Single Nucleotide Polymorphism Map Research Articles

Allele-specific binding (ASB) analyzer for annotation of allele-specific binding SNPs

BackgroundAllele-specific binding (ASB) events occur when transcription factors (TFs) bind more favorably to one of the two parental alleles at heterozygous single nucleotide polymorphisms (SNPs). Evidence suggests that ASB events could reveal the impact of sequence variations on TF binding and may have implications for the risk of diseases.ResultsHere we present ASB-analyzer, a software platform that enables the users to quickly and efficiently input raw sequencing data to generate individual reports containing the cytogenetic map of ASB SNPs and their associated phenotypes. This interactive tool thereby combines ASB SNP identification, biological annotation, motif analysis, phenotype associations and report summary in one pipeline. With this pipeline, we identified 3772 ASB SNPs from thirty GM12878 ChIP-seq datasets and demonstrated that the ASB SNPs were more likely to be enriched at important sites in TF-binding domains.ConclusionsASB-analyzer is a user-friendly tool that enables the detection, characterization and visualization of ASB SNPs. It is implemented in Python, R and bash shell and packaged in the Conda environment. It is available as an open-source tool on GitHub at https://github.com/Liying1996/ASBanalyzer.

Genetic architecture of quantitative trait loci (QTL) for FHB resistance and agronomic traits in a hard winter wheat population

Wheat resistance to Fusarium head blight (FHB) has often been associated with some undesirable agronomic traits. To study the relationship between wheat FHB resistance and agronomic traits, we constructed a linkage map of single nucleotide polymorphisms (SNPs) using an F6:8 population from G97252W × G97380A. The two hard winter wheat parents showed contrasts in FHB resistance, plant height (HT), heading date (HD), spike length (SL), spike compactness (SC), kernel number per spike (KNS), spikelet number per spike (SNS), thousand-grain weight (TGW) and grain size (length and width). Quantitative trait locus (QTL) mapping identified one major QTL (QFhb.hwwg-2DS) on chromosome arm 2DS for the percentage of symptomatic spikelets (PSS) in the spike, deoxynivalenol (DON) content and Fusarium damaged kernel (FDK). This QTL explained up to 71.8% of the phenotypic variation for the three FHB-related traits and overlapped with the major QTL for HT, HD, SL, KNS, SNS, TGW, and grain size. QTL on chromosome arms 2AL, 2DS, 3AL and 4BS were significant for the spike and grain traits measured. G97252W contributed FHB resistance and high SNS alleles at QFhb.hwwg-2DS, high KNS alleles at the QTL on 2AL and 2DS, and high TGW and grain size alleles at QTL on 3AL; whereas G97380A contributed high TGW and grain size alleles at the QTL on 2AL and 2DS, respectively, and the high KNS allele at the 4BS QTL. Combining QFhb.hwwg-2DS with positive alleles for spike and grain traits from other chromosomes may simultaneously improve FHB resistance and grain yield in new cultivars.

A multi-omic Nicotiana benthamiana resource for fundamental research and biotechnology

Nicotiana benthamiana is an invaluable model plant and biotechnology platform with a ~3 Gb allotetraploid genome. To further improve its usefulness and versatility, we have produced high-quality chromosome-level genome assemblies, coupled with transcriptome, epigenome, microRNA and transposable element datasets, for the ubiquitously used LAB strain and a related wild accession, QLD. In addition, single nucleotide polymorphism maps have been produced for a further two laboratory strains and four wild accessions. Despite the loss of five chromosomes from the ancestral tetraploid, expansion of intergenic regions, widespread segmental allopolyploidy, advanced diploidization and evidence of recent bursts of Copia pseudovirus (Copia) mobility not seen in other Nicotiana genomes, the two subgenomes of N. benthamiana show large regions of synteny across the Solanaceae. LAB and QLD have many genetic, metabolic and phenotypic differences, including disparate RNA interference responses, but are highly interfertile and amenable to genome editing and both transient and stable transformation. The LAB/QLD combination has the potential to be as useful as the Columbia-0/Landsberg errecta partnership, utilized from the early pioneering days of Arabidopsis genomics to today.

