High-density Single Nucleotide Polymorphism Chips Research Articles

Design and validation of high-density SNP array of goats and population stratification of Indian goat breeds

Goats are the supporting pillars of rural economy contributing significantly to meat and milk production in India. It is a species targeted for fulfilling the interdependent goals of poverty reduction and creation of employment for supporting the rural income. The increased demand for goat products necessitates their genetic characterization and improvement to augment the production of native breeds. Bi-allelic, genome wide, densely placed single nucleotide polymorphism (SNP) markers are most suitable for this purpose. This paper describes the design and validation of an Affymetrix Axiom-based high-density (HD) SNP chip for goats. The array was designed using a panel of 225 samples from 15 diverse goat breeds of India. In total, more than 38 million high quality SNPs were subjected to stringent filtering and 626,975 SNPs were finally tiled on the array. The average coverage of SNPs in our chip is one SNP per four kilobase (kb), providing a denser coverage of the goat genome than previously available arrays. The HD chip (Axiom_Cahi) was validated by genotyping 443 samples from 26 indigenous goat breeds/populations. The results revealed 95.83% markers to be highly informative and polymorphic in Indian goats. Multivariate analysis indicated population structuring, as 15 breeds could be segregated using the designed array. Phylogenetic analysis suggested stratification of breeds by geographic proximity. This HD SNP chip for goats is a valuable resource for genomic selection, genome wide association as well as population genetic studies in goats.

Restriction site-associated DNA sequencing technologies as an alternative to low-density SNP chips for genomic selection: a simulation study in layer chickens

BackgroundTo reduce the cost of genomic selection, a low-density (LD) single nucleotide polymorphism (SNP) chip can be used in combination with imputation for genotyping selection candidates instead of using a high-density (HD) SNP chip. Next-generation sequencing (NGS) techniques have been increasingly used in livestock species but remain expensive for routine use for genomic selection. An alternative and cost-efficient solution is to use restriction site-associated DNA sequencing (RADseq) techniques to sequence only a fraction of the genome using restriction enzymes. From this perspective, use of RADseq techniques followed by an imputation step on HD chip as alternatives to LD chips for genomic selection was studied in a pure layer line.ResultsGenome reduction and sequencing fragments were identified on reference genome using four restriction enzymes (EcoRI, TaqI, AvaII and PstI) and a double-digest RADseq (ddRADseq) method (TaqI-PstI). The SNPs contained in these fragments were detected from the 20X sequence data of the individuals in our population. Imputation accuracy on HD chip with these genotypes was assessed as the mean correlation between true and imputed genotypes. Several production traits were evaluated using single-step GBLUP methodology. The impact of imputation errors on the ranking of the selection candidates was assessed by comparing a genomic evaluation based on ancestry using true HD or imputed HD genotyping. The relative accuracy of genomic estimated breeding values (GEBVs) was investigated by considering the GEBVs estimated on offspring as a reference. With AvaII or PstI and ddRADseq with TaqI and PstI, more than 10 K SNPs were detected in common with the HD SNP chip, resulting in an imputation accuracy greater than 0.97. The impact of imputation errors on genomic evaluation of the breeders was reduced, with a Spearman correlation greater than 0.99. Finally, the relative accuracy of GEBVs was equivalent.ConclusionsRADseq approaches can be interesting alternatives to low-density SNP chips for genomic selection. With more than 10 K SNPs in common with the SNPs of the HD SNP chip, good imputation and genomic evaluation results can be obtained. However, with real data, heterogeneity between individuals with missing data must be considered.

