Genome-wide association study reveals the genetic control underlying node of the first fruiting branch and its height in upland cotton (Gossypium hirsutum L.)

Fu, Yuanzhi; Dong, Chengguang; Wang, Juan; Wang, Yuanyuan; Li, Chengqi

doi:10.1007/s10681-019-2361-1

Cited by 19 publications

(15 citation statements)

References 40 publications

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“…For MLM_ Q + K model analysis, the population structure ( Q ) and the kinship matrix ( K ) values were applied as covariates. Finally, 3,301 high-quality SNPs were selected for GWAS and the threshold of P-value for the significance of “suggestive association” that allows one time false positive effect in GWAS test was calculated based on “1/n” method with n being the number of SNPs as noted by many previous studies ( Cai et al 2017 , Duggal et al 2008 , Fu et al 2019 , Li et al 2013 , Shi et al 2018 , Sun et al 2017 , Yang et al 2014 ). Thus, the SNPs with -log10P ≥3.51 ( P = 1/3,301) were regarded as suggestive trait-associated SNPs.…”

Section: Methodsmentioning

confidence: 99%

Genome-wide association study of leaf chemistry traits in tobacco

et al. 2020

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Leaf chemistry traits are some of the key factors influencing tobacco quality, which can be significantly reduced by lower chemical components in cured leaf. To improve tobacco quality through breeding, genetic diversity analysis, population structure analysis, and genome-wide association studies were performed in a panel of 347 tobacco germplasms and the markers associated with five leaf chemistry traits, including total sugar (TS), reducing sugar (RS), total nitrogen (TN), nicotine (NIC), and total potassium (TP) contents were identified. Four groups were classified at a genetic distance of 0.316 by genetic diversity analysis based on coefficient parameter NEI72 using a program NTSYS-pc2.10e, whereas four well-differentiated subpopulations were postulated in the 347 tobacco accessions. A total of 47 target trait-associated SNPs was detected in at least three environments as well as the best linear unbiased predictions (BLUPs) across all environments, among which two, two, four, six, and one highly suggestive associated SNPs were repeatedly detected in all environments and BLUPs for TS, RS, TN, NIC, and TP, respectively. On the basis of the phenotypic effects of the alleles corresponding to suggestive associated SNPs, five tobacco accessions harboring favorable alleles with elite phenotypic performance in leaf chemistry traits were identified. The results could facilitate quality tobacco breeding for higher leaf chemistry trait contents through molecular marker-assisted approaches.

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Section: Methodsmentioning

confidence: 99%

Genome-wide association study of leaf chemistry traits in tobacco

et al. 2020

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“…Genome-wide association study (GWAS) is an effective approach to investigate complex phenotypic traits and to identify loci associated with target traits [32]. GWAS has been widely used to study agronomically important traits of a variety of crops, including maize, soybean, rice, cotton and wheat [33][34][35][36][37]. In addition, GWAS has been used to identify the genes underlying resistance to stripe rust in wheat [20,[38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Genome-wide association mapping reveals potential novel loci controlling stripe rust resistance in a Chinese wheat landrace diversity panel from the southern autumn-sown spring wheat zone

Wang

Cheng

et al. 2021

BMC Genomics

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Background Stripe rust, caused by the fungal pathogen Puccinia striiformis f. sp. tritici (Pst), is a serious foliar disease of wheat. Identification of novel stripe rust resistance genes and cultivation of resistant cultivars are considered to be the most effective approaches to control this disease. In this study, we evaluated the infection type (IT), disease severity (DS) and area under the disease progress curve (AUDPC) of 143 Chinese wheat landrace accessions for stripe rust resistance. Assessments were undertaken in five environments at the adult-plant stage with Pst mixture races under field conditions. In addition, IT was assessed at the seedling stage with two prevalent Pst races (CYR32 and CYR34) under a controlled greenhouse environment. Results Seventeen accessions showed stable high-level resistance to stripe rust across all environments in the field tests. Four accessions showed resistance to the Pst races CYR32 and CYR34 at the seedling stage. Combining phenotypic data from the field and greenhouse trials with 6404 markers that covered the entire genome, we detected 17 quantitative trait loci (QTL) on 11 chromosomes for IT associated with seedling resistance and 15 QTL on seven chromosomes for IT, final disease severity (FDS) or AUDPC associated with adult-plant resistance. Four stable QTL detected on four chromosomes, which explained 9.99–23.30% of the phenotypic variation, were simultaneously associated with seedling and adult-plant resistance. Integrating a linkage map of stripe rust resistance in wheat, 27 QTL overlapped with previously reported genes or QTL, whereas four and one QTL conferring seedling and adult-plant resistance, respectively, were mapped distantly from previously reported stripe rust resistance genes or QTL and thus may be novel resistance loci. Conclusions Our results provided an integrated overview of stripe rust resistance resources in a wheat landrace diversity panel from the southern autumn-sown spring wheat zone of China. The identified resistant accessions and resistance loci will be useful in the ongoing effort to develop new wheat cultivars with strong resistance to stripe rust.

