Bovine CLEC7A genetic variants and their association with seropositivity in Johne's disease ELISA

Mycobacterium avium ssp. paratuberculosis (MAP) infection in cattle causes significant economic losses to the dairy and beef industries resulting from reduced productivity, premature culling and mortality. Bovine Dectin-1, an important pattern recognition molecule that is able to generate a proinflammatory response by acting alongside Toll like receptor (TLR) signaling, is known to co-operate with TLR2 to specifically activate a macrophage proinflammatory response against mycobacterial infections. Therefore, the goal of this study was to identify single nucleotide polymorphisms (SNPs) in the gene encoding bovine Dectin-1 (CLEC7A) and to assess their association with susceptibility to MAP infection in dairy cattle. Blood and milk samples, collected from commercial dairy operations, were tested for MAP infection using blood and milk ELISAs and a resource population consisting of 197 infected and 242 healthy cattle was constructed. Pooled DNA was used for sequencing and eight single nucleotide polymorphisms (SNPs) were identified. Identified SNPs were genotyped on the resource population using the iPLEX MassARRAY system and statistical analysis was performed using logistic regression fitting the additive and dominance effects of each SNP in the model. Out of a total of eight identified SNPs, five were successfully genotyped, and three out of these five SNPs were found to be in complete linkage. Statistical analysis revealed a strong association between a non-synonymous SNP c.589A>G (p = 0.008), and MAP infection status of the resource population inferred by seropositivity in MAP antibody specific ELISAs. This SNP c.589A>G was located in the geneic region that encodes the carbohydrate recognition domain of bovine Dectin-1. Therefore, further investigation of its functional relevance is warranted.     

Bovine IFNGR2, IL12RB1, IL12RB2, and IL23R polymorphisms and MAP infection status

Mycobacterium avium ssp. paratuberculosis (MAP) infection causes a chronic granulomatous inflammatory condition of the bovine gut that is characterized by diarrhea, progressive weight loss, and emaciation, and ultimately leads to loss in productivity and profitability of dairy operations. The host cytokine machinery is known to play an important role in protecting against MAP infection. Therefore, the goal of the present study was to assess whether polymorphisms in candidate genes encoding important cytokines and cytokine receptors are associated with MAP infection status of dairy cattle. MAP infection status was evaluated based on serum and milk enzyme-linked immunosorbent assays (ELISAs) for MAP-specific antibodies. Twenty previously reported polymorphisms in genes encoding bovine interferon gamma (IFNG), IFNGR1, IFNGR2, IL22, IL22RA1, IL12RB1, IL12RB2, and IL23R were genotyped in a resource population of 446 dairy Holsteins with known MAP infection status, and logistic regression was used to assess the statistical association with a binomial MAP infection status phenotype. Four SNPs in IFNGR2, IL12RB1, IL12RB2, and IL23R were found to be associated with the MAP infection status of the resource population. These results underscore the importance of cytokines and their receptors in conferring protection against MAP infection and warrant further functional characterization of these associations.     

The extent of linkage disequilibrium in beef cattle breeds using high-density SNP genotypes

Background

The extent of linkage disequilibrium (LD) between molecular markers impacts genome-wide association studies and implementation of genomic selection. The availability of high-density single nucleotide polymorphism (SNP) genotyping platforms makes it possible to investigate LD at an unprecedented resolution. In this work, we characterised LD decay in breeds of beef cattle of taurine, indicine and composite origins and explored its variation across autosomes and the X chromosome.

Findings

In each breed, LD decayed rapidly and r² was less than 0.2 for marker pairs separated by 50 kb. The LD decay curves clustered into three groups of similar LD decay that distinguished the three main cattle types. At short distances between markers (< 10 kb), taurine breeds showed higher LD (r² = 0.45) than their indicine (r² = 0.25) and composite (r² = 0.32) counterparts. This higher LD in taurine breeds was attributed to a smaller effective population size and a stronger bottleneck during breed formation. Using all SNPs on only the X chromosome, the three cattle types could still be distinguished. However for taurine breeds, the LD decay on the X chromosome was much faster and the background level much lower than for indicine breeds and composite populations. When using only SNPs that were polymorphic in all breeds, the analysis of the X chromosome mimicked that of the autosomes.

