scholarly journals opulation Structure Analysis and Genome-Wide Association Study of Rice Landraces from Qiandongnan, China, using Specific–Locus Amplified Fragment Sequencing

2021 ◽  
Vol 25 (02) ◽  
pp. 388-396
Author(s):  
Yan Li
Keyword(s):  
Association Study ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Genome Wide Association ◽  
Rice Landraces ◽  
Genome Wide ◽  
Sequencing Method ◽  
A Genome ◽  
Specific Locus

Uncovering the genetic basis of rice landraces has important applications in breeding. In this study, the specific-locus amplified fragment (SLAF) sequencing method was used to analyze the population structure and conduct a genome-wide association study (GWAS) of the agronomic traits of 60 rice species in Southeast Guizhou. We obtained a total of 178,287,776 reads, 314,065 SLAFs, and 571,521 single nucleotide polymorphisms (SNPs). A neighbor-joining phylogenetic tree, admixture proportions, and principal component analyses revealed that the investigated landraces were divided into japonica (heterozygosity rate 0.062) and indica (heterozygosity rate 0.073) groups. The groupings were consistent with the local classifications of ―He‖ and ―Gu‖ based on the resistance to seed shattering, and the SNPs clustered in the qSH1 gene. The GWAS of eight agronomic traits revealed that the signal peaks at four locations were closely related to previously reported genes or gene regions. This study demonstrates that the SLAF sequencing method combined with a GWAS may be effective for investigating the evolution of rice and identifying genes regulating complex traits in rice landraces cultivated in relatively isolated regions. © 2021 Friends Science Publishers

Genome-Wide association study identifies new elements on the genetic basis of quality-related traits in wheat across multiple environments

2020 ◽  
Author(s):  
Zhien Pu ◽  
Xueling Ye ◽  
Yang Li ◽  
Zehou Liu ◽  
Bingxin Shi ◽  
...  
Keyword(s):  
Association Study ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Snp Array ◽  
Mixed Linear Model ◽  
Genome Wide Association ◽  
Phenotypic Analysis ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Regions

Abstract Backgrounds: Grain protein concentration (GPC), grain starch concentration (GSC), and wet gluten concentration (WGC) are complex traits that determine nutrient concentration, end-use quality, and yield in wheat. To identify the elite and stable loci or genomic regions conferring high GPC, GSC, and WGC, a genome-wide association study (GWAS) based on a mixed linear model (MLM) was performed using 55K single nucleotide polymorphism (SNP) array in a panel of 236 wheat accessions, including 160 commercial varieties and 76 landraces, derived from Sichuan Province, China. The panel was evaluated for GPC, GSC, and WGC at four different fields. Results: Phenotypic analysis showed variation in GPC, GSC, and WGC among the different genotypes and environments. GWAS identified 12 quantitative trait loci (QTL) (-log10(P) > 2.5) associated with these three quality traits in at least two environments and located on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 5D, and 7D; the phenotypic variation explained (PVE) by these QTL ranged from 4.2% to 10.7%. Among these, three, seven, and two QTL are associated with GPC, GSC, and WGC, respectively; five QTL (QGsc.sicau-1BL, QGsc.sicau-1DS, QGsc.sicau-2DL.1, QGsc.sicau-2DL.2, QWgc.sicau-5DL) were defined potentially novel Compared with the previously reported QTLs/genes by linkage or association mapping, 5 QTLs (QGsc.sicau-1BL, QGsc.sicau-1DS, QGsc.sicau-2DL.1, QGsc.sicau-2DL.2, QWgc.sicau-5DL) were potentially novel. Furthermore, 21 presumptive candidate genes, which are involved in the metabolism or transportation of all kinds of carbohydrates, photosynthesis, programmed cell death, the balance of abscisic acid and ethylene, within these potentially novel genomic regions were predicted. Conclusions: This study provided new genetic resources and valuable genetic information of nutritional quality to broaden the genetic background and laid the molecular foundation for marker-assisted selection in wheat quality breeding.

scholarly journals Rapid identification of a new gene influencing low amylose content in rice landraces (Oryza sativa L.) using genome-wide association study with specific-locus amplified fragment sequencing

