High-density SNP Genotyping Research Articles

A genome-wide association study for genetic susceptibility to Mycobacterium bovis infection in dairy cattle identifies a susceptibility QTL on chromosome 23.

BackgroundBovine tuberculosis (bTB) infection in cattle is a significant economic concern in many countries, with annual costs to the UK and Irish governments of approximately €190 million and €63 million, respectively, for bTB control. The existence of host additive and non-additive genetic components to bTB susceptibility has been established.MethodsTwo approaches i.e. single-SNP (single nucleotide polymorphism) regression and a Bayesian method were applied to genome-wide association studies (GWAS) using high-density SNP genotypes (n = 597,144 SNPs) from 841 dairy artificial insemination (AI) sires. Deregressed estimated breeding values for bTB susceptibility were used as the quantitative dependent variable. Network analysis was performed using the quantitative trait loci (QTL) that were identified as significant in the single-SNP regression and Bayesian analyses separately. In addition, an identity-by-descent analysis was performed on a subset of the most prolific sires in the dataset that showed contrasting prevalences of bTB infection in daughters.ResultsA significant QTL region was identified on BTA23 (P value >1 × 10−5, Bayes factor >10) across all analyses. Sires with the minor allele (minor allele frequency = 0.136) for this QTL on BTA23 had estimated breeding values that conferred a greater susceptibility to bTB infection than those that were homozygous for the major allele. Imputation of the regions that flank this QTL on BTA23 to full sequence indicated that the most significant associations were located within introns of the FKBP5 gene.ConclusionsA genomic region on BTA23 that is strongly associated with host susceptibility to bTB infection was identified. This region contained FKBP5, a gene involved in the TNFα/NFκ-B signalling pathway, which is a major biological pathway associated with immune response. Although there is no study that validates this region in the literature, our approach represents one of the most powerful studies for the analysis of bTB susceptibility to date.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0197-x) contains supplementary material, which is available to authorized users.

GBS-SNP-CROP: a reference-optional pipeline for SNP discovery and plant germplasm characterization using variable length, paired-end genotyping-by-sequencing data.

BackgroundWith its simple library preparation and robust approach to genome reduction, genotyping-by-sequencing (GBS) is a flexible and cost-effective strategy for SNP discovery and genotyping, provided an appropriate reference genome is available. For resource-limited curation, research, and breeding programs of underutilized plant genetic resources, however, even low-depth references may not be within reach, despite declining sequencing costs. Such programs would find value in an open-source bioinformatics pipeline that can maximize GBS data usage and perform high-density SNP genotyping in the absence of a reference.ResultsThe GBS SNP-Calling Reference Optional Pipeline (GBS-SNP-CROP) developed and presented here adopts a clustering strategy to build a population-tailored “Mock Reference” from the same GBS data used for downstream SNP calling and genotyping. Designed for libraries of paired-end (PE) reads, GBS-SNP-CROP maximizes data usage by eliminating unnecessary data culling due to imposed read-length uniformity requirements. Using 150 bp PE reads from a GBS library of 48 accessions of tetraploid kiwiberry (Actinidia arguta), GBS-SNP-CROP yielded on average three times as many SNPs as TASSEL-GBS analyses (32 and 64 bp tag lengths) and over 18 times as many as TASSEL-UNEAK, with fewer genotyping errors in all cases, as evidenced by comparing the genotypic characterizations of biological replicates. Using the published reference genome of a related diploid species (A. chinensis), the reference-based version of GBS-SNP-CROP behaved similarly to TASSEL-GBS in terms of the number of SNPs called but had an improved read depth distribution and fewer genotyping errors. Our results also indicate that the sets of SNPs detected by the different pipelines above are largely orthogonal to one another; thus GBS-SNP-CROP may be used to augment the results of alternative analyses, whether or not a reference is available.ConclusionsBy achieving high-density SNP genotyping in populations for which no reference genome is available, GBS-SNP-CROP is worth consideration by curators, researchers, and breeders of under-researched plant genetic resources. In cases where a reference is available, especially if from a related species or when the target population is particularly diverse, GBS-SNP-CROP may complement other reference-based pipelines by extracting more information per sequencing dollar spent. The current version of GBS-SNP-CROP is available at https://github.com/halelab/GBS-SNP-CROP.gitElectronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-0879-y) contains supplementary material, which is available to authorized users.

