SyntenyTracker: a tool for defining homologous synteny blocks using radiation hybrid maps and whole-genome sequence

<p>Abstract</p> <p>Background</p> <p>The recent availability of genomic sequences and BAC libraries for a large number of mammals provides an excellent opportunity for identifying comparatively-anchored markers that are useful for creating high-resolution radiation-hybrid (RH) and BAC-based comparative maps. To use these maps for multispecies genome comparison and evolutionary inference, robust bioinformatic tools are required for the identification of chromosomal regions shared between genomes and to localize the positions of evolutionary breakpoints that are the signatures of chromosomal rearrangements. Here we report an automated tool for the identification of homologous synteny blocks (HSBs) between genomes that tolerates errors common in RH comparative maps and can be used for automated whole-genome analysis of chromosome rearrangements that occur during evolution.</p> <p>Findings</p> <p>We developed an algorithm and software tool (SyntenyTracker) that can be used for automated definition of HSBs using pair-wise RH or gene-based comparative maps as input. To verify correct implementation of the underlying algorithm, SyntenyTracker was used to identify HSBs in the cattle and human genomes. Results demonstrated 96% agreement with HSBs defined manually using the same set of rules. A comparison of SyntenyTracker with the AutoGRAPH synteny tool was performed using identical datasets containing 14,380 genes with 1:1 orthology in human and mouse. Discrepancies between the results using the two tools and advantages of SyntenyTracker are reported.</p> <p>Conclusion</p> <p>SyntenyTracker was shown to be an efficient and accurate automated tool for defining HSBs using datasets that may contain minor errors resulting from limitations in map construction methodologies. The utility of SyntenyTracker will become more important for comparative genomics as the number of mapped and sequenced genomes increases.</p

Breakpoint regions and homologous synteny blocks in chromosomes have different evolutionary histories

The persistence of large blocks of homologous synteny and a high frequency of breakpoint reuse are distinctive features of mammalian chromosomes that are not well understood in evolutionary terms. To gain a better understanding of the evolutionary forces that affect genome architecture, synteny relationships among 10 amniotes (human, chimp, macaque, rat, mouse, pig, cattle, dog, opossum, and chicken) were compared at <1 human-Mbp resolution. Homologous synteny blocks (HSBs; N = 2233) and chromosome evolutionary breakpoint regions (EBRs; N = 1064) were identified from pairwise comparisons of all genomes. Analysis of the size distribution of HSBs shared in all 10 species' chromosomes (msHSBs) identified three (>20 Mbp) that are larger than expected by chance. Gene network analysis of msHSBs >3 human-Mbp and EBRs <1 Mbp demonstrated that msHSBs are significantly enriched for genes involved in development of the central nervous and other organ systems, whereas EBRs are enriched for genes associated with adaptive functions. In addition, we found EBRs are significantly enriched for structural variations (segmental duplications, copy number variants, and indels), retrotransposed and zinc finger genes, and single nucleotide polymorphisms. These results demonstrate that chromosome breakage in evolution is nonrandom and that HSBs and EBRs are evolving in distinctly different ways. We suggest that natural selection acts on the genome to maintain combinations of genes and their regulatory elements that are essential to fundamental processes of amniote development and biological organization. Furthermore, EBRs may be used extensively to generate new genetic variation and novel combinations of genes and regulatory elements that contribute to adaptive phenotypes

Fine Mapping and Evolution of a QTL Region on Cattle Chromosome 3

113 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.Using genotypes obtained from the offspring of three half sib families, paternal and maternal haplotypes of the offspring were reconstructed in addition to the six sire haplotypes. A 9.7 Mbp haplotype block likely to be identical by descent was identified in sires, S1 and S2. This shared haplotype block was found to be associated with high milk yield in families, F1 and F2, confirming previous studies. Maternal haplotypes of offspring were then used to define linkage disequilibrium (LD) within the QTL critical region. There were 15 LD blocks found to be shared among all three sires, covering 0.5 Mbp within the 9.7 Mbp region. These regions may contain QTL alleles carried by all three sires. Fst analysis and integrated haplotype scores (iHS) identified signatures of selection in a 3 Mbp subregion of the QTL critical region. For genes located in the QTL critical region, functions were predicted on the basis of human gene annotation. To identify orthologous genomic regions containing candidate genes, a bioinformatics tool, SyntenyTracker was developed. Within the QTL critical region, eight genes with well established functions related to metabolism, membrane transport or mammary gland function were identified. These results show that the combination of a high density marker map, haplotype analysis, characterization of LD, and identification of genomic regions and nucleotides under selection is a powerful approach for QTL fine mapping.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exer�cises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a frame�work for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exer�cise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so