Conclusions

The pattern of LD mirrored some aspects of the history of breed populations and showed a sharp decay with increasing physical distance between markers. We conclude that the availability of the HD chip can be used to detect association signals that remained hidden when using lower density genotyping platforms, since LD dropped below 0.2 at distances of 50 kb.     

Accuracy of genotype imputation in Nelore cattle

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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0069-1) contains supplementary material, which is available to authorized users.     

Bovine PGLYRP1 polymorphisms and their association with resistance to Mycobacterium avium ssp. paratuberculosis

Mycobacterium avium ssp. paratuberculosis (MAP) causes a chronic, granulomatous inflammatory condition of the intestines in ruminants and wild-type species. It causes significant economic losses to the dairy and beef industries owing to reduced productivity, premature culling and mortality. Bovine peptidoglycan recognition protein 1 is an important pattern recognition molecule that is capable of directly killing microorganisms. The goal of this study was to identify single nucleotide polymorphisms (SNPs) in the gene encoding bovine peptidoglycan recognition protein 1 and to assess their association with susceptibility to MAP infection in dairy cattle. Blood and milk samples were collected from Holsteins in Southwestern and Eastern Ontario and tested for MAP infection using blood and milk ELISAs. A resource population consisting of 197 infected (S/P > 0.25) and 242 healthy (S/P < 0.10) cattle was constructed. Sequencing of pooled DNA was used to identify three SNPs (c.102G>C, c.480G>A and c.625C>A) that were genotyped in the resource population. Statistical analysis was performed using a logistic regression model fitting the additive and dominance effects of each SNP in the model. SNP c.480G>A (P = 0.054) was found to be associated with susceptibility to MAP infection. Cows with a copy of the major allele 'G' at this locus had an odds ratio of 1.51 (95% CI: 0.99-2.31) for being infected with MAP.     

Association of TLR4 polymorphisms with Mycobacterium avium subspecies paratuberculosis infection status in Canadian Holsteins

Mycobacterium avium ssp. paratuberculosis (MAP) causes chronic enteritis in cattle that results in substantial financial losses to the cattle industry worldwide. Given that susceptibility to MAP infection is determined in part by genetics, marker‐assisted selection may help in the breeding of animals that are more resistant to MAP infection. The toll‐like receptor 4 gene (TLR4) was selected as a potential candidate gene because of its role in innate immunity and its involvement in MAP recognition and infection. The objective of this study, therefore, was to identify associations between TLR4 polymorphisms and susceptibility to MAP infection in Canadian Holstein cows. Two biologically relevant SNPs, including c.‐226G>C in the 5′‐untranslated region and the non‐synonymous SNP c.2021C>T in the potential TIR domain, were selected for an association analysis with MAP infection status in 409 Canadian Holsteins. The haplotype C‐T from these combined SNPs yielded significant association with susceptibility to MAP infection, supporting the involvement of TLR4 in susceptibility to MAP infection.     

Whole‐Genome association analysis of susceptibility to paratuberculosis in Holstein cattle

The objective of this study was to identify genetic markers and genomic regions associated with susceptibility to Mycobacterium avium ssp. paratuberculosis (MAP) infection in Holstein cattle. Associated single nucleotide polymorphisms (SNPs) were identified by genotyping 521 MAP‐infected Holstein cows and comparing SNP allele frequencies of these infected cows with allele frequencies estimated from specific reference populations. Reference population allele frequency estimates used Holstein sire genotype data and were weighted estimates based on sire usage within the population in question. The 521 infected cows were 233 and 288 cows from two resource populations of approximately 5000 cows each, collected independently. Population 1 was comprised primarily of daughters of twelve Holstein artificial insemination sires used heavily within the US dairy cattle population. Samples were obtained from 300 co‐operating commercial dairy herds throughout the US and were tested by both MAP faecal culture and blood‐enzyme‐linked immunosorbent assay (ELISA). Population 2 consisted of dairy cattle from six co‐operating dairy herds in Wisconsin, with all animals in the herds tested by blood enzyme‐linked immunosorbent assay (ELISA) for MAP infection. Genotyping was performed with the Illumina Bovine SNP50 Bead Chip, providing genotypes for 35 772 informative SNPs. Data from the two resource populations were analysed both in separate and combined analyses. The most significant autosomal markers from the individual and combined analyses (n = 197, nominal P < 0.001) were used in a stepwise logistic regression analysis to identify a set of 51 SNPs that could be used as a predictor of genetics for Holstein cattle susceptibility to MAP infection.     