Interest of using imputation for genomic evaluation in layer chicken

With the availability of the 600K Affymetrix Axiom high-density (HD) single nucleotide polymorphism (SNP) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-density SNP chip, at a lower price, and to impute all missing markers. But to routinely implement this solution, the impact of imputation on genomic evaluation accuracy must be studied. It is also interesting to study the consequences of the use of low-density SNP chips in genomic evaluation accuracy. In this perspective, the interest of using imputation in genomic selection was studied in a pure layer line. Two low-density SNP chip designs were compared: an equidistant methodology and a methodology based on linkage disequilibrium. Egg weight, egg shell color, egg shell strength, and albumen height were evaluated with single-step genomic best linear unbiased prediction methodology. The impact of imputation errors or the absence of imputation on the ranking of the male selection candidates was assessed with a genomic evaluation based on ancestry. Thus, genomic estimated breeding values (GEBV) obtained with imputed HD genotypes or low-density genotypes were compared with GEBV obtained with the HD SNP chip. The relative accuracy of GEBV was also investigated by considering as reference GEBV estimated on the offspring. A limited reordering of the breeders, selected on a multitrait index, was observed. Spearman correlations between GEBV on HD genotypes and GEBV on low-density genotypes (with or without imputation) were always higher than 0.94 with more than 3K SNP. For the genetically closer, top 150 individuals for a specific trait, with imputation, the reordering was reduced with correlation higher than 0.94 with more than 3K SNP. Without imputation, the correlations remained lower than 0.85 with less than 3K and 16K SNP for equidistant and linkage disequilibrium methodology, respectively. The differences in GEBV correlations between both methodologies were never significant. The conclusions were the same for all studied traits.

Genetic diversity and divergence among Korean cattle breeds assessed using a BovineHD single-nucleotide polymorphism chip.

ObjectiveIn Korea, there are three main cattle breeds, which are distinguished by coat color: Brown Hanwoo (BH), Brindle Hanwoo (BRH), and Jeju Black (JB). In this study, we sought to compare the genetic diversity and divergence among there Korean cattle breeds using a BovineHD chip genotyping array.MethodsSample data were collected from 168 cattle in three populations of BH (48 cattle), BRH (96 cattle), and JB (24 cattle). The single-nucleotide polymorphism (SNP) genotyping was performed using the Illumina BovineHD SNP 777K Bead chip.ResultsHeterozygosity, used as a measure of within-breed genetic diversity, was higher in BH (0.293) and BRH (0.296) than in JB (0.266). Linkage disequilibrium decay was more rapid in BH and BRH than in JB, reaching an average r2 value of 0.2 before 26 kb in BH and BRH, whereas the corresponding value was reached before 32 kb in JB. Intra-population, inter-population, and Fst analyses were used to identify candidate signatures of positive selection in the genome of a domestic Korean cattle population and 48, 11, and 11 loci were detected in the genomic region of the BRH breed, respectively. A Neighbor-Joining phylogenetic tree showed two main groups: a group comprising BH and BRH on one side and a group containing JB on the other. The runs of homozygosity analysis between Korean breeds indicated that the BRH and JB breeds have high inbreeding within breeds compared with BH. An analysis of differentiation based on a high-density SNP chip showed differences between Korean cattle breeds and the closeness of breeds corresponding to the geographic regions where they are evolving.ConclusionOur results indicate that although the Korean cattle breeds have common features, they also show reliable breed diversity.

Selection and effectiveness of informative SNPs for paternity in Chinese Simmental cattle based on a high-density SNP array

Incorrect paternity assignment in cattle can significantly influence the accuracy of genetic evaluation. Recent advances in high-throughput technology have facilitated the identification of single nucleotide polymorphism (SNP) markers and their applications for filiation and individual identification. We genotyped 1074 bulls from a reference population of Chinese Simmental cattle for genomic selection using a BovineSNP770K BeadChip. Among them, a total of 136 bulls were randomly selected to design a suitable low-density SNP panel for paternity testing in Simmental cattle. Our results showed that 50 SNPs were determined to be the most informative markers in parental testing, with an accuracy of 99.89% for CPE (cumulative probability of exclusion) in the unknown female parent case. The 50 highly informative SNP markers were distributed across 25 chromosomes, and the mean intermarker distance per chromosome was 26.72 Mb. The average minor allele frequency (MAF), expected heterozygosity (HE), and polymorphic information content (PIC) values were 0.3748, 0.4998, and 0.4818, respectively. Finally, the 50 identified SNPs were used to estimate paternity for the remaining 938 of 1074 bulls from 23 farms. Our results revealed that 76.75% of the 938 bulls were assigned parentage to the pedigree sires with 95% confidence, and the rate of pedigree record mistakes ranged from 9.52%–39.29% in different herds. Our study is the first attempt to provide valuable insights into the extraction of informative markers through the application of high-density SNP chips for paternity testing in Chinese Simmental cattle.

