Dataset Information

Genetic structure, gene flow pattern, and association analysis of superior germplasm resources in domesticated upland cotton (Gossypium hirsutum L.).

ABSTRACT: Gene flow patterns and the genetic structure of domesticated crops like cotton are not well understood. Furthermore, marker-assisted breeding of cotton has lagged far behind that of other major crops because the loci associated with cotton traits such as fiber yield and quality have scarcely been identified. In this study, we used 19 microsatellites to first determine the population genetic structure and patterns of gene flow of superior germplasm resources in upland cotton. We then used association analysis to identify which markers were associated with 15 agronomic traits (including ten yield and five fiber quality traits). The results showed that the upland cotton accessions have low levels of genetic diversity (polymorphism information content = 0.427), although extensive gene flow occurred among different ecological and geographic regions. Bayesian clustering analysis indicated that the cotton resources used in this study did not belong to obvious geographic populations, which may be the consequence of a single source of domestication followed by frequent genetic introgression mediated by human transference. A total of 82 maker-trait associations were examined in association analysis and the related ratios for phenotypic variations ranged from 3.04% to 47.14%. Interestingly, nine SSR markers were detected in more than one environmental condition. In addition, 14 SSR markers were co-associated with two or more different traits. It was noteworthy that NAU4860 and NAU5077 markers detected at least in two environments were simultaneously associated with three fiber quality traits (uniformity index, specific breaking strength and micronaire value). In conclusion, these findings provide new insights into the population structure and genetic exchange pattern of cultivated cotton accessions. The quantitative trait loci of domesticated cotton identified will also be very useful for improvement of yield and fiber quality of cotton in molecular breeding programs.

SUBMITTER: Zhang TT

PROVIDER: S-EPMC7361167 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic structure, gene flow pattern, and association analysis of superior germplasm resources in domesticated upland cotton (<i>Gossypium hirsutum</i> L.).

Zhang Ting-Ting TT Zhang Na-Yao NY Li Wei W Zhou Xiao-Jian XJ Pei Xiao-Yu XY Liu Yan-Gai YG Ren Zhong-Ying ZY He Kun-Lun KL Zhang Wen-Sheng WS Zhou Ke-Hai KH Zhang Fei F Ma Xiong-Feng XF Yang Dai-Gang DG Li Zhong-Hu ZH

Plant diversity 20200319 3

Gene flow patterns and the genetic structure of domesticated crops like cotton are not well understood. Furthermore, marker-assisted breeding of cotton has lagged far behind that of other major crops because the loci associated with cotton traits such as fiber yield and quality have scarcely been identified. In this study, we used 19 microsatellites to first determine the population genetic structure and patterns of gene flow of superior germplasm resources in upland cotton. We then used associa ...[more]

PMID: 32695952

Similar Datasets

Project description:Background:Genetically modified cotton accounts for 64% of the world's cotton growing area (22.3 million hectares). The genome sequencing of the diploid cotton progenitors Gossypium raimondii and Gossypium arboreum as well as the cultivated Gossypium hirsutum has provided a wealth of genetic information that could be exploited for crop improvement. Unfortunately, gene functional characterization in cotton is lagging behind other economically important crops due to the low efficiency, lengthiness and technical complexity of the available stable transformation methods. We present here a simple, fast and efficient method for the transient transformation of G. hirsutum that can be used for gene characterization studies. Results:We developed a transient transformation system for gene characterization in upland cotton. Using ?-glucuronidase as a reporter for Agrobacterium-mediated transformation assays, we evaluated multiple transformation parameters such as Agrobacterium strain, bacterial density, length of co-cultivation, chemicals and surfactants, which can affect transformation efficiency. After the initial characterization, the Agrobacterium EHA105 strain was selected and a number of binary constructs used to perform gene characterization studies. 7-days-old cotton seedlings were co-cultivated with Agrobacterium and transient gene expression was observed 5 days after infection of the plants. Transcript levels of two different transgenes under the control of the cauliflower mosaic virus (CaMV) 35S promoter were quantified by real-time reverse transcription PCR (qRT-PCR) showing a 3-10 times increase over the levels observed in non-infected controls. The expression patterns driven by the promoters of two G. hirsutum genes as well as the subcellular localization of their corresponding proteins were studied using the new transient expression system and our observations were consistent with previously published results using Arabidopsis as a heterologous system. Conclusions:The Agrobacterium-mediated transient transformation method is a fast and easy transient expression system enabling high transient expression and transformation efficiency in upland cotton seedlings. Our method can be used for gene functional studies such as promoter characterization and protein subcellular localization in cotton, obviating the need to perform such studies in a heterologous system such as Arabidopsis.

Project description:Upland cotton (Gossypium hirsutum L.) produces terpenoid aldehydes (TAs) that protect the plant from microbial and insect infestations. Foliar TAs include plus (+)- and minus (-)-gossypol, hemigossypolone, and heliocides. To examine foliar TAs' response to physical wounding, the four TA derivatives of a fully glanded G. hirsutum variety JACO GL were quantified by ultra-high performance liquid chromatography. The results show that foliar heliocides increased by 1.7-fold in younger leaves after wounding. While the hemigossypolone level was not affected by the physical wounding, the level of heliocides was significantly increased up to 1.8-fold in the younger leaves. Upland cotton accumulates concentrated carbohydrates, amino acids, and fatty acids in foliar extrafloral nectar (EFN) to serve as a nutrient resource, which attracts both beneficial insects and damaging pests. To better understand the nectar physiology, particularly to determine the temporal dynamics of EFN metabolites in response to the wounding, a gas chromatograph-mass spectrometer (GC-MS) was used to perform metabolic profiling analyses of a G. hirsutum variety Deltapine 383 that has fully developed extrafloral nectaries. A total of 301 compounds were monitored, specifically 75 primary metabolites, two secondary metabolites and 224 unidentified compounds. The physical wounding treatment changed the EFN composition and lowered overall production. The accumulation of 30 metabolites was altered in response to the wounding treatment and threonic acid levels increased consistently. GC-MS combined with Kovat's analysis enabled identification of EFN secondary metabolites including furfuryl alcohol and 5-hyrdomethoxyfurfural, which both have antioxidant and antimicrobial properties that may protect the nectar against microbial pathogens. This study provides new insights into the wounding response of cotton plants in terms of cotton metabolites found in leaf glands and extrafloral nectar as well as highlighting some protective functions of secondary metabolites produced in foliar glands and extrafloral nectaries.

Dataset Information

Genetic structure, gene flow pattern, and association analysis of superior germplasm resources in domesticated upland cotton (Gossypium hirsutum L.).

Publications

Genetic structure, gene flow pattern, and association analysis of superior germplasm resources in domesticated upland cotton (<i>Gossypium hirsutum</i> L.).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets