Curated variation benchmarks for challenging medically relevant autosomal genes

February 8, 2022

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Curated variation benchmarks for challenging medically relevant autosomal genes

AbstractThe repetitive nature and complexity of some medically relevant genes poses a challenge for their accurate analysis in a clinical setting. The Genome in a Bottle Consortium has provided variant benchmark sets, but these exclude nearly 400 medically relevant genes due to their repetitiveness or polymorphic complexity. Here, we characterize 273 of these 395 challenging…

Abstract

The repetitive nature and complexity of some medically relevant genes poses a scenario for his or her excellent analysis in a clinical environment. The Genome in a Bottle Consortium has offered variant benchmark sets, however these exclude nearly 400 medically relevant genes ensuing from their repetitiveness or polymorphic complexity. Right here, we train 273 of these 395 sharp autosomal genes the utilize of a haplotype-resolved total-genome assembly. This curated benchmark experiences over 17,000 single-nucleotide variations, 3,600 insertions and deletions and 200 structural variations every for human genome reference GRCh37 and GRCh38 loyal through HG002. We stamp that flawed duplications in both GRCh37 or GRCh38 lead to reference-particular, overlooked variants for short- and lengthy-read applied sciences in medically relevant genes, alongside with CBS, CRYAA and KCNE1. When masking these flawed duplications, variant purchase can support from 8% to 100%. Forming benchmarks from a haplotype-resolved total-genome assembly would maybe presumably turn into a prototype for future benchmarks masking the total genome.

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Records availability

The PacBio HiFi reads historical to generate the hifiasm assembly for the benchmark are within the NCBI Sequence Read Archive with accession numbers SRR10382245, SRR10382244, SRR10382249, SRR10382248, SRR10382247 and SRR10382246. The v1.00 benchmark VCF and BED files, as well to Liftoff gene annotations, assembly–assembly alignments and variant calls, are readily obtainable at https://label.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/AshkenazimTrio/HG002_NA24385_son/CMRG_v1.00/, and as a DOI at https://doi.org/10.18434/mds2-2475. Right here is released as a separate benchmark from v4.2.1, because it contains a microscopic part of the genome, it has different traits from the mapping-primarily primarily based v4.2.1 and v4.2.1 good contains microscopic variants. The utilize of v4.2.1 and the CMRG benchmarks as two separate benchmarks enables customers to receive broader efficiency metrics for plenty of of the genome and for a microscopic online page online of seriously sharp genes, respectively. The masked GRCh38 reference, now not too lengthy within the past updated to v2 with extra flawed duplications from the Telomere-to-Telomere Consortium, is below https://label.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/references. We point out the utilize of v3.0 GA4GH/GIAB stratification mattress files supposed to be used with hap.py when benchmarking, which would maybe presumably per chance be readily obtainable at https://label.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/genome-stratifications/. These stratifications consist of mattress files equivalent to flawed duplications and collapsed duplications in GRCh38. All records don’t receive any restrictions, as the HG002 sample has an begin consent from the Non-public Genome Mission.

Code availability

Scripts historical to manufacture the CMRG benchmark and generate figures and tables for the manuscript are readily obtainable at https://github.com/usnistgov/cmrg-benchmarkset-manuscript. The beforehand developed assembly, which modified into historical as the premise of this benchmark, modified into from hifiasm v0.11.

A quantity of begin supply scheme modified into historical for variant calling for the critiques of the benchmark, alongside with NextDenovo2.2-beta.0, DRAGEN 3.6.3, NeuSomatic’s submission for the PrecisionFDA fact scenario v2 (ref. ¹²) (BWA-MEM⁵⁰ version 0.7.17-r1188 (https://github.com/lh3/bwa) and GATK version gatk-4.1.4.1 (https://gatk.broadinstitute.org/hc/en-us)), Parabricks_DeepVariant (Parabricks Pipelines DeepVariant v3.0.0_2 (https://developer.nvidia.com/clara-parabricks)), Sentieon (DNAscope) version sentieon_release_201911 (https://www.sentieon.com/products/#dnaseq), BWA-MEM and Strelka2 (BWA-MEM version 0.7.17-r1188 (https://github.com/lh3/bwa) and Strelka2 version 2.9.10 (https://github.com/Illumina/strelka)), BWA-MEM⁵⁰(v0.7.8), Picard tools (https://broadinstitute.github.io/picard/) (ver. 1.83), GATK⁵² (v3.4-0), GATK (v3.5), BWA-MEM v0.7.15-r1140, SAMtools⁵³ v1.3, Picard v2.10.10, GATK v3.8, DELLY⁵⁴ v0.8.5, GRIDSS⁵⁵ v2.9.4, LUMPY⁵⁶ v0.3.1, Manta⁵⁷ v1.6.0, Wham⁵⁸ v1.7.0, NanoPlot⁶⁰ v1.27.0, Filtlong v0.2.0, minimap2 (refs. ^40,60) v2.17-r941, cuteSV v1.0.8, Sniffles⁶¹ v1.0.12, SURVIVOR⁵⁹ v1.0.7, BWA v0.7.15, GATK v3.6, Java v1.8.0_74 (OpenJDK), Picard Tools v2.6.0, Sambamba⁶³ v0.6.7, Samblaster⁶⁴ v0.1.24, Samtools v1.9, DeepVariant v1.0 and Liftoff32 v1.4.0.