Molecular characterization and SNP identification using genotyping-by-sequencing in high-yielding mutants of proso millet.

Proso millet (Panicummiliaceum L.) is a short-duration C4 crop that is drought tolerant and nutritionally rich and can grow well in marginal lands. Though the crop has many climate-resilient traits like tolerance to drought and heat, its yield is lower than that of common cereals like rice, wheat, and maize. Being an underutilized crop, the molecular resources in the crop are limited. The main aim of the present study was to develop and characterize contrasting mutants for yield and generate functional genomic information for the trait in proso millet. Gamma irradiation-induced mutant population was screened to identify high-yielding mutants, which were evaluated up to M4 generation. One mutant with a dense panicle and high yield (ATL_hy) and one with a lax panicle and low yield (ATL_ly) along with the wild type were sequenced using the genotyping-by-sequencing approach. The variants detected as single nucleotide polymorphisms (SNPs) and insertions-deletions (InDels) were annotated against the reference genome of proso millet. Bioinformatic analyses using the National Center for Biotechnology Information (NCBI) and UniProt databases were performed to elucidate genetic information related to the SNP variations. A total of 25,901, 30,335, and 31,488 SNPs, respectively, were detected in the wild type, ATL_hy mutants, and ATL_ly mutants. The total number of functional SNPs identified in high-yielding and low-yielding mutants was 84 and 171, respectively. Two functional SNPs in the high-yielding mutant (ATL_hy) and one in the low-yielding mutant (ATL_ly) corresponded to the gene coding for "E3 ubiquitin-protein ligase UPL7". Pathway mapping of the functional SNPs identified that two SNPs in ATL_ly were involved in the starch biosynthetic pathway coding for the starch synthase enzyme. This information can be further used in identifying genes responsible for various metabolic processes in proso millet and in designing useful genetic markers.

Advances in genomics for diversity studies and trait improvement in temperate fruit and nut crops under changing climatic scenarios.

Genetic improvement of temperate fruit and nut crops through conventional breeding methods is not sufficient alone due to its extreme time-consuming, cost-intensive, and hard-to-handle approach. Again, few other constraints that are associated with these species, viz., their long juvenile period, high heterozygosity, sterility, presence of sexual incompatibility, polyploidy, etc., make their selection and improvement process more complicated. Therefore, to promote precise and accurate selection of plants based on their genotypes, supplement of advanced biotechnological tools, viz., molecular marker approaches along with traditional breeding methods, is highly required in these species. Different markers, especially the molecular ones, enable direct selection of genomic regions governing the trait of interest such as high quality, yield, and resistance to abiotic and biotic stresses instead of the trait itself, thus saving the overall time and space and helping screen fruit quality and other related desired traits at early stages. The availability of molecular markers like SNP (single-nucleotide polymorphism), DArT (Diversity Arrays Technology) markers, and dense molecular genetic maps in crop plants, including fruit and nut crops, led to a revelation of facts from genetic markers, thus assisting in precise line selection. This review highlighted several aspects of the molecular marker approach that opens up tremendous possibilities to reveal valuable information about genetic diversity and phylogeny to boost the efficacy of selection in temperate fruit crops through genome sequencing and thus cultivar improvement with respect to adaptability and biotic and abiotic stress resistance in temperate fruit and nut species.

Genetic Dissection and Germplasm Selection of the Low Crude Fiber Component in Brassica napus L. Shoots.

Brassica napus is one of the most important oil crops in the world, and B. napus shoots are nutrient-rich fresh vegetables. The crude fiber (CF) component is one of the most important factors affecting the taste quality of B. napus shoots, but the factors underlying the desirable low-CF trait remain poorly understood. In this study, a high-density single-nucleotide polymorphism (SNP) map was used to map quantitative trait loci (QTLs) for five CF-related traits in a recombinant inbred population. A total of 49 QTLs were obtained in four environments, including eleven, twelve, eight, twelve and six QTLs for content of neutral detergent fiber, acid detergent fiber, acid detergent lignin, hemicellulose and cellulose, respectively. The phenotypic variation explained by single QTL ranged from 4.62% to 14.76%. Eight of these QTLs were further integrated into four unique QTLs, which controlled two different traits simultaneously. Five CF-component-related candidate genes were identified, among which BnaC03g07110D and BnaC07g21271D were considered to be the most likely candidate genes. In addition, five lines with low CF content were selected, which can be used as excellent germplasm resources in breeding. The QTLs identified in this study will contribute to our understanding of the genetic mechanism of CF and can be used as targets for reducing CF content in B. napus shoots. In addition, this study also provided excellent germplasm resources for low CF content breeding.