Publications

Background and Aim: There are over 400 genetically distinct breeds of dogs, each corresponding to a genetic isolate. The consequence of breeding practices is that most breeds naturally develop specific cancer types, reflecting the presence of predisposing alleles. This is interesting for lymphomas, as most human lymphoma subtypes are encountered in dogs, with some subtypes over-represented in specific breeds (Pastor et al., 2009; Rowell et al., 2011; Marconato et al., 2013). We focused on lymphoma occurring in large families of Bernese Mountain Dogs (BMDs) with the objectives to identify predisposing genetic regions and somatic alterations involved in lymphomagenesis. Materials and Methods: We collected blood and tumour samples, clinical and genealogical information of affected BMDs, using the French CaniDNA biobank at CNRS, Rennes. Histopathological diagnosis was performed from formalin-fixed paraffin-embedded tumour samples by veterinary pathologists F. N. and J. A. DNA and RNA were extracted using Macherey-Nagel® kits. Dog DNAs were genotyped on the canine Illumina®, and 170 000 single-nucleotide polymorphism (SNP) arrays and RNA of matched tumour and healthy tissues were sequenced (RNAseq) using Illumina technology, by the GIGA genomic facility, University of Liege. Data were analysed by the software crac/ chimCT (Philippe et al., 2013) to identify translocations. The fusion point was validated on tumour DNA and cDNA, by Sanger sequencing. Results: First, we demonstrated a familial segregation of lymphoma in a pedigree of BMDs. We performed a genome-wide association study using 63 lymphoma cases and 164 controls with the high-density SNP chips. Preliminary data showed a significant locus, associated with predisposition to lymphoma, on canine chromosome CFA 23. This locus does not correspond to any known locus for human lymphomas and thus represents an interesting candidate region. Second, while many chromosomal translocations are known to drive lymphomagenesis in humans, only little genetic data are available in dogs. We thus investigated somatic alterations through RNAseq on five lymphoma-affected dogs and identified a relevant translocation involving an immunoglobulin gene and a gene involved in cell cycle. Interestingly, this gene is known to be involved in translocations in human lymphomas, showing that similar genes are involved in both human and dog lymphomas. Conclusions: Based on the collection of different types of canine lymphomas in several predisposed breeds, we first identified a potential novel locus predisposing to lymphomas. We are exploring and reducing the region of interest by using other canine breeds. Second, we discovered a novel chromosomal translocation in dogs, homologous to a translocation in the same human lymphoma type. These data clearly showed that the same key pathways are involved in lymphomas in dogs and humans, justifying the setting up of clinical trials in dogs for the benefit of both humans and dogs.

Genetic tools to improve reproduction traits in dairy cattle.

Fertility is a major concern in the dairy cattle industry and has been the subject of numerous studies over the past 20 years. Surprisingly, most of these studies focused on rough female phenotypes and, despite their important role in reproductive success, male- and embryo-related traits have been poorly investigated. In recent years, the rapid and important evolution of technologies in genetic research has led to the development of genomic selection. The generalisation of this method in combination with the achievements of the AI industry have led to the constitution of large databases of genotyping and sequencing data, as well as refined phenotypes and pedigree records. These resources offer unprecedented opportunities in terms of fundamental and applied research. Here we present five such examples with a focus on reproduction-related traits: (1) detection of quantitative trait loci (QTL) for male fertility and semen quality traits; (2) detection of QTL for refined phenotypes associated with female fertility; (3) identification of recessive embryonic lethal mutations by depletion of homozygous haplotypes; (4) identification of recessive embryonic lethal mutations by mining whole-genome sequencing data; and (5) the contribution of high-density single nucleotide polymorphism chips, whole-genome sequencing and imputation to increasing the power of QTL detection methods and to the identification of causal variants.

