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Andreas Schlattl

Bio: Andreas Schlattl is an academic researcher from European Bioinformatics Institute. The author has contributed to research in topics: Genomics & Genome. The author has an hindex of 5, co-authored 6 publications receiving 3168 citations.

Papers
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Journal ArticleDOI
Peter H. Sudmant1, Tobias Rausch, Eugene J. Gardner2, Robert E. Handsaker3, Robert E. Handsaker4, Alexej Abyzov5, John Huddleston1, Yan Zhang6, Kai Ye7, Goo Jun8, Goo Jun9, Markus His Yang Fritz, Miriam K. Konkel10, Ankit Malhotra, Adrian M. Stütz, Xinghua Shi11, Francesco Paolo Casale12, Jieming Chen6, Fereydoun Hormozdiari1, Gargi Dayama9, Ken Chen13, Maika Malig1, Mark Chaisson1, Klaudia Walter12, Sascha Meiers, Seva Kashin3, Seva Kashin4, Erik Garrison14, Adam Auton15, Hugo Y. K. Lam, Xinmeng Jasmine Mu6, Xinmeng Jasmine Mu4, Can Alkan16, Danny Antaki17, Taejeong Bae5, Eliza Cerveira, Peter S. Chines18, Zechen Chong13, Laura Clarke12, Elif Dal16, Li Ding7, S. Emery9, Xian Fan13, Madhusudan Gujral17, Fatma Kahveci16, Jeffrey M. Kidd9, Yu Kong15, Eric-Wubbo Lameijer19, Shane A. McCarthy12, Paul Flicek12, Richard A. Gibbs20, Gabor T. Marth14, Christopher E. Mason21, Androniki Menelaou22, Androniki Menelaou23, Donna M. Muzny24, Bradley J. Nelson1, Amina Noor17, Nicholas F. Parrish25, Matthew Pendleton24, Andrew Quitadamo11, Benjamin Raeder, Eric E. Schadt24, Mallory Romanovitch, Andreas Schlattl, Robert Sebra24, Andrey A. Shabalin26, Andreas Untergasser27, Jerilyn A. Walker10, Min Wang20, Fuli Yu20, Chengsheng Zhang, Jing Zhang6, Xiangqun Zheng-Bradley12, Wanding Zhou13, Thomas Zichner, Jonathan Sebat17, Mark A. Batzer10, Steven A. McCarroll4, Steven A. McCarroll3, Ryan E. Mills9, Mark Gerstein6, Ali Bashir24, Oliver Stegle12, Scott E. Devine2, Charles Lee28, Evan E. Eichler1, Jan O. Korbel12 
01 Oct 2015-Nature
TL;DR: In this paper, the authors describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which are constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations.
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.

1,971 citations

Journal ArticleDOI
TL;DR: An SV discovery method that integrates short insert paired-ends, long-range mate-pairs and split-read alignments to accurately delineate genomic rearrangements at single-nucleotide resolution, called DELLY, which enables to ascertain the full spectrum of genomic rearrANGements, including complex events.
Abstract: Motivation: The discovery of genomic structural variants (SVs) at high sensitivity and specificity is an essential requirement for characterizing naturally occurring variation and for understanding pathological somatic rearrangements in personal genome sequencing data. Of particular interest are integrated methods that accurately identify simple and complex rearrangements in heterogeneous sequencing datasets at single-nucleotide resolution, as an optimal basis for investigating the formation mechanisms and functional consequences of SVs. Results: We have developed an SV discovery method, called DELLY, that integrates short insert paired-ends, long-range mate-pairs and split-read alignments to accurately delineate genomic rearrangements at single-nucleotide resolution. DELLY is suitable for detecting copy-number variable deletion and tandem duplication events as well as balanced rearrangements such as inversions or reciprocal translocations. DELLY, thus, enables to ascertain the full spectrum of genomic rearrangements, including complex events. On simulated data, DELLY compares favorably to other SV prediction methods across a wide range of sequencing parameters. On real data, DELLY reliably uncovers SVs from the 1000 Genomes Project and cancer genomes, and validation experiments of randomly selected deletion loci show a high specificity. Availability: DELLY is available at www.korbel.embl.de/software.html Contact: ed.lbme@hcsuar.saibot

