity reduction methods, bioinformatic tools

15-25

Generates large amounts of data, costly bioinformatics, false discovery rate for genomes without full sequence is relatively high

Genomic sequence is available either through conventional sequencing or next-generation sequencing

Reference genome, bioinformatic tools

<5-10

Small genomes can be fully sequenced and compared for SNPs, for large genomes targeted approaches will be necessary (e.g. exon capture and multiplex amplification)

Ganal et al. (2009) COPLBI,621Summary and comparison of SNP identification methods.

in silico SNPs in databases

in silico SNP

contigESTs

pSNP (for putative SNP)

Definition: sequence variation in silico that is present

in at least two ESTs between at least two varieties.

Verification of pSNP

SNP discovery in the -omics era

1. SNP discovery through transcriptome sequencing

2. SNP discovery through partial genome sequencing (GBS)

3. SNP discovery through genome resequencing

Genotyping by sequencing

Methods to reduce genome complexity

Simultaneous marker discovery and genotyping. For large genomes,

complexity has to be reduced prior to perform genotype by sequencing

We can use target enrichment (sequence capture, long range PCR,

molecular inversion probes) or Restriction enzymes

Use of sequence capture of gene regions avoids screening non-coding

regions of DNA, which may be a problem

image from Cornell University webpage

• Reduced-representation sequencing

i. reduced-representation libraries (RRLs)

ii. complexity reduction of polymorphic sequences (CRoPS)

• RAD-seq

• Low coverage genotyping

i. Multiplexed shotgun genotyping (MSG)

ii. genotyping by sequencing (GBS)

• RNA-seq

• Sequence capture

Davey et al. (2011) Nature Reviews

Types of NGS-based reduction of genome complexity

Davey et al. (2011) Nature Reviews

Platform specific

Reduced-representation libraries (RRL)

Fragments digested with frequently cutting

restriction enzymes are pooled, selected by size

and sequenced

Partial but genome-wide sequence data. Typically

used to sequence pools of DNA samples, not

allowing the detection of the sequence of each

individual. Each marker is sequence at high

coverage enabling markers to be genotyped

accurately across many individuals

Complexity reduction of polymorphic

sequences (CoRPS)

By adapting the amplification of AFLP fragments to

enable sequencing on the Roche sequencing

platform

First method to identify polymorphisms in each

individual sample by incorporating short barcode

identifier sequences into the barcodes on the

Roche platform. Each marker is sequence at high

coverage enabling markers to be genotyped

accurately across many individuals

RAD-Seq

RAD-seq sequences short regions surrounding the

restriction sites for a given restriction

endonuclease. Restriction fragments are randomly

sheared to a length suitable for the platform

chosen. Selective PCR is used to amplify for

sequencing only those fragments containing a

restriction site

Samples can be individually barcoded. Each

marker is sequence at high coverage enabling

markers to be genotyped accurately across many

individuals

Genotyping by sequencing (GBS)

Involves digestion of genomic DNA with frequent

cutter and sequencing of the ends of all resulting

restriction fragments. Adaptors containing

barcodes and common adaptors without barcodes

are mixed and used in the ligation process. Only

fragments with both types of adaptors or with

appropriate size will be sequenced. Thus, fragment

reduction occurs during the ligation process

Samples can be individually barcoded. Targeted

markers are sequenced at low coverage and not all

genotyped in all individuals. o missing data can be

inferred based on probabilistic calculations.

Suitable for mapping.

Multiplexed shotgut genotyping (MSG)Similar to GBS but with only one adaptor.

Fragments are size-selected before sequencing

Samples can be individually bar-coded. Targeted

markers are sequenced at low coverage and not all

genotyped in all individuals. Physical position of

markers known so missing data can be inferred

based on probabilistic calculations. Suitable for

mapping.

- We target a reduced representation of a genome for analysis.

- Discovery and genotyping of thousands of markers in a single step.

- Can be applied to species with no genetic information available.

- Directly applied to GWAS.

