Genetic variation in bovine LAP3 and SIRT1 genes associated with fertility traits in dairy cattle.

BACKGROUND: The genetic progress of fertility and reproduction traits in dairy cattle has been constrained by the low heritability of these traits. Identifying candidate genes and variants associated with fertility and reproduction could enhance the accuracy of genetic selection and expedite breeding process of dairy cattle with low-heritability traits. While the bovine LAP3 and SIRT1 genes exhibit well-documented associations with milk production traits in dairy cattle, their effect on cow fertility have not yet been explored. Eleven single nucleotide polymorphisms (SNPs), comprising five in the promoter (rs717156555: C > G, rs720373055: T > C, rs516876447: A > G, rs461857269: C > T and rs720349928: G > A), two in 5'UTR (rs722359733: C > T and rs462932574: T > G), two in intron 12 (rs110932626: A > G and rs43702363: C > T), and one in 3'UTR of exon 13 (rs41255599: C > T) in LAP3 and one in SIRT1 (rs718329990:T > C) genes, have previously been reported to be associated with various traits of milk production and clinical mastitis in Sahiwal and Karan Fries dairy cattle. In this study, the analysis primarily aimed to assess the impact of SNPs within LAP3 and SIRT1 genes on fertility traits in Sahiwal and Karan Fries cattle. Association studies were conducted using mixed linear models, involving 125 Sahiwal and 138 Karan Fries animals in each breed. The analysis utilized a designated PCR-RFLP panel. RESULTS: In the promoter region of the LAP3 gene, all variants demonstrated significant (P < 0.05) associations with AFC, except for rs722359733: C > T. However, specific variants with the LAP3 gene's promoter region, namely rs722359733: C > T, rs110932626: A > G, rs43702363: C > T, and rs41255599: C > T, showed significant associations with CI and DO in Sahiwal and Karan Fries cows, respectively. The SNP rs718329990: T > C in the promoter region of SIRT1 gene exhibited a significant association with CI and DO in Sahiwal cattle. Haplotype-based association analysis revealed significant associations between haplotype combinations and AFC, CI and DO in the studied dairy cattle population. Animals with H2H3 and H2H4 haplotype combination exhibited higher AFC, CI and DO than other combinations. CONCLUSIONS: These results affirm the involvement of the LAP3 and SIRT1 genes in female fertility traits, indicating that polymorphisms within these genes are linked to the studied traits. Overall, the significant SNPs and haplotypes identified in this study could have the potential to enhance herd profitability and ensure long-term sustainability on dairy farms by enabling the selection of animals with early age first calving and enhance reproductive performance in the dairy cattle breeding program.

Candidate genes associated with heat stress and breeding strategies to relieve its effects in dairy cattle: a deeper insight into the genetic architecture and immune response to heat stress.

The need for food products of animal origin is increasing worldwide. Satisfying these needs in a way that has minimal impact on the environment requires cutting-edge technologies and techniques to enhance the genetic quality of cattle. Heat stress (HS), in particular, is affecting dairy cattle with increasing frequency and severity. As future climatic challenges become more evident, identifying dairy cows that are more tolerant to HS will be important for breeding dairy herds that are better adapted to future environmental conditions and for supporting the sustainability of dairy farming. While research into the genetics of HS in the context of the effect of global warming on dairy cattle is gaining momentum, the specific genomic regions involved in heat tolerance are still not well documented. Advances in omics information, QTL mapping, transcriptome profiling and genome-wide association studies (GWAS) have identified genomic regions and variants associated with tolerance to HS. Such studies could provide deeper insights into the genetic basis for response to HS and make an important contribution to future breeding for heat tolerance, which will help to offset the adverse effects of HS in dairy cattle. Overall, there is a great interest in identifying candidate genes and the proportion of genetic variation associated with heat tolerance in dairy cattle, and this area of research is currently very active worldwide. This review provides comprehensive information pertaining to some of the notable recent studies on the genetic architecture of HS in dairy cattle, with particular emphasis on the identified candidate genes associated with heat tolerance in dairy cattle. Since effective breeding programs require optimal knowledge of the impaired immunity and associated health complications caused by HS, the underlying mechanisms by which HS modulates the immune response and renders animals susceptible to various health disorders are explained. In addition, future breeding strategies to relieve HS in dairy cattle and improve their welfare while maintaining milk production are discussed.

Genetic variation in promoter region of the bovine LAP3 gene associated with estimated breeding values of milk production traits and clinical mastitis in dairy cattle.