GENOME-WIDE MAPPING OF COPY NUMBER VARIATIONS IN COMMERCIAL HYBRID PIGS USING A HIGH-DENSITY SNP GENOTYPING ARRAY.

Copy number variations (CNVs) are important forms of structural variation in human and animals and can be considered as a major genetic component of phenotypic diversity. Here we used the Illumina PorcineSNP60 BeadChip V2 and a DLY [Duroc x (Large White x Landrace)] commercial hybrid population to identify 272 CNVs belonging to 165 CNV regions (CNVRs), of which 66 are new. As CNVRs are specific to origin of population, our DLY-specific data is an important complementary to the existing CNV map in the pig genome. Eight CNVRs were selected. for validation by quantitative real-time PCR (qRT-PCR) and the accurate rate was high (87.25%). Gene function analysis suggested that a common CNVR may play an important role in multiple traits, including growth rate and carcass quality.

Genome-wide mapping of copy number variations in commercial hybrid pigs using a high-density SNP genotyping array

Genome-wide mapping of copy number variations in commercial hybrid pigs using a high-density SNP genotyping array

Rare Variants in Transcript and Potential Regulatory Regions Explain a Small Percentage of the Missing Heritability of Complex Traits in Cattle.

The proportion of genetic variation in complex traits explained by rare variants is a key question for genomic prediction, and for identifying the basis of “missing heritability”–the proportion of additive genetic variation not captured by common variants on SNP arrays. Sequence variants in transcript and regulatory regions from 429 sequenced animals were used to impute high density SNP genotypes of 3311 Holstein sires to sequence. There were 675,062 common variants (MAF>0.05), 102,549 uncommon variants (0.01<MAF<0.05), and 83,856 rare variants (MAF<0.01). We describe a novel method for estimating the proportion of the rare variants that are sequencing errors using parent-progeny duos. We then used mixed model methodology to estimate the proportion of variance captured by these different classes of variants for fat, milk and protein yields, as well as for fertility. Common sequence variants captured 83%, 77%, 76% and 84% of the total genetic variance for fat, milk, and protein yields and fertility, respectively. This was between 2 and 5% more variance than that captured from 600k SNPs on a high density chip, although the difference was not significant. Rare variants captured 3%, 0%, 1% and 14% of the genetic variance for fat, milk and protein yields, and fertility respectively, whereas pedigree explained the remaining amount of genetic variance (none for fertility). The proportion of variation explained by rare variants is likely to be under-estimated due to reduced accuracies of imputation for this class of variants. Using common sequence variants slightly improved accuracy of genomic predictions for fat and milk yield, compared to high density SNP array genotypes. However, including rare variants from transcript regions did not increase the accuracy of genomic predictions. These results suggest that rare variants recover a small percentage of the missing heritability for complex traits, however very large reference sets will be required to exploit this to improve the accuracy of genomic predictions. Our results do suggest the contribution of rare variants to genetic variation may be greater for fitness traits.

Exome Sequencing in Myeloma Pedigrees Implicates RAS1 and NOTCH Signaling Are Involved in Inherited Myeloma Risk