- Methods developed for high-throughput genetic marker (SNP) discovery often include:

1. Digestion of multiple samples of genomic DNA with RE

2. Selection or reduction of the resulting restriction fragments

3. NGS of the final set of fragments (<1kb size)

- Use of methylation sensitive REs reduces repetitive regions

Genotyping by sequencing

Schematic diagram of a GBS procedure

Deschamps et al (2012) Biology

GBS 2011

GBS in Buckler’s lab

image from Cornell University webpage

GBS library construction

http://www.maizegenetics.net/gbs-overview

IBM maize mapping population: parents + 276 RILs

200,000 markers mapped

Barley Oregon Wolf (OWB): parents + 43 DHLs

25,000 markers mapped

GBS original paper

Resequencing and RNA-seq

Utilització de Next Generation Sequencing (NGS)

SNP discovery from RNAseq

454 GS FLX400 Mb (1.000.000 sequences of 700 bp per run)

RNAseq of 8 tomato varieties

RNA extraction

cDNA synthesis

High throughput sequencing 454 Titanium

SNP detection

High throughput genotyping (Fluidigm, KASPar)

Unigenes total 191122 Newbler

69 MIRA

SNPs total 618445 Newber

169 MIRA

Label Reads %

Re

gio

n1

LB0502 29465 6,62

LB0417-5-2 63819 14,33

LB0757 38903 8,73

A0124-9-1DA 75474 16,95

Re

gio

n2

B0422-2-1 54026 12,13

BDU0303-11-1 57610 12,94

A908-8 55129 12,38

LB0801 49952 11,22

Unidentified 21000 4,72

Total 445378 100

- The zucchini genome is not available. Alternatively, a transcriptome is available, which was used as a reference.

- RNA from 7 zucchini breeding varietes was sequenced using Illumina Hi-Seq2000 in a Flow-cell. RNA from fruit, leaf and flower.

SQUASH LINES BARCODEREAD

LENGTHAPPLICATION

A000422R K445 2X75 pb mRNAseq

A020351R K446 2X75 pb mRNAseq

A020231R K447 2X75 pb mRNAseq

A00081 K448 2X75 pb mRNAseq

LA701 K449 2X75 pb mRNAseq

A030362VH K450 2X75 pb mRNAseq

P0220 K451 2X75 pb mRNAseq

A000422R K445 2X75 pb mRNAseq

RNAseq of 7 zucchini varieties

- Remove low quality reads- Remove adaptors- Mapping against public 49,000 zucchini unigenes- SNP calling- Filtering no intron in a 60 bp window: 24,466 - Filtering read depth, SNP quality: 4,558- Filtering 3 SNPs/unigene: 2,719

Zucchini SNP mining

A problem when discovering SNPs from transcriptome data is the presence of introns

Software is available to predict introns: Intron Finder

Or BLAST against the reference genome, if available

An experimental validation is necessary

Genes have introns...

Reduced-representation or whole-genome sequencing?

Whole-genome sequencing feasible in species with small genomes

In larger genomes, reduced-representation methods are nowadays more convenient. Many research questions can be answered with a small set of markers and the whole genome sequence is not necessary

GBS or whole genome sequencing?

- Once we have a reference genome sequence, resequencing individualsis not complex.

- Illumina is the best option, regarding cost and throughput.

- PE sequencing to low coverage is the choice (10-20 x), depending inthe number of genotypes, genome size and application.

- PE reads are between 76-150 bp.

- Reads are mapped to the reference genome, using BWA, Bowtie orothers, generating BAM/SAM files.

- We can visualize the read alignments with different software, as IGV.

Resequencing

Mapped read visualization with IGV

- Variants (SNPs, short indels and structuralvariations (SVs)) between individuals

- SV (> 50bp) include CNV (copy-numbervariation), indels and duplications.

Genetic variation observedafter resequencing

Variant browser

Lai et al 2010 Nat Genet

- 6 maize elite inbred lines sequenced.- 1 milion SNP, 30,000 indel, hundreds ofpresence/absence genes

Lai et al 2010 Nat Genet

Pedigree analysis of maize inbred lines

Chia et al 2012 Nat Genet

- 103 lines of pre-domesticated and domesticated maize- Relative genus Tripsacum is included- 55 milion SNPs

Jiao et al 2012 Nat Genet

- 278 maize inbreds- Modern breeding afected thousands of genes and non-genicregions. Reduction in nucleotide diversity and increase of rarealleles.

Hufford et al 2012 Nat Genet

- 75 wild, landraces and improved maize lines- Domestication is studied and genes with signals of selectionare identified

SNP discovery for cucurbit breeding: cucumber

Cs CUCUMBER LINES TYPE LANEMULTIPLEX

INDEX

READ

LENGTHAPPLICATION

Cs1 A 202-3-1 Holandés 1 1 2x100 WG-Seq

Cs2 A 801-7 Holandés 1 2 2x100 WG-Seq

Cs3 P 501 Francés 1 3 2x100 WG-Seq

Cs4 A 0313-8-2-1 Mini verano 1 4 2x100 WG-Seq

Cs5 A 0318-7-4-1 Mini verano 2 5 2x100 WG-Seq

Cs6 A 808-1-1 Mini invierno 2 6 2x100 WG-Seq

Cs7 A 910-3-2 Mini invierno 2 7 2x100 WG-Seq

Cs8 A 919-2-4 Cornichon 2 8 2x100 WG-Seq

- There is a need of SNPs for MAS that are polymorphic in the narrow germplasm used in breeding- As the cucumber genome is available (Huang et al 2009), 8 cucumber breeding varietes were re-sequenced using Illumina Hi-Seq2000 at 25X (2 Flow-cell lanes, MIDS used)

