Gene-based Single Nucleotide Polymorphisms Research Articles

ClPSY1 gene-based SNP markers identified from whole-genome resequencing for the determination of orange flesh color and carotenoid content in watermelon

Watermelon (Citrullus lanatus) is an economically important crop worldwide. The color of watermelon flesh is affected by the type and content of carotenoids. Carotenoids are high in antioxidants, which are associated with lower risk of various cancers and cardiovascular diseases and support visual function. Accordingly, the color of watermelon flesh is considered an important characteristic as it not only provides color diversity but also serves as the main motivator of consumer choice in terms of nutrition. Molecular markers have emerged as a powerful tool in plant breeding and the development of markers for selection of important traits and highly desirable. We previously identified genome-wide single nucleotide polymorphism (SNP) by performing whole-genome resequencing (WGRS) of 24 inbred watermelon lines with different flesh color traits (PRJNA516776). In this study, we proposed candidate genes for orange flesh color based on SNPs unique to orange flesh genotypes. One SNP in the phytoene synthase (ClPSY1) allele, which mediates the first step in carotenoid biosynthesis, was found to be associated with the orange color of watermelon flesh. Based on the polymorphism present in the ClPSY1 gene, we developed a molecular marker for predicting watermelon flesh color and confirmed the association of the SNP with orange flesh. This marker and markers derived from several other previously reported genes could be useful for the selective breeding of watermelons with a specific flesh color.

Genome-wide analyses using multi-locus models revealed marker-trait associations for major agronomic traits in Sorghum bicolor.

Globally, sorghum is the fifth most important cereal crop, and it is a major crop in Ethiopia, where it has a high genetic diversity. The country’s sorghum gene pool contributes significantly to sorghum improvement worldwide. This study aimed to identify genomic regions and candidate genes associated with major agronomic traits in sorghum by using its genetic resources in Ethiopia for a genome-wide association study (GWAS). Phenotypic data of days to flowering (DTF), plant height (PH), panicle length (PALH), panicle width (PAWD), panicle weight (PAWT), and grain yield (GY) were collected from a GWAS panel comprising 324 sorghum accessions grown in three environments. SeqSNP, a targeted genotyping method, was used to genotype the panel using 5,000 gene-based single nucleotide polymorphism (SNP) markers. For marker-trait association (MTA) analyses, fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) models were used. In all traits, high phenotypic variation was observed, with broad-sense heritability ranging from 0.32 (for GY) to 0.90 (for PALH). A population structure, principal component analysis, and kinship analysis revealed that the accessions could be divided into two groups. In total, 54 MTAs were identified, 11 of which were detected by both BLINK and farmCPU. MTAs identified for each trait ranged from five (PAWT and GY) to fourteen (PH) representing both novel and previously identified quantitative trait loci (QTLs). Three SNPs were associated with more than one trait, including a SNP within the Sobic.004G189200 gene that was associated with PH and PAWT. Major effect SNP loci, Sbi2393610 (PVE = 23.3%), Sbi10438246 (PVE = 35.2%), Sbi17789352 (PVE = 11.9%) and Sbi30169733 (PVE = 18.9%) on chromosomes 1, 3, 5 and 9 that showed strong association signals for PAWD, DTF, GY and PALH, respectively, were major findings of this study. The SNP markers and candidate genes identified in this study provide insights into the genetic control of grain yield and related agronomic traits, and once validated, the markers could be used in genomics-led breeding.

Genome-Wide Association Study (GWAS) Reveals an SNP Associated with Waxy Trait and Development of a Functional Marker for Predicting Waxy Maize (Zea mays L. var. ceratina)