Multiple Myeloma (MM) is a cancer of plasma cells with poor prognosis. Although, MM has been shown to be highly heritable in genealogy studies, no inherited risk-alleles have been identified. We hypothesize MM heritability is in part due to rare, germline variation that can be discovered in high-risk pedigrees.High-risk MM pedigrees were identified using the Utah Population Database which contains both genealogical and state cancer records. High-risk pedigrees were defined to have statistical excess of MM (p < 0.05). In this study we whole-exome sequenced germline DNA from 42 MM cases from high-risk pedigrees. Best practice variant calling, joint genotyping, and quality control were performed on the cases, a set of background controls from the 1000 Genome Project (1000G), and a small set of local controls (for technical artifacts), and resulted in 607,908 variants. We prioritized variants that were: 1) shared by at least 3 related MM cases, 2) absent in local controls, and 3) rare (frequency ≤ 0.01 in 1000G). This prioritization resulted in 116 variants of interest.Of the 116 variants, 3 MM cases in one high-risk pedigree shared multiple variants on chromosome 1p36.11-35.1. To formally assess whether these variants were inherited from a common founder we performed shared genome segment analysis using high-density SNP genotyping. We identified a region at 1p36.11-35.1, 8.9 Mb in length (p = 6.0 × 10-4; 22,000 simulations), providing positive evidence for segregation from a common founder.The segregating variants identified from exome sequencing in this region are in the genes CNKSR1, ARID1A, and SDC3. All three variants are individually predicted to be moderately deleterious. The variant in CNKSR1 falls in a splice region and has minor allele frequency of 0.004 in the 1000G Europeans. This variant was also observed in 3 additional cases in our sequencing set, indicating a strong enrichment of this variant in our high-risk MM cases (6/42 = 0.143). CNKSR1 is involved in the RAS1 and NOTCH signaling pathways and is a known target for cancer therapy. The variants in ARID1A and SDC3 both result in non-synonymous codon changes. ARID1A is commonly mutated across cancers and has been associated with accelerated tumor growth in hepatocellular carcinomas. SDC3 also interacts with NOTCH signaling, a pathway involved in MM growth (especially in patients with MAF translocations) and osteoclastogenesis. The variants in ARID1A and SDC3 are not carried by other cases in our sequencing set, which may indicate the combination of these variants is important to confer risk in the pedigree, or merely that the variants are hitchhikers on the segregating chromosome.Germline risk-alleles will shed light on the genetic factors involved in MM susceptibility and ultimately may provide new avenues for screening, diagnosis and treatment. Here we have identified evidence for segregating variants in a high-risk pedigree that implicate the RAS1 and NOTCH signaling pathways as involved in MM risk. Future work includes confirmation sequencing in the pedigree and a broader set of MM cases, and functional follow-up of the variants and their role in disruption of the genes and pathways. DisclosuresNo relevant conflicts of interest to declare.

Comparison of linkage disequilibrium levels in Iranian indigenous cattle using whole genome SNPs data.

BackgroundKnowledge of linkage disequilibrium (LD) levels among different populations can be used to detect genetic diversity and to investigate the historical changes in population sizes. Availability of large numbers of SNP through new sequencing technologies has provided opportunities for extensive researches in quantifying LD patterns in cattle breeds. The aim of this study was to compare the extent of linkage disequilibrium among Iranian cattle breeds using high density SNP genotyping data.ResultsA total of 70 samples, representing seven Iranian indigenous cattle breeds, were genotyped for 777962 SNPs. The average values of LD based on the r2 criterion were computed by grouping all syntenic SNP pairwises for inter-marker distances from 0 Kb up to 1 Mb using three distance sets. Average r2 above 0.3 was observed at distances less than 30 Kb for Sistani and Kermani, 20 Kb for Najdi, Taleshi, Kurdi and Sarabi, and 10 Kb for Mazandarani. The LD levels were considerably different among the Iranian cattle breeds and the difference in LD extent was more detectable between the studied breeds at longer distances. Lower level of LD was observed for Mazandarani breed as compared to other breeds indicating larger ancestral population size in this breed. Kermani breed continued to have more slowly LD decay than all of the other breeds after 3 Kb distances. More slowly LD decay was observed in Kurdi and Sarabi breeds at larger distances (>100 Kb) showing that population decline has been more intense in more recent generations for these populations.ConclusionsA wide genetic diversity and different historical background were well reflected in the LD levels among Iranian cattle breeds. More LD fluctuation was observed in the shorter distances (less than 10 Kb) in different cattle populations. Despite of the sample size effects, High LD levels found in this study were in accordance with the presence of inbreeding and population decline in Iranian cattle breeds.

Inbreeding and purging at the genomic Level: the Chillingham cattle reveal extensive, non-random SNP heterozygosity.

