Multi-Locus Genome-Wide Association Study of Four Yield-Related Traits in Chinese Wheat Landraces.
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ABSTRACT:
SUBMITTER: Lin Y
PROVIDER: S-EPMC8415402 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits.Supplementary informationThe online version contains supplementary material available at 10.1007/s11032-021-01240-1.
| S-EPMC10236106 | biostudies-literature
Project description:Multi-locus genome wide association study was undertaken using a set of 320 diverse spring wheat accessions, which were each genotyped for 9,626 SNPs. The association panel was grown in replicated trials in four environments [two each in irrigated (IR) and rainfed (RF) environments], and phenotypic data were recorded for five traits including days to heading, days to maturity, plant height, thousand grain weight and grain yield. Forty-six significant marker-trait associations (MTAs) were identified for five traits. These included 20 MTAs in IR and 19 MTAs in RF environments; seven additional MTAs were common to both the environments. Five of these MTAs were co-localized with previously known QTL/MTAs and the remaining MTAs were novel and add to the existing knowledge. Three desirable haplotypes for agronomic traits, one for improvement in RF environment and two for improvement in IR environment were identified. Eighteen (18) promising candidate genes (CGs) involved in seven different biological activities were also identified. The expression profiles of four (Trehalose-6-Phosphate, APETALA2/Ethylene-responsive factor, DNA-binding One Zinc Finger and Gibberellin-dioxygenases) of the 18 genes showed that they were induced by drought stress in the wheat seedlings. The MTAs, haplotypes and CG-based markers may be used in marker-assisted breeding for drought tolerance in wheat.
| S-EPMC6925107 | biostudies-literature
Project description:BackgroundImproving the overall production of rice with high quality is a major target of breeders. Mining potential yield-related loci have been geared towards developing efficient rice breeding strategies. In this study, one single-locus genome-wide association studies (SL-GWAS) method (MLM) in conjunction with five multi-locus genome-wide association studies (ML-GWAS) approaches (mrMLM, FASTmrMLM, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were conducted in a panel consisting of 529 rice core varieties with 607,201 SNPs.ResultsA total of 152, 106, 12, 111, and 64 SNPs were detected by the MLM model associated with the five yield-related traits, namely grain length (GL), grain width (GW), grain thickness (GT), thousand-grain weight (TGW), and yield per plant (YPP), respectively. Furthermore, 74 significant quantitative trait nucleotides (QTNs) were presented across at least two ML-GWAS methods to be associated with the above five traits successively. Finally, 20 common QTNs were simultaneously discovered by both SL-GWAS and ML-GWAS methods. Based on genome annotation, gene expression analysis, and previous studies, two candidate key genes (LOC_Os09g02830 and LOC_Os07g31450) were characterized to affect GW and TGW, separately.ConclusionsThese outcomes will provide an indication for breeding high-yielding rice varieties in the immediate future.
| S-EPMC8353822 | biostudies-literature
Project description:BackgroundBread wheat (Triticum aestivum L.) is one of the most important cereal food crops for the global population. Spike-layer uniformity (the consistency of the spike distribution in the vertical space)-related traits (SLURTs) are quantitative and have been shown to directly affect yield potential by modifying the plant architecture. Therefore, these parameters are important breeding targets for wheat improvement. The present study is the first genome-wide association study (GWAS) targeting SLURTs in wheat. In this study, a set of 225 diverse spring wheat accessions were used for multi-locus GWAS to evaluate SLURTs, including the number of spikes per plant (NSPP), spike length (SL), number of spikelets per spike (NSPS), grain weight per spike (GWPS), lowest tiller height (LTH), spike-layer thickness (SLT), spike-layer number (SLN) and spike-layer uniformity (SLU).ResultsIn total, 136 significant marker trait associations (MTAs) were identified when the analysis was both performed individually and combined for two environments. Twenty-nine MTAs were detected in environment one, 48 MTAs were discovered in environment two and 59 MTAs were detected using combined data from the two environments. Altogether, 15 significant MTAs were found for five traits in one of the two environments, and four significant MTAs were detected for the two traits, LTH and SLU, in both environments i.e. E1, E2 and also in combined data from the two environments. In total, 279 candidate genes (CGs) were identified, including Chaperone DnaJ, ABC transporter-like, AP2/ERF, SWEET sugar transporter, as well as genes that have previously been associated with wheat spike development, seed development and grain yield.ConclusionsThe MTAs detected through multi-locus GWAS will be useful for improving SLURTs and thus yield in wheat production through marker-assisted and genomic selection.
| S-EPMC8340506 | biostudies-literature
Project description:Rapeseed (Brassica napus L.), the third largest oil crop, is an important source of vegetable oil and biofuel for the world. Although the breeding and yield has been improved, rapeseed still has the lowest yield compared with other major crops. Thus, increasing rapeseed yield is essential for the high demand of vegetable oil and high-quality protein for live stocks. Silique number per plant (SN), seed per pod (SP), and 1000-seed weight (SW) are the three important factors for seed yield in rapeseed. Some yield-related traits, including plant height (PH), flowering time (FT), primary branch number (BN) and silique number per inflorescence (SI) also affect the yield per plant (YP). Using six multi-locus genome-wide association study (ML-GWAS) approaches, a total of 908 yield-related quantitative trait nucleotides (QTNs) were identified in a panel consisting of 403 rapeseed core accessions based on whole-genome sequencing. Integration of ML-GWAS with transcriptome analysis, 79 candidate genes, including BnaA09g39790D (RNA helicase), BnaA09g39950D (Lipase) and BnaC09g25980D (SWEET7), were further identified and twelve genes were validated by qRT-PCRs to affect the SW or SP in rapeseed. The distribution of superior alleles from nineteen stable QTNs in 20 elite rapeseed accessions suggested that the high-yielding accessions contained more superior alleles. These results would contribute to a further understanding of the genetic basis of yield-related traits and could be used for crop improvement in B. napus.
| S-EPMC10140536 | biostudies-literature
Project description:From the perspective of wheat yield improvement, the coleoptile is vital for successful crop establishment, and long coleoptile lengths (CLs) are preferred in wheat-growing regions where deep planting is practiced. To determine the genetic basis of CL, we performed a genome-wide association study on a set of 707 Chinese wheat landraces using 18,594 single-nucleotide polymorphisms and 38,678 diversity array technology sequencing markers. We accordingly detected a total of 29 significant markers [-log10 (P) > 4.76] distributed on chromosomes 2B, 2D, 3A, 4A, 5A, 6A, 6B, 6D, and 7B. Based on linkage disequilibrium decay distance, we identified a total of 17 quantitative trait loci associated with CL, among which QCl.sicau-6B.2, located at 508.17-509.26 Mb on chromosome 6B, was recognized as a novel major locus. We subsequently developed a high-resolution melt marker for QCl.sicau-6B.2, which was validated in an F 2 : 3 population. Our findings provide important insights into the genetic mechanisms underlying coleoptile growth and could be applied to marker-assisted wheat selection.
| S-EPMC7287122 | biostudies-literature
Project description:Key messageAssociation mapping conducted in 189 Spanish bread wheat landraces revealed six key genomic regions that constitute stable QTLs for yield and include 15 candidate genes. Genetically diverse landraces provide an ideal population to conduct association analysis. In this study, association mapping was conducted in a collection of 189 Spanish bread wheat landraces whose genomic diversity had been previously assessed. These genomic data were combined with characterization for yield-related traits, including grain size and shape, and phenological traits screened across five seasons. The association analysis revealed a total of 881 significant marker trait associations, involving 434 markers across the genome, that could be grouped in 366 QTLs based on linkage disequilibrium. After accounting for days to heading, we defined 33 high density QTL genomic regions associated to at least four traits. Considering the importance of detecting stable QTLs, 6 regions associated to several grain traits and thousand kernel weight in at least three environments were selected as the most promising ones to harbour targets for breeding. To dissect the genetic cause of the observed associations, we studied the function and in silico expression of the 413 genes located inside these six regions. This identified 15 candidate genes that provide a starting point for future analysis aimed at the identification and validation of wheat yield related genes.
