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      Characterising and Predicting Haploinsufficiency in the Human Genome

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          Abstract

          Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.

          Author Summary

          Humans, like most complex organisms, have two copies of most genes in their genome, one from the mother and one from the father. This redundancy provides a back-up copy for most genes, should one copy be lost through mutation. For a minority of genes, one functional copy is not enough to sustain normal human function, and mutations causing the loss of function of one of the copies of such genes are a major cause of childhood developmental diseases. Over the past 20 years medical geneticists have identified over 300 such genes, but it is not known how many of the 22,000 genes in our genome may also be sensitive to gene loss. By comparing these ∼300 genes known to be sensitive to gene loss with over 1,000 genes where loss of a single copy does not result in disease, we have identified some key evolutionary and functional similarities between genes sensitive to loss of a single copy. We have used these similarities to predict for most genes in the genome, whether loss of a single copy is likely to result in disease. These predictions will help in the interpretation of mutations seen in patients.

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          Most cited references26

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          Ensembl 2009

          The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases, and other information for chordate, selected model organism and disease vector genomes. As of release 51 (November 2008), Ensembl fully supports 45 species, and three additional species have preliminary support. New species in the past year include orangutan and six additional low coverage mammalian genomes. Major additions and improvements to Ensembl since our previous report include a major redesign of our website; generation of multiple genome alignments and ancestral sequences using the new Enredo-Pecan-Ortheus pipeline and development of our software infrastructure, particularly to support the Ensembl Genomes project (http://www.ensemblgenomes.org/).
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            MINT: the Molecular INTeraction database

            The Molecular INTeraction database (MINT, ) aims at storing, in a structured format, information about molecular interactions (MIs) by extracting experimental details from work published in peer-reviewed journals. At present the MINT team focuses the curation work on physical interactions between proteins. Genetic or computationally inferred interactions are not included in the database. Over the past four years MINT has undergone extensive revision. The new version of MINT is based on a completely remodeled database structure, which offers more efficient data exploration and analysis, and is characterized by entries with a richer annotation. Over the past few years the number of curated physical interactions has soared to over 95 000. The whole dataset can be freely accessed online in both interactive and batch modes through web-based interfaces and an FTP server. MINT now includes, as an integrated addition, HomoMINT, a database of interactions between human proteins inferred from experiments with ortholog proteins in model organisms ().
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              Integrated detection and population-genetic analysis of SNPs and copy number variation.

              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.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                October 2010
                October 2010
                14 October 2010
                : 6
                : 10
                : e1001154
                Affiliations
                [1 ]Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
                [2 ]Center for Systems and Synthetic Biology, Department of Chemistry and Biochemistry, Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, United States of America
                [3 ]Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, South Korea
                University of Aarhus, Denmark
                Author notes

                Conceived and designed the experiments: NH MEH. Analyzed the data: NH. Contributed reagents/materials/analysis tools: IL EMM. Wrote the paper: NH MEH.

                Article
                10-PLGE-RA-2311R2
                10.1371/journal.pgen.1001154
                2954820
                20976243
                a99e1892-d786-4a3d-beaf-ee27ce456c04
                Huang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 6 January 2010
                : 10 September 2010
                Page count
                Pages: 11
                Categories
                Research Article
                Evolutionary Biology/Genomics
                Genetics and Genomics/Genetics of Disease
                Genetics and Genomics/Population Genetics

                Genetics
                Genetics

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