Dual-Model GWAS Analysis and Genomic Selection of Maize Flowering Time-Related Traits
Ontology highlight
ABSTRACT:
SUBMITTER:
PROVIDER: S-EPMC11203321 | biostudies-literature | 2024 Jun
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundFlowering time is an important agronomic trait of crops and significantly affects plant adaptation and seed production. Flowering time varies greatly among maize (Zea mays) inbred lines, but the genetic basis of this variation is not well understood. Here, we report the comprehensive genetic architecture of six flowering time-related traits using a recombinant inbred line (RIL) population obtained from a cross between two maize genotypes, B73 and Abe2, and combined with genome-wide association studies to identify candidate genes that affect flowering time.ResultsOur results indicate that these six traits showed extensive phenotypic variation and high heritability in the RIL population. The flowering time of this RIL population showed little correlation with the leaf number under different environmental conditions. A genetic linkage map was constructed by 10,114 polymorphic markers covering the whole maize genome, which was applied to QTL mapping for these traits, and identified a total of 82 QTLs that contain 13 flowering genes. Furthermore, a combined genome-wide association study and linkage mapping analysis revealed 17 new candidate genes associated with flowering time.ConclusionsIn the present study, by using genetic mapping and GWAS approaches with the RIL population, we revealed a list of genomic regions and candidate genes that were significantly associated with flowering time. This work provides an important resource for the breeding of flowering time traits in maize.
| S-EPMC9264602 | biostudies-literature
Project description:Maize (Zea mays) inbred lines vary greatly in flowering time, but the genetic basis of this variation is unknown. In this study, three maize flowering-related traits (DTT, days to tasselling; DTP, days to pollen shed; DTS, days to silking) were evaluated with an association panel consisting of 226 maize inbred lines and an F2:3 population with 120 offspring from a cross between the T32 and Qi319 lines in different environments. A total of 82 significant single nucleotide polymorphisms (SNPs) and 117 candidate genes were identified by genome-wide association analysis. Twenty-one quantitative trait loci (QTLs) and 65 candidate genes were found for maize flowering time by linkage analysis with the constructed high-density genetic map. Transcriptome analysis was performed for Qi319, which is an early-maturing inbred line, and T32, which is a late-maturing inbred line, in two different environments. Compared with T32, Qi319 showed upregulation of 3815 genes and downregulation of 3906 genes. By integrating a genome-wide association study (GWAS), linkage analysis and transcriptome analysis, 25 important candidate genes for maize flowering time were identified. Together, our results provide an important resource and a foundation for an enhanced understanding of flowering time in maize.
| S-EPMC10073556 | biostudies-literature
Project description:BackgroundTransition to flowering at the right time is critical for local adaptation and to maximize grain yield in crops. Canola is an important oilseed crop with extensive variation in flowering time among varieties. However, our understanding of underlying genes and their role in canola productivity is limited.ResultsWe report our analyses of a diverse GWAS panel (300-368 accessions) of canola and identify SNPs that are significantly associated with variation in flowering time and response to photoperiod across multiple locations. We show that several of these associations map in the vicinity of FLOWERING LOCUS T (FT) paralogs and its known transcriptional regulators. Complementary QTL and eQTL mapping studies, conducted in an Australian doubled haploid population, also detected consistent genomic regions close to the FT paralogs associated with flowering time and yield-related traits. FT sequences vary between accessions. Expression levels of FT in plants grown in field (or under controlled environment cabinets) correlated with flowering time. We show that markers linked to the FT paralogs display association with variation in multiple traits including flowering time, plant emergence, shoot biomass and grain yield.ConclusionsOur findings suggest that FT paralogs not only control flowering time but also modulate yield-related productivity traits in canola.
| S-EPMC6685183 | biostudies-literature
Project description:Traits related to flowering time are the most promising agronomic traits that directly impact the seed yield and oil quality of rapeseed (Brassica napus L.). Developing early flowering and maturity rapeseed varieties is an important breeding objective in B. napus. Many studies have reported on days to flowering, but few have reported on budding, bolting, and the interval between bolting and DTF. Therefore, elucidating the genetic architecture of QTLs and genes regulating flowering time, we presented an integrated investigation on SNP and haplotype-based genome-wide association study of 373 diverse B. napus germplasm, which were genotyped by the 60K SNP array and were phenotyped in the four environments. The results showed that a total of 15 and 37 QTLs were detected from SNP and haplotype-based GWAS, respectively. Among them, seven QTL clusters were identified by haplotype-based GWAS. Moreover, three and eight environmentally stable QTLs were detected by SNP-GWAS and haplotype-based GWAS, respectively. By integrating the above two approaches and by co-localizing the four traits, ten (10) genomic regions were under selection on chromosomes A03, A07, A08, A10, C06, C07, and C08. Interestingly, the genomic regions FT.A07.1, FT.A08, FT.C06, and FT.C07 were identified as novel. In these ten regions, a total of 197 genes controlling FT were detected, of which 14 highly expressed DEGs were orthologous to 13 Arabidopsis thaliana genes after integration with transcriptome results. In a nutshell, the above results uncovered the genetic architecture of important agronomic traits related to flowering time and provided a basis for multiple molecular marker-trait associations in B. napus.
| S-EPMC8619824 | biostudies-literature
Project description:In the field, maize flowering time and height traits are closely linked with yield, planting density, lodging resistance, and grain fill. To explore the genetic basis of flowering time and height traits in maize, we investigated six related traits, namely, days to anthesis (AD), days to silking (SD), the anthesis-silking interval (ASI), plant height (PH), ear height (EH), and the EH/PH ratio (ER) in two locations for two years based on two doubled haploid (DH) populations. Based on the two high-density genetic linkage maps, 12 and 22 quantitative trait loci (QTL) were identified, respectively, for flowering time and height-related traits. Of these, ten QTLs had overlapping confidence intervals between the two populations and were integrated into three consensus QTLs (qFT_YZ1a, qHT_YZ5a, and qHT_YZ7a). Of these, qFT_YZ1a, conferring flowering time, is located at 221.1-277.0 Mb on chromosome 1 and explained 10.0-12.5% of the AD and SD variation, and qHT_YZ5a, conferring height traits, is located at 147.4-217.3 Mb on chromosome 5 and explained 11.6-15.3% of the PH and EH variation. These consensus QTLs, in addition to the other repeatedly detected QTLs, provide useful information for further genetic studies and variety improvements in flowering time and height-related traits.
| S-EPMC8399143 | biostudies-literature
Project description:Genomic selection (GS) is the one of the new method for molecular marker-assisted selection (MAS) that can improve selection efficiency and thereby accelerate selective breeding progress. In the present study, we used the exotic germplasm LK1 to improve the shelling percentage of Qi319 by GS. Genome-wide marker effects for each trait were estimated based on the performance of the testcross and SNP data for F2 progenies in the training population. The accuracy of genomic predictions was estimated as the correlation between marker-predicted genotypic values and phenotypic values of the testcrosses for each trait in the validation population. Our study result indicated that selection response for shell percentage was 33.7%, which is greater than those for grain yield, kernel number per ear, or grain moisture at harvest. Selection response for tassel branch number and weight per 100 kernels was greater than 60%. The Higher trait heritability resulted in better prediction efficiency; Prediction accuracy increased with the training population size; Prediction efficiency did not differ significantly between SNP densities of 1000 bp and 55,000 bp. The results of the present research project will provide a basis for genome-wide selection technology in maize breeding, and lay the groundwork for the application of GS to germplasms that are useful in China.
| S-EPMC6711738 | biostudies-literature
Project description:Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.
| S-EPMC10674677 | biostudies-literature
Project description:The quality of corn kernels is crucial for their nutritional value, making the enhancement of kernel quality a primary objective of contemporary corn breeding efforts. This study utilized 260 corn inbred lines as research materials and assessed three traits associated with grain quality. A genome-wide association study (GWAS) was conducted using the best linear unbiased estimator (BLUE) for quality traits, resulting in the identification of 23 significant single nucleotide polymorphisms (SNPs). Additionally, nine genes associated with grain quality traits were identified through gene function annotation and prediction. Furthermore, a total of 697 quantitative trait loci (QTL) related to quality traits were compiled from 27 documents, followed by a meta-QTL analysis that revealed 40 meta-QTL associated with these traits. Among these, 19 functional genes and reported candidate genes related to quality traits were detected. Three significant SNPs identified by GWAS were located within the intervals of these QTL, while the remaining eight significant SNPs were situated within 2 Mb of the QTL. In summary, the findings of this study provide a theoretical framework for analyzing the genetic basis of corn grain quality-related traits and for enhancing corn quality.
| S-EPMC11479128 | biostudies-literature
Project description:PremisePlant flowering time plays an important role in plant fitness and thus evolutionary processes. Soil microbial communities are diverse and have a large impact, both positive and negative, on the host plant. However, owing to few available studies, how the soil microbial community may influence the evolutionary response of plant populations is not well understood. Here we sought to uncover whether belowground microbial communities act as an agent of selection on flowering and growth traits in the common morning glory, Ipomoea purpurea.MethodsWe performed a controlled greenhouse experiment in which genetic lines of I. purpurea were planted into either sterilized soils or in soils that were sterilized and inoculated with the microbial community from original field soil. We could thus directly test the influence of alterations to the microbial community on plant growth, flowering, and fitness and assess patterns of selection in both soil microbial environments.ResultsA more complex soil microbial community resulted in larger plants that produced more flowers. Selection strongly favored earlier flowering when plants were grown in the complex microbial environment than compared to sterilized soil. We also uncovered a pattern of negative correlational selection on growth rate and flowering time, indicating that selection favored different combinations of growth and flowering traits in the simplified versus complex soil community.ConclusionsTogether, these results suggest the soil microbial community is a selective agent on flowering time and ultimately that soil microbial community influences important plant evolutionary processes.
| S-EPMC7065020 | biostudies-literature
Project description:Despite the reduction in the price of sequencing, it remains expensive to sequence and assemble whole, complex genomes of multiple samples for population studies, particularly for large genomes like those of many crop species. Enrichment of target genome regions coupled with next generation sequencing is a cost-effective strategy to obtain sequence information for loci of interest across many individuals, providing a less expensive approach to evaluating sequence variation at the population scale. Here we evaluate amplicon-based enrichment coupled with semiconductor sequencing on a validation set consisting of three maize inbred lines, two hybrids and 19 landrace accessions. We report the use of a multiplexed panel of 319 PCR assays that target 20 candidate loci associated with photoperiod sensitivity in maize while requiring 25 ng or less of starting DNA per sample. Enriched regions had an average on-target sequence read depth of 105 with 98% of the sequence data mapping to the maize 'B73' reference and 80% of the reads mapping to the target interval. Sequence reads were aligned to B73 and 1,486 and 1,244 variants were called using SAMtools and GATK, respectively. Of the variants called by both SAMtools and GATK, 30% were not previously reported in maize. Due to the high sequence read depth, heterozygote genotypes could be called with at least 92.5% accuracy in hybrid materials using GATK. The genetic data are congruent with previous reports of high total genetic diversity and substantial population differentiation among maize landraces. In conclusion, semiconductor sequencing of highly multiplexed PCR reactions is a cost-effective strategy for resequencing targeted genomic loci in diverse maize materials.
| S-EPMC5207663 | biostudies-literature