The aim of this research was to investigate the polymorphism of prolificacy gene, GDF9 in Zel sheep breed using RFLP-PCR method and to study the association of genotypes with multiple birth records. Genomic DNA of 200 sheep was extracted using modified salting out extraction protocol to evaluate the mutations in G1 and G8 variants of GDF9 gene. Polymerase chain reaction was carried out to amplify a 462 and 139 bp fragments of GDF9 gene. The amplified fragments of G1 and G8 variants of GDF9 genes were digested with restriction enzymes Hin6I and DdeI, respectively. The G1 variant of GDF9 gene was polymorphic. Two mutant (B) and wild (A) type alleles with frequencies of 0.05 and 0.95 were detected in tested animals. Known's point mutation FecGT was monomorphic in tested animals. For G1 variant of GDF9 gene, a Chi-square test indicated that the population was in equilibrium. GLM procedure of SAS software was used to investigate the association of G1 variant of GDF9 gene with twining. Results indicated that there was no significant association (P>0.05) between polymorphism at this locus and twining.

Adding genotypic and phenotypic information from cows to the reference population has the potential to increase the accuracy and decrease selection bias of genomic estimated breeding values (GEBV) in dairy cattle populations (Mc-Hugh et al. 2011; Thomasen et al. 2014; Wiggans et al. 2010). However, the cost of genotyping limits its use to an informative subset of animals (Boligon et al. 2012) and hence looking for an optimal strategy is crucial herein. Now a day, selective genotyping strategies (Boligon et al. 2012; Jiménez-Montero et al. 2012) and imputation methods (Calus et al. 2014) are some suggestive tools to reduce genotyping costs. Therefore, the aim of this study was to assess the effect of inclusion of cow genomic data in the reference population for genomic prediction under scenarios encompassing different selection strategies, number of genotyped cows and heritability on accuracy and bias of genomic breeding values when compared to the use of only bulls in the reference population.

Context. Developing effective selection strategies to enhance efficiency and productivity remains a priority for Merino sheep producers in Australia. Aims. Beyond traditional approaches that rely on liveweight and energy-based assumptions, this study aimed to provide more precise insights into sheep efficiency and profitability by examining genetic parameters for 15 body composition traits. The study estimated the heritability of traits, including liveweight and body condition score, wool growth and leptin concentration, ultrasound measurements of fat and muscle depth, direct whole-body composition measured using dual-energy X-ray absorptiometry (DEXA) and predicted DEXA from ultrasound and liveweight. Methods. Multiple records were collected on 640 wethers aged almost 30 months and 1023 ewes aged 5.5 years, born in 2016 and 2017 and bred from 29 different sires in the Merino Lifetime Productivity (MLP) project. Key results. Direct heritability estimates from a univariate repeated animal measurement model, ranged from low for wool growth and leptin concentration (0.14 ± 0.06 to 0.22 ± 0.06), moderate for liveweight, body condition score and ultrasound fat and muscle depth (0.37 ± 0.08 to 0.48 ± 0.04), moderate to high for DEXA whole-body composition (0.42 ± 0.11 to 0.66 ± 0.14), moderate for predicted whole-body composition (0.17 ± 0.05 to 0.21 ± 0.06). Repeatability estimates were low for wool growth and leptin concentration (0.22 ± 0.06 and 0.23 ± 0.06), moderate for condition score (0.48 ± 0.04) and predicted DEXA measurements (0.58 ± 0.02 to 0.64 ± 0.02), and moderate to high for liveweight (0.71 ± 0.01), ultrasound measurements (0.49 ± 0.02 to 0.61 ± 0.01), and DEXA measurements (0.52 ± 0.03 to 0.95 ± 0.01). Maternal permanent environmental effects were insignificant for most measurements. Conclusion. The heritability and repeatability of DEXA whole-body composition traits were higher than those of body condition score and ultrasound-measured fat and eye muscle depth. Implications. These findings provide information on the genetic variation and repeatability of wool growth and body composition traits that can inform future selection strategies in Merino sheep. The relatively high heritability and repeatability of DEXA-derived traits indicate their potential as a reference technology for body composition assessment in Merino sheep. Further evaluation of genetic relationships with production, reproduction, health traits, simpler indicator traits and their economic value is required to determine their suitability for Merino breeding programs.

Accurate genetic evaluation of flystrike resistance in Merino sheep is limited by low heritability and recording challenges. Combining information across related traits and time points, such as breech and body strike at early (EBRS and EBDS) and late (LBRS and LBDS) age stages, can improve prediction accuracy by exploiting genetic correlations and increasing the amount of information available for each trait. Therefore, a multi-trait approach is expected to enhance precision in genetic evaluation and support sustainable improvement in strike resistance. This study compares single-trait and multi-trait analyses (EBRS, LBRS, EBDS and LBDS) using flystrike records to assess their impact on prediction accuracy and bias.