Identification of polymorphisms in the bovine collagenous lectins and their association with infectious diseases in cattle

Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data

Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.

Candidate genes for mastitis resistance in dairy cattle: a data integration approach

BACKGROUND

Inflammation of the mammary tissue (mastitis) is one of the most detrimental health conditions in dairy ruminants and is considered the most economically important infectious disease of the dairy sector. Improving mastitis resistance is becoming an important goal in dairy ruminant breeding programmes. However, mastitis resistance is a complex trait and identification of mastitis-associated alleles in livestock is difficult. Currently, the only applicable approach to identify candidate loci for complex traits in large farm animals is to combine different information that supports the functionality of the identified genomic regions with respect to a complex trait.

METHODS

To identify the most promising candidate loci for mastitis resistance we integrated heterogeneous data from multiple sources and compiled the information into a comprehensive database of mastitis-associated candidate loci. Mastitis-associated candidate genes reported in association, expression, and mouse model studies were collected by searching the relevant literature and databases. The collected data were integrated into a single database, screened for overlaps, and used for gene set enrichment analysis.

RESULTS

The database contains candidate genes from association and expression studies and relevant transgenic mouse models. The 2448 collected candidate loci are evenly distributed across bovine chromosomes. Data integration and analysis revealed overlaps between different studies and/or with mastitis-associated QTL, revealing promising candidate genes for mastitis resistance.

CONCLUSION

Mastitis resistance is a complex trait influenced by numerous alleles. Based on the number of independent studies, we were able to prioritise candidate genes and propose a list of the 22 most promising. To our knowledge this is the most comprehensive database of mastitis associated candidate genes and could be helpful in selecting genes for functional validation studies.

Comparative gene expression profiling of milk somatic cells of Sahiwal cattle and Murrah buffaloes

India is the world's largest milk producing country because of massive contribution made by cattle and buffaloes. In the present investigation, comprehensive comparative profiling of transcriptomic landscape of milk somatic cells of Sahiwal cattle and Murrah buffaloes was carried out. Genes with highest transcript abundance in both species were enriched for biological processes such as lactation, immune response, cellular oxidant detoxification and response to hormones. Analysis of differential expression identified 377 significantly up-regulated and 847 significantly down-regulated genes with fold change >1.5 in Murrah buffaloes as compared to Sahiwal cattle (p_adj <0.05). Marked enrichment of innate and adaptive immune response related GO terms and higher expression of genes for various host defense peptides such as lysozyme, defensin β and granzymes were evident in buffaloes. Genes related to ECM-receptor interaction, complement and coagulation cascades, cytokine-cytokine receptor interaction and keratinization pathway showed more abundant expression in cattle. Network analysis of the up-regulated genes delineated highly connected genes representing immunity and haematopoietic cell lineage (CBL, CD28, CD247, PECAM1 and ITGA4). For the down-regulated dataset, genes with highest interactions were KRT18, FGFR1, GPR183, ITGB3 and DKK3. Our results lend support to more robust immune mechanisms in buffaloes, possibly explaining lower susceptibility to mammary infections as compared to cattle.

Functional characterization of partial recombinant goat conglutinin: Its role as innate immunity marker and use as antigen in sandwich ELISA

Conglutinin, a liver synthesized versatile innate immune marker consisting C-type lectin domain belongs to collectin superfamily of proteins. The protein, first detected in bovine serum as soluble pattern recognition receptor (PRR) has wide range of antimicrobial activities. In the present study, open reading frame (ORF) encoding neck and carbohydrate recognition domain (NCRD) of goat conglutinin gene ligated to the vector pRSET-A was expressed in E. coli BL-21(pLys) cells. The 27 kDa recombinant protein (rGCGN) purified by single step Ni⁺² -NTA affinity chromatography was found to cross-react with recombinant anti-buffalo conglutinin antibody raised in poultry. Further, it displayed calcium-dependant sugar binding activity towards yeast mannan and calcium-independent binding activity towards LPS. The mannan binding activity of rGCGN was inhibited in the presence of N-acetyl-glucosamine because of higher affinity towards this sugar. The recombinant protein was found to stimulate production of superoxide ions and hydrogen peroxide in goat neutrophils, which are instrumental in stimulating phagocytic activity of cells. When used as antigen in Sandwich ELISA, straight line (Y = 0.299x + 0.067, R² = 0.997) was observed within the concentration range of 200-1000 ng/100 μl of rGCGN. Using this equation, the native conglutinin concentration in goat sera was estimated to be 0.5-7.5 μg/ml. The results indicated that prokaryotically expressed functionally active rGCGN can be used as antigen to assess native serum conglutinin levels in Sandwich ELISA and as immunomodulator in therapeutic applications to sequester unwanted immune complexes from the circulation.

