Comprehensive Physiology Wiley Online Library

Computational and Experimental Analysis of Genetic Variants

Full Article on Wiley Online Library



Abstract

Genomics has grown exponentially over the last decade. Common variants are associated with physiological changes through statistical strategies such as Genome‐Wide Association Studies (GWAS) and quantitative trail loci (QTL). Rare variants are associated with diseases through extensive filtering tools, including population genomics and trio‐based sequencing (parents and probands). However, the genomic associations require follow‐up analyses to narrow causal variants, identify genes that are influenced, and to determine the physiological changes. Large quantities of data exist that can be used to connect variants to gene changes, cell types, protein pathways, clinical phenotypes, and animal models that establish physiological genomics. This data combined with bioinformatics including evolutionary analysis, structural insights, and gene regulation can yield testable hypotheses for mechanisms of genomic variants. Molecular biology, biochemistry, cell culture, CRISPR editing, and animal models can test the hypotheses to give molecular variant mechanisms. Variant characterizations can be a significant component of educating future professionals at the undergraduate, graduate, or medical training programs through teaching the basic concepts and terminology of genetics while learning independent research hypothesis design. This article goes through the computational and experimental analysis strategies of variant characterization and provides examples of these tools applied in publications. © 2022 American Physiological Society. Compr Physiol 12:3303‐3336, 2022.

Figure 1. Figure 1. Sequencing to association studies for rare and common variants. Created with BioRender. Genomics can be performed by SNP arrays or genome/exome sequencing chemistries, followed by various statistical strategies for rare or common variants.
Figure 2. Figure 2. EBI/NHGRI GWAS catalog. (A) Associations per year. (B) The number of associations per trait is ranked based on the number of associations. Data was pulled from the GWAS catalog on March 6, 2021.
Figure 3. Figure 3. Population variants and linkage disequilibrium for rs12126142. The population allele frequency is listed to the left in diverse populations based on gnomAD. Below rs12126142 is listed the chromosome annotation (chromosome_location_wildtype_minor allele). LD was imputed from the 1000 genomes project phase 3 using European imputation.
Figure 4. Figure 4. GTEx v8 eQTL and sQTL analysis. (A) The number of genes with GTEx annotated significant eQTLs (blue) or sQTLs (red) in each of 49 different tissues. (B) A volcano plot of log2 fold change (x‐axis) relative to the −log10 p‐value (y‐axis) for all significant eQTLs. (C) A plot of mean allele frequency (MAF) relative to the ‐Log10 p‐value (y‐axis) for all significant sQTLs.
Figure 5. Figure 5. The eQTL for PSPHP1 on chromosome 7. (A) Violin plot rs6593279 in skeletal muscle tissue for each genotype. (B) LD analysis for rs6593279 using 1000 genomes project phase 3 East Asian imputation.
Figure 6. Figure 6. GTEx sQTLs for rs56105022 on CNIH4. (A) Violin plots for variants in skeletal muscle and cultured fibroblasts. (B) Exons of CNIH4 with splicing shown. In red is the alternative splicing event of panel A with the resulting splicing isoform shown below in red. (C) The genome browser view of the splicing site (red) in respect to the exon structure and chromosome positions. (D) The Ensembl table of isoforms with the resulting splice site highlighted, which does not code for a protein. (E) LD imputed from the 1000 genomes project phase 3 using European imputation for rs56105022.
Figure 7. Figure 7. Representative plot of colocalized (A) or not colocalized (B) associations between two traits. The black line represents the significance cutoff.
Figure 8. Figure 8. Epigenetic regulation dataset overlap to association regions. (A) Schematic of various epigenetic insights measured in ENCODE. (B) Representative GWAS hit in red box looking at the overlap of peaks for a transcription factor (TF, blue) or histone modification (red) relative to LD block for the site. Created with BioRender.
Figure 9. Figure 9. Noncoding RNA. (A) A breakdown of the biotype annotations within the Gencode38 database. The top 6 groups are labeled with the percentage of total transcripts. (B) The number of transcripts for several of the noncoding RNA groups. (C) The percent of transcripts in each biotype that have publications (gray) or do not have publications (red). (D) The size of long noncoding RNA (lncRNA) transcripts. (E‐F) The number of disease associations (E) or VEP (F) annotated consequences for various noncoding RNA found within the ncRNAVar database (www.liwzlab.cn/ncrnavar/ncrnavar.html).
Figure 10. Figure 10. Missense variants in GWAS LD blocks. (A) Plot of GWAS associations (x‐axis) from the GWAS catalog and the top‐ranked p‐value (y‐axis) for that variant. Outlier missense variants are labeled. (B) The ALDH2 missense variant E504K.
Figure 11. Figure 11. Alzheimer's Disease GWAS. (A) All SNPs in GWAS database for Alzheimer's Disease showing the number of LD SNPs (x‐axis) and the significance (y‐axis). (B) rs429358 allele frequencies in gnomAD populations. (C) LD imputed from the 1000 genomes project phase 3 using African imputation for rs429358. (D) rs429358 results in the missense variant APOE C130R.
Figure 12. Figure 12. Stroke GWAS. (A) All SNPs in GWAS database for stroke showing the number of LD SNPs (x‐axis) and the significance (y‐axis). (B) rs6025 allele frequencies in gnomAD populations. (C) LD imputed from the 1000 genomes project phase 3 using American imputation for rs6025. (D) rs6025 results in the missense variant F5 R534Q.
Figure 13. Figure 13. Chronic Kidney Disease (CKD). (A) All SNPs in GWAS database for Chronic Kidney Disease (CKD) showing the number of LD SNPs (x‐axis) and the significance (y‐axis). (B) rs2147896 allele frequencies in gnomAD populations. (C) LD imputed from the 1000 genomes project phase 3 using African imputation for rs2147896. (D) rs2147896 results in an eQTL for PYROXD2. (E) rs17319721 allele frequencies in gnomAD populations. (F) LD imputed from the 1000 genomes project phase 3 using American imputation for rs17319721. (G) rs17319721 results in altered gene regulation of a shortened SHROOM3 isoform through disruption of TCF7L2 binding and looping between an enhancer and promoter.
Figure 14. Figure 14. Inheritance and de novo rare variants of the genome. 63 is a representative number of de novo variants, with each individual of the pedigree have added variants in subsequent generations.
Figure 15. Figure 15. Large‐scale population whole genomes completed in gnomAD and TOPMed. Data extracted on March 8, 2021.
Figure 16. Figure 16. ClinVar variants (A) Clinical annotation of 774,966 ClinVar variants. (B) Molecular type of 774,966 ClinVar variants. (C) Percent of each molecular type that falls into pathogenic (red) or VUS (cyan) annotations. Data were extracted from the UCSC Genome Browser on October 14, 2020.
Figure 17. Figure 17. ClinVar genes. (A) Plot of the number of genes within the grouped pathogenic (red) or VUS (cyan) variants. (B) Scatter plot of the number of pathogenic (x‐axis) vs. VUS (y‐axis) with the top genes labeled.
Figure 18. Figure 18. Nonsense‐mediated decay (NMD). As it reads mRNA, the ribosome (cyan/green) can remove RNA interacting proteins (magenta) that form exon junction complexes (EJC) near splice sites. When a nonsense variant arises, the 3′UTR is enlarged, with the accumulation of decay‐inducing complex proteins (red) that initiate the mRNA's degradation to prevent partial protein production. Created with BioRender.
Figure 19. Figure 19. Trio genomes: from variants to narrowed list. Created with BioRender.
Figure 20. Figure 20. ACMG59 STRING plot. The 59 genes were processed with the STRING tools (https://string‐db.org/) for known associations and enrichments in the genes. Enriched pathways are labeled at the top, and colors of gene nodes correspond to terms.
Figure 21. Figure 21. Narrowing rare missense variants in SHROOM3 with pathogenic outcomes in Chronic Kidney Disease. Modified, with permission, from Prokop JW, et al., 2018 124.
Figure 22. Figure 22. ABCC8 evolution. (A) Phylogenic tree of 221 sequences for ABCC8. Human is the red box. Values at the nodes represent the clustering of 50 bootstrapped trees. (B) Conservation score for each codon. (C) Conservation score on a 21‐codon sliding window, where each site is added to the scores of 10 before and 10 codons after to smooth out enriched motifs/domains. (D) Pictoral of the transmembrane domains and the ATP binding sites. (E) Conservation of the two ATP binding site amino acids. Amino acids in red are those annotated in UniProt for association with familial hyperinsulinemic hypoglycemia.
Figure 23. Figure 23. Screening variants for ABCC8 using protein model and variant analysis workflow.
Figure 24. Figure 24. Viral Induced Genetics and RNASEH2B. (A) NMD of RNASEH2B alleles. (B) Pictorial of viral inhibition of NMD. (C) Viral activation of dominant‐negative genetics of patriation RNASEH2B protein inhibiting the protein complex. It was created with BioRender.


Figure 1. Sequencing to association studies for rare and common variants. Created with BioRender. Genomics can be performed by SNP arrays or genome/exome sequencing chemistries, followed by various statistical strategies for rare or common variants.


Figure 2. EBI/NHGRI GWAS catalog. (A) Associations per year. (B) The number of associations per trait is ranked based on the number of associations. Data was pulled from the GWAS catalog on March 6, 2021.


Figure 3. Population variants and linkage disequilibrium for rs12126142. The population allele frequency is listed to the left in diverse populations based on gnomAD. Below rs12126142 is listed the chromosome annotation (chromosome_location_wildtype_minor allele). LD was imputed from the 1000 genomes project phase 3 using European imputation.


Figure 4. GTEx v8 eQTL and sQTL analysis. (A) The number of genes with GTEx annotated significant eQTLs (blue) or sQTLs (red) in each of 49 different tissues. (B) A volcano plot of log2 fold change (x‐axis) relative to the −log10 p‐value (y‐axis) for all significant eQTLs. (C) A plot of mean allele frequency (MAF) relative to the ‐Log10 p‐value (y‐axis) for all significant sQTLs.


Figure 5. The eQTL for PSPHP1 on chromosome 7. (A) Violin plot rs6593279 in skeletal muscle tissue for each genotype. (B) LD analysis for rs6593279 using 1000 genomes project phase 3 East Asian imputation.


Figure 6. GTEx sQTLs for rs56105022 on CNIH4. (A) Violin plots for variants in skeletal muscle and cultured fibroblasts. (B) Exons of CNIH4 with splicing shown. In red is the alternative splicing event of panel A with the resulting splicing isoform shown below in red. (C) The genome browser view of the splicing site (red) in respect to the exon structure and chromosome positions. (D) The Ensembl table of isoforms with the resulting splice site highlighted, which does not code for a protein. (E) LD imputed from the 1000 genomes project phase 3 using European imputation for rs56105022.


Figure 7. Representative plot of colocalized (A) or not colocalized (B) associations between two traits. The black line represents the significance cutoff.


Figure 8. Epigenetic regulation dataset overlap to association regions. (A) Schematic of various epigenetic insights measured in ENCODE. (B) Representative GWAS hit in red box looking at the overlap of peaks for a transcription factor (TF, blue) or histone modification (red) relative to LD block for the site. Created with BioRender.


Figure 9. Noncoding RNA. (A) A breakdown of the biotype annotations within the Gencode38 database. The top 6 groups are labeled with the percentage of total transcripts. (B) The number of transcripts for several of the noncoding RNA groups. (C) The percent of transcripts in each biotype that have publications (gray) or do not have publications (red). (D) The size of long noncoding RNA (lncRNA) transcripts. (E‐F) The number of disease associations (E) or VEP (F) annotated consequences for various noncoding RNA found within the ncRNAVar database (www.liwzlab.cn/ncrnavar/ncrnavar.html).