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“…With the completion of cotton genome sequencing (Paterson et al 2012;Zhang et al 2015;Hu et al 2019;Huang et al 2020) and the establishment of a high-throughput genotyping platform based on the high-throughput array (Hulse-Kemp et al 2015;Cai et al 2017), a large number of single nucleotide polymorphism (SNP) markers have been developed, which greatly promoted the application genome-wide association analyses in cotton. Recently, GWAS research have mainly focused on ber quality (Gapare et al 2017;Sun et al 2017;Dong et al 2018;Li et al 2018a;Tan et al 2018;Yuan et al 2019b) and cotton yield components (Su et al 2016;Sun et al 2018;Song et al 2019;Xing et al 2019;Zhu et al 2020), disease tolerance (Li et al 2017), reniform nematode resistance (Li et al 2018c), salt tolerance (Yuan et al 2019a), drought stress (Hou et al 2018;Li et al 2020) and other agronomic traits in cotton (Li et al 2018b;Yuan et al 2018;Fu et al 2019). However, there are few reports for revealing loci and candidate genes of the lint percentage (LP, %) by GWAS and WGCNA analysis combining strategy in cotton.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide Association Study Reveals Novel Quantitative Trait Loci and Candidate Genes of Lint Percentage in Upland Cotton Based on the CottonSNP80K Array

Chen¹,

Gao²,

Chen³

et al. 2021

Preprint

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Cotton (Gossypium spp.) is an important natural textile fiber and oilseed crop widely cultivated in the world. Lint percentage (LP, %) is one of the important yield factor, thus increasing lint percentage is a core goal of cotton breeding improvement. However, the underlying genetic and molecular mechanisms that control lint percentage in upland cotton remain largely unknown. Here, we performed a Genome-wide association study (GWAS) for LP based on phenotypic tests of 254 upland cotton accessions in four environments and BLUPs using the high-density CottonSNP80K array. A total of 41,413 high-quality single-nucleotide polymorphisms (SNPs) were screened and 34 SNPs within 22 QTLs were identified as significantly associated with lint percentage trait in different environments. In total, 175 candidate genes were identified from two major genomic loci (GR1 and GR2) of upland cotton and 50 hub genes were identified through GO enrichment and WGCNA analysis. Furthermore, two candidate/causal genes, Gh_D01G0162 and Gh_D07G0463, which pleiotropically increased lint percentage were identified and further verified its function through LD blocks, haplotypes and qRT-PCR analysis. Co-expression network analysis showed that the candidate/causal and hub gene, Gh_D07G0463, was significantly related to another candidate gene, Gh_D01G0162, and the simultaneous pyramid of the two genes lays the foundation for a more efficient increase in cotton production. Our study provides crucial insights into the genetic and molecular mechanisms underlying variations of yield traits and serves as an important foundation for lint percentage improvement via marker-assisted breeding.

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Genome-wide association study reveals the genetic control underlying node of the first fruiting branch and its height in upland cotton (Gossypium hirsutum L.)

Cited by 19 publications

References 40 publications

Genome-wide association study of leaf chemistry traits in tobacco

Genome-wide association study of leaf chemistry traits in tobacco

Genome-wide association mapping reveals potential novel loci controlling stripe rust resistance in a Chinese wheat landrace diversity panel from the southern autumn-sown spring wheat zone

Genome-wide Association Study Reveals Novel Quantitative Trait Loci and Candidate Genes of Lint Percentage in Upland Cotton Based on the CottonSNP80K Array

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