Waxy maize (Zea mays L. var. ceratina) is a special type of maize characterized by a sticky texture when cooked, due to high amylopectin content in the endosperm. Waxy maize is popular in China and Southeast Asia for fresh consumption. Breeding strategies have been used to improve the quality of waxy maize, including hybrid breeding by crossing super sweet maize and waxy maize. However, the lack of a marker has limited the efficiency of breeding for the waxy trait, especially because the waxy allele is recessive. In this study, we conducted a genome-wide association study (GWAS) in an association panel consisting of 213 inbred lines and recombinant inbred lines (RILs) of field maize and waxy maize to identify loci associated with the waxy kernel phenotype. The genotypic data were 155,768 SNPs derived from the high-density 600 K maize genotyping array for single-nucleotide polymorphisms (SNPs). The GWAS results identified the qWx9 locus on chromosome 9 (25.06–25.18 Mb) associated with the trait. Based on the most significantly associated SNP (AX-90613979, −log10(P) = 6.8)), which was located on Wx1, a MassArray marker was developed and validated in a panel of 139 maize lines containing waxy maize and sweet maize with different amylose content. The newly developed marker had a significant association with amylose content (R2 value of 0.81, p < 0.001) and clearly distinguished between waxy maize and sweet maize lines that had different amylose content. This marker will be useful for maize breeding programs for the waxy trait, as well as for breeding programs for hybrid maize combining the sweetness and waxy traits. The gene-based SNP markers could aid breeders by eliminating the costs and time required to perform lengthy field trials and help to accelerate sweet maize and waxy maize breeding programs.

Identification of Secreted Protein Gene-Based SNP Markers Associated with Virulence Phenotypes of Puccinia striiformis f. sp. tritici, the Wheat Stripe Rust Pathogen.

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is a destructive disease that occurs throughout the major wheat-growing regions of the world. This pathogen is highly variable due to the capacity of virulent races to undergo rapid changes in order to circumvent resistance in wheat cultivars and genotypes and to adapt to different environments. Intensive efforts have been made to study the genetics of wheat resistance to this disease; however, no known avirulence genes have been molecularly identified in Pst so far. To identify molecular markers for avirulence genes, a Pst panel of 157 selected isolates representing 126 races with diverse virulence spectra was genotyped using 209 secreted protein gene-based single nucleotide polymorphism (SP-SNP) markers via association analysis. Nineteen SP-SNP markers were identified for significant associations with 12 avirulence genes: AvYr1, AvYr6, AvYr7, AvYr9, AvYr10, AvYr24, AvYr27, AvYr32, AvYr43, AvYr44, AvYrSP, and AvYr76. Some SP-SNPs were associated with two or more avirulence genes. These results further confirmed that association analysis in combination with SP-SNP markers is a powerful tool for identifying markers for avirulence genes. This study provides genomic resources for further studies on the cloning of avirulence genes, understanding the mechanisms of host–pathogen interactions, and developing functional markers for tagging specific virulence genes and race groups.

The generalized Fisher's combination and accurate p-value calculation under dependence.

Combining dependent tests of significance has broad applications but the related p-value calculation is challenging. For Fisher's combination test, current p-value calculation methods (eg, Brown's approximation) tend to inflate the type I error rate when the desired significance level is substantially less than 0.05. The problem could lead to significant false discoveries in big data analyses. This paper provides two main contributions. First, it presents a general family of Fisher type statistics, referred to as the GFisher, which covers many classic statistics, such as Fisher's combination, Good's statistic, Lancaster's statistic, weighted Z-score combination, and so forth. The GFisher allows a flexible weighting scheme, as well as an omnibus procedure that automatically adapts proper weights and the statistic-defining parameters to a given data. Second, the paper presents several new p-value calculation methods based on two novel ideas: moment-ratio matching and joint-distribution surrogating. Systematic simulations show that the new calculation methods are more accurate under multivariate Gaussian, and more robust under the generalized linear model and the multivariate t-distribution. The applications of the GFisher and the new p-value calculation methods are demonstrated by a gene-based single nucleotide polymorphism (SNP)-set association study. Relevant computation has been implemented to an R package GFisher available on the Comprehensive R ArchiveNetwork.

Genetic Diversity and Population Structure of Sorghum [Sorghum Bicolor (L.) Moench] Accessions as Revealed by Single Nucleotide Polymorphism Markers.