Genomic relationships based on X chromosome markers and accuracy of genomic predictions with and without X chromosome markers

Background

Although the X chromosome is the second largest bovine chromosome, markers on the X chromosome are not used for genomic prediction in some countries and populations. In this study, we presented a method for computing genomic relationships using X chromosome markers, investigated the accuracy of imputation from a low density (7K) to the 54K SNP (single nucleotide polymorphism) panel, and compared the accuracy of genomic prediction with and without using X chromosome markers.

Methods

The impact of considering X chromosome markers on prediction accuracy was assessed using data from Nordic Holstein bulls and different sets of SNPs: (a) the 54K SNPs for reference and test animals, (b) SNPs imputed from the 7K to the 54K SNP panel for test animals, (c) SNPs imputed from the 7K to the 54K panel for half of the reference animals, and (d) the 7K SNP panel for all animals. Beagle and Findhap were used for imputation. GBLUP (genomic best linear unbiased prediction) models with or without X chromosome markers and with or without a residual polygenic effect were used to predict genomic breeding values for 15 traits.

Results

Averaged over the two imputation datasets, correlation coefficients between imputed and true genotypes for autosomal markers, pseudo-autosomal markers, and X-specific markers were 0.971, 0.831 and 0.935 when using Findhap, and 0.983, 0.856 and 0.937 when using Beagle. Estimated reliabilities of genomic predictions based on the imputed datasets using Findhap or Beagle were very close to those using the real 54K data. Genomic prediction using all markers gave slightly higher reliabilities than predictions without X chromosome markers. Based on our data which included only bulls, using a G matrix that accounted for sex-linked relationships did not improve prediction, compared with a G matrix that did not account for sex-linked relationships. A model that included a polygenic effect did not recover the loss of prediction accuracy from exclusion of X chromosome markers.

Conclusions

The results from this study suggest that markers on the X chromosome contribute to accuracy of genomic predictions and should be used for routine genomic evaluation.     

Can Immune Response Mechanisms Explain the Fecal Shedding Patterns of Cattle Infected with Mycobacterium avium Subspecies paratuberculosis?

Johne’s disease (JD) is a chronic disease in ruminants and is caused by infection with Mycobacterium avium subspecies paratuberculosis (MAP). At late stages of the disease, MAP bacilli are shed via feces excretion and in turn create the potential for oral-fecal transmission. The role of the host immune response in MAP bacteria shedding patterns at different stages of JD is still unclear. We employed mathematical modeling to predict if the variation in MAP shedding could be correlated to the immune response in infected animals. We used a novel inverse modeling approach that assumed biological interactions among the antigen-specific lymphocyte proliferation response (cell-mediated response), antibody/humoral immune responses, and MAP bacteria. The modeling framework was used to predict and test possible biological interactions between the measured variables and returns only the essential interactions that are relevant in explaining the observed cattle MAP experimental infection data. Through confronting the models with data, we predicted observed effects (enhancement or suppression) and extents of interactions among the three variables. This analysis enabled classification of the infected cattle into three different groups that correspond to the unique predicted immune responses that are essential to explain the data from cattle within these groups. Our analysis highlights the strong and weak points of the modeling approach, as well as the key immune mechanisms predicted to be expressed in all animals and those that were different between animals, hence giving insight into how animals exhibit different disease dynamics and bacteria shedding patterns.     