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Acknowledgements

We thank the Genome Reference Consortium for his or her curation efforts of GRCh37 and GRCh38 (https://www.genomereference.org), especially V.A. Schneider and P.A. Kitts from the Nationwide Institutes of Health (NIH)/NCBI for increasing the falsely duplicated regions that ought to be masked in GRCh38. We thank S. Miller at NIST for serving to type readily obtainable benchmark sets and READMEs. Certain industrial tools, devices or materials are identified to adequately specify experimental prerequisites or reported results. Such identification doesn’t mean advice or endorsement by NIST, nor does it point out that the tools, devices or materials identified are necessarily the most efficient readily obtainable for the intention. C.F. modified into funded by Instituto de Salud Carlos III (PI20/00876) and Ministerio de Ciencia e Innovación (RTC-2017-6471-1; AEI/FEDER, UE), cofinanced by the European Regional Style Fund ‘A Strategy of Making Europe’ from the European Union, and Cabildo Insular de Tenerife (CGIEU0000219140). J.M.L.-S. modified into funded by Consejería de Educación-Gobierno de Canarias and Cabildo Insular de Tenerife (BOC 163, 24/08/2017). F.J.S. and M.M. modified into supported by the NIH (UM1 HG008898). C.X. modified into supported by the Intramural Evaluate Program of the Nationwide Library of Treatment, NIH. K.H.M. modified into supported by the NIH/Nationwide Human Genome Evaluate Institute (R01 1R01HG011274-01 and U01 1U01HG010971). H.L. modified into supported by the NIH (R01 HG010040 and U01 HG010961). C.E.M. thanks funding from the WorldQuant Foundation, NASA (NNX14AH50G), the Nationwide Institutes of Health (R01MH117406, R01CA249054, R01AI151059, P01CA214274) and the Leukemia and Lymphoma Society (LLS) (MCL7001-18, LLS 9238-16, LLS-MCL7001-18).

Writer records

Writer notes

These authors contributed equally: Chen-Shan Chin, Justin M. Zook, Fritz J. Sedlazeck.

Affiliations

Field materials Measurement Laboratory, Nationwide Institute of Standards and Skills, Gaithersburg, MD, USA
Justin Wagner, Nathan D. Olson, Lindsay Harris, Jennifer McDaniel & Justin M. Zook
Department of Records Science, Dana-Farber Cancer Institute, Boston, MA, USA
Haoyu Cheng & Heng Li
DNAnexus, Inc., Mountain Leer, CA, USA
Arkarachai Fungtammasan, Yih-Chii Hwang, Richa Gupta & Chen-Shan Chin
Pacific Biosciences, Menlo Park, CA, USA
Aaron M. Wenger & William J. Rowell
Human Genome Sequencing Heart, Baylor School of Treatment, Houston, TX, USA
Ziad M. Khan, Jesse Farek, Yiming Zhu, Aishwarya Pisupati, Medhat Mahmoud & Fritz J. Sedlazeck
Nationwide Heart for Biotechnology Records, Nationwide Library of Treatment, Nationwide Institutes of Health, Bethesda, MD, USA
Chunlin Xiao
Genomic Treatment Heart, Kids’s Mercy Kansas City, Kansas City, MO, USA
Byunggil Yoo
Roche Sequencing Choices, Santa Clara, CA, USA
Sayed Mohammad Ebrahim Sahraeian
Department of Pediatrics, Division of Genetic Treatment, University of Washington and Seattle Kids’s Clinical institution, Seattle, WA, USA
Danny E. Miller
Department of Genome Sciences, University of Washington, Seattle, WA, USA
Danny E. Miller
Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
David Jáspez, José M. Lorenzo-Salazar, Adrián Muñoz-Barrera, Luis A. Rubio-Rodríguez & Carlos Flores
CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
Carlos Flores
Evaluate Unit, Clinical institution Universitario N.S. de Candelaria, Santa Cruz de Tenerife, Spain
Carlos Flores
Unique York Genome Heart, Unique York, NY, USA
Giuseppe Narzisi, Uday Shanker Evani & Wayne E. Clarke
Bionano Genomics, San Diego, CA, USA
Joyce Lee
Department of Physiology and Biophysics, Weill Cornell Treatment, Unique York, NY, USA
Christopher E. Mason
Invitae, San Francisco, CA, USA
Stephen E. Lincoln
UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
Karen H. Miga
Sanders-Brown Heart on Growing outdated, University of Kentucky, Lexington, KY, USA
Tag T. W. Ebbert
Department of Interior Treatment, Division of Biomedical Informatics, University of Kentucky, Lexington, KY, USA
Tag T. W. Ebbert
Department of Neuroscience, University of Kentucky, Lexington, KY, USA
Tag T. W. Ebbert
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
Alaina Shumate
Heart for Computational Biology, Whiting College of Engineering, Johns Hopkins University, Baltimore, MD, USA
Alaina Shumate

