Variant Annotation and Interpretation:

Tools and Public Data

Functional Genomics Symposium, Qatar

December 12, 2015

Gabe Rudy

@gabeinformatics

VP Product Management and Engineering

Golden Helix

My Background

Golden Helix- Founded in 1998- Genetic association software- Analytic services- Over ten-thousand users worldwide- Over 800 customer citations in journals

Products I Build with My Team- SNP & Variation Suite (SVS) - Research- VarSeq – Clinical & NGS Research- GenomeBrowse (Free!) - All

What I Do (Coding, Bioinformatics)- Build tools, build pipelines of tools- Blog- Participate in GA4GH, HGVS Discussions,

NCBI EVAC

Topics

• ACMG Guidelines for Variant Interpretation

• Necessity of visualization

• Public data and tools for annotations

• Accurate gene annotations, choice of “clinical transcripts”

• Variant representation, “left-shifting” and HGVS nomenclature

• Warehousing variants

ACMG Guidlines

Five-tier terminology system:- “pathogenic,” “likely pathogenic,” “uncertain significance,” “likely

benign,” and “benign” - Mendelian and mitochondrial variants- Variant assessment guidelines as combined from 11 labs- Report variant with condition and inheritance pattern

- c.1521_1523delCTT (p.Phe508del), pathogenic, cystic fibrosis, autosomal recessive

- Likely pathogenic, likely benign mean 90% certainty- Provide genomic coordinates (g.)- Transcript selection up to lab to define "clinically relevant"

You Need Visualization, Not Just a Table to Interpret

Recovery of Frameshift (in Supercentenarian)

Visualization of Variants to Aid Interpretation

Variants + Genomic Context- Where it is in gene- Annotations that match, don’t match- Other variants in cohort / warehouse- Locality and rare/common variants- Locality of pathogenic variants

Interpreting Multiple Transcript Alignment Evidence

- BAM files provide more than is in VCF- Phasing of same-ready mutations- Examine sites of related samples with

no variants called

Visualization

Free Genome Browsers:- IGV

- Popular desktop by Broad- UCSC

- Web-based, most extensive annotations

- GenomeBrowse- Designed to be publication ready- Smooth zoom and navigation- Built in all Golden Helix curated

annotations (stream or download)

Annotation with Public Data

Pop databases- Don't assume “population” == healthy controls- ExAC, EVS, 1kG, dbSNP

Disease databases:- OMIM, ClinVar, HGMD

In-Silico Prediction- Whether missense change is damaging

- 65–80% accurate when examining known disease variants- Expect over-sensitive, but can be a low-pass filter to call "likely benign”- Expect correlation between tools as often using similar underlying pieces of evidence.

- Splicing: predicting effect on splicing on genes

RefSeqGenes and Human Reference

Annotations are Hard!

HGVS is a standard that is not computable- Tries to serve different goals- Many representations of same variant- Difficult when used as identifier, but only

alternative is genomic representation (g.)

Transcripts- Transcript set choice extremely important- Hard to curate with meaningful tx attributes.

Public Data Curation- ClinVar: multi-record lines, bits in VCF/XML- NHLBI: MAF vs AAF, splitting “glob” fields- 1kG: No genotype counts- ExAC: Multi-allelic splitting, left-align- ClinVitae (and COSMIC): only HGVS- dbNSFP: Abbreviations and aggregate scores

Versioning and Issues- ClinVar missing ~5K pathogenic in VCF- dbSNP patches without version changes

Population Catalogs

1000 Genomes (WGS, Exome, SNP Array)- Many releases, most recent now

standardized, still incrementally updated- 2,500 genomes – Phase3

“ESP” (NHLBI 6,500 Exomes) (a.k.a EVS)- Had many releases, now V2-SSA137 0.0.30- European American / African American only

ExAC (Broad 61,486 Exomes v0.3)- Many sub-populations

Supercentenarians (110+ yo, 17 WGS)- Available as raw Complete Genomic data- Requires normalizing to match Illumina NGS

InSilico Predictions

Non-synonymous functional predictions- SIFT, Polyphen2, LFT, MutationTaster,

MutationAccessor, FATHMM

Conservation- GERP++, PhyloP, phastCons

All-In-One Scores- CADD, VAAST,VEST3, DANN, FATHM-MKL,

MetaSVM and MetaLR- Use machine learning, “feature selection”,

train and predict on public databases- Can predicting synonymous and intergenic

dbNSFP 3.0 – 82M precomputed scores- N of 6 Voting on prediction algorithms

RNA Splicing Effect (dbscSNV)- 5+ splice algorithms, can pre-compute- −3 to +8 at the 5’, −12 to +2 at the 3’

Disease Databases

ClinVar- Voluntary submissions of lab- Use 5-tier classification (variant + phenotype pairs)- Star-rating of variants- Lab owns submission, can revoke and monitor

status

ClinVitae (Invitae curated, not updated)

