Background: Genotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions. Imputation methods rely partially on linkage disequilibrium between markers to infer unobserved genotypes. Bos indicus cattle (e.g. Nelore breed) are characterized, in general, by lower levels of linkage disequilibrium between genetic markers at short distances, compared to taurine breeds. Thus, it is important to evaluate the accuracy of imputation to better define which imputation method and chip are most appropriate for genomic applications in indicine breeds.
Methods: Accuracy of genotype imputation in Nelore cattle was evaluated using different LD chips, imputation software and sets of animals. Twelve commercial and customized LD chips with densities ranging from 7 K to 75 K were tested. Customized LD chips were virtually designed taking into account minor allele frequency, linkage disequilibrium and distance between markers. Software programs FImpute and BEAGLE were applied to impute genotypes. From 995 bulls and 1247 cows that were genotyped with the Illumina® BovineHD chip (HD), 793 sires composed the reference set, and the remaining 202 younger sires and all the cows composed two separate validation sets for which genotypes were masked except for the SNPs of the LD chip that were to be tested.
Results: Imputation accuracy increased with the SNP density of the LD chip. However, the gain in accuracy with LD chips with more than 15 K SNPs was relatively small because accuracy was already high at this density. Commercial and customized LD chips with equivalent densities presented similar results. FImpute outperformed BEAGLE for all LD chips and validation sets. Regardless of the imputation software used, accuracy tended to increase as the relatedness between imputed and reference animals increased, especially for the 7 K chip.
Conclusions: If the Illumina® BovineHD is considered as the target chip for genomic applications in the Nelore breed, cost-effectiveness can be improved by genotyping part of the animals with a chip containing around 15 K useful SNPs and imputing their high-density missing genotypes with FImpute.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4192291 | PMC |
http://dx.doi.org/10.1186/s12711-014-0069-1 | DOI Listing |
One of the major challenges in genomic data sharing is protecting participants' privacy in collaborative studies and when genomic data is outsourced to perform analysis tasks, e.g., genotype imputation services and federated collaborations genomic analysis.
View Article and Find Full Text PDFPlant Genome
March 2025
Plant Breeding Graduate Program, Horticultural Sciences Department, University of Florida, IFAS Gulf Coast Research and Education Center, Wimauma, Florida, USA.
Genomic selection is a widely used quantitative method of determining the genetic value of an individual from genomic information and phenotypic data. In this study, we used a large, multi-year training population of 3248 individuals from the University of Florida strawberry (Fragaria × ananassa Duchesne) breeding program. We coupled this training population with a test population of 1460 individuals derived from 20 biparental families.
View Article and Find Full Text PDFJ Dairy Sci
January 2025
Confederación de Asociaciones de Frisona Española (CONAFE), Ctra. de Andalucía km 23600 Valdemoro, 28340 Madrid, Spain.
Epizootic hemorrhagic disease (EHD) is a non-contagious viral infection that can cause important economic losses in dairy farms. This study aimed to identify epidemiological and genetic factors influencing the susceptibility and severity of EHD in Holstein dairy cattle during the 2023 outbreak in Spain. Data from 2852 animals in 7 affected farms from 5 Spanish provinces were used.
View Article and Find Full Text PDFJ Dairy Sci
January 2025
College of Animal Science and Technology, Northwest A&F University, 22 nt, Xinong Road, Yangling, Shaanxi, China. Electronic address:
Low-coverage whole-genome sequencing (LcWGS), a cost-effective genotyping method, offers greater flexibility in variant detection than does single-nucleotide polymorphism (SNP) chips. However, to our knowledge, no studies have explored the application of LcWGS in sheep. This study aimed to evaluate the feasibility of implementing LcWGS and genotype imputation and assess their applicability in genomic studies of body weight and milk yield in sheep.
View Article and Find Full Text PDFJ Anim Sci
January 2025
USDA-Agricultural Research Service, U.S. Meat Animal Research Center (USMARC), Clay Center, NE, USA.
Sow lameness results in premature culling, causing economic loss and well-being issues. A study, utilizing a pressure-sensing mat (GAIT4) and video monitoring system (NUtrack), was conducted to identify objective measurements on gilts that are predictive of future lameness. Gilts (N = 3656) were categorized to describe their lifetime soundness: SOUND, retained for breeding with no detected mobility issues; LAME_SOW, retained for breeding and detected lame as a sow; CULL_STR, not retained due to poor leg structure; LAME_GILT, not retained due to visible signs of lameness; and CULL, not retained due to reasons other than leg structure.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!