scholarly journals Quantitative Trait Loci Variation for Growth and Obesity Between and Within Lines of Pigs (Sus scrofa)

Genetics ◽  
2003 ◽  
Vol 164 (2) ◽  
pp. 629-635 ◽  
Author(s):  
Yoshitaka Nagamine ◽  
Chris S Haley ◽  
Asheber Sewalem ◽  
Peter M Visscher
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Sus Scrofa ◽  
Strong Support ◽  
Wild Type ◽  
Porcine Genome ◽  
Trait Loci ◽  
Sib Families ◽  
Related Population

Abstract The hypothesis that quantitative trait loci (QTL) that explain variation between divergent populations also account for genetic variation within populations was tested using pig populations. Two regions of the porcine genome that had previously been reported to harbor QTL with allelic effects that differed between the modern pig and its wild-type ancestor and between the modern pig and a more distantly related population of Asian pigs were studied. QTL for growth and obesity traits were mapped using selectively genotyped half-sib families from five domesticated modern populations. Strong support was found for at least one QTL segregating in each population. For all five populations there was evidence of a segregating QTL affecting fatness in a region on chromosome 7. These findings confirm that QTL can be detected in highly selected commercial populations and are consistent with the hypothesis that the same chromosome locations that account for variation between populations also explain genetic variation within populations.

Quantitative trait loci define genes and pathways underlying genetic variation in longevity

2006 ◽  
Vol 41 (10) ◽  
pp. 1046-1054 ◽  
Author(s):  
Robert J. Shmookler Reis ◽  
Ping Kang ◽  
Srinivas Ayyadevara
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Trait Loci

Markers, maps and the detection of trait loci

1996 ◽  
Vol 1996 ◽  
pp. 50-50
Author(s):  
C.S. Haley
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Genetic Markers ◽  
Quantitative Trait ◽  
Coat Colour ◽  
Combined Effects ◽  
Potential Interest ◽  
Naturally Occurring ◽  
Trait Loci ◽  
Modern Breeding

Naturally occurring genetic variation is the basis for differences in performance and appearance between and within different breeds and lines of livestock. In a few instances (e.g. coat colour, polling) the genes (or loci) which control the variation between animals and breeds have a large enough effect to be individually recognisable. For many traits, however, the combined effects of many different genes act together to control quantitative differences between breeds and individuals within breeds (hence such genes are often referred to as quantitative trait loci or QTLs). Thus the dramatic successes of modern breeding result from generations of selection which has produced accumulated changes at a number of different loci. The genome contains up to 100,000 different genes and identifying those which contribute to variation in traits of interest is a difficult task. One first step is to identify regions of the genome containing loci of potential interest through their linkage to genetic markers.

scholarly journals How to deal with genotype uncertainty in variance component quantitative trait loci analyses

2011 ◽  
Vol 93 (5) ◽  
pp. 333-342 ◽  
Author(s):  
XIA SHEN ◽  
LARS RÖNNEGÅRD ◽  
ÖRJAN CARLBORG
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Variance Component ◽  
Large Animal ◽  
Trait Loci ◽  
Sib Families ◽  
Variance Component Estimates ◽  
Variance Component Models ◽  
Component Models

SummaryDealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

Genetic variation underlying pod size and color traits of common bean depends on quantitative trait loci with epistatic effects

2014 ◽  
Vol 33 (4) ◽  
pp. 939-952 ◽  
Author(s):  
Fernando J. Yuste-Lisbona ◽  
Ana M. González ◽  
Carmen Capel ◽  
Manuel García-Alcázar ◽  
Juan Capel ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Common Bean ◽  
Quantitative Trait ◽  
Epistatic Effects ◽  
Color Traits ◽  
Trait Loci

scholarly journals Linkage Analysis of Molecular Markers and Quantitative Trait Loci in Populations of Inbred Backcross Lines of Brassica napus L.

Genetics ◽  
1999 ◽  
Vol 153 (2) ◽  
pp. 949-964 ◽  
Author(s):  
David V Butruille ◽  
Raymond P Guries ◽  
Thomas C Osborn
Keyword(s):  
Genetic Variation ◽  
Brassica Napus ◽  
Quantitative Trait Loci ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Agronomic Traits ◽  
Pedigree Structure ◽  
Inbred Backcross Lines ◽  
Trait Loci ◽  
Inbred Backcross

Abstract Backcross populations are often used to study quantitative trait loci (QTL) after they are initially discovered in balanced populations, such as F2, BC1, or recombinant inbreds. While the latter are more powerful for mapping marker loci, the former have the reduced background genetic variation necessary for more precise estimation of QTL effects. Many populations of inbred backcross lines (IBLs) have been developed in plant and animal systems to permit simultaneous study and dissection of quantitative genetic variation introgressed from one source to another. Such populations have a genetic structure that can be used for linkage estimation and discovery of QTL. In this study, four populations of IBLs of oilseed Brassica napus were developed and analyzed to map genomic regions from the donor parent (a winter-type cultivar) that affect agronomic traits in spring-type inbreds and hybrids. Restriction fragment length polymorphisms (RFLPs) identified among the IBLs were used to calculate two-point recombination fractions and LOD scores through grid searches. This information allowed the enrichment of a composite genetic map of B. napus with 72 new RFLP loci. The selfed and hybrid progenies of the IBLs were evaluated during two growing seasons for several agronomic traits. Both pedigree structure and map information were incorporated into the QTL analysis by using a regression approach. The number of QTL detected for each trait and the number of effective factors calculated by using biometrical methods were of similar magnitude. Populations of IBLs were shown to be valuable for both marker mapping and QTL analysis.

Fine mapping of quantitative trait loci for meat color on Sus scrofa chromosome 6: Analysis of the swine NUDT7 gene1

2010 ◽  
Vol 88 (1) ◽  
pp. 23-31 ◽  
Author(s):  
M. Taniguchi ◽  
T. Hayashi ◽  
M. Nii ◽  
T. Yamaguchi ◽  
N. Fujishima-Kanaya ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Fine Mapping ◽  
Quantitative Trait ◽  
Sus Scrofa ◽  
Chromosome 6 ◽  
Meat Color ◽  
Trait Loci

Genetic mapping of quantitative trait loci affecting bodyweight on chromosome 1 in a commercial strain of Japanese quail

2012 ◽  
Vol 52 (1) ◽  
pp. 64 ◽  
Author(s):  
A. K. Esmailizadeh ◽  
A. Baghizadeh ◽  
M. Ahmadizadeh
Keyword(s):  
Quantitative Trait Loci ◽  
Japanese Quail ◽  
Quantitative Trait ◽  
Average Daily Gain ◽  
Interval Mapping ◽  
Chromosome 1 ◽  
Commercial Strain ◽  
Kleiber Ratio ◽  
Trait Loci ◽  
Sib Families

This study was conducted to identify quantitative trait loci (QTL) affecting growth on chromosome 1 in quail. Liveweight data were recorded on 300 progeny from three half-sib families created from a commercial strain of Japanese quail. Three half-sib families were genotyped for nine microsatellite loci on chromosome 1 and QTL analysis was conducted applying the least-squares interval mapping approach. Significant QTL affecting bodyweight at 3, 4, 5 and 6 weeks of age, average daily gain, and Kleiber ratio, an indirect criterion for feed efficiency, were mapped at 0–23 cM on chromosome 1. The detected QTL segregated in two of the three half-sib families and the size of the QTL effect ranged from 0.6 to 1.1 in unit of the trait standard deviation. This is the first report of liveweight QTL segregating in a commercial strain of Japanese quail.

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