Identifying sequence variants in whole genome sequencing data

Transcription

1 Identifying sequence variants in whole genome sequencing data Saumya Kumar MRC-MGU

2 Outline of the talk Genomic approaches at Harwell o Methods to identify mouse models for diseases. Next Generation Sequencing: DNA Seq o Mutation detection (workflow analysis). o Mutation consequence of SNVs, INDELs and SVs o Mutational effects on protein structure and function Data Resources

3 Genomic approaches at Harwell Genotype driven screens. o International Mouse Phenotyping Consortium (IMPC): To build a resource of knockout mice and associated encyclopaedia of gene functions. Phenotype driven screens ENU Mutagenesis : To identify novel mouse models of human disease. o Harwell Ageing Screen: To identify mouse models for studying mutations that lead to early and late onset of diseases.

4 Harwell Ageing Mutant Screen pedigree production ENU C3H X X X X C57BL/6 (G0) G2 female offspring mated with G1 father +/+ +/m1 WT X +/m1 +/m2 +/m3 G1 offspring (Heterozygous) +/+ +/+ +/+ +/m1 +/m1 +/m1 +/m1 m1/m1 G3 Heterozygous and homozygous mutant offspring 100 mice per pedigree pedigrees over 5 years Produce, age and screen 20,000-25,000 mice Phenotyping

5 Next Generation Sequencing Massively parallel sequencing technologies to provide whole genome or exome sequence data. An efficient, low-cost and high-throughput sequencing method. Major sequencing platforms used are: o Illumina bp read length, reads are of same size o Roche 454- up to 1kbp, reads of variable lengths o Ion torrent - ~200 bp read length

6 Different Mutations detected using NGS Single Nucleotide Variations (SNVs) or point mutations. Substitution of a single nucleotide base. INDEL: small insertions/deletions. Size varies from 1bp to 100bps. Structural Variations(SVs), genomic variations involving large number of nucleotides (101bp-kbs) and more.

7 Analysis Workflow (SNVs and INDELs) DNA samples sent to Oxford for sequencing RAW SEQUENCE DATA REFERENCE GUIDED ASSEMBLY ALIGN ED READS ALIGNMENT AND ASSEMBLY Illumina paired-end BWA MGP dbsnp HARWELL INBRED SNPS DETECT HIGH CONFIDENCE SNPS AND INDELs FILTER KNOWN SNPS AND INDELs IDENTIFY ENU POSSIBLE SNPS AND INDELs SNP and INDEL DETECTION GATK SNP AND INDEL ANNOTATION DATABASE VISUALISATI ON - GENOME BROWSER ANNOTATION AND DISSEMINATION NGS-SNP VEP IGV

8 NGS: Alignment and sequence variation finding Single Nucleotide Variation (SNV) INDEL

9 Mutation Consequence :SNV SNVs can be coding or non-coding. Coding mutations are usually deleterious to the protein structure and function. These are: missense, splice-site and nonsense mutations Non-coding mutations are synonymous, intronic, intergenic, upstream, downstream, 5 UTR, 3 UTR, lincrna,other RNA etc. UPSTREAM 5`UTR INTRON EXON 3`UTR DOWNSTREAM INTERGENIC Coding mutations Non-Coding mutations

10 Harwell Ageing Screen NGS Coding Non-Coding 0% 0% initiator_codon 3% 1% 4% 7% missense splice_acceptor splice_donor 24% Promoter Associated 47% lincrna splice_region 29% other RNA(inc mirna, snrna) stop_gained 85% stop_lost The average high confidence coding changes is ~45 per genome. Coding mutation rate is 1.76 Mb -1 Using ENSEMBL and ENCODE we found approximately 198 SNVs are located in regulatory regions of the genome, with the greatest number found in promoter regions (47%) and lincrnas (29%). Non-coding mutation rate is comparable at 1.78 Mb -1 Cloned mutations Total Early Late Missense Stop gained Splice mutant 19*/9 10/1 3/2

