Cyberinfrastructure for Life Sciences - iAnimal Resources for Genomics and Other Data Driven Biology

Whole genome sequence, SNPs, copy number variation, phenotypes and other “-omics” data underlie evidence-based estimations of breeding value. Unfortunately, the computational resources (data storage, high-performance computing, analysis pipelines, etc.) that exploit this knowledge are limited in availability – many investigations are therefore restricted to the commercial sector or well-funded academic programs. Cyberinfrastructure developed by the iPlant Collaborative (NSF-#DBI0735191) and its extension iAnimal (USDA-#2013-67015-21231) provides the animal breeding community a comprehensive and freely available platform for the storage, sharing, and analyses of large datasets – from genomes to phenotype data. iPlant/iAnimal tools support a variety of genotype-phenotype related analyses in a platform that accommodates every level of user – from breeder to bioinformatician. These tools have been used to develop scalable, accessible versions of common workflows required for applying sequencing to livestock genomics

Characterizing Haplotype Diversity in Ten US Beef Cattle Breeds

The distributions of haplotype diversity across the whole genome among 10 US beef cattle breeds were constructed. In most chromosomes for all the breeds, consistent low haplotype diversity were observed in some specific regions, 55% of which was found to match the positions of reported gene duplications. Further work is required to determine whether the low haplotype diversity is real, or a result of problems in sequencing which have limited our ability to identify informative markers in those regions. Haplotype diversity will be the subject of ongoing work to identify haplotypes that are under-represented as homozygotes, to fine-map regions with major gene effects, and to fit haplotype rather than SNP models for genomic prediction

Population genomics of local adaptation versus speciation in coral reef fishes (Hypoplectrus spp, Serranidae)

Are the population genomic patterns underlying local adaptation and the early stages of speciation similar? Addressing this question requires a system in which (i) local adaptation and the early stages of speciation can be clearly identified and distinguished, (ii) the amount of genetic divergence driven by the two processes is similar, and (iii) comparisons can be repeated both taxonomically (for local adaptation) and geographically (for speciation). Here, we report just such a situation in the hamlets (Hypoplectrus spp), brightly colored reef fishes from the wider Caribbean. Close to 100,000 SNPs genotyped in 126 individuals from three sympatric species sampled in three repeated populations provide genome-wide levels of divergence that are comparable among allopatric populations (Fst estimate = 0.0042) and sympatric species (Fst estimate = 0.0038). Population genetic, clustering, and phylogenetic analyses reveal very similar patterns for local adaptation and speciation, with a large fraction of the genome undifferentiated (Fst estimate ≈ 0), a very small proportion of Fst outlier loci (0.05–0.07%), and remarkably few repeated outliers (1–3). Nevertheless, different loci appear to be involved in the two processes in Hypoplectrus, with only 7% of the most differentiated SNPs and outliers shared between populations and species comparisons. In particular, a tropomyosin (Tpm4) and a previously identified hox (HoxCa) locus emerge as candidate loci (repeated outliers) for local adaptation and speciation, respectively. We conclude that marine populations may be locally adapted notwithstanding shallow levels of genetic divergence, and that from a population genomic perspective, this process does not appear to differ fundamentally from the early stages of speciation

Single nucleotide variant discovery of highly inbred Leghorn and Fayoumi chicken breeds using pooled whole genome resequencing data reveals insights into phenotype differences

Background Analyses of sequence variants of two distinct and highly inbred chicken lines allowed characterization of genomic variation that may be associated with phenotypic differences between breeds. These lines were the Leghorn, the major contributing breed to commercial white-egg production lines, and the Fayoumi, representative of an outbred indigenous and robust breed. Unique within- and between-line genetic diversity was used to define the genetic differences of the two breeds through the use of variant discovery and functional annotation. Results Downstream fixation test (F ST ) analysis and subsequent gene ontology (GO) enrichment analysis elucidated major differences between the two lines. The genes with high F STvalues for both breeds were used to identify enriched gene ontology terms. Over-enriched GO annotations were uncovered for functions indicative of breed-related traits of pathogen resistance and reproductive ability for Fayoumi and Leghorn, respectively. Conclusions Variant analysis elucidated GO functions indicative of breed-predominant phenotypes related to genomic variation in the lines, showing a possible link between the genetic variants and breed traits