- Remove low quality reads- Remove adaptors- Mapping against reference genome- SNP calling- Filtering SNPs Phred>20, heterozygous, SNP in all lines: 557,110- Filtering at least 8 reads in each line: 407,753- Filtering no SNPs in 50 bp windows: 20,501

Cucumber SNP mining

Cucumber SNP validation

483 SNPs evenly distributed in the genome were used for validation using Kaspar chemistry

93% of the SNPs were experimentally validated

SNPs now used in breeding programs routinely

- Resequencing of 7 representative varieties with Illumina paired-end sequencing (35x106 paired reads/sample, read

length 150 bp, 22x coverage, 10 Gb/sample)

- 4,556,377 SNPs and 718,832 small insertion/deletions (DIPs ) were called

- Structural variation (SV) and transposable element (TE) polymorphisms were also called

- TE polymorphism analysed with Jitterbug

Exploring natural variation using genome resequencing

Trigonous (India)

C-836 (Cabo Verde)

PI 124112 (India)

C-1012 (Irak)

PI 161375 (Korea)

Védrantais (France)

Piel de sapo (Spain)

Sanseverino et al. 2015

Non-uniform distribution of diversity across the genome

Sanseverino et al. 2015

SV and TE polymorphism

Sanseverino et al. 2015

SNP discovery

PI 161375 Piel de sapo T111

Sanseverino et al. 2015

SNP genotyping

technologies

• CAPS• Denaturing HPLC (DHPLC)• Pyrosequencing• SNaPshot• Taqman• Molecular beacons• High resolution melting (HRM)• SNPlex• Illumina GoldenGate and Infinium• Kaspar• Fluidigm • Microarray Single Feature Polymorphisms (SFPs)

… and many others

SNP• SNP detection systems, many available

• Single-base extension (SBE)

– Sequenom (MS), SNaPshot

• Allele-Specific Extension

– Illumina

• Primer Extension

– Pyrosequencing

• Differential Hybridization

– Taqman, Affymetrix/GeneChip

SNP detection methods: type of detection

Taqman

- 5’-3’ nuclease assay: activity of the enzyme Taq-polymerase and fluorophore-based detection.-Two specific primers targeting the region flanking the SNP and two TaqMan fluorescent probes with a Minor Groove Binder (MGB) (quencher).- Single SNP assay

High resolution melting (HRM)

- High Resolution Melting Analysis is based on PCR melting

(dissociation) curve techniques.

- High Resolution Melting Analysis (HRM) is a post PCR method.

- The region of interest is first amplified using PCR. During this process, special

saturation dyes are added to the reaction, that fluoresce only in the

presence of double stranded DNA. Such dyes are known as Intercalating dyes

(eg SYBR green)

- When melting dsDNA, fluorescence fades away

High resolution melting (HRM)

BioMark™ (Fluidigm)

Each 96.96 Dynamic Array is capable of producing 9,216

real-time qPCR data points using just 1/200th the amount of

reagents.

- SNPtype assays available- Compatible with other chemistries as Taqman or Kaspar

Fluidigm SNPtype assays

- Allele specific PCR- Suitable for multiplexing medium number of SNPs (48-96)

Illumina genotyping

http://www.youtube.com/watch?v=lVG04dAAyvY

• Two competitive, allele-specific, tailed forward

primers and one common (reverse) primer

• Proprietary FRET cassette for fluorescent (FAM, VIC)

signal generation

• Uses passive reference dye (ROX)

• Two components: a SNP-specific assay mix (primers)

and reaction mix (everything else)

• Includes specially-developed KTaq polymerase

• Uses same equipment as TaqMan®

KASP chemistry

https://www.youtube.com/watch?v=_S0m2PrwPdE

End-point Analyser

KBioscience-LIMS

KBioscience Assay Dispenser

96/384 DNA stamping

KBioscience Laser Sealer KBioscience waterbath PCR

Projects/routine

SNPline components

Genome-wide association

studies (GWAS) and

Genomic selection

Definition of GWAS

A genome-wide association study (GWAS) is defined as any study of genetic variation across the entire genome that is designed to identify genetic associations with observable traits.

