Alan F. McCulloch

Background: Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. Results: Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. Conclusions: This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log ₁₀ proportions of each tag normalized within cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

The Tunisian Noire de Thibar sheep breed is a composite breed, recently selected to create animals that are uniformly black in order to avoid skin photosensitization after the ingestion of toxic “hypericum perforatum” weeds, which causes a major economic loss to sheep farmers. We assessed genetic differentiation and estimated marker F_ST using genotyping-by-sequencing (GBS) data in black (Noire de Thibar) and related white-coated (Queue fine de l’ouest) sheep breeds to identify signals of artificial selection. The results revealed the selection signatures within candidate genes related to coat color, which are assumed to be indirectly involved in the mechanism of photosensitization in sheep. The identified genes could provide important information for molecular breeding.

Non-semantic approaches to bioinformatic data analysis have potential relevance where semantic resources such as annotated finished reference genomes are lacking, such as in the analysis and utilisation of growing amounts of sequence data from non-model organisms, often associated with sequence-based agricultural, aqua-cultural and environmental sampling studies and commercial services. Even where rich semantic resources are available, semantic approaches to problems such as contrasting and comparing reference assemblies, and utilising multiple references in parallel to avoid reference bias, are costly and difficult to fully automate. We introduce and discuss a non-semantic data representation approach intended mainly for bioinformatic data called non-semantic labelling. Non-semantic labelling involves tensorially combining multiple kinds of model-based entropy-reducing data representation, with multiple representation models, so as to map both data and models into dual metric representation spaces, with goals of both reducing the statistical complexity of the data, and highlighting latent structure via machine learning and statistical analyses conducted within the dual representation spaces. As part of the framework, we introduce a novel algebraic abstraction of data representation mappings, and present four proof-of-concept examples of its application, to problems such as comparing and contrasting sequence assemblies, utilisation of multiple references for annotation and development of quality control diagnostics in a variety of high-throughput sequencing contexts. Database URL: https://github.com/AgResearch/data_prism

The nucleotide-binding oligomerization domain containing 1 (NOD1) gene encodes a pattern recognition receptor that senses pathogens, leading to downstream responses characteristic of innate immunity. We investigated the role of NOD1 single nucleotide polymorphisms (SNPs) on IBD risk in a New Zealand Caucasian population, and studied Nod1 expression in response to bacterial invasion in the Caco2 cell line. DNA samples from 388 Crohn's disease (CD), 405 ulcerative colitis (UC), 27 indeterminate colitis patients and 201 randomly selected controls, from Canterbury, New Zealand were screened for 3 common SNPs in NOD1, using the MassARRAY^® iPLEX Gold assay. Transcriptional activation of the protein produced by NOD1 (Nod1) was studied after infection of Caco2 cells with Escherichia coli LF82. Carrying the rs2075818 G allele decreased the risk of CD (OR = 0.66, 95% CI = 0.50–0.88, p < 0.002) but not UC. There was an increased frequency of the three SNP (rs2075818, rs2075822, rs2907748) haplotype, CTG (p = 0.004) and a decreased frequency of the GTG haplotype (p = 0.02).in CD. The rs2075822 CT or TT genotypes were at an increased frequency (genotype p value = 0.02), while the rs2907748 AA or AG genotypes showed decreased frequencies in UC (p = 0.04), but not in CD. Functional assays showed that Nod1 is produced 6 hours after bacterial invasion of the Caco2 cell line. The NOD1 gene is important in signalling invasion of colonic cells by pathogenic bacteria, indicative of its' key role in innate immunity. Carrying specific SNPs in this gene significantly modifies the risk of CD and/or UC in a New Zealand Caucasian population.

If mutation within the coding region of the genome is largely not adaptive, the ratio of nonsynonymous (dN) to synonymous substitutions (dS) per site (dN/dS) should be approximately equal among closely related species. Furthermore, dN/dS in divergence between species should be equivalent to dN/dS in polymorphisms. This hypothesis is of particular interest in closely related members of the Bovini tribe, because domestication has promoted rapid phenotypic divergence through strong artificial selection of some species while others remain undomesticated. We examined a number of genes that may be involved in milk production in Domestic cattle and a number of their wild relatives for evidence that domestication had affected molecular evolution. Elevated rates of dN/dS were further queried to determine if they were the result of positive selection, low effective population size (Ne) or reduced selective constraint.

Background Single nucleotide polymorphisms (SNPs) are an abundant form of genetic variation in the genome of every species and are useful for gene mapping and association studies. Of particular interest are non-synonymous SNPs, which may alter protein function and phenotype. We therefore examined bovine expressed sequences for non-synonymous SNPs and validated and tested selected SNPs for their association with measured traits. Results Over 500,000 public bovine expressed sequence tagged (EST) sequences were used to search for coding SNPs (cSNPs). A total of 15,353 SNPs were detected in the transcribed sequences studied, of which 6,325 were predicted to be coding SNPs with the remaining 9,028 SNPs presumed to be in untranslated regions. Of the cSNPs detected, 2,868 were predicted to result in a change in the amino acid encoded. In order to determine the actual number of non-synonymous polymorphic SNPs we designed assays for 920 of the putative SNPs. These SNPs were then genotyped through a panel of cattle DNA pools using chip-based MALDI-TOF mass spectrometry. Of the SNPs tested, 29% were found to be polymorphic with a minor allele frequency >10%. A subset of the SNPs was genotyped through animal resources in order to look for association with age of puberty, facial eczema resistance or meat yield. Three SNPs were nominally associated with resistance to the disease facial eczema (P < 0.01). Conclusion We have identified 15,353 putative SNPs in or close to bovine genes and 2,868 of these SNPs were predicted to be non-synonymous. Approximately 29% of the non-synonymous SNPs were polymorphic and common with a minor allele frequency >10%. Of the SNPs detected in this study, 99% have not been previously reported. These novel SNPs will be useful for association studies or gene mapping.

Background: Gastrointestinal nematodes constitute a major cause of morbidity and mortality in grazing ruminants. Individual animals or breeds, however, are known to differ in their resistance to infection. Gene expression profiling allows us to examine large numbers of transcripts simultaneously in order to identify those transcripts that contribute to an animal's susceptibility or resistance.Results: With the goal of identifying genes with a differential pattern of expression between sheep genetically resistant and susceptible to gastrointestinal nematodes, a 20,000 spot ovine cDNA microarray was constructed. This array was used to interrogate the expression of 9,238 known genes in duodenum tissue of four resistant and four susceptible female lambs. Naïve animals were used in order to look at genes that were differentially expressed in the absence of infection with gastrointestinal nematodes. Forty one unique known genes were identified that were differentially expressed between the resistant and susceptible animals. Northern blotting of a selection of the genes confirmed differential expression. The differentially expressed genes had a variety of functions, although many genes relating to the stress response and response to stimulus were more highly expressed in the susceptible animals.Conclusion: We have constructed the first reported ovine microarray and used this array to examine gene expression in lambs genetically resistant and susceptible to gastrointestinal nematode infection. This study indicates that susceptible animals appear to be generating a hyper-sensitive immune response to non-nematode challenges. The gastrointestinal tract of susceptible animals is therefore under stress and compromised even in the absence of gastrointestinal nematodes. These factors may contribute to the genetic susceptibility of these animals.