QTL mapping in multiple families using logistic regression

This study compares logistic regression (LR) with maximum likelihood (ML) methods for mapping quantitative trait loci (QTL) in multiple half-sib families under selective or full genotyping strategies, with various levels of marker informativeness and marker interval. In ideal conditions involving evenly located polymorphic markers and all individuals genotyped, both LR and ML methods showed a high power of detecting QTL and produced accurate estimates of QTL locations and effects. Under selective genotyping strategy, the power of ML is limited by regions with low information content. The LR method performed better than ML and is a straight-forward and robust method for this case

Direct Molecular Markers for Pig Improvement: APL1756 QTL Analyses on Chromosomes 10, 9 and 4

This report summarizes analyses at AGBU and covers two areas. The first area is the supplementary analyses for APL1756 and US43 animals on chromosome 10, as a result of additional genotyping for two APL1756 sire families and re-scoring of some genotypes. The second area reports the analysis of chromosome 4 for US43 animals and of chromosome 9 for APL1756 animals

Population stratification, not genotype error, causes some SNPs to depart from Hardy-Weinberg Equilibrium

Large scale whole genome scans generate massive amounts of genotype data. It is essential to check genotype integrity and identify genotype errors prior to association analysis. Departure from Hardy-Weinberg Equilibrium has been adopted as one of the main methods to identify genotype errors. However population stratification also causes departure from Hardy-Weinberg Equilibrium, which is a disadvantage of this approach. This study used 2 sets of SNP genotypes to show that after basic editing using Call Rate and minor allele frequency, up to 13% of SNPs departed from Hardy-Weinberg Equilibrium (HWD) and about one third of these HWD SNPs could be falsely identified as genotype errors, were attributable to population subdivision (eg herd of origin, cohort) for one dataset and corresponding numbers for the second dataset are 21% and 16%, respectively. This approach can avoid improper culling of a considerable proportion of SNPs

QTL mapping using logistic regression

This study compares logistic regression (LR) with maximum likelihood (ML) for mapping quantitative trait loci (QTL) in halfsib family with respect to genotyping schemes (full and selective), various levels of marker informativeness and marker interval. Under selective genotyping, the power of ML is limited in regions with low information contents. In this case, LR performed better than ML and provides a straightforward and robust solution to such situation

Genetic parameters of post-partum reproductive status in beef cattle from northern Australia

Lifetime reproductive performance is a major issue for the Northern Australian beef industry. Delayed cycling of lactating cows after parturition is one of major causes of reproductive inefficiency and impacts on the profitability of beef businesses. In the CRC for Beef Genetic Technologies, genetic markers have been used to develop prediction equations for the improvement of post partum anoestrus interval in tropically adapted beef cattle. An independent cattle population was established to validate these prediction equations. Data were collected at weaning on 4286 cows from 27 herds of 4 breeds in Northern Australia. Using ultrasonic ovarian scans and pregnancy tests, cows were scored for the reproductive status (REP3): 1) being pregnant (P), or 2) having a 'corpus luteum' (CL), or 3) having a follicle (F). REP3 was also rescored into two binary traits: PREG2: pregnant (P) or not pregnant (F or CL) and HEAT2: cycling (P or CL) or not cycling (F). A threshold model was fitted to estimate genetic variance for these three traits. Analyses were implemented using both REML (sire model) and Gibbs Sampler (animal model) for the pooled dataset and two large breeds. The heritability estimates for reproductive status, either in REP3 or binary traits (PREG2 and HEAT2) were low to moderate. Results from REML and Gibbs Sampler were similar for REP3 and PREG2. The practical and important trait is PREG2. For this trait, the estimates of heritability in this study ranged from 0.15 to 0.22. These data may provide a useful resource for validating genomic prediction equations

Fine mapping QTL with haplotypes determined from dense single nucleotide polymorphic markers

We use publicly available methods to impute missing genotypes, infer haplotypes and partition haplotypes into blocks for large numbers of single nucleotide polymorphic data on two sections of chromosomes. Haplotype trend regression was used to associate these haplotype blocks with a continuously distributed trait. A number of significant regions of chromosomes, that were not found when tested with single-marker tests, were identified. This study demonstrated a feasible framework to fine-mapping QTL using haplotypes of SNP markers

Pig Genome Web Site: Online Resources For Swine Molecular Genetics and Genome Information

The pig genome Web page provides materials for swine researchers, students, producers, and members of the industry with information covering all aspects of swine genetics, genomics, and animal breeding. This Web site is the home of a great deal of diverse and interesting information, including the pig genome database (PigBase) and the pig expressed sequence tag (EST) database, and it houses an animal gene mapping discussion forum (ANGENMAP mail list). This site also includes a bimonthly swine genome newsletter and information on gene mapping materials and information. This resource plays an important role in swine genetics and swine breeding education by including tutorial materials and lecture notes on genetics, gene mapping, QTL detection, and genetic linkage analysis. Many additional pig genome Web sites worldwide also can be accessed from this site.</p