Dataset Information

Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean.

ABSTRACT: The time to flowering (DF), pod beginning (DPB), seed formation (DSF), and maturity initiation (DMI) in soybean (Glycine max [L.] Merr) are important characteristics of growth stage traits (GSTs) in Chinese summer-sowing soybean, and are influenced by genetic as well as environmental factors. To better understand the molecular mechanism underlying the initiation times of GSTs, we investigated four GSTs of 309 diverse soybean accessions in six different environments and Best Linear Unbiased Prediction values. Furthermore, the genome-wide association study was conducted by a Fixed and random model Circulating Probability Unification method using over 60,000 single nucleotide polymorphism (SNP) markers to identify the significant quantitative trait nucleotide (QTN) regions with phenotypic data. As a result, 212 SNPs within 102 QTN regions were associated with four GSTs. Of which, eight stable regions were repeatedly detected in least three datasets for one GST. Interestingly, half of the QTN regions overlapped with previously reported quantitative trait loci or well-known soybean growth period genes. The hotspots associated with all GSTs were concentrated on chromosome 10. E2 (Glyma10g36600), a gene with a known function in regulating flowering and maturity in soybean, is also found on this chromosome. Thus, this genomic region may account for the strong correlation among the four GSTs. All the significant SNPs in the remaining 7 QTN regions could cause the significant phenotypic variation with both the major and minor alleles. Two hundred and seventy-five genes in soybean and their homologs in Arabidopsis were screened within ± 500 kb of 7 peak SNPs in the corresponding QTN regions. Most of the genes are involved in flowering, response to auxin stimulus, or regulation of seed germination, among others. The findings reported here provide an insight for genetic improvement which will aid in breeding of soybean cultivars that can be adapted to the various summer sowing areas in China and beyond.

SUBMITTER: Yan W

PROVIDER: S-EPMC8476948 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSince the domestication of chicken, various breeds have been developed for food production, entertainment, and so on. Compared to indigenous chicken breeds which generally do not show elite production performance, commercial breeds or lines are selected intensely for meat or egg production. In the present study, in order to understand the molecular mechanisms underlying the dramatic differences of egg number between commercial egg-type chickens and indigenous chickens, we performed a genome-wide association study (GWAS) in a mixed linear model.ResultsWe obtained 148 single nucleotide polymorphisms (SNPs) associated with egg number traits (57 significantly, 91 suggestively). Among them, 4 SNPs overlapped with previously reported quantitative trait loci (QTL), including 2 for egg production and 2 for reproductive traits. Furthermore, we identified 32 candidate genes based on the function of the screened genes. These genes were found to be mainly involved in regulating hormones, playing a role in the formation, growth, and development of follicles, and in the development of the reproductive system. Some genes such as NELL2 (neural EGFL like 2), KITLG (KIT ligand), GHRHR (Growth hormone releasing hormone receptor), NCOA1 (Nuclear receptor coactivator 1), ITPR1 (inositol 1, 4, 5-trisphosphate receptor type 1), GAMT (guanidinoacetate N-methyltransferase), and CAMK4 (calcium/calmodulin-dependent protein kinase IV) deserve our attention and further study since they have been reported to be closely related to egg production, egg number and reproductive traits. In addition, the most significant genomic region obtained in this study was located at 48.61-48.84 Mb on GGA5. In this region, we have repeatedly identified four genes, in which YY1 (YY1 transcription factor) and WDR25 (WD repeat domain 25) have been shown to be related to oocytes and reproductive tissues, respectively, which implies that this region may be a candidate region underlying egg number traits.ConclusionOur study utilized the genomic information from various chicken breeds or populations differed in the average annual egg number to understand the molecular genetic mechanisms involved in egg number traits. We identified a series of SNPs, candidate genes, or genomic regions that associated with egg number, which could help us in developing the egg production trait in chickens.

Project description:The population growth trend in recent decades has resulted in continuing efforts to guarantee food security in which leguminous plants, such as the common bean (Phaseolus vulgaris L.), play a particularly important role as they are relatively cheap and have high nutritional value. To meet this demand for food, the main target for genetic improvement programs is to increase productivity, which is a complex quantitative trait influenced by many component traits. This research aims to identify Quantitative Trait Nucleotides (QTNs) associated with productivity and its components using multi-locus genome-wide association studies. Ten morpho-agronomic traits [plant height (PH), first pod insertion height (FPIH), number of nodules (NN), pod length (PL), total number of pods per plant (NPP), number of locules per pod (LP), number of seeds per pod (SP), total seed weight per plant (TSW), 100-seed weight (W100), and grain yield (YLD)] were evaluated in four environments for 178 Mesoamerican common bean domesticated accessions belonging to the Brazilian Diversity Panel. In order to identify stable QTNs, only those identified by multiple methods (mrMLM, FASTmrMLM, pLARmEB, and ISIS EM-BLASSO) or in multiple environments were selected. Among the identified QTNs, 64 were detected at least thrice by different methods or in different environments, and 39 showed significant phenotypic differences between their corresponding alleles. The alleles that positively increased the corresponding traits, except PH (for which lower values are desired), were considered favorable alleles. The most influenced trait by the accumulation of favorable alleles was PH, showing a 51.7% reduction, while NN, TSW, YLD, FPIH, and NPP increased between 18 and 34%. Identifying QTNs in several environments (four environments and overall adjusted mean) and by multiple methods reinforces the reliability of the associations obtained and the importance of conducting these studies in multiple environments. Using these QTNs through molecular techniques for genetic improvement, such as marker-assisted selection or genomic selection, can be a strategy to increase common bean production.

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Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean.

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