| S-EPMC10643358 | biostudies-literature
Project description:Genome wide association study (GWAS) was conducted for 14 agronomic traits in wheat following widely used single locus single trait (SLST) approach, and two recent approaches viz. multi locus mixed model (MLMM), and multi-trait mixed model (MTMM). Association panel consisted of 230 diverse Indian bread wheat cultivars (released during 1910-2006 for commercial cultivation in different agro-climatic regions in India). Three years phenotypic data for 14 traits and genotyping data for 250 SSR markers (distributed across all the 21 wheat chromosomes) was utilized for GWAS. Using SLST, as many as 213 MTAs (p ? 0.05, 129 SSRs) were identified for 14 traits, however, only 10 MTAs (~9%; 10 out of 123 MTAs) qualified FDR criteria; these MTAs did not show any linkage drag. Interestingly, these genomic regions were coincident with the genomic regions that were already known to harbor QTLs for same or related agronomic traits. Using MLMM and MTMM, many more QTLs and markers were identified; 22 MTAs (19 QTLs, 21 markers) using MLMM, and 58 MTAs (29 QTLs, 40 markers) using MTMM were identified. In addition, 63 epistatic QTLs were also identified for 13 of the 14 traits, flag leaf length (FLL) being the only exception. Clearly, the power of association mapping improved due to MLMM and MTMM analyses. The epistatic interactions detected during the present study also provided better insight into genetic architecture of the 14 traits that were examined during the present study. Following eight wheat genotypes carried desirable alleles of QTLs for one or more traits, WH542, NI345, NI170, Sharbati Sonora, A90, HW1085, HYB11, and DWR39 (Pragati). These genotypes and the markers associated with important QTLs for major traits can be used in wheat improvement programs either using marker-assisted recurrent selection (MARS) or pseudo-backcrossing method.
| S-EPMC4956103 | biostudies-literature
Project description:Early-maturity varieties of upland cotton are becoming increasingly important for farmers to improve their economic benefits through double cropping practices and mechanical harvesting production in China. However, fiber qualities of early-maturing varieties are relatively poor compared with those of middle- and late- maturing ones. Therefore, it is crucial for researchers to elucidate the genetic bases controlling fiber-quality related traits in early-maturity cultivars, and to improve synergistically cotton earliness and fiber quality. Here, multi-locus genome-wide association studies (ML-GWAS) were conducted in a panel consisting of 160 early-maturing cotton accessions. Each accession was genotyped by 72,792 high-quality single nucleotide polymorphisms (SNPs) using specific-locus amplified fragment sequencing (SLAF-seq) approach, and fiber quality-related traits under four environmental conditions were measured. Applying at least three ML-GWAS methods, a total of 70 significant quantitative trait nucleotides (QTNs) were identified to be associated with five objective traits, including fiber length (FL), fiber strength (FS), fiber micronaire (FM), fiber uniformity (FU) and fiber elongation (FE). Among these QTNs, D11_21619830, A05_28352019 and D03_34920546 were found to be significantly associated with FL, FS, and FM, respectively, across at least two environments. Among 96 genes located in the three target genomic regions (A05: 27.95 28.75, D03: 34.52 35.32, and D11: 21.22 22.02 Mbp), six genes (Gh_A05G2325, Gh_A05G2329, Gh_A05G2334, Gh_D11G1853, Gh_D11G1876, and Gh_D11G1879) were detected to be highly expressed in fibers relative to other eight tissues by transcriptome sequencing method in 12 cotton tissues. Together, multiple favorable QTN alleles and six candidate key genes were characterized to regulate fiber development in early-maturity cotton. This will lay a solid foundation for breeding novel cotton varieties with earliness and excellent fiber-quality in the future.
| S-EPMC6107031 | biostudies-literature
Project description:The main goal of this study was to investigate the genetic basis of yield and grain quality traits in winter wheat genotypes using association mapping approach, and identify linked molecular markers for marker assisted selection. A total of 120 elite facultative/winter wheat genotypes were evaluated for yield, quality and other agronomic traits under rain-fed and irrigated conditions for two years (2011-2012) at the Tel Hadya station of ICARDA, Syria. The same genotypes were genotyped using 3,051 Diversity Array Technologies (DArT) markers, of which 1,586 were of known chromosome positions. The grain yield performance of the genotypes was highly significant both in rain-fed and irrigated sites. Average yield of the genotypes ranged from 2295 to 4038 kg/ha and 4268 to 7102 kg/ha under rain-fed and irrigated conditions, respectively. Protein content and alveograph strength (W) ranged from 13.6-16.1% and 217.6-375 Jx10-4, respectively. DArT markers wPt731910 (3B), wPt4680 (4A), wPt3509 (5A), wPt8183 (6B), and wPt0298 (2D) were significantly associated with yield under rain-fed conditions. Under irrigated condition, tPt4125 on chromosome 2B was significantly associated with yield explaining about 13% of the variation. Markers wPt2607 and wPt1482 on 5B were highly associated with protein content and alveograph strength explaining 16 and 14% of the variations, respectively. The elite genotypes have been distributed to many countries using ICARDA's International system for potential direct release and/or use as parents after local adaptation trials by the NARSs of respective countries. The QTLs identified in this study are recommended to be used for marker assisted selection after through validation using bi-parental populations.
| S-EPMC4619745 | biostudies-literature