Local breeds of livestock are of conservation significance as components of global biodiversity and as reservoirs of genetic variation relevant to the future sustainability of agriculture. One such rare historic breed, the Chillingham cattle of northern England, has a 350-year history of isolation and inbreeding yet shows no diminution of viability or fertility. The Chillingham cattle have not been subjected to selective breeding. It has been suggested previously that the herd has minimal genetic variation. In this study, high-density SNP genotyping with the 777K SNP chip showed that 9.1% of loci on the chip are polymorphic in the herd, compared with 62-90% seen in commercial cattle breeds. Instead of being homogeneously distributed along the genome, these loci are clustered at specific chromosomal locations. A high proportion of the Chillingham individuals examined were heterozygous at many of these polymorphic loci, suggesting that some loci are under balancing selection. Some of these frequently heterozygous loci have been implicated as sites of recessive lethal mutations in cattle. Linkage disequilibrium equal or close to 100% was found to span up to 1350 kb, and LD was above r(2) = 0.25 up to more than 5000 kb. This strong LD is consistent with the lack of polymorphic loci in the herd. The heterozygous regions in the Chillingham cattle may be the locations of genes relevant to fitness or survival, which may help elucidate the biology of local adaptation in traditional breeds and facilitate selection for such traits in commercial cattle.

XSim: Simulation of Descendants from Ancestors with Sequence Data.

Real or imputed high-density SNP genotypes are routinely used for genomic prediction and genome-wide association studies. Many researchers are moving toward the use of actual or imputed next-generation sequence data in whole-genome analyses. Simulation studies are useful to mimic complex scenarios and test different analytical methods. We have developed the software tool XSim to efficiently simulate sequence data in descendants in arbitrary pedigrees. In this software, a strategy to drop-down origins and positions of chromosomal segments rather than every allele state is implemented to simulate sequence data and to accommodate complicated pedigree structures across multiple generations. Both C++ and Julia versions of XSim have been developed.

Genetic-geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping.

Key messagePublically available SNP array increases the marker density for genotyping of forage crop,Lolium perenne. Applied to 90 European ecotypes composed of 716 individuals identifies a significant genetic–geographic correlation. Grassland ecosystems are ubiquitous across temperate and tropical regions, totalling 37 % of the terrestrial land cover of the planet, and thus represent a global resource for understanding local adaptations to environment. However, genomic resources for grass species (outside cereals) are relatively poor. The advent of next-generation DNA sequencing and high-density SNP genotyping platforms enables the development of dense marker assays for population genetics analyses and genome-wide association studies. A high-density SNP marker resource (Illumina Infinium assay) for perennial ryegrass (Lolium perenne) was created and validated in a broad ecotype collection of 716 individuals sampled from 90 sites across Europe. Genetic diversity within and between populations was assessed. A strong correlation of geographic origin to genetic structure was found using principal component analysis, with significant correlation to longitude and latitude (P < 0.001). The potential of this array as a resource for studies of germplasm diversity and identifying traits underpinning adaptive variation is highlighted.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-015-2556-3) contains supplementary material, which is available to authorized users.

Genomics in aquaculture to better understand species biology and accelerate genetic progress.

Genomics in aquaculture to better understand species biology and accelerate genetic progress.

Assessment of autozygosity in Nellore cows (Bos indicus) through high-density SNP genotypes.

The use of relatively low numbers of sires in cattle breeding programs, particularly on those for carcass and weight traits in Nellore beef cattle (Bos indicus) in Brazil, has always raised concerns about inbreeding, which affects conservation of genetic resources and sustainability of this breed. Here, we investigated the distribution of autozygosity levels based on runs of homozygosity (ROH) in a sample of 1,278 Nellore cows, genotyped for over 777,000 SNPs. We found ROH segments larger than 10 Mb in over 70% of the samples, representing signatures most likely related to the recent massive use of few sires. However, the average genome coverage by ROH (>1 Mb) was lower than previously reported for other cattle breeds (4.58%). In spite of 99.98% of the SNPs being included within a ROH in at least one individual, only 19.37% of the markers were encompassed by common ROH, suggesting that the ongoing selection for weight, carcass and reproductive traits in this population is too recent to have produced selection signatures in the form of ROH. Three short-range highly prevalent ROH autosomal hotspots (occurring in over 50% of the samples) were observed, indicating candidate regions most likely under selection since before the foundation of Brazilian Nellore cattle. The putative signatures of selection on chromosomes 4, 7, and 12 may be involved in resistance to infectious diseases and fertility, and should be subject of future investigation.

