next generation sequencing (ngs) applications€¦ · •the expression of the transgenes did not...
TRANSCRIPT
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Next Generation Sequencing (NGS)applications
Pumipat Tongyoo, Ph.D.
Center of Excellence on Agricultural Biotechnology (AG-BIO)Center for Agricultural Biotechnology (CAB)
Kasetsart University Kamphaeng Saen Campus
Genome assembly and annotation workshop 7 August 2018
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NGS workflow
Sample Library preparation Sequencing Bioinformatics
What you get out is never better than what you put in!!
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Next Generation Sequencing (NGS)
• generally produces short reads or short read pairs
• Fastq
• <~200 bases
• Sanger ~ 1000 bases
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Next Generation Sequencing (NGS)
Ye H, et al. Pharmaceutics. 2015 Nov 23;7(4):523-41
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Big data
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Main concept
Biological data
Biological information
Bioinformatics analysis
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Applications of NGS
• DNA sequencing
• de Novo sequencing
• Resequencing
• RNA sequencing
• Small RNA sequencing
• ChIP-Seq
• …
Lee, Chien-Yueh, et al. Translational Cancer Research 2.1 (2013): 33-45.
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DNA/Genome sequencing
• De novo assembly
• Single nucleotide variant (SNV) detection
• Structural variation detection
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De Novo Plant and Animal Sequencing
• focused on a novel species
• de novo sequencing is a first step toward
understanding the genetic underpinnings of organism
• long-paired read and mate-pair sequence data
• subsequent to discover SNPs and other genetic
variations.
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Plant and Animal Genotyping
• Whole-Genome Resequencing
• create fine map traits
• Genotyping by Sequencing (GBS)
• test a genotype-phenotype hypothesis
• Quantitative trait loci (QTL) analyses
• large-scale Genome-Wide Association Study (GWAS)
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A brief flow chart of genetic studies using NGS
Ye H, et al. Pharmaceutics. 2015 Nov 23;7(4):523-41
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Sequence Annotation
• Give biological meaning to sequence
• BLAST (Basic Local Alignment Search Tool)
• Type of SNP• Non-coding region• Coding region
• Synnonymous• Nonsynonymous
• Missense• Nonsense
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Comparative genomics
http://darlinglab.org/mauve/mauve.html
• rearrangement and inversion
• Requirement• .gbk (GenBank)• FastA, • Multi-FastA
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Comparative genomics
• MUMMER 3+
• http://mummer.sourceforge.net/
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Genome coverage
C=LN/G
C = Coverage (X),L = Read length (bp),G = Haploid genome size (bp)N = Number of reads.
What is the coverage depth of human genome? If I have 150 million reads of 100 bp, paired end sequence.
http://apps.bioconnector.virginia.edu/covcalc/
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Soil and Agricultural Metagenomics
• study of large microbial communities directly in
their natural environment
• important information about diverse microbial
populations associated with animal and plant
development
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Soil and Agricultural Metagenomics
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Metagenomics analysisMicrobial community composition and function insights
• OTUs : Operational Taxonomic Units
• Alpha-diversity analysis
• Beta-diversity analysis
clustering reads based on similarity (default is 97%)
(diversity within a sample)
(diversity across samples)
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Metagenomics analysisMicrobial community composition and function insights
www.ebi.ac.uk/metagenomics
113993 data sets
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• Transgenic and control lines
• Investigating associated microbiome by 16S rRNAgene profiling
• Three year after planting
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Transgenic banana lines resistant to banana Xanthomonas wilt.
• Amplicon sequencing-based 16S rRNA gene profiling
Nimusiima J. et al. Scientific Reports. 2015
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Transgenic banana lines resistant to banana Xanthomonas wilt.
• The expression of the transgenes did not result in
changes in the diversity of Gammaproteobacteria,
the closest relatives of the target pathogen.
• In this field experiment, the expression of the resistance genes appears to have no consequences for non-target rhizobacteria and endophytes.
Nimusiima J. et al. Scientific Reports. 2015
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RNA sequencing data analysis
• De novo transcriptome assembly
• Expression profiling analysis
• Variant calling
• Splice site identification
• Isoform detection
• Novel transcripts
• transcriptomic epigenetics
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RNA sequencing
Condition 1(normal colon)
Condition 2(colon tumor)
Isolate RNAs
Sequence ends
100s of millions of paired reads10s of billions bases of sequence
Generate cDNA, fragment, size select, add linkersSamples of interest
Map to genome, transcriptome, and
predicted exon junctions
Downstream analysis
Paired-end reads(e.g. 2 x 100 bp)
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RNA-seq analysisAlternative splicing
Differences in gene expression
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DNA & RNA -seq analysis
Transposable element in Human ~ 46 %
Genome analysis
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DNA & RNA -seq analysis
Transposable element in Human
http://sysbio.chula.ac.th/enherv/index.php
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Chimeric transcript detection using RNA-Seq
• HERVs are associated with up-regulated genes in SLE.
