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.

The Human Gene Mutation Database (HGMD) constitutes a comprehensive core collection of data on germ‐line mutations in nuclear genes underlying or associated with human inherited disease (www.hgmd.org). Data catalogued includes: single base‐pair substitutions in coding, regulatory and splicing‐relevant regions; micro‐deletions and micro‐insertions; indels; triplet repeat expansions as well as gross deletions; insertions; duplications; and complex rearrangements. Each mutation is entered into HGMD only once in order to avoid confusion between recurrent and identical‐by‐descent lesions. By March 2003, the database contained in excess of 39,415 different lesions detected in 1,516 different nuclear genes, with new entries currently accumulating at a rate exceeding 5,000 per annum. Since its inception, HGMD has been expanded to include cDNA reference sequences for more than 87% of listed genes, splice junction sequences, disease‐associated and functional polymorphisms, as well as links to data present in publicly available online locus‐specific mutation databases. Although HGMD has recently entered into a licensing agreement with Celera Genomics (Rockville, MD), mutation data will continue to be made freely available via the Internet. Hum Mutat 21:577–581, 2003.

The rate at which nonsynonymous single nucleotide polymorphisms (nsSNPs) are being identified in the human genome is increasing dramatically owing to advances in whole‐genome/whole‐exome sequencing technologies. Automated methods capable of accurately and reliably distinguishing between pathogenic and functionally neutral nsSNPs are therefore assuming ever‐increasing importance. Here, we describe the Functional Analysis Through Hidden Markov Models (FATHMM) software and server: a species‐independent method with optional species‐specific weightings for the prediction of the functional effects of protein missense variants. Using a model weighted for human mutations, we obtained performance accuracies that outperformed traditional prediction methods (i.e., SIFT, PolyPhen, and PANTHER) on two separate benchmarks. Furthermore, in one benchmark, we achieve performance accuracies that outperform current state‐of‐the‐art prediction methods (i.e., SNPs&GO and MutPred). We demonstrate that FATHMM can be efficiently applied to high‐throughput/large‐scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations. To illustrate this, we evaluated nsSNPs in wheat (Triticum spp.) to identify some of the important genetic variants responsible for the phenotypic differences introduced by intense selection during domestication. A Web‐based implementation of FATHMM, including a high‐throughput batch facility and a downloadable standalone package, is available at http://fathmm.biocompute.org.uk.

The Human Gene Mutation Database (HGMD ^® ) is a comprehensive collection of germline mutations in nuclear genes that underlie, or are associated with, human inherited disease. By June 2013, the database contained over 141,000 different lesions detected in over 5,700 different genes, with new mutation entries currently accumulating at a rate exceeding 10,000 per annum. HGMD was originally established in 1996 for the scientific study of mutational mechanisms in human genes. However, it has since acquired a much broader utility as a central unified disease-oriented mutation repository utilized by human molecular geneticists, genome scientists, molecular biologists, clinicians and genetic counsellors as well as by those specializing in biopharmaceuticals, bioinformatics and personalized genomics. The public version of HGMD ( https://www.hgmd.cf.ac.uk ) is freely available to registered users from academic institutions/non-profit organizations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via BIOBASE GmbH.

The Human Gene Mutation Database (HGMD^®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc.