Studies on the Value of Incorporating Effect of Dominance in Genetic Evaluations of Dairy Cattle, Beef Cattle, and Swine

Potential gains from including the dominance effect in genetic evaluations include “purification” of additive values and availability of specific combining abilities for each pair of prospective parents. The magnitude of such gains was tested for dairy and beef cattle and for swine by estimating variance components for several traits and by analyzing changes in additive evaluations when the parental dominance effect was added to the model. Estimates of dominance variance for dairy and beef cattle and for swine were up to 10% of phenotypic variance; estimates were larger for growth traits. As a percentage of additive variance, the estimate of dominance variance reached 78% for 21-day litter weight of swine and 47% for postweaning weight of beef cattle. Changes in additive evaluations after considering dominance are largest for dams of a single large family. These changes were found to be important for dairy cattle especially for dams of full-sibs, but less important for swin

Genetic and phenotypic characterization of African goat populations to prioritize conservation and production efforts for small-holder farmers in sub-Saharan Africa

Food production systems in Africa depend heavily on the use of locally adapted animals. Goats are critical to small-holder farmers being easier to acquire, maintain, and act as scavengers in sparse pasture. Indigenous goats have undergone generations of adaptation and genetic isolation that have led to great phenotypic variation. These indigenous goats serve as a genetic reservoir for the identification of genes important to environmental adaptation, disease resistance, and improved productivity under local conditions. The immediate goal is to characterize African goat populations to prioritize conservation and production efforts and to develop genomic tools for use in selective breeding programs. We have established a standardized phenotypic scoring system to characterize goats including geographical information data, body measurements, photo characterization, and DNA. To date, 2,443 goats from 12 countries, representing 46 breeds have been sampled. Using the 50K goat beadchip, we report parameters of population structure of 620 African goats

Copy number variation of individual cattle genomes using next-generation sequencing

Copy number variations (CNVs) affect a wide range of phenotypic traits; however, CNVs in or near segmental duplication regions are often intractable. Using a read depth approach based on next-generation sequencing, we examined genome - wide copy number differences among five taurine (three Angus, one Holstein, and one Hereford) and one indicine (Nelore) cattle. Within mapped chromosomal sequence, we identified 1265 CNV regions comprising ∼55.6-Mbp sequence-476 of which (~38%) have not previously been reported. We validated this sequence-based CNV call set with array comparative genomic hybridization (aCGH), quantitative PCR (qPCR), and fluorescent in situ hybridization (FISH), achieving a validation rate of 82% and a false positive rate of 8%. We further estimated absolute copy numbers for genomic segments and annotated genes in each individual. Surveys of the top 25 most variable genes revealed that the Nelore individual had the lowest copy numbers in 13 cases (∼52%, χ 2 test; P-value <0.05). In contrast, genes related to pathogen- and parasite-resistance, such as CATHL4 and ULBP17, were highly duplicated in the Nelore individual relative to the taurine cattle, while genes involved in lipid transport and metabolism, including APOL3 and FABP2, were highly duplicated in the beef breeds. These CNV regions also harbor genes like BPIFA2A (BSP30A) and WC1, suggesting that some CNVs may be associated with breed-specific differences in adaptation, health, and production traits. By providing the first individualized cattle CNV and segmental duplication maps and genome-wide gene copy number estimates, we enable future CNV studies into highly duplicated regions in the cattle genome. © 2012 by Cold Spring Harbor Laboratory Press