• Whole genome information combined with phenotypic data has the potential for understanding of basic biological processes.

• High-throughput, cost-effective methods for genotyping are providing powerful research tools for identifying genetic variants that contribute to interesting agronomic traits.

• GBS in 2,815 maize inbreds producing

681,000 SNPs

• GWAS for kernel color (Y1 gene),

sweet corn (Su1 gene) and flowering

time (complex trait)

Example of GWAS in maize

Romay et al. Genome Biol 2013

Example of GWAS in tomato

• Resequencing of 360

accessions

• GWAS for pink color (Y gene)

using 231 accessions

• Association with a SNP 8 kb

upstream of the SLMYB12 gene

Lin et al. Nat Genet 2014

Genomic selection: predicting the phenotype from the genotype

• En lugar de identificar loci

individuales asociados a un

caracter, se utilizan datos de

marcadores en todo el

genoma como predictivos

del fenotipo

• La selección se basa en

predicciones, e incorpora el

efecto de la variación debida

a QTLs menores

Genomic selection pipeline

Gene editing

Gene editing

Precision removal or change of a few nucleotides

- Oligo directed mutagenesis (ODM)- Site-directed nucleases (SDN)

- Zinc finger mucleases- Meganucleases- TALENs- CRISPR/Cas9

Hsu et al. Cell 2014

The endogenous DNA repair mechanism

Natural mechanisms of microbial CRISPR

Belhaj et al. Curr Op Biotechnol 2015

Engineering the CRISPR editing tool

Ding et al. Front Plant Sci 2016

Cas9/gRNA genome editing

Belhaj et al. Curr Op Biotechnol 2015

Pipeline for CRISPR/Cas9 editing in plants

CRISPR/Cas9 genome editing ofcucumber eIF4E

Some examples

Virus disease resistance in cucumber

2) BSA + NGS : resequence of 15 R and 15 S homozygous families from F3 population

Strategies for the development of linked markers

1 ) SNP mining from resequenced parentals lines, mapping resistance in F2 population; gene mapped in chr5

Resistant parental x Susceptible parental

F1

F2 population (135 pl)

F3 population (135 families) pathology test(1 dominant gene)

Bulk segregant analysis combined with a next generation sequencing strategy

- Selection of 15 R homozygous (bulk R)+ 15 S homozygous (bulk S) DNA extraction

- Resequencing of parental lines + 30 individuals tagged (12 x coverage)

- Bioinformatic analysis and SNP mining between R and S bulks

15 R 15 S

2 parentals

Mapping reads against cucumber genome and filtering

~1,400,000 SNPs

Quality and coverage

1,214,344 SNPs

Not against ref genome & 30 individuals genotyped

129,301 SNPs

1,133 SNPs

SNPs bulk R against bulk S

All SNPs in Ch5 in a 794 Kbinterval (containing 64 genes)

Selection of 48 SNPs in the interval and genotyping of 135 F3 families. A singlecandidate gene identified.

A set of markers for MAS is available

- eth3.5 and eth6.3 induce climacteric ripening

independently.

- Both QTLs interact in SC3-5-1 to induce precocity in fruit

ripening.

- SC alleles in the PS background partially recover the

capacity to produce ethylene.

8M35 8M318M40

PS SC

PS and SC are non-climacteric, but two climacteric NILs were found

Moreno et al. TAG (2008); Vegas et al. TAG (2013)

eth3.5 + eth6.3

eth3.5eth6.3

PS

Mapping of eth6.3

Vegas et al TAG (2013)

≈ 2,8 Mbp

eth6.3 lies in the centromeric region of LGVI, a region with low recombination rate

SNP1 SNP2

SNP1 SNP2 Recombinants

B H 10

A H 6

H B 6

H A 5

Total 27

Fine mapping of eth6.3

- Recombinant search in 1,400 F2 individuals withflanking markers: 27 recombinants

eth6.3: NAC domain-containing protein

≈ 2,8 Mbp

Fine mapping of eth6.3 resulted in the identification of a candidate gene

139 kb interval containing 5 annotated genes

Gene

mRNA

SNP1

SNP3 SNP2

SNP2SNP1 SNP3

Validation of eth6.3

- In a climacteric genetic background TILLING population (URGV, France), 6,200 families were screened. 17 mutants identified: 5 non-coding regions, 4 silent, 8 non-synonymous.

Phenotyping in 2014 and 2015 revealed an increased time period from pollination to dehiscence and to change of external fruit color in mutated fruits in two families, confirming the role of this gene in climacteric ripening.