Ethiopia is the center of origin for sorghum [Sorghum bicolor (L.) Moench], where the distinct agro-ecological zones significantly contributed to the genetic diversity of the crops. A large number of sorghum landrace accessions have been conserved ex situ. Molecular characterization of this diverse germplasm can contribute to its efficient conservation and utilization in the breeding programs. This study aimed to investigate the genetic diversity of Ethiopian sorghum using gene-based single nucleotide polymorphism (SNP) markers. In total, 359 individuals representing 24 landrace accessions were genotyped using 3,001 SNP markers. The SNP markers had moderately high polymorphism information content (PIC = 0.24) and gene diversity (H = 0.29), on average. This study revealed 48 SNP loci that were significantly deviated from Hardy–Weinberg equilibrium with excess heterozygosity and 13 loci presumed to be under selection (P < 0.01). The analysis of molecular variance (AMOVA) determined that 35.5% of the total variation occurred within and 64.5% among the accessions. Similarly, significant differentiations were observed among geographic regions and peduncle shape-based groups. In the latter case, accessions with bent peduncles had higher genetic variation than those with erect peduncles. More alleles that are private were found in the eastern region than in the other regions of the country, suggesting a good in situ conservation status in the east. Cluster, principal coordinates (PCoA), and STRUCTURE analyses revealed distinct accession clusters. Hence, crossbreeding genotypes from different clusters and evaluating their progenies for desirable traits is advantageous. The exceptionally high heterozygosity observed in accession SB4 and SB21 from the western geographic region is an intriguing finding of this study, which merits further investigation.

Dissecting nematode resistance regions in soybean revealed pleiotropic effect of soybean cyst and reniform nematode resistance genes.

Reniform nematode (RN, Rotylenchulus reniformis Linford & Oliveira) has emerged as one of the most important plant parasitic nematodes of soybean [Glycine max (L.) Merr.]. Planting resistant varieties is the most effective strategy for nematode management. The objective of this study was to identify quantitative trait loci (QTL) for RN resistance in an exotic soybean line, PI 438489B, using two linkage maps constructed from the Universal Soybean Linkage Panel (USLP 1.0) and next-generation whole-genome resequencing (WGRS) technology. Two QTL controlling RN resistance were identified-the soybean cyst nematode (SCN, Heterodera glycines) resistance gene GmSNAP18 at the rhg1 locus and its paralog GmSNAP11. Strong association between resistant phenotype and haplotypes of the GmSNAP11 and GmSNAP18 was observed. The results indicated that GmSNAP11 possibly could have epistatic effect on GmSNAP18, or vice versa, with the presence of a significant correlation in RN resistance of rhg1-a GmSNAP18 vs. rhg1-b GmSNAP18. Most importantly, our preliminary data suggested that GmSNAP18 and GmSNAP11 proteins physically interact in planta, suggesting that they belong to the same pathway for resistance. Unlike GmSNAP18, no indication of GmSNAP11 copy number variation was found. Moreover, gene-based single nucleotide polymorphism (SNP) markers were developed for rapid detection of RN or SCN resistance at these loci. Our analysis substantiates synergic interaction between GmSNAP11 and GmSNAP18 genes and confirms their roles in RN as well as SCN resistance. These results could contribute to a better understanding of evolution and subfunctionalization of genes conferring resistance to multiple nematode species and provide a framework for further investigations.

Genome-wide identification of major genes and genomic prediction using high-density and text-mined gene-based SNP panels in Hanwoo (Korean cattle).

It was hypothesized that single-nucleotide polymorphisms (SNPs) extracted from text-mined genes could be more tightly related to causal variant for each trait and that differentially weighting of this SNP panel in the GBLUP model could improve the performance of genomic prediction in cattle. Fitting two GRMs constructed by text-mined SNPs and SNPs except text-mined SNPs from 777k SNPs set (exp_777K) as different random effects showed better accuracy than fitting one GRM (Im_777K) for six traits (e.g. backfat thickness: + 0.002, eye muscle area: + 0.014, Warner-Bratzler Shear Force of semimembranosus and longissimus dorsi: + 0.024 and + 0.068, intramuscular fat content of semimembranosus and longissimus dorsi: + 0.008 and + 0.018). These results can suggest that attempts to incorporate text mining into genomic predictions seem valuable, and further study using text mining can be expected to present the significant results.

