%A Choi,Igseo %A Steibel,Juan %A Bates,Ronald %A Raney,Nancy %A Rumph,Janice %A Ernst,Catherine %D 2011 %J Frontiers in Genetics %C %F %G English %K Carcass merit,meat quality,pig,QTL %Q %R 10.3389/fgene.2011.00018 %W %L %M %P %7 %8 2011-May-02 %9 Original Research %+ Dr Catherine Ernst,Michigan State University,Department of Animal Science,Anthony Hall,East Lansing,48824,Michigan,United States,ernstc@msu.edu %# %! Carcass and pork quality QTL %* %< %T Identification of Carcass and Meat Quality QTL in an F2 Duroc × Pietrain Pig Resource Population Using Different Least-Squares Analysis Models %U https://www.frontiersin.org/articles/10.3389/fgene.2011.00018 %V 2 %0 JOURNAL ARTICLE %@ 1664-8021 %X A three-generation resource population was constructed by crossing pigs from the Duroc and Pietrain breeds. In this study, 954 F2 animals were used to identify quantitative trait loci (QTL) affecting carcass and meat quality traits. Based on results of the first scan analyzed with a line-cross (LC) model using 124 microsatellite markers and 510 F2 animals, 9 chromosomes were selected for genotyping of additional markers. Twenty additional markers were genotyped for 954 F2 animals and 20 markers used in the first scan were genotyped for 444 additional F2 animals. Three different Mendelian models using least-squares for QTL analysis were applied for the second scan: a LC model, a half-sib (HS) model, and a combined LC and HS model. Significance thresholds were determined by false discovery rate (FDR). In total, 50 QTL using the LC model, 38 QTL using the HS model, and 3 additional QTL using the combined LC and HS model were identified (q < 0.05). The LC and HS models revealed strong evidence for QTL regions on SSC6 for carcass traits (e.g., 10th-rib backfat; q < 0.0001) and on SSC15 for meat quality traits (e.g., tenderness, color, pH; q < 0.01), respectively. QTL for pH (SSC3), dressing percent (SSC7), marbling score and moisture percent (SSC12), CIE a* (SSC16), and carcass length and spareribs weight (SSC18) were also significant (q < 0.01). Additional marker and animal genotypes increased the statistical power for QTL detection, and applying different analysis models allowed confirmation of QTL and detection of new QTL.