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

2021 ◽  
Vol 12 ◽  
Author(s):  
Wenliang Yan ◽  
Benjamin Karikari ◽  
Fangguo Chang ◽  
Fangzhou Zhao ◽  
Yinghu Zhang ◽  
...  
Keyword(s):  
Association Study ◽  
Quantitative Trait ◽  
Growth Stage ◽  
Genome Wide Association Study ◽  
Growth Period ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Phenotypic Data ◽  
Seed Formation ◽  
Genome Wide

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.

scholarly journals Identification of genetic loci and candidate genes related to soybean flowering through genome wide association study

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Minmin Li ◽  
Ying Liu ◽  
Yahan Tao ◽  
Chongjing Xu ◽  
Xin Li ◽  
...  
Keyword(s):  
Association Study ◽  
Flowering Time ◽  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Growth Period ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Chromosome 1 ◽  
Genome Wide ◽  
A Genome

Abstract Background As a photoperiod-sensitive and self-pollinated species, the growth periods traits play important roles in the adaptability and yield of soybean. To examine the genetic architecture of soybean growth periods, we performed a genome-wide association study (GWAS) using a panel of 278 soybean accessions and 34,710 single nucleotide polymorphisms (SNPs) with minor allele frequencies (MAF) higher than 0.04 detected by the specific-locus amplified fragment sequencing (SLAF-seq) with a 6.14-fold average sequencing depth. GWAS was conducted by a compressed mixed linear model (CMLM) involving in both relative kinship and population structure. Results GWAS revealed that 37 significant SNP peaks associated with soybean flowering time or other growth periods related traits including full bloom, beginning pod, full pod, beginning seed, and full seed in two or more environments at -log10(P) > 3.75 or -log10(P) > 4.44 were distributed on 14 chromosomes, including chromosome 1, 2, 3, 5, 6, 9, 11, 12, 13, 14, 15, 17, 18, 19. Fourteen SNPs were novel loci and 23 SNPs were located within known QTLs or 75 kb near the known SNPs. Five candidate genes (Glyma.05G101800, Glyma.11G140100, Glyma.11G142900, Glyma.19G099700, Glyma.19G100900) in a 90 kb genomic region of each side of four significant SNPs (Gm5_27111367, Gm11_10629613, Gm11_10950924, Gm19_34768458) based on the average LD decay were homologs of Arabidopsis flowering time genes of AT5G48385.1, AT3G46510.1, AT5G59780.3, AT1G28050.1, and AT3G26790.1. These genes encoding FRI (FRIGIDA), PUB13 (plant U-box 13), MYB59, CONSTANS, and FUS3 proteins respectively might play important roles in controlling soybean growth periods. Conclusions This study identified putative SNP markers associated with soybean growth period traits, which could be used for the marker-assisted selection of soybean growth period traits. Furthermore, the possible candidate genes involved in the control of soybean flowering time were predicted.

scholarly journals Dissecting Four Correlated Growth Period Traits Using a Genome-Wide Association Study Approach in Soybean

2021 ◽  
Author(s):  
Yinghui Li ◽  
Li Yanfei ◽  
Hong Huilong ◽  
Ma Yansong ◽  
Gu Yongzhe ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Growth Period ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Study Approach ◽  
Genome Wide ◽  
A Genome ◽  
Photoperiod Sensitive

Abstract Soybean (Glycine max (L.) Merri) is a short-day, photoperiod-sensitive crop. The vegetative growth period (V), reproductive growth period (R), whole growth period (V + R) and the ratio of growth period structure (R/V) are photoperiod traits critical to adaptability and yield in soybean. To thoroughly dissect the genetic basis of these growth period traits and their correlations, a panel of 277 soybean accessions were genotyped with a single nucleotide polymorphisms (SNPs) chip and phenotyped at three field environments over three years. A genome-wide association study found 29 SNPs on fifteen chromosomes with 33 significant marker-trait associations, eleven, eight, four and ten for V, R, V + R and R/V, respectively. Two SNPs, Map-6077 and − 6502, showed pleiotropy in three and two traits, respectively. Map-6077, associated with V, R, and V + R, was a synonymous SNP of the GmMFT, a member of PEBP family that has been reported to inhibit seed germination and regulate oil content. These results provide candidate SNP markers and genes for further functional experiments to advance molecular marker-assisted breeding.

