Robert E. Handsaker
Harvard University
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Publication
Featured researches published by Robert E. Handsaker.
Nature | 2009
Brian J. Haas; Sophien Kamoun; Michael C. Zody; Rays H. Y. Jiang; Robert E. Handsaker; Liliana M. Cano; Manfred Grabherr; Chinnappa D. Kodira; Sylvain Raffaele; Trudy Torto-Alalibo; Tolga O. Bozkurt; Audrey M. V. Ah-Fong; Lucia Alvarado; Vicky L. Anderson; Miles R. Armstrong; Anna O. Avrova; Laura Baxter; Jim Beynon; Petra C. Boevink; Stephanie R. Bollmann; Jorunn I. B. Bos; Vincent Bulone; Guohong Cai; Cahid Cakir; James C. Carrington; Megan Chawner; Lucio Conti; Stefano Costanzo; Richard Ewan; Noah Fahlgren
Phytophthora infestans is the most destructive pathogen of potato and a model organism for the oomycetes, a distinct lineage of fungus-like eukaryotes that are related to organisms such as brown algae and diatoms. As the agent of the Irish potato famine in the mid-nineteenth century, P. infestans has had a tremendous effect on human history, resulting in famine and population displacement. To this day, it affects world agriculture by causing the most destructive disease of potato, the fourth largest food crop and a critical alternative to the major cereal crops for feeding the world’s population. Current annual worldwide potato crop losses due to late blight are conservatively estimated at
Nature Genetics | 2008
Steven A. McCarroll; Finny Kuruvilla; Joshua M. Korn; Simon Cawley; James Nemesh; Alec Wysoker; Michael H. Shapero; Paul I. W. de Bakker; Julian Maller; Andrew Kirby; Amanda L. Elliott; Melissa Parkin; Earl Hubbell; Teresa Webster; Rui Mei; James Veitch; Patrick J Collins; Robert E. Handsaker; Steve Lincoln; Marcia M. Nizzari; John E. Blume; Keith W. Jones; Rich Rava; Mark J. Daly; Stacey Gabriel; David Altshuler
6.7 billion. Management of this devastating pathogen is challenged by its remarkable speed of adaptation to control strategies such as genetically resistant cultivars. Here we report the sequence of the P. infestans genome, which at ∼240 megabases (Mb) is by far the largest and most complex genome sequenced so far in the chromalveolates. Its expansion results from a proliferation of repetitive DNA accounting for ∼74% of the genome. Comparison with two other Phytophthora genomes showed rapid turnover and extensive expansion of specific families of secreted disease effector proteins, including many genes that are induced during infection or are predicted to have activities that alter host physiology. These fast-evolving effector genes are localized to highly dynamic and expanded regions of the P. infestans genome. This probably plays a crucial part in the rapid adaptability of the pathogen to host plants and underpins its evolutionary potential.
Nature | 2011
Ryan E. Mills; Klaudia Walter; Chip Stewart; Robert E. Handsaker; Ken Chen; Can Alkan; Alexej Abyzov; Seungtai Yoon; Kai Ye; R. Keira Cheetham; Asif T. Chinwalla; Donald F. Conrad; Yutao Fu; Fabian Grubert; Iman Hajirasouliha; Fereydoun Hormozdiari; Lilia M. Iakoucheva; Zamin Iqbal; Shuli Kang; Jeffrey M. Kidd; Miriam K. Konkel; Joshua M. Korn; Ekta Khurana; Deniz Kural; Hugo Y. K. Lam; Jing Leng; Ruiqiang Li; Yingrui Li; Chang-Yun Lin; Ruibang Luo
Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.
Science | 2012
Daniel G. MacArthur; Suganthi Balasubramanian; Adam Frankish; Ni Huang; James A. Morris; Klaudia Walter; Luke Jostins; Lukas Habegger; Joseph K. Pickrell; Stephen B. Montgomery; Cornelis A. Albers; Zhengdong D. Zhang; Donald F. Conrad; Gerton Lunter; Hancheng Zheng; Qasim Ayub; Mark A. DePristo; Eric Banks; Min Hu; Robert E. Handsaker; Jeffrey A. Rosenfeld; Menachem Fromer; Mike Jin; Xinmeng Jasmine Mu; Ekta Khurana; Kai Ye; Mike Kay; Gary Saunders; Marie-Marthe Suner; Toby Hunt
Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.
