Single Nucleotide Polymorphism Marker Panels Research Articles

From Wisent to the Lab and Back Again—A Complex SNP Set for Population Management as an Effective Tool in European Bison Conservation

Proper management and genetic monitoring of the modern European bison (Bison bonasus) population is one of the most important responsibilities for this species’ conservation. Up-to-date, complex genetic analysis performed using a consistent molecular method is needed for population management as a tool to further validate and maintain the genetic diversity of the species. The identification of the genetic line when pedigree data are missing, as well as the identification of parentage and individuals, are crucial for this purpose. The aim of our research was to create a small but informative panel of SNP (single-nucleotide polymorphism) markers that can be used for routine genotyping of the European bison at low cost. In our study, we used a custom-designed microarray to genotype a large number of European bison, totaling 455 samples from two genetic lines. The results of this analysis allowed us to select highly informative markers. In this paper, we present an effective single nucleotide polymorphism set, divided into separate panels to perform genetic analyses of European bison, which is needed for population monitoring and management. We proposed a total of 20 SNPs to detect hybridization with Bos taurus and Bison bison, a panel of 50 SNPs for individuals and parentage identification, as well as a panel of 30 SNPs for assessing membership of the genetic line. These panels can be used together or independently depending on the research goal and can be applied using various methods.

Effects of single nucleotide polymorphism ascertainment on population structure inferences.

Single nucleotide polymorphism (SNP) data are widely used in research on natural populations. Although they are useful, SNP genotyping data are known to contain bias, normally referred to as ascertainment bias, because they are conditioned by already confirmed variants. This bias is introduced during the genotyping process, including the selection of populations for novel SNP discovery and the number of individuals involved in the discovery panel and selection of SNP markers. It is widely recognized that ascertainment bias can cause inaccurate inferences in population genetics and several methods to address these bias issues have been proposed. However, especially in natural populations, it is not always possible to apply an ideal ascertainment scheme because natural populations tend to have complex structures and histories. In addition, it was not fully assessed if ascertainment bias has the same effect on different types of population structure. Here, we examine the effects of bias produced during the selection of population for SNP discovery and consequent SNP marker selection processes under three demographic models: the island, stepping-stone, and population split models. Results show that site frequency spectra and summary statistics contain biases that depend on the joint effect of population structure and ascertainment schemes. Additionally, population structure inferences are also affected by ascertainment bias. Based on these results, it is recommended to evaluate the validity of the ascertainment strategy prior to the actual typing process because the direction and extent of ascertainment bias vary depending on several factors.

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.

A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata.

Development of genome-wide resources for application in genomic selection or genome-wide association studies, in the absence of full reference genomes, present a challenge to the forestry industry, where longer breeding cycles could benefit from the accelerated selection possible through marker-based breeding value predictions. In particular, large conifer megagenomes require a strategy to reduce complexity, whilst ensuring genome-wide coverage is achieved. Using a transcriptome-based reference template, we have successfully developed a high density exome capture genotype-by-sequencing panel for radiata pine (Pinus radiata D.Don), capable of capturing in excess of 80,000 single nucleotide polymorphism (SNP) markers with a minor allele frequency above 0.03 in the population tested. This represents approximately 29,000 gene models from a core set of 48,914 probes. A set of 704 SNP markers capable of pedigree reconstruction and differentiating individual genotypes were tested within two full-sib mapping populations. While as few as 70 markers could reconstruct parentage in almost all cases, the impact of missing genotypes was noticeable in several offspring. Therefore, 60 sets of 110 randomly selected SNP markers were compared for both parentage reconstruction and clone differentiation. The performance in parentage reconstruction showed little variation over 60 iterations. However, there was notable variation in discriminatory power between closely related individuals, indicating a higher density SNP marker panel may be required to elucidate hidden relationships in complex pedigrees.

