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      Sequencing of the core MHC region of black grouse ( Tetrao tetrix) and comparative genomics of the galliform MHC

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          Abstract

          Background

          The MHC, which is regarded as the most polymorphic region in the genomes of jawed vertebrates, plays a central role in the immune system by encoding various proteins involved in the immune response. The chicken MHC-B genomic region has a highly streamlined gene content compared to mammalian MHCs. Its core region includes genes encoding Class I and Class IIB molecules but is only ~92Kb in length. Sequences of other galliform MHCs show varying degrees of similarity as that of chicken. The black grouse ( Tetrao tetrix) is a wild galliform bird species which is an important model in conservation genetics and ecology. We sequenced the black grouse core MHC-B region and combined this with available data from related species (chicken, turkey, gold pheasant and quail) to perform a comparative genomics study of the galliform MHC. This kind of analysis has previously been severely hampered by the lack of genomic information on avian MHC regions, and the galliformes is still the only bird lineage where such a comparison is possible.

          Results

          In this study, we present the complete genomic sequence of the MHC-B locus of black grouse, which is 88,390 bp long and contains 19 genes. It shows the same simplicity as, and almost perfect synteny with, the corresponding genomic region of chicken. We also use 454-transcriptome sequencing to verify expression in 17 of the black grouse MHC-B genes. Multiple sequence inversions of the TAPBP gene and TAP1-TAP2 gene block identify the recombination breakpoints near the BF and BLB genes. Some of the genes in the galliform MHC-B region also seem to have been affected by selective forces, as inferred from deviating phylogenetic signals and elevated rates of non-synonymous nucleotide substitutions.

          Conclusions

          We conclude that there is large synteny between the MHC-B region of the black grouse and that of other galliform birds, but that some duplications and rearrangements have occurred within this lineage. The MHC-B sequence reported here will provide a valuable resource for future studies on the evolution of the avian MHC genes and on links between immunogenetics and ecology of black grouse.

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          Most cited references43

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          Ab initio gene finding in Drosophila genomic DNA.

          Ab initio gene identification in the genomic sequence of Drosophila melanogaster was obtained using (human gene predictor) and Fgenesh programs that have organism-specific parameters for human, Drosophila, plants, yeast, and nematode. We did not use information about cDNA/EST in most predictions to model a real situation for finding new genes because information about complete cDNA is often absent or based on very small partial fragments. We investigated the accuracy of gene prediction on different levels and designed several schemes to predict an unambiguous set of genes (annotation CGG1), a set of reliable exons (annotation CGG2), and the most complete set of exons (annotation CGG3). For 49 genes, protein products of which have clear homologs in protein databases, predictions were recomputed by Fgenesh+ program. The first annotation serves as the optimal computational description of new sequence to be presented in a database. Reliable exons from the second annotation serve as good candidates for selecting the PCR primers for experimental work for gene structure verification. Our results shows that we can identify approximately 90% of coding nucleotides with 20% false positives. At the exon level we accurately predicted 65% of exons and 89% including overlapping exons with 49% false positives. Optimizing accuracy of prediction, we designed a gene identification scheme using Fgenesh, which provided sensitivity (Sn) = 98% and specificity (Sp) = 86% at the base level, Sn = 81% (97% including overlapping exons) and Sp = 58% at the exon level and Sn = 72% and Sp = 39% at the gene level (estimating sensitivity on std1 set and specificity on std3 set). In general, these results showed that computational gene prediction can be a reliable tool for annotating new genomic sequences, giving accurate information on 90% of coding sequences with 14% false positives. However, exact gene prediction (especially at the gene level) needs additional improvement using gene prediction algorithms. The program was also tested for predicting genes of human Chromosome 22 (the last variant of Fgenesh can analyze the whole chromosome sequence). This analysis has demonstrated that the 88% of manually annotated exons in Chromosome 22 were among the ab initio predicted exons. The suite of gene identification programs is available through the WWW server of Computational Genomics Group at http://genomic.sanger.ac.uk/gf. html.
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            Mapping and sequencing of structural variation from eight human genomes.

            Genetic variation among individual humans occurs on many different scales, ranging from gross alterations in the human karyotype to single nucleotide changes. Here we explore variation on an intermediate scale--particularly insertions, deletions and inversions affecting from a few thousand to a few million base pairs. We employed a clone-based method to interrogate this intermediate structural variation in eight individuals of diverse geographic ancestry. Our analysis provides a comprehensive overview of the normal pattern of structural variation present in these genomes, refining the location of 1,695 structural variants. We find that 50% were seen in more than one individual and that nearly half lay outside regions of the genome previously described as structurally variant. We discover 525 new insertion sequences that are not present in the human reference genome and show that many of these are variable in copy number between individuals. Complete sequencing of 261 structural variants reveals considerable locus complexity and provides insights into the different mutational processes that have shaped the human genome. These data provide the first high-resolution sequence map of human structural variation--a standard for genotyping platforms and a prelude to future individual genome sequencing projects.
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              Gene map of the extended human MHC.

              The major histocompatibility complex (MHC) is the most important region in the vertebrate genome with respect to infection and autoimmunity, and is crucial in adaptive and innate immunity. Decades of biomedical research have revealed many MHC genes that are duplicated, polymorphic and associated with more diseases than any other region of the human genome. The recent completion of several large-scale studies offers the opportunity to assimilate the latest data into an integrated gene map of the extended human MHC. Here, we present this map and review its content in relation to paralogy, polymorphism, immune function and disease.
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                Author and article information

                Contributors
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2012
                15 October 2012
                : 13
                : 553
                Affiliations
                [1 ]Population Biology and Conservation Biology, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18 D, Uppsala, SE-752 36, Sweden
                [2 ]Evolutionary Biology, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18 D, Uppsala, SE-752 36, Sweden
                [3 ]Swedish Institute for Communicable Disease Control, Department of Preparedness, Nobels väg, , 18, Solna, SE-171 82, Sweden
                Article
                1471-2164-13-553
                10.1186/1471-2164-13-553
                3500228
                23066932
                c544f086-970d-4779-81c3-ebcd625e9f42
                Copyright ©2012 Wang et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 10 April 2012
                : 24 September 2012
                Categories
                Research Article

                Genetics
                Genetics

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