Nature | 2016
Aswin Sekar; Allison R. Bialas; Heather de Rivera; Avery Davis; Timothy R. Hammond; Nolan Kamitaki; Katherine Tooley; Jessy Presumey; Matthew A. Baum; Vanessa Van Doren; Giulio Genovese; Samuel A. Rose; Robert E. Handsaker; Mark J. Daly; Michael C. Carroll; Beth Stevens; Steven A. McCarroll
Defective Gene Detective Identifying genes that give rise to diseases is one of the major goals of sequencing human genomes. However, putative loss-of-function genes, which are often some of the first identified targets of genome and exome sequencing, have often turned out to be sequencing errors rather than true genetic variants. In order to identify the true scope of loss-of-function genes within the human genome, MacArthur et al. (p. 823; see the Perspective by Quintana-Murci) extensively validated the genomes from the 1000 Genomes Project, as well as an additional European individual, and found that the average person has about 100 true loss-of-function alleles of which approximately 20 have two copies within an individual. Because many known disease-causing genes were identified in “normal” individuals, the process of clinical sequencing needs to reassess how to identify likely causative alleles. Validation of predicted nonfunctional alleles in the human genome affects the medical interpretation of genomic analyses. Genome-sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. Here we apply stringent filters to 2951 putative LoF variants obtained from 185 human genomes to determine their true prevalence and properties. We estimate that human genomes typically contain ~100 genuine LoF variants with ~20 genes completely inactivated. We identify rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease–causing variants, as well as common LoF variants in nonessential genes. We describe functional and evolutionary differences between LoF-tolerant and recessive disease genes and a method for using these differences to prioritize candidate genes found in clinical sequencing studies.
Nature | 2015
Peter H. Sudmant; Tobias Rausch; Eugene J. Gardner; Robert E. Handsaker; Alexej Abyzov; John Huddleston; Zhang Y; Kai Ye; Goo Jun; Markus His Yang Fritz; Miriam K. Konkel; Ankit Malhotra; Adrian M. Stütz; Xinghua Shi; Francesco Paolo Casale; Jieming Chen; Fereydoun Hormozdiari; Gargi Dayama; Ken Chen; Maika Malig; Mark Chaisson; Klaudia Walter; Sascha Meiers; Seva Kashin; Erik Garrison; Adam Auton; Hugo Y. K. Lam; Xinmeng Jasmine Mu; Can Alkan; Danny Antaki
Schizophrenia is a heritable brain illness with unknown pathogenic mechanisms. Schizophrenia’s strongest genetic association at a population level involves variation in the major histocompatibility complex (MHC) locus, but the genes and molecular mechanisms accounting for this have been challenging to identify. Here we show that this association arises in part from many structurally diverse alleles of the complement component 4 (C4) genes. We found that these alleles generated widely varying levels of C4A and C4B expression in the brain, with each common C4 allele associating with schizophrenia in proportion to its tendency to generate greater expression of C4A. Human C4 protein localized to neuronal synapses, dendrites, axons, and cell bodies. In mice, C4 mediated synapse elimination during postnatal development. These results implicate excessive complement activity in the development of schizophrenia and may help explain the reduced numbers of synapses in the brains of individuals with schizophrenia.
Nature Genetics | 2011
Robert E. Handsaker; Joshua M. Korn; James Nemesh; Steven A. McCarroll
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.