Genome ◽  
2017 ◽  
Vol 60 (6) ◽  
pp. 465-472 ◽  
Author(s):  
Xinghai Yang ◽  
Baoxuan Nong ◽  
Xiuzhong Xia ◽  
Zongqiong Zhang ◽  
Yu Zeng ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Gene ◽  
Genome Wide Association Study ◽  
Amylose Content ◽  
Genome Wide Association ◽  
Eating Quality ◽  
Rice Landraces ◽  
Genome Wide ◽  
New Gene ◽  
Specific Locus

Starch is the major component of milled rice, and amylose content (AC) affects eating quality. In this study, a genome-wide association study (GWAS) with specific-locus amplified fragment sequencing (SLAF-seq) data was performed for AC on a core collection of 419 rice landraces. Using the compressed mixed linear method based on the Q+K model, we identified a new gene, LAC6 (Chr6: 5.65–6.04 Mb), associated with AC in the low amylose content panel. The LAC6 candidate gene was detected by qRT-PCR in rice panicles. Results indicate that LOC_Os06g11130 was up-regulated, and LOC_Os06g11340 was significantly down-regulated, making it most likely a key candidate gene of LAC6. In conclusion, the findings provide a certain theoretiacal basis of molecular biology for genetic improvement of AC in rice and rice quality variety breeding.

scholarly journals A Genome-Wide Association Study of Highly Heritable Agronomic Traits in Durum Wheat

2019 ◽  
Vol 10 ◽  
Author(s):  
Shubin Wang ◽  
Steven Xu ◽  
Shiaoman Chao ◽  
Qun Sun ◽  
Shuwei Liu ◽  
...  
Keyword(s):  
Association Study ◽  
Durum Wheat ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

scholarly journals A Genome-Wide Association Study for Agronomic Traits in Soybean Using SNP Markers and SNP-Based Haplotype Analysis

PLoS ONE ◽  
2017 ◽  
Vol 12 (2) ◽  
pp. e0171105 ◽  
Author(s):  
Rodrigo Iván Contreras-Soto ◽  
Freddy Mora ◽  
Marco Antônio Rott de Oliveira ◽  
Wilson Higashi ◽  
Carlos Alberto Scapim ◽  
...  
Keyword(s):  
Association Study ◽  
Haplotype Analysis ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

scholarly journals Genome-wide association study in the pseudocereal quinoa reveals selection pattern typical for crops with a short breeding history

2020 ◽  
Author(s):  
Dilan S. R. Patiranage ◽  
Elodie Rey ◽  
Nazgol Emrani ◽  
Gordon Wellman ◽  
Karl Schmid ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Sequence Data ◽  
Genome Wide Association ◽  
Sequencing Data ◽  
Genome Wide ◽  
A Genome ◽  
Modern Breeding ◽  
Orphan Crop

AbstractQuinoa germplasm preserves useful and substantial genetic variation, yet it remains untapped due to a lack of implementation of modern breeding tools. We have integrated field and sequence data to characterize a large diversity panel of quinoa. Whole-genome sequencing of 310 accessions revealed 2.9 million polymorphic high confidence SNP loci. Highland and Lowland quinoa were clustered into two main groups, with FST divergence of 0.36 and fast LD decay of 6.5 and 49.8 Kb, respectively. A genome-wide association study uncovered 600 SNPs stably associated with 17 agronomic traits. Two candidate genes are associated with thousand seed weight, and a resistance gene analog is associated with downy mildew resistance. We also identified pleiotropically acting loci for four agronomic traits that are highly responding to photoperiod hence important for the adaptation to different environments. This work demonstrates the use of re-sequencing data of an orphan crop, which is partially domesticated to rapidly identify marker-trait association and provides the underpinning elements for genomics-enabled quinoa breeding.

scholarly journals Genome-wide association study and genomic selection for yield and related traits in soybean

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255761
Author(s):  
Waltram Ravelombola ◽  
Jun Qin ◽  
Ainong Shi ◽  
Qijian Song ◽  
Jin Yuan ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Selection ◽  
Plant Height ◽  
Seed Weight ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

Sign in / Sign up

Export Citation Format

Share Document