scholarly journals Identification of genetic loci associated with major agronomic traits of wheat (Triticum aestivum L.) based on genome-wide association analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Woo Joo Jung ◽  
Yong Jin Lee ◽  
Chon-Sik Kang ◽  
Yong Weon Seo

Abstract Background Bread wheat (Triticum aestivum L.) is one of the most widely consumed cereal crops, but its complex genome makes it difficult to investigate the genetic effect on important agronomic traits. Genome-wide association (GWA) analysis is a useful method to identify genetic loci controlling complex phenotypic traits. With the RNA-sequencing based gene expression analysis, putative candidate genes governing important agronomic trait can be suggested and also molecular markers can be developed. Results We observed major quantitative agronomic traits of wheat; the winter survival rate (WSR), days to heading (DTH), days to maturity (DTM), stem length (SL), spike length (SPL), awn length (AL), liter weight (LW), thousand kernel weight (TKW), and the number of seeds per spike (SPS), of 287 wheat accessions from diverse country origins. A significant correlation was observed between the observed traits, and the wheat genotypes were divided into three subpopulations according to the population structure analysis. The best linear unbiased prediction (BLUP) values of the genotypic effect for each trait under different environments were predicted, and these were used for GWA analysis based on a mixed linear model (MLM). A total of 254 highly significant marker-trait associations (MTAs) were identified, and 28 candidate genes closely located to the significant markers were predicted by searching the wheat reference genome and RNAseq data. Further, it was shown that the phenotypic traits were significantly affected by the accumulation of favorable or unfavorable alleles. Conclusions From this study, newly identified MTA and putative agronomically useful genes will help to study molecular mechanism of each phenotypic trait. Further, the agronomically favorable alleles found in this study can be used to develop wheats with superior agronomic traits.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Raju Bheemanahalli ◽  
Montana Knight ◽  
Cherryl Quinones ◽  
Colleen J. Doherty ◽  
S. V. Krishna Jagadish

AbstractHigh night temperatures (HNT) are shown to significantly reduce rice (Oryza sativa L.) yield and quality. A better understanding of the genetic architecture of HNT tolerance will help rice breeders to develop varieties adapted to future warmer climates. In this study, a diverse indica rice panel displayed a wide range of phenotypic variability in yield and quality traits under control night (24 °C) and higher night (29 °C) temperatures. Genome-wide association analysis revealed 38 genetic loci associated across treatments (18 for control and 20 for HNT). Nineteen loci were detected with the relative changes in the traits between control and HNT. Positive phenotypic correlations and co-located genetic loci with previously cloned grain size genes revealed common genetic regulation between control and HNT, particularly grain size. Network-based predictive models prioritized 20 causal genes at the genetic loci based on known gene/s expression under HNT in rice. Our study provides important insights for future candidate gene validation and molecular marker development to enhance HNT tolerance in rice. Integrated physiological, genomic, and gene network-informed approaches indicate that the candidate genes for stay-green trait may be relevant to minimizing HNT-induced yield and quality losses during grain filling in rice by optimizing source-sink relationships.


2019 ◽  
Author(s):  
Waltram Ravelombola ◽  
Jun Qin ◽  
Ainong Shi ◽  
Fengmin Wang ◽  
Yan Feng ◽  
...  

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.


2021 ◽  
Author(s):  
Bo Peng ◽  
Xiaolei Zhao ◽  
Yi Wang ◽  
Chunhui Li ◽  
Yongxiang Li ◽  
...  

Abstract Compact plant-type with small leaf angle has increased canopy light interception, which is conducive to the photosynthesis of the population and higher population yield at high density planting in maize. In this study, a panel of 285 diverse maize inbred lines genotyped with 56,000 SNPs was used to investigate the genetic basis of leaf angle across three consecutive years using a genome-wide association study (GWAS). The leaf angle showed broad phenotypic variation and high heritability across different years. Population structure analysis subdivided the panel into four subgroups that correspond to the four major empirical germplasm origins in China, i.e., Tangsipingtou, Reid, Lancaster and P. When tested with the optimal GWAS model, we found that the Q+K model was the best in reducing false positive. In total, 96 SNPs accounting for 5.54%-10.44% of phenotypic variation were significantly (P<0.0001) associated with leaf angle across three years. According to the linkage disequilibrium decay distance, 96 SNPs were binned in 43 QTLs for leaf angle. Seven major QTLs with R2>8% stably detected in at least two years and BLUP values were clustered in four genomic regions (bins 2.01, 2.07, 5.06, and 10.04). Seven important candidate genes, Zm00001d001961, Zm00001d006348, Zm00001d006463, Zm00001d017618, Zm00001d024919, Zm00001d025018, and Zm00001d025033 were predicted for the seven stable major QTLs, respectively. The markers identified in this study can be used for molecular breeding for leaf angle, and the candidate genes would contribute to further understanding of the genetic basis of leaf angle.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Y. Tilahun ◽  
T. A. Gipson ◽  
T. Alexander ◽  
M. L. McCallum ◽  
P. R. Hoyt