Quantitative trait locus mapping for important yield traits of a sorghum-sudangrass hybrid using a high-density single nucleotide polymorphism map.

The sorghum-sudangrass hybrid is a vital gramineous herbage.The F2 population was obtained to clarify genetic regularities among the traits of sorghum-sudangrass hybrids by bagging and selfing in the F1 generation using 'scattered ear sorghum' and 'red hull sudangrass.' This hybrid combines the characteristics of the strong resistance of parents, high yield, and good palatability and has clear heterosis. A thorough understanding of the genetic mechanisms of yield traits in sorghum-sudangrass hybrids is essential in improving their yield. Therefore, we conducted quantitative trait locus (QTL) mapping for plant height, stem diameter, tiller number, leaf number, leaf length, leaf width, and fresh weight of each plant in three different environments, using a high-density genetic linkage map based on single nucleotide polymorphism markers previously constructed by our team. A total of 55 QTLs were detected, uniformly distributed over the 10 linkage groups (LGs), with logarithm of odds values ranging between 2.5 and 7.1, which could explain the 4.9-52.44% phenotypic variation. Furthermore, 17 yield-related relatively high-frequency QTL (RHF-QTL) loci were repeatedly detected in at least two environments, with an explanatory phenotypic variation of 4.9-30.97%. No RHF-QTLs were associated with the tiller number. The genes within the confidence interval of RHF-QTL were annotated, and seven candidate genes related to yield traits were screened. Three QTL sites overlapping or adjacent to previous studies were detected by comparative analysis. We also found that QTL was enriched and that qLL-10-1 and qFW-10-4 were located at the same location of 25.81 cM on LG10. The results of this study provide a foundation for QTL fine mapping, candidate gene cloning, and molecular marker-assisted breeding of sorghum-sudangrass hybrids.

Body surface area is a potential obesity index: Its genetic determination and its causality for later-life diseases.

This study aimedto identify novel genetic factors that contribute to body surface area (BSA) and explore its relationship with complex traits and diseases. Based on more than 330,000 European individuals in the UK Biobank, the first large-scale genome-wide association study for BSA was performed. Comprehensive genetic analysis and enrichment analysis were then performed to explore the biological function of the identified loci. The genetic correlations and causal associations between BSA and other anthropometry parameters, early growth indices, and later-life diseases, respectively, were assessed by complex genetic approaches. Genome-wide association study analysis identified a total of 456 conditionally independent single-nucleotide polymorphism mapping genes with known functions in the regulation of adipogenesis and metabolism and enriched in adipogenesis-related pathways. BSA was highly genetically correlated with obesity phenotypes, and all the studied anthropometry parameters from the UK Biobank were significantly positively associated with BSA. BSA was phenotypically associated with 13 chronic diseases and genetically associated with 6 diseases. Mendelian randomization analyses showed that BSA has a causal effect in increasing the risk of some diseases. These findings increase understanding of genetic determinants for BSA and its relationship with complex traits and diseases, and BSA could be regarded as a potential obesity trait.

The association between vitamin D receptor polymorphism and phases of chronic hepatitis B infection in HBV carriers in Thailand.