The purpose of this study was to identify genetic variants in the promoter and 5'UTR regions of bovine leucine amino peptidase three (LAP3) gene and analysed their associations with estimated breeding values (EBVs) of milk production traits and clinical mastitis in Sahiwal and Karan Fries cattle. Eleven SNPs were identified within the region under study of the LAP3 gene, including seven promoter variants (rs717156555: C>G, rs720373055: T>C, rs715189731: A>G, rs516876447: A>G, rs461857269: C>T, rs136548163: C>T, and rs720349928: G>A) and four 5'UTR variants (rs717884982: C>T, rs722359733: C>T, rs481631804: C>T and rs462932574: T>G). Out of them, 10 SNPs variants were found in both Sahiwal and Karan Fries cattle, with one SNP variant (rs481631804: C>T) being unique to Karan Fries cattle. Seven of these identified SNPs were chosen for association analyses. Individual SNP based association analysis revealed that two SNPs (rs720373055: T>C and rs720349928: G>A) were significantly associated with EBVs of lactation milk yield (LMY), 305-day milk yield (305dMY), and one significant association of SNP rs722359733: C>T with lactation length (LL) was observed. Haplotype based association analysis indicated that diplotypes are significantly associated with EBVs of LMY, 305dMY, and LL, individuals with H1H3 (CTACGCT/GCGTACG) being linked to higher lactation performance than other diplotypes. Further logistic regression analysis revealed that, animals with diplotype H1H3 was less susceptible to the incidence of clinical mastitis than other cows, as the odds ratio for the non-incidence of clinical mastitis was found to be low. Altogether, variations in the LAP3 gene promoter could be used as a genetic marker, most notably diplotype H1H3, may greatly benefit the simultaneous improvement of mastitis resistance and milk yield traits in dairy cattle. Moreover, bioinformatics analysis predicted that the SNPs rs720373055: T>C, rs715189731:A>G and rs720349928: G>A is located in the core promoter region and in TFBs, play key role in regulation of studied phenotypes.

Estimation of genetic parameters of growth traits for direct and maternal effects in Murrah buffalo.

An understanding of genetic principles and environmental factors affecting the growth traits is essential to implement optimal breeding and selection programs. Early growth is an indicator of future success in production and reproduction status of dairy animals. In this study, a total of 18,989 records of body weight were used to estimate genetic parameters of body weight at birth (BW), 3 months (3BW), 6 months (6BW), 9 months (9BW),12 months (12BW), 18 months (18BW), 24 months (24 BW), 30 months (3BW), and 36 months (36BW) in Murrah buffalo at ICAR-NDRI Karnal, Haryana, for the period 1974-2019. The genetic parameters were estimated using the average information restricted maximum likelihood (AIREML) procedure by excluding or including maternal effects. Six analytical models were fitted in order to optimize the model for each trait. The most appropriate univariate model was selected based on the log likelihood ratio test (LRT). Influencing factors like calf sex, period of birth, season of birth, and dam's parity were investigated. The results showed that the maternal genetic effects, in addition to direct additive effects, were important for unbiased and accurate genetic parameter estimates of growth traits in Murrah buffaloes. Total heritability estimates h2T1 for BW, 3BW, 6BW, 9BW, 12BW, 18BW, 24BW, 30BW, and 36BW were 0.25, 0.04, 0.14, 0.16, 0.10, 0.15, 0.21, 0.24, and 0.23, respectively. Maternal effect was significant for birth weight and accounted for 13% variation through maternal genetic and 5% variability through maternal permanent environmental effect. Maternal genetic effect was also important for other traits. However, it interfered with the estimates of variance ratios in live weight traits owing to large and negative covariance between direct and maternal genetic effects. Direct genetic correlations between body weight traits were positive and high ranging from 0.10 to 0.94. Results revealed that the Murrah herd has a sizable genetic variability for growth traits and hence, there is sufficient scope for selection for achieving better growth rate if selection in this direction is applied. Owing to higher positive genetic correlation of 6BW with later ages, the scope of indirect selection for optimum growth in later ages can be aimed at by selecting animals for their higher 6-month live weight.

Associations between polymorphisms of LAP3 and SIRT1 genes with clinical mastitis and milk production traits in Sahiwal and Karan Fries dairy cattle.

BACKGROUND: Bovine mastitis continues to remain as the most challenging disease in dairy cattle, as a result improvement of selection methods has great economic relevance while a deeper understanding of the genetic mechanisms regulating milk production traits and mastitis is of general scientific interest. OBJECTIVES: This study aimed to evaluate the association of SNPs of the LAP3 and SIRT1 genes with estimated breeding values (EBVs) of milk production traits and clinical mastitis in dairy cattle of Indian origin. METHODS: DNA samples from 263 animals (Sahiwal and Karan Fries cattle) were genotyped by PCR-RFLP to assess their pattern of genetic variation. EBVs of milk production traits and phenotypic records of incidences of clinical mastitis were used for association analysis. RESULTS: A total of 9 SNPs were identified, including three (rs110932626: A>G, rs716493845: C>T and rs43702363: C>T) in intron 12, four (g.24904G>C, rs110839532: G>T, rs43702361: T>C and rs41255599: C>T) in exon 13 and within 3'UTR of LAP3 gene and two (rs110250233: G>A and rs42140046: C>G) in the promoter region of SIRT1 gene. Eight of these identified SNPs were chosen for subsequent genotyping and association analyses. Association analysis revealed that SNP rs41255599: C>T was significantly associated with lactation milk yield, 305-day milk yield, 305-day fat yield, 305-day solid not fat yield, lactation length and incidence of clinical mastitis (p < 0.05) in Sahiwal cattle. For Karan Fries cattle, two SNPs including rs110932626: A>G and rs43702363: C>T showed significant association with 305-day milk yield. CONCLUSION: Overall, these findings provide evidence for association of the LAP3 gene with milk production traits and clinical mastitis in dairy cattle, indicating the potential role of LAP3 variants in these traits.