OMIM- Gene to Phenotype documentation- Expertly curated, hand updated- Changes dynamically- Small list of cited / implicated variants

HGMD- Commercially supported- Best linkage of (possible) publication to

variant/genes- Classifications not directly trusted

Your own Lab (more later)

Web-Based Annotation Tools

NCBI Variant Reporter- HGVS Annotation- PubMed, ClinVar links

SeattleSeq- NHLBI supported- Some public annotations

Ensembl VEP- Same as running VEP locally

Scripps Genome ADVISER- Out of of date annotations- Scripps Wellderly Frequencies- Splice Site Predictions- Basic Java GUI for filtering

Mutalyzer – HGVS only

Variant Annotation Tools

snpEff- Open source, commercial use allowed- Tx Annotation, HGVS output- Limited public annotations

ANNOVAR- Academic/Commercial split- Many public annotations- Non-standard Tx prioritization

Ensembl VEP- Ensembl tx only, HGVS output- Limited public annotations

VarSeq- Commercially supported- Largest public annotation repo- RefSeq/Ensembl tx, HGVS- Clinical Tx, many export formats- Integrated data transformations

Reference Sequence and Transcripts

RefSeqGenes – mRNA sequence archive, with mappings to genomes- Provided mappings to Locus Reference Gene (LRG) database- Use genome mappings by NCBI (through genome annotation builds). NOT UCSC- “Clinically Relevant” metric:

- LRG if available- Longest if tied

Ensembl – defined directly against the human genome- More inclusive of genes discovered with high-throughput methods- Gencode subset – similar to RefSeqGenes in size / definition

Each have unique Accessions and Version Numbers- Newer releases GRCh38- GRCh37 mappings not being updated (unfortunately)

Reference Sequence Versus Gene Sequence

EMG1 on GRCh37 “Gap” of the mRNA coding sequence versus reference seq: Handled differently by 3 different “gene alignments”

Reference Sequence Versus Gene Sequence

EMG1 on GRCh38 Reference sequence patched, no gap Alignments agree

RefSeq Accession Not Sufficient for Var-Tx Interaction

RefSeq defines transcripts as mRNA sequence NCBI “Annotation Releases” (like v105) provides alignments using “Splign” UCSC pulls RefSeq mRNA and aligns themselves using “BLAT” They can choose equally valid but different alignments for the same accession This alignment of NM_052814.3 places the exon at dramatically different loci. Will result in different annotations of any variant overlapping these exons

Variant Representation and Normalization

Allelic Primitives- AG/CT -> A/C & G/T- AT/G -> A/- & T/G- May have different annotations

Left Align- NGS standard, not consistent

historically- May be needed after primitives- HGVS -> 3’ shift (right for forward)

Multi-Allelic (2 Non-Ref Alleles)- Each non-ref has own annotations- Pop level should be “split” for counts

HGVS, Transcript Projection- Dependent on Tx->Genome Mapping- hgvs-eval: Benchmarking tool in

progress

Left-Align Annotations

Using a Smith-Waterman algorithm to left-align variants from public databases show non-obvious differences

NGS alignment and variant calling always left-aligned

Left-align your database so they can be annotated

Left-Align Delta F508 to Make it Match

Called in Both Locations – Affect Frequencies

Allelic Split + Left Align. Discover Existing Freq

Multi Allelic

The Supercentenarian annotation found records for both alternates, and looks like this:

Trio Analysis, Variant is a G/T/C (Reference G, Alternates of T/C):

Variant Warehouse

"Clinical laboratories should implement an internal system to track all sequence variants identified in each gene and clinical assertions when reported.

This is is important for tracking genotype–phenotype correlations and the frequency of variants in affected and normal populations."

Why Warehouse?

A place to archive full VCFs of every sequenced sample (by assay/test)

Query and retrieve subsets of data at any time

Ask the Variant Warehouse:- Have I ever seen this variant in my

previous test samples?- At what frequency? (counts as well)- Does this gene contain other rare variants

in my cohort?- Did I provide a pathogenicity assessment

for this variant? Has that changed?- Has ClinVar changed since that

assessment was initially made?- Have I put this variant into a clinical report

for any previous samples?

NM_002626.4:c.1877G>C in PFKL

NP_002617.3:p.Arg626Pro missense mutation

Predicted damaging by 4/5 functional predictions

VEST3: 0.948, GERP++: 4.59

ExAC and 1kG have a G>A, but G>C is novel

Variants in region are extremely rare (G>C ExAC 4 of 122,364 alleles) – 0.003%

No ClinVar variants for gene

OMIM entry has no known disease association

PubMed search shows few recent articles: Most recent 1998 paper showed- phosphofructokinase (PFKL) overexpressed in Down syndrome (DS) - Transgenic PFKL mice had an abnormal glucose metabolism with reduced clearance

rate from blood and enhanced metabolic rate in brain.

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35 LoF Variants, None Homozygous

Questions?