Development and validation of a small SNP panel for feed efficiency in beef cattle.

The objective of this study was to develop and validate a customized cost-effective single nucleotide polymorphism (SNP) panel for genetic improvement of feed efficiency in beef cattle. The SNPs identified in previous association studies and through extensive analysis of candidate genomic regions and genes, were screened for their functional impact and allele frequency in Angus and Hereford breeds used as validation candidates for the panel. Association analyses were performed on genotypes of 159 SNPs from new samples of Angus (n = 160), Hereford (n = 329), and Angus-Hereford crossbred (n = 382) cattle using allele substitution and genotypic models in ASReml. Genomic heritabilities were estimated for feed efficiency traits using the full set of SNPs, SNPs associated with at least one of the traits (at P ≤ 0.05 and P < 0.10), as well as the Illumina bovine 50K representing a widely used commercial genotyping panel. A total of 63 SNPs within 43 genes showed association (P ≤ 0.05) with at least one trait. The minor alleles of SNPs located in the GHR and CAST genes were associated with decreasing effects on residual feed intake (RFI) and/or RFI adjusted for backfat (RFIf), whereas minor alleles of SNPs within MKI67 gene were associated with increasing effects on RFI and RFIf. Additionally, the minor allele of rs137400016 SNP within CNTFR was associated with increasing average daily gain (ADG). The SNPs genotypes within UMPS, SMARCAL, CCSER1, and LMCD1 genes showed significant over-dominance effects whereas other SNPs located in SMARCAL1, ANXA2, CACNA1G, and PHYHIPL genes showed additive effects on RFI and RFIf. Gene enrichment analysis indicated that gland development, as well as ion and cation transport are important physiological mechanisms contributing to variation in feed efficiency traits. The study revealed the effect of the Jak-STAT signaling pathway on feed efficiency through the CNTFR, OSMR, and GHR genes. Genomic heritability using the 63 significant (P ≤ 0.05) SNPs was 0.09, 0.09, 0.13, 0.05, 0.05, and 0.07 for ADG, dry matter intake, midpoint metabolic weight, RFI, RFIf, and backfat, respectively. These SNPs contributed to genetic variation in the studied traits and thus can potentially be used or tested to generate cost-effective molecular breeding values for feed efficiency in beef cattle.

Abo-Ismail MK ，Lansink N ，Akanno E ，Karisa BK ，Crowley JJ ，Moore SS ，Bork E ，Stothard P ，Basarab JA ，Plastow GS ... -  《-》

Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle.

Single nucleotide polymorphism (SNP) arrays for domestic cattle have catalyzed the identification of genetic markers associated with complex traits for inclusion in modern breeding and selection programs. Using actual and imputed Illumina 778K genotypes for 3887 U.S. beef cattle from 3 populations (Angus, Hereford, SimAngus), we performed genome-wide association analyses for feed efficiency and growth traits including average daily gain (ADG), dry matter intake (DMI), mid-test metabolic weight (MMWT), and residual feed intake (RFI), with marker-based heritability estimates produced for all traits and populations. Moderate and/or large-effect QTL were detected for all traits in all populations, as jointly defined by the estimated proportion of variance explained (PVE) by marker effects (PVE ≥ 1.0%) and a nominal P-value threshold (P ≤ 5e-05). Lead SNPs with PVE ≥ 2.0% were considered putative evidence of large-effect QTL (n = 52), whereas those with PVE ≥ 1.0% but < 2.0% were considered putative evidence for moderate-effect QTL (n = 35). Identical or proximal lead SNPs associated with ADG, DMI, MMWT, and RFI collectively supported the potential for either pleiotropic QTL, or independent but proximal causal mutations for multiple traits within and between the analyzed populations. Marker-based heritability estimates for all investigated traits ranged from 0.18 to 0.60 using 778K genotypes, or from 0.17 to 0.57 using 50K genotypes (reduced from Illumina 778K HD to Illumina Bovine SNP50). An investigation to determine if QTL detected by 778K analysis could also be detected using 50K genotypes produced variable results, suggesting that 50K analyses were generally insufficient for QTL detection in these populations, and that relevant breeding or selection programs should be based on higher density analyses (imputed or directly ascertained). Fourteen moderate to large-effect QTL regions which ranged from being physically proximal (lead SNPs ≤ 3Mb) to fully overlapping for RFI, DMI, ADG, and MMWT were detected within and between populations, and included evidence for pleiotropy, proximal but independent causal mutations, and multi-breed QTL. Bovine positional candidate genes for these traits were functionally conserved across vertebrate species.