Inputs for optimizing selection platform for milk production traits of dairy Sahiwal cattle.

The premises for the potential success of molecular breeding is the ability to identify major genes associated with important dairy related traits. The present study was taken up with the objectives to identify single nucleotide polymorphism (SNP) of bovine MASP2 and SIRT1 genes and its effect on estimated breeding values (EBVs) and to estimate genetic parameters for lactation milk yield (LMY), 305-day milk yield (305dMY), 305-day fat yield (305dFY), 305-day solid not fat yield (305dSNFY) and lactation length (LL) in Sahiwal dairy cattle to devise a promising improvement strategy. Genetic parameters and breeding values of milk production traits were estimated from 935 Sahiwal cattle population (1979-2019) reared at National Dairy Research Institute at Karnal, India. A total of 7 SNPs, where one SNP (g.499C>T) in exon 2 and four SNPs (g.576G>A, g.609T>C, g.684G>T and g.845A>G) in exon 3 region of MASP2 gene and 2 SNPs (g.-306T>C and g.-274G>C) in the promoter region of SIRT1 gene were identified in Sahiwal cattle population. Five of these identified SNPs were chosen for further genotyping by PCR-RFLP and association analysis. Association analysis was performed using estimated breeding values (n = 150) to test the effect of SNPs on LMY, 305dMY, 305dFY, 305dSNFY and LL. Association analysis revealed that, three SNP markers (g.499C>T, g.609T>C and g.-306T>C) were significantly associated with all milk yield traits. The estimates for heritability using repeatability model for LMY, 305dMY, 305dFY, 305dSNFY and LL were low, however the corresponding estimates from first parity were 0.20±0.08, 0.17±0.08, 0.13±0.09, 0.13±0.09 and 0.24, respectively. The repeatability estimates were moderate to high indicating consistency of performance over the parities and hence reliability of first lactation traits. Genetic correlations among the traits of first parity were high (0.55 to 0.99). From the results we could conclude that optimum strategy to improve the Sahiwal cattle further would be selecting the animals based on their first lactation 305dMY. Option top include the significant SNP in selection criteria can be explored. Taken together, a 2-stage selection approach, select Sahiwal animals early for the SNP and then on the basis of first lactation 305dMY will help to save resources.

Estimation of genetic parameters for production and reproductive traits in Indian Karan-Fries cattle using multi-trait Bayesian approach.

Estimates of variance components are needed for implementing genetic selection. This study was conducted to genetic parameters for production and reproductive traits on Indian Karan-Fries cattle using multi-trait repeatability animal model. Data collected from ICAR-National Dairy Research Institute, Karnal, India (from 1988 to 2019) were used. Single-trait and multi-trait repeatability animal models were used for parameter estimation. The posterior mean of Heritability estimates for 305-day milk yield (305-DMY), lactation milk yield (LMY), lactation length (LL) were 0.20 ± 0.03, 0.19 ± 0.03 and 0.06 ± 0.02, respectively. For age at first calving (AFC), calving interval (CI), and days open (DO), the posterior mean of heritability estimates were 0.24 ± 0.08, 0.06 ± 0.01, and 0.07 ± 0.02, respectively. The repeatability estimates for 305-DMY, LMY, LL, CI, and DO were 0.37 ± 0.02, 0.34 ± 0.02, 0.15 ± 0.02, 0.09 ± 0.02, and 0.12 ± 0.02, respectively. Genetic correlation between milk production traits (305-DMY, LMY, and LL) was positive and strong (> 0.80). However, the genetic correlation between milk production trait and AFC ranges from - 0.31 to 0.12. Unfavorable strong genetic correlations were observed between production and reproductive traits (CI and DO) with values ranged from 0.5 to 0.7. Phenotypic correlations among 305-DMY, LMY, and LL were generally positive and high. The moderate heritability estimates and potential genetic variation for 305-DMY, TMY, and AFC suggested that genetic gain can be obtained for these traits through genetic selection. Low heritability estimates found for LL, CI and DO, indicating that the possibility of changing these traits through genetic selection is small. High genetic correlation observed between productive and fertility traits were unfavorable. The existed strong genetic and phenotypic correlation estimates between CI and DO indicates that recording only one of them would be sufficient in the herd. As the multi-trait model showed slight improvements in the h2 as well as r estimates for both productive and reproductive traits over univariate analysis, future selection with a multi-trait animal model applying Bayesian approach would be recommended.