Matthew Pendleton

Bio: Matthew Pendleton is an academic researcher from Icahn School of Medicine at Mount Sinai. The author has contributed to research in topics: Genome & Structural variation. The author has an hindex of 5, co-authored 6 publications receiving 2194 citations.

An integrated map of structural variation in 2,504 human genomes

Abstract: Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Assembly and diploid architecture of an individual human genome via single-molecule technologies

Abstract: We present the first comprehensive analysis of a diploid human genome that combines single-molecule sequencing with single-molecule genome maps. Our hybrid assembly markedly improves upon the contiguity observed from traditional shotgun sequencing approaches, with scaffold N50 values approaching 30 Mb, and we identified complex structural variants (SVs) missed by other high-throughput approaches. Furthermore, by combining Illumina short-read data with long reads, we phased both single-nucleotide variants and SVs, generating haplotypes with over 99% consistency with previous trio-based studies. Our work shows that it is now possible to integrate single-molecule and high-throughput sequence data to generate de novo assembled genomes that approach reference quality.

Characterizing and Overriding the Structural Mechanism of the Quizartinib-Resistant FLT3 “Gatekeeper” F691L Mutation with PLX3397

Abstract: Tyrosine kinase domain mutations are a common cause of acquired clinical resistance to tyrosine kinase inhibitors (TKIs) used to treat cancer, including the FLT3 inhibitor quizartinib. Mutation of kinase "gatekeeper" residues, which control access to an allosteric pocket adjacent to the ATP-binding site, have been frequently implicated in TKI resistance. The molecular underpinnings of gatekeeper mutation-mediated resistance are incompletely understood. We report the first co-crystal structure of FLT3 with the TKI quizartinib, which demonstrates that quizartinib binding relies on essential edge-to-face aromatic interactions with the gatekeeper F691 residue, and F830 within the highly conserved DFG motif in the activation loop. This reliance makes quizartinib critically vulnerable to gatekeeper and activation loop substitutions while minimizing the impact of mutations elsewhere. Moreover, we identify PLX3397, a novel FLT3 inhibitor that retains activity against the F691L mutant due to a binding mode that depends less vitally on specific interactions with the gatekeeper position.

Impact of HCV core gene quasispecies on hepatocellular carcinoma risk among HALT-C trial patients.

Abstract: Mutations at positions 70 and/or 91 in the core protein of genotype-1b, hepatitis C virus (HCV) are associated with hepatocellular carcinoma (HCC) risk in Asian patients. To evaluate this in a US population, the relationship between the percentage of 70 and/or 91 mutant HCV quasispecies in baseline serum samples of chronic HCV patients from the HALT-C trial and the incidence of HCC was determined by deep sequencing. Quasispecies percentage cut-points, ≥42% of non-arginine at 70 (non-R70) or ≥98.5% of non-leucine at 91 (non-L91) had optimal sensitivity at discerning higher or lower HCC risk. In baseline samples, 88.5% of chronic HCV patients who later developed HCC and 68.8% of matched HCC-free control patients had ≥42% non-R70 quasispecies (P = 0.06). Furthermore, 30.8% of patients who developed HCC and 54.7% of matched HCC-free patients had quasispecies with ≥98.5% non-L91 (P = 0.06). By Kaplan-Meier analysis, HCC incidence was higher, but not statistically significant, among patients with quasispecies ≥42% non-R70 (P = 0.08), while HCC incidence was significantly reduced among patients with quasispecies ≥98.5% non-L91 (P = 0.01). In a Cox regression model, non-R70 ≥42% was associated with increased HCC risk. This study of US patients indicates the potential utility of HCV quasispecies analysis as a non-invasive biomarker of HCC risk.

A global reference for human genetic variation.

Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

Coming of age: ten years of next-generation sequencing technologies

Abstract: Since the completion of the human genome project in 2003, extraordinary progress has been made in genome sequencing technologies, which has led to a decreased cost per megabase and an increase in the number and diversity of sequenced genomes. An astonishing complexity of genome architecture has been revealed, bringing these sequencing technologies to even greater advancements. Some approaches maximize the number of bases sequenced in the least amount of time, generating a wealth of data that can be used to understand increasingly complex phenotypes. Alternatively, other approaches now aim to sequence longer contiguous pieces of DNA, which are essential for resolving structurally complex regions. These and other strategies are providing researchers and clinicians a variety of tools to probe genomes in greater depth, leading to an enhanced understanding of how genome sequence variants underlie phenotype and disease.

An integrated map of structural variation in 2,504 human genomes

Abstract: Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Pan-cancer analysis of whole genomes

Abstract: Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1,2,3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10,11,12,13,14,15,16,17,18.

Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder

Abstract: Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.