Linkage disequilibrium levels in Bos indicus and Bos taurus cattle using medium and high density SNP chip data and different minor allele frequency distributions

Linkage disequilibrium (LD), the observed correlation between alleles at different loci in the genome, is a determinant parameter in many applications of molecular genetics. With the wider use of genomic technologies in animal breeding and animal genetics, it is worthwhile revising and improving the current knowledge and understanding of cattle LD.This study analyzes levels of LD assessed through the r2 measurement in seven breeds of cattle from both indicine (Bos indicus) and taurine (Bos taurus) (sub)species, genotyped with a high density panel (HD) of over 777,000 single nucleotide polymorphism (SNP) markers. Average levels of LD were assessed for inter-marker distances from 0kb up to 10Mb. Two more SNP panels were built in silico from the original genotypes to represent a lower density SNP chip including approximately 50,000 SNPs (50K) and a panel of 249,000 SNPs chosen to comply with specific minor allele frequency (MAF) distributions.The results show higher levels of LD than previously reported, especially at short inter-marker distances of less than 20kb, assessed through the use of the higher density panel. Negligible impact of MAF changes in the estimation of r2 was observed, supporting the use of the HD panel for LD-based methodologies even when ascertainment bias in the choice of SNPs is suspected. The 50K SNP panel indicated lower levels of LD in the first 100kb and highly unreliable LD estimates for distances shorter than 50kb. Overall, lower levels of LD were observed for all indicine breeds as compared to taurine breeds, with larger differences assessed in the first 100kb, suggesting the need for use of higher SNP densities in this (sub)species when applying LD-dependent methods, as compared to most taurine breeds.

Manifestation of diffuse yellowish keratoderma on the palms and soles in autosomal recessive congenital ichthyosis patients may be indicative of mutations in NIPAL4

Ichthyosis is a heterogeneous disorder characterized by abnormal skin scaling over the whole body. Autosomal recessive congenital ichthyosis (ARCI) comprises various forms, the most important of which are lamellar ichthyosis (LI) and congenital ichthyosiform erythroderma (CIE). Seven genes have been identified to be causative of ARCI, and these account for disease in 60-80% of the patients. There is notable phenotypic overlap between the major forms of ARCI, and a strong genotype-phenotype correlation has not been found. Here, we initially aimed to identify the causative gene in a large Iranian ARCI pedigree, and subsequently performed genetic analysis on four other affected pedigrees. A genotype-phenotype correlation was sought. Whole genome homozygosity mapping using high-density single nucleotide polymorphism chips was performed on the large pedigree. Linkage to chromosome 5 and a mutation in NIPAL4 causing p.G297R were identified. The same mutation was also identified in two of the remaining four Iranian pedigrees. Two of the NIPAL4 mutation bearing pedigrees were classified as CIE and one as LI. Notably, all NIPAL4 mutation-bearing patients manifested diffuse yellowish keratoderma on the palms and soles. We provide evidence suggesting presentation of this diffuse yellowish keratoderma may be indicative of mutations in NIPAL4, providing an easily assessable genotype-phenotype correlation.

Genes controlling vaccine responses and disease resistance to respiratory viral pathogens in cattle

Farm animals remain at risk of endemic, exotic and newly emerging viruses. Vaccination is often promoted as the best possible solution, and yet for many pathogens, either there are no appropriate vaccines or those that are available are far from ideal. A complementary approach to disease control may be to identify genes and chromosomal regions that underlie genetic variation in disease resistance and response to vaccination. However, identification of the causal polymorphisms is not straightforward as it generally requires large numbers of animals with linked phenotypes and genotypes. Investigation of genes underlying complex traits such as resistance or response to viral pathogens requires several genetic approaches including candidate genes deduced from knowledge about the cellular pathways leading to protection or pathology, or unbiased whole genome scans using markers spread across the genome.Evidence for host genetic variation exists for a number of viral diseases in cattle including bovine respiratory disease and anecdotally, foot and mouth disease virus (FMDV). We immunised and vaccinated a cattle cross herd with a 40-mer peptide derived from FMDV and a vaccine against bovine respiratory syncytial virus (BRSV). Genetic variation has been quantified. A candidate gene approach has grouped high and low antibody and T cell responders by common motifs in the peptide binding pockets of the bovine major histocompatibility complex (BoLA) DRB3 gene. This suggests that vaccines with a minimal number of epitopes that are recognised by most cattle could be designed. Whole genome scans using microsatellite and single nucleotide polymorphism (SNP) markers has revealed many novel quantitative trait loci (QTL) and SNP markers controlling both humoral and cell-mediated immunity, some of which are in genes of known immunological relevance including the toll-like receptors (TLRs).The sequencing, assembly and annotation of livestock genomes and is continuing apace. In addition, provision of high-density SNP chips should make it possible to link phenotypes with genotypes in field populations without the need for structured populations or pedigree information. This will hopefully enable fine mapping of QTL and ultimate identification of the causal gene(s). The research could lead to selection of animals that are more resistant to disease and new ways to improve vaccine efficacy.