Characterization of 337 exon-based single nucleotide polymorphisms (SNPs) unique to the Indonesian soybean varieties

Genome resequencing of five Indonesian soybean varieties resulted in a total of 2,597,286 single nucleotide polymorphisms (SNPs), 257,598 insertions, and 202,157 deletions. Out of those SNPs, only 95,207 (2.15%) were located in the protein-coding region (exon). The objective of this study was to characterize 337 exon-based SNPs unique to the Indonesian soybean varieties. The study was conducted by taking SNP samples located in the exons using criteria of gene fragments containing the SNPs that were sequenced at least five times within each of the soybean varieties. Out of 95,154 gene-based SNPs detected, only 337 SNPs met the criteria. Each of the soybean varieties was genotyped with the 337 SNP loci, and the genotypic data were scored and analyzed. Results showed that 59 SNPs were common to all five soybean genotypes. A total of 43, 41, 25, 32 and 28 SNPs loci were unique to soybean genotype Davros, Grobogan, Malabar, Tambora and B3293, respectively. These unique SNPs can function as DNA fingerprints for each variety. Out of 59 common SNPs, 24 SNPs were mutations that change the amino acid sequence of the encoded proteins. These genes with amino acid change may have high economic values such as those controlling soybean adaptation in tropical climate, photoperiod insensitivity, disease and insect resistance genes. Expression analyses of the genes with amino acid change showed variation in the expression pattern across different soybean tissues. Functional genomic analysis is necessary to isolate genes useful for breeding purposes.

Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping

BackgroundSalinity is an abiotic stress that negatively affects soybean [Glycine max (L.) Merr.] seed yield. Although a major gene for salt tolerance was identified and consistently mapped to chromosome (Chr.) 3 by linkage mapping studies, it does not fully explain genetic variability for tolerance in soybean germplasm. In this study, a genome-wide association study (GWAS) was performed to map genomic regions for salt tolerance in a diverse panel of 305 soybean accessions using a single nucleotide polymorphism (SNP) dataset derived from the SoySNP50K iSelect BeadChip. A second GWAS was also conducted in a subset of 234 accessions using another 3.7 M SNP dataset derived from a whole-genome resequencing (WGRS) study. In addition, three gene-based markers (GBM) of the known gene, Glyma03g32900, on Chr. 3 were also integrated into the two datasets. Salt tolerance among soybean lines was evaluated by leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC).ResultsFor both association studies, a major locus for salt tolerance on Chr. 3 was confirmed by a number of significant SNPs, of which three gene-based SNP markers, Salt-20, Salt14056 and Salt11655, had the highest association with all four traits studied. Also, additional genomic regions on Chrs. 1, 8, and 18 were found to be associated with various traits measured in the second GWAS using the WGRS-derived SNP dataset.ConclusionsA region identified on Chr. 8 was identified to be associated with all four traits and predicted as a new minor locus for salt tolerance in soybean. The candidate genes harbored in this minor locus may help reveal the molecular mechanism involved in salt tolerance and to improve tolerance in soybean cultivars. The significant SNPs will be useful for marker-assisted selection for salt tolerance in soybean breeding programs.

Multiple genotype\u2013phenotype association study reveals intronic variant pair on SIDT2 associated with metabolic syndrome in a Korean population

BackgroundMetabolic syndrome is a risk factor for type 2 diabetes and cardiovascular disease. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We also performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set.ResultsWe found an association between metabolic syndrome and an intronic SNP pair, rs7107152 and rs1242229, in SIDT2 gene at 11q23.3. Both SNPs correlate with the expression of SIDT2 and TAGLN, whose products promote insulin secretion and lipid metabolism, respectively. This SNP pair showed statistical significance at the replication stage.ConclusionsOur findings provide insight into an underlying mechanism that contributes to metabolic syndrome.

Functional Evaluation of ZNF350 Missense Genetic Variants Associated with Breast Cancer Susceptibility.