Figure 10. Missense variants in GWAS LD blocks. (A) Plot of GWAS associations (x‐axis) from the GWAS catalog and the top‐ranked p‐value (y‐axis) for that variant. Outlier missense variants are labeled. (B) The ALDH2 missense variant E504K.


Figure 11. Alzheimer's Disease GWAS. (A) All SNPs in GWAS database for Alzheimer's Disease showing the number of LD SNPs (x‐axis) and the significance (y‐axis). (B) rs429358 allele frequencies in gnomAD populations. (C) LD imputed from the 1000 genomes project phase 3 using African imputation for rs429358. (D) rs429358 results in the missense variant APOE C130R.


Figure 12. Stroke GWAS. (A) All SNPs in GWAS database for stroke showing the number of LD SNPs (x‐axis) and the significance (y‐axis). (B) rs6025 allele frequencies in gnomAD populations. (C) LD imputed from the 1000 genomes project phase 3 using American imputation for rs6025. (D) rs6025 results in the missense variant F5 R534Q.


Figure 13. Chronic Kidney Disease (CKD). (A) All SNPs in GWAS database for Chronic Kidney Disease (CKD) showing the number of LD SNPs (x‐axis) and the significance (y‐axis). (B) rs2147896 allele frequencies in gnomAD populations. (C) LD imputed from the 1000 genomes project phase 3 using African imputation for rs2147896. (D) rs2147896 results in an eQTL for PYROXD2. (E) rs17319721 allele frequencies in gnomAD populations. (F) LD imputed from the 1000 genomes project phase 3 using American imputation for rs17319721. (G) rs17319721 results in altered gene regulation of a shortened SHROOM3 isoform through disruption of TCF7L2 binding and looping between an enhancer and promoter.


Figure 14. Inheritance and de novo rare variants of the genome. 63 is a representative number of de novo variants, with each individual of the pedigree have added variants in subsequent generations.


Figure 15. Large‐scale population whole genomes completed in gnomAD and TOPMed. Data extracted on March 8, 2021.


Figure 16. ClinVar variants (A) Clinical annotation of 774,966 ClinVar variants. (B) Molecular type of 774,966 ClinVar variants. (C) Percent of each molecular type that falls into pathogenic (red) or VUS (cyan) annotations. Data were extracted from the UCSC Genome Browser on October 14, 2020.


Figure 17. ClinVar genes. (A) Plot of the number of genes within the grouped pathogenic (red) or VUS (cyan) variants. (B) Scatter plot of the number of pathogenic (x‐axis) vs. VUS (y‐axis) with the top genes labeled.


Figure 18. Nonsense‐mediated decay (NMD). As it reads mRNA, the ribosome (cyan/green) can remove RNA interacting proteins (magenta) that form exon junction complexes (EJC) near splice sites. When a nonsense variant arises, the 3′UTR is enlarged, with the accumulation of decay‐inducing complex proteins (red) that initiate the mRNA's degradation to prevent partial protein production. Created with BioRender.


Figure 19. Trio genomes: from variants to narrowed list. Created with BioRender.


Figure 20. ACMG59 STRING plot. The 59 genes were processed with the STRING tools (https://string‐db.org/) for known associations and enrichments in the genes. Enriched pathways are labeled at the top, and colors of gene nodes correspond to terms.


Figure 21. Narrowing rare missense variants in SHROOM3 with pathogenic outcomes in Chronic Kidney Disease. Modified, with permission, from Prokop JW, et al., 2018 124.


Figure 22. ABCC8 evolution. (A) Phylogenic tree of 221 sequences for ABCC8. Human is the red box. Values at the nodes represent the clustering of 50 bootstrapped trees. (B) Conservation score for each codon. (C) Conservation score on a 21‐codon sliding window, where each site is added to the scores of 10 before and 10 codons after to smooth out enriched motifs/domains. (D) Pictoral of the transmembrane domains and the ATP binding sites. (E) Conservation of the two ATP binding site amino acids. Amino acids in red are those annotated in UniProt for association with familial hyperinsulinemic hypoglycemia.


Figure 23. Screening variants for ABCC8 using protein model and variant analysis workflow.