Genome-wide identification of copy number variations in Holstein cattle from Baja California, Mexico, using high-density SNP genotyping arrays.

Copy number variations (CNVs) are an important source of genomic structural variation, and can be used as markers to investigate phenotypic and economic traits. CNVs also have functional effects on gene expression and can contribute to disease susceptibility in mammals. Currently, single nucleotide polymorphism genotyping arrays (SNP chips) are the technology of choice for identifying CNV variations. Microarray technologies have recently been used to study the bovine genome. The objective of the present study was to develop CNVs in Holstein cows from the Northwest of Mexico using the Affymetrix Axiom Genome-Wide BOS 1 Array, which assays 648,315 SNPs and provides a wide coverage for genome-wide studies. We applied the two most widely used algorithms for the discovery of CNVs (PennCNV and QuantiSNP) and found 56 CNV regions (CNVRs) representing 0.33% of the bovine genome (8.46 Mb). These CNVRs ranged from 1.5 to 970.8 kb with an average length of 151 kb. They involved 103 genes and showed a 28% overlap with CNVRs already reported. Of the 56 CNVRs found, 20 were novel. In this study we present the first genomic analysis of CNVs in Mexican cattle using high-density SNP data. Our results provide a new reference basis for future genomic variation and association studies between CNVs and phenotypes, especially in Mexican cattle.

Insights into the origin of rare haplogroup C3* Y chromosomes in South America from high-density autosomal SNP genotyping

The colonization of Americas is thought to have occurred 15–20 thousand years ago (Kya), with little or no subsequent migration into South America until the European expansions beginning 0.5Kya. Recently, however, haplogroup C3* Y chromosomes were discovered in two nearby Native American populations from Ecuador. Since this haplogroup is otherwise nearly absent from the Americas but is common in East Asia, and an archaeological link between Ecuador and Japan is known from 6Kya, an additional migration 6Kya was suggested. Here, we have generated high-density autosomal SNP genotypes from the Ecuadorian populations and compared them with genotypes from East Asia and elsewhere to evaluate three hypotheses: a recent migration from Japan, a single pulse of migration from Japan 6Kya, and no migration after the First Americans. First, using forward-time simulations and an appropriate demographic model, we investigated our power to detect both ancient and recent gene flow at different levels. Second, we analyzed 207,321 single nucleotide polymorphisms from 16 Ecuadorian individuals, comparing them with populations from the HGDP panel using descriptive and formal tests for admixture. Our simulations revealed good power to detect recent admixture, and that ≥5% admixture 6Kya ago could be detected. However, in the experimental data we saw no evidence of gene flow from Japan to Ecuador. In summary, we can exclude recent migration and probably admixture 6Kya as the source of the C3* Y chromosomes in Ecuador, and thus suggest that they represent a rare founding lineage lost by drift elsewhere.

A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array.

BackgroundHigh density genotyping data are indispensable for genomic analyses of complex traits in animal and crop species. Maize is one of the most important crop plants worldwide, however a high density SNP genotyping array for analysis of its large and highly dynamic genome was not available so far.ResultsWe developed a high density maize SNP array composed of 616,201 variants (SNPs and small indels). Initially, 57 M variants were discovered by sequencing 30 representative temperate maize lines and then stringently filtered for sequence quality scores and predicted conversion performance on the array resulting in the selection of 1.2 M polymorphic variants assayed on two screening arrays. To identify high-confidence variants, 285 DNA samples from a broad genetic diversity panel of worldwide maize lines including the samples used for sequencing, important founder lines for European maize breeding, hybrids, and proprietary samples with European, US, semi-tropical, and tropical origin were used for experimental validation. We selected 616 k variants according to their performance during validation, support of genotype calls through sequencing data, and physical distribution for further analysis and for the design of the commercially available Affymetrix® Axiom® Maize Genotyping Array. This array is composed of 609,442 SNPs and 6,759 indels. Among these are 116,224 variants in coding regions and 45,655 SNPs of the Illumina® MaizeSNP50 BeadChip for study comparison. In a subset of 45,974 variants, apart from the target SNP additional off-target variants are detected, which show only a minor bias towards intermediate allele frequencies. We performed principal coordinate and admixture analyses to determine the ability of the array to detect and resolve population structure and investigated the extent of LD within a worldwide validation panel.ConclusionsThe high density Affymetrix® Axiom® Maize Genotyping Array is optimized for European and American temperate maize and was developed based on a diverse sample panel by applying stringent quality filter criteria to ensure its suitability for a broad range of applications. With 600 k variants it is the largest currently publically available genotyping array in crop species.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-823) contains supplementary material, which is available to authorized users.

