Submitted to: Genetics
Publication Type: Peer reviewed journal
Publication Acceptance Date: 3/29/1996
Publication Date: N/A
Citation: Interpretive Summary: ARS scientists have developed the most extensive linkage map produced to date for swine by linking 1040 genetic markers into 19 linkage groups which cover 99% of the porcine genome. This map is in an interactive genomic database that can be viewed by scientists around the world via the World Wide Web at http://sol.marc.usda.gov. We expect this research to lead to the identification of genes which affect meat quality, reproduction, and disease resistance. Once locations of economically important genes have been mapped, scientists can develop marker assisted selection technology. With this, producers can more precisely select breeding animals for desired traits.
Technical Abstract: We report the highest density genetic linkage map for a livestock species produced to date. Three published maps for Sus scrofa were merged by genotyping virtually every publicly available microsatellite across a single reference population to yield 1,040 linked loci , 536 of which are novel assignments, spanning 2,295.1 cM (average interval 2.25 cM) in 19 linkage groups (18 autosomal and X chromosomes, N=19). Linkage groups were constructed de novo and mapped by locus content to avoid propagation of errors in older genotypes. The physical and genetic maps were integrated with 121 informative loci previously assigned by fluorescence in situ hybridization (FISH). Fourteen linkage groups span the entire length of each chromosome. Coverage of chromosomes 11, 12, 15, and 18 will be evaluated as more markers are physically assigned. Marker deficient regions were identified only on 11q1.7-qter and 14 cen-q1.2. Recombination rates (cM/Mbp) varied between and within chromosomes. Short chromosomal arms recombined at higher rates than long arms and recombination was more frequent in telomeric regions than in pericentric regions. The high resolution comprehensive map has the marker density needed to identify quantitative trait loci (QTL), implement marker assisted selection or introgression and YAC contig construction or chromosomal microdissection.