Evaluation of approaches for identifying population informative markers from high density SNP Chips

BackgroundGenetic markers can be used to identify and verify the origin of individuals. Motivation for the inference of ancestry ranges from conservation genetics to forensic analysis. High density assays featuring Single Nucleotide Polymorphism (SNP) markers can be exploited to create a reduced panel containing the most informative markers for these purposes. The objectives of this study were to evaluate methods of marker selection and determine the minimum number of markers from the BovineSNP50 BeadChip required to verify the origin of individuals in European cattle breeds. Delta, Wright's FST, Weir & Cockerham's FST and PCA methods for population differentiation were compared. The level of informativeness of each SNP was estimated from the breed specific allele frequencies. Individual assignment analysis was performed using the ranked informative markers. Stringency levels were applied by log-likelihood ratio to assess the confidence of the assignment test.ResultsA 95% assignment success rate for the 384 individually genotyped animals was achieved with < 80, < 100, < 140 and < 200 SNP markers (with increasing stringency threshold levels) across all the examined methods for marker selection. No further gain in power of assignment was achieved by sampling in excess of 200 SNP markers. The marker selection method that required the lowest number of SNP markers to verify the animal's breed origin was Wright's FST (60 to 140 SNPs depending on the chosen degree of confidence). Certain breeds required fewer markers (< 100) to achieve 100% assignment success. In contrast, closely related breeds require more markers (~200) to achieve > 95% assignment success. The power of assignment success, and therefore the number of SNP markers required, is dependent on the levels of genetic heterogeneity and pool of samples considered.ConclusionsWhile all SNP selection methods produced marker panels capable of breed identification, the power of assignment varied markedly among analysis methods. Thus, with effective exploration of available high density genetic markers, a diagnostic panel of highly informative markers can be produced.

Genetics of fibre production and fleece characteristics in small ruminants, Angora rabbit and South American camelids

This paper reviews genetics of fibre production and fleece characteristics in small ruminants, Angora rabbit and South American camelids with a special distinction between single-coated (SC) and double-coated (DC) species. Considering the biology of fibre production, there are variations in coat composition and structure, fibre growth pattern and fibre structure and quality between these two main kinds of fibre-producing animals. In SC species, all fibres are nearly similar in dimensions and are produced from individual follicles that have a very long period, essentially permanent, of active growth without a synchronous phase of rest between follicles. In contrast, in DC species the fleece comprises a coarse outer coat and a fine inner coat with variations of coat composition and structure, and fibre growth pattern according to the season with a well-defined duration of fibre growth. Genetic basis of hair growth pattern, coat composition and fibre structure are different between species. In small ruminants, these coat characters are additive and because of several genes whereas in rabbit, several autosomal recessive genes determine fibre growth, coat composition and structure. In alpaca, the fleece type (Suri or Huacaya) is determined by a single dominant gene. This paper also reviews genetic parameters of fibre production traits in Angora goat, Angora rabbit and alpaca in which many aspects of the genetic basis of fibre production are analogous. There are many traits controlling both fibre quality and fibre quantity, and most of these traits tend to be moderately to strongly inherited so that a rapid genetic progress in any traits is possible and indeed has been achieved. However, there are differences in breeding programmes. In DC Angora rabbit, selection for one single trait, the easy measurable total fleece weight has general beneficial effects on fleece quality. However, because of antagonistic relations between qualitative and quantitative traits in SC species, achieving this goal requires a multi-trait selection index approach. Gene mapping studies have recently identified several putative quantitative trait loci and major genes affecting fibre and fleece characteristics in sheep, goat and rabbit are reviewed. The whole genome sequence of sheep and rabbit will be available in the near future and the use of high-density single nucleotide polymorphism chip will allow fine mapping and dissection of the genetic basis of many production traits including fibre production and fleece characteristics. The application of these techniques will thus contribute to improving the efficiency, profitability and sustainability of small ruminant and rabbit fibre production.