DsRNA binding protein PACT/RAX in gene silencing, development and diseases.

PACT (Protein kinase, interferon-inducible double stranded RNA dependent activator) and its murine ortholog RAX (PKR-associated protein X) were originally identified as a protein activator for the dsRNA-dependent, interferon-inducible protein kinase (PKR). Endogenous PACT/RAX activates PKR in response to diverse stress signals such as serum starvation, and peroxide or arsenite treatment. PACT/RAX heterodimerized with PKR and activated it with its third motif in the absence of dsRNA. The activation of PKR leads to enhanced eIF2α phosphorylation followed by apoptosis or inhibition of growth. Besides the role of activating PKR, PACT is associated with a ~500 kDa complex that contains Dicer, hAgo2, and TRBP (TAR RNA binding protein) and it associates with Dicer to facilitate the production of small interfering RNA. PACT/RAX plays an important role in diverse physiological and pathological processes. Pact-/- mice exhibit notable developmental abnormalities including microtia, with craniofacial ear, and hearing defects. Pact-/- mice had smaller body sizes and fertility defects, both of which were caused by defective pituitary functions. It was found that dRAX disrupted fly embryos homozygous, displayed highly abnormal commissural axon structure of the central nervous system, and 70% of the flies homozygous for the mutant allele died prior to adulthood. Using high density SNP genotyping arrays, it was found that a mutation in PRKRA (the PACT/RAX gene) is the causative genetic mutation in DYT16, a novel autosomal recessive dystonia-parkinsonism syndrome in Brazilian patients.

The USDA barley core collection: genetic diversity, population structure, and potential for genome-wide association studies.

New sources of genetic diversity must be incorporated into plant breeding programs if they are to continue increasing grain yield and quality, and tolerance to abiotic and biotic stresses. Germplasm collections provide a source of genetic and phenotypic diversity, but characterization of these resources is required to increase their utility for breeding programs. We used a barley SNP iSelect platform with 7,842 SNPs to genotype 2,417 barley accessions sampled from the USDA National Small Grains Collection of 33,176 accessions. Most of the accessions in this core collection are categorized as landraces or cultivars/breeding lines and were obtained from more than 100 countries. Both STRUCTURE and principal component analysis identified five major subpopulations within the core collection, mainly differentiated by geographical origin and spike row number (an inflorescence architecture trait). Different patterns of linkage disequilibrium (LD) were found across the barley genome and many regions of high LD contained traits involved in domestication and breeding selection. The genotype data were used to define ‘mini-core’ sets of accessions capturing the majority of the allelic diversity present in the core collection. These ‘mini-core’ sets can be used for evaluating traits that are difficult or expensive to score. Genome-wide association studies (GWAS) of ‘hull cover’, ‘spike row number’, and ‘heading date’ demonstrate the utility of the core collection for locating genetic factors determining important phenotypes. The GWAS results were referenced to a new barley consensus map containing 5,665 SNPs. Our results demonstrate that GWAS and high-density SNP genotyping are effective tools for plant breeders interested in accessing genetic diversity in large germplasm collections.