Vitamin D receptor (VDR) polymorphism partly regulates the immune system and is associated with hepatic flare in chronic Hepatitis B virus infection (HBV). Our study identified the association between two distinct phases, VDR polymorphisms and HBV inactive carrier (IC) and chronic hepatitis (CH). Chronic HBV patients were enrolled from February to August 2020. An HBV viral load (VL) < 2,000 IU/ml twice for 6 months apart, with no prior history of HBV treatment, defined the IC phase. Six common polymorphisms in the VDR gene, including CdX-2, GATA, FokI, Bsml, ApaI, and TaqI, were studied using real-time PCR. The different outcomes in allele, genotype, and haplotype frequencies in between groups and linkage disequilibrium (LD) mapping were analyzed. Among 324 enrolled patients, there were 163 patients in IC and 161 patients in CH phases. The mean vitamin D levels were not statistically different between groups. The proportion of allele frequencies of CdX-2 in IC and CH was 53.7% and 62.7% for G allele, and 46.3% and 37.3% for A allele (p 0.019). The proportion of GG genotype of CdX-2 was less frequently found in patients with IC compared to that in patients with CH (27% vs 41%, p 0.028). By multivariate analysis, CdX-2 G/A genotypes were independently associated with IC, with adjusted odd ratio (OR) 1.83 (1.10-3.04), p 0.019. The LD mapping of single nucleotide polymorphisms (SNP) revealed high LD scores in Bsml/ApaI/TaqI (BAT) haplotype in both groups while, CdX-2/GATA and GATA/FokI demonstrated high LD score only in CH group. CdX-2 G/A genotypes were independently associated with IC status in Thai patients with chronic HBV infection. The difference in LD of the CdX-2/GATA and GATA/FokI haplotypes in between groups may represent a non-random selection resulting in the variation of immune control.

Identification of loci governing soybean seed protein content via genome-wide association study and selective signature analyses.

Soybean [Glycine max (L.) Merr.] is an excellent source of protein. Understanding the genetic basis of protein content (PC) will accelerate breeding efforts to increase soybean quality. In the present study, a genome-wide association study (GWAS) was applied to detect quantitative trait loci (QTL) for PC in soybean using 264 re-sequenced soybean accessions and a high-quality single nucleotide polymorphism (SNP) map. Eleven QTL were identified as associated with PC. The QTL qPC-14 was detected by GWAS in both environments and was shown to have undergone strong selection during soybean improvement. Fifteen candidate genes were identified in qPC-14, and three candidate genes showed differential expression between a high-PC and a low-PC variety during the seed development stage. The QTL identified here will be of significant use in molecular breeding efforts, and the candidate genes will play essential roles in exploring the mechanisms of protein biosynthesis.

Construction of a single nucleotide polymorphism linkage map and identification of quantitative trait loci controlling heat tolerance in cowpea, Vigna unguiculata (L.) Walp.

Plant tolerance to heat or high temperature is crucial to crop production, especially in the situation of elevated temperature resulting from global climate change. Cowpea, Vigna unguiculata (L.) Walp., is an internationally important legume food crop and an excellent pool of genes for numerous traits resilient to environmental extremes, particularly heat and drought. Here, we report a single nucleotide polymorphism (SNP) genetic map for cowpea and identification of the loci controlling the heat tolerance in the species. The SNP map consists of 531 bins containing 4,154 SNPs grouped into 11 linkage groups, and collectively spans 1,084.7cM, thus having a density of one SNP in 0.26cM or 149kb. The 11 linkage groups of the map were aligned to the 11 cowpea chromosomes. Quantitative trait locus (QTL) mapping identified nine QTLs responsible for the cowpea heat tolerance on seven of the 11 chromosomes, with each QTL explaining 6.5-21.8% of heat tolerance phenotypic variation. Moreover, we aligned these nine QTLs to the cowpea genome. Each of the QTLs was positioned in a genomic region ranging from 209,000bp to 12,590,450bp, and the QTL with the largest effect (21.8%) on heat tolerance, qHT4-1, was located within an interval of only 234,195bp. These results provide SNP markers useful for marker-assisted selection for heat tolerance and lay a foundation for cloning, characterization, and applications of the genes controlling the cowpea heat tolerance for heat tolerance genetic improvement in cowpea and related crops.

Characterizing Fractal Genetic Variation in the Human Genome from the Hapmap Project.

