Signals of Historical Interlocus Gene Conversion in Human Segmental

Standard methods of DNA sequence analysis assume that sequences evolve independently, yet this assumption may not be appropriate for segmental duplications that exchange variants via interlocus gene conversion (IGC). Here, we use high quality multiple sequence alignments from well-annotated segmental duplications to systematically identify IGC signals in the human reference genome. Our analysis combines two complementary methods: (i) a paralog quartet method that uses DNA sequence simulations to identify a statistical excess of sites consistent with inter-paralog exchange, and (ii) the alignment-based method implemented in the GENECONV program. One-quarter (25.4%) of the paralog families in our analysis harbor clear IGC signals by the quartet approach. Using GENECONV, we identify 1477 gene conversion tracks that cumulatively span 1.54 Mb of the genome. Our analyses confirm the previously reported high rates of IGC in subtelomeric regions and Y-chromosome palindromes, and identify multiple novel IGC hotspots, including the pregnancy specific glycoproteins and the neuroblastoma breakpoint gene families. Although the duplication history of a paralog family is described by a single tree, we show that IGC has introduced incredible site-to-site variation in the evolutionary relationships among paralogs in the human genome. Our findings indicate that IGC has left significant footprints in patterns of sequence diversity across segmental duplications in the human genome, out-pacing the contributions of single base mutation by orders of magnitude. Collectively, the IGC signals we report comprise a catalog that will provide a critical reference fo