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Context Greater production of oocytes and embryos from Gir donors contributes to greater fertility and genetic progress. Aims This study aimed to obtain genetic parameters for oocyte and embryo production in the Gir breed. Methods Repeatability and random regression models were applied to data consisting of 17 526 Ovum Pick Up observations from 1641 Gir donors from five different herds. Single and multi-trait analyses were carried out with the application of both models for the traits: number of viable oocytes, number of total oocytes and number of embryos, using the BLUPF90 family programs. Legendre polynomials of second order were used in the random regression model. Key results Considering the repeatability model, additive genetic variance ranged from 0.06 to 0.13 and permanent environment variance ranged from 0.05 to 0.08 for all evaluated traits. Residual variance ranged from 0.30 to 0.45. Heritability estimates were 0.10 for number of embryos, 0.24 for total oocytes, and 0.25 for viable oocytes. Repeatability estimates were moderate, ranging from 0.20 to 0.40, and genetic correlation estimates were always above 0.80. Phenotypic correlation was high only between viable and total oocytes (0.95), and moderate in the other cases. Random regression model results were consistent with those from the repeatability model. The heritability values remained similar throughout the donors’ ages, with moderate values for viable and total oocytes, and low values for number of embryos. Genetic correlations among ages for each trait were moderate to high. Also, the genetic correlations between traits within each age were high, with values always above 0.7. Conclusions Selection of Gir donors for total oocyte production at any time, between 1 and 16 years of age, might lead to an increase in the number of viable oocytes and embryos obtained, but it’s preferable at younger ages to hasten genetic progress. Repeatability models could be the best method, as they require less computational effort when compared to the random regression models and the parameter estimates do not vary substantially throughout different ages of the donor. Implications The use of repeatability models to estimate genetic parameters of oocytes and embryos resulted in similar results compared to random regression models.

Runs of homozygosity (ROH) and signatures of selection are results of selection processes in livestock species that has been shown to affect several traits in cattle. The aim of the current work was to verify the profile of ROH and inbreeding depression in the number of total (TO) and viable oocytes (VO), and number of embryos (EMBR) in Gir Indicine cattle. In addition, we aimed to identify signatures of selection, genes and enriched regions between Gir subpopulations sorted by breeding value for these traits. The genotype file contained 2,093 animals and 420,718 SNP markers. Breeding values used to sort Gir animals were previously obtained. ROH and signature of selection analyses were performed using PLINK software, followed by ROH- and pedigree-based inbreeding (FROH) and search for genes and their functions. A total of 105,327 ROHs were found in Gir cattle. ROHs were separated in classes according to the size, ranging from 1 to 2 Mb (ROH1–2 Mb: 58.17%), representing ancient inbreeding, ROH2–4 Mb (22.74%), ROH4 − 8 Mb (11.34%), ROH8 − 16 Mb (5.51%) and ROH> 16 Mb (2.24%). Putting together our results, we conclude that the increase in general ROH-based and pedigree-based inbreeding significantly decreases TO and VO; however, the way ROH affects the traits vary among chromosomes. In the analysis for signatures of selection, we identified 15 genes from 47 significant genomic regions, indicating differences in populations with high and low breeding value for the three traits.

Our objective was to establish a SNPs panel for pedigree reconstruction using chips of different densities and evaluate the genomic relationship coefficient of the inferred pedigree, in addition to analyzing the population structure based on genomic analyses in Gir cattle. For parentage analysis and genomic relationship, 16,205 genotyped Gir animals were used being 14,458 females and 1,747 males, and 1,810 common markers to the four SNP chips. For population structure analyses, which include linkage disequilibrium, effective population size, and runs of homozygosity (ROH), the genotypes of 21,656 animals were imputed. The likelihood ratio (LR) approach was used to reconstruct the pedigree. The LR approach deepened the pedigree and showed that it is well established in terms of recent information for this breed. The coefficients for each 2 relationship category of the inferred pedigree were adequate. Linkage disequilibrium showed rapid decay. We detected a decrease in the effective population size over the last 50 generations, with the average generation interval estimated at 9.08 years. A higher ROH-based inbreeding coefficient in a class of short segments of ROH, with moderate to high values was also detected, suggesting the presence of bottlenecks in the Gir cattle genome. Breeding strategies to minimize inbreeding and avoid massive use of a few proven sires with high genetic value are suggested to maintain genetic variability in future generations. In addition, we recommend reducing the generation interval to maximize genetic progress and increase effective population size.

Genome-Wide Association Studies (GWAS) are used for identification of quantitate trait loci (QTL) and genes associated with several traits. We aimed to identify QTLs, genes, and biological processes associated with number of total and viable oocytes, and number of embryos in Gir dairy cattle. A dataset with 17,526 follicular aspirations, including the following traits: number of viable oocytes (VO), number of total oocytes (TO) and number of embryos (EMBR) from 1,641 Gir donors was provided by five different stock farms. A genotype file with 2,093 animals and 395,524 SNP markers was used to perform a single-step GWAS analysis for each trait. The top 10 windows with the highest percentage of additive genetic variance explained by 100 adjacent SNPs were selected. QTLs were identified on chromosomes 1, 2, 5, 6, 7, 8, 9, 13, 17, 18, 20, 21, 22, 24 and 29. These QTLs were classified as External, Health, Meat and carcass, Production or Reproduction traits, and about 38% were related to Reproduction. In total, 117 genes were identified, of which 111 were protein-coding genes. Exclusively associations were observed for 42 genes with EMBR, and 1 with TO. Also, 42 genes were in common between VO and TO, 28 between VO and EMBR and four genes were in common among all traits. In conclusion, great part of the identified genes plays a functional role in initial embryo development or general cell functions. ARNT, EGR1, HIF1A, AHR and PAX2 are good markers for the production of oocytes and embryos in Gir cattle.

Runs of homozygosity (ROH) and signatures of selection are results of selection processes in livestock species that has been shown to affect several traits in cattle. The aim of the current work was to verify the pro le of ROH and inbreeding depression in the number of total (TO) and viable oocytes (VO), and number of embryos (EMBR) in Gir Indicine cattle. In addition, we aimed to identify signatures of selection, genes and enriched regions between Gir subpopulations sorted by breeding value for these traits. The genotype le contained 2,093 animals and 420,718 SNP markers. Breeding values used to sort Gir animals were previously obtained. ROH and signature of selection analyses were performed using PLINK software, followed by ROH-and pedigree-based inbreeding (F ROH ) and search for genes and their functions. A total of 105,327 ROHs were found in Gir cattle. ROHs were separated in classes according to the size, ranging from 1 to 2 Mb (ROH 1-2 Mb : 58.17%), representing ancient inbreeding, ROH 2-4 Mb (22.74%), ROH 4 − 8 Mb (11.34%), ROH 8 − 16 Mb (5.51%) and ROH > 16 Mb (2.24%). Putting together our results, we conclude that the increase in general ROH-based and pedigree-based inbreeding signi cantly decreases TO and VO; however, the way ROH affects the traits vary among chromosomes. In the analysis for signatures of selection, we identi ed 15 genes from 47 signi cant genomic regions, indicating differences in populations with high and low breeding value for the three traits.