A locus conferring tolerance to Theileria infection in African cattle

East Coast fever, a tick-borne cattle disease caused by the Theileria parva parasite, is among the biggest natural killers of cattle in East Africa, leading to over 1 million deaths annually. Here we report on the genetic analysis of a cohort of Bos indicus (Boran) cattle demonstrating heritable tolerance to infection with T. parva (h² = 0.65, s.e. 0.57). Through a linkage analysis we identify a 6 Mb genomic region on bovine chromosome 15 that is significantly associated with survival outcome following T. parva exposure. Testing this locus in an independent cohort of animals replicates this association with survival following T. parva infection. A stop gained variant in a paralogue of the FAF1 gene in this region was found to be highly associated with survival across both related and unrelated animals, with only one of the 20 homozygote carriers (T/T) of this change succumbing to the disease in contrast to 44 out of 97 animals homozygote for the reference allele (C/C). Consequently, we present a genetic locus linked to tolerance of one of Africa’s most important cattle diseases, raising the promise of marker-assisted selection for cattle that are less susceptible to infection by T. parva.     

A region on BTA14 that includes the positional candidate genes LYPLA1, XKR4 and TMEM68 is associated with feed intake and growth phenotypes in cattle(1)

Feed cost for beef cattle is the largest expense incurred by cattle producers. The development of genetic markers to enhance selection of more efficient animals that require less feed while still achieving acceptable levels of production has the potential to substantially reduce production costs. A genome‐wide marker association approach based on the Illumina BovineSNP50 BeadChip? was used to identify genomic regions affecting average daily feed intake (ADFI), average daily gain (ADG) and residual feed intake traits in a population of 1159 crossbred steers. This approach identified a region on BTA14 from 22.02 to 23.92 Mb containing several single‐nucleotide polymorphisms (SNPs) that have significant association with at least one of the traits. Two genes in this region, lysophospholipase 1 (LYPLA1) and transmembrane protein 68 (TMEM68), appeared to be logical positional and functional candidate genes. LYPLA1 deacylates ghrelin, a hormone involved in the regulation of appetite in the rat stomach, while TMEM68 is expressed in bovine rumen, abomasum, intestine and adipose tissue in cattle, and likely affects lipid biosynthetic processes. SNPs lying in or near these two genes were identified by sequencing a subset of animals with extreme phenotypes. A total of 55 SNPs were genotyped and tested for association with the same population of steers. After correction for multiple testing, five markers within 22.79–22.84 Mb, located downstream of TMEM68, and between TMEM68 and the neighbouring gene XKR4, were significant for both ADFI and ADG. Genetic markers predictive of feed intake and weight gain phenotypes in this population of cattle may be useful for the identification and selection of animals that consume less feed, although further evaluation of these markers for effects on other production traits and validation in additional populations will be required.     

Family-based analysis using a dense single-nucleotide polymorphism-based map defines genetic variation at PSORS1, the major psoriasis-susceptibility locus

Psoriasis is a common skin disorder of multifactorial origin. Genomewide scans for disease susceptibility have repeatedly demonstrated the existence of a major locus, PSORS1 (psoriasis susceptibility 1), contained within the major histocompatibility complex (MHC), on chromosome 6p21. Subsequent refinement studies have highlighted linkage disequilibrium (LD) with psoriasis, along a 150-kb segment that includes at least three candidate genes (encoding human leukocyte antigen-C [HLA-C], alpha-helix-coiled-coil-rod homologue, and corneodesmosin), each of which has been shown to harbor disease-associated alleles. However, the boundaries of the minimal PSORS1 region remain poorly defined. Moreover, interpretations of allelic association with psoriasis are compounded by limited insight of LD conservation within MHC class I interval. To address these issues, we have pursued a high-resolution genetic characterization of the PSORS1 locus. We resequenced genomic segments along a 220-kb region at chromosome 6p21 and identified a total of 119 high-frequency SNPs. Using 59 SNPs (18 coding and 41 noncoding SNPs) whose position was representative of the overall marker distribution, we genotyped a data set of 171 independently ascertained parent-affected offspring trios. Family-based association analysis of this cohort highlighted two SNPs (n.7 and n.9) respectively lying 7 and 4 kb proximal to HLA-C. These markers generated highly significant evidence of disease association (P<10-9), several orders of magnitude greater than the observed significance displayed by any other SNP that has previously been associated with disease susceptibility. This observation was replicated in a Gujarati Indian case/control data set. Haplotype-based analysis detected overtransmission of a cluster of chromosomes, which probably originated by ancestral mutation of a common disease-bearing haplotype. The only markers exclusive to the overtransmitted chromosomes are SNPs n.7 and n.9, which define a 10-kb PSORS1 core risk haplotype. These data demonstrate the power of SNP haplotype-based association analyses and provide high-resolution dissection of genetic variation across the PSORS1 interval, the major susceptibility locus for psoriasis.     