1,673 citations

Journal ArticleDOI
TL;DR: The results suggest that association studies can gain in resolution and power by including fine-scale CNV information, such as those obtained from population-scale sequencing, as well as elucidated unexpected cases of negative correlations between copy number and expression.
Abstract: Copy-number variants (CNVs) form an abundant class of genetic variation with a presumed widespread impact on individual traits. While recent advances, such as the population-scale sequencing of human genomes, facilitated the fine-scale mapping of CNVs, the phenotypic impact of most of these CNVs remains unclear. By relating copy-number genotypes to transcriptome sequencing data, we have evaluated the impact of CNVs, mapped at fine scale, on gene expression. Based on data from 129 individuals with ancestry from two populations, we identified CNVs associated with the expression of 110 genes, with 13% of the associations involving complex, multiallelic CNVs. Categorization of CNVs according to variant type, size, and gene overlap enabled us to examine the impact of different CNV classes on expression variation. While many small (<4 kb) CNVs were associated with expression variation, overall we observed an enrichment of large duplications and deletions, including large intergenic CNVs, relative to the entire set of expression-associated CNVs. Furthermore, the copy number of genes intersecting with CNVs typically correlated positively with the genes' expression, and also was more strongly correlated with expression than nearby single nucleotide polymorphisms, suggesting a frequent causal role of CNVs in expression quantitative trait loci (eQTLs). We also elucidated unexpected cases of negative correlations between copy number and expression by assessing the CNVs' effects on the structure and regulation of genes. Finally, we examined dosage compensation of transcript levels. Our results suggest that association studies can gain in resolution and power by including fine-scale CNV information, such as those obtained from population-scale sequencing.

106 citations

Journal ArticleDOI
TL;DR: The results indicate that the diploid yeast nuclear genome is remarkably stable during the vegetative and meiotic cell cycles and support the hypothesis that peripheral regions of chromosomes are more dynamic than gene-rich central sections where structural rearrangements could be deleterious.
Abstract: Accurate estimates of mutation rates provide critical information to analyze genome evolution and organism fitness. We used whole-genome DNA sequencing, pulse-field gel electrophoresis, and compara ...

103 citations

Journal ArticleDOI
TL;DR: The utility of CopySeq for analyzing gene regions enriched for segmental duplications is demonstrated by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci and for several OR loci the reference genome appears to represent a minor-frequency variant.
Abstract: Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95-99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ~15% and ~20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing.

74 citations


Cited by
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Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
TL;DR: 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, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
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.

12,661 citations

Journal ArticleDOI
TL;DR: 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.
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.

3,096 citations

Journal ArticleDOI
Ahmet Zehir1, Ryma Benayed1, Ronak Shah1, Aijazuddin Syed1, Sumit Middha1, Hyunjae R. Kim1, Preethi Srinivasan1, Jianjiong Gao1, Debyani Chakravarty1, Sean M. Devlin1, Matthew D. Hellmann1, David Barron1, Alison M. Schram1, Meera Hameed1, Snjezana Dogan1, Dara S. Ross1, Jaclyn F. Hechtman1, Deborah DeLair1, Jinjuan Yao1, Diana Mandelker1, Donavan T. Cheng1, Raghu Chandramohan1, Abhinita Mohanty1, Ryan Ptashkin1, Gowtham Jayakumaran1, Meera Prasad1, Mustafa H Syed1, Anoop Balakrishnan Rema1, Zhen Y Liu1, Khedoudja Nafa1, Laetitia Borsu1, Justyna Sadowska1, Jacklyn Casanova1, Ruben Bacares1, Iwona Kiecka1, Anna Razumova1, Julie B Son1, Lisa Stewart1, Tessara Baldi1, Kerry Mullaney1, Hikmat Al-Ahmadie1, Efsevia Vakiani1, Adam Abeshouse1, Alexander V Penson1, Philip Jonsson1, Niedzica Camacho1, Matthew T. Chang1, Helen Won1, Benjamin Gross1, Ritika Kundra1, Zachary J. Heins1, Hsiao-Wei Chen1, Sarah Phillips1, Hongxin Zhang1, Jiaojiao Wang1, Angelica Ochoa1, Jonathan Wills1, Michael H. Eubank1, Stacy B. Thomas1, Stuart Gardos1, Dalicia N. Reales1, Jesse Galle1, Robert Durany1, Roy Cambria1, Wassim Abida1, Andrea Cercek1, Darren R. Feldman1, Mrinal M. Gounder1, A. Ari Hakimi1, James J. Harding1, Gopa Iyer1, Yelena Y. Janjigian1, Emmet Jordan1, Ciara Marie Kelly1, Maeve A. Lowery1, Luc G. T. Morris1, Antonio Omuro1, Nitya Raj1, Pedram Razavi1, Alexander N. Shoushtari1, Neerav Shukla1, Tara Soumerai1, Anna M. Varghese1, Rona Yaeger1, Jonathan A. Coleman1, Bernard H. Bochner1, Gregory J. Riely1, Leonard B. Saltz1, Howard I. Scher1, Paul Sabbatini1, Mark E. Robson1, David S. Klimstra1, Barry S. Taylor1, José Baselga1, Nikolaus Schultz1, David M. Hyman1, Maria E. Arcila1, David B. Solit1, Marc Ladanyi1, Michael F. Berger1 
TL;DR: A large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer are compiled and identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types.
Abstract: Tumor molecular profiling is a fundamental component of precision oncology, enabling the identification of genomic alterations in genes and pathways that can be targeted therapeutically. The existence of recurrent targetable alterations across distinct histologically defined tumor types, coupled with an expanding portfolio of molecularly targeted therapies, demands flexible and comprehensive approaches to profile clinically relevant genes across the full spectrum of cancers. We established a large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which we have compiled tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer and available pathological and clinical annotations. Using these data, we identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types. Patients were enrolled on genomically matched clinical trials at a rate of 11%. To enable discovery of novel biomarkers and deeper investigation into rare alterations and tumor types, all results are publicly accessible.

