Genome-wide association studies for methane emission and ruminal volatile fatty acids using Holstein cattle sequence data.

BACKGROUND: Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle. RESULTS: Based on the significant-association threshold (p < 5 × 10- 8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10- 2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10- 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs. CONCLUSIONS: Our results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.

Genetic parameter estimates for growth traits and prolificacy in Raeini Cashmere goats.

The main objectives of this study were to estimate genetic and phenotypic parameters for growth traits and prolificacy in the Raeini Cashmere goat. Traits included, birth weight (BWT), weaning weight (WWT), 6-month weight (6WT), 9-month weight (9WT), 12-month weight (12WT), average daily gain from birth to weaning (ADG1), average daily gain from weaning to 6WT (ADG2), average daily gain from 6WT to 12WT (ADG3), survival rate (SR), litter size at birth (LSB) and litter size at weaning (LSW) and total litter weight at birth (LWB). Data were collected over a period of 28 years (1982-2009) at the experimental breeding station of Raeini goat, southeast of Iran. Genetic parameters were estimated with univariate models using restricted maximum likelihood (REML) procedures. In addition to an animal model, sire and threshold models, using a logit link function, were used for analyses of SR. Age of dam, birth of type, sex and of kidding had significant influence (p < 0.05 or 0.01) all the traits. Direct heritability estimates were low for prolificacy traits (0.04 ± 0.01 for LSB, 0.09 ± 0.02 for LSW, 0.16 ± 0.02 for LWB and 0.05 ± 0.02 for SR) and average daily gain (0.12 ± 0.03 for ADG1, 0.08 ± 0.02 for ADG2, and 0.07 ± 0.03 for ADG3) to moderate for production traits (0.22 ± 0.02 for BWT, 0.25 ± 0.02 for WWT, 0.29 ± 0.04 for 6WT, 0.30 ± 0.02 for 9WT, 0.32 ± 0.05 for 12WT). The estimates for the maternal additive genetic variance ratios were lower than direct heritability for BWT (0.17 ± 0.03) and WWT (0.07 ± 0.02).