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Dive into the research topics where Klaudia Walter is active.

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Featured researches published by Klaudia Walter.


Nature | 2010

Origins and functional impact of copy number variation in the human genome

Donald F. Conrad; Dalila Pinto; Richard Redon; Lars Feuk; Omer Gokcumen; Yujun Zhang; Jan Aerts; T. Daniel Andrews; C. Barnes; Peter J. Campbell; Tomas Fitzgerald; Min Hu; Chun Hwa Ihm; Kati Kristiansson; Daniel G. MacArthur; Jeffrey R. MacDonald; Ifejinelo Onyiah; Andy Wing Chun Pang; Samuel Robson; Kathy Stirrups; Armand Valsesia; Klaudia Walter; John T. Wei; Chris Tyler-Smith; Nigel P. Carter; Charles Lee; Stephen W. Scherer

Structural variations of DNA greater than 1 kilobase in size account for most bases that vary among human genomes, but are still relatively under-ascertained. Here we use tiling oligonucleotide microarrays, comprising 42 million probes, to generate a comprehensive map of 11,700 copy number variations (CNVs) greater than 443 base pairs, of which most (8,599) have been validated independently. For 4,978 of these CNVs, we generated reference genotypes from 450 individuals of European, African or East Asian ancestry. The predominant mutational mechanisms differ among CNV size classes. Retrotransposition has duplicated and inserted some coding and non-coding DNA segments randomly around the genome. Furthermore, by correlation with known trait-associated single nucleotide polymorphisms (SNPs), we identified 30 loci with CNVs that are candidates for influencing disease susceptibility. Despite this, having assessed the completeness of our map and the patterns of linkage disequilibrium between CNVs and SNPs, we conclude that, for complex traits, the heritability void left by genome-wide association studies will not be accounted for by common CNVs.


Nature | 2011

Mapping copy number variation by population-scale genome sequencing

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

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.


PLOS Biology | 2004

Highly Conserved Non-Coding Sequences Are Associated with Vertebrate Development

Adam Woolfe; Martin Goodson; Debbie K. Goode; Phil Snell; Gayle K. McEwen; Tanya Vavouri; Sarah Smith; Phil North; Heather Callaway; Krys Kelly; Klaudia Walter; Irina I. Abnizova; Walter R. Gilks; Yvonne J. K. Edwards; Julie Cooke; Greg Elgar

In addition to protein coding sequence, the human genome contains a significant amount of regulatory DNA, the identification of which is proving somewhat recalcitrant to both in silico and functional methods. An approach that has been used with some success is comparative sequence analysis, whereby equivalent genomic regions from different organisms are compared in order to identify both similarities and differences. In general, similarities in sequence between highly divergent organisms imply functional constraint. We have used a whole-genome comparison between humans and the pufferfish, Fugu rubripes, to identify nearly 1,400 highly conserved non-coding sequences. Given the evolutionary divergence between these species, it is likely that these sequences are found in, and furthermore are essential to, all vertebrates. Most, and possibly all, of these sequences are located in and around genes that act as developmental regulators. Some of these sequences are over 90% identical across more than 500 bases, being more highly conserved than coding sequence between these two species. Despite this, we cannot find any similar sequences in invertebrate genomes. In order to begin to functionally test this set of sequences, we have used a rapid in vivo assay system using zebrafish embryos that allows tissue-specific enhancer activity to be identified. Functional data is presented for highly conserved non-coding sequences associated with four unrelated developmental regulators (SOX21, PAX6, HLXB9, and SHH), in order to demonstrate the suitability of this screen to a wide range of genes and expression patterns. Of 25 sequence elements tested around these four genes, 23 show significant enhancer activity in one or more tissues. We have identified a set of non-coding sequences that are highly conserved throughout vertebrates. They are found in clusters across the human genome, principally around genes that are implicated in the regulation of development, including many transcription factors. These highly conserved non-coding sequences are likely to form part of the genomic circuitry that uniquely defines vertebrate development.


Science | 2012

A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes

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

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

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

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

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.


Nature Genetics | 2014

An atlas of genetic influences on human blood metabolites.