Optimizing Selection of the Reference Population for Genotype Imputation From Array to Sequence Variants

Imputation of high-density genotypes to whole-genome sequences (WGS) is a cost-effective method to increase the density of available markers within a population. Imputed genotypes have been successfully used for genomic selection and discovery of variants associated with traits of interest for the population. To allow for the use of imputed genotypes for genomic analyses, accuracy of imputation must be high. Accuracy of imputation is influenced by multiple factors, such as size and composition of the reference group, and the allele frequency of variants included. Understanding the use of imputed WGSs prior to the generation of the reference population is important, as accurate imputation might be more focused, for instance, on common or on rare variants. The aim of this study was to present and evaluate new methods to select animals for sequencing relying on a previously genotyped population. The Genetic Diversity Index method optimizes the number of unique haplotypes in the future reference population, while the Highly Segregating Haplotype selection method targets haplotype alleles found throughout the majority of the population of interest. First the WGSs of a dairy cattle population were simulated. The simulated sequences mimicked the linkage disequilibrium level and the variants’ frequency distribution observed in currently available Holstein sequences. Then, reference populations of different sizes, in which animals were selected using both novel methods proposed here as well as two other methods presented in previous studies, were created. Finally, accuracies of imputation obtained with different reference populations were compared against each other. The novel methods were found to have overall accuracies of imputation of more than 0.85. Accuracies of imputation of rare variants reached values above 0.50. In conclusion, if imputed sequences are to be used for discovery of novel associations between variants and traits of interest in the population, animals carrying novel information should be selected and, consequently, the Genetic Diversity Index method proposed here may be used. If sequences are to be used to impute the overall genotyped population, a reference population consisting of common haplotypes carriers selected using the proposed Highly Segregating Haplotype method is recommended.

Identification of genetic variation in equine collagenous lectins using targeted resequencing

Collagenous lectins are a family of soluble pattern recognition receptors that play an important role in innate immune resistance to infectious disease. Through recognition of carbohydrate motifs on the surface of pathogens, some collagenous lectins can activate the lectin pathway of complement, providing an effective means of host defense. Genetic polymorphisms in collagenous lectins have been shown in several species to predispose animals to a variety of infectious diseases. Infectious diseases are an important cause of morbidity in horses, however little is known regarding the role of equine collagenous lectins. Using a high-throughput, targeted re-sequencing approach, the relationship between genetic variation in equine collagenous lectin genes and susceptibility to disease was investigated. DNA was isolated from tissues obtained from horses submitted for post-mortem examination. Animals were divided into two populations, those with infectious or autoinflammatory diseases (n = 37) and those without (n = 52), and then subdivided by dominant pathological process for a total of 21 pools, each containing 4-5 horses. DNA was extracted from each horse and pooled in equimolar amounts, and the exons, introns, upstream (approximately 50 kb) and downstream (approximately 3 kb) regulatory regions for the 11 equine collagenous lectin genes and related MASP genes were targeted for re-sequencing. A custom target capture kit was used to prepare a sequencing library, which was sequenced on an Illumina MiSeq. After implementing quality control filters, 4559 variants were identified. Of these, 92 were present in the coding regions (43 missense, 1 nonsense, and 48 synonymous), 1414 in introns, 3029 in the upstream region, and 240 in the downstream region. In silico analysis of the missense short nucleotide variants identified 12 mutations with potential to disrupt collagenous lectin protein structure or function, 280 mutations located within predicted transcription factor binding sites, and 95 mutations located within predicted microRNA binding elements. Analysis of allelic association identified 113 mutations that segregated between the infectious/autoinflammatory and non-infectious populations. The variants discovered in this experiment represent potential genetic contributors to disease susceptibility of horses, and will serve as candidates for further population-level genotyping. This study contributes to the growing body of evidence that pooled, high-throughput sequencing is a viable strategy for cost-effective variant discovery.