Characterization of a divergent chromosome region in the willow warbler Phylloscopus trochilus using avian genomic resources

Genome scans have made it possible to find outlier markers thought to have been influenced by divergent selection in almost any wild population. However, the lack of genomic information in nonmodel species often makes it difficult to associate these markers with certain genes or chromosome regions. Furthermore, the extent of linkage disequilibrium (LD) in the genome will determine the density of markers required to identify the genes under selection. In this study, we investigated a chromosome region in the willow warbler Phylloscopus trochilus surrounding a single marker previously identified in a genome scan. We first located the marker in the assembled genome of another species, the zebra finch Taeniopygia guttata, and amplified surrounding sequences in Fennoscandian willow warblers. Within an investigated chromosome region of 7.3 Mb as mapped to the zebra finch genome, we observed elevated genetic differentiation between a southern and a northern population across a 2.5-Mb interval comprising numerous coding genes. Within the southern and northern populations, higher values of LD were mostly found between SNPs within the same locus, but extended across distantly situated loci when the analyses were restricted to sampling sites showing intermediate allele frequencies of southern and northern alleles. Our study shows that cross-species genome information is a useful resource to obtain candidate sequences adjacent to outlier markers in nonmodel species.     

Patterns of genetic diversity and linkage disequilibrium in a highly structured Hordeum vulgare association-mapping population for the Mediterranean basin

Population structure and genome-wide linkage disequilibrium (LD) were investigated in 192 Hordeum vulgare accessions providing a comprehensive coverage of past and present barley breeding in the Mediterranean basin, using 50 nuclear microsatellite and 1,130 DArT^® markers. Both clustering and principal coordinate analyses clearly sub-divided the sample into five distinct groups centred on key ancestors and regions of origin of the germplasm. For given genetic distances, large variation in LD values was observed, ranging from closely linked markers completely at equilibrium to marker pairs at 50 cM separation still showing significant LD. Mean LD values across the whole population sample decayed below r ² of 0.15 after 3.2 cM. By assaying 1,130 genome-wide DArT^® markers, we demonstrated that, after accounting for population substructure, current genome coverage of 1 marker per 1.5 cM except for chromosome 4H with 1 marker per 3.62 cM is sufficient for whole genome association scans. We show, by identifying associations with powdery mildew that map in genomic regions known to have resistance loci, that associations can be detected in strongly stratified samples provided population structure is effectively controlled in the analysis. The population we describe is, therefore, shown to be a valuable resource, which can be used in basic and applied research in barley.     

A population-based LD map of the human chromosome 6p

The recent publication of the complete sequence of human chromosome 6 provides a platform from which to investigate genomic sequence variation. We report here a detailed linkage disequilibrium (LD) pattern map across the entire human chromosome 6p by using a set of 1152 single nucleotide polymorphisms (SNPs) in a population of 198 Singaporean Chinese, with 326 SNPs focused in the major histocompatibility complex (MHC) region. Our analysis shows some unexpectedly high segments of strong LD in a 10-Mb region that includes the extremely polymorphic and gene-rich MHC loci and many non-MHC genes. These include the telomeric peri-MHC region that harbors olfactory receptors, histones and zinc finger clusters, and the centromeric peri-MHC region that contains several unknown open reading frames. The data also help refine a human–mouse synteny break in the region between 28.6 and 29.4 Mb. The population-based LD map presented here will provide an essential resource for understanding the genomic sequence variation of chromosome 6p and LD mapping of disease genes of complex genetic traits. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users. H. Yu and J.-M. Chia should be regarded as joint first authors.     

