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Wu M, Xu Z, Fu C, Wang N, Zhang R, Le Y, Chen M, Yang N, Li Y, Zhang X, Li X, Lin Z. NAC transcription factor GbNTL9 modifies the accumulation and organization of cellulose microfibrils to enhance cotton fiber strength. J Adv Res 2025:S2090-1232(25)00120-1. [PMID: 39971129 DOI: 10.1016/j.jare.2025.02.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2024] [Revised: 01/22/2025] [Accepted: 02/17/2025] [Indexed: 02/21/2025] Open
Abstract
INTRODUCTION Fiber strength is a critical determinant of fiber quality, with stronger fibers being highly preferred in the cotton textile industry. However, the genetic basis and the specific regulatory mechanism underlying the formation of cotton fiber strength remain largely unknown. OBJECTIVES To explore fiber strength-related genes, QTL mapping, map-based cloning, and gene function verification were conducted in a backcross inbred line BS41 derived from interspecific hybridization between upland cotton and sea-island cotton. METHODS Upland cotton Emian22 (E22) and an interspecific backcross inbred line (BIL) BS41 were used as parents to construct secondary segregation populations for BSA and QTL mapping of fiber strength. The candidate gene GbNTL9 was identified through map-based cloning and expression analysis. The function of NTL9 was determined through transgenic experiments and cytological observations. The regulatory mechanisms of NTL9 were explored using RNA-seq, RT-qPCR, yeast two-hybrid, bimolecular fluorescence complementation, and yeast one-hybrid. RESULTS A major QTL for fiber strength, qFS-A11-1, was mapped to a 14.6-kb genomic region using segregating populations from E22 × BS41. GbNTL9, which encodes a NAC transcription factor, was identified as the candidate gene. Overexpression of both upland cotton genotype NTL9E22 and sea-island genotype NTL9BS41 in upland cotton enhanced fiber strength by facilitating the dense accumulation and orderly organization of cellulose microfibrils within the cell wall. Transcriptomic analysis revealed that NTL9 inhibited the expression of genes involved in secondary wall synthesis, such as CESA4, CESA7, and CESA8, thereby delaying cell wall cellulose deposition and altering the microfibril deposition pattern. NTL9 interacted with MYB6 and functioned as a downstream gene in the ethylene signaling pathway. Additionally, an effective gene marker NTL9-24 was developed to distinguish haplotypes from G. barbadense and G. hirsutum for fiber quality breeding program. CONCLUSION Our findings demonstrate that GbNTL9 positively regulates fiber strength through altering the microfibril deposition pattern, and provide a new insight into the molecular mechanism underlying fiber strength.
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Affiliation(s)
- Mi Wu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Zhiyong Xu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Chao Fu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Nian Wang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Ruiting Zhang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Yu Le
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Meilin Chen
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Ningyu Yang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Yuanxue Li
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
| | - Ximei Li
- Shandong Key Laboratory of Dryland Farming Technology, Shandong Engineering Research Center of Germplasm Innovation and Utilization of Salt-Tolerant Crops, College of Agronomy, Qingdao Agricultural University, Qingdao 266109 Shandong, China.
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070 Hubei, China.
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Han B, Zhang W, Wang F, Yue P, Liu Z, Yue D, Zhang B, Ma Y, Lin Z, Yu Y, Wang Y, Zhang X, Yang X. Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2400445. [PMID: 38984458 PMCID: PMC11425955 DOI: 10.1002/advs.202400445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 05/07/2024] [Indexed: 07/11/2024]
Abstract
Global water scarcity and extreme weather intensify drought stress, significantly reducing cotton yield and quality worldwide. Drought treatments are conducted using a population of chromosome segment substitution lines generated from E22 (G. hirsutum) and 3-79 (G. barbadense) as parental lines either show superior yields or fiber quality under both control and drought conditions. Fourteen datasets, covering 4 yields and 4 quality traits, are compiled and assessed for drought resistance using the drought resistance coefficient (DRC) and membership function value of drought resistance (MFVD). Genome-wide association studies, linkage analysis, and bulked segregant analysis are combined to analyze the DR-related QTL. A total of 121 significant QTL are identified by DRC and MFVD of the 8 traits. CRISPR/Cas9 and virus-induced gene silencing techniques verified DRR1 and DRT1 as pivotal genes in regulating drought resistant of cotton, with hap3-79 exhibiting greater drought resistance than hapE22 concerning DRR1 and DRT1. Moreover, 14 markers with superior yield and fiber quality are selected for drought treatment. This study offers valuable insights into yield and fiber quality variations between G. hirsutum and G. barbadense amid drought, providing crucial theoretical and technological backing for developing cotton varieties resilient to drought, with high yield and superior fiber quality.
