Multilocus Single Nucleotide Polymorphism Research Articles

The Spherical Evolutionary Multi-Objective (SEMO) Algorithm for Identifying Disease Multi-Locus SNP Interactions.

Single-nucleotide polymorphisms (SNPs), as disease-related biogenetic markers, are crucial in elucidating complex disease susceptibility and pathogenesis. Due to computational inefficiency, it is difficult to identify high-dimensional SNP interactions efficiently using combinatorial search methods, so the spherical evolutionary multi-objective (SEMO) algorithm for detecting multi-locus SNP interactions was proposed. The algorithm uses a spherical search factor and a feedback mechanism of excellent individual history memory to enhance the balance between search and acquisition. Moreover, a multi-objective fitness function based on the decomposition idea was used to evaluate the associations by combining two functions, K2-Score and LR-Score, as an objective function for the algorithm's evolutionary iterations. The performance evaluation of SEMO was compared with six state-of-the-art algorithms on a simulated dataset. The results showed that SEMO outperforms the comparative methods by detecting SNP interactions quickly and accurately with a shorter average run time. The SEMO algorithm was applied to the Wellcome Trust Case Control Consortium (WTCCC) breast cancer dataset and detected two- and three-point SNP interactions that were significantly associated with breast cancer, confirming the effectiveness of the algorithm. New combinations of SNPs associated with breast cancer were also identified, which will provide a new way to detect SNP interactions quickly and accurately.

Accurate Differentiation of Green Beans of Arabica and Robusta Coffee Using Nanofluidic Array of Single Nucleotide Polymorphism (SNP) Markers.

Green (unroasted) coffee is one of the most traded agricultural commodities in the world. The Arabica (Coffea arabica L.) and Robusta (Coffea canephora Pierre ex A. Froehner) species are the two main types of coffees for commercial production. In general, Arabica coffee is known to have better quality in terms of sensory characteristics; thus, it has a higher market value than Robusta coffee. Accurate differentiation of green beans of the two species is, therefore, of commercial interest in the coffee industry. Using the newly developed single nucleotide polymorphism (SNP) markers, we analyzed a total of 80 single green bean samples, representing 20 Arabica cultivars and four Robusta accessions. Reliable SNP fingerprints were generated for all tested samples. Unambiguous differentiation between Robusta and Arabica coffees was achieved using multivariate analysis and assignment test. The SNP marker panel and the genotyping protocol are sufficiently robust to detect admixture of green coffee in a high-throughput fashion. Moreover, the multilocus SNP approach can differentiate every single bean within Robusta and 55% of Arabica samples. This advantage, together with the single-bean sensitivity, suggests a significant potential for practical application of this technology in the coffee industry.

An outbreak of multiple genotypes of Listeria monocytogenes in New Zealand linked to contaminated ready-to-eat meats-a retrospective analysis using whole-genome sequencing.

Four cases of listeriosis in a hospital (A) in New Zealand were identified in 2012. Pulsed-field gel electrophoresis (PFGE) used at the time identified four pulsotypes amongst the clinical isolates. Two of the pulsotypes matched to Listeria monocytogenes isolates obtained from ready-to-eat (RTE) meat samples from a RTE producer tested during a nationwide microbiological survey the month prior. The outbreak investigation confirmed that the RTE producer had supplied product to the hospital and additional testing confirmed the presence of L.monocytogenes in RTE meats from the hospital kitchen. Two further listeriosis cases presented in another hospital (B) with one clinical isolate identified as the same pulsotype as identified for one case in hospital A, but the epidemiology information concluded that the clinical cases from hospital B were not linked to the outbreak. Retrospective whole-genome sequencing confirmed that epidemiologically linked isolates belonging to three different genotypes for clinical cases from hospital A and RTE meats samples from the hospital kitchen differed by 0-1 core-genome locus or single nucleotide polymorphisms (SNP). The use of core-genome multilocus sequence typing and SNP analysis provided a greater degree of discrimination between isolates compared to PFGE. SIGNIFICANCE AND IMPACT OF THE STUDY: This study describes a listeriosis outbreak associated with a hospital in New Zealand and attributed to contaminated ready-to-eat (RTE) meat supplied to the hospital by a single producer. Retrospective whole-genome sequence analysis of outbreak isolates was found to provide a greater degree of discrimination between isolates compared to pulsed-field gel electrophoresis and supported the conclusions made at the time of the outbreak. The multiple genotypes identified from clinical cases and the RTE meats obtained during the outbreak highlight the importance of epidemiological concordance alongside genotyping.

Whole genome sequencing-based association study to unravel genetic architecture of cooked grain width and length traits in rice

In this study, we used 2.9 million single nucleotide polymorphisms (SNP) and 393,429 indels derived from whole genome sequences of 591 rice landraces to determine the genetic basis of cooked and raw grain length, width and shape using genome-wide association study (GWAS). We identified a unique fine-mapped genetic region GWi7.1 significantly associated with cooked and raw grain width. Additionally, GWi7.2 that harbors GL7/GW7 a cloned gene for grain dimension was found. Novel regions in chromosomes 10 and 11 were also found to be associated with cooked grain shape and raw grain width, respectively. The indel-based GWAS identified fine-mapped genetic regions GL3.1 and GWi5.1 that matched synteny breakpoints between indica and japonica. GL3.1 was positioned a few kilobases away from GS3, a cloned gene for cooked and raw grain lengths in indica. GWi5.1 found to be significantly associated with cooked and raw grain width. It anchors upstream of cloned gene GW5, which varied between indica and japonica accessions. GWi11.1 is present inside the 3′-UTR of a functional gene in indica that corresponds to a syntenic break in chromosome 11 of japonica. Our results identified novel allelic structural variants and haplotypes confirmed using single locus and multilocus SNP and indel-based GWAS.

Single-nucleotide polymorphisms in DNA bypass polymerase genes and association with breast cancer and breast cancer subtypes among African Americans and Whites.

DNA damage recognition and repair is a complex system of genes focused on maintaining genomic stability. Recently, there has been a focus on how breast cancer susceptibility relates to genetic variation in the DNA bypass polymerases pathway. Race-stratified and subtype-specific logistic regression models were used to estimate odds ratios (ORs) and 95 % confidence intervals (CIs) for the association between 22 single-nucleotide polymorphisms (SNPs) in seven bypass polymerase genes and breast cancer risk in the Carolina Breast Cancer Study, a population-based, case-control study (1,972 cases and 1,776 controls). We used SNP-set kernel association test (SKAT) to evaluate the multi-gene, multi-locus (combined) SNP effects within bypass polymerase genes. We found similar ORs for breast cancer with three POLQ SNPs (rs487848 AG/AA vs. GG; OR = 1.31, 95 % CI 1.03-1.68 for Whites and OR = 1.22, 95 % CI 1.00-1.49 for African Americans), (rs532411 CT/TT vs. CC; OR = 1.31, 95 % CI 1.02-1.66 for Whites and OR = 1.22, 95 % CI 1.00-1.48 for African Americans), and (rs3218634 CG/CC vs. GG; OR = 1.29, 95 % CI 1.02-1.65 for Whites). These three SNPs are in high linkage disequilibrium in both races. Tumor subtype analysis showed the same SNPs to be associated with increased risk of Luminal breast cancer. SKAT analysis showed no significant combined SNP effects. These results suggest that variants in the POLQ gene may be associated with the risk of Luminal breast cancer.

Nucleotide diversity in lignification genes and QTNs for lignin quality in a multi-parental population of Eucalyptus urophylla

Lignin is a major chemical compound of wood and one of the most abundant organic biopolymers on earth. It accumulates in the secondary cell wall of xylem cells and is a major target for tree breeders because of its foreseen role in the emerging bioeconomy. In this study, we paved the way toward an accelerated domestication of a widely grown tree species, Eucalyptus urophylla, by molecular breeding. To this end, we first described the pattern of nucleotide variation occurring at seven structural and regulatory genes of the lignin biosynthesis pathway and found high levels of average nucleotide and haplotype diversity per gene (π = 0.0065 and Hd = 0.853). Then, taking advantage of a pre-existing factorial mating design, a candidate-gene-based quantitative trait locus (QTL) detection strategy was used to compare the variation of lignin quality (syringyl by guaiacyl ratio (S/G)) with the nucleotidic variability in these seven genes in 304 genotypes belonging to 33 connected full-sib families. Two genes, encoding cinnamoyl-CoA reductase (CCR) and a Rho-like GTPase (ROP1), were shown to be linked to the variation of S/G through different single and multi-locus single-nucleotide polymorphism (SNP)- and haplotype-based association methods. Providing that relevant candidate genes are selected and their patterns of nucleotide diversity is accurately described, we showed that quantitative trait nucleotides (QTNs) can be detected taking advantage of pre-existing field experiments and trait measurements gathered in the framework of a forest tree breeding program.

SNP markers identify widely distributed clonal lineages of Phytophthora colocasiae in Vietnam, Hawaii and Hainan Island, China

Taro (Colocasia esculenta) is an important food crop, and taro leaf blight caused by Phytophthora colocasiae can significantly affect production. Our objectives were to develop single nucleotide polymorphism (SNP) markers for P. colocasiae and characterize populations in Hawaii (HI), Vietnam (VN) and Hainan Island, China (HIC). In total, 379 isolates were analyzed for mating type and multilocus SNP profiles including 214 from HI, 97 from VN and 68 from HIC. A total of 1152 single nucleotide variant (SNV) sites were identified via restriction site-associated DNA (RAD) sequencing of two field isolates. Genotyping with 27 SNPs revealed 41 multilocus SNP genotypes grouped into seven clonal lineages containing 2–232 members. Three clonal lineages were shared among countries. In addition, five SNP markers had a low incidence of loss of heterozygosity (LOH) during asexual laboratory growth. For HI and VN, >95% of isolates were the A2 mating type. On HIC, isolates within single clonal lineages had A1, A2 and A0 (neuter) isolates. The implications for the wide dispersal of clonal lineages are discussed.

English

Accurate identification of individual genotypes is important for cacao ( Theobroma cacao L.) breeding, germplasm conservation and seed propagation. The development of single nucleotide polymorphism (SNP) markers in cacao offers an effective way to use a high-throughput genotyping system for cacao genotype verification. In the present study, high-throughput genotyping with SNP markers was used to fingerprint 160 cacao trees in the germplasm collection at the Cocoa Research Institute of Ghana (CRIG). These accessions had been originally introduced from international germplasm collections. The multilocus SNP profiles, generated by the Sequenom Mass Spectrometry platform, were compared with the SNP profiles of reference trees maintained in the international cacao collections. The comparison unambiguously identified mislabeled trees. For materials introduced as hybrid seeds without an available reference genotype, parentage analysis and model-based assignment were applied to verify their recorded parentage and genetic background. Our study shows that a small set of polymorphic SNP markers can provide a robust and accurate result for cacao genotype identification. This protocol can be applied for large-scale genotyping of cacao as well as for many other crops. Keywords: Cacao, conservation, chocolate, DNA fingerprint, molecular marker, tropical plant, off-type, true-to-type, West Africa. African Journal of Biotechnology , Vol 13(21), 2127-2136

A new multiplex SNP genotyping assay for detecting hybridization and introgression between the M and S molecular forms of Anopheles gambiae

The M and S forms of Anopheles gambiae have been the subject of intense study, but are morphologically indistinguishable and can only be identified using molecular techniques. PCR-based assays to distinguish the two forms have been designed and applied widely. However, the application of these assays towards identifying hybrids between the two forms, and backcrossed hybrids in particular, has been problematic as the currently available diagnostic assays are based on single locus and/or are located within a multicopy gene. Here, we present an alternative genotyping method for detecting hybridization and introgression between M and S molecular forms based on a multilocus panel of single-nucleotide polymorphisms (SNPs) fixed between the M and S forms. The panel of SNPs employed is located in so-called islands of divergence leading us to describe this method as the 'Divergence Island SNP' (DIS) assay. We show this multilocus SNP genotyping approach can robustly and accurately detect F1 hybrids as well as backcrossed individuals.

The adaptive potential of Populus balsamifera L. to phenology requirements in a warmer global climate

The manner in which organisms adapt to climate change informs a broader understanding of the evolution of biodiversity as well as conservation and mitigation plans. We apply common garden and association mapping approaches to quantify genetic variance and identify loci affecting bud flush and bud set, traits that define a tree's season for height growth, in the boreal forest tree Populus balsamifera L. (balsam poplar). Using data from 478 genotypes grown in each of two common gardens, one near the southern edge and another near the northern edge of P. balsamifera's range, we found that broad-sense heritability for bud flush and bud set was generally high (H(2) > 0.5 in most cases), suggesting that abundant genetic variation exists for phenological response to changes in the length of the growing season. To identify the molecular genetic basis of this variation, we genotyped trees for 346 candidate single nucleotide polymorphisms (SNPs) from 27 candidate genes for the CO/FT pathway in poplar. Mixed-model analyses of variance identified SNPs in 10 genes to be associated with variation in either bud flush or bud set. Multiple SNPs within FRIGIDA were associated with bud flush, whereas multiple SNPs in LEAFY and GIGANTEA 5 were associated with bud set. Although there was strong population structure in stem phenology, the geographic distribution of multilocus association SNP genotypes was widespread except at the most northern populations, indicating that geographic regions may harbour sufficient diversity in functional genes to facilitate adaption to future climatic conditions in many sites.

Genetic diversity of Phytophthora capsici isolates from pepper and pumpkin in Argentina

Phytophthora capsici is a soilborne oomycete plant pathogen that limits pepper production worldwide. The population structure varies significantly depending on the location (e.g. Peru vs. USA) and little is known about the diversity of P. capsici in Argentina. Our objective was to assess the diversity of P. capsici in Argentina at key pepper production areas. Forty isolates were recovered 2006–2009 from pepper and one isolate from pumpkin at 11 locations. Isolates were assessed for mating type, mefenoxam sensitivity and multilocus single nucleotide polymorphism (SNP) genotype profiles. Ten isolates with identical SNP profiles also were genotyped with amplified fragment length polymorphism (AFLP) markers. All 41 isolates had the A1 mating type and were sensitive to mefenoxam. Genotypic analysis using eight polymorphic SNP markers indicated 87% of the isolates had the same multilocus genotype, which is fixed for heterozygosity at seven of the eight SNP sites. AFLP analyses confirmed these findings, and overall it appears that clonal reproduction drives the population structure of P. capsici in Argentina. The implications for breeding resistant peppers and overall disease management are discussed.

Identification of New Single Nucleotide Polymorphism-Based Markers for Inter- and Intraspecies Discrimination of Obligate Bacterial Parasites (Pasteuria spp.) of Invertebrates

Protein-encoding and 16S rRNA genes of Pasteuria penetrans populations from a wide range of geographic locations were examined. Most interpopulation single nucleotide polymorphisms (SNPs) were detected in the 16S rRNA gene. However, in order to fully resolve all populations, these were supplemented with SNPs from protein-encoding genes in a multilocus SNP typing approach. Examination of individual 16S rRNA gene sequences revealed the occurrence of "cryptic" SNPs which were not present in the consensus sequences of any P. penetrans population. Additionally, hierarchical cluster analysis separated P. penetrans 16S rRNA gene clones into four groups, and one of which contained sequences from the most highly passaged population, demonstrating that it is possible to manipulate the population structure of this fastidious bacterium. The other groups were made from representatives of the other populations in various proportions. Comparison of sequences among three Pasteuria species, namely, P. penetrans, P. hartismeri, and P. ramosa, showed that the protein-encoding genes provided greater discrimination than the 16S rRNA gene. From these findings, we have developed a toolbox for the discrimination of Pasteuria at both the inter- and intraspecies levels. We also provide a model to monitor genetic variation in other obligate hyperparasites and difficult-to-culture microorganisms.

Sniper: improved SNP discovery by multiply mapping deep sequenced reads

SNP (single nucleotide polymorphism) discovery using next-generation sequencing data remains difficult primarily because of redundant genomic regions, such as interspersed repetitive elements and paralogous genes, present in all eukaryotic genomes. To address this problem, we developed Sniper, a novel multi-locus Bayesian probabilistic model and a computationally efficient algorithm that explicitly incorporates sequence reads that map to multiple genomic loci. Our model fully accounts for sequencing error, template bias, and multi-locus SNP combinations, maintaining high sensitivity and specificity under a broad range of conditions. An implementation of Sniper is freely available at http://kim.bio.upenn.edu/software/sniper.shtml.

Protocol: a simple gel-free method for SNP genotyping using allele-specific primers in rice and other plant species

BackgroundGenotype analysis using multiple single nucleotide polymorphisms (SNPs) is a useful but labor-intensive or high-cost procedure in plant research. Here we describe an alternative genotyping method that is suited to multi-sample or multi-locus SNP genotyping and does not require electrophoresis or specialized equipment.ResultsWe have developed a simple method for multi-sample or multi-locus SNP genotyping using allele-specific primers (ASP). More specifically, we (1) improved the design of allele-specific primers, (2) established a method to detect PCR products optically without electrophoresis, and (3) standardized PCR conditions for parallel genomic assay using various allele-specific primers. As an illustration of multi-sample SNP genotyping using ASP, we mapped the locus for lodging resistance in a typhoon (lrt5). Additionally, we successfully tested multi-locus ASP-PCR analysis using 96 SNPs located throughout the genomes of rice (Oryza sativa) cultivars 'Koshihikari' and 'Kasalath', and demonstrated its applicability to other diverse cultivars/subspecies, including wild rice (O. rufipogon).ConclusionOur ASP methodology allows characterization of SNPs genotypes without electrophoresis, expensive probes or specialized equipment, and is highly versatile due to the flexibility in the design of primers. The method could be established easily in any molecular biology laboratory, and is applicable to diverse organisms.

Bayesian variable and model selection methods for genetic association studies

Variable selection is growing in importance with the advent of high throughput genotyping methods requiring analysis of hundreds to thousands of single nucleotide polymorphisms (SNPs) and the increased interest in using these genetic studies to better understand common, complex diseases. Up to now, the standard approach has been to analyze the genotypes for each SNP individually to look for an association with a disease. Alternatively, combinations of SNPs or haplotypes are analyzed for association. Another added complication in studying complex diseases or phenotypes is that genetic risk for the disease is often due to multiple SNPs in various locations on the chromosome with small individual effects that may have a collectively large effect on the phenotype. Hence, multi-locus SNP models, as opposed to single SNP models, may better capture the true underlying genotypic-phenotypic relationship. Thus, innovative methods for determining which SNPs to include in the model are needed. The goal of this article is to describe several methods currently available for variable and model selection using Bayesian approaches and to illustrate their application for genetic association studies using both real and simulated candidate gene data for a complex disease. In particular, Bayesian model averaging (BMA), stochastic search variable selection (SSVS), and Bayesian variable selection (BVS) using a reversible jump Markov chain Monte Carlo (MCMC) for candidate gene association studies are illustrated using a study of age-related macular degeneration (AMD) and simulated data.

Association of Four-locus Gene Interaction with Aspirin-intolerant Asthma in Korean Asthmatics

Aspirin-intolerant asthma (AIA), a major clinical presentation of aspirin hypersensitivity, affects 10% of adult asthmatics. The genetic risk factors involved in the susceptibility to AIA have recently been investigated, but multilocus single-nucleotide polymorphisms (SNPs) associated with this susceptibility has not been evaluated. We examined 246 asthmatic patients: 94 having aspirin intolerance and 152 having aspirin tolerance. We selected 23 SNPs of 13 candidate genes and genotyped each SNP using a primer extension method. Multilocus genetic interactions were examined using multifactor dimensionality reduction (MDR) to test all multilocus SNP combinations to identify a useful SNP set for predicting the AIA phenotype. We identified the best model using the MDR method, which consisted of a four-locus gene-gene interaction with 65.16% balanced accuracy and a cross-validation consistency of 70% in predicting AIA disease risk among asthmatic patients. This model included four SNPs such as B2ADR 46A>G, CCR3-520T>G, CysLTR1-634C>T, and FCER1B-109T>C. These results suggest that a multilocus SNP acts in combination to influence the susceptibility to aspirin intolerance in asthmatics and could be a useful genetic marker for the diagnosis of AIA.

Sequence diversity of the mucABD locus in Pseudomonas aeruginosa isolates from patients with cystic fibrosis

The mucA gene of the muc operon, which is instrumental in the control of the biosynthesis of the exopolysaccharide alginate, is a hotspot of mutation in Pseudomonas aeruginosa, a micro-organism that chronically colonizes the airways of individuals with cystic fibrosis (CF). The mucA, mucB and mucD genes were sequenced in nine environmental isolates from aquatic habitats, and in 37 P. aeruginosa strains isolated from 10 patients with CF, at onset or at a late stage of chronic airway colonization, in order to elucidate whether there was any association between mutation and background genotype. The 61 identified single nucleotide polymorphisms (SNPs) segregated into 18 mucABD genotypes. Acquired and de novo stop mucA mutations were present in 14 isolates (38 %) of five mucABD genotypes. DeltaG430 was the most frequent and recurrent mucA mutation detected in four genotypes. The classification of strains by mucABD genotype was generally concordant with that by genome-wide SpeI fragment pattern or multilocus SNP genotypes. The exceptions point to intragenic mosaicism and interclonal recombination as major forces for intraclonal evolution at the mucABD locus.