Enhancer exon1 exon2 exon3LTR
Alt-Promoter exon1 exon2 exon3LTR
* HERV : Human Endogenous Retrovirus
SLE : Systemic Lupus Erythematosus
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Raw reads
Trinity transcripts Solo LTRshg19RefSeq
SRA
SRA toolkit
FastQC
Trinity
blastblastx
Annotation process
Predicted chimeric transcripts
Candidate chimeric transcripts
UCSC BLAT Manual curation process
Chimeric transcripts
Validation process
De novo approach
Haas BJ, et al., 2013. Nat Protoc. Aug;8(8):1494-512
Repbase
30
GSE72509Illumina HiSeq 250099 SLE18 Control
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Detected chimeric patterns
LTR Predicted chimeric transcript
start end start end length4 287 1 281 283 Only LTR transcript
1 362 495 149 1958 LTR insertion in mRNA1 374 1849 2201 3208
1 128 126 1 1004 start of LTR, end of transcript
127 343 1 211 1249323 355 1 33 405 end of LTR, start of transcript
mRNA
LTR
LTRmRNA
LTRmRNA
mRNALTR31
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THE1C
predicted IFI44-THE1C chimeric transcript
IFI44
IFI44 - higher expression in SLE
IFN-α-inducible genes are candidate biomarkers for disease activity
KA Kirou. et al. 2004. Arthritis Res Ther. 6(Suppl 3):9132
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IFI44-THE1C chimeric amplicons.
The expected size is 1740 bps.
normSLEM
1500 bp
3000 bp
neg
33
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THE1C-forward amplicon
IFI44-reverse amplicon
IFI44-THE1B chimeric amplicons.
• Molecular cloning for precise amplicon sequencing 34
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miRNA
• A microRNA (abbreviated miRNA)
• a small non-coding RNA molecule ~ 22 nucleotides
• found in plants, animals and some viruses
• functions in RNA silencing
• post-transcriptionalregulation of gene expression.
https://en.wikipedia.org/wiki/MicroRNA#/media/File:MiRNA.svg
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Small RNA sequencing
• Small RNA prediction
• Micro RNA (miRNA)
• piwi-interacting RNA (piRNA)
• small interfering RNA (siRNA)
• miRNA characterization
• Target Prediction
• Differential Expression Analysis
• Novel miRNA Discovery
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ChIP-Seq
• Chromatin ImmunoPrecipitation followed by next-
generation sequencing
• Identification of protein binding sites on the DNA
• DNA–protein complexes are cross-linked and
precipitated using an antibody
• transcription factor (TF) binding sites as well as histone
modifications on a genome-wide scale
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ChIP-Seq process
Cross-linked ChIP (XChIP)Native ChIP (NChIP)
Information based on Illumina data sheet
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ChIP-Seq
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Bioinformatics for plant breeding
Genotype
Sequence variationsSNP, in/del, SSR
Association analysis
Phenotype
Quantitative trait locus (QTL) Genome-wide association study (GWAS)
Genetic resources
- collection- conservation
Development of new varieties
Genotyping by sequencing (GBS)
Marker Assisted Selection (MAS)
Plant breeding process
Germplasm manipulation
Bioinformatics databases and tools
Genomic Selection (GS)Genomic estimated
breeding value (GEBV)
Genome sequencing
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Bioinformatics for plant breeding
Genotype
Sequence variationsSNP, in/del, SSR
Association analysis
Phenotype
Quantitative trait locus (QTL) Genome-wide association study (GWAS)
Genetic resources
- collection- conservation
Development of new varieties
Genotyping by sequencing (GBS)
Marker Assisted Selection (MAS)
Plant breeding process
Germplasm manipulation
Bioinformatics databases and tools
Genomic Selection (GS)Genomic estimated
breeding value (GEBV)
Genome sequencing
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Germplasm/resource evaluation
• Germplasm bank core-collections
• useful for allele-mining of candidate genes and fine-mapping QTLs
• Draft genome : De novo sequencing
• Genotyping
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Resequencing
• Alternative to de novo assembly:align every read to a reference genome
• Requires less coverage, but not easy to find “new”genetic material
• Often used to detection genetic variation
Genome Res. 2009 Jun; 19(6)http://www.genomecompiler.com
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STRUCTURE / Fast-STRUCTURE
K = hypothetical number of subpopulations. Look for the optimal number of subpopulations
44
• Detects the underlying genetic population among a set of individuals genotyped at multiple markers
• Computes the proportion of the genome of an individual originating from each inferred population (quantitative clustering method)
• Calculate K: when approaching a plateau or continues increasing slightly
• For the TRUE value of K, find the smallest value of K that captures the major structure in the data
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PCA analysis of population structure
• Using all SNPs in each accession/individual in the population gives too many data for clear analysis
• Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset. Often used to reduce number of variables and so make data easy to explore and visualize.