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Affiliation(s)
- Bei Han
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Wenhao Zhang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Fengjiao Wang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Pengkai Yue
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Zhilin Liu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Dandan Yue
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Bing Zhang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Yizan Ma
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
| | - Zhongxu Lin
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
- Hubei Hongshan LaboratoryWuhan430070China
| | - Yu Yu
- Cotton InstituteXinjiang Academy of Agriculture and Reclamation ScienceShihezi832000China
| | - Yanqin Wang
- College of Life SciencesTarim UniversityAlar843300China
| | - Xianlong Zhang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
- Hubei Hongshan LaboratoryWuhan430070China
| | - Xiyan Yang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhan430070China
- Hubei Hongshan LaboratoryWuhan430070China
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Ma J, Yang L, Dang Y, Shahzad K, Song J, Jia B, Wang L, Feng J, Wang N, Pei W, Wu M, Zhang X, Zhang J, Wu J, Yu J. Deciphering the dynamic expression network of fiber elongation and the functional role of the GhTUB5 gene for fiber length in cotton based on an introgression population of upland cotton. J Adv Res 2024:S2090-1232(24)00324-2. [PMID: 39106927 DOI: 10.1016/j.jare.2024.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 07/02/2024] [Accepted: 08/02/2024] [Indexed: 08/09/2024] Open
Abstract
INTRODUCTION Interspecific introgression between Gossypium hirsutum and G. barbadense allows breeding cotton with outstanding fiber length (FL). However, the dynamic gene regulatory network of FL-related genes has not been characterized, and the functional mechanism through which the hub gene GhTUB5 mediates fiber elongation has yet to be determined. METHODS Coexpression analyses of 277 developing fiber transcriptomes integrated with QTL mapping using 250 introgression lines of different FL phenotypes were conducted to identify genes related to fiber elongation. The function of GhTUB5 was determined by ectopic expression of two TUB5 alleles in Arabidopsis and knockout of GhTUB5 in upland cotton. Yeast two-hybrid, split-luciferase and pull-down assays were conducted to screen for interacting proteins, and upstream genes were identified by yeast one-hybrid, dual-LUC and electrophoretic mobility shift assays. RESULTS The 32,612, 30,837 and 30,277 genes expressed at 5, 10 and 15 days postanthesis (dpa) were grouped into 19 distinct coexpression modules, and 988 genes in the MEblack module were enriched in the cell wall process and exhibited significant associations with FL. A total of 20 FL-QTLs were identified, each explaining 3.34-16.04 % of the phenotypic variance in the FL. Furthermore, several FL-QTLs contained 15 genes that were differentially expressed in the MEblack module including the tubulin beta gene (TUB5). Compared with the wild type, the overexpression of GhTUB5 and GbTUB5 in Arabidopsis suppressed root cell length but promoted cellulose synthesis. Knockout of GhTUB5 resulted in longer fiber lines. Protein-based experiments revealed that GhTUB5 interacts with GhZFP6. Additionally, GhTUB5 was directly activated by GhHD-ZIP7, a homeobox-leucine zipper transcription factor, and its paralogous gene was previously reported to mediate fiber elongation. CONCLUSION This study opens a new avenue to dissect functional mechanism of cotton fiber elongation. Our findings provide some molecular details on how GhTUB5 mediates the FL phenotype in cotton.