So-Youn Shin; Eric Fauman; Ann-Kristin Petersen; Jan Krumsiek; Rita Santos; Jie Huang; Matthias Arnold; Idil Erte; Vincenzo Forgetta; Tsun-Po Yang; Klaudia Walter; Cristina Menni; Lu Chen; Louella Vasquez; Ana M. Valdes; Craig L. Hyde; Vicky Wang; Daniel Ziemek; Phoebe M. Roberts; Li Xi; Elin Grundberg; Melanie Waldenberger; J. Brent Richards; Robert P. Mohney; Michael V. Milburn; Sally John; Jeff Trimmer; Fabian J. Theis; John P. Overington; Karsten Suhre

Genome-wide association scans with high-throughput metabolic profiling provide unprecedented insights into how genetic variation influences metabolism and complex disease. Here we report the most comprehensive exploration of genetic loci influencing human metabolism thus far, comprising 7,824 adult individuals from 2 European population studies. We report genome-wide significant associations at 145 metabolic loci and their biochemical connectivity with more than 400 metabolites in human blood. We extensively characterize the resulting in vivo blueprint of metabolism in human blood by integrating it with information on gene expression, heritability and overlap with known loci for complex disorders, inborn errors of metabolism and pharmacological targets. We further developed a database and web-based resources for data mining and results visualization. Our findings provide new insights into the role of inherited variation in blood metabolic diversity and identify potential new opportunities for drug development and for understanding disease.


Cell | 2016

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease

William Astle; Heather Elding; Tao Jiang; Dave Allen; Dace Ruklisa; Alice L. Mann; Daniel Mead; Heleen Bouman; Fernando Riveros-Mckay; Myrto Kostadima; John J. Lambourne; Suthesh Sivapalaratnam; Kate Downes; Kousik Kundu; Lorenzo Bomba; Kim Berentsen; John R. Bradley; Louise C. Daugherty; Olivier Delaneau; Kathleen Freson; Stephen F. Garner; Luigi Grassi; Jose A. Guerrero; Matthias Haimel; Eva M. Janssen-Megens; Anita M. Kaan; Mihir Anant Kamat; Bowon Kim; Amit Mandoli; Jonathan Marchini

Summary Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.


Nature Communications | 2015

Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

Jie Huang; Bryan Howie; Shane McCarthy; Yasin Memari; Klaudia Walter; Jl Min; Petr Danecek; Giovanni Malerba; Elisabetta Trabetti; Hou-Feng Zheng; Giovanni Gambaro; Jb Richards; Richard Durbin; Nj Timpson; Jonathan Marchini; Nicole Soranzo

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.


Cell | 2016

Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells

Lu Chen; Bing Ge; Francesco Paolo Casale; Louella Vasquez; Tony Kwan; Diego Garrido-Martín; Stephen Watt; Ying Yan; Kousik Kundu; Simone Ecker; Avik Datta; David C. Richardson; Frances Burden; Daniel Mead; Alice L. Mann; José María Fernández; Sophia Rowlston; Steven P. Wilder; Samantha Farrow; Xiaojian Shao; John J. Lambourne; Adriana Redensek; Cornelis A. Albers; Vyacheslav Amstislavskiy; Sofie Ashford; Kim Berentsen; Lorenzo Bomba; Guillaume Bourque; David Bujold; Stephan Busche

Summary Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.


The Journal of Infectious Diseases | 2004

Increases in human T helper 2 cytokine responses to Schistosoma mansoni worm and worm-tegument antigens are induced by treatment with praziquantel.

Sarah Joseph; Frances M. Jones; Klaudia Walter; A. J. C. Fulford; Gachuhi Kimani; Joseph K. Mwatha; Timothy Kamau; Henry C. Kariuki; Francis Kazibwe; Edridah M. Tukahebwa; Narcis B. Kabatereine; John H. Ouma; Birgitte J. Vennervald; David W. Dunne

Levels of Schistosoma mansoni-induced interleukin (IL)-4 and IL-5 and posttreatment levels of immunoglobulin E recognizing the parasites tegument (Teg) correlate with human resistance to subsequent reinfection after treatment. We measured changes in whole-blood cytokine production in response to soluble egg antigen (SEA), soluble worm antigen (SWA), or Teg after treatment with praziquantel (PZQ) in a cohort of 187 individuals living near Lake Albert, Uganda. Levels of SWA-induced IL-4, IL-5, IL-10, and IL-13 increased after treatment with PZQ, and the greatest relative increases were seen in the responses to Teg. Mean levels of Teg-specific IL-5 and IL-10 increased ~10-15-fold, and mean levels of IL-13 increased ~5-fold. Correlations between the changes in cytokines suggested that their production was positively coregulated by tegumentally derived antigens. Levels of SEA-, SWA-, and Teg-induced interferon- gamma were not significantly changed by treatment, and, with the exception of IL-10, which increased slightly, responses to SEA also remained largely unchanged. The changes in cytokines were not strongly influenced by age or intensity of infection and were not accompanied by corresponding increases in the numbers of circulating eosinophils or lymphocytes.

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Jie Huang

Wellcome Trust Sanger Institute

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Yasin Memari

Wellcome Trust Sanger Institute

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Daniel Mead

Wellcome Trust Sanger Institute

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Irina I. Abnizova

Wellcome Trust Sanger Institute

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John Perry

University of Cambridge

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Nicole Soranzo

Wellcome Trust Sanger Institute

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Shane McCarthy

Wellcome Trust Sanger Institute

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