By using genome-wide markers to predict an individual’s genetic potential, the introduction of Genomic Selection (GS) has transformed animal breeding. This greatly accelerated selection for complex traits by lowering reliance on drawn-out field trials, allowing for faster genetic gains in livestock. However, there is little research on the effects of genomic selection on Sahiwal cattle in India, and comparing it to the current culling or selection process is even more uncommon, particularly in nations with fewer genotyped animals. This study is an initial effort to address the aforementioned gaps in knowledge. Genomic selection was implemented in Sahiwal cattle for the 305 days milk yield using univariate animal model and the single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) method. The Effective Population size (Ne) of the Sahiwal herd was calculated using genomic data and was reported for the previous generation to be 71.927. The heritability of 305 days milk yield was estimated as 0.177 ± 0.068. Genomic estimated breeding values (GEBVs) were predicted for each individual using ssGBLUP, yielding a mean prediction accuracy of 43.11%, compared with 40.88% obtained using conventional pedigree-based BLUP. Cross-validation further demonstrated superior predictive performance of ssGBLUP, with accuracies of 76.82% and 70.50% for ssGBLUP and PBLUP, respectively. To further check the effectiveness of the genomic selection methodology, we also compared the GEBVs obtained and compared it with the Expected Progeny Difference (EPD) which is being applied in our farm for culling decisions. It was seen that GEBVs obtained from ssGBLUP methodology were also in line with the conventionally used method of EPD. The use of genomic selection enables genetic studies with limited pedigree information. Additionally, the ssGBLUP methodology allows to check for pedigree errors, where family relationships are incorrectly recorded. The EPD and GEBVs were consistent with one another, indicating that genomic selection may also be utilised to support culling and selection decisions in a farm. Thus, in a conventional animal breeding program with constraint resources and an incomplete pedigree, we recommend employing the ssGBLUP model for regular genomic assessment and identification of suitable candidates to effectively carry out a genomic selection program.
Simple Summary Identification of genetic variability and genomic regions under selection pressure has significant potential not only for sustaining animal production but also for comprehensive breeding programs to address future challenges. As one of the native sheep breeds of Iraq, Hamdani (HAM) sheep are also found i...
Ebru Demir, F. Perini, E. Demir et al.· Biology· 0 citations
Genomic selection; A Modern perspective in Animal breeding which has revolutionized the Dairy and Beef industry. It has enabled us to predict the genetic merit of candidate animals early and accurately by means of Genome Wide testing technologies. This review article focuses on the key advancements in genomic selection...
Muhammad Hassan Raza, Muhammad Ali Raza, Abdullah Basra et al.· Discoveries in Agriculture a...· 0 citations
The exponential increase in the number of genotyped animals, combined with the availability of high-density SNP chips has introduced computational challenges for routine genomic evaluations, particularly during the construction of the genomic relationship matrix. Although higher-density SNP panels can facilitate the id...
A. R. Ogunbawo, H. Mulim, J. Hidalgo et al.· bioRxiv· 0 citations
Feed efficiency is a core economic trait in pig breeding, with feed costs accounting for 60%-70% of total production expenses. Deciphering its genetic basis is critical for precise molecular breeding and the development of grain-saving pig breeds. However, most existing studies rely on SNP arrays, which cannot capture...
Lin Chen, Bin Yang, Haoran Shi et al.· Animal Genetics· 0 citations
The results suggest that, in elite wheat germplasm characterized by long-range linkage disequilibrium and strong realized genomic relationships, medium-density targeted genotyping platforms can retain most of the predictability achieved by higher-density systems.
Predictive breeding has been proposed as an effective approach to accelerate genetic gain for complex traits. Genomic prediction (GP) models have been developed in alfalfa (
Medicago sativa
L.) for key traits in the last decade. More recently, phenomic prediction (PP) models have been proposed as a low‐cost, high...
P. Sipowicz, Ayush K. Sharma, M. M. Andrade et al.· The Plant Phenome Journal· 0 citations
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