Relationship ofEGFRMutations, Expression, Amplification, and Polymorphisms to Epidermal Growth Factor Receptor Inhibitors in the NCI60 Cell Lines

The mechanism of sensitivity and resistance to epidermal growth factor receptor (EGFR) inhibitors is incompletely understood, particularly in cancers other than non-small-cell lung cancer (NSCLC). To understand the variable response to this class of drugs, we used the NCI60 cancer cell lines. We aimed to determine if there are interactions between EGFR expression, mutations, polymorphisms, and gene amplification, and whether these factors are associated with variability in response to EGFR inhibitors. The EGFRVIII and tyrosine kinase (TK) domain mutations were examined in the NCI60 cancer cell lines. Five polymorphisms, -216G/T, -191C/A, intron 1 (CA)n, R497K, and 2607A/G, were genotyped. EGFR amplification was also assessed with high-density single-nucleotide polymorphism chip and real-time PCR, respectively. The results were correlated with cytotoxicity data for erlotinib and other 11 EGFR inhibitors, as well as other publicly available data for these lines. All 12 inhibitors behaved similarly. No EGFRVIII but putative TK mutations in two cell lines were found. Both mutant cell lines were insensitive to all inhibitors. Meanwhile, response did not correlate with EGFR amplification but with EGFR gene expression, especially in the cell lines with relatively normal gene status. In addition, EGFR expression was associated with the -216G/T polymorphism but not with the intron 1 (CA)n polymorphism. A combination of -216G/T and R497K polymorphisms was weakly associated with drug response. These observations suggest that in addition to TK mutations, germ-line variability may also contribute to the pharmacodynamics of EGFR inhibitors, particularly when EGFR is genetically normal.

Analytic methods for colorectal cancer

Colorectal cancer (CRC) is a major cause of morbidity and mortality from cancers in the United States. The field of molecular epidemiology is in the forefront in the discovery of genes associated with the development and progression of complex diseases such as CRC, including hereditary CRC, and polyposis syndromes such as familial adenomatous polyposis and hereditary nonpolyposis colon cancer. Recent advances in laboratory methods (ie, high-throughput genotyping and high-density single nucleotide polymorphism chips, etc.) allow the molecular epidemiologist to elucidate biological determinates of disease. However, with these advancements in the lab, advances in modeling and testing of such data are needed as well. Herein, we review the current analytical methods that have been applied to molecular epidemiologic studies for CRC and hereditary nonpolyposis colon cancer within the past 2 years, comment on the application of these methods, and examine new and promising tools that will likely influence the discovery of gene-gene and gene-environment interactions and development of pathway-based analytical approaches for CRC risk and progression.

Unraveling A Complex Genetic Disease: Age-related Macular Degeneration

In most of the Western world, age-related macular degeneration (AMD) remains the largest single cause of severe visual impairment, and its prevalence continues to increase. It is considered to be a complex disease, in which multiple genes and environment play a role in pathogenesis. Several environmental insults are implicated with smoking, serum cholesterol, hypertension, sunlight exposure, and many other factors being variously associated with disease pathogenesis. Until recently, there have been relatively few breakthroughs to further our understanding of the genetics of AMD, despite remarkable progress in molecular genetic techniques over the last 20 years, and the fact that many rare inherited macular diseases have had their causative genes mapped. Development of new tools such as high-density single-nucleotide polymorphism chips and microarrays have changed the face of genetic research, but have yet to directly translate into improved clinical outcomes in ophthalmology. However with the recent finding of the Tyr402His polymorphism in the complement factor H gene being implicated in AMD, we are about to witness a new wave of research in this disease. Not only does the identification of a biologically plausible gene identify a new pathway, but it also identifies new biological mechanisms for disease, avenues to pursue treatment, and a better understanding of how the environment interacts with the genetic background to create disease. This article aims to review the process of gene discovery in complex disease, why the search for genes remains difficult, how to translate laboratory findings to a clinical setting, and how these findings will impact on disease treatment and public health issues.