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10,953 result(s) for "candidate genes"
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Superior haplotypes for haplotype‐based breeding for drought tolerance in pigeonpea ( Cajanus cajan L.)
Haplotype-based breeding, a recent promising breeding approach to develop tailor-made crop varieties, deals with identification of superior haplotypes and their deployment in breeding programmes. In this context, whole genome re-sequencing data of 292 genotypes from pigeonpea reference set were mined to identify the superior haplotypes for 10 droughtresponsive candidate genes. A total of 83, 132 and 60 haplotypes were identified in breeding lines, landraces and wild species, respectively. Candidate gene-based association analysis of these 10 genes on a subset of 137 accessions of the pigeonpea reference set revealed 23 strong marker-trait associations (MTAs) in five genes influencing seven drought-responsive component traits. Haplo-pheno analysis for the strongly associated genes resulted in the identification of most promising haplotypes for three genes regulating five component drought traits. The haplotype C. cajan_23080-H2 for plant weight (PW), fresh weight (FW) and turgid weight (TW), the haplotype C. cajan_30211-H6 for PW, FW, TW and dry weight (DW), the haplotype C. cajan_26230-H11 for FW and DW and the haplotype C. cajan_26230-H5 for relative water content (RWC) were identified as superior haplotypes under drought stress condition. Furthermore, 17 accessions containing superior haplotypes for three drought-responsive genes were identified. The identified superior haplotypes and the accessions carrying these superior haplotypes will be very useful for deploying haplotype-based breeding to develop nextgeneration tailor-made better drought-responsive pigeonpea cultivars.
Development and Validation of SNP and InDel Markers for Pod-Shattering Tolerance in Soybean
Pod-shattering causes a significant yield loss in many soybean cultivars. Shattering-tolerant cultivars provide the most effective approach to minimizing this loss. We developed molecular markers for pod-shattering and validated them in soybeans with diverse genetic backgrounds. The genes Glyma.16g141200, Glyma.16g141500, and Glyma.16g076600, identified in our previous study by quantitative trait locus (QTL) mapping and whole-genome resequencing, were selected for marker development. The whole-genome resequencing of three parental lines (one shattering-tolerant and two shattering-susceptible) identified single nucleotide polymorphism (SNP) and/or insertion/deletion (InDel) regions within or near the selected genes. Two SNPs and one InDel were converted to Kompetitive Allele-Specific PCR (KASP) and InDel markers, respectively. The accuracy of the markers was examined in the two recombinant inbred line populations used for the QTL mapping, as well as the 120 varieties and elite lines, through allelic discrimination and phenotyping by the oven-drying method. Both types of markers successfully discriminated the pod shattering-tolerant and shattering-susceptible genotypes. The prediction accuracy, which was as high as 90.9% for the RILs and was 100% for the varieties and elite lines, also supported the accuracy and usefulness of these markers. Thus, the markers can be used effectively for genetic and genomic studies and the marker-assisted selection for pod-shattering tolerance in soybean.
Survey of Candidate Genes for Maize Resistance to Infection by Aspergillus flavus and/or Aflatoxin Contamination
Many projects have identified candidate genes for resistance to aflatoxin accumulation or Aspergillus flavus infection and growth in maize using genetic mapping, genomics, transcriptomics and/or proteomics studies. However, only a small percentage of these candidates have been validated in field conditions, and their relative contribution to resistance, if any, is unknown. This study presents a consolidated list of candidate genes identified in past studies or in-house studies, with descriptive data including genetic location, gene annotation, known protein identifiers, and associated pathway information, if known. A candidate gene pipeline to test the phenotypic effect of any maize DNA sequence on aflatoxin accumulation resistance was used in this study to determine any measurable effect on polymorphisms within or linked to the candidate gene sequences, and the results are published here.