11 Mutation Consequence: INDEL Protein-coding DNA is divided into codons. INDELs can alter these codons in a gene, causing frameshifts mutations leading to either nonsense mutations and/or missense mutations. E.g. A single base pair deletion in the gene Crb1 causes frameshift mutation which leads to blindness in C57B6N mice.(simon et. al, 2013)

12 Mutational Consequence on protein Coding SNVs(missense) and INDEL mutations can be damaging or tolerant to the protein structure and function. Various tools exist that can evaluate the mutation effect on the protein. E.g. Sift, Provean, Polyphen2 etc. These tools give a score to the missense/indels mutations indicating their tolerant or damaging behaviour.

13 Mutational Consequence on protein: tools Tool Notes Organism Reference CONSERVATION SiFT SiFT Predicts effect of SNVs Human and known mouse SNPs (dbsnp) (Kumar et al. 2009) MutationAssessor Predicts effect of SNVs Human data: cancer studies (Reva et al. 2011) Provean Predicts effect of SNVs, insertions and deletions Organism independent (Choi et al. 2012) STRUCTURE SNPs3D Sequence, 3-D structure, biological networks Human, useful for association physical properties of amino acids. studies MACHINE LEARNING / MULTIPLE DATASETS Polyphen-2 Implements MSA, amino acid changes, evolutionary Human, can be adapted for mouse conservation, SNV site hypermutability. Uses a naïve Bayes genome (standalone) classifier. MutationTaster2 Predicts amino acid substitution affects on protein function based on sequence homology and the Machine learning on evolutionary conservation, splice site changes, gene expression and protein features. Uses a Bayes classifier. (Yue et al. 2006) Can be applied to naturally occurring and laboratoryinduced missense mutations. (Adzhubei et al. 2010) Human, uses 1000G data (Schwarz et al. 2014) SNAP Site Directed Mutator(SDM) Uses neural networks for evolutionary conservation, secondary structure, solvent accessibility Uses a potential free energy function for protein stability; algorithm uses environment-specific substitution tables to calculate stability, predicts disease association. Human (Bromberg and Rost 2007) Organism independent (Worth et al. 2011) POST TRANSLATIONAL MODIFICATIONS PhosSNP Predicts SNV effect on PTM Human (Ren et al. 2010) SNPeffect Predicts SNV effect on PTM, structural features of proteins, subcellular localization and interactions Human (De Baets et al. 2012) PROTEIN-PROTEIN INTERACTIONS MuSiC Predicts SNV effect on pathways (Cancer studies). To segregate passenger mutations from truly significant mutations. human (Dees et al. 2012)

14 Mutational Consequence on protein Map3k1: It is 1493 aa long protein. Map3k1 knockout viable on mixed genetic background, but not viable on C57B6J background. Mutation at amino acid 184, changing Leucine to Arginine. Sift predictions suggest that the amino acid change is going to affect the protein function with a score of A score of <= 0.05 is considered to be damaging to the protein.

15 Mutational Consequence on protein structure Mapk1 mutation from Leucine to Arginine Wildtype Mutant Wildtype Mutant

16 SifT: Worked example The worked example is on SOD1 ALS mutation. Things required: Sequence of the gene: >SOD1 MAMKAVCVLKGDGPVQGTIHFEQKASGEPVVLSGQITGLTE GQHGFHVHQYGDNTQGCTSAGPHFNPHSKKHGGPADEER HVGDLGNVTAGKDGVANVSIEDRVISLSGEHSIIGRTMVVH EKQDDLGKGGNEESTKTGNAGSRLACGVIGIAQ Substitution position and aa : D84G SiFT link-

17 Structural Variations Structural variations e.g. deletions can span segments to whole genes. Insertions refers to extra DNA segment(s) added to the reference genome. Inversion can be explained as 180 flip in the DNA segment. Tandem Duplication refers to multiple copies of a DNA segment.