Seabury CM ，Oldeschulte DL ，Saatchi M ，Beever JE ，Decker JE ，Halley YA ，Bhattarai EK ，Molaei M ，Freetly HC ，Hansen SL ，Yampara-Iquise H ，Johnson KA ，Kerley MS ，Kim J ，Loy DD ，Marques E ，Neibergs HL ，Schnabel RD ，Shike DW ，Spangler ML ，Weaber RL ，Garrick DJ ，Taylor JF ... -  《BMC GENOMICS》

Accuracy of genomic predictions for feed efficiency traits of beef cattle using 50K and imputed HD genotypes.

The accuracy of genomic predictions can be used to assess the utility of dense marker genotypes for genetic improvement of beef efficiency traits. This study was designed to test the impact of genomic distance between training and validation populations, training population size, statistical methods, and density of genetic markers on prediction accuracy for feed efficiency traits in multibreed and crossbred beef cattle. A total of 6,794 beef cattle data collated from various projects and research herds across Canada were used. Illumina BovineSNP50 (50K) and imputed Axiom Genome-Wide BOS 1 Array (HD) genotypes were available for all animals. The traits studied were DMI, ADG, and residual feed intake (RFI). Four validation groups of 150 animals each, including Angus (AN), Charolais (CH), Angus-Hereford crosses (ANHH), and a Charolais-based composite (TX) were created by considering the genomic distance between pairs of individuals in the validation groups. Each validation group had 7 corresponding training groups of increasing sizes ( = 1,000, 1,999, 2,999, 3,999, 4,999, 5,998, and 6,644), which also represent increasing average genomic distance between pairs of individuals in the training and validations groups. Prediction of genomic estimated breeding values (GEBV) was performed using genomic best linear unbiased prediction (GBLUP) and Bayesian method C (BayesC). The accuracy of genomic predictions was defined as the Pearson's correlation between adjusted phenotype and GEBV (), unless otherwise stated. Using 50K genotypes, the highest average achieved in purebreds (AN, CH) was 0.41 for DMI, 0.34 for ADG, and 0.35 for RFI, whereas in crossbreds (ANHH, TX) it was 0.38 for DMI, 0.21 for ADG, and 0.25 for RFI. Similarly, when imputed HD genotypes were applied in purebreds (AN, CH), the highest average was 0.14 for DMI, 0.15 for ADG, and 0.14 for RFI, whereas in crossbreds (ANHH, TX) it was 0.38 for DMI, 0.22 for ADG, and 0.24 for RFI. The of GBLUP predictions were greatly reduced with increasing genomic average distance compared to those from BayesC predictions. The results indicate that 50K genotypes, used with BayesC, are more effective for predicting GEBV in purebred cattle. Imputed HD genotypes found utility when dealing with composites and crossbreds. Formulation of a fairly large training set for genomic predictions in beef cattle should consider the genomic distance between the training and target populations.

Lu D ，Akanno EC ，Crowley JJ ，Schenkel F ，Li H ，De Pauw M ，Moore SS ，Wang Z ，Li C ，Stothard P ，Plastow G ，Miller SP ，Basarab JA ... -  《-》

Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle.