Over the last decades, the exuberant development of next-generation sequencing has revolutionized gene discovery. These technologies have boosted the mapping of single nucleotide polymorphisms (SNPs) across the human genome, providing a complex universe of heterogeneity characterizing individuals worldwide. Fractal dimension (FD) measures the degree of geometric irregularity, quantifying how "complex" a self-similar natural phenomenon is. We compared two FD algorithms, box-counting dimension (BCD) and Higuchi's fractal dimension (HFD), to characterize genome-wide patterns of SNPs extracted from the HapMap data set, which includes data from 1184 healthy subjects of eleven populations. In addition, we have used cluster and classification analysis to relate the genetic distances within chromosomes based on FD similarities to the geographical distances among the 11 global populations. We found that HFD outperformed BCD at both grand average clusterization analysis by the cophenetic correlation coefficient, in which the closest value to 1 represents the most accurate clustering solution (0.981 for the HFD and 0.956 for the BCD) and classification (79.0% accuracy, 61.7% sensitivity, and 96.4% specificity for the HFD with respect to 69.1% accuracy, 43.2% sensitivity, and 94.9% specificity for the BCD) of the 11 populations present in the HapMap data set. These results support the evidence that HFD is a reliable measure helpful in representing individual variations within all chromosomes and categorizing individuals and global populations.

The Causal Relationships Between Sleep-related Phenotypes and Body Composition: A Mendelian Randomized Study.

Despite cumulative evidence showing obesity is associated with changes in sleep quality and quantity, the study about the relationships between sleep and body composition is scarce, and whether the relationship is causal remains unknown. In this study, we examined whether there are causal associations between sleep and body composition. First, we estimated genetic correlations between sleep-related phenotypes and body composition using the linkage disequilibrium score regression (LDSC). Mendelian randomization (MR) analysis was then conducted to test 2-way causal relationships on phenotypes with significant genetic associations. Finally, Bayesian colocalization (COLOC) analysis was performed to calculate the posterior probability of causal variation and identify the common genes to verify the results of MR. For the LDSC analysis, we observed some significant genetic correlations (rG), such as snoring and right leg fat mass (rG = 0.376, P = 7.21 × 10-80). For the MR analysis, we identified some significant causal relationships, such as snoring is the causal risk factor for whole-body fat-free mass (Pweighted median = 1.28 × 10-6, PMR-PRESSO = 1.35 × 10-7), dozing is the causal risk factor for right leg fat mass (Pweighted median = 9.22 × 10-4, PMR-PRESSO = 9.55 × 10-4), and right arm fat mass (Pweighted median = 1.11 × 10-40, PMR-PRESSO = 4.93 × 10-55) is the causal risk factor for snoring. For the COLOC analysis, we identified rs143384 mapping on GDF5 and 6 overlapped single nucleotide polymorphisms (eg, rs1421085, rs11642015) mapping on FTO. Our study identified the causal relationships between sleep-related phenotypes and body composition. These findings may give insights into the mechanism of sleep disturbances and provide novel therapeutic targets.

Quantitative Trait Loci Analysis Based on High-Density Mapping of Single-Nucleotide Polymorphisms by Genotyping-by-Sequencing Against Pine Wilt Disease in Japanese Black Pine (Pinus thunbergii).

Identifying genes/loci for resistance to pine wilt disease (PWD) caused by the pine wood nematode (PWN) is beneficial for improving resistance breeding in Pinus thunbergii, but to date, genetic information using molecular markers has been limited. Here, we constructed a high-density linkage map using genotyping-by-sequencing (GBS) and conducted quantitative trait loci (QTL) analysis for PWD resistance for the self-pollinated progeny of “Namikata 73,” which is the most resistant variety among resistant varieties of P. thunbergii, following inoculation tests with PWN. An S1 mapping population consisting of the 116 progenies derived from self-pollination of the resistant variety, “Namikata 73” (resistance rank 5 to PWN), was inoculated with PWN isolate Ka-4 and evaluated for disease symptoms. To construct a high-density linkage map, we used single-nucleotide polymorphisms (SNPs) identified by GBS based on next-generation sequencing technology and some anchor DNA markers, expressed sequence tag (EST)-derived SNP markers and EST-derived simple sequence repeat (SSR) markers, and genomic SSR markers. The linkage map had 13 linkage groups (LGs) consisting of 2,365 markers including 2,243 GBS-SNP markers over a total map distance of 1968.4 centimorgans (cM). Results from QTL analysis using phenotype data and the linkage map indicated that PWD resistance is controlled by a single locus located on LG-3, as identified in a previous study. This locus showed overdominant genetic action in the present study. With the confirmation of PWD1 in two different mapping populations (present study and a previous study), the locus associated with this region is thought to be a good target for marker-assisted selection in P. thunbergii breeding programs in order to obtain high levels of resistance to PWD caused by PWN.