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Affiliation(s)
- Jianjiang Ma
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China; Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Liupeng Yang
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yuanyue Dang
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China; Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China
| | - Kashif Shahzad
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jikun Song
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Bing Jia
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Li Wang
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China; Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Juanjuan Feng
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Nuohan Wang
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China; Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Man Wu
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China; Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Xuexian Zhang
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, USA.
| | - Jianyong Wu
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China; Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China.
| | - Jiwen Yu
- State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Anyang, China; Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China; Engineering Research Centre of Cotton of Ministry of Education, College of Agriculture, Xinjiang Agricultural University, Urumqi, China.
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Ma J, Jia B, Bian Y, Pei W, Song J, Wu M, Wang W, Kashif, Shahzad, Wang L, Zhang B, Feng P, Yang L, Zhang J, Yu J. Genomic and co-expression network analyses reveal candidate genes for oil accumulation based on an introgression population in Upland cotton (Gossypium hirsutum). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:23. [PMID: 38231256 DOI: 10.1007/s00122-023-04527-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/11/2023] [Indexed: 01/18/2024]
Abstract
KEY MESSAGE Integrated QTL mapping and WGCNA condense the potential gene regulatory network involved in oil accumulation. A glycosyl hydrolases gene (GhHSD1) for oil biosynthesis was confirmed in Arabidopsis, which will provide useful knowledge to understand the functional mechanism of oil biosynthesis in cotton. Cotton is an economical source of edible oil for the food industry. The genetic mechanism that regulates oil biosynthesis in cottonseeds is essential for the genetic enhancement of oil content (OC). To explore the functional genomics of OC, this study utilized an interspecific backcross inbred line population to dissect the quantitative trait locus (QTL) interlinked with OC. In total, nine OC QTLs were identified, four of which were novel, and each QTL explained 3.62-34.73% of the phenotypic variation of OC. The comprehensive transcript profiling of developing cottonseeds revealed 3,646 core genes differentially expressed in both inbred parents. Functional enrichment analysis determined 43 genes were annotated with oil biosynthesis processes. Implementation of weighted gene co-expression network analysis showed that 803 differential genes had a significant correlation with the OC phenotype. Further integrated analysis identified seven important genes located in OC QTLs. Of which, the GhHSD1 gene located in stable QTL qOC-Dt3-1 exhibited the highest functional linkages with the other network genes. Phylogenetic analysis showed significant evolutionary differences in the HSD1 sequences between oilseed- and starch- crops. Furthermore, the overexpression of GhHSD1 in Arabidopsis yielded almost 6.78% higher seed oil. This study not only uncovers important genetic loci for oil accumulation in cottonseed, but also provides a set of new candidate genes that potentially influence the oil biosynthesis pathway in cottonseed.
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Affiliation(s)
- Jianjiang Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
- State Key Laboratory of Cotton Biology, Zhengzhou Research Base, Zhengzhou University, Zhengzhou, China
| | - Bing Jia
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Yingying Bian
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Jikun Song
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Wenkui Wang
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | | | - Shahzad
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Li Wang
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Bingbing Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Pan Feng
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Liupeng Yang
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, USA.
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
- State Key Laboratory of Cotton Biology, Zhengzhou Research Base, Zhengzhou University, Zhengzhou, China.
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Li S, Kong L, Xiao X, Li P, Liu A, Li J, Gong J, Gong W, Ge Q, Shang H, Pan J, Chen H, Peng Y, Zhang Y, Lu Q, Shi Y, Yuan Y. Genome-wide artificial introgressions of Gossypium barbadense into G. hirsutum reveal superior loci for simultaneous improvement of cotton fiber quality and yield traits. J Adv Res 2023; 53:1-16. [PMID: 36460274 PMCID: PMC10658236 DOI: 10.1016/j.jare.2022.11.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 10/31/2022] [Accepted: 11/24/2022] [Indexed: 12/02/2022] Open
Abstract
INTRODUCTION The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield. OBJECTIVES This study was to identify superior loci for the improvement of fiber quality and yield. METHODS Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci. RESULTS A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population. CONCLUSION The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.
