32 research outputs found
Predicting expected progeny difference for marbling score in Angus cattle using artificial neural networks and Bayesian regression models
Application of neural networks with back-propagation to genome-enabled prediction of complex traits in Holstein-Friesian and German Fleckvieh cattle
Comparison of synchronisation and fertility after different modifications of the ovsynch protocol in cyclic dairy cows
Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations
Genotypic Expression at Different Ages: I. Prolificacy Traits of Sheep
Genetic parameters for prolificacy traits for Columbia (COLU), Polypay (POLY), Rambouillet (RAMB), and Targhee (TARG) breeds of sheep were estimated with REML using animal models. Traits were number of live births (LAB), litter size at birth (LSB) and weaning (LSW), and litter weight weaned (LWW). Numbers of observations ranged from 5,140 to 7,095 for prolificacy traits and from 5,101 to 8,973 for litter weight weaned for the four breeds. For single-trait analyses, ewes were classified as young (1 yr old), middle-aged (2 and 3 yr old), or older (\u3e 3 yr old). After single-trait analyses, three-trait analyses were done for each characteristic with traits defined by age class. Generally, heritability estimates from single-trait analyses were low and ranged from .01 to .17 for LAB and LSB and from .00 to .10 for LSW. Heritability estimates obtained for LWW ranged from low to moderate (.00 to .25) and were less for older ewes. Heritability estimates from the three-trait analyses were generally similar to estimates from single-trait analyses. Heritabilities for LAB and LSB were similar, and, for three-trait analyses, they ranged across age groups from .07 to .13 for COLU, .13 to .16 for POLY, .10 to .16 for RAMB, and .01 to .16 for TARG. Estimates for LSW from three-trait analyses ranged from .07 to .12 for COLU, .04 to .09 for POLY, .01 to .11 for RAMB, and .03 to .11 for TARG. For LWW, heritabilities ranged from .00 to .21 for COLU, .05 to .08 for POLY, .12 to .15 for RAMB, and .18 to .29 for TARG. Genetic correlations for LAB, LSB and LSW among age-defined traits ranged from .25 to 1.00. Genetic correlations for LAB and LSB between young and middle and between young and older age classes were less than .80 in COLU, POLY, and RAMB breeds. Only genetic correlations between middle and older age classes for these breeds were greater than .80. For TARG, genetic correlations among all age classes were greater than .80 (.88 to 1.00) for those traits. All genetic correlations among ages for LSW were greater than .80 for POLY and TARG. For RAMB, only the correlation between young and older age classes for LSW was less than .80 (.45). None was greater than .80 for COLU. For LWW, genetic correlations among all age classes in POLY and RAMB were greater than .80 (.82 to 1.00). For COLU, genetic correlation between young and middle was low (.07), between young and older was high (.88), and between middle and older classes was moderately high (.54). For TARG, genetic correlations were .49, .65, and .98 for young-middle, young-older, and middle-older age classes, respectively. Results indicate that more progress could be made in selection programs for prolificacy traits in some sheep breeds by considering age of ewe as a part of the trait rather than by simply adjusting for ages of ewes
Genotypic Expression with Different Ages of Dams: III. Weight Traits of Sheep
Correlations between genetic expression in lambs when dams were young (1 yr), middle-aged (2 and 3 yr), or older (older than 3 yr) were estimated with three-trait analyses for weight traits. Weights at birth ( BWT) and weaning ( WWT) and ADG from birth to weaning were used. Numbers of observations were 7,731, 9,518, 9,512, and 9,201 for Columbia ( COLU) , Polypay ( POLY) , Rambouillet ( RAMB) , and Targhee ( TARG) breeds of sheep, respectively. When averaged, relative estimates for WWT and ADG were similar across breeds. Estimates were variable across breeds. On average, direct heritability was greater when environment was young dams (.44 for BWT and .34 for WWT) than when environment was dams of middle age or older (.24 and .28 for BWT and .20 and .16 for WWT, respectively). Maternal heritability was greater when dams were middle-aged or older (.28 and .22 vs .18) for BWT but was greater when dams were younger (.10 vs .05 and .04) for WWT. The estimates of genetic correlations for direct effects across age of dam environments averaged .32 for birth weight and averaged .70 for weaning weight. Average estimates of maternal genetic correlations across age of dam classes were .36 or less for both BWT and WWT. Average estimates of correlations among maternal permanent environmental effects were .49 or less across age of dam classes. Total maternal effects accounted for .33 to .42 of phenotypic variance for BWT and for .09 to .26 of phenotypic variance for WWT. The average estimates of genetic correlations between expressions of the same genotypes with different ages of dams suggest that measurements of BWT of lambs with dams in young, middle, and older age classes should be considered to be separate traits for genetic evaluation and that for WWT measurements with young age of dam class and combined middle and older age of dam classes should be considered to be separate traits for genetic evaluation
Genotypic Expression at Different Ages: II. Wool Traits of Sheep
Genetic parameters for wool traits for Columbia, Polypay, Rambouillet, and Targhee breeds of sheep were estimated with single- and multiple-trait analyses using REML with animal models. Traits considered were fleece grade, fleece weight, and staple length. Total number of observations ranged from 11,673 to 34,746 for fleece grade and fleece weight and from 3,500 to 11,641 for staple length for the four breeds. For single-trait analyses, data were divided by age of ewe: young ages (age of 1 yr), middle ages (ages of 2 and 3 yr), and older ages (age greater than 3 yr). Heritability estimates averaged over breeds for fleece grade decreased from .42 at a young age to .37 for older ages. For fleece weight, heritability estimates averaged .52, .57, and .55 within the successively older groups. Heritability estimates for staple length averaged .54 for young and middle age classes. Few older ewes had staple length measurements. After single-trait analyses, new data sets were created for three-trait analyses with traits defined by three age classes when animals were measured. Heritability estimates with three-trait analyses, except for a few cases, were somewhat greater than those from single-trait analyses. For fleece grade, the genetic correlations averaged over breeds were .72 for young with middle, .42 for young with older, and .86 for middle with older age classes. For fleece weight, the average genetic correlations were .81, .83, and .98. For staple length, the average genetic correlation for young with middle age classes was .82. Estimates of genetic correlations across ages varied considerably among breeds. The average estimates of correlations suggest that fleece grade may need to be defined by age, especially for the Columbia and Rambouillet breeds. For fleece weight and staple length, however, the average correlations suggest no need to define those traits by age