Isolation and characterization of 10 MHC Class I-associated microsatellite loci in tammar wallaby (Macropus eugenii)

The major histocompatibility complex (MHC) contain genes which play a key role in immune response and mate choice, and are therefore of functional importance to molecular ecologists. Here we describe the design of 10 MHC Class I-associated microsatellite loci from the tammar wallaby. All 10 loci are highly polymorphic, with the expected heterozygosity ranging from 0.547 to 0.919. Six loci successfully cross-amplify in other macropodid species. These microsatellites will serve as useful tools for studying the level of MHC diversity, the impact of selection on genetic variation and the unique structure of the tammar wallaby MHC.

Sequencing and comparative analysis of the gorilla MHC genomic sequence

Major histocompatibility complex (MHC) genes play a critical role in vertebrate immune response and because the MHC is linked to a significant number of auto-immune and other diseases it is of great medical interest. Here we describe the clone-based sequencing and subsequent annotation of the MHC region of the gorilla genome. Because the MHC is subject to extensive variation, both structural and sequence-wise, it is not readily amenable to study in whole genome shotgun sequence such as the recently published gorilla genome. The variation of the MHC also makes it of evolutionary interest and therefore we analyse the sequence in the context of human and chimpanzee. In our comparisons with human and re-annotated chimpanzee MHC sequence we find that gorilla has a trimodular RCCX cluster, versus the reference human bimodular cluster, and additional copies of Class I (pseudo)genes between Gogo-K and Gogo-A (the orthologues of HLA-K and -A). We also find that Gogo-H (and Patr-H) is coding versus the HLA-H pseudogene and, conversely, there is a Gogo-DQB2 pseudogene versus the HLA-DQB2 coding gene. Our analysis, which is freely available through the VEGA genome browser, provides the research community with a comprehensive dataset for comparative and evolutionary research of the MHC.

The Pfam protein families database

Pfam is a widely used database of protein families, currently containing more than 13,000 manually curated protein families as of release 26.0. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/). Here, we report on changes that have occurred since our 2010 NAR paper (release 24.0). Over the last 2 years, we have generated 1840 new families and increased coverage of the UniProt Knowledgebase (UniProtKB) to nearly 80%. Notably, we have taken the step of opening up the annotation of our families to the Wikipedia community, by linking Pfam families to relevant Wikipedia pages and encouraging the Pfam and Wikipedia communities to improve and expand those pages. We continue to improve the Pfam website and add new visualizations, such as the 'sunburst' representation of taxonomic distribution of families. In this work we additionally address two topics that will be of particular interest to the Pfam community. First, we explain the definition and use of family-specific, manually curated gathering thresholds. Second, we discuss some of the features of domains of unknown function (also known as DUFs), which constitute a rapidly growing class of families within Pfam.

The Pfam protein families database

Pfam is a comprehensive collection of protein domains and families, represented as multiple sequence alignments and as profile hidden Markov models. The current release of Pfam (22.0) contains 9318 protein families. Pfam is now based not only on the UniProtKB sequence database, but also on NCBI GenPept and on sequences from selected metagenomics projects. Pfam is available on the web from the consortium members using a new, consistent and improved website design in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/), as well as from mirror sites in France (http://pfam.jouy.inra.fr/) and South Korea (http://pfam.ccbb.re.kr/).

A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms

We describe a map of 1.42 million single nucleotide polymorphisms (SNPs) distributed throughout the human genome, providing an average density on available sequence of one SNP every 1.9 kilobases. These SNPs were primarily discovered by two projects: The SNP Consortium and the analysis of clone overlaps by the International Human Genome Sequencing Consortium. The map integrates all publicly available SNPs with described genes and other genomic features. We estimate that 60,000 SNPs fall within exon (coding and untranslated regions), and 85% of exons are within 5 kb of the nearest SNP. Nucleotide diversity varies greatly across the genome, in a manner broadly consistent with a standard population genetic model of human history. This high-density SNP map provides a public resource for defining haplotype variation across the genome, and should help to identify biomedically important genes for diagnosis and therapy.

An SNP map of human chromosome 22

The human genome sequence will provide a reference for measuring DNA sequence variation in human populations. Sequence variants are responsible for the genetic component of individuality, including complex characteristics such as disease susceptibility and drug response. Most sequence variants are single nucleotide polymorphisms (SNPs), where two alternate bases occur at one position. Comparison of any two genomes reveals around 1 SNP per kilobase. A sufficiently dense map of SNPs would allow the detection of sequence variants responsible for particular characteristics on the basis that they are associated with a specific SNP allele. Here we have evaluated large-scale sequencing approaches to obtaining SNPs, and have constructed a map of 2,730 SNPs on human chromosome 22. Most of the SNPs are within 25 kilobases of a transcribed exon, and are valuable for association studies. We have scaled up the process, detecting over 65,000 SNPs in the genome as part of The SNP Consortium programme, which is on target to build a map of 1 SNP every 5 kilobases that is integrated with the human genome sequence and that is freely available in the public domain.