Figure 24. Viral Induced Genetics and RNASEH2B. (A) NMD of RNASEH2B alleles. (B) Pictorial of viral inhibition of NMD. (C) Viral activation of dominant‐negative genetics of patriation RNASEH2B protein inhibiting the protein complex. It was created with BioRender.
References
 1.1000 Genomes Project Consortium, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA. An integrated map of genetic variation from 1092 human genomes. Nature 491: 56‐65, 2012. DOI: 10.1038/nature11632.
 2.1000 Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA, Abecasis GR. A global reference for human genetic variation. Nature 526: 68‐74, 2015. DOI: 10.1038/nature15393.
 3.Abugessaisa I, Noguchi S, Carninci P, Kasukawa T. The FANTOM5 computation ecosystem: Genomic information hub for promoters and active enhancers. Methods Mol Biol 1611: 199‐217, 2017. DOI: 10.1007/978‐1‐4939‐7015‐5_15.
 4.Acuna‐Hidalgo R, Veltman JA, Hoischen A. New insights into the generation and role of de novo mutations in health and disease. Genome Biol 17: 241, 2016. DOI: 10.1186/s13059‐016‐1110‐1.
 5.Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR. A method and server for predicting damaging missense mutations. Nat Methods 7: 248‐249, 2010. DOI: 10.1038/nmeth0410‐248.
 6.Afrin A, Prokop JW, Underwood A, Uhl KL, VanSickle EA, Baruwal R, Wajda M, Rajasekaran S, Bupp C. NAA10 variant in 38‐week‐gestation male patient: A case study. Cold Spring Harb Mol Case Stud 6, 2020. DOI: 10.1101/mcs.a005868.
 7.Amberger JS, Bocchini CA, Schiettecatte F, Scott AF, Hamosh A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res 43: D789‐D798, 2015. DOI: 10.1093/nar/gku1205.
 8.Apweiler R, Bairoch A, Wu CH, Barker WC, Boeckmann B, Ferro S, Gasteiger E, Huang H, Lopez R, Magrane M, Martin MJ, Natale DA, O'Donovan C, Redaschi N, Yeh L‐SL. UniProt: The universal protein knowledgebase. Nucleic Acids Res 32: D115‐D119, 2004. DOI: 10.1093/nar/gkh131.
 9.Ashkenazy H, Erez E, Martz E, Pupko T, Ben‐Tal N. ConSurf 2010: Calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res 38: W529‐W533, 2010. DOI: 10.1093/nar/gkq399.
 10.Augusto BM, Lake P, Scherr CL, Couch FJ, Lindor NM, Vadaparampil ST. From the laboratory to the clinic: Sharing BRCA VUS reclassification tools with practicing genetics professionals. J Community Genet 9: 209‐215, 2018. DOI: 10.1007/s12687‐017‐0343‐3.
 11.Babenko AP, Polak M, Cavé H, Busiah K, Czernichow P, Scharfmann R, Bryan J, Aguilar‐Bryan L, Vaxillaire M, Froguel P. Activating mutations in the ABCC8 gene in neonatal diabetes mellitus. N Engl J Med 355: 456‐466, 2006. DOI: 10.1056/NEJMoa055068.
 12.Barrangou R, Doudna JA. Applications of CRISPR technologies in research and beyond. Nat Biotechnol 34: 933‐941, 2016. DOI: 10.1038/nbt.3659.
 13.Baujat G, Le Merrer M. Ellis‐van Creveld syndrome. Orphanet J Rare Dis 2: 27, 2007. DOI: 10.1186/1750‐1172‐2‐27.
 14.Beckmann JS, Estivill X, Antonarakis SE. Copy number variants and genetic traits: Closer to the resolution of phenotypic to genotypic variability. Nat Rev Genet 8: 639‐646, 2007. DOI: 10.1038/nrg2149.
 15.Berman H, Henrick K, Nakamura H, Markley JL. The worldwide Protein Data Bank (wwPDB): Ensuring a single, uniform archive of PDB data. Nucleic Acids Res 35: D301‐D303, 2007. DOI: 10.1093/nar/gkl971.
 16.Bertina RM, Koeleman BP, Koster T, Rosendaal FR, Dirven RJ, de Ronde H, van der Velden PA, Reitsma PH. Mutation in blood coagulation factor V associated with resistance to activated protein C. Nature 369: 64‐67, 1994. DOI: 10.1038/369064a0.
 17.Bilinovich SM, Uhl KL, Lewis K, Soehnlen X, Williams M, Vogt D, Prokop JW, Campbell DB. Integrated RNA sequencing reveals epigenetic impacts of diesel particulate matter exposure in human cerebral organoids. Dev Neurosci 42: 195‐207, 2020. DOI: 10.1159/000513536.
 18.Blom N, Gammeltoft S, Brunak S. Sequence and structure‐based prediction of eukaryotic protein phosphorylation sites. J Mol Biol 294: 1351‐1362, 1999. DOI: 10.1006/jmbi.1999.3310.
 19.Blom N, Sicheritz‐Pontén T, Gupta R, Gammeltoft S, Brunak S. Prediction of post‐translational glycosylation and phosphorylation of proteins from the amino acid sequence. Proteomics 4: 1633‐1649, 2004. DOI: 10.1002/pmic.200300771.
 20.Boehme AK, Esenwa C, Elkind MSV. Stroke risk factors, genetics, and prevention. Circ Res 120: 472‐495, 2017. DOI: 10.1161/CIRCRESAHA.116.308398.
 21.Boyle AP, Hong EL, Hariharan M, Cheng Y, Schaub MA, Kasowski M, Karczewski KJ, Park J, Hitz BC, Weng S, Cherry JM, Snyder M. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res 22: 1790‐1797, 2012. DOI: 10.1101/gr.137323.112.
 22.Brooks BR, Brooks CL, Mackerell AD, Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M. CHARMM: The biomolecular simulation program. J Comput Chem 30: 1545‐1614, 2009. DOI: 10.1002/jcc.21287.
 23.Brown GR, Hem V, Katz KS, Ovetsky M, Wallin C, Ermolaeva O, Tolstoy I, Tatusova T, Pruitt KD, Maglott DR, Murphy TD. Gene: A gene‐centered information resource at NCBI. Nucleic Acids Res 43: D36‐D42, 2015. DOI: 10.1093/nar/gku1055.
 24.Bult CJ, Eppig JT, Kadin JA, Richardson JE, Blake JA, Mouse Genome Database Group. The Mouse Genome Database (MGD): Mouse biology and model systems. Nucleic Acids Res 36: D724‐D728, 2008. DOI: 10.1093/nar/gkm961.
 25.Bupp CP, Schultz CR, Uhl KL, Rajasekaran S, Bachmann AS. Novel de novo pathogenic variant in the ODC1 gene in a girl with developmental delay, alopecia, and dysmorphic features. Am J Med Genet A 176: 2548‐2553, 2018. DOI: 10.1002/ajmg.a.40523.
 26.Buysse K, Delle Chiaie B, Van Coster R, Loeys B, De Paepe A, Mortier G, Speleman F, Menten B. Challenges for CNV interpretation in clinical molecular karyotyping: Lessons learned from a 1001 sample experience. Eur J Med Genet 52: 398‐403, 2009. DOI: 10.1016/j.ejmg.2009.09.002.
 27.Calore M, De Windt LJ, Rampazzo A. Genetics meets epigenetics: Genetic variants that modulate noncoding RNA in cardiovascular diseases. J Mol Cell Cardiol 89: 27‐34, 2015. DOI: 10.1016/j.yjmcc.2015.10.028.
 28.Carter NP. Methods and strategies for analyzing copy number variation using DNA microarrays. Nat Genet 39: S16‐S21, 2007. DOI: 10.1038/ng2028.
 29.Castoldi E, Simioni P, Kalafatis M, Lunghi B, Tormene D, Girelli D, Girolami A, Bernardi F. Combinations of 4 mutations (FV R506Q, FV H1299R, FV Y1702C, PT 20210G/A) affecting the prothrombinase complex in a thrombophilic family. Blood 96: 1443‐1448, 2000.
 30.Chang AT, Liu Y, Ayyanathan K, Benner C, Jiang Y, Prokop JW, Paz H, Wang D, Li H‐R, Fu X‐D, Rauscher FJ, Yang J. An evolutionarily conserved DNA architecture determines target specificity of the TWIST family bHLH transcription factors. Genes Dev 29: 603‐616, 2015. DOI: 10.1101/gad.242842.114.
 31.Chatr‐Aryamontri A, Breitkreutz B‐J, Heinicke S, Boucher L, Winter A, Stark C, Nixon J, Ramage L, Kolas N, O'Donnell L, Reguly T, Breitkreutz A, Sellam A, Chen D, Chang C, Rust J, Livstone M, Oughtred R, Dolinski K, Tyers M. The BioGRID interaction database: 2013 update. Nucleic Acids Res 41: D816‐D823, 2013. DOI: 10.1093/nar/gks1158.
 32.Choi Y, Chan AP. PROVEAN web server: A tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics 31: 2745‐2747, 2015. DOI: 10.1093/bioinformatics/btv195.
 33.Cirulli ET, Goldstein DB. Uncovering the roles of rare variants in common disease through whole‐genome sequencing. Nat Rev Genet 11: 415‐425, 2010. DOI: 10.1038/nrg2779.
 34.Clark MM, Hildreth A, Batalov S, Ding Y, Chowdhury S, Watkins K, Ellsworth K, Camp B, Kint CI, Yacoubian C, Farnaes L, Bainbridge MN, Beebe C, Braun JJA, Bray M, Carroll J, Cakici JA, Caylor SA, Clarke C, Creed MP, Friedman J, Frith A, Gain R, Gaughran M, George S, Gilmer S, Gleeson J, Gore J, Grunenwald H, Hovey RL, Janes ML, Lin K, McDonagh PD, McBride K, Mulrooney P, Nahas S, Oh D, Oriol A, Puckett L, Rady Z, Reese MG, Ryu J, Salz L, Sanford E, Stewart L, Sweeney N, Tokita M, Van Der Kraan L, White S, Wigby K, Williams B, Wong T, Wright MS, Yamada C, Schols P, Reynders J, Hall K, Dimmock D, Veeraraghavan N, Defay T, Kingsmore SF. Diagnosis of genetic diseases in seriously ill children by rapid whole‐genome sequencing and automated phenotyping and interpretation. Sci Transl Med 11, 2019. DOI: 10.1126/scitranslmed.aat6177.
 35.Corder EH, Saunders AM, Strittmatter WJ, Schmechel DE, Gaskell PC, Small GW, Roses AD, Haines JL, Pericak‐Vance MA. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science 261: 921‐923, 1993. DOI: 10.1126/science.8346443.
 36.COVID‐19 Host Genetics Initiative. The COVID‐19 Host Genetics Initiative, a global initiative to elucidate the role of host genetic factors in susceptibility and severity of the SARS‐CoV‐2 virus pandemic. Eur J Hum Genet 28: 715‐718, 2020. DOI: 10.1038/s41431‐020‐0636‐6.
 37.Das S, Forer L, Schönherr S, Sidore C, Locke AE, Kwong A, Vrieze SI, Chew EY, Levy S, McGue M, Schlessinger D, Stambolian D, Loh P‐R, Iacono WG, Swaroop A, Scott LJ, Cucca F, Kronenberg F, Boehnke M, Abecasis GR, Fuchsberger C. Next‐generation genotype imputation service and methods. Nat Genet 48: 1284‐1287, 2016. DOI: 10.1038/ng.3656.
 38.Davis MA, Larimore EA, Fissel BM, Swanger J, Taatjes DJ, Clurman BE. The SCF‐Fbw7 ubiquitin ligase degrades MED13 and MED13L and regulates CDK8 module association with mediator. Genes Dev 27: 151‐156, 2013. DOI: 10.1101/gad.207720.112.
 39.de Knijff P, van den Maagdenberg AM, Frants RR, Havekes LM. Genetic heterogeneity of apolipoprotein E and its influence on plasma lipid and lipoprotein levels. Hum Mutat 4: 178‐194, 1994. DOI: 10.1002/humu.1380040303.
 40.Desmet F‐O, Hamroun D, Lalande M, Collod‐Béroud G, Claustres M, Béroud C. Human Splicing Finder: An online bioinformatics tool to predict splicing signals. Nucleic Acids Res 37: e67, 2009. DOI: 10.1093/nar/gkp215.
 41.Dickinson ME, Flenniken AM, Ji X, Teboul L, Wong MD, White JK, Meehan TF, Weninger WJ, Westerberg H, Adissu H, Baker CN, Bower L, Brown JM, Caddle LB, Chiani F, Clary D, Cleak J, Daly MJ, Denegre JM, Doe B, Dolan ME, Edie SM, Fuchs H, Gailus‐Durner V, Galli A, Gambadoro A, Gallegos J, Guo S, Horner NR, Hsu C‐W, Johnson SJ, Kalaga S, Keith LC, Lanoue L, Lawson TN, Lek M, Mark M, Marschall S, Mason J, McElwee ML, Newbigging S, Nutter LMJ, Peterson KA, Ramirez‐Solis R, Rowland DJ, Ryder E, Samocha KE, Seavitt JR, Selloum M, Szoke‐Kovacs Z, Tamura M, Trainor AG, Tudose I, Wakana S, Warren J, Wendling O, West DB, Wong L, Yoshiki A, International Mouse Phenotyping Consortium, Jackson Laboratory, Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS), Charles River Laboratories, MRC Harwell, Toronto Centre for Phenogenomics, Wellcome Trust Sanger Institute, RIKEN BioResource Center, MacArthur DG, Tocchini‐Valentini GP, Gao X, Flicek P, Bradley A, Skarnes WC, Justice MJ, Parkinson HE, Moore M, Wells S, Braun RE, Svenson KL, de Angelis MH, Herault Y, Mohun T, Mallon A‐M, Henkelman RM, Brown SDM, Adams DJ, Lloyd KCK, McKerlie C, Beaudet AL, Bućan M, Murray SA. High‐throughput discovery of novel developmental phenotypes. Nature 537: 508‐514, 2016. DOI: 10.1038/nature19356.
 42.Diederichs S. The four dimensions of noncoding RNA conservation. Trends Genet 30: 121‐123, 2014. DOI: 10.1016/j.tig.2014.01.004.
 43.Dinkel H, Michael S, Weatheritt RJ, Davey NE, Van Roey K, Altenberg B, Toedt G, Uyar B, Seiler M, Budd A, Jödicke L, Dammert MA, Schroeter C, Hammer M, Schmidt T, Jehl P, McGuigan C, Dymecka M, Chica C, Luck K, Via A, Chatr‐Aryamontri A, Haslam N, Grebnev G, Edwards RJ, Steinmetz MO, Meiselbach H, Diella F, Gibson TJ. ELM‐‐the database of eukaryotic linear motifs. Nucleic Acids Res 40: D242‐D251, 2012. DOI: 10.1093/nar/gkr1064.
 44.Durek P, Schudoma C, Weckwerth W, Selbig J, Walther D. Detection and characterization of 3D‐signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins. BMC Bioinformatics 10: 117, 2009. DOI: 10.1186/1471‐2105‐10‐117.
 45.ENCODE. Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489: 57‐74, 2012. DOI: 10.1038/nature11247.
 46.ENCODE Project Consortium, Birney E, Stamatoyannopoulos JA, Dutta A, Guigó R, Gingeras TR, Margulies EH, Weng Z, Snyder M, Dermitzakis ET, Thurman RE, Kuehn MS, Taylor CM, Neph S, Koch CM, Asthana S, Malhotra A, Adzhubei I, Greenbaum JA, Andrews RM, Flicek P, Boyle PJ, Cao H, Carter NP, Clelland GK, Davis S, Day N, Dhami P, Dillon SC, Dorschner MO, Fiegler H, Giresi PG, Goldy J, Hawrylycz M, Haydock A, Humbert R, James KD, Johnson BE, Johnson EM, Frum TT, Rosenzweig ER, Karnani N, Lee K, Lefebvre GC, Navas PA, Neri F, Parker SCJ, Sabo PJ, Sandstrom R, Shafer A, Vetrie D, Weaver M, Wilcox S, Yu M, Collins FS, Dekker J, Lieb JD, Tullius TD, Crawford GE, Sunyaev S, Noble WS, Dunham I, Denoeud F, Reymond A, Kapranov P, Rozowsky J, Zheng D, Castelo R, Frankish A, Harrow J, Ghosh S, Sandelin A, Hofacker IL, Baertsch R, Keefe D, Dike S, Cheng J, Hirsch HA, Sekinger EA, Lagarde J, Abril JF, Shahab A, Flamm C, Fried C, Hackermüller J, Hertel J, Lindemeyer M, Missal K, Tanzer A, Washietl S, Korbel J, Emanuelsson O, Pedersen JS, Holroyd N, Taylor R, Swarbreck D, Matthews N, Dickson MC, Thomas DJ, Weirauch MT, Gilbert J, Drenkow J, Bell I, Zhao X, Srinivasan KG, Sung W‐K, Ooi HS, Chiu KP, Foissac S, Alioto T, Brent M, Pachter L, Tress ML, Valencia A, Choo SW, Choo CY, Ucla C, Manzano C, Wyss C, Cheung E, Clark TG, Brown JB, Ganesh M, Patel S, Tammana H, Chrast J, Henrichsen CN, Kai C, Kawai J, Nagalakshmi U, Wu J, Lian Z, Lian J, Newburger P, Zhang X, Bickel P, Mattick JS, Carninci P, Hayashizaki Y, Weissman S, Hubbard T, Myers RM, Rogers J, Stadler PF, Lowe TM, Wei C‐L, Ruan Y, Struhl K, Gerstein M, Antonarakis SE, Fu Y, Green ED, Karaöz U, Siepel A, Taylor J, Liefer LA, Wetterstrand KA, Good PJ, Feingold EA, Guyer MS, Cooper GM, Asimenos G, Dewey CN, Hou M, Nikolaev S, Montoya‐Burgos JI, Löytynoja A, Whelan S, Pardi F, Massingham T, Huang H, Zhang NR, Holmes I, Mullikin JC, Ureta‐Vidal A, Paten B, Seringhaus M, Church D, Rosenbloom K, Kent WJ, Stone EA, NISC Comparative Sequencing Program, Baylor College of Medicine Human Genome Sequencing Center, Washington University Genome Sequencing Center, Broad Institute, Children's Hospital Oakland Research Institute, Batzoglou S, Goldman N, Hardison RC, Haussler D, Miller W, Sidow A, Trinklein ND, Zhang ZD, Barrera L, Stuart R, King DC, Ameur A, Enroth S, Bieda MC, Kim J, Bhinge AA, Jiang N, Liu J, Yao F, Vega VB, Lee CWH, Ng P, Shahab A, Yang A, Moqtaderi Z, Zhu Z, Xu X, Squazzo S, Oberley MJ, Inman D, Singer MA, Richmond TA, Munn KJ, Rada‐Iglesias A, Wallerman O, Komorowski J, Fowler JC, Couttet P, Bruce AW, Dovey OM, Ellis PD, Langford CF, Nix DA, Euskirchen G, Hartman S, Urban AE, Kraus P, Van Calcar S, Heintzman N, Kim TH, Wang K, Qu C, Hon G, Luna R, Glass CK, Rosenfeld MG, Aldred SF, Cooper SJ, Halees A, Lin JM, Shulha HP, Zhang X, Xu M, Haidar JNS, Yu Y, Ruan Y, Iyer VR, Green RD, Wadelius C, Farnham PJ, Ren B, Harte RA, Hinrichs AS, Trumbower H, Clawson H, Hillman‐Jackson J, Zweig AS, Smith K, Thakkapallayil A, Barber G, Kuhn RM, Karolchik D, Armengol L, Bird CP, de Bakker PIW, Kern AD, Lopez‐Bigas N, Martin JD, Stranger BE, Woodroffe A, Davydov E, Dimas A, Eyras E, Hallgrímsdóttir IB, Huppert J, Zody MC, Abecasis GR, Estivill X, Bouffard GG, Guan X, Hansen NF, Idol JR, Maduro VVB, Maskeri B, McDowell JC, Park M, Thomas PJ, Young AC, Blakesley RW, Muzny DM, Sodergren E, Wheeler DA, Worley KC, Jiang H, Weinstock GM, Gibbs RA, Graves T, Fulton R, Mardis ER, Wilson RK, Clamp M, Cuff J, Gnerre S, Jaffe DB, Chang JL, Lindblad‐Toh K, Lander ES, Koriabine M, Nefedov M, Osoegawa K, Yoshinaga Y, Zhu B, de Jong PJ. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447: 799‐816, 2007. DOI: 10.1038/nature05874.
 47.ENCODE Project Consortium, Snyder MP, Gingeras TR, Moore JE, Weng Z, Gerstein MB, Ren B, Hardison RC, Stamatoyannopoulos JA, Graveley BR, Feingold EA, Pazin MJ, Pagan M, Gilchrist DA, Hitz BC, Cherry JM, Bernstein BE, Mendenhall EM, Zerbino DR, Frankish A, Flicek P, Myers RM. Perspectives on ENCODE. Nature 583: 693‐698, 2020. DOI: 10.1038/s41586‐020‐2449‐8.
 48.Estivill X, Armengol L. Copy number variants and common disorders: Filling the gaps and exploring complexity in genome‐wide association studies. PLoS Genet 3: 1787‐1799, 2007. DOI: 10.1371/journal.pgen.0030190.
 49.Fernández‐Ruiz I. Immune system and cardiovascular disease. Nat Rev Cardiol 13: 503, 2016. DOI: 10.1038/nrcardio.2016.127.
 50.Fishilevich S, Nudel R, Rappaport N, Hadar R, Plaschkes I, Iny Stein T, Rosen N, Kohn A, Twik M, Safran M, Lancet D, Cohen D. GeneHancer: Genome‐wide integration of enhancers and target genes in GeneCards. Database (Oxford) 2017, 2017. DOI: 10.1093/database/bax028.
 51.Flister MJ, Prokop JW, Lazar J, Shimoyama M, Dwinell M, Geurts A. 2015 Guidelines for Establishing Genetically Modified Rat Models for Cardiovascular Research. J Cardiovasc Transl Res 8 (4): 269‐277, 2015.
 52.Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, Lin J, Minguez P, Bork P, von Mering C, Jensen LJ. STRING v9.1: Protein‐protein interaction networks, with increased coverage and integration. Nucleic Acids Res 41: D808‐D815, 2013. DOI: 10.1093/nar/gks1094.
 53.Frankish A, Diekhans M, Ferreira A‐M, Johnson R, Jungreis I, Loveland J, Mudge JM, Sisu C, Wright J, Armstrong J, Barnes I, Berry A, Bignell A, Carbonell Sala S, Chrast J, Cunningham F, Di Domenico T, Donaldson S, Fiddes IT, García Girón C, Gonzalez JM, Grego T, Hardy M, Hourlier T, Hunt T, Izuogu OG, Lagarde J, Martin FJ, Martínez L, Mohanan S, Muir P, Navarro FCP, Parker A, Pei B, Pozo F, Ruffier M, Schmitt BM, Stapleton E, Suner M‐M, Sycheva I, Uszczynska‐Ratajczak B, Xu J, Yates A, Zerbino D, Zhang Y, Aken B, Choudhary JS, Gerstein M, Guigó R, Hubbard TJP, Kellis M, Paten B, Reymond A, Tress ML, Flicek P. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res 47: D766‐D773, 2019. DOI: 10.1093/nar/gky955.
 54.Franzén O, Gan L‐M, Björkegren JLM. PanglaoDB: A web server for exploration of mouse and human single‐cell RNA sequencing data. Database (Oxford) 2019, 2019. DOI: 10.1093/database/baz046.
 55.Garalde DR, Snell EA, Jachimowicz D, Sipos B, Lloyd JH, Bruce M, Pantic N, Admassu T, James P, Warland A, Jordan M, Ciccone J, Serra S, Keenan J, Martin S, McNeill L, Wallace EJ, Jayasinghe L, Wright C, Blasco J, Young S, Brocklebank D, Juul S, Clarke J, Heron AJ, Turner DJ. Highly parallel direct RNA sequencing on an array of nanopores. Nat Methods 15: 201‐206, 2018. DOI: 10.1038/nmeth.4577.
 56.Garbers C, Monhasery N, Aparicio‐Siegmund S, Lokau J, Baran P, Nowell MA, Jones SA, Rose‐John S, Scheller J. The interleukin‐6 receptor Asp358Ala single nucleotide polymorphism rs2228145 confers increased proteolytic conversion rates by ADAM proteases. Biochim Biophys Acta 1842: 1485‐1494, 2014. DOI: 10.1016/j.bbadis.2014.05.018.
 57.Gatz M, Pedersen NL, Berg S, Johansson B, Johansson K, Mortimer JA, Posner SF, Viitanen M, Winblad B, Ahlbom A. Heritability for Alzheimer's disease: The study of dementia in Swedish twins. J Gerontol A Biol Sci Med Sci 52: M117‐M125, 1997. DOI: 10.1093/gerona/52a.2.m117.
