Biomedical subjects

Warren M Snelling

Publications and source records attributed to Warren M Snelling.

8 recordsLinked to original sources

PubMed2025

Genomic prediction and genome-wide association study for liver abscesses in crossbred beef cattle.

Liver abscesses are a concern in feedlot cattle, and little is known about the role of genetics in their development. This study aimed to estimate genetic parameters and to identify single-nucleotide polymorphisms (SNPs) associated with liver abscesses. Crossbred cattle representing 18 breeds in the U.S. Meat Animal Research Center Germplasm Evaluation Program were phenotyped for liver abscesses at slaughter (n = 9,044). Seventeen percent of cattle had liver abscesses. These cattle had genotypes that were imputed to sequence variant genotypes. After filtering and quality control, 340,723 SNPs were used in the analysis. Liver abscess prevalence was modeled with a single-step genomic best linear unbiased prediction (ssGBLUP) threshold model using a Bayesian framework. The model included contemporary group (sex, treatment group, and slaughter date), additive genomic, and residual effects. Genomic heritability was 0.039 (95% highest posterior density = 0.005, 0.081), which was very small. To assess prediction quality, a 5-fold random cross-validation structure was used. Method Linear Regression was used to assess accuracy, bias, and dispersion by comparing estimated breeding values (EBV) from full and reduced analyses. Cross-validation metrics showed EBV based on genotypes had 0.05 reliability (SD < 0.01) with no bias relative to EBV based on genotypes and phenotypes. For the genome-wide association study, SNP effects were back calculated from the EBV solutions from ssGBLUP. No SNPs were associated with liver abscesses at a Benjamini-Hochberg adjusted 0.05 significance level. Although a large dataset was used, this result was because of the low genomic heritability and imprecise EBV used to calculate SNP effects. Based on these results, environmental factors contribute to most of the variation in liver abscesses. Genetic selection to reduce liver abscesses would be slow because of the low genomic heritability, measurement late in life, and inability to measure breeding animals. A faster approach would be finding additional environmental interventions that maintain animal performance.

Animals↗

PubMed2025

A vision of how low-coverage sequence data should contribute to genetic evaluation in the future.

Low-coverage sequencing refers to sequencing DNA of individuals to a low depth of coverage (e.g., 0.5X) and imputing that sequence to a genomic sequence based on reference haplotypes from individuals sequenced to a high depth of coverage (e.g., ≥10X). It has been proposed as an alternative to genotyping by Single-nucleotide polymorphisms (SNP) arrays. At least one commercial product based on it is available for agricultural species. Concerns limiting adoption in its current form are: 1) the cost of storing the huge volume of data it generates and 2) whether that additional data will result in improved accuracy of genetic evaluation. This work envisions future implementation of low-coverage sequencing to reduce storage costs and enhance genetic evaluations by leveraging the additional information in the full sequence of the pangenome to account for more genetic variation. We propose addressing the storage issue by representing genomic sequence of an individual in a pair of haplotype arrays with each element pointing to an enumerated haplotype of the sequence within one of approximately 50,000 defined genome segments. Assuming 60 million genomic variants, the infrastructure required to translate the identifier of any enumerated haplotype into its genomic sequence would require less than 10 gigabytes of binary storage. Each haplotype array element would require 2 bytes, so the marginal binary storage required to represent the genomic sequence of an individual would be about 200 kilobytes (KB), similar to the genotypes from a SNP array with 200,000 markers. This assumes no pedigree and no ambiguity of the imputation, though the latter is unrealistic. Strategies to minimize, and when necessary, to manage and efficiently represent ambiguity are proposed. The genomic sequence of an individual could be stored in about 1 KB (binary) if both parents have unambiguous sequences stored as described above. The proposed system for representing the pangenome includes algorithms for read mapping and imputation intended to leverage all known genetic variation in the target population. It is also designed to use sequencing reads generated for imputing the genomic sequence of new individuals to identify unrecognized mutations, crossovers, and structural variants, thus continuously improving the genome representation, especially if widespread use of low-coverage sequencing in livestock industries is realized. This could make improved genetic merit and management of livestock feasible without computational burden.

Animals↗

PubMed2005

Characterization of 954 bovine full-CDS cDNA sequences.