Single nucleotide polymorphisms generated by genotyping by sequencing to characterize genome-wide diversity,linkage disequilibrium,and selective sweeps in cultivated watermelon

Background

A large single nucleotide polymorphism (SNP) dataset was used to analyze genome-wide diversity in a diverse collection of watermelon cultivars representing globally cultivated, watermelon genetic diversity. The marker density required for conducting successful association mapping depends on the extent of linkage disequilibrium (LD) within a population. Use of genotyping by sequencing reveals large numbers of SNPs that in turn generate opportunities in genome-wide association mapping and marker-assisted selection, even in crops such as watermelon for which few genomic resources are available. In this paper, we used genome-wide genetic diversity to study LD, selective sweeps, and pairwise F_ST distributions among worldwide cultivated watermelons to track signals of domestication.

Results

We examined 183 Citrullus lanatus var. lanatus accessions representing domesticated watermelon and generated a set of 11,485 SNP markers using genotyping by sequencing. With a diverse panel of worldwide cultivated watermelons, we identified a set of 5,254 SNPs with a minor allele frequency of ≥ 0.05, distributed across the genome. All ancestries were traced to Africa and an admixture of various ancestries constituted secondary gene pools across various continents. A sliding window analysis using pairwise F_ST values was used to resolve selective sweeps. We identified strong selection on chromosomes 3 and 9 that might have contributed to the domestication process. Pairwise analysis of adjacent SNPs within a chromosome as well as within a haplotype allowed us to estimate genome-wide LD decay. LD was also detected within individual genes on various chromosomes. Principal component and ancestry analyses were used to account for population structure in a genome-wide association study. We further mapped important genes for soluble solid content using a mixed linear model.

Conclusions

Information concerning the SNP resources, population structure, and LD developed in this study will help in identifying agronomically important candidate genes from the genomic regions underlying selection and for mapping quantitative trait loci using a genome-wide association study in sweet watermelon.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-767) contains supplementary material, which is available to authorized users.     

A genome‐wide association study for the incidence of persistent bovine viral diarrhea virus infection in cattle

Bovine viral diarrhea viruses (BVDV) comprise a diverse group of viruses that cause disease in cattle. BVDV may establish both transient and persistent infections depending on the developmental stage of the animal at exposure. The objective was to determine whether genomic regions harboring single nucleotide polymorphisms (SNPs) could be associated with the presence or absence of persistent BVDV infection. A genome‐wide association approach based on 777 000 SNP markers was used. Samples of animals identified as positive (n = 1200) or negative (n = 1200) for the presence of BVDV in skin samples (n = 1200) were used. DNA samples were combined in 24 pools (100 animals per pool). One SNP, significant at the 5 percent genome‐wide level (P = 9.41 × 10^?8), was detected on chromosome 14, located at position 80 675 176 bp. Fifteen SNPs, residing on chromosomes 1, 2, 6, 8, 10, 15 and 18, were moderately associated (P < 1 × 10^?5) with persistent BVDV infection. Results show that genes harboring or neighboring significant SNPs are involved in leucopenia, signal transduction, RNA splicing and DNA methylation processes.     

Meta-analysis of two genome-wide association studies of bovine paratuberculosis

Background

Bovine paratuberculosis (ParaTB) also known as Johne''s disease, is a contagious fatal disease resulting from infection by Mycobacterium avium subspecies paratuberculosis (MAP). Previous studies have identified loci associated with ParaTB using different measurements to define cases and controls. The objective of this study was to combine the data from two recent studies to identify genetic loci associated with MAP tissue infection and humoral immune response, defined by MAP ELISA-positive cattle, by comparing cases and control animals for one or both measures of infection.

