Genome-wide association study of micronaire using a natural population of representative upland cotton (Gossypium hirsutum L.)

Song, Jikun; Pei, Wenfeng; Ma, Jianjiang; Yang, Shaobo; Jia, Bing; Bian, Yingying; Yue, Xin; Wu, Luyao; Zang, Xinshan; Qu, Yanying; Zhang, Jinfa; Wu, Man; Yu, Jie-Ae

doi:10.1186/s42397-021-00089-1

Cited by 10 publications

(10 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The cDNA was synthesized by using a reverse transcription kit HiScript III Q RT SuperMix for qPCR (Vazyme Biotech Co., Ltd.). Furthermore, the ChamQ Universal SYBR qPCR Master Mix Kit (Vazyme) was used to carry out qRT‐PCR verification as previously described (Song et al, 2020). The real‐time PCR primers are listed in Table S1.…”

Section: Methodsmentioning

confidence: 99%

Transcriptome analysis and identification of genes associated with oil accumulation in upland cotton

Song

Pei

Wang

et al. 2022

Physiologia Plantarum

Self Cite

View full text Add to dashboard Cite

Cotton is not only the most important fiber crop but also the fifth most important oilseed crop in the world because of its oil‐rich seeds as a byproduct of fiber production. By comparative transcriptome analysis between two germplasms with diverse oil accumulation, we reveal pieces of the gene expression network involved in the process of oil synthesis in cottonseeds. Approximately, 197.16 Gb of raw data from 30 RNA sequencing samples with 3 biological replicates were generated. Comparison of the high‐oil and low‐oil transcriptomes enabled the identification of 7682 differentially expressed genes (DEGs). Based on gene expression profiles relevant to triacylglycerol (TAG) biosynthesis, we proposed that the Kennedy pathway (diacylglycerol acyltransferase‐catalyzed diacylglycerol to TAG) is the main pathway for oil production, rather than the phospholipid diacylglycerol acyltransferase‐mediated pathway. Using weighted gene co‐expression network analysis, 5312 DEGs were obtained and classified into 14 co‐expression modules, including the MEblack module containing 10 genes involved in lipid metabolism. Among the DEGs in the MEblack module, GhCYSD1 was identified as a potential key player in oil biosynthesis. The overexpression of GhCYSD1 in yeast resulted in increased oil content and altered fatty acid composition. This study may not only shed more light on the underlying molecular mechanism of oil accumulation in cottonseed oil, but also provide a set of new gene for potential enhancement of oil content in cottonseeds.

show abstract

Section: Methodsmentioning

confidence: 99%

Transcriptome analysis and identification of genes associated with oil accumulation in upland cotton

Song

Pei

Wang

et al. 2022

Physiologia Plantarum

Self Cite

View full text Add to dashboard Cite

show abstract

“…Overexpression of a gene that encodes a fiber-preferential actin-binding protein, GhPFN2, resulted in early termination of fiber elongation and a shorter fiber phenotype . Suppression of a tubulin-interacting gene, GhMAP20L5, significantly reduced the cotton fiber cell elongation rate, fiber length, and lint percentage (Song et al, 2023).…”

Section: Crop Sciencementioning

confidence: 98%

“…Recently, live-cell imaging revealed that cotton fibers elongate by tip-biased diffuse growth (Yu et al, 2019). Multiple studies have shown that genes encoding proteins that affect the cytoskeleton are essential for cotton fiber elongation (Li et al, 2007(Li et al, , 2005Preuss et al, 2004;Song et al, 2023;Thyssen et al, 2017;Wang et al, 2009;Zhang, Han, et al, 2017). A member of the XI-K myosin protein (GhXIK) family was identified by GWAS as a major QTL for fiber length, elongation, strength, and uniformity .…”

Section: 21mentioning

confidence: 99%

“…Advances in high‐throughput sequencing, bioinformatics, and biotechnology have provided new tools that can help in the development of cotton varieties with high yield and superior fiber properties. GWAS has been proven as an efficient approach to identify the major QTLs and potential genes associated with fiber quality traits (Chen et al., 2022; Dong et al., 2019; Islam, Thyssen, et al., 2016; Li, Fu, et al., 2018, 2020; Liu et al., 2018; Liu, Song, et al., 2020; Ma et al., 2018; Sarfraz et al., 2021; Song, Pei, et al., 2021; Song, Zhu, et al., 2021; Su et al., 2020; Thyssen et al., 2019; Wang, Qi, et al., 2022; Yu et al., 2021; Zhao et al., 2022; Zhu et al., 2020). Functional analyses of candidate‐genes associated with fiber quality traits determine the causative genes.…”