Genomic analysis of Ugandan and Rwandan chicken ecotypes using a 600 k genotyping array

Background Indigenous populations of animals have developed unique adaptations to their local environments, which may include factors such as response to thermal stress, drought, pathogens and suboptimal nutrition. The survival and subsequent evolution within these local environments can be the result of both natural and artificial selection driving the acquisition of favorable traits, which over time leave genomic signatures in a population. This study’s goals are to characterize genomic diversity and identify selection signatures in chickens from equatorial Africa to identify genomic regions that may confer adaptive advantages of these ecotypes to their environments. Results Indigenous chickens from Uganda (n = 72) and Rwanda (n = 100), plus Kuroilers (n = 24, an Indian breed imported to Africa), were genotyped using the Axiom® 600 k Chicken Genotyping Array. Indigenous ecotypes were defined based upon location of sampling within Africa. The results revealed the presence of admixture among the Ugandan, Rwandan, and Kuroiler populations. Genes within runs of homozygosity consensus regions are linked to gene ontology (GO) terms related to lipid metabolism, immune functions and stress-mediated responses (FDR \u3c 0.15). The genes within regions of signatures of selection are enriched for GO terms related to health and oxidative stress processes. Key genes in these regions had anti-oxidant, apoptosis, and inflammation functions. Conclusions The study suggests that these populations have alleles under selective pressure from their environment, which may aid in adaptation to harsh environments. The correspondence in gene ontology terms connected to stress-mediated processes across the populations could be related to the similarity of environments or an artifact of the detected admixture

The genetic architecture of complete blood counts in lactating Holstein dairy cows

Complete blood counts (CBCs) measure the abundance of individual immune cells, red blood cells, and related measures such as platelets in circulating blood. These measures can indicate the health status of an animal; thus, baseline circulating levels in a healthy animal may be related to the productive life, resilience, and production efficiency of cattle. The objective of this study is to determine the heritability of CBC traits and identify genomic regions that are associated with CBC measurements in lactating Holstein dairy cattle. The heritability of CBCs was estimated using a Bayes C0 model. The study population consisted of 388 cows with genotypes at roughly 75,000 markers and 16 different CBC phenotypes taken at one to three time points (n = 33, 131, and 224 for 1, 2, and 3 time points, respectively). Heritabilities ranged from 0.00 ± 0.00 (red cell distribution width) to 0.68 ± 0.06 (lymphocytes). A total of 96 different 1-Mb windows were identified that explained more than 1% of the genetic variance for at least one CBC trait, with 10 windows explaining more than 1% of the genetic variance for two or more traits. Multiple genes in the identified regions have functions related to immune response, cell differentiation, anemia, and disease. Positional candidate genes include RAD52 motif-containing protein 1 (RDM1), which is correlated with the degree of immune infiltration of immune cells, and C-X-C motif chemokine ligand 12 (CXCL12), which is critically involved in neutrophil bone marrow storage and release regulation and enhances neutrophil migration. Since animal health directly impacts feed intake, understanding the genetics of CBCs may be useful in identifying more disease-resilient and feed-efficient dairy cattle. Identification of genes responsible for variation in CBCs will also help identify the variability in how dairy cattle defend against illness and injury

Comparison of variant calling methods for whole genome sequencing data in dairy cattle

Accurate identification of SNPs from next-generation sequencing data is crucial for high-quality downstream analysis. Whole genome sequence data of 65 key ancestors of genotyped Swiss dairy populations were available for investigation (24 billion reads, 96.8% mapped to UMD31, 12x coverage). Four publically available variant calling programmes were assessed and different levels of pre-calling handling for each method were tested and compared. SNP concordance was examined with Illumina’s BovineHD Genotyping BeadChip®. Depending on variant calling software used, between 16,894,054 and 22,048,382 SNP were identified (multi-sample calling). A total of 14,644,310 SNP were identified by all four variant callers (multi-sample calling). InDel counts ranged from 1,997,791 to 2,857,754; 1,708,649 InDels were identified by all four variant callers. A minimum of pre-calling data handling resulted in the highest non-reference sensitivity and the lowest non-reference discrepancy rates