Cell Stem Cell | 2014
Evangelos Kiskinis; Jackson Sandoe; Luis A. Williams; Gabriella L. Boulting; Rob Moccia; Brian J. Wainger; Steve S.W. Han; Theodore Peng; Sebastian Thams; Shravani Mikkilineni; Cassidy Mellin; Florian T. Merkle; Brandi N. Davis-Dusenbery; Michael J. Ziller; Derek Oakley; Justin K. Ichida; Stefania Di Costanzo; Nick Atwater; Morgan L. Maeder; Mathew J. Goodwin; James Nemesh; Robert E. Handsaker; Daniel Paull; Scott Noggle; Steven A. McCarroll; J. Keith Joung; Clifford J. Woolf; Robert H. Brown; Kevin Eggan
Accurate and complete analysis of genome variation in large populations will be required to understand the role of genome variation in complex disease. We present an analytical framework for characterizing genome deletion polymorphism in populations using sequence data that are distributed across hundreds or thousands of genomes. Our approach uses population-level concepts to reinterpret the technical features of sequence data that often reflect structural variation. In the 1000 Genomes Project pilot, this approach identified deletion polymorphism across 168 genomes (sequenced at 4× average coverage) with sensitivity and specificity unmatched by other algorithms. We also describe a way to determine the allelic state or genotype of each deletion polymorphism in each genome; the 1000 Genomes Project used this approach to type 13,826 deletion polymorphisms (48–995,664 bp) at high accuracy in populations. These methods offer a way to relate genome structural polymorphism to complex disease in populations.
Molecular Psychiatry | 2012
Sarah E. Bergen; Colm O'Dushlaine; Stephan Ripke; Phil H. Lee; Douglas M. Ruderfer; Susanne Akterin; Jennifer L. Moran; Robert E. Handsaker; Lena Backlund; Urban Ösby; Steven A. McCarroll; Mikael Landén; Edward M. Scolnick; Patrik K. E. Magnusson; Paul Lichtenstein; Christina M. Hultman; Shaun Purcell; Pamela Sklar; Patrick F. Sullivan
Although many distinct mutations in a variety of genes are known to cause Amyotrophic Lateral Sclerosis (ALS), it remains poorly understood how they selectively impact motor neuron biology and whether they converge on common pathways to cause neuronal degeneration. Here, we have combined reprogramming and stem cell differentiation approaches with genome engineering and RNA sequencing to define the transcriptional and functional changes that are induced in human motor neurons by mutant SOD1. Mutant SOD1 protein induced a transcriptional signature indicative of increased oxidative stress, reduced mitochondrial function, altered subcellular transport, and activation of the ER stress and unfolded protein response pathways. Functional studies demonstrated that these pathways were perturbed in a manner dependent on the SOD1 mutation. Finally, interrogation of stem-cell-derived motor neurons produced from ALS patients harboring a repeat expansion in C9orf72 indicates that at least a subset of these changes are more broadly conserved in ALS.
Nature Genetics | 2013
Andrew Kirby; Andreas Gnirke; David B. Jaffe; Veronika Barešová; Nathalie Pochet; Brendan Blumenstiel; Chun Ye; Daniel Aird; Christine Stevens; James Robinson; Moran N. Cabili; Irit Gat-Viks; Edward Kelliher; Riza Daza; Matthew DeFelice; Helena Hůlková; Jana Sovová; Petr Vylet’al; Corinne Antignac; Mitchell Guttman; Robert E. Handsaker; Danielle Perrin; Scott Steelman; Snaevar Sigurdsson; Steven J. Scheinman; Carrie Sougnez; Kristian Cibulskis; Melissa Parkin; Todd Green; Elizabeth Rossin
Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders with overlapping susceptibility loci and symptomatology. We conducted a genome-wide association study (GWAS) of these disorders in a large Swedish sample. We report a new and independent case–control analysis of 1507 SCZ cases, 836 BD cases and 2093 controls. No single-nucleotide polymorphisms (SNPs) achieved significance in these new samples; however, combining new and previously reported SCZ samples (2111 SCZ and 2535 controls) revealed a genome-wide significant association in the major histocompatibility complex (MHC) region (rs886424, P=4.54 × 10−8). Imputation using multiple reference panels and meta-analysis with the Psychiatric Genomics Consortium SCZ results underscored the broad, significant association in the MHC region in the full SCZ sample. We evaluated the role of copy number variants (CNVs) in these subjects. As in prior reports, deletions were enriched in SCZ, but not BD cases compared with controls. Singleton deletions were more frequent in both case groups compared with controls (SCZ: P=0.003, BD: P=0.013), whereas the largest CNVs (>500 kb) were significantly enriched only in SCZ cases (P=0.0035). Two CNVs with previously reported SCZ associations were also overrepresented in this SCZ sample: 16p11.2 duplications (P=0.0035) and 22q11 deletions (P=0.03). These results reinforce prior reports of significant MHC and CNV associations in SCZ, but not BD.