Fine mapping and cloning of the major seed protein quantitative trait loci on soybean chromosome 20.
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ABSTRACT:
SUBMITTER: Fliege CE
PROVIDER: S-EPMC9303569 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Flowering time is a major adaptive trait in plants and an important selection criterion for crop species. In maize, however, little is known about its molecular basis. In this study, we report the fine mapping and characterization of a major quantitative trait locus located on maize chromosome 10, which regulates flowering time through photoperiod sensitivity. This study was performed in near-isogenic material derived from a cross between the day-neutral European flint inbred line FV286 and the tropical short-day inbred line FV331. Recombinant individuals were identified among a large segregating population and their progenies were scored for flowering time. Combined genotypic characterization led to delimit the QTL to an interval of 170 kb and highlighted an unbalanced recombination pattern. Two bacterial artificial chromosomes (BACs) covering the region were analyzed to identify putative candidate genes, and synteny with rice, sorghum, and brachypodium was investigated. A gene encoding a CCT domain protein homologous to the rice Ghd7 heading date regulator was identified, but its causative role was not demonstrated and deserves further analyses. Finally, an association study showed a strong level of linkage disequilibrium over the region and highlighted haplotypes that could provide useful information for the exploitation of genetic resources and marker-assisted selection in maize.
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Project description:In soybean [Glycine max (L.) Merrill], the genetic analysis of seed yield is important to aid in the breeding of high-yielding cultivars. Seed yield is a complex trait, and the number of quantitative trait loci (QTL) involved in seed yield is high. The aims of this study were to identify QTL associated with seed yield and validate their effects on seed yield using near-isogenic lines. The QTL analysis was conducted using a recombinant inbred line population derived from a cross between Japanese cultivars 'Toyoharuka' and 'Toyomusume', and eight seed yield-associated QTL were identified. There were significant positive correlations between seed yield and the number of favorable alleles at QTL associated with seed yield in the recombinant inbred lines for three years. The effects of qSY8-1, a QTL promoting greater seed yield, was validated in the Toyoharuka background. In a two-year yield trial, the 100-seed weight and seed yield of Toyoharuka-NIL, the near-isogenic line having the Toyomusume allele at qSY8-1, were significantly greater than those of Toyoharuka (106% and 107%, respectively) without any change for days to flowering and maturity. Our results suggest that qSY8-1 was not associated with maturity genes, and contributed to the 100-seed weight.
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Project description:Quantitative trait loci (QTL) are genomic regions associated with phenotype variation of quantitative traits. To date, a total of 313 QTL for 31 quantitative traits have been reported in 14 studies on flax. Of these, 200 QTL from 12 studies were identified based on genetic maps, the scaffold sequences, or the pre-released chromosome-scale pseudomolecules. Molecular markers for QTL identification differed across studies but the most used ones were simple sequence repeats (SSRs) or single nucleotide polymorphisms (SNPs). To uniquely map the SSR and SNP markers from different references onto the recently released chromosome-scale pseudomolecules, methods with several scripts and database files were developed to locate PCR- and SNP-based markers onto the same reference, co-locate QTL, and scan genome-wide candidate genes. Using these methods, 195 out of 200 QTL were successfully sorted onto the 15 flax chromosomes and grouped into 133 co-located QTL clusters; the candidate genes that co-located with these QTL clusters were also predicted. The methods and tools presented in this article facilitate marker re-mapping to a new reference, genome-wide QTL analysis, candidate gene scanning, and breeding applications in flax and other crops.
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Project description:Pythium root rot is one of the significant diseases of soybean (Glycine max (L.) Merr.) in the United States. The causal agent of the disease is a soil-borne oomycete pathogen Pythium irregulare, the most prevalent and aggressive species of Pythium in North Central United States. However, few studies have been conducted in soybean for the identification of quantitative trait loci (QTL) for tolerance to P. irregulare In this study, two recombinant inbred line (RIL) populations (designated as POP1 and POP2) were challenged with P. irregulare (isolate CMISO2-5-14) in a greenhouse assay. POP1 and POP2 were derived from 'E09014' × 'E05226-T' and 'E05226-T' × 'E09088', and contained 113 and 79 lines, respectively. Parental tests indicated that 'E05226-T' and 'E09014' were more tolerant than 'E09088', while 'E09088' was highly susceptible to the pathogen. The disease indices, root weight of inoculation (RWI) and ratio of root weight (RRW) of both populations showed near normal distributions, with transgressive segregation, suggesting the involvement of multiple QTL from both parents contributed to the tolerance. All the lines were genotyped using Illumina Infinium BARCSoySNP6K iSelect BeadChip and yielded 1373 and 1384 polymorphic markers for POP1 and POP2, respectively. Notably, despite high density, polymorphic markers coverage was incomplete in some genomic regions. As such, 28 and 37 linkage groups were obtained in POP1 and POP2, respectively corresponding to the 20 soybean chromosomes. Using RRW, one QTL was identified in POP1 on Chromosome 20 that explained 12.7-13.3% of phenotypic variation. The desirable allele of this QTL was from 'E05226-T'. Another QTL was found in POP2 on Chromosome 11. It explained 15.4% of the phenotypic variation and the desirable allele was from 'E09088'. However, no QTL were identified using RWI in either population. These results supported that RRW was more suitable to be used to evaluate P. irregulare tolerance in soybean.
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Project description:BackgroundSingle nucleotide polymorphisms (SNPs) which capture a significant impact on a trait can be identified with genome-wide association studies. High linkage disequilibrium (LD) among SNPs makes it difficult to identify causative variants correctly. Thus, often target regions instead of single SNPs are reported. Sample size has not only a crucial impact on the precision of parameter estimates, it also ensures that a desired level of statistical power can be reached. We study the design of experiments for fine-mapping of signals of a quantitative trait locus in such a target region.MethodsA multi-locus model allows to identify causative variants simultaneously, to state their positions more precisely and to account for existing dependencies. Based on the commonly applied SNP-BLUP approach, we determine the z-score statistic for locally testing non-zero SNP effects and investigate its distribution under the alternative hypothesis. This quantity employs the theoretical instead of observed dependence between SNPs; it can be set up as a function of paternal and maternal LD for any given population structure.ResultsWe simulated multiple paternal half-sib families and considered a target region of 1 Mbp. A bimodal distribution of estimated sample size was observed, particularly if more than two causative variants were assumed. The median of estimates constituted the final proposal of optimal sample size; it was consistently less than sample size estimated from single-SNP investigation which was used as a baseline approach. The second mode pointed to inflated sample sizes and could be explained by blocks of varying linkage phases leading to negative correlations between SNPs. Optimal sample size increased almost linearly with number of signals to be identified but depended much stronger on the assumption on heritability. For instance, three times as many samples were required if heritability was 0.1 compared to 0.3. An R package is provided that comprises all required tools.ConclusionsOur approach incorporates information about the population structure into the design of experiments. Compared to a conventional method, this leads to a reduced estimate of sample size enabling the resource-saving design of future experiments for fine-mapping of candidate variants.
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Project description:Prior studies with crosses of the FVB/NJ (FVB; seizure-induced cell death-susceptible) mouse and the C57BL/6J (B6; seizure-induced cell death-resistant) mouse revealed the presence of a quantitative trait locus (QTL) on chromosome 15 that influenced susceptibility to kainic acid-induced cell death (Sicd2). In an earlier study, we confirmed that the Sicd2 interval harbors gene(s) conferring strong protection against seizure-induced cell death through the creation of the FVB.B6-Sicd2 congenic strain, and created three interval-specific congenic lines (ISCLs) that encompass Sicd2 on chromosome 15 to fine-map this locus. To further localise this Sicd2 QTL, an additional congenic line carrying overlapping intervals of the B6 segment was created (ISCL-4), and compared with the previously created ISCL-1-ISCL-3 and assessed for seizure-induced cell death phenotype. Whereas all of the ISCLs showed reduced cell death associated with the B6 phenotype, ISCL-4, showed the most extensive reduction in seizure-induced cell death throughout all hippocampal subfields. In order to characterise the susceptibility loci on Sicd2 by use of this ISCL and identify compelling candidate genes, we undertook an integrative genomic strategy of comparing exon transcript abundance in the hippocampus of this newly developed chromosome 15 subcongenic line (ISCL-4) and FVB-like littermates. We identified 10 putative candidate genes that are alternatively spliced between the strains and may govern strain-dependent differences in susceptibility to seizure-induced excitotoxic cell death. These results illustrate the importance of identifying transcriptomics variants in expression studies, and implicate novel candidate genes conferring susceptibility to seizure-induced cell death.
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Project description:BACKGROUND:Deciphering the genetic basis of prostate cancer aggressiveness could provide valuable information for the screening and treatment of this common but complex disease. We previously detected linkage between a broad region on chromosome 7q22-35 and Gleason score-a strong predictor of prostate cancer aggressiveness. To further clarify this finding and focus on the potentially causative gene, we undertook a fine-mapping study across the 7q22-35 region. METHODS:Our study population encompassed 698 siblings diagnosed with prostate cancer. 3,072 single nucleotide polymorphisms (SNPs) spanning the chromosome 7q22-35 region were genotyped using the Illumina GoldenGate assay. The impact of SNPs on Gleason scores were evaluated using affected sibling pair linkage and family-based association tests. RESULTS:We confirmed the previous linkage signal and narrowed the 7q22-35 prostate cancer aggressiveness locus to a 370?kb region. Centered under the linkage peak is the gene KLRG2 (killer cell lectin-like receptor subfamily G, member 2). Association tests indicated that the potentially functional non-synonymous SNP rs17160911 in KLRG2 was significantly associated with Gleason score (P?=?0.0007). CONCLUSIONS:These findings suggest that genetic variants in the gene KLRG2 may affect Gleason score at diagnosis and hence the aggressiveness of prostate cancer.
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Project description:Soybean oil is the most widely produced vegetable oil in the world and its content in soybean seed is an important quality trait in breeding programs. More than 100 quantitative trait loci (QTLs) for soybean oil content have been identified. However, most of them are genotype specific and/or environment sensitive. Here, we used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2, was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1, and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.
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