Genetic dissection of 2-heptenal content in soybean (Glycine max) seed through genome-wide association study

2020 ◽  
Vol 71 (10) ◽  
pp. 884
Author(s):  
Zhikun Wang ◽  
Mingming Yang ◽  
Yuanzhuo Wang ◽  
Chao Yang ◽  
Xue Zhao ◽  
...  
Keyword(s):  
Glycine Max ◽  
Association Study ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Fatty Acid Content ◽  
Soybean Seed ◽  
Genome Wide Association ◽  
Quality Characteristic ◽  
Genome Wide ◽  
A Genome

Association analysis is an alternative to conventional, family-based methods for detecting the location of gene(s) or quantitative trait loci (QTLs), and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Flavour is an essential quality characteristic of soymilk; however, soymilk contains volatile compounds unacceptable to consumers. One of main constituents in the volatiles of normal soymilk is 2-heptenal, which is thought to be a degradative oxidation product of polyunsaturated acids. In this study, a genome-wide association study using 24651 single-nucleotide polymorphisms (SNPs) was performed to identify quantitative trait nucleotides (QTNs) controlling 2-heptenal content in soybean (Glycine max (L.) Merr.) seed from a natural population of 110 soybean germplasm accessions. We detected 62 significant QTNs located on 18 different chromosomes that are significantly associated with 2-heptenal content in soybean seed. Among these, 17 QTNs co-localised with QTLs previously found to be related to protein, oil and/or fatty acid content in soybean seed. We also identified some candidate genes involved in lipid metabolism. These findings further our understanding of the genetic basis of 2-heptenal content in soybean seed and the improvement of marker-assisted breeding efficiency, which will be important for breeding soybean cultivars with low 2-heptenal content.

scholarly journals A Genome-Wide Association Study Identifies Protein Quantitative Trait Loci (pQTLs)

PLoS Genetics ◽  
2008 ◽  
Vol 4 (5) ◽  
pp. e1000072 ◽  
Author(s):  
David Melzer ◽  
John R. B. Perry ◽  
Dena Hernandez ◽  
Anna-Maria Corsi ◽  
Kara Stevens ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Association Study ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome ◽  
Trait Loci

scholarly journals Genome-wide association study and genomic selection for plant height, maturity, seed weight, and yield in soybean

2019 ◽  
Author(s):  
Waltram Ravelombola ◽  
Jun Qin ◽  
Ainong Shi ◽  
Fengmin Wang ◽  
Yan Feng ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Selection ◽  
Candidate Genes ◽  
Plant Height ◽  
Seed Weight ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide

Abstract Background Soybean [ Glycine max (L.) Merr.] is a legume of great interest worldwide. Enhancing genetic gain for agronomic traits via molecular approaches has been long considered as the main task for soybean breeders and geneticists. The objectives of this study were to evaluate maturity, plant height, seed weight, and yield in a diverse soybean accession panel, to conduct a genome-wide association study (GWAS) for these traits and identify SNP markers associated with the four traits, and to assess genomic selection (GS) accuracy. Results A total of 250 soybean accessions were evaluated for maturity, plant height, seed weight, and yield over three years. This panel was genotyped with a total of 10,259 high quality SNPs postulated from genotyping by sequencing (GBS). GWAS was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model, and GS was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that a total of 20, 31, 37, 31, and 23 SNPs were significantly associated with the average 3-year data for maturity, plant height, seed weight, and yield, respectively; some significant SNPs were mapped into previously described loci ( E2 , E4 , and Dt1 ) affecting maturity and plant height in soybean and a new locus mapped on chromosome 20 was significantly associated with plant height; Glyma.10g228900 , Glyma.19g200800 , Glyma.09g196700 , and Glyma.09g038300 were candidate genes found in the vicinity of the top or the second best SNP for maturity, plant height, seed weight, and yield, respectively; a 11.5-Mb region of chromosome 10 was associated with both seed weight and yield; and GS accuracy was trait-, year-, and population structure-dependent. Conclusions The SNP markers identified from this study for plant height, maturity, seed weight and yield can be used to improve the four agronomic traits through marker-assisted selection (MAS) and GS in soybean breeding programs. After validation, the candidate genes can be transferred to new cultivars using SNP markers through MAS. The high GS accuracy has confirmed that the four agronomic traits can be selected in molecular breeding through GS.