This paper reports an exploratory study based on quantitative genomic analysis in dairy traits of American Alpine goats. The dairy traits are quality-determining components in goat milk, cheese, ice cream, etc. Alpine goat phenotypes for quality components have been routinely recorded for many years and deposited in the Council on Dairy Cattle Breeding (CDCB) repository. The data collected were used to conduct an exploratory genome-wide association study (GWAS) from 72 female Alpine goats originating from locations throughout the U.S. Genotypes were identified with the Illumina Goat 50K single-nucleotide polymorphisms (SNP) BeadChip. The analysis used a polygenic model where the dropping criterion was a call rate≥0.95. The initial dataset was composed of ~60,000 rows of SNPs and 21 columns of phenotypic traits and composed of 53,384 scaffolds containing other informative data points used for genomic predictive power. Phenotypic association with the 50K BeadChip revealed 26,074 reads of candidate genes. These candidate genes segregated as separate novel SNPs and were identified as statistically significant regions for genome and chromosome level trait associations. Candidate genes associated differently for each of the following phenotypic traits: test day milk yield (13,469 candidate genes), test day protein yield (25,690 candidate genes), test day fat yield (25,690 candidate genes), percentage protein (25,690 candidate genes), percentage fat (25,690 candidate genes), and percentage lactose content (25,690 candidate genes). The outcome of this study supports elucidation of novel genes that are important for livestock species in association to key phenotypic traits. Validation towards the development of marker-based selection that provides precision breeding methods will thereby increase the breeding value.


Cells ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 1085
Author(s):  
Veroniqa Lundbäck ◽  
Agné Kulyté ◽  
Peter Arner ◽  
Rona J. Strawbridge ◽  
Ingrid Dahlman

An increased adipocyte size relative to the size of fat depots, also denoted hypertrophic adipose morphology, is a strong risk factor for the future development of insulin resistance and type 2 diabetes. The regulation of adipose morphology is poorly understood. We set out to identify genetic loci associated with adipose morphology and functionally evaluate candidate genes for impact on adipocyte development. We performed a genome-wide association study (GWAS) in the unique GENetics of Adipocyte Lipolysis (GENiAL) cohort comprising 948 participants who have undergone abdominal subcutaneous adipose biopsy with a determination of average adipose volume and morphology. The GWAS identified 31 genetic loci displaying suggestive association with adipose morphology. Functional evaluation of candidate genes by small interfering RNAs (siRNA)-mediated knockdown in adipose-derived precursor cells identified six genes controlling adipocyte renewal and differentiation, and thus of potential importance for adipose hypertrophy. In conclusion, genetic and functional studies implicate a regulatory role for ATL2, ARHGEF10, CYP1B1, TMEM200A, C17orf51, and L3MBTL3 in adipose morphology by their impact on adipogenesis.


2020 ◽  
Author(s):  
Fang Wang ◽  
Meiling Zou ◽  
Long Zhao ◽  
Huaqing Li ◽  
Zhiqiang Xia ◽  
...  

Abstract Background: Potatoes are dicotyledonous plants of the genus Solanum, family Solanaceae, and contain large amounts of starch, proteins, and trace elements required by the human. Potato late blight is the main disease hindering potato production. In this study, Phytophthora infestans were used to quantify late blight resistance in 284 germplasm resources, and resistance genes were mined through genome-wide association analysis.Results: The results showed that among the 284 potato germplasm resources, 37 showed immunity, 15 were highly resistant to late blight, 30 were moderately resistant to late blight, 107 were moderately susceptible to late blight, and 95 were highly susceptible to late blight. Through screening and filtering, 22,489 high-quality single-nucleotide polymorphisms (SNPs) and indels were obtained. Through population structure analysis and principal-component analysis, 284 germplasm resources were divided into eight subgroups, which was consistent with the results of the phylogenetic tree analysis. The genetic diversity index of the 284 potato germplasm resources was 0.2161, and the differentiation index of each subgroup was 0.0251-0.1489. A mixed linear model was built to perform an association analysis on the diameter of the lesions identified from isolated leaves of potato affected by late blight. The genes within 100 kb of both sides of the obtained significant SNP loci were searched and functionally annotated, and 18 candidate genes were obtained. Twenty-two candidate genes were obtained from the association analysis of disease resistance grade.Conclusions: 284 potato germplasm resources were used to identify for Phytophthora infestans resistance. The potato germplasm resources were divided into 8 subgroups by population structure analysis, and the main differentiation among subgroups was moderate. Candidate genes were mined by genome-wide association analysis.The results of this study provides the foundation for the genetic improvement of potato varieties resistant to late blight.


2021 ◽  
Vol 11 ◽  
Author(s):  
Xianju Lu ◽  
Jinglu Wang ◽  
Yongjian Wang ◽  
Weiliang Wen ◽  
Ying Zhang ◽  
...  

Dry matter accumulation and partitioning during the early phases of development could significantly affect crop growth and productivity. In this study, the aboveground dry matter (DM), the DM of different organs, and partition coefficients of a maize association mapping panel of 412 inbred lines were evaluated at the third and sixth leaf stages (V3 and V6). Further, the properties of these phenotypic traits were analyzed. Genome-wide association studies (GWAS) were conducted on the total aboveground biomass and the DM of different organs. Analysis of GWAS results identified a total of 1,103 unique candidate genes annotated by 678 significant SNPs (P value &lt; 1.28e–6). A total of 224 genes annotated by SNPs at the top five of each GWAS method and detected by multiple GWAS methods were regarded as having high reliability. Pathway enrichment analysis was also performed to explore the biological significance and functions of these candidate genes. Several biological pathways related to the regulation of seed growth, gibberellin-mediated signaling pathway, and long-day photoperiodism were enriched. The results of our study could provide new perspectives on breeding high-yielding maize varieties.


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