Quantitative Trait Loci Mapping and Development of KASP Marker Smut Screening Assay Using High-Density Genetic Map and Bulked Segregant RNA Sequencing in Sugarcane (Saccharum spp.).

Sugarcane is one of the most important industrial crops globally. It is the second largest source of bioethanol, and a major crop for biomass-derived electricity and sugar worldwide. Smut, caused by Sporisorium scitamineum, is a major sugarcane disease in many countries, and is managed by smut-resistant varieties. In China, smut remains the single largest constraint for sugarcane production, and consequently it impacts the value of sugarcane as an energy feedstock. Quantitative trait loci (QTLs) associated with smut resistance and linked diagnostic markers are valuable tools for smut resistance breeding. Here, we developed an F1 population (192 progeny) by crossing two sugarcane varieties with contrasting smut resistance and used for genome-wide single nucleotide polymorphism (SNP) discovery and mapping, using a high-throughput genotyping method called “specific locus amplified fragment sequencing (SLAF-seq) and bulked-segregant RNA sequencing (BSR-seq). SLAF-seq generated 148,500 polymorphic SNP markers. Using SNP and previously identified SSR markers, an integrated genetic map with an average 1.96 cM marker interval was produced. With this genetic map and smut resistance scores of the F1 individuals from four crop years, 21 major QTLs were mapped, with a phenotypic variance explanation (PVE) > 8.0%. Among them, 10 QTLs were stable (repeatable) with PVEs ranging from 8.0 to 81.7%. Further, four QTLs were detected based on BSR-seq analysis. aligning major QTLs with the genome of a sugarcane progenitor Saccharum spontaneum, six markers were found co-localized. Markers located in QTLs and functional annotation of BSR-seq-derived unigenes helped identify four disease resistance candidate genes located in major QTLs. 77 SNPs from major QTLs were then converted to Kompetitive Allele-Specific PCR (KASP) markers, of which five were highly significantly linked to smut resistance. The co-localized QTLs, candidate resistance genes, and KASP markers identified in this study provide practically useful tools for marker-assisted sugarcane smut resistance breeding.

A review of literature on the pharmacogenomics of single-nucleotide polymorphisms

Pharmacogenomics is the study of how our genetic structure determines the response to a therapeutic intervention. It is a rapidly growing field that aims to elaborate the genetic basis for differences in drug response between different individuals and to use such genetic information to predict the safety, toxicity, and/or efficacy of drugs in individual patients or groups of patients. Although drug–drug interactions and environmental factors significantly contribute to interindividual variability in drug response, genetic factors (e.g., inherited variability of drug targets, drug-metabolizing enzymes, and/or drug transporters) also appear to have a major impact on drug response and disposition. When a gene variant is associated with a particular drug response in a patient, there is the potential for making clinical decisions based on genetics by adjusting the dosage or choosing a different drug. Single-nucleotide polymorphisms (SNPs), also called SNPs, are the most common type of genetic variation among people. They are basically a substitution of a single nucleotide that occurs at a specific position in the genome. They occur normally throughout a person's DNA. They occur almost once in every 1000 nucleotides on average, which means there are roughly 4–5 million SNPs in a person's genome. Most SNPs have no effect on health or development. Some of them, however, have proven to be very important in the study of human health, especially in the field of pharmacogenomics. Researchers have found SNPs that may help predict an individual's response to certain drugs, susceptibility to environmental factors such as toxins, and risk of developing particular diseases. Scientists assess gene variants affecting an individual's drug response the same way they assess gene variants associated with diseases: by identifying genetic loci associated with known drug responses, and then testing individuals whose response is unknown. SNPs account for the most common genetic differences from person to person and pharmacogenomics explores how such changes in genetic makeup effect drug responses, resistance, etc., With our literature review, we aim to study some of the effects of these SNPs on drug responses in patients. The purpose of the study was to understand and implicate the effects of SNPs in modern medicine and how it can be applied to personalize health care for every patient. A systematic literature search was carried in search of studies pertaining to personalized medicine and implications of SNPs. A thorough search through PubMed, Google Scholar, and ProQuest revealed 61 relevant studies. All study types were considered eligible. Over the past 10 years, tremendous progress has been made in cataloging human sequence variations since this high-density map can offer the required tools to develop genetically based diagnostic and therapeutic tests. When additional functional polymorphisms are known, it may be attainable to develop helpful genetic markers also as personalized medicines. In the future, the main aim is to use SNPs not only to find certain aspects to be used in the future (individualized drug therapy, development of genome-based diets, etc.) but to also unveil the details of genome evolution. A number of challenges exist today in realizing the value of a high-density map of anonymous SNPs for pharmacogenomics. Concerns about the high price of genotyping are being addressed; however, it may be several years before the price of genotyping large populations is acceptable. In addition, availability of large patient populations will be crucial for discovering and validating SNPs.

