The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here.
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http://dx.doi.org/10.3168/jds.2021-21601 | DOI Listing |
Mamm Genome
January 2025
Universidade Professor Edson Antônio Velano (UNIFENAS), Rodovia 179, Km 0, Alfenas, MG, 37132440, Brasil.
This study aimed to identify splicing quantitative trait loci (cis-sQTL) in Nelore cattle muscle tissue and explore the involvement of spliced genes (sGenes) in immune system-related biological processes. Genotypic data from 80 intact male Nelore cattle were obtained using SNP-Chip technology, while RNA-Seq analysis was performed to measure gene expression levels, enabling the integration of genomic and transcriptomic datasets. The normalized expression levels of spliced transcripts were associated with single nucleotide polymorphisms (SNPs) through an analysis of variance using an additive linear model with the MatrixEQTL package.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy.
The 3p21.31 locus is the most robust genomic region associated with COVID-19 severity. This locus contains a main chemokine receptor (CKR) cluster.
View Article and Find Full Text PDFCell Mol Biol (Noisy-le-grand)
January 2025
Dept. of Genetics and Plant Breeding, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur 1706, Bangladesh.
Rice salt tolerance is highly anticipated to meet global demand in response to decreasing farmland and soil salinization. Therefore, dissecting the genetic loci controlling salt tolerance in rice for improving productivity is of utmost importance. Here, we evaluated six salt-tolerance-related traits of a biparental mapping population comprising 280 F2 rice individuals (Oryza sativa L.
View Article and Find Full Text PDFCancer Innov
February 2025
Department of Breast Medical Oncology Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences Jinan Shandong China.
Background: Identification of risk genes and loci associated with the recurrence and metastasis of breast cancer (BC) is of utmost importance. Genome-wide association studies (GWASs) represent valuable tools for identifying the disease risk associated with a given single-nucleotide polymorphism (SNP); they offer significant insights into the disease progression mechanism by analyzing SNP information of the entire genome. Though GWAS has already identified several genetic susceptibility SNPs for BC, their significance in the recurrence and metastasis of this cancer remains unclear.
View Article and Find Full Text PDFTheor Appl Genet
January 2025
State Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.
112 candidate quantitative trait loci (QTLs) and 53 key candidate genes have been identified as associated with stomatal traits in wheat. These include bHLH, MADS-box transcription factors, and mitogen-activated protein kinases (MAPKs). Stomata is a common feature of the leaf surface of plants and serve as vital conduits for the exchange of gases (primarily CO₂ and water vapor) between plants and the external environment.
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