Kent D Taylor

Dr. Kent D Taylor

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Research Focus & Metrics

Academic Career Length

33Years (1994-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 May 2020 in Nature
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Journal Article
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RCRyan L. Collins
Ryan L. Collins
HBHarrison Brand
Harrison Brand
KKKonrad J. Karczewski
Konrad J. Karczewski
XZXuefang Zhao
Xuefang Zhao
JAJessica Alföldi
Jessica Alföldi
MTMichael E. Talkowski
Michael E. Talkowski
Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

9 January 2020 in Nature Communications
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Journal Article
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SSSonia Shah
Sonia Shah
AHAlbert Henry
Albert Henry
CRCarolina Roselli
Carolina Roselli
HLHonghuang Lin
Honghuang Lin
GSGarðar Sveinbjörnsson
Garðar Sveinbjörnsson
RLR. Thomas Lumbers
R. Thomas Lumbers
Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

17 December 2021 in Science
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Journal Article
Closed access
JSJouni Sirén
Jouni Sirén
JMJean Monlong
Jean Monlong
XCXian Chang
Xian Chang
ANAdam M. Novak
Adam M. Novak
JEJordan M. Eizenga
Jordan M. Eizenga
BPBenedict Paten
Benedict Paten
Giraffe pangenomes: Genomes within a species often have a core, conserved component, as well as a variable set of genetic material among individuals or populations that is referred to as a “pangenome.” Inference of the relationships between pangenomes sequenced with short-read technology is often done computationally by mapping the sequences to a reference genome. The computational method affects genome assembly and comparisons, especially in cases of structural variants that are longer than an average sequenced region, for highly polymorphic loci, and for cross-species analyses. Siren et al . present a bioinformatic method called Giraffe, which improves mapping pangenomes in polymorphic regions of the genome containing single nucleotide polymorphisms and structural variants with standard computational resources, making large-scale genomic analyses more accessible. —LMZ

14 August 2019 in Nature Communications
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JDJoris Deelen
Joris Deelen
DEDaniel S. Evans
Daniel S. Evans
DADan E. Arking
Dan E. Arking
NTNiccolo Tesi
Niccolo Tesi
MNMarianne Nygaard
Marianne Nygaard
JMJoanne Murabito, Murabito
Joanne Murabito, Murabito
Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

23 December 2019 in PLOS Genetics
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MKMadeline H. Kowalski
Madeline H. Kowalski
HQHuijun Qian
Huijun Qian
ZHZiyi Hou
Ziyi Hou
JRJonathan Rosen
Jonathan Rosen
ATAmanda L. Tapia
Amanda L. Tapia
YLYun Li
Yun Li
Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11–34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count 86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations. Admixed African and Hispanic/Latino populations remain understudied in genetic studies of complex diseases. These populations have more complex linkage disequilibrium (LD) structure that can impair mapping of variants. Genotype imputation represents an approach to improve genome coverage, especially for rare or ancestry-specific variation; however, these understudied populations also have smaller relevant imputation reference panels. In this study, we leveraged >100,000 phased sequences generated from the multi-ethnic NHLBI TOPMed project for imputation in ~21,600 individuals of African ancestry (AAs) and ~21,700 Hispanics/Latinos. We demonstrated substantially higher imputation quality for low frequency and rare variants in comparison to the 1000 Genomes Project and Haplotype Reference Consortium reference panels. Analysis of quantitative hematological traits led to the discovery of associations with two rare variants in the HBB gene; one of these variants was replicated in an independent sample, and the other is known to cause anemia in the homozygous state. By comparison, the same HBB variants would not have been genome-wide significant using current reference panels due to lower imputation quality. Our findings demonstrate the power of TOPMed whole genome sequencing data for imputation and subsequent association analysis in admixed African and Hispanic/Latino populations.

11 September 2019 in Nature Communications
Verified
Journal Article
Open access
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ATAlexander Teumer
Alexander Teumer
YLYong Li
Yong Li
SGSahar Ghasemi
Sahar Ghasemi
BPBram Peter Prins
Bram Peter Prins
MWMatthias Wuttke
Matthias Wuttke
AKAnna Köttgen
Anna Köttgen
Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria.