Genetic evaluation of growth in Barki sheep using random regression models

Genetic evaluation of growth using random regression models

The variability in growth traits provides enormous scope for improvement through selection and breeding. However, growth is a longitudinal trait measured repeatedly on the animal and random regression models (RRM) have been found to be suitable for modeling the trait as a growth curve. RRM accommodate repeated records for traits which change gradually and continually, over time, and do not require stringent assumptions about constancy of variances and correlations. RRM has the advantage that, variance components can be estimated for any point in the trajectory of the growth curve and genetic parameters could be estimated for any age class within the range of ages included in the study. RRM is suitable for group breeding schemes and field performance recording systems where the growth data will be uneven and for varying age points. Worldwide, several studies on use of the tool, RRM in growth of various livestock species are available, but literature on such studies is scanty from India. The methodology used, data requirement, assumptions, validity, software available and application of RRM in the field are discussed based on the earlier reports.

Genetic variations in the Myostatin gene affecting growth traits in sheep

Background and Aim

Sheep productivity in developing countries is crucial, as this animal is an essential source of meat and wool. Myostatin (MSTN) plays an important role in the regulation of muscle mass through the regulation of muscle growth, differentiation, and regeneration. The present study sought to investigate genetic variation in the first intron of the MSTN gene and the association of variants with growth traits in major sheep breeds in Egypt (Barki, Ossimi, and Rahmani) and Saudi Arabia (Najdi) using polymerase chain reaction (PCR) and sequencing.

Materials and Methods

Blood samples were collected, and DNA was extracted from 75 animals. A 386 bp fragment in the first intron of the MSTN gene was amplified using PCR. Polymorphic sites were detected using direct sequencing and then correlated with growth traits using a general linear model.

Results

Sequence analysis of the first intron of MSTN gene identified six single-nucleotide polymorphisms (SNPs) in the studied breeds. Four mutual SNPs were determined: c.18 G>T, c.241 T>C, c.243 G>A, and c.259 G>T. In addition, two SNPs c.159 A>T and c.173 T>G were monomorphic (AA and TT, respectively) in the Ossimi, Rahmani, and Najdi breeds and polymorphic in the Barki breed. The association analysis revealed that the c.18 G>T and c.241 C>T significantly associated (p<0.05) with birth weight and average daily weight gain, respectively.

Conclusion

Our results strongly support MSTN as a candidate gene for marker-assisted selection in sheep breeding programs. Furthermore, the identified variants may be considered as putative markers to improve growth traits in sheep.

A missense mutation in the coding region of the toll-like receptor 4 gene affects milk traits in Barki sheep

OBJECTIVE

Milk production is one of the most desirable traits in livestock. Recently, the toll-like receptor (TLR) has been identified as a candidate gene for milk traits in cows. So far, there is no information concerning the contribution of this gene in milk traits in sheep. This study was designed to investigate the TLR 4 gene polymorphisms in Barki ewes in Egypt and then correlate that with milk traits in order to identify potential single nucleotide polymorphisms (SNPs) for these traits in sheep.

METHODS

A part of the ovine TLR 4 gene was amplified in Barki ewes, to identify the SNPs. Consequently; Barki ewes were genotyped using polymerase chain reaction-single strand conformation polymorphism protocol. These genotypes were correlated with milk traits, which were the daily milk yield (DMY), protein percentage (PP), fat percentage (FP), lactose percentage, and total solid percentage (TSP).

RESULTS

Age and parity of the ewe had a significant effect (p<0.05 or p<0.01) on DMY, FP, and TSP. The direct sequencing identified a missense mutation located in the coding sequence of the gene (rs592076818; c.1710C>A) and was predicted to change the amino acid sequence of the resulted protein (p.Asn570Lys). The association analyses suggested a significant effect (p<0.05) of the TLR genotype on the FP and PP, while the DMY tended to be influenced as well (p = 0.07). Interestingly, the presence of the G allele tended to increase the DMY (+40.5 g/d) and significantly (p<0.05 or p<0.01) decreased the FP (-1.11%), PP (-1.21%), and TSP (-7.98%).

CONCLUSION

The results of this study suggested the toll-like receptor 4 (TLR4) as a candidate gene to improve milk traits in sheep worldwide, which will enhance the ability to understand the genetic architecture of genes underlying SNPs that affect such traits.