• the principal components are linear combinations of the original variables. The first principal component is the direction along which the samples show the largest variation. etc.
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Bioinformatics for plant breeding
Genotype
Sequence variationsSNP, in/del, SSR
Association analysis
Phenotype
Quantitative trait locus (QTL) Genome-wide association study (GWAS)
Genetic resources
- collection- conservation
Development of new varieties
Genotyping by sequencing (GBS)
Marker Assisted Selection (MAS)
Plant breeding process
Germplasm manipulation
Bioinformatics databases and tools
Genomic Selection (GS)Genomic estimated
breeding value (GEBV)
Genome sequencing
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SNP Genotyping technology
• Sequencing (High throughput)• capillary electrophoresis• Next Generation Sequencing
• Array (High throughput)• hybridization signal
• Electrophoresis• single-strand conformation polymorphism (SSCP)
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single-strand conformation polymorphism (SSCP)
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SNP Array
• DNA microarray
• allele-specific
oligonucleotide (ASO) probes.
• Fragmented nucleic
acid sequences
• Hybridization signal
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Resequencing : Sequence Capture
- Discover genetic variation in genome
- Require reference genome
- Shallow sequencing approach
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Genotyping By
Sequencing
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DArTSeq
• Genotyping By Sequencing (GBS)
• genome complexity reduction
• selection of genome fraction corresponding
predominantly to active genes
http://www.diversityarrays.com
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Bioinformatics for plant breeding
Genotype
Sequence variationsSNP, in/del, SSR
Association analysis
Phenotype
Quantitative trait locus (QTL) Genome-wide association study (GWAS)
Genetic resources
- collection- conservation
Development of new varieties
Genotyping by sequencing (GBS)
Marker Assisted Selection (MAS)
Plant breeding process
Germplasm manipulation
Bioinformatics databases and tools
Genomic Selection (GS)Genomic estimated
breeding value (GEBV)
Genome sequencing
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Strategies for Molecular Breeding
• Genomic Selection (Meuwissen, Hayes & Goddard 2001)
• Genome-wide markers that are used to develop prediction models for estimating genomic breeding values
• Association Breeding (Breseghello & Sorrells 2006)
• Association mapping methods are superimposed on a conventional hybridization/selection/testing program for allele discovery and validation
• Marker Assisted Selection• Only significant markers are used for selection, usually qualitative
traits
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Quantitative Trait Loci (QTL)
• Traits with phenotypes that vary continuously
• Most traits are influenced by many genes
• A chromosomal location associated with variation trait
• large effect QTLs can be used in MAS to improve a trait
• Influenced by the environment
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Example:
Carotenoid content in Maize
Yield
Poland et al. (2009). Trends in Plant Science, Resistance to southern corn leaf blight
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Quantitative trait phenotypes
Phenotype= Genotype + Environment +Error
Effect of the genetic makeup
Souza LM, et al. 2013. PLOS ONE 8(4): e61238
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Genotyping
Sequence variationsSNP, in/del, SSR
Genomic selection (GS)
Genotyping by sequencing
“The rapid selection of superior genotypes
and accelerates the breeding cycle”
Crossa J. et al. Trends Plant Sci. 2017 Nov;22(11)
Genomic Selection
• A marker assisted selection on a genome wide scale.
• uses statistical models to predict how a plant will perform (Breeding Values), before it is field-tested.
• ASreml• rrBLUB, BGLR, EMMREML
Genomic Estimated Breeding Value (GEBV)
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Bioinformatics for plant breeding
Genotype
Sequence variationsSNP, in/del, SSR
Association analysis
Phenotype
Quantitative trait locus (QTL) Genome-wide association study (GWAS)
Genetic resources
- collection- conservation
Development of new varieties
Genotyping by sequencing (GBS)
Marker Assisted Selection (MAS)
Plant breeding process
Germplasm manipulation
Bioinformatics databases and tools
Genomic Selection (GS)Genomic estimated
breeding value (GEBV)
Genome sequencing
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Marker development strategy
Sequence qc
De novo assembly
SSR identification
Primer design
Primer screening
Primer3
BLAST
Validation
Set of informative markers
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Sequence with information
>SSR
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Associations reported for certain traits.
• Genome annotation
• Transcriptomic variation
http://pathview.r-forge.r-project.org/
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NGS community
http://seqanswers.com/forums/index.php https://www.biostars.org
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“Use the right tool for
the right job”
“Knowledge of biology is vital in
the interpretation of
computational results.”