2,330 citations

Journal ArticleDOI
Peter H. Sudmant1, Tobias Rausch, Eugene J. Gardner2, Robert E. Handsaker3, Robert E. Handsaker4, Alexej Abyzov5, John Huddleston1, Yan Zhang6, Kai Ye7, Goo Jun8, Goo Jun9, Markus His Yang Fritz, Miriam K. Konkel10, Ankit Malhotra, Adrian M. Stütz, Xinghua Shi11, Francesco Paolo Casale12, Jieming Chen6, Fereydoun Hormozdiari1, Gargi Dayama9, Ken Chen13, Maika Malig1, Mark Chaisson1, Klaudia Walter12, Sascha Meiers, Seva Kashin3, Seva Kashin4, Erik Garrison14, Adam Auton15, Hugo Y. K. Lam, Xinmeng Jasmine Mu4, Xinmeng Jasmine Mu6, Can Alkan16, Danny Antaki17, Taejeong Bae5, Eliza Cerveira, Peter S. Chines18, Zechen Chong13, Laura Clarke12, Elif Dal16, Li Ding7, S. Emery9, Xian Fan13, Madhusudan Gujral17, Fatma Kahveci16, Jeffrey M. Kidd9, Yu Kong15, Eric-Wubbo Lameijer19, Shane A. McCarthy12, Paul Flicek12, Richard A. Gibbs20, Gabor T. Marth14, Christopher E. Mason21, Androniki Menelaou22, Androniki Menelaou23, Donna M. Muzny24, Bradley J. Nelson1, Amina Noor17, Nicholas F. Parrish25, Matthew Pendleton24, Andrew Quitadamo11, Benjamin Raeder, Eric E. Schadt24, Mallory Romanovitch, Andreas Schlattl, Robert Sebra24, Andrey A. Shabalin26, Andreas Untergasser27, Jerilyn A. Walker10, Min Wang20, Fuli Yu20, Chengsheng Zhang, Jing Zhang6, Xiangqun Zheng-Bradley12, Wanding Zhou13, Thomas Zichner, Jonathan Sebat17, Mark A. Batzer10, Steven A. McCarroll4, Steven A. McCarroll3, Ryan E. Mills9, Mark Gerstein6, Ali Bashir24, Oliver Stegle12, Scott E. Devine2, Charles Lee28, Evan E. Eichler1, Jan O. Korbel12 
01 Oct 2015-Nature
TL;DR: In this paper, the authors describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which are constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations.
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.

1,971 citations

Journal ArticleDOI
Peter J. Campbell1, Gad Getz2, Jan O. Korbel3, Joshua M. Stuart4  +1329 moreInstitutions (238)
06 Feb 2020-Nature
TL;DR: The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.
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.

1,600 citations