A Limousin Specific Myostatin Allele Affects Longissimus Muscle Area and Fatty Acid Profiles in a Wagyu-Limousin F2 Population

A microsatellite-based genome scan of a Wagyu x Limousin F(2) cross population previously demonstrated QTL affecting LM area and fatty acid composition were present in regions near the centromere of BTA2. In this study, we used 70 SNP markers to examine the centromeric 24 megabases (Mb) of BTA2, including the Limousin-specific F94L myostatin allele (AB076403.1; 415C \u3e A) located at approximately 6 Mb on the draft genome sequence of BTA2. A significant effect of the F94L marker was observed (F = 60.17) for LM area, which indicated that myostatin is most likely responsible for the effect. This is consistent with previous reports that the substitution of Leu for Phe at AA 94 of myostatin (caused by the 415C \u3e A transversion) is associated with increased muscle growth. Surprisingly, several fatty acid trait QTL, which affected the amount of unsaturated fats, also mapped to or very near the myostatin marker, including the ratio of C16:1 MUFA to C16:0 saturated fat (F = 16.72), C18:1 to C18:0 (F = 18.88), and total content of MUFA (F = 17.12). In addition, QTL for extent of marbling (F = 14.73) approached significance (P = 0.05), and CLA concentration (F = 9.22) was marginally significant (P = 0.18). We also observed associations of SNP located at 16.3 Mb with KPH (F = 15.00) and for the amount of SFA (F = 12.01). These results provide insight into genetic differences between the Wagyu and Limousin breeds and may lead to a better tasting and healthier product for consumers through improved selection for lipid content of beef

Identification of a putative quantitative trait nucleotide in guanylate binding protein 5 for host response to PRRS virus infection

Citation: Koltes, J. E., Fritz-Waters, E., Eisley, C. J., Choi, I., Bao, H., Kommadath, A., . . . Reecy, J. M. (2015). Identification of a putative quantitative trait nucleotide in guanylate binding protein 5 for host response to PRRS virus infection. Bmc Genomics, 16, 13. doi:10.1186/s12864-015-1635-9Background: Previously, we identified a major quantitative trait locus (QTL) for host response to Porcine Respiratory and Reproductive Syndrome virus (PRRSV) infection in high linkage disequilibrium (LD) with SNP rs80800372 on Sus scrofa chromosome 4 (SSC4). Results: Within this QTL, guanylate binding protein 5 (GBP5) was differentially expressed (DE) (p < 0.05) in blood from AA versus AB rs80800372 genotyped pigs at 7,11, and 14 days post PRRSV infection. All variants within the GBP5 transcript in LD with rs80800372 exhibited allele specific expression (ASE) in AB individuals (p < 0.0001). A transcript re-assembly revealed three alternatively spliced transcripts for GBP5. An intronic SNP in GBP5, rs340943904, introduces a splice acceptor site that inserts five nucleotides into the transcript. Individuals homozygous for the unfavorable AA genotype predominantly produced this transcript, with a shifted reading frame and early stop codon that truncates the 88 C-terminal amino acids of the protein. RNA-seq analysis confirmed this SNP was associated with differential splicing by QTL genotype (p < 0.0001) and this was validated by quantitative capillary electrophoresis (p < 0.0001). The wild-type transcript was expressed at a higher level in AB versus AA individuals, whereas the five-nucleotide insertion transcript was the dominant form in AA individuals. Splicing and ASE results are consistent with the observed dominant nature of the favorable QTL allele. The rs340943904 SNP was also 100 % concordant with rs80800372 in a validation population that possessed an alternate form of the favorable B QTL haplotype. Conclusions: GBP5 is known to play a role in inflammasome assembly during immune response. However, the role of GBP5 host genetic variation in viral immunity is novel. These findings demonstrate that rs340943904 is a strong candidate causal mutation for the SSC4 QTL that controls variation in host response to PRRSV.Additional Authors: Lunney, J. K.;Liu, P.;Carpenter, S.;Rowland, R. R. R.;Dekkers, J. C. M.;Reecy, J. M