Independent Polled Mutations Leading to Complex Gene Expression Differences in Cattle

The molecular regulation of horn growth in ruminants is still poorly understood. To investigate this process, we collected 1019 hornless (polled) animals from different cattle breeds. High-density SNP genotyping confirmed the presence of two different polled associated haplotypes in Simmental and Holstein cattle co-localized on BTA 1. We refined the critical region of the Simmental polled mutation to 212 kb and identified an overlapping region of 932 kb containing the Holstein polled mutation. Subsequently, whole genome sequencing of polled Simmental and Holstein cows was used to determine polled associated genomic variants. By genotyping larger cohorts of animals with known horn status we found a single perfectly associated insertion/deletion variant in Simmental and other beef cattle confirming the recently published possible Celtic polled mutation. We identified a total of 182 sequence variants as candidate mutations for polledness in Holstein cattle, including an 80 kb genomic duplication and three SNPs reported before. For the first time we showed that hornless cattle with scurs are obligate heterozygous for one of the polled mutations. This is in contrast to published complex inheritance models for the bovine scurs phenotype. Studying differential expression of the annotated genes and loci within the mapped region on BTA 1 revealed a locus (LOC100848215), known in cow and buffalo only, which is higher expressed in fetal tissue of wildtype horn buds compared to tissue of polled fetuses. This implicates that the presence of this long noncoding RNA is a prerequisite for horn bud formation. In addition, both transcripts associated with polledness in goat and sheep (FOXL2 and RXFP2), show an overexpression in horn buds confirming their importance during horn development in cattle.

Susceptibility loci revealed for bovine respiratory disease complex in pre-weaned holstein calves.

BackgroundBovine respiratory disease complex (BRDC) is an infectious disease of cattle that is caused by a combination of viral and/or bacterial pathogens. Selection for cattle with reduced susceptibility to respiratory disease would provide a permanent tool for reducing the prevalence of BRDC. The objective of this study was to identify BRDC susceptibility loci in pre-weaned Holstein calves as a prerequisite to using genetic improvement as a tool for decreasing the prevalence of BRDC. High density SNP genotyping with the Illumina BovineHD BeadChip was conducted on 1257 male and 757 female Holstein calves from California (CA), and 767 calves identified as female from New Mexico (NM). Of these, 1382 were classified as BRDC cases, and 1396 were classified as controls, with all phenotypes assigned using the McGuirk health scoring system. During the acquisition of blood for DNA isolation, two deep pharyngeal and one mid-nasal diagnostic swab were obtained from each calf for the identification of bacterial and viral pathogens. Genome-wide association analyses were conducted using four analytical approaches (EIGENSTRAT, EMMAX-GRM, GBLUP and FvR). The most strongly associated SNPs from each individual analysis were ranked and evaluated for concordance. The heritability of susceptibility to BRDC in pre-weaned Holstein calves was estimated.ResultsThe four statistical approaches produced highly concordant results for 373 top ranked SNPs that defined 126 chromosomal regions for the CA population. Similarly, in NM, 370 SNPs defined 138 genomic regions that were identified by all four approaches. When the two populations were combined (i.e., CA + NM) and analyzed, 324 SNPs defined 116 genomic regions that were associated with BRDC across all analytical methods. Heritability estimates for BRDC were 21% for both CA and NM as individual populations, but declined to 13% when the populations were combined.ConclusionsFour analytical approaches utilizing both single and multi-marker association methods revealed common genomic regions associated with BRDC susceptibility that can be further characterized and used for genomic selection. Moderate heritability estimates were observed for BRDC susceptibility in pre-weaned Holstein calves, thereby supporting the application of genomic selection to reduce the prevalence of BRDC in U.S. Holsteins.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-1164) contains supplementary material, which is available to authorized users.

Analyzing copy number variation using SNP array data: protocols for calling CNV and association tests.

High-density SNP genotyping technology provides a low-cost, effective tool for conducting Genome Wide Association (GWA) studies. The wide adoption of GWA studies has indeed led to discoveries of disease- or trait-associated SNPs, some of which were subsequently shown to be causal. However, the nearly universal shortcoming of many GWA studies--missing heritability--has prompted great interest in searching for other types of genetic variation, such as copy number variation (CNV). Certain CNVs have been reported to alter disease susceptibility. Algorithms and tools have been developed to identify CNVs using SNP array hybridization intensity data. Such an approach provides an additional source of data with almost no extra cost. In this unit, we demonstrate the steps for calling CNVs from Illumina SNP array data using PennCNV and performing association analysis using R and PLINK.