 58.Giral H, Landmesser U, Kratzer A. Into the Wild: GWAS Exploration of Non‐coding RNAs. Front Cardiovasc Med 5: 181, 2018. DOI: 10.3389/fcvm.2018.00181.
 59.GTEx Consortium. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369: 1318‐1330, 2020. DOI: 10.1126/science.aaz1776.
 60.GTEx Consortium, Laboratory, Data Analysis & Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, Lead analysts, Laboratory, Data Analysis & Coordinating Center (LDACC), NIH program management, Biospecimen collection, Pathology, eQTL manuscript working group, Battle A, Brown CD, Engelhardt BE, Montgomery SB. Genetic effects on gene expression across human tissues. Nature 550: 204‐213, 2017. DOI: 10.1038/nature24277.
 61.Guo MH, Plummer L, Chan Y‐M, Hirschhorn JN, Lippincott MF. Burden testing of rare variants identified through exome sequencing via publicly available control data. Am J Hum Genet 103: 522‐534, 2018. DOI: 10.1016/j.ajhg.2018.08.016.
 62.Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, Couger MB, Eccles D, Li B, Lieber M, MacManes MD, Ott M, Orvis J, Pochet N, Strozzi F, Weeks N, Westerman R, William T, Dewey CN, Henschel R, LeDuc RD, Friedman N, Regev A. De novo transcript sequence reconstruction from RNA‐seq using the Trinity platform for reference generation and analysis. Nat Protoc 8: 1494‐1512, 2013. DOI: 10.1038/nprot.2013.084.
 63.Han A, Kim W‐Y, Park S‐M. SNP2NMD: A database of human single nucleotide polymorphisms causing nonsense‐mediated mRNA decay. Bioinformatics 23: 397‐399, 2007. DOI: 10.1093/bioinformatics/btl593.
 64.Hartog N, Faber W, Frisch A, Bauss J, Bupp CP, Rajasekaran S, Prokop JW. SARS‐CoV‐2 infection: Molecular mechanisms of severe outcomes to suggest therapeutics. Expert Rev Proteomics 18 (2): 105‐118, 2021.
 65.Hasenfuss G. Animal models of human cardiovascular disease, heart failure and hypertrophy. Cardiovasc Res 39: 60‐76, 1998. DOI: 10.1016/s0008‐6363(98)00110‐2.
 66.Hentze MW, Kulozik AE. A perfect message: RNA surveillance and nonsense‐mediated decay. Cell 96: 307‐310, 1999. DOI: 10.1016/s0092‐8674(00)80542‐5.
 67.Hewett M, Oliver DE, Rubin DL, Easton KL, Stuart JM, Altman RB, Klein TE. PharmGKB: The pharmacogenetics knowledge base. Nucleic Acids Res 30: 163‐165, 2002. DOI: 10.1093/nar/30.1.163.
 68.Hiatt SM, Lawlor JMJ, Handley LH, Ramaker RC, Rogers BB, Partridge EC, Boston LB, Williams M, Plott CB, Jenkins J, Gray DE, Holt JM, Bowling KM, Bebin EM, Grimwood J, Schmutz J, Cooper GM. Long‐read genome sequencing for the diagnosis of neurodevelopmental disorders. HGG Adv. 2 (2): 100023.
 69.Hiatt SM, Neu MB, Ramaker RC, Hardigan AA, Prokop JW, Hancarova M, Prchalova D, Havlovicova M, Prchal J, Stranecky V, Yim DKC, Powis Z, Keren B, Nava C, Mignot C, Rio M, Revah‐Politi A, Hemati P, Stong N, Iglesias AD, Suchy SF, Willaert R, Wentzensen IM, Wheeler PG, Brick L, Kozenko M, Hurst ACE, Wheless JW, Lacassie Y, Myers RM, Barsh GS, Sedlacek Z, Cooper GM. De novo mutations in the GTP/GDP‐binding region of RALA, a RAS‐like small GTPase, cause intellectual disability and developmental delay. PLoS Genet 14, 2018. DOI: 10.1371/journal.pgen.1007671.
 70.Hinds DA, Buil A, Ziemek D, Martinez‐Perez A, Malik R, Folkersen L, Germain M, Mälarstig A, Brown A, Soria JM, Dichgans M, Bing N, Franco‐Cereceda A, Souto JC, Dermitzakis ET, Hamsten A, Worrall BB, Tung JY, METASTROKE Consortium, INVENT Consortium, Sabater‐Lleal M. Genome‐wide association analysis of self‐reported events in 6135 individuals and 252 827 controls identifies 8 loci associated with thrombosis. Hum Mol Genet 25: 1867‐1874, 2016. DOI: 10.1093/hmg/ddw037.
 71.Holbrook JA, Neu‐Yilik G, Hentze MW, Kulozik AE. Nonsense‐mediated decay approaches the clinic. Nat Genet 36: 801‐808, 2004. DOI: 10.1038/ng1403.
 72.Hsu M‐K, Lin H‐Y, Chen F‐C. NMD Classifier: A reliable and systematic classification tool for nonsense‐mediated decay events. PLoS One 12: e0174798, 2017. DOI: 10.1371/journal.pone.0174798.
 73.Hulo N, Bairoch A, Bulliard V, Cerutti L, Cuche BA, de Castro E, Lachaize C, Langendijk‐Genevaux PS, Sigrist CJA. The 20 years of PROSITE. Nucleic Acids Res 36: D245‐D249, 2008. DOI: 10.1093/nar/gkm977.
 74.Jones AR, Overly CC, Sunkin SM. The Allen Brain Atlas: 5 years and beyond. Nat Rev Neurosci 10: 821‐828, 2009. DOI: 10.1038/nrn2722.
 75.Jucker M. The benefits and limitations of animal models for translational research in neurodegenerative diseases. Nat Med 16: 1210‐1214, 2010. DOI: 10.1038/nm.2224.
 76.Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C, Evans JP, Herman GE, Hufnagel SB, Klein TE, Korf BR, McKelvey KD, Ormond KE, Richards CS, Vlangos CN, Watson M, Martin CL, Miller DT. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): A policy statement of the American College of Medical Genetics and Genomics. Genet Med 19: 249‐255, 2017. DOI: 10.1038/gim.2016.190.
 77.Keele GR, Prokop JW, He H, Holl K, Littrell J, Deal AW, Kim Y, Kyle PB, Attipoe E, Johnson AC, Uhl KL. Sept8/SEPTIN8 involvement in cellular structure and kidney damage is identified by genetic mapping and a novel human tubule hypoxic model. Sci Rep 11 (1): 1‐15, 2021.
 78.Keele GR, Prokop JW, He H, Holl K, Littrell J, Deal AW, Kim Y, Kyle PB, Attipoe E, Johnson AC, Uhl KL, Sirpilla OL, Jahanbakhsh S, Robinson M, Levy S, Valdar W, Garrett MR, Solberg Woods LC. Sept8/SEPTIN8 involvement in cellular structure and kidney damage is identified by genetic mapping and a novel human tubule hypoxic model. Sci Rep 11: 2071, 2021. DOI: 10.1038/s41598‐021‐81550‐8.
 79.Kellum JA, Kong L, Fink MP, Weissfeld LA, Yealy DM, Pinsky MR, Fine J, Krichevsky A, Delude RL, Angus DC. GenIMS investigators. Understanding the inflammatory cytokine response in pneumonia and sepsis: Results of the genetic and inflammatory markers of sepsis (GenIMS) Study. Arch Intern Med 167: 1655‐1663, 2007. DOI: 10.1001/archinte.167.15.1655.
 80.Kelly KM, Smith JA, Mezuk B. Depression and interleukin‐6 signaling: A Mendelian Randomization study. Brain Behav Immun 95: 106‐114, 2021. DOI: 10.1016/j.bbi.2021.02.019.
 81.Kerin T, Ramanathan A, Rivas K, Grepo N, Coetzee GA, Campbell DB. A noncoding RNA antisense to moesin at 5p14.1 in autism. Sci Transl Med 4: 128ra40, 2012. DOI: 10.1126/scitranslmed.3003479.
 82.Kilk K. Metabolomics for Animal Models of Rare Human Diseases: An expert review and lessons learned. OMICS 23: 300‐307, 2019. DOI: 10.1089/omi.2019.0065.
 83.Kingsmore SF, Cakici JA, Clark MM, Gaughran M, Feddock M, Batalov S, Bainbridge MN, Carroll J, Caylor SA, Clarke C, Ding Y, Ellsworth K, Farnaes L, Hildreth A, Hobbs C, James K, Kint CI, Lenberg J, Nahas S, Prince L, Reyes I, Salz L, Sanford E, Schols P, Sweeney N, Tokita M, Veeraraghavan N, Watkins K, Wigby K, Wong T, Chowdhury S, Wright MS, Dimmock D. A randomized, controlled trial of the analytic and diagnostic performance of Singleton and Trio, rapid genome and exome sequencing in ill infants. Am J Hum Genet 105: 719‐733, 2019. DOI: 10.1016/j.ajhg.2019.08.009.
 84.Korakavi N, Prokop JW, Seaver LH. Evolution of the phenotype of craniosynostosis with dental anomalies syndrome and report of IL11RA variant population frequencies in a Crouzon‐like autosomal recessive syndrome. Am J Med Genet A 179 (4): 668‐673, 2019.
 85.Krieger E, Joo K, Lee J, Lee J, Raman S, Thompson J, Tyka M, Baker D, Karplus K. Improving physical realism, stereochemistry, and side‐chain accuracy in homology modeling: Four approaches that performed well in CASP8. Proteins 77 (Suppl 9): 114‐122, 2009. DOI: 10.1002/prot.22570.
 86.Kuechler A, Czeschik JC, Graf E, Grasshoff U, Hüffmeier U, Busa T, Beck‐Woedl S, Faivre L, Rivière J‐B, Bader I, Koch J, Reis A, Hehr U, Rittinger O, Sperl W, Haack TB, Wieland T, Engels H, Prokisch H, Strom TM, Lüdecke H‐J, Wieczorek D. Bainbridge‐Ropers syndrome caused by loss‐of‐function variants in ASXL3: A recognizable condition. Eur J Hum Genet 25: 183‐191, 2017. DOI: 10.1038/ejhg.2016.165.
 87.Kumar S, Ambrosini G, Bucher P. SNP2TFBS – A database of regulatory SNPs affecting predicted transcription factor binding site affinity. Nucleic Acids Res 45: D139‐D144, 2017. DOI: 10.1093/nar/gkw1064.
 88.Kurosaki T, Popp MW, Maquat LE. Quality and quantity control of gene expression by nonsense‐mediated mRNA decay. Nat Rev Mol Cell Biol 20: 406‐420, 2019. DOI: 10.1038/s41580‐019‐0126‐2.
