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Identification and fine mapping of r...
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Holl, Justin W.
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Identification and fine mapping of reproductive quantitative trait loci in Nebraska selection lines of pigs.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Identification and fine mapping of reproductive quantitative trait loci in Nebraska selection lines of pigs./
作者:
Holl, Justin W.
面頁冊數:
139 p.
附註:
Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1276.
Contained By:
Dissertation Abstracts International66-03B.
標題:
Biology, Genetics. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3167460
ISBN:
9780542031762
Identification and fine mapping of reproductive quantitative trait loci in Nebraska selection lines of pigs.
Holl, Justin W.
Identification and fine mapping of reproductive quantitative trait loci in Nebraska selection lines of pigs.
- 139 p.
Source: Dissertation Abstracts International, Volume: 66-03, Section: B, page: 1276.
Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2005.
The objectives were to identify chromosomal regions containing QTL affecting reproductive traits, develop a simulation program to determine the optimum number of markers for fine mapping QTL, and estimate variation due to QTL in UNL selection lines. Previous analyses identified 16 QTL (P < 0.05) from a three-generation resource population using microsatellites across all 18 autosomes, records on 428 F2 gilts, and single Mendelian QTL line-cross models. In Experiment 1, data were reanalyzed with multiple QTL models including imprinting effects. Twenty Mendelian QTL and 11 imprinted QTL were identified (P < 0.05). In the simulation project, selection procedures replicated observed practices. Litter traits were simulated with an adapted uterine capacity and ovulation rate (OR) model, including a QTL for OR. Forty-one evenly-spaced markers spanning a 40 cM region were simulated. Simulations tended to yield similar results for heritabilities, genetic and phenotypic trends compared to reported literature estimates. Four-marker analyses optimized fine mapping QTL accuracy. In Experiment 2, phenotypic data were collected on pigs from three lines selected for increased litter size, two random control lines, and F2 resource population. Sampled animals were genotyped for 118 densely spaced SNP markers within four chromosomal regions previously associated with QTL. Mixed-model analyses were able to confirm eight previously identified QTL and identify five additional QTL. Estimated QTL variances on SSC6 were 0.02 nipples2, 0.13 pigs2, 0.05 pigs 2, 0.26 pigs2, 0.002 g2, 0.70 pigs 2, 0.68 pigs2, and 0.09 nipples2 for NN (95 cM), SB (95 cM), MUM (123 cM), SB (125 cM), BWT (126 cM), BA (127 cM), FF (127 cM), and NN (144 cM), respectively. Estimated QTL variances on SSC11 were 0.75 pigs2 for BA and 0.52 pigs2 for FF. Estimated QTL variances on SSC12 were 36.45 d2 for AP and 0.95 pigs2 for BA. Estimated QTL variance on SSC13 was 0.26 pigs 2 for SB. Pedigree data and densely spaced markers allowed estimation of QTL variation and identification of sets of markers for marker assisted selection.
ISBN: 9780542031762Subjects--Topical Terms:
1017730
Biology, Genetics.
Identification and fine mapping of reproductive quantitative trait loci in Nebraska selection lines of pigs.
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The objectives were to identify chromosomal regions containing QTL affecting reproductive traits, develop a simulation program to determine the optimum number of markers for fine mapping QTL, and estimate variation due to QTL in UNL selection lines. Previous analyses identified 16 QTL (P < 0.05) from a three-generation resource population using microsatellites across all 18 autosomes, records on 428 F2 gilts, and single Mendelian QTL line-cross models. In Experiment 1, data were reanalyzed with multiple QTL models including imprinting effects. Twenty Mendelian QTL and 11 imprinted QTL were identified (P < 0.05). In the simulation project, selection procedures replicated observed practices. Litter traits were simulated with an adapted uterine capacity and ovulation rate (OR) model, including a QTL for OR. Forty-one evenly-spaced markers spanning a 40 cM region were simulated. Simulations tended to yield similar results for heritabilities, genetic and phenotypic trends compared to reported literature estimates. Four-marker analyses optimized fine mapping QTL accuracy. In Experiment 2, phenotypic data were collected on pigs from three lines selected for increased litter size, two random control lines, and F2 resource population. Sampled animals were genotyped for 118 densely spaced SNP markers within four chromosomal regions previously associated with QTL. Mixed-model analyses were able to confirm eight previously identified QTL and identify five additional QTL. Estimated QTL variances on SSC6 were 0.02 nipples2, 0.13 pigs2, 0.05 pigs 2, 0.26 pigs2, 0.002 g2, 0.70 pigs 2, 0.68 pigs2, and 0.09 nipples2 for NN (95 cM), SB (95 cM), MUM (123 cM), SB (125 cM), BWT (126 cM), BA (127 cM), FF (127 cM), and NN (144 cM), respectively. Estimated QTL variances on SSC11 were 0.75 pigs2 for BA and 0.52 pigs2 for FF. Estimated QTL variances on SSC12 were 36.45 d2 for AP and 0.95 pigs2 for BA. Estimated QTL variance on SSC13 was 0.26 pigs 2 for SB. Pedigree data and densely spaced markers allowed estimation of QTL variation and identification of sets of markers for marker assisted selection.
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