18 Analysis Workflow (Structural Variations) RAW SEQUENCE DATA REFERENCE GUIDEDED ASSEMBLY ALIGN ED READS ALIGNMENT AND ASSEMBLY Illumina paired-end BWA SV DETECTION REALIGNMENT OF READS DETECT SV BREAKPOINTS (Deletions, Insertions, Inversions, Tandem Duplicates) PINDEL SV DETECTION FILTER KNOWN SVs FILTER ON RANGE MGP FILTERATION HARWELL SPECIFIC SVs ANNOTATION ANNOTATION MANUAL CURATION Deletion; Structural OWN SCRIPT Variation(SV) IGV

19 Mutation Consequence: SV Since structural variations involve large number of base pairs, therefore if they are spanning over exons of a gene they are very likely to be detrimental to the gene/protein for the organism. E.g. a 4kb deletion in Dclre1c gene involves deletion of exons 10 and 11 in C57B6J mice. This deletion leads to immune system, hematopoietic system and endocrine/exocrine glands phenotypes. (Barthels et.al, 2013)

20 Data resources Mouse Genome Project (17 genomes) MouseBook

21 Mouse Genome Project Mouse Genome Project data at Sanger Institute. Whole genome sequencing data of up to 36 inbred mice strains to date. Provides information on inbred SNPs, INDELs and Structural Variations. Search Page:

22 MouseBook MRC Harwell s portal for all the Ageing screen data. Provides phenotype data for mice from all the pedigrees over various parameter and time points. o Graphs for each pedigree and advanced searches Holds the complete range of ENU mutations identified in F1 mice (coding and non-coding) from whole genome sequencing. Functional annotations Mutational Consequence on protein.

23 Bioinformatic Resources Genome Browsers: Ensembl UCSC Mutant Mouse Resources MouseBook Mouse Genome Informatics (MGI) NCBI Functional Analysis Gene Ontology G:Profiler EBI: BLAST Aligners InterproScan (Protein Domain Analysis) Protein Families pfam Smart Superfamily TreeFam Protein-protein/gene interactions Reactome Brenada String GeneMania KEGG Protein Structure Predictors nfold3/intfold Phyre GenThreader Pymol I-Tasser

24 MGP: Gene Search Step1: Load anger/mouse_snpviewer/rel Step2: Search on Gene name or genomic location. Start typing Cops5 and select that gene. Step3: Select SNP/INDEL types, SV types and strains of interest (scroll below). Press Search

25 MGP: Gene Search Select tabs for SNPs, INDELs and SV information Allele in different strains SNP consequence in the gene. Data can be saved in text-format or csv format Reference SNP IDs for known SNPs dbsnp.

26 MGP: Location Search Step2: Click on All. Press Search Step1: Search by Location: Enter 10: in the location box

27 MGP: Location Search Shows intergenic SNPs in strains

28 SiFT: Sorting Intolerant From Tolerant The worked example in the next slides is on SOD1 ALS mutation. Things required: Sequence of the gene Substitution position and aa

29 Worked Example: SiFT Step1: Load Step2: Click on SIFT Sequence

30 Worked Example: SiFT Step3: Copy-Paste the sequence in fasta format from the handout Step4: Copy-Paste the substitution Step5: Click on Submit Query

31 Worked Example: SiFT Step6: Click on Predictions of substitutions entered

32 MouseBook: Phenotype Heatmap Step1: Load Step 3: Scroll to locate MUTA-PED- C3PDE-49 Step 4: Click on Body weight parameter for this pedigree Step2: Click on Phenotype Heatmap

33 MouseBook: Phenotype Heatmap Shows other significant annotations for this pedigree This page shows the different time points at which the data was collected for body weight parameter. Step 5: Select on any test month to view graphs. Step 6: Hover over the data points to see details of a mouse at any time point.

34 MouseBook: SNVs and small Indels Step1: Load Step2: Click on SNVs and small indels

35 MouseBook: SNVs and small indels List of SNVs from the ageing database and APN. Selection can be made on any one of these: Based on protein coding information, Gene, Chromosome, Genomic Position,Type of Mutation, Mutational Consequence and SNV source. Step 3: Click on the SNV