Methodology/Principal Findings

The two populations used for the association analyses were a cohort of MAP tissue infected animals and control Holstein cows from the USA and the second cohort composed of ELISA-positive and ELISA-negative Holstein cows from Italy. Altogether 1190 cattle were genotyped with the Illumina BovineSNP50 BeadChip. SNP markers were removed if the minor allele frequency <0.01 or genotyping failure was >5%. Animals were removed with >5% genotyping failure. Whole genome association analyses were conducted with the GRAMMAR-CG method using two different definitions of control populations.

Conclusion/Significance

The analyses identified several loci (P<5 e-05) associated with ParaTB, defined by positive ELISA and presence of bacteria in tissue compared to ELISA and tissue negative animals, on chromosomes 1, 12 and 15 and one unassigned SNP. These results confirmed associations on chromosome 12 and the unassigned SNP with ParaTB which had been found in the Italian population alone. Furthermore, several additional genomic regions were found associated with ParaTB when ELISA and tissue positive animals were compared with tissue negative samples. These loci were on chromosomes 1, 6, 7, 13, 16, 21,23 and 25 (P<5 e-05). The results clearly indicate the importance of the phenotype definition when seeking to identify markers associated with different disease responses.     

Extent and consistency of linkage disequilibrium and identification of DNA markers for production and egg quality traits in commercial layer chicken populations

Background

The genome sequence and a high-density SNP map are now available for the chicken and can be used to identify genetic markers for use in marker-assisted selection (MAS). Effective MAS requires high linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), and sustained marker-QTL LD over generations. This study used data from a 3,000 SNP panel to assess the level and consistency of LD between single nucleotide polymorphisms (SNPs) over consecutive years in two egg-layer chicken lines, and analyzed one line by two methods (SNP-wise association and genome-wise Bayesian analysis) to identify markers associated with egg-quality and egg-production phenotypes.

Results

The LD between markers pairs was high at short distances (r² > 0.2 at < 2 Mb) and remained high after one generation (correlations of 0.80 to 0.92 at < 5 Mb) in both lines. Single- and 3-SNP regression analyses using a mixed model with SNP as fixed effect resulted in 159 and 76 significant tests (P < 0.01), respectively, across 12 traits. A Bayesian analysis called BayesB, that fits all SNPs simultaneously as random effects and uses model averaging procedures, identified 33 SNPs that were included in the model >20% of the time (φ > 0.2) and an additional ten 3-SNP windows that had a sum of φ greater than 0.35. Generally, SNPs included in the Bayesian model also had a small P-value in the 1-SNP analyses.

Conclusion

High LD correlations between markers at short distances across two generations indicate that such markers will retain high LD with linked QTL and be effective for MAS. The different association analysis methods used provided consistent results. Multiple single SNPs and 3-SNP windows were significantly associated with egg-related traits, providing genomic positions of QTL that can be useful for both MAS and to identify causal mutations.

     

Insights into Colon Cancer Etiology via a Regularized Approach to Gene Set Analysis of GWAS Data

Genome-wide association studies (GWAS) have successfully identified susceptibility loci from marginal association analysis of SNPs. Valuable insight into genetic variation underlying complex diseases will likely be gained by considering functionally related sets of genes simultaneously. One approach is to further develop gene set enrichment analysis methods, which are initiated in gene expression studies, to account for the distinctive features of GWAS data. These features include the large number of SNPs per gene, the modest and sparse SNP associations, and the additional information provided by linkage disequilibrium (LD) patterns within genes. We propose a “gene set ridge regression in association studies (GRASS)” algorithm. GRASS summarizes the genetic structure for each gene as eigenSNPs and uses a novel form of regularized regression technique, termed group ridge regression, to select representative eigenSNPs for each gene and assess their joint association with disease risk. Compared with existing methods, the proposed algorithm greatly reduces the high dimensionality of GWAS data while still accounting for multiple hits and/or LD in the same gene. We show by simulation that this algorithm performs well in situations in which there are a large number of predictors compared to sample size. We applied the GRASS algorithm to a genome-wide association study of colon cancer and identified nicotinate and nicotinamide metabolism and transforming growth factor beta signaling as the top two significantly enriched pathways. Elucidating the role of variation in these pathways may enhance our understanding of colon cancer etiology.