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Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis
Published on: August 12, 2019
Sex-linked recombination variation and distribution of disease-related genes
Claude Chelala1, Charles Auffray
1Genexpress, Functional Genomics and Systems Biology for Health, CNRS UMR 7091-7, rue Guy Moquet, BP8, 94801 Villejuif Cedex, France.
Abstract:
Analysis of the distribution of recombination along human chromosomes and correlation with sequence features and genes have been previously performed on one genetic map for a given chromosome, limiting therefore their validity and precision. In this paper, we circumvent these issues: (1) by testing the correlation between recombination frequency in sex-specific versions of three genetic maps of chromosome 21 and their content in disease-related loci compared to the distribution of genes along the chromosome, and (2) by reanalysing the previously reported chromosome 22 results (Chelala et al., J. Biol. Syst. 10 (2002) 303-317) with updated version of the sequence and mapping tools. Recombination hot zones were detected and analysed on each genetic map. Despite local differences, for chromosome 21, recombination hot zones were found relatively enriched in disease-related genes on the male genetic maps. This contrasts with the previously described enrichment of the chromosome 22 female genetic map hot zones in disease-related loci (Chelala et al., J. Biol. Syst. 10 (2002) 303-317), which was confirmed with the updated data and tools. Our study demonstrates that the use of different data sets and tools have only a local impact on the distribution of genetic recombination hot zones and provides evidence for gender-specific differences in enrichment in disease-related loci in relation with recombination frequency. Automation of such analyses and extension to the entire human genome will be required in order assess the general character of these observations and to advance in the understanding of genome-wide recombination patterns to help the process of identifying disease-causing genes.
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