Section: Concluding Remarks and Future Perspectivesmentioning

confidence: 99%

See 1 more Smart Citation

Bridging molecular genetics and genomics for cotton fiber quality improvement

Naoumkina

Kim

2023

Crop Science

View full text Add to dashboard Cite

Upland cotton (Gossypium hirsutum L.) is the main source of natural fiber for the textile industry. Cotton fibers are unicellular trichomes that emerge from the epidermal cells of the seed. In cultivated cotton species, seed trichomes differentiate into two distinct types, spinnable lint, and short fuzz. The main priority for cotton growers is fiber yield, whereas the textile industry also demands better fiber quality characteristics, such as length, uniformity, strength, maturity, and optimal fineness. However, it is a major challenge for breeders to improve fiber quality while maintaining yield, because of the observed negative correlation between yield and fiber quality traits. Recent technical advances in sequencing and bioinformatics have facilitated the assembly of reference quality genomes of multiple cotton species, bringing a new era for cotton genomics. Available genomic resources will help genetically dissect the agronomic and fiber quality traits of cotton and identify gene variants that can be used for cotton improvement through breeding or biotechnology. Here, we review recent progress in the sequencing of genomes of cotton species and approaches in molecular genetics and genomics for the improvement of cotton fiber quality traits.We discuss progress in the understanding of each stage of cotton fiber development and the remaining challenges.

show abstract

“…At present, two SNP arrays are available in cotton, a 63K SNP array and an 80K SNP array (Cai et al., 2017; Hulse‐Kemp et al., 2015b). These SNP arrays have been used to assess genetic diversity (Billings et al., 2021), perform genome‐wide association studies (GWAS) (Cai et al., 2017; Gowda et al., 2022; Song et al., 2021; Sun et al., 2017), construct genetic maps (Hulse‐Kemp et al., 2015b; Zhang et al., 2019; Zhu et al., 2021), and detect QTL for fiber quality traits, yield traits, and morphological traits (Li et al., 2016; Zhang et al., 2019; Zhu et al., 2021). However, only a few studies have reported their use in identifying novel and stable QTL and develop functional markers for fiber quality traits, yield traits, and plant height in intraspecific Upland cotton populations.…”

Section: Introductionmentioning

confidence: 99%

Identification of quantitative trait loci for fiber quality, yield, and plant height traits in Upland cotton

et al. 2023

View full text Add to dashboard Cite

In cotton, most agronomic traits are controlled by polygenes. In this study, 110 F 6 recombinant inbred lines (RILs), derived from Upland cotton cross NC05AZ06 x NC11-2100, were used to develop a linkage map and to identify quantitative trait loci (QTL) for six fiber quality traits, three yield traits, and plant height. These RILs were genotyped using the CottonSNP63K array and phenotyped for fiber quality, yield traits, and plant height in 2-year field trials. Analysis of variance revealed significant (p < 0.05) differences among RILs for all traits studied, and the heritability estimates were moderate (30%-60%) to high (> 60%). Both positive and negative correlations were observed for fiber quality and yield traits. A total of 3,774 polymorphic SNP markers were used to develop a genetic map with an average marker density of 1.54 SNP/cM. Thirty QTL for fiber quality traits, yield traits, and plant height were detected on 15 different chromosomes, explaining 6.80%-20.02% of the phenotypic variance (PVE). Of these, 14 were major QTL (PVE > 10%), and three major QTL were detected in both years. Candidate gene analysis in the major QTL detected in both years and plant height QTL with PVE of 20.02% revealed five putative genes for fiber quality traits and one putative gene for plant height. The linkage map and identified QTL along with the candidate genes in the study could serve as additional breeding resources for Upland cotton genetic improvement.

show abstract

Genome-wide association study of micronaire using a natural population of representative upland cotton (Gossypium hirsutum L.)

Cited by 10 publications

References 38 publications

Transcriptome analysis and identification of genes associated with oil accumulation in upland cotton

Transcriptome analysis and identification of genes associated with oil accumulation in upland cotton

Bridging molecular genetics and genomics for cotton fiber quality improvement

Identification of quantitative trait loci for fiber quality, yield, and plant height traits in Upland cotton

Contact Info

Product

Resources

About