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Affiliation(s)
- Shaoqi Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Linglei Kong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Xianghui Xiao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Pengtao Li
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China
| | - Hong Chen
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832000, China
| | - Yan Peng
- Third Division of the Xinjiang Production and Construction Corps Agricultural Research Institute, Tumushuke 843900, China
| | - Yuanming Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Quanwei Lu
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China.
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China.
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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Ma J, Jiang Y, Pei W, Wu M, Ma Q, Liu J, Song J, Jia B, Liu S, Wu J, Zhang J, Yu J. Expressed genes and their new alleles identification during fibre elongation reveal the genetic factors underlying improvements of fibre length in cotton. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:1940-1955. [PMID: 35718938 PMCID: PMC9491459 DOI: 10.1111/pbi.13874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 05/29/2022] [Accepted: 06/11/2022] [Indexed: 05/27/2023]
Abstract
Interspecific breeding in cotton takes advantage of genetic recombination among desirable genes from different parental lines. However, the expression new alleles (ENAs) from crossovers within genic regions and their significance in fibre length (FL) improvement are currently not understood. Here, we generated resequencing genomes of 191 interspecific backcross inbred lines derived from CRI36 (Gossypium hirsutum) × Hai7124 (Gossypium barbadense) and 277 dynamic fibre transcriptomes to identify the ENAs and extremely expressed genes (eGenes) potentially influencing FL, and uncovered the dynamic regulatory network of fibre elongation. Of 35 420 eGenes in developing fibres, 10 366 ENAs were identified and preferentially distributed in chromosomes subtelomeric regions. In total, 1056-1255 ENAs showed transgressive expression in fibres at 5-15 dpa (days post-anthesis) of some BILs, 520 of which were located in FL-quantitative trait locus (QTLs) and GhFLA9 (recombination allele) was identified with a larger effect for FL than GhFLA9 of CRI36 allele. Using ENAs as a type of markers, we identified three novel FL-QTLs. Additionally, 456 extremely eGenes were identified that were preferentially distributed in recombination hotspots. Importantly, 34 of them were significantly associated with FL. Gene expression quantitative trait locus analysis identified 1286, 1089 and 1059 eGenes that were colocalized with the FL trait at 5, 10 and 15 dpa, respectively. Finally, we verified the Ghir_D10G011050 gene linked to fibre elongation by the CRISPR-cas9 system. This study provides the first glimpse into the occurrence, distribution and expression of the developing fibres genes (especially ENAs) in an introgression population, and their possible biological significance in FL.
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Affiliation(s)
- Jianjiang Ma
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
| | - Yafei Jiang
- Novogene Bioinformatics InstituteBeijingChina
| | - Wenfeng Pei
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Man Wu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Qifeng Ma
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Ji Liu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Jikun Song
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Bing Jia
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Shang Liu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Jianyong Wu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
| | - Jinfa Zhang
- Department of Plant and Environmental SciencesNew Mexico State UniversityLas CrucesNew MexicoUSA
| | - Jiwen Yu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
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Guo X, Ullah A, Siuta D, Kukfisz B, Iqbal S. Role of WRKY Transcription Factors in Regulation of Abiotic Stress Responses in Cotton. Life (Basel) 2022; 12:life12091410. [PMID: 36143446 PMCID: PMC9504182 DOI: 10.3390/life12091410] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 08/31/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
Environmental factors are the major constraints in sustainable agriculture. WRKY proteins are a large family of transcription factors (TFs) that regulate various developmental processes and stress responses in plants, including cotton. On the basis of Gossypium raimondii genome sequencing, WRKY TFs have been identified in cotton and characterized for their functions in abiotic stress responses. WRKY members of cotton play a significant role in the regulation of abiotic stresses, i.e., drought, salt, and extreme temperatures. These TFs either activate or repress various signaling pathways such as abscisic acid, jasmonic acid, salicylic acid, mitogen-activated protein kinases (MAPK), and the scavenging of reactive oxygen species. WRKY-associated genes in cotton have been genetically engineered in Arabidopsis, Nicotiana, and Gossypium successfully, which subsequently enhanced tolerance in corresponding plants against abiotic stresses. Although a few review reports are available for WRKY TFs, there is no critical report available on the WRKY TFs of cotton. Hereby, the role of cotton WRKY TFs in environmental stress responses is studied to enhance the understanding of abiotic stress response and further improve in cotton plants.
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Affiliation(s)
- Xiaoqiang Guo
- College of Life Science and Technology, Longdong University, Qingyang 745000, China
- Correspondence: (X.G.); (A.U.)
| | - Abid Ullah
- Department of Botany, Post Graduate College Dargai, Malakand 23060, Khyber Pakhtunkhwa, Pakistan
- Correspondence: (X.G.); (A.U.)
| | - Dorota Siuta
- Faculty of Process and Environmental Engineering, Lodz University of Technology, Wolczanska Str. 213, 90-924 Lodz, Poland
| | - Bożena Kukfisz
- Faculty of Security Engineering and Civil Protection, The Main School of Fire Service, 01-629 Warsaw, Poland
| | - Shehzad Iqbal
- College of Plant Sciences and Technology, Huazhong Agricultural University, Wuhan 430070, China
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Yang P, Sun X, Liu X, Wang W, Hao Y, Chen L, Liu J, He H, Zhang T, Bao W, Tang Y, He X, Ji M, Guo K, Liu D, Teng Z, Liu D, Zhang J, Zhang Z. Identification of Candidate Genes for Lint Percentage and Fiber Quality Through QTL Mapping and Transcriptome Analysis in an Allotetraploid Interspecific Cotton CSSLs Population. FRONTIERS IN PLANT SCIENCE 2022; 13:882051. [PMID: 35574150 PMCID: PMC9100888 DOI: 10.3389/fpls.2022.882051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 04/06/2022] [Indexed: 06/15/2023]
Abstract
Upland cotton (Gossypium hirsutum) has long been an important fiber crop, but the narrow genetic diversity of modern G. hirsutum limits the potential for simultaneous improvement of yield and fiber quality. It is an effective approach to broaden the genetic base of G. hirsutum through introgression of novel alleles from G. barbadense with excellent fiber quality. In the present study, an interspecific chromosome segment substitution lines (CSSLs) population was established using G. barbadense cultivar Pima S-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. A total of 105 quantitative trait loci (QTL), including 85 QTL for fiber quality and 20 QTL for lint percentage (LP), were identified based on phenotypic data collected from four environments. Among these QTL, 25 stable QTL were detected in two or more environments, including four for LP, eleven for fiber length (FL), three for fiber strength (FS), six for fiber micronaire (FM), and one for fiber elongation (FE). Eleven QTL clusters were observed on nine chromosomes, of which seven QTL clusters harbored stable QTL. Moreover, eleven major QTL for fiber quality were verified through analysis of introgressed segments of the eight superior lines with the best comprehensive phenotypes. A total of 586 putative candidate genes were identified for 25 stable QTL associated with lint percentage and fiber quality through transcriptome analysis. Furthermore, three candidate genes for FL, GH_A08G1681 (GhSCPL40), GH_A12G2328 (GhPBL19), and GH_D02G0370 (GhHSP22.7), and one candidate gene for FM, GH_D05G1346 (GhAPG), were identified through RNA-Seq and qRT-PCR analysis. These results lay the foundation for understanding the molecular regulatory mechanism of fiber development and provide valuable information for marker-assisted selection (MAS) in cotton breeding.
