QTL mapping and candidate gene identification of lint percentage based on a recombinant inbred line population of upland cotton

Wang, Hantao; Jia, Xiaoyun; Kang, Meng; Li, Wei; Fu, Xiaokang; Ma, Liang; Lü, Jianhua; Wei, Hengling; Yu, Shuang

doi:10.1007/s10681-021-02823-x

Cited by 4 publications

(5 citation statements)

References 48 publications

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“…TM73642 on D10 was 70 Kb away from TM73693 detected by Zhu et al [13]. TM75017 on D10 also was approximately 70 Kb away from i12188Gh, i12189Gh, and i12190Gh detected by Song et al [5] and was 70 Kb and 150 Kb away from qLP-Dt10-3 (Marker36441-Marker36437) and qLP-Dt10-2 (Marker36463-Marker36442) detected by Wang et al [41], respectively. TM80159 on D13 was 34-170 Kb away from three SNPs (TM80151, TM80163, and TM80171) detected by Xing et al [32].…”

Section: Validation Of the Stability Of 45 Snps Associated With Lint ...mentioning

confidence: 64%

“…Specifically, four SNPs (TM6245, TM6246, TM6247, and TM6248) on A3 were located on the overlap of qLP-C-3 (CGR6528–BNL2443) detected by Wang et al [ 39 ] and were 100 Kb away from TM6282 detected by Zhu et al [ 13 ]. Eight SNPs (TM21439 on A7, TM42563 on A12, TM53197 on D2, TM53588 on D3, TM55461 on D4, TM55582 on D4, TM57478 and TM57486 on D5) were within 200 Kb away from TM21493 detected by Zhu et al [ 13 ], LDB_12_93252980 detected by Su et al [ 4 ], TM53255 detected by Zhu et al [ 13 ], TM53212 detected by Xing et al [ 32 ], DPL0281 detected by Zhang et al [ 26 ], SWU20808 detected by Yang et al [ 40 ], TM55475 detected by Zhu et al [ 13 ], Marker26949 detected by Wang et al [ 41 ], TM57480 and TM57483 detected by Zhu et al [ 13 ], or D05_20162316 detected by Sarfraz et al [ 20 ]. TM73642 on D10 was 70 Kb away from TM73693 detected by Zhu et al [ 13 ].…”

Section: Resultsmentioning

confidence: 89%

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Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races

Wang

Guo

Cai

et al. 2023

IJMS

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Lint percentage is one of the most essential yield components and an important economic index for cotton planting. Improving lint percentage is an effective way to achieve high-yield in cotton breeding worldwide, especially upland cotton (Gossypium hirsutum L.). However, the genetic basis controlling lint percentage has not yet been systematically understood. Here, we performed a genome-wide association mapping for lint percentage using a natural population consisting of 189 G. hirsutum accessions (188 accessions of G. hirsutum races and one cultivar TM-1). The results showed that 274 single-nucleotide polymorphisms (SNPs) significantly associated with lint percentage were detected, and they were distributed on 24 chromosomes. Forty-five SNPs were detected at least by two models or at least in two environments, and their 5 Mb up- and downstream regions included 584 makers related to lint percentage identified in previous studies. In total, 11 out of 45 SNPs were detected at least in two environments, and their 550 Kb up- and downstream region contained 335 genes. Through RNA sequencing, gene annotation, qRT-PCR, protein–protein interaction analysis, the cis-elements of the promotor region, and related miRNA prediction, Gh_D12G0934 and Gh_A08G0526 were selected as key candidate genes for fiber initiation and elongation, respectively. These excavated SNPs and candidate genes could supplement marker and gene information for deciphering the genetic basis of lint percentage and facilitate high-yield breeding programs of G. hirsutum ultimately.

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Section: Validation Of the Stability Of 45 Snps Associated With Lint ...mentioning

confidence: 64%

Section: Resultsmentioning

confidence: 89%

Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races

Wang

Guo

Cai

et al. 2023

IJMS

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“…Transcription factors have been shown to play an important role in fiber initiation and elongation, such as MYB, ERF, and bHLH families. The number of initial fiber cells in the 0 DPA ovules of GhMYB5_A12 over‐expressed cotton was increased significantly than that in wild‐type plants, which indicated a positive role in fiber initiation (Wang, Jia, et al., 2021; Wang, Li, et al., 2021; Wang, Ma, et al., 2021). Overexpressed the bHLH gene ( GhFP2 ) in cotton suppressed fiber elongation, while suppression of GhFP2 expression led to longer fiber.…”

Section: Discussionmentioning

confidence: 96%

“…G2005. Furthermore, two genes ( Gh_A05G1584 and Gh_A05G1689 ), which are highly expressed during fiber development stages in the high LP variety (CCRI 36), were revealed as candidate genes for LP (Wang, Jia, et al., 2021). And numerous QTL related to salt tolerance at germination and seedling stages were identified in upland cotton (Diouf et al., 2017; Gu et al., 2021; Hussain et al., 2017; Oluoch et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