 89.Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, Devon K, Dewar K, Doyle M, FitzHugh W, Funke R, Gage D, Harris K, Heaford A, Howland J, Kann L, Lehoczky J, LeVine R, McEwan P, McKernan K, Meldrim J, Mesirov JP, Miranda C, Morris W, Naylor J, Raymond C, Rosetti M, Santos R, Sheridan A, Sougnez C, Stange‐Thomann Y, Stojanovic N, Subramanian A, Wyman D, Rogers J, Sulston J, Ainscough R, Beck S, Bentley D, Burton J, Clee C, Carter N, Coulson A, Deadman R, Deloukas P, Dunham A, Dunham I, Durbin R, French L, Grafham D, Gregory S, Hubbard T, Humphray S, Hunt A, Jones M, Lloyd C, McMurray A, Matthews L, Mercer S, Milne S, Mullikin JC, Mungall A, Plumb R, Ross M, Shownkeen R, Sims S, Waterston RH, Wilson RK, Hillier LW, McPherson JD, Marra MA, Mardis ER, Fulton LA, Chinwalla AT, Pepin KH, Gish WR, Chissoe SL, Wendl MC, Delehaunty KD, Miner TL, Delehaunty A, Kramer JB, Cook LL, Fulton RS, Johnson DL, Minx PJ, Clifton SW, Hawkins T, Branscomb E, Predki P, Richardson P, Wenning S, Slezak T, Doggett N, Cheng JF, Olsen A, Lucas S, Elkin C, Uberbacher E, Frazier M, Gibbs RA, Muzny DM, Scherer SE, Bouck JB, Sodergren EJ, Worley KC, Rives CM, Gorrell JH, Metzker ML, Naylor SL, Kucherlapati RS, Nelson DL, Weinstock GM, Sakaki Y, Fujiyama A, Hattori M, Yada T, Toyoda A, Itoh T, Kawagoe C, Watanabe H, Totoki Y, Taylor T, Weissenbach J, Heilig R, Saurin W, Artiguenave F, Brottier P, Bruls T, Pelletier E, Robert C, Wincker P, Smith DR, Doucette‐Stamm L, Rubenfield M, Weinstock K, Lee HM, Dubois J, Rosenthal A, Platzer M, Nyakatura G, Taudien S, Rump A, Yang H, Yu J, Wang J, Huang G, Gu J, Hood L, Rowen L, Madan A, Qin S, Davis RW, Federspiel NA, Abola AP, Proctor MJ, Myers RM, Schmutz J, Dickson M, Grimwood J, Cox DR, Olson MV, Kaul R, Raymond C, Shimizu N, Kawasaki K, Minoshima S, Evans GA, Athanasiou M, Schultz R, Roe BA, Chen F, Pan H, Ramser J, Lehrach H, Reinhardt R, McCombie WR, de la Bastide M, Dedhia N, Blöcker H, Hornischer K, Nordsiek G, Agarwala R, Aravind L, Bailey JA, Bateman A, Batzoglou S, Birney E, Bork P, Brown DG, Burge CB, Cerutti L, Chen HC, Church D, Clamp M, Copley RR, Doerks T, Eddy SR, Eichler EE, Furey TS, Galagan J, Gilbert JG, Harmon C, Hayashizaki Y, Haussler D, Hermjakob H, Hokamp K, Jang W, Johnson LS, Jones TA, Kasif S, Kaspryzk A, Kennedy S, Kent WJ, Kitts P, Koonin EV, Korf I, Kulp D, Lancet D, Lowe TM, McLysaght A, Mikkelsen T, Moran JV, Mulder N, Pollara VJ, Ponting CP, Schuler G, Schultz J, Slater G, Smit AF, Stupka E, Szustakowki J, Thierry‐Mieg D, Thierry‐Mieg J, Wagner L, Wallis J, Wheeler R, Williams A, Wolf YI, Wolfe KH, Yang SP, Yeh RF, Collins F, Guyer MS, Peterson J, Felsenfeld A, Wetterstrand KA, Patrinos A, Morgan MJ, de Jong P, Catanese JJ, Osoegawa K, Shizuya H, Choi S, Chen YJ, Szustakowki J. International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature 409: 860‐921, 2001. DOI: 10.1038/35057062.
 90.Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, Maglott DR. ClinVar: Public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 42 (D1): D980‐D985.
 91.Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG. Clustal W and Clustal X version 2.0. Bioinformatics 23: 2947‐2948, 2007. DOI: 10.1093/bioinformatics/btm404.
 92.Larson MH, Gilbert LA, Wang X, Lim WA, Weissman JS, Qi LS. CRISPR interference (CRISPRi) for sequence‐specific control of gene expression. Nat Protoc 8: 2180‐2196, 2013. DOI: 10.1038/nprot.2013.132.
 93.Lieschke GJ, Currie PD. Animal models of human disease: Zebrafish swim into view. Nat Rev Genet 8: 353‐367, 2007. DOI: 10.1038/nrg2091.
 94.Lorenzi L, Avila Cobos F, Decock A, Everaert C, Helsmoortel H, Lefever S, Verboom K, Volders P‐J, Speleman F, Vandesompele J, Mestdagh P. Long noncoding RNA expression profiling in cancer: Challenges and opportunities. Genes Chromosomes Cancer 58: 191‐199, 2019. DOI: 10.1002/gcc.22709.
 95.Luoto KR, Kumareswaran R, Bristow RG. Tumor hypoxia as a driving force in genetic instability. Genome Integr 4: 5, 2013. DOI: 10.1186/2041‐9414‐4‐5.
 96.Ma H, Yu L, Byra EA, Hu N, Kitagawa K, Nakayama KI, Kawamoto T, Ren J. Aldehyde dehydrogenase 2 knockout accentuates ethanol‐induced cardiac depression: Role of protein phosphatases. J Mol Cell Cardiol 49: 322‐329, 2010. DOI: 10.1016/j.yjmcc.2010.03.017.
 97.MacArthur J, Bowler E, Cerezo M, Gil L, Hall P, Hastings E, Junkins H, McMahon A, Milano A, Morales J, Pendlington ZM, Welter D, Burdett T, Hindorff L, Flicek P, Cunningham F, Parkinson H. The new NHGRI‐EBI Catalog of published genome‐wide association studies (GWAS Catalog). Nucleic Acids Res 45: D896‐D901, 2017. DOI: 10.1093/nar/gkw1133.
 98.Mandl KD, Glauser T, Krantz ID, Avillach P, Bartels A, Beggs AH, Biswas S, Bourgeois FT, Corsmo J, Dauber A, Devkota B, Fleisher GR, Heath AP, Helbig I, Hirschhorn JN, Kilbourn J, Kong SW, Kornetsky S, Majzoub JA, Marsolo K, Martin LJ, Nix J, Schwarzhoff A, Stedman J, Strauss A, Sund KL, Taylor DM, White PS, Marsh E, Grimberg A, Hawkes C, Genomics Research and InnovationNetwork. The Genomics Research and Innovation Network: Creating an interoperable, federated, genomics learning system. Genet Med 22: 371‐380, 2020. DOI: 10.1038/s41436‐019‐0646‐3.
 99.Matoba N, Akiyama M, Ishigaki K, Kanai M, Takahashi A, Momozawa Y, Ikegawa S, Ikeda M, Iwata N, Hirata M, Matsuda K, Murakami Y, Kubo M, Kamatani Y, Okada Y. GWAS of 165,084 Japanese individuals identified nine loci associated with dietary habits. Nat Hum Behav 4: 308‐316, 2020. DOI: 10.1038/s41562‐019‐0805‐1.
 100.May JP, Yuan X, Sawicki E, Simon AE. RNA virus evasion of nonsense‐mediated decay. PLoS Pathog 14: e1007459, 2018. DOI: 10.1371/journal.ppat.1007459.
 101.McGonigle P, Ruggeri B. Animal models of human disease: Challenges in enabling translation. Biochem Pharmacol 87: 162‐171, 2014. DOI: 10.1016/j.bcp.2013.08.006.
 102.McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GRS, Thormann A, Flicek P, Cunningham F. The Ensembl variant effect predictor. Genome Biol 17: 122, 2016. DOI: 10.1186/s13059‐016‐0974‐4.
 103.Mi H, Huang X, Muruganujan A, Tang H, Mills C, Kang D, Thomas PD. PANTHER version 11: Expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res 45: D183‐D189, 2017. DOI: 10.1093/nar/gkw1138.
 104.Mort M, Sterne‐Weiler T, Li B, Ball EV, Cooper DN, Radivojac P, Sanford JR, Mooney SD. MutPred Splice: Machine learning‐based prediction of exonic variants that disrupt splicing. Genome Biol 15: R19, 2014. DOI: 10.1186/gb‐2014‐15‐1‐r19.
 105.Mulligan MK, Mozhui K, Prins P, Williams RW. GeneNetwork: A toolbox for systems genetics. Methods Mol Biol 1488: 75‐120, 2017. DOI: 10.1007/978‐1‐4939‐6427‐7_4.
 106.Nakayama A, Nakatochi M, Kawamura Y, Yamamoto K, Nakaoka H, Shimizu S, Higashino T, Koyama T, Hishida A, Kuriki K, Watanabe M, Shimizu T, Ooyama K, Ooyama H, Nagase M, Hidaka Y, Matsui D, Tamura T, Nishiyama T, Shimanoe C, Katsuura‐Kamano S, Takashima N, Shirai Y, Kawaguchi M, Takao M, Sugiyama R, Takada Y, Nakamura T, Nakashima H, Tsunoda M, Danjoh I, Hozawa A, Hosomichi K, Toyoda Y, Kubota Y, Takada T, Suzuki H, Stiburkova B, Major TJ, Merriman TR, Kuriyama N, Mikami H, Takezaki T, Matsuo K, Suzuki S, Hosoya T, Kamatani Y, Kubo M, Ichida K, Wakai K, Inoue I, Okada Y, Shinomiya N, Matsuo H, Japan Gout Genomics Consortium (Japan Gout). Subtype‐specific gout susceptibility loci and enrichment of selection pressure on ABCG2 and ALDH2 identified by subtype genome‐wide meta‐analyses of clinically defined gout patients. Ann Rheum Dis 79: 657‐665, 2020. DOI: 10.1136/annrheumdis‐2019‐216644.
 107.Navarro Gonzalez J, Zweig AS, Speir ML, Schmelter D, Rosenbloom KR, Raney BJ, Powell CC, Nassar LR, Maulding ND, Lee CM, Lee BT, Hinrichs AS, Fyfe AC, Fernandes JD, Diekhans M, Clawson H, Casper J, Benet‐Pagès A, Barber GP, Haussler D, Kuhn RM, Haeussler M, Kent WJ. The UCSC Genome Browser database: 2021 update. Nucleic Acids Res 49: D1046‐D1057, 2021. DOI: 10.1093/nar/gkaa1070.
 108.Ng PC, Henikoff S. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res 31: 3812‐3814, 2003.
 109.Oscanoa J, Sivapalan L, Gadaleta E, Dayem Ullah AZ, Lemoine NR, Chelala C. SNPnexus: A web server for functional annotation of human genome sequence variation (2020 update). Nucleic Acids Res 48: W185‐W192, 2020. DOI: 10.1093/nar/gkaa420.
 110.Papasavva P, Kleanthous M, Lederer CW. Rare Opportunities: CRISPR/Cas‐based therapy development for rare genetic diseases. Mol Diagn Ther 23: 201‐222, 2019. DOI: 10.1007/s40291‐019‐00392‐3.
 111.Partridge EC, Chhetri SB, Prokop JW, Ramaker RC, Jansen CS, Goh S‐T, Mackiewicz M, Newberry KM, Brandsmeier LA, Meadows SK, Messer CL, Hardigan AA, Coppola CJ, Dean EC, Jiang S, Savic D, Mortazavi A, Wold BJ, Myers RM, Mendenhall EM. Occupancy maps of 208 chromatin‐associated proteins in one human cell type. Nature 583: 720‐728, 2020. DOI: 10.1038/s41586‐020‐2023‐4.
 112.Peng H, Prokop J, Karar J, Park K, Cao L, Harbour JW, Bowcock AM, Malkowicz SB, Cheung M, Testa JR, Rauscher FJ. Familial and somatic BAP1 mutations inactivate ASXL1/2‐mediated allosteric regulation of BAP1 deubiquitinase by targeting multiple independent domains. Cancer Res 78: 1200‐1213, 2018. DOI: 10.1158/0008‐5472.CAN‐17‐2876.
 113.Peng H, Talebzadeh‐Farrooji M, Osborne MJ, Prokop JW, McDonald PC, Karar J, Hou Z, He M, Kebebew E, Orntoft T, Herlyn M, Caton AJ, Fredericks W, Malkowicz B, Paterno CS, Carolin AS, Speicher DW, Skordalakes E, Huang Q, Dedhar S, Borden KLB, Rauscher FJ. LIMD2 is a small LIM‐only protein overexpressed in metastatic lesions that regulates cell motility and tumor progression by directly binding to and activating the integrin‐linked kinase. Cancer Res 74: 1390‐1403, 2014. DOI: 10.1158/0008‐5472.CAN‐13‐1275.
 114.Pérez‐Palma E, Gramm M, Nürnberg P, May P, Lal D. Simple ClinVar: An interactive web server to explore and retrieve gene and disease variants aggregated in ClinVar database. Nucleic Acids Res 47: W99‐W105, 2019. DOI: 10.1093/nar/gkz411.
 115.Peri S, Navarro JD, Amanchy R, Kristiansen TZ, Jonnalagadda CK, Surendranath V, Niranjan V, Muthusamy B, Gandhi TKB, Gronborg M, Ibarrola N, Deshpande N, Shanker K, Shivashankar HN, Rashmi BP, Ramya MA, Zhao Z, Chandrika KN, Padma N, Harsha HC, Yatish AJ, Kavitha MP, Menezes M, Choudhury DR, Suresh S, Ghosh N, Saravana R, Chandran S, Krishna S, Joy M, Anand SK, Madavan V, Joseph A, Wong GW, Schiemann WP, Constantinescu SN, Huang L, Khosravi‐Far R, Steen H, Tewari M, Ghaffari S, Blobe GC, Dang CV, Garcia JGN, Pevsner J, Jensen ON, Roepstorff P, Deshpande KS, Chinnaiyan AM, Hamosh A, Chakravarti A, Pandey A. Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res 13: 2363‐2371, 2003. DOI: 10.1101/gr.1680803.