The candidate gene approach was used to identify genes associated with residual feed intake (RFI) in beef steers. The approach uses prior knowledge of gene functions to predict their biological role in the variation observed in a trait. It is suited to identify genes associated with complex traits where each gene has a relatively small effect. First, positional candidate genes were identified within the genomic positions of previously reported QTL associated with component traits related to RFI such as dry matter intake (DMI), growth, feed conversion ratio (FCR), average daily gain (ADG), and energy balance. Secondly, the positional candidate genes were prioritized into functional candidate genes according to their biological functions and their relationship with the biological processes associated with RFI including carbohydrate, fat and protein metabolism, thermoregulation, immunity and muscle activity. Single nucleotide polymorphisms (SNPs) located within the functional candidate genes were identified using mRNA sequences and prioritized into functional classes such as non-synonymous (nsSNP), synonymous (sSNP) or intronic SNP. A total of 117 nsSNP were considered as functional SNP and genotyped in steers at the University of Alberta ranch in Kinsella. Multiple marker association analysis in ASReml was performed using RFI data obtained from 531 beef steers. Twenty-five SNP were significantly associated with RFI (P < 0.05) accounting for 19.7% of the phenotypic variation. Using SIFT program to predict the effect of the SNP on the function of the corresponding protein, 3 of the 25 SNP were predicted to cause a significant effect on protein function (P < 0.05). One of the 3 SNP was located in the GHR gene and was also associated with a significant effect on the tertiary structure of the GHR protein (P < 0.05) as modeled using SWISSModel software. Least square means for each genotype were estimated and an over-dominance effect was observed for the SNP located in the GHR, CAST, ACAD11 and UGT3A1 genes. In addition, 2 other SNP showed a dominance effect and 3 genes had an additive effect. Gene network analysis performed in Ingenuity pathway analysis (IPA) software (Ingenuity Systems, www.ingenuity.com) indicated that the significant genes were involved in biological pathways such as lipid, protein and energy metabolism, electron transport and membrane signaling. The genes in this study, if validated in other beef cattle populations, may be useful for marker assisted selection for feed efficiency.

Karisa BK ，Thomson J ，Wang Z ，Stothard P ，Moore SS ，Plastow GS ... -  《-》

Identification of single nucleotide polymorphisms in genes involved in digestive and metabolic processes associated with feed efficiency and performance traits in beef cattle.

Discovery of genetic mutations that have a significant association with economically important traits would benefit beef cattle breeders. Objectives were to identify with an in silico approach new SNP in 8 genes involved in digestive function and metabolic processes and to examine the associations between the identified SNP and feed efficiency and performance traits. The association between SNP and daily DMI, ADG, midpoint metabolic weight (MMWT), residual feed intake (RFI), and feed conversion ratio (FCR; the ratio of average daily DMI to ADG) was tested in discovery and validation populations using a univariate mixed-inheritance animal model fitted in ASReml. Substitution effect of the T allele of SNP rs41256901 in protease, serine, 2 (trypsin 2; PRSS2) was associated with FCR (-0.293 ± 0.08 kg DMI kg(-1) BW gain; P < 0.001) and RFI (-0.199 ± 0.08 kg; P < 0.01) and although not significant in the validation population, the phase of association remained. In the cholecystokinin B receptor (CCKBR) gene, genotypes in rs42670351 were associated with RFI (P < 0.05) whereas genotypes in rs42670352 were associated with RFI (P = 0.002) and DMI (P < 0.05). Substitution of the G allele in rs42670352 was associated with DMI (-0.236 ± 0.12 kg; P = 0.055) and RFI (-0.175 ± 0.09 kg; P = 0.05). Substitution of the G allele of SNP rs42670353 was associated with ADG (0.043 ± 0.02 kg/d; P < 0.01) and FCR (0.114 ± 0.05 kg BW gain kg(-1) DMI; P < 0.05). In the validation dataset, SNP rs42670352 in gene CCKBR was significant for RFI and DMI and had the same phase of associations; SNP rs42670353 was significantly associated with FCR with same phase of association and the C allele in SNP rs42670351 was validated as decreasing DMI, RFI, and FCR. Substituting the G allele of SNP rs42670352 in CCKBR2 was associated with decreasing DMI and RFI in the validation study. New SNP were reported in genes PRSS2 and CCKBR, being associated with feed efficiency and performance traits in beef cattle. The association between these SNP with fertility, carcass, and meat quality traits must still be tested.

Abo-Ismail MK ，Kelly MJ ，Squires EJ ，Swanson KC ，Bauck S ，Miller SP ... -  《-》