Overt and concealed genetic loads revealed by QTL mapping of genotype-dependent viability in the Pacific oyster Crassostrea gigas.

Understanding the genetic bases of inbreeding depression, heterosis, and genetic load is integral to understanding how genetic diversity is maintained in natural populations. The Pacific oyster Crassostrea gigas, like many long-lived plants, has high fecundity and high early mortality (type-III survivorship), manifesting a large, overt, genetic load; the oyster harbors an even greater concealed genetic load revealed by inbreeding. Here, we map viability QTL (vQTL) in six interrelated F2 oyster families, using high-density linkage maps of single nucleotide polymorphisms generated by genotyping-by-sequencing (GBS) methods. Altogether, we detect 70 vQTL and provisionally infer 89 causal mutations, 11 to 20 per family. Genetic mortality caused by independent (unlinked) vQTL ranges from 94.2% to 97.8% across families, consistent with previous reports. High-density maps provide better resolution of genetic mechanisms, however. Models of one causal mutation present in both identical-by-descent (IBD) homozygotes and heterozygotes fit genotype frequencies at 37 vQTL; consistent with the mutation-selection balance theory of genetic load, 20 are highly deleterious, completely recessive mutations and 17 are less deleterious, partially dominant mutations. Another 22 vQTL require pairs of recessive or partially dominant causal mutations, half showing selection against recessive mutations linked in repulsion, producing pseudo-overdominance. Only eight vQTL appear to support the overdominance theory of genetic load, with deficiencies of both IBD homozygotes, but at least four of these are likely caused by pseudo-overdominance. Evidence for epistasis is absent. A high mutation rate, random genetic drift, and pseudo-overdominance may explain both the oyster's extremely high genetic diversity and a high genetic load maintained primarily by mutation-selection balance.

Variability in porcine microRNA genes and its association with mRNA expression and lipid phenotypes

BackgroundMature microRNAs (miRNAs) play an important role in repressing the expression of a wide range of mRNAs. The presence of polymorphic sites in miRNA genes and their corresponding 3′UTR binding sites can disrupt canonical conserved miRNA–mRNA pairings, and thus modify gene expression patterns. However, to date such polymorphic sites in miRNA genes and their association with gene expression phenotypes and complex traits are poorly characterized in pigs.ResultsBy analyzing whole-genome sequences from 120 pigs and wild boars from Europe and Asia, we identified 285 single nucleotide polymorphisms (SNPs) that map to miRNA loci, and 109,724 SNPs that are located in predicted 7mer-m8 miRNA binding sites within porcine 3′UTR. In porcine miRNA genes, SNP density is reduced compared with their flanking non-miRNA regions. By sequencing the genomes of five Duroc boars, we identified 12 miRNA SNPs that were subsequently genotyped in their offspring (N = 345, Lipgen population). Association analyses of miRNA SNPs with 38 lipid-related traits and hepatic and muscle microarray expression phenotypes recorded in the Lipgen population were performed. The most relevant detected association was between the genotype of the rs319154814 (G/A) SNP located in the apical loop of the ssc-miR-326 hairpin precursor and PPP1CC mRNA levels in the liver (q-value = 0.058). This result was subsequently confirmed by qPCR (P-value = 0.027). The rs319154814 (G/A) genotype was also associated with several fatty acid composition traits.ConclusionsOur findings show a reduced variability of porcine miRNA genes, which is consistent with strong purifying selection, particularly in the seed region that plays a critical role in miRNA binding. Although it is generally assumed that SNPs mapping to the seed region are those with the most pronounced consequences on mRNA expression, we show that a SNP mapping to the apical region of ssc-miR-326 is significantly associated with hepatic mRNA levels of the PPP1CC gene, one of its predicted targets. Although experimental confirmation of such an interaction is reported in humans but not in pigs, this result highlights the need to further investigate the functional effects of miRNA polymorphisms that are located outside the seed region on gene expression in pigs.