Evaluation of ten SNP Markers for Human Identification and Paternity Analysis in Persian Population

Background: DNA markers are inevitable tools of human identification in forensic science. Single Nucleotide Polymorphisms (SNPs) are one category of these markers which is concerned to use especially in the case of degraded DNA because of their short amplicons.Objectives: Detection of highly informative SNPs by the criteria is the essential step to develop a useful panel of SNP markers. The purpose of this work is to get high informative SNPs for human identification in Persian ethnic of the Iranian population.Material and Methods: Genotype and allele frequencies of 10 SNPs from the SNPforID browser were determined by a PCR-RFLP method on 100 samples that was taken from 100 unrelated Persian people.Results: These ten SNPs were in Hardy-Weinberg equilibrium (P value > 0.1) except rs1355366 (P value = 0.02) and Heterozygosity of seven SNPs is greater than 0.45 but minor allele frequency of only four SNPs is more than 0.45. According to criteria only three SNPs rs1454361, rs2111980 and rs2107612 can pass all standards and are highly informative in population for forensic uses.Conclusions: Our data showed that the CPI (Combined probability of Identity) and CPE (Combined Power of Exclusion) for ten SNPs are 1.13 E-04 and 0.809 respectively. It was also showed based on the criteria only three SNPs (rs2107612, rs1454361 and rs2111980) are highly informative in Persian population. If we can find 39 SNPs with PE and PI close to PE and PI of these three SNPs (rs2107612, rs1454361 and rs2111980), we will be able to use of these 39 SNPs in human identification with sufficient power of discrimination.

Mapping of barley susceptibility/resistance QTL against spot form net blotch caused by Pyrenophora teres f. maculata using RIL populations.

Spot form net blotch (SFNB) caused by the necrotrophic fungal pathogen Pyrenophora teres f. maculata (Ptm) is an important disease of barley worldwide including the major barley production regions of North America. To characterize SFNB resistance/susceptibility quantitative trait loci (QTL), three recombinant inbred line (RIL) populations were developed from crosses between the malting barley cultivars, Tradition (six row) and Pinnacle (two row), and the two world barley core collection lines, PI67381 and PI84314. Tradition and Pinnacle were susceptible to many North American Ptm isolates, while PI67381 and PI84314 carry resistances to diverse Ptm isolates from across the globe. The RIL populations, Tradition/PI67381, Pinnacle/PI67381, and Pinnacle/PI84314 were genotyped using polymerase chain reaction-mediated genotype-by-sequencing single nucleotide polymorphism marker panels and phenotyped at the seedling stage with six geographically distinct Ptm isolates: FGOB10Ptm-1 (North Dakota, USA), Pin-A14 (Montana, USA), Cel-A17 (Montana, USA), SG1 (Australia), NZKF2 (New Zealand) and DEN2.6 (Denmark). The goal was to determine if the susceptible elite lines contained common susceptibility genes/QTL or if the resistant lines had common resistant genes/QTL effective against diverse Ptm isolates. The QTL analyses identified a total of 12 resistance and/or susceptibility loci on chromosomes 2H, 3H, 4H, 6H, and 7H of which three had not been previously reported. Common major QTL were detected on chromosome 2H (R2 = 14-40%) and 7H (R2 = 24-80%) in all three RIL populations, suggesting underlying genes with broad resistance specificity. The major 7H QTL was shown to be a dominant susceptibility gene in both susceptible malting barley varieties.

Short communication: Single-step genomic evaluation of milk production traits using multiple-trait random regression model in Chinese Holsteins

The objectives of this study were to evaluate the prediction performance of the single-step genomic BLUP method using a multi-trait random regression model in genomic evaluation for milk production traits of Chinese Holsteins, and investigate how parameters w, τ, and ω used in the construction of the combined relationship matrix (H) affected prediction accuracy and bias. A total of 2.8 million test-day records from 0.2 million cows were available for milk, protein, and fat yields. Pedigree information included 0.3 million animals and 7,577 of them were genotyped with medium-density single nucleotide polymorphism marker panels. Genotypes were imputed into Geneseek Genomic Profiler HD (GeneSeek, Lincoln, NE) including 77K markers. A reduced data set for evaluating models was extracted from the full data set by removing test-day records from the last 4 yr. Bull and cow validation populations were constructed for each trait. We evaluated the prediction performance of the multiple-trait multiple-lactation random regression single-step genomic BLUP (RR-ssGBLUP) models with different values of parameters w, τ, and ω in the H matrix, taking consideration of inbreeding. We compared RR-ssGBLUP with the multiple-trait multiple-lactation random regression model based on pedigree and genomic BLUP. De-regressed proofs for 305-d milk, protein, and fat yields averaged over 3 lactations, which were calculated from the full data set, were used for posteriori validations. The results showed that RR-ssGBLUP was feasible for implementation in breeding practice, and its prediction performance was superior to the other 2 methods in the comparison, including prediction accuracy and unbiasedness. For bulls, RR-ssGBLUP models with w0.05τ2.0ω1.0,w0.05τ2.5ω1.0, and w0.1τ1.6ω0.4 achieved the best performance for milk, protein, and fat yields, respectively. For cows, the RR-ssGBLUP with w0.2τ1.6ω0.4 performed the best for all 3 traits. The H matrix constructed with larger τ and smaller ω gave better convergence in solving mixed model equations. Among different RR-ssGBLUP models, the differences in validation accuracy were small. However, the regression coefficient indicating prediction bias varied substantially. The increase of w and τ, and decrease of ω, led to an increase in the regression coefficient. The results demonstrated RR-ssGBLUP is a good alternative to the multi-step approach, but the optimal choice of parameters should be found via preliminary validation study to achieve the best performance.