Genetic Control and Geo-Climate Adaptation of Pod Dehiscence Provide Novel Insights into Soybean Domestication
Loss of pod dehiscence was a key step in soybean [Glycine max (L.) Merr.] domestication. Genome-wide association analysis for soybean shattering identified loci harboring Pdh1, NST1A and SHAT1-5. Pairwise epistatic interactions were observed, and the dehiscent Pdh1 overcomes resistance conferred by NST1A or SHAT1-5 locus. Further candidate gene association analysis identified a nonsense mutation in NST1A associated with pod dehiscence. Geographic analysis showed that in Northeast China (NEC), indehiscence at both Pdh1 and NST1A were required in cultivated soybean, while indehiscent Pdh1 alone is capable of preventing shattering in Huang-Huai-Hai (HHH) valleys. Indehiscent Pdh1 allele was only identified in wild soybean (Glycine soja L.) accession from HHH valleys suggesting that it may have originated in this region. No specific indehiscence was required in Southern China. Geo-climatic investigation revealed strong correlation between relative humidity and frequency of indehiscent Pdh1 across China. This study demonstrates that epistatic interaction between Pdh1 and NST1A fulfills a pivotal role in determining the level of resistance against pod dehiscence, and humidity shapes the distribution of indehiscent alleles. Our results give further evidence to the hypothesis that HHH valleys was at least one of the origin centers of cultivated soybean.
Gentrepid V2.0: a web server for candidate disease gene prediction
Candidate disease gene prediction is a rapidly developing area of bioinformatics research with the potential to deliver great benefits to human health. As experimental studies detecting associations between genetic intervals and disease proliferate, better bioinformatic techniques that can expand and exploit the data are required. Gentrepid is a web resource which predicts and prioritizes candidate disease genes for both Mendelian and complex diseases. The system can take input from linkage analysis of single genetic intervals or multiple marker loci from genome-wide association studies. The underlying database of the Gentrepid tool sources data from numerous gene and protein resources, taking advantage of the wealth of biological information available. Using known disease gene information from OMIM, the system predicts and prioritizes disease gene candidates that participate in the same protein pathways or share similar protein domains. Alternatively, using an ab initio approach, the system can detect enrichment of these protein annotations without prior knowledge of the phenotype. The system aims to integrate the wealth of protein information currently available with known and novel phenotype/genotype information to acquire knowledge of biological mechanisms underpinning disease. We have updated the system to facilitate analysis of GWAS data and the study of complex diseases. Application of the system to GWAS data on hypertension using the ICBP data is provided as an example. An interesting prediction is a ZIP transporter additional to the one found by the ICBP analysis. The webserver URL is https://www.gentrepid.org/.
Polymorphic simple sequence repeat (SSR) loci within cellulose synthase (PtoCesA) genes are associated with growth and wood properties in Populus tomentosa
Chinese white poplar (Populus tomentosa), an important commercial tree species for timber and pulp production in northern China, has been used to examine the individual genes and allelic diversity responsible for complex traits controlling growth and lignocellulosic biosynthesis. Taking advantage of the low degree of linkage disequilibrium (LD) within P. tomentosa association populations, we examined associations between 15 cellulose synthase (PtoCesA) genes and traits including growth and wood properties. Thirty-six novel simple sequence repeat (SSR) markers within PtoCesA genes were detected by re-sequencing and genotyped in an association population (460 individuals). Single-marker and haplotype-based LD approaches were used to identify significant marker–trait associations. Family-based linkage studies and real-time PCR testing were conducted to validate the functional significance of SSR variation. Fifteen single-marker associations from seven PtoCesA genes and nine haplotype-based associations within six genes were identified in the association population (false discovery rate Q < 0.05). Next, five SSR marker–trait associations (Q< 0.05) from four PtoCesA genes were successfully validated in a linkage mapping population (1200 individuals). The results imply a functional role for these genes in mediating wood properties, demonstrating the potential of combining single-marker and haplotype-based LD approaches to detect functional allelic variation underlying quantitative traits in a low-LD population.
A Genome-Wide Search for Candidate Genes of Meat Production in Jalgin Merino Considering Known Productivity Genes
In a group of Jalgin merino rams with no significant influence on the dispersion of the phenotypes of known productivity genes (MSTN, MEF2B, FABP4, etc.), a genome-wide search for associations of individual polymorphisms with intravital indicators of meat productivity was performed. Using the Ovine Infinium HD BeadChip 600K, 606,000 genome loci were evaluated. Twenty-three substitutions were found to be significantly associated with external measurements of the body and ultrasonic parameters. This made it possible to describe 14 candidate genes, the structural features of which can cause changes in animal phenotypes. No closely spaced genes were found for two substitutions. The identified polymorphisms were found in the exons, introns, and adjacent regions of the following genes and transcripts: CDCA2, ENSOARG00000014477, C4BPA, RIPOR2, ENSOARG00000007198, ENSOARG00000026965 (LincRNA), ENSOARG00000026436 (LincRNA), ENSOARG00000026782 (LincRNA), TENM3, RTL8A, MOSPD1, RTL8C, RIMS2, and P4HA3. The detected genes affect the metabolic pathways of cell differentiation and proliferation and are associated with the regulation of the immune system. This confirms their possible participation in the formation of the phenotypes of productivity parameters in animals and indicates the need for further study of the structure of candidate genes in order to identify their internal polymorphisms.
Interactions between gut microbes and host promote degradation of various fiber components in Meishan pigs
Studies on porcine intestinal microbiota have been widely conducted, and some microbial taxa with fiber degradation functions have been identified. However, the mechanisms of division among gut microbes in the degradation of complex fiber components are still unclear. In addition, the regulation of fiber digestion by host through absorption of short-chain fatty acids (SCFAs) needs to be further investigated. Our study used apparent total tract digestibility of dietary fiber to assess the utilization efficiency of dietary fiber between Meishan and Large White pigs. Subsequently, through metagenome sequencing and determination of fiber-degrading products, we found that in Meishan pigs, positive interactions among Treponema bryantii , Treponema sp . , Rikenellaceae bacterium, and Bacteroidales bacterium WCE2004 facilitated the degradation of both cellulose and pectin. RNA-seq analysis elucidated breed-specific genes associated with SCFA absorption in cecum. By integrating multi-omics data, we constructed a framework outlining host-microbiota interactions that control dietary fiber utilization in pigs. Our data provide novel insights into host-microbiota interactions regulating fiber degradation and lay some theoretical foundations for improving the utilization efficiency of high-fiber cereal feed in pigs through targeted modulation of gut microbial function.
“Soldier's Heart”: A Genetic Basis for Elevated Cardiovascular Disease Risk Associated with Post-traumatic Stress Disorder
\"Soldier's Heart,\" is an American Civil War term linking post-traumatic stress disorder (PTSD) with increased propensity for cardiovascular disease (CVD). We have hypothesized that there might be a quantifiable genetic basis for this linkage. To test this hypothesis we identified a comprehensive set of candidate risk genes for PTSD, and tested whether any were also independent risk genes for CVD. A functional analysis algorithm was used to identify associated signaling networks. We identified 106 PTSD studies that report one or more polymorphic variants in 87 candidate genes in 83,463 subjects and controls. The top upstream drivers for these PTSD risk genes are predicted to be the glucocorticoid receptor (NR3C1) and Tumor Necrosis Factor alpha (TNFA). We find that 37 of the PTSD candidate risk genes are also candidate independent risk genes for CVD. The association between PTSD and CVD is significant by Fisher's Exact Test ( = 3 × 10 ). We also find 15 PTSD risk genes that are independently associated with Type 2 Diabetes Mellitus (T2DM; also significant by Fisher's Exact Test ( = 1.8 × 10 ). Our findings offer quantitative evidence for a genetic link between post-traumatic stress and cardiovascular disease, Computationally, the common mechanism for this linkage between PTSD and CVD is innate immunity and NFκB-mediated inflammation.
Organ-Specific Quantitative Genetics and Candidate Genes of Phenylpropanoid Metabolism in Brassica oleracea
Phenolic compounds are proving to be increasingly important for human health and in crop development, defense and adaptation. In spite of the economical importance of Brassica crops in agriculture, the mechanisms involved in the biosynthesis of phenolic compounds presents in these species remain unknown. The genetic and metabolic basis of phenolics accumulation was dissected through analysis of total phenolics concentration and its individual components in leaves, flower buds, and seeds of a double haploid (DH) mapping population of Brassica oleracea. The quantitative trait loci (QTL) that had an effect on phenolics concentration in each organ were integrated, resulting in 33 consensus QTLs controlling phenolics traits. Most of the studied compounds had organ-specific genomic regulation. Moreover, this information allowed us to propose candidate genes and to predict the function of genes underlying the QTL. A number of previously unknown potential regulatory regions involved in phenylpropanoid metabolism were identified and this study illustrates how plant ontogeny can affect a biochemical pathway.