Variant Intronic Enhancer Controls SCN10A-short Expression and Heart Conduction.

Genetic variants in SCN10A, encoding the neuronal voltage-gated sodium channel NaV1.8, are strongly associated with atrial fibrillation, Brugada syndrome, cardiac conduction velocities, and heart rate. The cardiac function of SCN10A has not been resolved, however, and diverging mechanisms have been proposed. Here, we investigated the cardiac expression of SCN10A and the function of a variant-sensitive intronic enhancer previously linked to the regulation of SCN5A, encoding the major essential cardiac sodium channel NaV1.5. The expression of SCN10A was investigated in mouse and human hearts. With the use of CRISPR/Cas9 genome editing, the mouse intronic enhancer was disrupted, and mutant mice were characterized by transcriptomic and electrophysiological analyses. The association of genetic variants at SCN5A-SCN10A enhancer regions and gene expression were evaluated by genome-wide association studies single-nucleotide polymorphism mapping and expression quantitative trait loci analysis. We found that cardiomyocytes of the atria, sinoatrial node, and ventricular conduction system express a short transcript comprising the last 7 exons of the gene (Scn10a-short). Transcription occurs from an intronic enhancer-promoter complex, whereas full-length Scn10a transcript was undetectable in the human and mouse heart. Expression quantitative trait loci analysis revealed that the genetic variants in linkage disequilibrium with genetic variant rs6801957 in the intronic enhancer associate with SCN10A transcript levels in the heart. Genetic modification of the enhancer in the mouse genome led to reduced cardiac Scn10a-short expression in atria and ventricles, reduced cardiac sodium current in atrial cardiomyocytes, atrial conduction slowing and arrhythmia, whereas the expression of Scn5a, the presumed enhancer target gene, remained unaffected. In patch-clamp transfection experiments, expression of Scn10a-short-encoded NaV1.8-short increased NaV1.5-mediated sodium current. We propose that noncoding genetic variation modulates transcriptional regulation of Scn10a-short in cardiomyocytes that impacts NaV1.5-mediated sodium current and heart rhythm. Genetic variants in and around SCN10A modulate enhancer function and expression of a cardiac-specific SCN10A-short transcript. We propose that noncoding genetic variation modulates transcriptional regulation of a functional C-terminal portion of NaV1.8 in cardiomyocytes that impacts on NaV1.5 function, cardiac conduction velocities, and arrhythmia susceptibility.

Genome resequencing reveals DNA polymorphisms associated with seed size/weight determination in chickpea

Crop productivity in legumes is determined by number and size/weight of seeds. To understand the genetic basis of seed size/weight in chickpea, we performed genome resequencing of 13 small- and 5 large-seeded genotypes using Illumina platform. Single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) differentiating small- and large-seeded genotypes were identified. A total of 17,902 SNPs and 2594 InDels located in promoter and/or coding regions that may contribute to seed size/weight were detected. Of these, 266 SNPs showed significant association with seed size/weight trait. Twenty-three genes including those involved in cell growth/division, encoding transcription factors and located within QTLs associated with seed size/weight harbored SNPs within transcription factor binding motif(s) and/or coding region. The non-synonymous SNPs were found to affect the mutational sensitivity and stability of the encoded proteins. Overall, we provided a high-quality SNP map for large-scale genotyping applications and identified candidate genes that determine seed size/weight in chickpea.