 116.Philippakis AA, Azzariti DR, Beltran S, Brookes AJ, Brownstein CA, Brudno M, Brunner HG, Buske OJ, Carey K, Doll C, Dumitriu S, Dyke SOM, den Dunnen JT, Firth HV, Gibbs RA, Girdea M, Gonzalez M, Haendel MA, Hamosh A, Holm IA, Huang L, Hurles ME, Hutton B, Krier JB, Misyura A, Mungall CJ, Paschall J, Paten B, Robinson PN, Schiettecatte F, Sobreira NL, Swaminathan GJ, Taschner PE, Terry SF, Washington NL, Züchner S, Boycott KM, Rehm HL. The Matchmaker Exchange: A platform for rare disease gene discovery. Hum Mutat 36: 915‐921, 2015. DOI: 10.1002/humu.22858.
 117.Pinto D, Darvishi K, Shi X, Rajan D, Rigler D, Fitzgerald T, Lionel AC, Thiruvahindrapuram B, Macdonald JR, Mills R, Prasad A, Noonan K, Gribble S, Prigmore E, Donahoe PK, Smith RS, Park JH, Hurles ME, Carter NP, Lee C, Scherer SW, Feuk L. Comprehensive assessment of array‐based platforms and calling algorithms for detection of copy number variants. Nat Biotechnol 29: 512‐520, 2011. DOI: 10.1038/nbt.1852.
 118.Prabhakar NR. Sensing hypoxia: Physiology, genetics and epigenetics. J Physiol 591: 2245‐2257, 2013. DOI: 10.1113/jphysiol.2012.247759.
 119.Prokop JW, Bupp CP, Frisch A, Bilinovich SM, Campbell DB, Vogt D, Schultz CR, Uhl KL, VanSickle E, Rajasekaran S, Bachmann AS. Emerging role of ODC1 in neurodevelopmental disorders and brain development. Genes (Basel) 12: 470, 2021. DOI: 10.3390/genes12040470.
 120.Prokop JW, Hartog NL, Chesla D, Faber W, Love CP, Karam R, Abualkheir N, Feldmann B, Teng L, McBride T, Leimanis ML, English BK, Holsworth A, Frisch A, Bauss J, Kalpage N, Derbedrossian A, Pinti RM, Hale N, Mills J, Eby A, VanSickle EA, Pageau SC, Shankar R, Chen B, Carcillo JA, Sanfilippo D, Olivero R, Bupp CP, Rajasekaran S. High‐density blood transcriptomics reveals precision immune signatures of SARS‐CoV‐2 infection in hospitalized individuals. Front Immunol, 2021. DOI: 10.3389/fimmu.2021.694243.
 121.Prokop JW, Lazar J, Crapitto G, Smith DC, Worthey EA, Jacob HJ. Molecular modeling in the age of clinical genomics, the enterprise of the next generation. J Mol Model 23: 75, 2017. DOI: 10.1007/s00894‐017‐3258‐3.
 122.Prokop JW, Leeper TC, Duan Z‐H, Milsted A. Amino acid function and docking site prediction through combining disease variants, structure alignments, sequence alignments, and molecular dynamics: A study of the HMG domain. BMC Bioinformatics 13, S3 (Suppl 2), 2012. DOI: 10.1186/1471‐2105‐13‐S2‐S3.
 123.Prokop JW, Shankar R, Gupta R, Leimanis ML, Nedveck D, Uhl K, Chen B, Hartog NL, Van Veen J, Sisco JS, Sirpilla O, Lydic T, Boville B, Hernandez A, Braunreiter C, Kuk CC, Singh V, Mills J, Wegener M, Adams M, Rhodes M, Bachmann AS, Pan W, Byrne‐Steele ML, Smith DC, Depinet M, Brown BE, Eisenhower M, Han J, Haw M, Madura C, Sanfilippo DJ, Seaver LH, Bupp C, Rajasekaran S. Virus‐induced genetics revealed by multidimensional precision medicine transcriptional workflow applicable to COVID‐19. Physiol Genomics 52: 255‐268, 2020. DOI: 10.1152/physiolgenomics.00045.2020.
 124.Prokop JW, Yeo NC, Ottmann C, Chhetri SB, Florus KL, Ross EJ, Sosonkina N, Link BA, Freedman BI, Coppola CJ, McDermott‐Roe C, Leysen S, Milroy L‐G, Meijer FA, Geurts AM, Rauscher FJ, Ramaker R, Flister MJ, Jacob HJ, Mendenhall EM, Lazar J. Characterization of coding/noncoding variants forSHROOM3in patients with CKD. J Am Soc Nephrol 29 (5): 1525‐1535, 2018.
 125.Quillen EE, Chen X‐D, Almasy L, Yang F, He H, Li X, Wang X‐Y, Liu T‐Q, Hao W, Deng H‐W, Kranzler HR, Gelernter J. ALDH2 is associated to alcohol dependence and is the major genetic determinant of “daily maximum drinks” in a GWAS study of an isolated rural Chinese sample. Am J Med Genet B Neuropsychiatr Genet 165B: 103‐110, 2014. DOI: 10.1002/ajmg.b.32213.
 126.Radivojac P, Vacic V, Haynes C, Cocklin RR, Mohan A, Heyen JW, Goebl MG, Iakoucheva LM. Identification, analysis, and prediction of protein ubiquitination sites. Proteins 78: 365‐380, 2010. DOI: 10.1002/prot.22555.
 127.Rajasekaran S, Bupp CP, Leimanis‐Laurens M, Shukla A, Russell C, Junewick J, Gleason E, VanSickle EA, Edgerly Y, Wittmann BM, Prokop JW, Bachmann AS. Repurposing eflornithine to treat a patient with a rare ODC1 gain‐of‐function variant disease. Lifestyles 10: e67097, 2021. DOI: 10.7554/eLife.67097.
 128.Ray D, Boehnke M. Methods for meta‐analysis of multiple traits using GWAS summary statistics. Genet Epidemiol 42: 134‐145, 2018. DOI: 10.1002/gepi.22105.
 129.Rehm HL, Berg JS, Brooks LD, Bustamante CD, Evans JP, Landrum MJ, Ledbetter DH, Maglott DR, Martin CL, Nussbaum RL, Plon SE, Ramos EM, Sherry ST, Watson MS. ClinGen. ClinGen–The clinical genome resource. N Engl J Med 372: 2235‐2242, 2015. DOI: 10.1056/NEJMsr1406261.
 130.Rentzsch P, Witten D, Cooper GM, Shendure J, Kircher M. CADD: Predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res 47: D886‐D894, 2019. DOI: 10.1093/nar/gky1016.
 131.Rice G, Patrick T, Parmar R, Taylor CF, Aeby A, Aicardi J, Artuch R, Montalto SA, Bacino CA, Barroso B, Baxter P, Benko WS, Bergmann C, Bertini E, Biancheri R, Blair EM, Blau N, Bonthron DT, Briggs T, Brueton LA, Brunner HG, Burke CJ, Carr IM, Carvalho DR, Chandler KE, Christen H‐J, Corry PC, Cowan FM, Cox H, D'Arrigo S, Dean J, De Laet C, De Praeter C, Dery C, Ferrie CD, Flintoff K, Frints SGM, Garcia‐Cazorla A, Gener B, Goizet C, Goutieres F, Green AJ, Guet A, Hamel BCJ, Hayward BE, Heiberg A, Hennekam RC, Husson M, Jackson AP, Jayatunga R, Jiang Y‐H, Kant SG, Kao A, King MD, Kingston HM, Klepper J, van der Knaap MS, Kornberg AJ, Kotzot D, Kratzer W, Lacombe D, Lagae L, Landrieu PG, Lanzi G, Leitch A, Lim MJ, Livingston JH, Lourenco CM, Lyall EGH, Lynch SA, Lyons MJ, Marom D, Mcclure JP, Mcwilliam R, Melancon SB, Mewasingh LD, Moutard M‐L, Nischal KK, Ostergaard JR, Prendiville J, Rasmussen M, Rogers RC, Roland D, Rosser EM, Rostasy K, Roubertie A, Sanchis A, Schiffmann R, Scholl‐Burgi S, Seal S, Shalev SA, Corcoles CS, Sinha GP, Soler D, Spiegel R, Stephenson JBP, Tacke U, Tan TY, Till M, Tolmie JL, Tomlin P, Vagnarelli F, Valente EM, Van Coster RNA, Van der Aa N, Vanderver A, Vles JSH, Voit T, Wassmer E, Weschke B, Whiteford ML, Willemsen MAA, Zankl A, Zuberi SM, Orcesi S, Fazzi E, Lebon P, Crow YJ. Clinical and molecular phenotype of Aicardi‐Goutieres syndrome. Am J Hum Genet 81: 713‐725, 2007. DOI: 10.1086/521373.
 132.Rice GI, Forte GMA, Szynkiewicz M, Chase DS, Aeby A, Abdel‐Hamid MS, Ackroyd S, Allcock R, Bailey KM, Balottin U, Barnerias C, Bernard G, Bodemer C, Botella MP, Cereda C, Chandler KE, Dabydeen L, Dale RC, De Laet C, De Goede CGEL, Del Toro M, Effat L, Enamorado NN, Fazzi E, Gener B, Haldre M, Lin J‐P‐S‐M, Livingston JH, Lourenco CM, Marques W, Oades P, Peterson P, Rasmussen M, Roubertie A, Schmidt JL, Shalev SA, Simon R, Spiegel R, Swoboda KJ, Temtamy SA, Vassallo G, Vilain CN, Vogt J, Wermenbol V, Whitehouse WP, Soler D, Olivieri I, Orcesi S, Aglan MS, Zaki MS, Abdel‐Salam GMH, Vanderver A, Kisand K, Rozenberg F, Lebon P, Crow YJ. Assessment of interferon‐related biomarkers in Aicardi‐Goutières syndrome associated with mutations in TREX1, RNASEH2A, RNASEH2B, RNASEH2C, SAMHD1, and ADAR: A case‐control study. Lancet Neurol 12: 1159‐1169, 2013. DOI: 10.1016/S1474‐4422(13)70258‐8.
 133.Richards S, Aziz N, Bale S, Bick D, Das S, Gastier‐Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL, ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17: 405‐424, 2015. DOI: 10.1038/gim.2015.30.
 134.Ridge PG, Mukherjee S, Crane PK, Kauwe JSK. Alzheimer's Disease Genetics Consortium. Alzheimer's disease: Analyzing the missing heritability. PLoS One 8: e79771, 2013. DOI: 10.1371/journal.pone.0079771.
 135.Ritchie GRS, Dunham I, Zeggini E, Flicek P. Functional annotation of noncoding sequence variants. Nat Methods 11: 294‐296, 2014. DOI: 10.1038/nmeth.2832.
 136.Roadmap Epigenomics Consortium, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, Heravi‐Moussavi A, Kheradpour P, Zhang Z, Wang J, Ziller MJ, Amin V, Whitaker JW, Schultz MD, Ward LD, Sarkar A, Quon G, Sandstrom RS, Eaton ML, Wu Y‐C, Pfenning AR, Wang X, Claussnitzer M, Liu Y, Coarfa C, Harris RA, Shoresh N, Epstein CB, Gjoneska E, Leung D, Xie W, Hawkins RD, Lister R, Hong C, Gascard P, Mungall AJ, Moore R, Chuah E, Tam A, Canfield TK, Hansen RS, Kaul R, Sabo PJ, Bansal MS, Carles A, Dixon JR, Farh K‐H, Feizi S, Karlic R, Kim A‐R, Kulkarni A, Li D, Lowdon R, Elliott G, Mercer TR, Neph SJ, Onuchic V, Polak P, Rajagopal N, Ray P, Sallari RC, Siebenthall KT, Sinnott‐Armstrong NA, Stevens M, Thurman RE, Wu J, Zhang B, Zhou X, Beaudet AE, Boyer LA, De Jager PL, Farnham PJ, Fisher SJ, Haussler D, Jones SJM, Li W, Marra MA, McManus MT, Sunyaev S, Thomson JA, Tlsty TD, Tsai L‐H, Wang W, Waterland RA, Zhang MQ, Chadwick LH, Bernstein BE, Costello JF, Ecker JR, Hirst M, Meissner A, Milosavljevic A, Ren B, Stamatoyannopoulos JA, Wang T, Kellis M. Integrative analysis of 111 reference human epigenomes. Nature 518: 317‐330, 2015. DOI: 10.1038/nature14248.
 137.Sanders M, Lawlor JMJ, Li X, Schuen JN, Millard SL, Zhang X, Buck L, Grysko B, Uhl KL, Hinds D, Stenger CL, Morris M, Lamb N, Levy H, Bupp C, Prokop JW. Genomic, transcriptomic, and protein landscape profile of CFTR and cystic fibrosis. Hum Genet 140: 423‐439, 2021. DOI: 10.1007/s00439‐020‐02211‐w.