BACKGROUND: Genome assemblies rely on the existence of transcript sequence to stitch together contigs, verify assembly of whole genome shotgun reads, and annotate genes. Functional genomics studies also rely on transcript sequence to create expression microarrays or interpret digital tag data produced by methods such as Serial Analysis of Gene Expression (SAGE). Transcript sequence can be predicted based on reconstruction from overlapping expressed sequence tags (EST) that are obtained by single-pass sequencing of random cDNA clones, but these reconstructions are prone to errors caused by alternative splice forms, transcripts from gene families with related sequences, and expressed pseudogenes. These errors confound genome assembly and annotation. The most useful transcript sequences are derived by complete insert sequencing of clones containing the entire length, or at least the full protein coding sequence (CDS) portion, of the source mRNA. While the bovine genome sequencing initiative is nearing completion, there is currently a paucity of bovine full-CDS mRNA and protein sequence data to support bovine genome assembly and functional genomics studies. Consequently, the production of high-quality bovine full-CDS cDNA sequences will enhance the bovine genome assembly and functional studies of bovine genes and gene products. The goal of this investigation was to identify and characterize the full-CDS sequences of bovine transcripts from clones identified in non-full-length enriched cDNA libraries. In contrast to several recent full-length cDNA investigations, these full-CDS cDNAs were selected, sequenced, and annotated without the benefit of the target organism's genomic sequence, by using comparison of bovine EST sequence to existing human mRNA to identify likely full-CDS clones for full-length insert cDNA (FLIC) sequencing. RESULTS: The predicted bovine protein lengths, 5' UTR lengths, and Kozak consensus sequences from 954 bovine FLIC sequences (bFLICs; average length 1713 nt, representing 762 distinct loci) are all consistent with previously sequenced mammalian full-length transcripts. CONCLUSION: In most cases, the bFLICs span the entire CDS of the genes, providing the basis for creating predicted bovine protein sequences to support proteomics and comparative evolutionary research as well as functional genomics and genome annotation. The results demonstrate the utility of the comparative approach in obtaining predicted protein sequences in other species.

5' Untranslated Regions↗

PubMed2005

Linkage mapping bovine EST-based SNP.

BACKGROUND: Existing linkage maps of the bovine genome primarily contain anonymous microsatellite markers. These maps have proved valuable for mapping quantitative trait loci (QTL) to broad regions of the genome, but more closely spaced markers are needed to fine-map QTL, and markers associated with genes and annotated sequence are needed to identify genes and sequence variation that may explain QTL. RESULTS: Bovine expressed sequence tag (EST) and bacterial artificial chromosome (BAC)sequence data were used to develop 918 single nucleotide polymorphism (SNP) markers to map genes on the bovine linkage map. DNA of sires from the MARC reference population was used to detect SNPs, and progeny and mates of heterozygous sires were genotyped. Chromosome assignments for 861 SNPs were determined by twopoint analysis, and positions for 735 SNPs were established by multipoint analyses. Linkage maps of bovine autosomes with these SNPs represent 4585 markers in 2475 positions spanning 3058 cM. Markers include 3612 microsatellites, 913 SNPs and 60 other markers. Mean separation between marker positions is 1.2 cM. New SNP markers appear in 511 positions, with mean separation of 4.7 cM. Multi-allelic markers, mostly microsatellites, had a mean (maximum) of 216 (366) informative meioses, and a mean 3-lod confidence interval of 3.6 cM Bi-allelic markers, including SNP and other marker types, had a mean (maximum) of 55 (191) informative meioses, and were placed within a mean 8.5 cM 3-lod confidence interval. Homologous human sequences were identified for 1159 markers, including 582 newly developed and mapped SNP. CONCLUSION: Addition of these EST- and BAC-based SNPs to the bovine linkage map not only increases marker density, but provides connections to gene-rich physical maps, including annotated human sequence. The map provides a resource for fine-mapping quantitative trait loci and identification of positional candidate genes, and can be integrated with other data to guide and refine assembly of bovine genome sequence. Even after the bovine genome is completely sequenced, the map will continue to be a useful tool to link observable phenotypes and animal genotypes to underlying genes and molecular mechanisms influencing economically important beef and dairy traits.

Alleles↗

PubMed2004

Integrating linkage and radiation hybrid mapping data for bovine chromosome 15.

BACKGROUND: Bovine chromosome (BTA) 15 contains a quantitative trait loci (QTL) for meat tenderness, as well as several breaks in synteny with human chromosome (HSA) 11. Both linkage and radiation hybrid (RH) maps of BTA 15 are available, but the linkage map lacks gene-specific markers needed to identify genes underlying the QTL, and the gene-rich RH map lacks associations with marker genotypes needed to define the QTL. Integrating the maps will provide information to further explore the QTL as well as refine the comparative map between BTA 15 and HSA 11. A recently developed approach to integrating linkage and RH maps uses both linkage and RH data to resolve a consensus marker order, rather than aligning independently constructed maps. Automated map construction procedures employing this maximum-likelihood approach were developed to integrate BTA RH and linkage data, and establish comparative positions of BTA 15 markers with HSA 11 homologs. RESULTS: The integrated BTA 15 map represents 145 markers; 42 shared by both data sets, 36 unique to the linkage data and 67 unique to RH data. Sequence alignment yielded comparative positions for 77 bovine markers with homologs on HSA 11. The map covers approximately 32% of HSA 11 sequence in five segments of conserved synteny, another 15% of HSA 11 is shared with BTA 29. Bovine and human order are consistent in portions of the syntenic segments, but some rearrangement is apparent. Comparative positions of gene markers near the meat tenderness QTL indicate the region includes separate segments of HSA 11. The two microsatellite markers flanking the QTL peak are between defined syntenic segments. CONCLUSIONS: Combining data to construct an integrated map not only consolidates information from different sources onto a single map, but information contributed from each data set increases the accuracy of the map. Comparison of bovine maps with well annotated human sequence can provide useful information about genes near mapped bovine markers, but bovine gene order may be different than human. Procedures to connect genetic and physical mapping data, build integrated maps for livestock species, and connect those maps to more fully annotated sequence can be automated, facilitating the maintenance of up-to-date maps, and providing a valuable tool to further explore genetic variation in livestock.