Yield‐related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton

Guo,

Li,

Huang

et al. 2024

The Plant Journal

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SUMMARYSalinity is frequently mentioned as a major constraint in worldwide agricultural production. Lint percentage (LP) is a crucial yield‐component in cotton lint production. While the genetic factors affect cotton yield in saline soils are still unclear. Here, we employed a recombinant inbred line population in upland cotton (Gossypium hirsutum L.) and investigated the effects of salt stress on five yield and yield component traits, including seed cotton yield per plant, lint yield per plant, boll number per plant, boll weight, and LP. Between three datasets of salt stress (E1), normal growth (E2), and the difference values dataset of salt stress and normal conditions (D‐value), 87, 82, and 55 quantitative trait loci (QTL) were detectable, respectively. In total, five QTL (qLY‐Chr6‐2, qBNP‐Chr4‐1, qBNP‐Chr12‐1, qBNP‐Chr15‐5, qLP‐Chr19‐2) detected in both in E1 and D‐value were salt related QTL, and three stable QTL (qLP‐Chr5‐3, qLP‐Chr13‐1, qBW‐Chr5‐5) were detected both in E1 and E2 across 3 years. Silencing of nine genes within a stable QTL (qLP‐Chr5‐3) highly expressed in fiber developmental stages increased LP and decreased fiber length (FL), indicating that multiple minor‐effect genes clustered on Chromosome 5 regulate LP and FL. Additionally, the difference in LP caused by Gh_A05G3226 is mainly in transcription level rather than in the sequence difference. Moreover, silencing of salt related gene (GhDAAT) within qBNP‐Chr4‐1 decreased salt tolerance in cotton. Our findings shed light on the regulatory mechanisms underlining cotton salt tolerance and fiber initiation.

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“…The use of MAS to pyramid several QTLs that affect numerous desired target characteristics enhanced the selection efficiency among breeding populations with varied genetic origins. Recent studies ( Abdelraheem et al, 2021 ; Guo et al, 2021 ; Wang H. et al, 2021 ; Wang N. et al, 2021 ; Zhu et al, 2021 ) demonstrated the necessity of dissecting complicated fiber traits using QTL mapping and the potential of MAS in the cotton breeding program.…”

Section: Introductionmentioning

confidence: 99%

Identification of Stable and Multiple Environment Interaction QTLs and Candidate Genes for Fiber Productive Traits Under Irrigated and Water Stress Conditions Using Intraspecific RILs of Gossypium hirsutum var. MCU5 X TCH1218

et al. 2022

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Cotton productivity under water-stressed conditions is controlled by multiple quantitative trait loci (QTL). Enhancement of these productivity traits under water deficit stress is crucial for the genetic improvement of upland cotton, Gossypium hirsutum. In the present study, we constructed a genetic map with 504 single nucleotide polymorphisms (SNPs) covering a total span length of 4,416 cM with an average inter-marker distance of 8.76 cM. A total of 181 intra-specific recombinant inbred lines (RILs) were derived from a cross between G. hirsutum var. MCU5 and TCH1218 were used. Although 2,457 polymorphic SNPs were detected between the parents using the CottonSNP50K assay, only 504 SNPs were found to be useful for the construction of the genetic map. In the SNP genotyping, a large number of SNPs showed either >20% missing data, duplication, or segregation distortion. However, the mapped SNPs of this study showed collinearity with the physical map of the reference genome (G. hirsutum var.TM-1), indicating that there was no chromosomal rearrangement within the studied mapping population. RILs were evaluated under multi-environments and seasons for which the phenotypic data were acquired. A total of 53 QTL controlling plant height (PH), number of sympodial branches, boll number (BN), and boll weight (BW) were dissected by QTL analysis under irrigated and water stress conditions. Additionally, it was found that nine QTL hot spots not only co-localized for more than one investigated trait but were also stable with major QTL, i.e., with > 10% of phenotypic variation. One QTL hotspot on chromosome 22 flanked by AX-182254626–AX-182264770 with a span length of 89.4 cM co-localized with seven major and stable QTL linked to a number of sympodial branches both under irrigated and water stress conditions. In addition, putative candidate genes associated with water stress in the QTL hotspots were identified. Besides, few QTL from the hotspots were previously reported across various genetic architects in cotton validating the potential applications of these identified QTL for cotton breeding and improvement. Thus, the major and stable QTL identified in the present study would improve the cotton productivity under water-limited environments through marker-assisted selection.

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QTL mapping and candidate gene identification of lint percentage based on a recombinant inbred line population of upland cotton

Cited by 4 publications

References 48 publications

Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races

Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races

Yield‐related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton

Identification of Stable and Multiple Environment Interaction QTLs and Candidate Genes for Fiber Productive Traits Under Irrigated and Water Stress Conditions Using Intraspecific RILs of Gossypium hirsutum var. MCU5 X TCH1218

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