ZNF350, a BRCA1-interacting protein, could mediate BRCA1-induced sequence-specific transcriptional repression of several genes, including GADD45α. As a potential breast cancer susceptibility gene, single nucleotide polymorphisms (SNPs), especially missense SNPs, may influence the transcriptional repression of its target tumor suppressor genes and individuals' breast cancer risk. Using the gene-based haplotype-tagging SNPs strategy, we evaluated the association between six ZNF350 polymorphisms and breast cancer risk in a case-control set from a northern Chinese population. The impact of ZNF350 variations on transcriptional repression of GADD45α was also examined. It was found that ZNF350 rs2278420 (L66P) and rs2278415 (S501R) missense genetic variants are in complete linkage disequilibrium and have a significant impact on inter-individual susceptibility to breast cancer. Additionally, ZNF350 GGCGT or GGCGC haplotype is also associated with a significantly increased breast cancer risk compared with the GGCAC haplotype. ZNF350 L66P variant modifies the risk of breast cancer not only by itself but also in a gene-environment interaction manner with age, age at menarche, menopause status, or estrogen receptor status. Interestingly, we observed that ZNF350 L66P and S501R SNPs could weaken the capability of ZNF350-mediated GADD45α transcription repression and it may be an underlying mechanism of the observed epidemiological associations. Our results highlight ZNF350 as an important gene in human mammary oncogenesis and ZNF350 missense genetic polymorphisms confer susceptibility to breast cancer.

Genome-wide association of yield traits in a nested association mapping population of barley reveals new gene diversity for future breeding.

To explore wild barley as a source of useful alleles for yield improvement in breeding, we have carried out a genome-wide association scan using the nested association mapping population HEB-25, which contains 25 diverse exotic barley genomes superimposed on an ~70% genetic background of cultivated barley. A total of 1420 HEB-25 lines were trialled for nine yield-related grain traits for 2 years in Germany and Scotland, with varying N fertilizer application. The phenotypic data were related to genotype scores for 5398 gene-based single nucleotide polymorphism (SNP) markers. A total of 96 quantitative trait locus (QTL) regions were identified across all measured traits, the majority of which co-localize with known major genes controlling flowering time (Ppd-H2, HvCEN, HvGI, VRN-H1, and VRN-H3) and spike morphology (VRS3, VRS1, VRS4, and INT-C) in barley. Fourteen QTL hotspots, with at least three traits coinciding, were also identified, several of which co-localize with barley orthologues of genes controlling grain dimensions in rice. Most of the allele effects are specific to geographical location and/or exotic parental genotype. This study shows the existence of beneficial alleles for yield-related traits in exotic barley germplasm and provides candidate alleles for future improvement of these traits by the breeder.

Genome-Wide Association Analysis of Grain Yield-Associated Traits in a Pan-European Barley Cultivar Collection.

A collection of 379 Hordeum vulgare cultivars, comprising all combinations of spring and winter growth habits with two and six row ear type, was screened by genome wide association analysis to discover alleles controlling traits related to grain yield. Genotypes were obtained at 6,810 segregating gene-based single nucleotide polymorphism (SNP) loci and corresponding field trial data were obtained for eight traits related to grain yield at four European sites in three countries over two growth years. The combined data were analyzed and statistically significant associations between the traits and regions of the barley genomes were obtained. Combining this information with the high resolution gene map for barley allowed the identification of candidate genes underlying all scored traits and superposition of this information with the known genomics of grain trait genes in rice resulted in the assignation of 13 putative barley genes controlling grain traits in European cultivated barley. Several of these genes are associated with grain traits in both winter and spring barley.

The SNP-set based association study identifies ITGA1 as a susceptibility gene of attention-deficit/hyperactivity disorder in Han Chinese

Genome-wide association studies, which detect the association between single-nucleotide polymorphisms (SNPs) and disease susceptibility, have been extensively applied to study attention-deficit/hyperactivity disorder (ADHD), but genome-wide significant associations have not been found yet. Genetic heterogeneity and insufficient genomic coverage may account for the missing heritability. We performed a two-stage association study for ADHD in the Han Chinese population. In the discovery stage, 1033 ADHD patients and 950 healthy controls were genotyped using both the Affymetrix Genome-Wide Human SNP Array 6.0 and the Illumina Infinium HumanExome BeadChip. The genotyped SNPs were combined to generate a powerful SNP set with better genomic coverage especially for the nonsynonymous variants. In addition to the association of single SNPs, we collected adjacent SNPs as SNP sets, which were determined by either genes or successive sliding windows, to evaluate their synergetic effect. The candidate susceptibility SNPs were further replicated in an independent cohort of 1441 ADHD patients and 1447 healthy controls. No genome-wide significant SNPs or gene-based SNP sets were found to be associated with ADHD. However, two continuous sliding windows located in ITGA1 (P-value=8.33E−7 and P-value=8.43E−7) were genome-wide significant. The quantitative trait analyses also demonstrated their association with ADHD core symptoms and executive functions. The association was further validated by follow-up replications for four selected SNPs: rs1979398 (P-value=2.64E−6), rs16880453 (P-value=3.58E−4), rs1531545 (P-value=7.62E−4) and rs4074793 (P-value=2.03E−4). Our results suggest that genetic variants in ITGA1 may be involved in the etiology of ADHD and the SNP-set based analysis is a promising strategy for the detection of underlying genetic risk factors.

GENOMIC VARIATION OF FIVE INDONESIAN CACAO (Theobroma cacao L.) VARIETIES BASED ON ANALYSIS USING NEXT GENERATION SEQUENCING

&lt;p class="abstrakInggris"&gt;&lt;span&gt;Indonesian cacao productivity is still low mainly due to the lack availability of superior cacao planting materials. A new breeding method is necessary to expedite cacao yield improvement programs. To date, no study has yet been done to characterize Indonesian cacao varieties at the whole genome level. The objective of this study was to characterize genomic variation of five superior Indonesian cacao varieties using next-generation sequencing. Genetic materials used were five Indonesian cacao varieties, i.e. ICCRI2, ICCRI3, ICCRI4, SUL2 and ICS13. Genome sequences were mapped to the cacao reference genome sequence of Criollo variety. Sequence alignment and genomic variation discovery were done using Bowtie2 and mpileup software of Samtools, respectively. A total of 2,326,088 single nucleotide polymorphisms (SNPs) and 362,081 insertions and deletions (Indels) were obtained from this study. In average, a DNA variant was identified in every 121 nucleotides of the genome sequence. Most of the DNA variants were located outside the genes. Only 347,907 SNPs and Indels (13.18%) were located within protein coding region (exon). Among the DNA variations within exon, 188,949 SNPs caused missense mutation and 1,535 SNPs induced nonsense mutation. Unique gene-based SNPs were also discovered from this study that can be used as fingerprints for the particular cacao variety. The DNA variants obtained were excellent DNA marker resources to support cacao breeding programs. The SNPs discovered are useful as materials for genome-wide SNP chip development to be used for gene and QTL tagging of important traits for expediting national cacao breeding program.&lt;/span&gt;&lt;/p&gt;

A saturated SNP linkage map for the orange wheat blossom midge resistance gene Sm1.

SNP markers were developed for the OWBM resistance gene Sm1 that will be useful for MAS. The wheat Sm1 region is collinear with an inverted syntenic interval in B. distachyon. Orange wheat blossom midge (OWBM, Sitodiplosis mosellana Géhin) is an important insect pest of wheat (Triticum aestivum) in many growing regions. Sm1 is the only described OWBM resistance gene and is the foundation of managing OWBM through host genetics. Sm1 was previously mapped to wheat chromosome arm 2BS relative to simple sequence repeat (SSR) markers and the dominant, sequence characterized amplified region (SCAR) marker WM1. The objectives of this research were to saturate the Sm1 region with markers, develop improved markers for marker-assisted selection (MAS), and examine the synteny between wheat, Brachypodium distachyon, and rice (Oryza sativa) in the Sm1 region. The present study mapped Sm1 in four populations relative to single nucleotide polymorphisms (SNPs), SSRs, Diversity Array Technology (DArT) markers, single strand conformation polymorphisms (SSCPs), and the SCAR WM1. Numerous high quality SNP assays were designed that mapped near Sm1. BLAST delineated the syntenic intervals in B. distachyon and rice using gene-based SNPs as query sequences. The Sm1 region in wheat was inverted relative to B. distachyon and rice, which suggests a chromosomal rearrangement within the Triticeae lineage. Seven SNPs were tested on a collection of wheat lines known to carry Sm1 and not to carry Sm1. Sm1-flanking SNPs were identified that were useful for predicting the presence or absence of Sm1 based upon haplotype. These SNPs will be a major improvement for MAS of Sm1 in wheat breeding programs.

High-density linkage mapping and distribution of segregation distortion regions in the oak genome.

We developed the densest single-nucleotide polymorphism (SNP)-based linkage genetic map to date for the genus Quercus. An 8k gene-based SNP array was used to genotype more than 1,000 full-sibs from two intraspecific and two interspecific full-sib families of Quercus petraea and Quercus robur. A high degree of collinearity was observed between the eight parental maps of the two species. A composite map was then established with 4,261 SNP markers spanning 742 cM over the 12 linkage groups (LGs) of the oak genome. Nine genomic regions from six LGs displayed highly significant distortions of segregation. Two main hypotheses concerning the mechanisms underlying segregation distortion are discussed: genetic load vs. reproductive barriers. Our findings suggest a predominance of pre-zygotic to post-zygotic barriers.

Gene-based aggregate SNP associations between candidate AD genes and cognitive decline.

Single nucleotide polymorphisms (SNPs) in and near ABCA7, BIN1, CASS4, CD2AP, CD33, CELF1, CLU, complement receptor 1 (CR1), EPHA1, EXOC3L2, FERMT2, HLA cluster (DRB5-DQA), INPP5D, MEF2C, MS4A cluster (MS4A3-MS4A6E), NME8, PICALM, PTK2B, SLC24A4, SORL1, and ZCWPW1 have been associated with Alzheimer's disease (AD) in large meta-analyses. We aimed to determine whether established AD-associated genes are associated with longitudinal cognitive decline by examining aggregate variation across these gene regions. In two single-sex cohorts of older, community-dwelling adults, we examined the association between SNPs in previously implicated gene regions and cognitive decline (age-adjusted person-specific cognitive slopes) using a Sequence Kernel Association Test (SKAT). In regions which showed aggregate significance, we examined the univariate association between individual SNPs in the region and cognitive decline. Only two of the original AD-associated SNPs were significantly associated with cognitive decline in our cohorts. We identified significant aggregate-level associations between cognitive decline and the gene regions BIN1, CD33, CELF1, CR1, HLA cluster, and MEF2C in the all-female cohort and significant associations with ABCA7, HLA cluster, MS4A6E, PICALM, PTK2B, SLC24A4, and SORL1 in the all-male cohort. We also identified a block of eight correlated SNPs in CD33 and several blocks of correlated SNPs in CELF1 that were significantly associated with cognitive decline in univariate analysis in the all-female cohort.

Gene-based SNP discovery in tepary bean (Phaseolus acutifolius) and common bean (P. vulgaris) for diversity analysis and comparative mapping.

BackgroundCommon bean (Phaseolus vulgaris) is an important grain legume and there has been a recent resurgence in interest in its relative, tepary bean (P. acutifolius), owing to this species’ ability to better withstand abiotic stresses. Genomic resources are scarce for this minor crop species and a better knowledge of the genome-level relationship between these two species would facilitate improvement in both. High-throughput genotyping has facilitated large-scale single nucleotide polymorphism (SNP) identification leading to the development of molecular markers with associated sequence information that can be used to place them in the context of a full genome assembly.ResultsTranscript-based SNPs were identified from six common bean and two tepary bean accessions and a subset were used to generate a 768-SNP Illumina GoldenGate assay for each species. The tepary bean assay was used to assess diversity in wild and cultivated tepary bean and to generate the first gene-based map of the tepary bean genome. Genotypic analyses of the diversity panel showed a clear separation between domesticated and cultivated tepary beans, two distinct groups within the domesticated types, and P. parvifolius was confirmed to be distinct. The genetic map of tepary bean was compared to the common bean genome assembly to demonstrate high levels of collinearity between the two species with differences limited to a few intra-chromosomal rearrangements.ConclusionsThe development of the first set of genomic resources specifically for tepary bean has allowed for greater insight into the structure of this species and its relationship to its agriculturally more prominent relative, common bean. These resources will be helpful in the development of efficient breeding strategies for both species and will facilitate the introgression of agriculturally important traits from one crop into the other.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2499-3) contains supplementary material, which is available to authorized users.