Animals↗

PubMed2004

Beta-2-microglobulin haplotypes in U.S. beef cattle and association with failure of passive transfer in newborn calves.

Failure of passive transfer (FPT) is a condition in which neonates do not acquire protective serum levels of maternal antibodies. A principal component of antibody transport is the neonatal receptor for the Fc portion of immunoglobulin, a heterodimer of a MHC-1 alpha-chain homolog ( FCGRT) and beta-2-microglobulin ( B2M). Previously, two FCGRT haplotypes were associated with differences in immunoglobulin G (IgG) passive transfer in cattle (Laegreid et al. (2002) Mamm Genome 13, 704-710). The present study had two objectives: first, to characterize the B2M haplotype structure in a diverse group of U.S. beef cattle, and second, to evaluate those haplotypes for association with either high or low serum IgG levels in newborn calves. Twelve single nucleotide polymorphisms (SNPs), assorted into eight haplotypes, were identified by sequencing regions of B2M exons II and IV in a multi-breed panel of 96 beef cattle. Calves homozygous for one of the eight haplotypes ( B2M 2,2) were at increased risk of FPT (odds ratio = 10.60, CI(95%) 2.07-54.24, p = 0.005). These results indicate that this haplotype is in linkage disequilibrium with genetic risk factors affecting passive transfer of IgG in beef calves, an important determinant of neonatal calf morbidity and mortality.

Animal Husbandry↗

PubMed2004

A comprehensive genetic map of the cattle genome based on 3802 microsatellites.

A microsatellite-based high-density genetic map facilitates for fine mapping of hereditary traits of interest, characterization of meiosis, and providing a foundation for physical map construction. Here, we developed a comprehensive genetic map on the basis of >880,000 genotypes across the USDA MARC cattle reference families with a potential genetic resolution of 0.8 cM at the 95% confidence level ( approximately 800 kb in the bovine genome). We incorporated 2325 microsatellites into the second-generation genetic map by linkage analysis based on sex-averaged two-point LOD scores (>3.0), of which 2293 were fine-mapped by multipoint linkage analysis. The new 3160-cM map comprised of 29 sex-averaged autosomal linkage groups and a sex-specific X-chromosome linkage group includes 3960 markers with 2389 positions, resulting in an average interval size of 1.4 cM. More than half (51%) of the total length of the map is covered with intervals of 2.0 cM or less, and the largest gap is a 10.2-cM interval on the X-linkage group. The new map should accelerate fine mapping and positional cloning of genes for genetic diseases and economically important traits in cattle, as well as related livestock species, such as sheep and goat.

Animals↗

PubMed2003

Prion gene sequence variation within diverse groups of U.S. sheep, beef cattle, and deer.

Prions are proteins that play a central role in transmissible spongiform encephalopathies in a variety of mammals. Among the most notable prion disorders in ungulates are scrapie in sheep, bovine spongiform encephalopathy in cattle, and chronic wasting disease in deer. Single nucleotide polymorphisms in the sheep prion gene ( PRNP) have been correlated with susceptibility to natural scrapie in some populations. Similar correlations have not been reported in cattle or deer; however, characterization of PRNP nucleotide diversity in those species is incomplete. This report describes nucleotide sequence variation and frequency estimates for the PRNP locus within diverse groups of U.S. sheep, U.S. beef cattle, and free-ranging deer ( Odocoileus virginianus and O. hemionus from Wyoming). DNA segments corresponding to the complete prion coding sequence and a 596-bp portion of the PRNP promoter region were amplified and sequenced from DNA panels with 90 sheep, 96 cattle, and 94 deer. Each panel was designed to contain the most diverse germplasm available from their respective populations to facilitate polymorphism detection. Sequence comparisons identified a total of 86 polymorphisms. Previously unreported polymorphisms were identified in sheep (9), cattle (13), and deer (32). The number of individuals sampled within each population was sufficient to detect more than 95% of all alleles present at a frequency greater than 0.02. The estimation of PRNP allele and genotype frequencies within these diverse groups of sheep, cattle, and deer provides a framework for designing accurate genotype assays for use in genetic epidemiology, allele management, and disease control.

Amyloid↗