 138.Satterstrom FK, Kosmicki JA, Wang J, Breen MS, De Rubeis S, An J‐Y, Peng M, Collins R, Grove J, Klei L, Stevens C, Reichert J, Mulhern MS, Artomov M, Gerges S, Sheppard B, Xu X, Bhaduri A, Norman U, Brand H, Schwartz G, Nguyen R, Guerrero EE, Dias C, Autism Sequencing Consortium, iPSYCH‐Broad Consortium, Betancur C, Cook EH, Gallagher L, Gill M, Sutcliffe JS, Thurm A, Zwick ME, Børglum AD, State MW, Cicek AE, Talkowski ME, Cutler DJ, Devlin B, Sanders SJ, Roeder K, Daly MJ, Buxbaum JD. Large‐scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell 180: 568‐584.e23, 2020. DOI: 10.1016/j.cell.2019.12.036.
 139.Savage LT, Adams SD, James KN, Chowdhury S, Rajasekaran S, Prokop JW, Bupp CP. Rapid whole‐genome sequencing identifies a homozygous novel variant, His540Arg, in HSD17B4 resulting in D‐bifunctional protein deficiency disorder diagnosis. Mol Case Stud 6 (6): a005496, 2020.
 140.Schaid DJ, Chen W, Larson NB. From genome‐wide associations to candidate causal variants by statistical fine‐mapping. Nat Rev Genet 19: 491‐504, 2018. DOI: 10.1038/s41576‐018‐0016‐z.
 141.Schmutz J, Wheeler J, Grimwood J, Dickson M, Yang J, Caoile C, Bajorek E, Black S, Chan YM, Denys M, Escobar J, Flowers D, Fotopulos D, Garcia C, Gomez M, Gonzales E, Haydu L, Lopez F, Ramirez L, Retterer J, Rodriguez A, Rogers S, Salazar A, Tsai M, Myers RM. Quality assessment of the human genome sequence. Nature 429: 365‐368, 2004. DOI: 10.1038/nature02390.
 142.Schröck E, du Manoir S, Veldman T, Schoell B, Wienberg J, Ferguson‐Smith MA, Ning Y, Ledbetter DH, Bar‐Am I, Soenksen D, Garini Y, Ried T. Multicolor spectral karyotyping of human chromosomes. Science 273: 494‐497, 1996. DOI: 10.1126/science.273.5274.494.
 143.Schultz CR, Bupp CP, Rajasekaran S, Bachmann AS. Biochemical features of primary cells from a pediatric patient with a gain‐of‐function ODC1 genetic mutation. Biochem J 476: 2047‐2057, 2019. DOI: 10.1042/BCJ20190294.
 144.Sirpilla O, Bauss J, Gupta R, Underwood A, Qutob D, Freeland T, Bupp C, Carcillo J, Hartog N, Rajasekaran S, Prokop JW. SARS‐CoV‐2‐encoded proteome and human genetics: From interaction‐based to ribosomal biology impact on disease and risk processes. J Proteome Res 19: 4275‐4290, 2020. DOI: 10.1021/acs.jproteome.0c00421.
 145.Snijders Blok L, Hiatt SM, Bowling KM, Prokop JW, Engel KL, Cochran JN, Bebin EM, Bijlsma EK, Ruivenkamp CAL, Terhal P, Simon MEH, Smith R, Hurst JA, McLaughlin H, Person R, Crunk A, Wangler MF, Streff H, Symonds JD, Zuberi SM, Elliott KS, Sanders VR, Masunga A, Hopkin RJ, Dubbs HA, Ortiz‐Gonzalez XR, Pfundt R, Brunner HG, Fisher SE, Kleefstra T, Cooper GM. De novo mutations in MED13, a component of the mediator complex, are associated with a novel neurodevelopmental disorder. Hum Genet 137: 375‐388, 2018. DOI: 10.1007/s00439‐018‐1887‐y.
 146.Sobreira N, Schiettecatte F, Valle D, Hamosh A. GeneMatcher: A matching tool for connecting investigators with an interest in the same gene. Hum Mutat 36: 928‐930, 2015. DOI: 10.1002/humu.22844.
 147.Spain SL, Barrett JC. Strategies for fine‐mapping complex traits. Hum Mol Genet 24: R111‐R119, 2015. DOI: 10.1093/hmg/ddv260.
 148.Spurdle AB, Couch FJ, Hogervorst FBL, Radice P, Sinilnikova OM, IARC Unclassified Genetic Variants Working Group. Prediction and assessment of splicing alterations: Implications for clinical testing. Hum Mutat 29: 1304‐1313, 2008. DOI: 10.1002/humu.20901.
 149.Takeuchi F, Isono M, Nabika T, Katsuya T, Sugiyama T, Yamaguchi S, Kobayashi S, Ogihara T, Yamori Y, Fujioka A, Kato N. Confirmation of ALDH2 as a Major locus of drinking behavior and of its variants regulating multiple metabolic phenotypes in a Japanese population. Circ J 75: 911‐918, 2011. DOI: 10.1253/circj.cj‐10‐0774.
 150.Takeuchi F, Yokota M, Yamamoto K, Nakashima E, Katsuya T, Asano H, Isono M, Nabika T, Sugiyama T, Fujioka A, Awata N, Ohnaka K, Nakatochi M, Kitajima H, Rakugi H, Nakamura J, Ohkubo T, Imai Y, Shimamoto K, Yamori Y, Yamaguchi S, Kobayashi S, Takayanagi R, Ogihara T, Kato N. Genome‐wide association study of coronary artery disease in the Japanese. Eur J Hum Genet 20: 333‐340, 2012. DOI: 10.1038/ejhg.2011.184.
 151.Tang J, Yu Y, Yang W. Long noncoding RNA and its contribution to autism spectrum disorders. CNS Neurosci Ther 23: 645‐656, 2017. DOI: 10.1111/cns.12710.
 152.Tsai GJ, Rañola JMO, Smith C, Garrett LT, Bergquist T, Casadei S, Bowen DJ, Shirts BH. Outcomes of 92 patient‐driven family studies for reclassification of variants of uncertain significance. Genet Med 21: 1435‐1442, 2019. DOI: 10.1038/s41436‐018‐0335‐7.
 153.Twigger S, Lu J, Shimoyama M, Chen D, Pasko D, Long H, Ginster J, Chen C‐F, Nigam R, Kwitek A, Eppig J, Maltais L, Maglott D, Schuler G, Jacob H, Tonellato PJ. Rat Genome Database (RGD): Mapping disease onto the genome. Nucleic Acids Res 30: 125‐128, 2002. DOI: 10.1093/nar/30.1.125.
 154.Uhlen M, Oksvold P, Fagerberg L, Lundberg E, Jonasson K, Forsberg M, Zwahlen M, Kampf C, Wester K, Hober S, Wernerus H, Björling L, Ponten F. Towards a knowledge‐based Human Protein Atlas. Nat Biotechnol 28: 1248‐1250, 2010. DOI: 10.1038/nbt1210‐1248.
 155.UK Biobank [Online]. 2021. Neale lab: [date unknown]. http://www.nealelab.is/uk‐biobank [March 6, 2021].
 156.UniProt Consortium. UniProt: A hub for protein information. Nucleic Acids Res 43: D204‐D212, 2015. DOI: 10.1093/nar/gku989.
 157.Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC. GROMACS: Fast, flexible, and free. J Comput Chem 26: 1701‐1718, 2005. DOI: 10.1002/jcc.20291.
 158.Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, Perak AM, Rosamond WD, Roth GA, UKA S, Satou GM, Schroeder EB, Shah SH, Shay CM, Spartano NL, Stokes A, Tirschwell DL, LB VW, Tsao CW, American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Heart Disease and Stroke Statistics‐2020 Update: A report from the American Heart Association. Circulation 141: e139‐e596, 2020. DOI: 10.1161/CIR.0000000000000757.
 159.Wall RJ, Shani M. Are animal models as good as we think? Theriogenology 69: 2‐9, 2008. DOI: 10.1016/j.theriogenology.2007.09.030.
 160.Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA. Development and testing of a general amber force field. J Comput Chem 25: 1157‐1174, 2004. DOI: 10.1002/jcc.20035.
 161.Wang K, Li M, Hakonarson H. ANNOVAR: Functional annotation of genetic variants from high‐throughput sequencing data. Nucleic Acids Res 38: e164, 2010. DOI: 10.1093/nar/gkq603.
 162.Wilkinson B, Campbell DB. Contribution of long noncoding RNAs to autism spectrum disorder risk. Int Rev Neurobiol 113: 35‐59, 2013. DOI: 10.1016/B978‐0‐12‐418700‐9.00002‐2.
 163.Wright CF, FitzPatrick DR, Firth HV. Paediatric genomics: Diagnosing rare disease in children. Nat Rev Genet 19: 253‐268, 2018. DOI: 10.1038/nrg.2017.116.
 164.Xue Y, Zhou F, Fu C, Xu Y, Yao X. SUMOsp: A web server for sumoylation site prediction. Nucleic Acids Res 34: W254‐W257, 2006. DOI: 10.1093/nar/gkl207.
 165.Yamada Y, Kato K, Oguri M, Horibe H, Fujimaki T, Yasukochi Y, Takeuchi I, Sakuma J. Identification of 13 novel susceptibility loci for early‐onset myocardial infarction, hypertension, or chronic kidney disease. Int J Mol Med 42: 2415‐2436, 2018. DOI: 10.3892/ijmm.2018.3852.
 166.Yamanaka S. Induced pluripotent stem cells: Past, present, and future. Cell Stem Cell 10: 678‐684, 2012. DOI: 10.1016/j.stem.2012.05.005.
 167.Yari M, Bitarafan S, Broumand MA, Fazeli Z, Rahimi M, Ghaderian SMH, Mirfakhraie R, Omrani MD. Association between long noncoding RNA ANRIL expression variants and susceptibility to coronary artery disease. Int J Mol Cell Med 7: 1‐7, 2018. DOI: 10.22088/IJMCM.BUMS.7.1.1.
 168.Yeo NC, O'Meara CC, Bonomo JA, Veth KN, Tomar R, Flister MJ, Drummond IA, Bowden DW, Freedman BI, Lazar J, Link BA, Jacob HJ. Shroom3 contributes to the maintenance of the glomerular filtration barrier integrity. Genome Res 25: 57‐65, 2015. DOI: 10.1101/gr.182881.114.
 169.Zamore PD, Tuschl T, Sharp PA, Bartel DP. RNAi: Double‐stranded RNA directs the ATP‐dependent cleavage of mRNA at 21 to 23 nucleotide intervals. Cell 101: 25‐33, 2000. DOI: 10.1016/S0092‐8674(00)80620‐0.
 170.Zhang F, Lupski JR. Non‐coding genetic variants in human disease. Hum Mol Genet 24: R102‐R110, 2015. DOI: 10.1093/hmg/ddv259.
 171.Zhang W, Zeng B, Yang M, Yang H, Wang J, Deng Y, Zhang H, Yao G, Wu S, Li W. ncRNAVar: A manually curated database for identification of noncoding RNA variants associated with human diseases. J Mol Biol 433: 166727, 2021. DOI: 10.1016/j.jmb.2020.166727.
 172.Zhu Y, Zhang D, Zhou D, Li Z, Li Z, Fang L, Yang M, Shan Z, Li H, Chen J, Zhou X, Ye W, Yu S, Li H, Cai L, Liu C, Zhang J, Wang L, Lai Y, Ruan L, Sun Z, Zhang S, Wang H, Liu Y, Xu Y, Ling J, Xu C, Zhang Y, Lv D, Yuan Z, Zhang J, Zhang Y, Shi Y, Lai M. Susceptibility loci for metabolic syndrome and metabolic components identified in Han Chinese: A multi‐stage genome‐wide association study. J Cell Mol Med 21: 1106‐1116, 2017. DOI: 10.1111/jcmm.13042.
 173.Zou Z, Liu C, Che C, Huang H. Clinical genetics of Alzheimer's disease. Biomed Res Int 2014: 291862, 2014. DOI: 10.1155/2014/291862.

Contact Editor

Submit a note to the editor about this article by filling in the form below.

* Required Field

How to Cite

Jeremy W. Prokop, Vladislav Jdanov, Lane Savage, Michele Morris, Neil Lamb, Elizabeth VanSickle, Cynthia L. Stenger, Surender Rajasekaran, Caleb P. Bupp. Computational and Experimental Analysis of Genetic Variants. Compr Physiol 2022, 12: 3303-3336. doi: 10.1002/cphy.c210012