Genome sequencing and conservation genomics in the Scandinavian wolverine population.

Genetic approaches have proved valuable to the study and conservation of endangered populations, especially for monitoring programs, and there is potential for further developments in this direction by extending analyses to the genomic level. We assembled the genome of the wolverine (Gulo gulo), a mustelid that in Scandinavia has recently recovered from a significant population decline, and obtained a 2.42Gb draft sequence representing >85% of the genome and including >21,000protein-coding genes. We then performed whole-genome resequencing of 10Scandinavian wolverines for population genomic and demographic analyses. Genetic diversity was among the lowest detected in a red-listed population (mean genome-wide nucleotide diversity of 0.05%). Results of the demographic analyses indicated a long-term decline of the effective population size (Ne ) from 10,000well before the last glaciation to <500 after this period. Current Ne appeared even lower. The genome-wide FIS level was 0.089 (possibly signaling inbreeding), but this effect was not observed when analyzing a set of highly variable SNP markers, illustrating that such markers can give a biased picture of the overall character of genetic diversity. We found significant population structure, which has implications for population connectivity and conservation. We used an integrated microfluidic circuit chip technology to develop an SNP-array consisting of 96 highly informative markers that, together with a multiplex pre-amplification step, was successfully applied to low-quality DNA from scat samples. Our findings will inform management, conservation, and genetic monitoring of wolverines and serve as a genomic roadmap that can be applied to other endangered species. The approach used here can be generally utilized in other systems, but we acknowledge the trade-off between investing in genomic resources and direct conservation actions.

Outlier SNPs enable food traceability of the southern rock lobster, Jasus edwardsii

Recent advances in next-generation sequencing have enhanced the resolution of population genetic studies of non-model organisms through increased marker generation and sample throughput. Using double digest restriction site-associated DNA sequencing (ddRADseq), we investigated the population structure of the commercially important southern rock lobster, Jasus edwardsii, in Australia and New Zealand with the aim of identifying a panel of SNP markers that could be used to trace country of origin. Four ddRADseq libraries comprising a total of 88 individuals were sequenced on the Illumina MiSeq platform, and demultiplexed reads were used to create a reference catalog of loci. Individual reads were then mapped to the reference catalog, and variant calling was performed. We have characterized two single-nucleotide polymorphism (SNP) panels comprised in total of 656 SNPs. The first panel contained 535 neutral SNPs and the second, 121 outlier SNPs that were characteristic of being putatively under selection. Both neutral and outlier SNP panels showed significant differentiation between the two countries, with the outlier loci demonstrating much larger F ST values (F ST outlier SNP panel = 0.134, P < 0.0001; F ST neutral SNP panel = 0.022, P < 0.0001). Assignment tests performed with the outlier SNP panel allocated 100 % of the individuals to country of origin, demonstrating the usefulness of these markers for food traceability of J. edwardsii.

Use of genotyping by sequencing data to develop a high-throughput and multifunctional SNP panel for conservation applications in Pacific lamprey.

Next-generation sequencing data can be mined for highly informative single nucleotide polymorphisms (SNPs) to develop high-throughput genomic assays for nonmodel organisms. However, choosing a set of SNPs to address a variety of objectives can be difficult because SNPs are often not equally informative. We developed an optimal combination of 96 high-throughput SNP assays from a total of 4439 SNPs identified in a previous study of Pacific lamprey (Entosphenus tridentatus) and used them to address four disparate objectives: parentage analysis, species identification and characterization of neutral and adaptive variation. Nine of these SNPs are FST outliers, and five of these outliers are localized within genes and significantly associated with geography, run-timing and dwarf life history. Two of the 96 SNPs were diagnostic for two other lamprey species that were morphologically indistinguishable at early larval stages and were sympatric in the Pacific Northwest. The majority (85) of SNPs in the panel were highly informative for parentage analysis, that is, putatively neutral with high minor allele frequency across the species' range. Results from three case studies are presented to demonstrate the broad utility of this panel of SNP markers in this species. As Pacific lamprey populations are undergoing rapid decline, these SNPs provide an important resource to address critical uncertainties associated with the conservation and recovery of this imperiled species.

Guidelines for MSAT and SNP panels that lead to high-quality data for genetic mark–recapture studies

Molecular markers with inadequate power to discriminate among individuals can lead to false recaptures (shadows), and inaccurate genotyping can lead to missed recaptures (ghosts), potentially biasing genetic mark–recapture estimates. We used simulations to examine the impact of microsatellite (MSAT) and single nucleotide polymorphism (SNP) marker-set size, allelic frequency, multitubes approaches, and sample matching protocols on shadow and ghost events in genetic mark–recapture studies, presenting guidance on the specifications for MSAT and SNP marker panels, and sample matching protocols necessary to produce high-quality data. Shadow events are controllable by increasing the number of markers or by selecting markers with high discriminatory power; reasonably sized marker sets (e.g., ≥9 MSATs or ≥32 SNPs) of moderate allelic diversity lead to low probabilities of shadow errors. Ghost events are more challenging to control and low allelic dropout or false-allele error rates produced high rates of erroneous mismatches in mark–recapture sampling. Fortunately, error-tolerant matching protocols, which use information from positively matching loci between comparisons of samples, and multitubes protocols to achieve consensus genotypes are effective at eliminating ghost events. We present a case study on Pacific walrus, Odobenus rosmarus divergens (Illiger, 1815), using simulation results to inform genetic marker choices.

Comparison of genomic predictions using medium-density (∼54,000) and high-density (∼777,000) single nucleotide polymorphism marker panels in Nordic Holstein and Red Dairy Cattle populations

This study investigated genomic prediction using medium-density (∼54,000; 54K) and high-density marker panels (∼777,000; 777K), based on data from Nordic Holstein and Red Dairy Cattle (RDC). The Holstein data comprised 4,539 progeny-tested bulls, and the RDC data 4,403 progeny-tested bulls. The data were divided into reference data and test data using October 1, 2001, as a cut-off date (birth date of the bulls). This resulted in about 25% genotyped bulls in the Holstein test data and 20% in the RDC test data. For each breed, 3 data sets of markers were used to predict breeding values: (1) 54K data set with missing genotypes, (2) 54K data set where missing genotypes were imputed, and (3) imputed high-density (HD) marker data set created by imputing the 54K data to the HD data based on 557 bulls genotyped using a 777K single nucleotide polymorphism chip in Holstein, and 706 bulls in RDC. Based on the 3 marker data sets, direct genomic breeding values (DGV) for protein, fertility, and udder health were predicted using a genomic BLUP model (GBLUP) and a Bayesian mixture model with 2 normal distributions. Reliability of DGV was measured as squared correlations between deregressed proofs (DRP) and DGV corrected for reliability of DRP. Unbiasedness was assessed by regression of DRP on DGV, based on the bulls in the test data sets. Averaged over the 3 traits, reliability of DGV based on the HD markers was 0.5% higher than that based on the 54K data in Holstein, and 1.0% higher than that in RDC. In addition, the HD markers led to an improvement of unbiasedness of DGV. The Bayesian mixture model led to 0.5% higher reliability than the GBLUP model in Holstein, but not in RDC. Imputing missing genotypes in the 54K marker data did not improve genomic predictions for most of the traits.

Heterozygosity–fitness correlations in zebra finches: microsatellite markers can be better than their reputation

Numerous studies have reported associations between heterozygosity in microsatellite markers and fitness-related traits (heterozygosity-fitness correlations, HFCs). However, it has often been questioned whether HFCs reflect general inbreeding depression, because a small panel of microsatellite markers does not reflect very well an individual's inbreeding coefficient (F) as calculated from a pedigree. Here, we challenge this prevailing view. Because of chance events during Mendelian segregation, an individual's realized proportion of the genome that is identical by descent (IBD) may substantially deviate from the pedigree-based expectation (i.e. F). This Mendelian noise may result in a weak correlation between F and multi-locus heterozygosity, but this does not imply that multi-locus heterozygosity is a bad estimator of realized IBD. We examined correlations between 11 fitness-related traits measured in up to 1192 captive zebra finches and three measures of inbreeding: (i) heterozygosity across 11 microsatellite markers, (ii) heterozygosity across 1359 single-nucleotide polymorphism (SNP) markers and (iii) F, based on a 5th-generation pedigree. All 11 phenotypic traits showed positive relationships with measures of heterozygosity, especially traits that are most closely related to fitness. Remarkably, the small panel of microsatellite markers produced equally strong HFCs as the large panel of SNP markers. Both marker-based approaches produced stronger correlations with phenotypes than the pedigree-based F, and this did not seem to result from the shortness of our pedigree. We argue that a small panel of microsatellites with high allelic richness may better reflect an individual's realized IBD than previously appreciated, especially in species like the zebra finch, where much of the genome is inherited in large blocks that rarely experience cross-over during meiosis.

Autosomal linkage scan for loci predisposing to comorbid dependence on multiple substances

Multiple substance dependence (MSD) trait comorbidity is common, and MSD patients are often severely affected clinically. While shared genetic risks have been documented, so far there has been no published report using the linkage scan approach to survey risk loci for MSD as a phenotype. A total of 1,758 individuals in 739 families [384 African American (AA) and 355 European American (EA) families] ascertained via affected sib-pairs with cocaine or opioid or alcohol dependence were genotyped using an array-based linkage panel of single-nucleotide polymorphism markers. Fuzzy clustering analysis was conducted on individuals with alcohol, cannabis, cocaine, opioid, and nicotine dependence for AAs and EAs separately, and linkage scans were conducted for the output membership coefficients using Merlin-regression. In EAs, we observed an autosome-wide significant linkage signal on chromosome 4 (peak lod = 3.31 at 68.3 cM; empirical autosome-wide P = 0.038), and a suggestive linkage signal on chromosome 21 (peak lod = 2.37 at 19.4 cM). In AAs, four suggestive linkage peaks were observed: two peaks on chromosome 10 (lod = 2.66 at 96.7 cM and lod = 3.02 at 147.6 cM] and the other two on chromosomes 3 (lod = 2.81 at 145.5 cM) and 9 (lod = 1.93 at 146.8 cM). Three particularly promising candidate genes, GABRA4, GABRB1, and CLOCK, are located within or very close to the autosome-wide significant linkage region for EAs on chromosome 4. This is the first linkage evidence supporting existence of genetic loci influencing risk for several comorbid disorders simultaneously in two major US populations.

The Association of Genome-Wide Significant Spirometric Loci with Chronic Obstructive Pulmonary Disease Susceptibility

Two recent metaanalyses of genome-wide association studies conducted by the CHARGE and SpiroMeta consortia identified novel loci yielding evidence of association at or near genome-wide significance (GWS) with FEV(1) and FEV(1)/FVC. We hypothesized that a subset of these markers would also be associated with chronic obstructive pulmonary disease (COPD) susceptibility. Thirty-two single-nucleotide polymorphisms (SNPs) in or near 17 genes in 11 previously identified GWS spirometric genomic regions were tested for association with COPD status in four COPD case-control study samples (NETT/NAS, the Norway case-control study, ECLIPSE, and the first 1,000 subjects in COPDGene; total sample size, 3,456 cases and 1,906 controls). In addition to testing the 32 spirometric GWS SNPs, we tested a dense panel of imputed HapMap2 SNP markers from the 17 genes located near the 32 GWS SNPs and in a set of 21 well studied COPD candidate genes. Of the previously identified GWS spirometric genomic regions, three loci harbored SNPs associated with COPD susceptibility at a 5% false discovery rate: the 4q24 locus including FLJ20184/INTS12/GSTCD/NPNT, the 6p21 locus including AGER and PPT2, and the 5q33 locus including ADAM19. In conclusion, markers previously associated at or near GWS with spirometric measures were tested for association with COPD status in data from four COPD case-control studies, and three loci showed evidence of association with COPD susceptibility at a 5% false discovery rate.

Comprehensive family‐based association study of the glutamate transporter gene SLC1A1 in obsessive‐compulsive disorder

SLC1A1 encodes a neuronal glutamate transporter and is a promising candidate gene for obsessive-compulsive disorder (OCD). Several independent research groups have reported significant associations between OCD and single nucleotide polymorphisms (SNPs) in this gene. Previously, we evaluated 13 SNPs in, or near, SLC1A1 and reported a strong association signal with rs301443, a SNP 7.5 kb downstream of the gene [Shugart et al. (2009); Am J Med Genet Part B 150B:886–892]. The aims of the current study were first, to further investigate this finding by saturating the region around rs301443; and second, to explore the entire gene more thoroughly with a dense panel of SNP markers. We genotyped an additional 111 SNPs in or near SLC1A1, covering from 9 kb upstream to 84 kb downstream of the gene at average spacing of 1.7 kb per SNP, and conducted family-based association analyses in 1,576 participants in 377 families.We found that none of the surrounding markers were in linkage disequilibrium with rs301443, nor were any associated with OCD. We also found that SNP rs4740788, located about 8.8 kb upstream of the gene, was associated with OCD in all families (P = 0.003) and in families with male affecteds (P = 0.002). A three-SNP haplotype (rs4740788–rs10491734–rs10491733) was associated with OCD in the total sample (P = 0.00015) and in families with male affecteds (P = 0.0007). Although of nominal statistical significance considering the number of comparisons, these findings provide further support for the involvement of SLC1A1 in the pathogenesis of OCD.

Whole genome fine mapping of quantitative trait loci for ultrasound and carcass merit traits in beef cattle

Nalaila, S. M., Stothard, P., Moore, S. S., Wang, Z. and Li, C. 2011. Whole genome fine mapping of quantitative trait loci for ultrasound and carcass merit traits in beef cattle. Can. J. Anim. Sci. 91: 61–73. Quantitative trait loci (QTL) mapped to large chromosomal regions have limited utility as DNA markers for marker-assisted selection (MAS) and are less informative as a reference for the identification of the underlying causative quantitative trait nucleotides (QTN). The objective of this study was to conduct a whole genome fine mapping of QTL for ultrasound and carcass merit traits in beef cattle using a greater density of single nucleotide polymorphism (SNP) markers, and to identify SNP markers within the QTL regions that are associated with the traits. A total of 418 steers from 28 sires were used in this study with nine ultrasound and seven carcass merit traits that were collected as part of a feedlot trial conducted from 2003 to 2005 at the University of Alberta Kinsella ranch. Sires and their progeny were genotyped for a total of 4592 SNP markers distributed across all 29 bovine autosomes (BTA). Across-family analyses detected 12 QTL for five ultrasound traits on nine chromosomes and 18 QTL for six carcass merit traits on 10 chromosomes (P&lt;0.05). Within-family analyses identified 78 significant QTL for nine ultrasound and seven carcass merit traits (P&lt;0.01). The use of a denser panel of SNP markers allowed fine mapping of QTL to smaller chromosomal regions ranging from 0.6 to 11 cM compared with relatively larger QTL regions of 4 to 24 cM reported in previous studies. Furthermore, single SNP marker association analyses identified 22 SNPs that were significantly associated with three ultrasound and four carcass merit traits under 12 QTL regions (P&lt;0.05). These identified SNP markers significantly associated with the traits under the fine mapped QTL regions provide genomic tools for potential application of MAS and a reference to assist with the identification of QTN causing variations in ultrasound and carcass merit traits in beef cattle.

Nucleotide diversity maps reveal variation in diversity among wheat genomes and chromosomes.

BackgroundA genome-wide assessment of nucleotide diversity in a polyploid species must minimize the inclusion of homoeologous sequences into diversity estimates and reliably allocate individual haplotypes into their respective genomes. The same requirements complicate the development and deployment of single nucleotide polymorphism (SNP) markers in polyploid species. We report here a strategy that satisfies these requirements and deploy it in the sequencing of genes in cultivated hexaploid wheat (Triticum aestivum, genomes AABBDD) and wild tetraploid wheat (Triticum turgidum ssp. dicoccoides, genomes AABB) from the putative site of wheat domestication in Turkey. Data are used to assess the distribution of diversity among and within wheat genomes and to develop a panel of SNP markers for polyploid wheat.ResultsNucleotide diversity was estimated in 2114 wheat genes and was similar between the A and B genomes and reduced in the D genome. Within a genome, diversity was diminished on some chromosomes. Low diversity was always accompanied by an excess of rare alleles. A total of 5,471 SNPs was discovered in 1791 wheat genes. Totals of 1,271, 1,218, and 2,203 SNPs were discovered in 488, 463, and 641 genes of wheat putative diploid ancestors, T. urartu, Aegilops speltoides, and Ae. tauschii, respectively. A public database containing genome-specific primers, SNPs, and other information was constructed. A total of 987 genes with nucleotide diversity estimated in one or more of the wheat genomes was placed on an Ae. tauschii genetic map, and the map was superimposed on wheat deletion-bin maps. The agreement between the maps was assessed.ConclusionsIn a young polyploid, exemplified by T. aestivum, ancestral species are the primary source of genetic diversity. Low effective recombination due to self-pollination and a genetic mechanism precluding homoeologous chromosome pairing during polyploid meiosis can lead to the loss of diversity from large chromosomal regions. The net effect of these factors in T. aestivum is large variation in diversity among genomes and chromosomes, which impacts the development of SNP markers and their practical utility. Accumulation of new mutations in older polyploid species, such as wild emmer, results in increased diversity and its more uniform distribution across the genome.

Analysis on the interaction between IL-1F7 gene and environmental factors on patients with ankylosing spondylitis: a case-only study

To examine the interaction between IL-1F7 gene and environmental factors in patients with ankylosing spondylities (AS). 150 AS Han Chinese patients (all human leukocyte antigen-B27 positive) were genotyped using a panel of single-nucleotide polymorphism markers within IL-1F7 gene (rs3811047) by ligase detection reactions. Polymerase chain reaction with sequence-specific primer was used to determine HLA-B27 subtypes. We analyzed the interaction between IF-1F7 gene and eight environmental factors in AS patients by using a case-only study. The genetic polymorphism and environmental factors were considered as dependent variables in logistic models, and P-values, ORi and 95% confidence intervals were used for estimating the effects of interaction. The different frequency of A/G between drinking group and non-drinking group was significant (ORi 3.163, 95% CI 1.368-7.317, P=0.006). Within the cooking oil group, odds ratio for interaction of G×E between main plants fats and half plants -half animal fats subunits was 4.273 (95% CI 1.590-11.479, P=0.004). Our data show that there was no interaction between IL-1F7 alleles and the other six environmental factors in AS patients (all P>0.05). We observed that there was an interaction between IF-1F7 gene and drinking in AS patients. Thus, drinking may be a risk exposure factor to take combined action with predisposing genes in AS patients. This action may increase the incident risk of AS. Also, main plants fats may be protective factors to AS.

Discovery of single nucleotide polymorphism in Capsicum and SNP markers for cultivar identification

Molecular markers based on single nucleotide polymorphisms (SNPs) are abundant and evenly distributed in a whole genome enough to distinguish individuals in a population. In recent years, sets of SNP markers have been designed and applied for cultivar identification in various crop species. This paper is the first to report the development of a panel of SNP markers for variety identification in peppers. We used conserved ortholog set II (COSII) markers developed from conserved unigenes between tomato and Arabidopsis to identify SNPs in peppers. We tested 438 COSII primer sets amplified as single PCR products out of a total 600 COSII primer sets. Among the 438 COSII primers, 170 primer sets (38.8%) showed polymorphisms between Capsicum annuum ‘RNaky (RN)’and C. chinense ‘PI 159234 (234)’. In contrast, only 48 primer sets (11.0%) out of 438 primers sets were polymorphic between C. annuum ‘Perennial (PER), and ‘Dempsey (DEMP)’. The average frequency of SNPs plus InDels between C. annuum and C. chinense was 1/189 bp and between C. annuum spp. was 1/948 bp. Primer sets showing SNP between C. annuum PER and DEMP were re-designed to Allele Specific PCR (AS-PCR) primers and we finally selected a total of 40 SNP markers for cultivar identification. As the result, we were able to discriminate 97.5% of the 81 commercial hot cultivars and 100% of the 17 sweet pepper cultivars. We conclude the paper by discussing the use of the SNP marker set for cultivar identification and other applications.