Contributions

Conceptualization: J.W., N.D.O., A.F., K.H.M., S.E.L., M.T.W.E., H.L., C.-S.C., J.M.Z. and F.J.S. Records curation: J.W., N.D.O. and J.M. Formal analysis – benchmark: J.W., N.D.O., J.M. and J.M.Z. Formal analysis – assembly: H.C., A.S., H.L. and C.-S.C. Methodology: J.W., H.C., H.L., C.-S.C., J.M.Z. and F.J.S. Mission administration: J.W., J.M.Z. and F.J.S. Resources: C.X. Application: J.W. and N.D.O. Supervision: C.-S.C., J.M.Z. and F.J.S. Validation: J.W., N.D.O., L.H., J.M., H.C., A.F., Y.-C.H., R.G., A.M.W., W.J.R., Z.M.K., J.F., Y.Z., A.P., M.M., C.X., B.Y., S.M.E.S., D.J., J.M.L.-S., A.M.-B., L.A.R.-R., C.F., G.N., U.S.E., S.E.C., J.L., H.L., C.-S.C., J.M.Z. and F.J.S. Visualization: J.W., N.D.O., H.C., H.L. and C.-S.C. Writing – fashioned draft: J.W., L.H., C.-S.C., J.M.Z. and F.J.S. Writing – evaluation and editing: J.W., N.D.O., D.E.M., J.L., C.E.M., S.E.L., M.T.W.E., C.-S.C., J.M.Z. and F.J.S.

Corresponding authors

Correspondence to Chen-Shan Chin, Justin M. Zook or Fritz J. Sedlazeck.

Ethics declarations

Competing pursuits

A.M.W. and W.J.R. are workers and shareholders of Pacific Biosciences. A.F., Y.-C.H, R.G., and C.-S.C. are workers and shareholders of DNAnexus. S.M.E.S. is an employee of Roche. J.L. is a outdated employee and shareholder of Bionano Genomics. S.E.L. modified into an employee of Invitae. F.J.S. has backed shuttle from Pacific Biosciences and Oxford Nanopore Technologies. The last authors uncover no competing pursuits.

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Nature Biotechnology thanks Adam Ameur, Christian Marshall and different, anonymous, reviewer(s) for his or her contribution to the undercover agent evaluation of this work.

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Supplementary records

Supplementary Records

Supplementary Figures 1–17, Notes 1–5 and Desk 1.

Supplementary Records 1

Additional traits of excessive-priority clinical genes.

Supplementary Records 2

Overlaps of the 5,038 genes on GRCh38 predominant assembly between both HG002 GRCh38 v4.2.1 and HG002 hifiasm v0.11.

Supplementary Records 3

Benchmarking of the hifiasm v0.11 assembly-primarily primarily based variants known as with dipcall in opposition to the GIAB v4.2.1 benchmark for HG002.

Supplementary Records 4

Benchmarking statistics in opposition to CMRG benchmark and overview callsets.

Supplementary Records 5

Ebook curation results for overview and fashioned errors in v0.02.03 microscopic variant benchmark.

Supplementary Records 6

Primer designs and response prerequisites for Long-Vary PCR and Sanger confirmation.

Supplementary Records 7

Genes excluded from the CMRG benchmarks, with in all probability causes for exclusion annotated for GRCh38 within the closing column.

Supplementary Records 8

Instructions for BWA-GATK variant calling on fashioned GRCh38 reference.

Supplementary Records 9

Instructions for BWA-GATK variant calling on v1 masked GRCh38 reference.

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Wagner, J., Olson, N.D., Harris, L. et al. Curated variation benchmarks for sharp medically relevant autosomal genes. Nat Biotechnol (2022). https://doi.org/10.1038/s41587-021-01158-1

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