scholarly journals Genome-wide association study overcomes the genome complexity in autohexaploid chrysanthemum and tags SNP markers onto the flower color genes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Katsuhiko Sumitomo ◽  
Kenta Shirasawa ◽  
Sachiko Isobe ◽  
Hideki Hirakawa ◽  
Tamotsu Hisamatsu ◽  
...  
Keyword(s):  
Single Dose ◽  
Association Study ◽  
Allele Frequency ◽  
Dna Markers ◽  
Genome Wide Association Study ◽  
Chrysanthemum Morifolium ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Complexity ◽  
Genome Wide

Abstract The use of DNA markers has revolutionized selection in crop breeding by linkage mapping and QTL analysis, but major problems still remain for polyploid species where marker-assisted selection lags behind the situation in diploids because of its high genome complexity. To overcome the complex genetic mode in the polyploids, we investigated the development of a strategy of genome-wide association study (GWAS) using single-dose SNPs, which simplify the segregation patterns associated polyploids, with respect to the development of DNA markers. In addition, we employed biparental populations for the GWAS, wherein the SNP allele frequency could be predicted. The research investigated whether the method could be used to effectively develop DNA markers for petal color in autohexaploid chrysanthemum (Chrysanthemum morifolium; 2n = 6x = 54). The causal gene for this trait is already-known CmCCD4a encoding a dioxygenase which cleaves carotenoids in petals. We selected 9,219 single-dose SNPs, out of total 52,489 SNPs identified by dd-RAD-Seq, showing simplex (1 × 0) and double-simplex (1 × 1) inheritance pattern according to alternative allele frequency with respect to the SNP loci in the F1 population. GWAS, using these single-dose SNPs, discovered highly reproducible SNP markers tightly linked to the causal genes. This is the first report of a straightforward GWAS-based marker developing system for use in autohexaploid species.

scholarly journals Identification of Quantitative Trait Loci for Leaf Rust and Stem Rust Seedling Resistance in Bread Wheat Using a Genome-Wide Association Study

Plants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 74
Author(s):  
Alibek Zatybekov ◽  
Yuliya Genievskaya ◽  
Aralbek Rsaliyev ◽  
Akerke Maulenbay ◽  
Gulbahar Yskakova ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Association Study ◽  
Leaf Rust ◽  
Bread Wheat ◽  
Stem Rust ◽  
Quantitative Trait ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

In recent years, leaf rust (LR) and stem rust (SR) have become a serious threat to bread wheat production in Kazakhstan. Most local cultivars are susceptible to these rusts, which has affected their yield and quality. The development of new cultivars with high productivity and LR and SR disease resistance, including using marker-assisted selection, is becoming an important priority in local breeding projects. Therefore, the search for key genetic factors controlling resistance in all plant stages, including the seedling stage, is of great significance. In this work, we applied a genome-wide association study (GWAS) approach using 212 local bread wheat accessions that were phenotyped for resistance to specific races of Puccinia triticina Eriks. (Pt) and Puccinia graminis f. sp. tritici (Pgt) at the seedling stages. The collection was genotyped using a 20 K Illumina iSelect SNP assay, and 11,150 polymorphic SNP markers were selected for the association mapping. Using a mixed linear model, we identified 11 quantitative trait loci (QTLs) for five out of six specific races of Pt and Pgt. The comparison of the results from this GWAS with those from previously published work showed that nine out of eleven QTLs for LR and SR resistance had been previously reported in a GWAS study at the adult plant stages of wheat growth. Therefore, it was assumed that these nine common identified QTLs were effective for all-stage resistance to LR and SR, and the two other QTLs appear to be novel QTLs. In addition, five out of these nine QTLs that had been identified earlier were found to be associated with yield components, suggesting that they may directly influence the field performance of bread wheat. The identified QTLs, including novel QTLs found in this study, may play an essential role in the breeding process for improving wheat resistance to LR and SR.

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