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9
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Lu Q, Li P, Yang R, Xiao X, Li Z, Wu Q, Gong J, Ge Q, Liu A, Du S, Wang J, Shi Y, Yuan Y. QTL mapping and candidate gene prediction for fiber yield and quality traits in a high-generation cotton chromosome substitution line with Gossypium barbadense segments. Mol Genet Genomics 2022; 297:287-301. [DOI: 10.1007/s00438-021-01833-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/30/2021] [Indexed: 12/27/2022]
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10
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Liu X, Yang L, Wang J, Wang Y, Guo Z, Li Q, Yang J, Wu Y, Chen L, Teng Z, Liu D, Liu D, Guo K, Zhang Z. Analyzing Quantitative Trait Loci for Fiber Quality and Yield-Related Traits From a Recombinant Inbred Line Population With Gossypium hirsutum Race palmeri as One Parent. FRONTIERS IN PLANT SCIENCE 2022; 12:817748. [PMID: 35046989 PMCID: PMC8763314 DOI: 10.3389/fpls.2021.817748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 12/01/2021] [Indexed: 06/14/2023]
Abstract
Fiber quality and yield-related traits are important agronomic traits in cotton breeding. To detect the genetic basis of fiber quality and yield related traits, a recombinant inbred line (RIL) population consisting of 182 lines was established from a cross between Gossypium hirsutum cultivar CCRI35 and G. hirsutum race palmeri accession TX-832. The RIL population was deeply genotyped using SLAF-seq and was phenotyped in six environments. A high-density genetic linkage map with 15,765 SNP markers and 153 SSR markers was constructed, with an average distance of 0.30 cM between adjacent markers. A total of 210 fiber quality quantitative trait loci (QTLs) and 73 yield-related QTLs were identified. Of the detected QTLs, 62 fiber quality QTLs and 10 yield-related QTLs were stable across multiple environments. Twelve and twenty QTL clusters were detected on the At and Dt subgenome, respectively. Twenty-three major QTL clusters were further validated through associated analysis and five candidate genes of four stable fiber quality QTLs were identified. This study revealed elite loci influencing fiber quality and yield and significant phenotypic selection regions during G. hirsutum domestication, and set a stage for future utilization of molecular marker assisted breeding in cotton breeding programs.
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11
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Lu Q, Xiao X, Gong J, Li P, Zhao Y, Feng J, Peng R, Shi Y, Yuan Y. Identification of Candidate Cotton Genes Associated With Fiber Length Through Quantitative Trait Loci Mapping and RNA-Sequencing Using a Chromosome Segment Substitution Line. FRONTIERS IN PLANT SCIENCE 2021; 12:796722. [PMID: 34970293 PMCID: PMC8712442 DOI: 10.3389/fpls.2021.796722] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 11/23/2021] [Indexed: 06/14/2023]
Abstract
Fiber length is an important determinant of fiber quality, and it is a quantitative multi-genic trait. Identifying genes associated with fiber length is of great importance for efforts to improve fiber quality in the context of cotton breeding. Integrating transcriptomic information and details regarding candidate gene regions can aid in candidate gene identification. In the present study, the CCRI45 line and a chromosome segment substitution line (CSSL) with a significantly higher fiber length (MBI7747) were utilized to establish F2 and F2:3 populations. Using a high-density genetic map published previously, six quantitative trait loci (QTLs) associated with fiber length and two QTLs associated with fiber strength were identified on four chromosomes. Within these QTLs, qFL-A07-1, qFL-A12-2, qFL-A12-5, and qFL-D02-1 were identified in two or three environments and confirmed by a meta-analysis. By integrating transcriptomic data from the two parental lines and through qPCR analyses, four genes associated with these QTLs including Cellulose synthase-like protein D3 (CSLD3, GH_A12G2259 for qFL-A12-2), expansin-A1 (EXPA1, GH_A12G1972 for qFL-A12-5), plasmodesmata callose-binding protein 3 (PDCB3, GH_A12G2014 for qFL-A12-5), and Polygalacturonase (At1g48100, GH_D02G0616 for qFL-D02-1) were identified as promising candidate genes associated with fiber length. Overall, these results offer a robust foundation for further studies regarding the molecular basis for fiber length and for efforts to improve cotton fiber quality.
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Affiliation(s)
- Quanwei Lu
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Xianghui Xiao
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Pengtao Li
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Yan Zhao
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Jiajia Feng
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Renhai Peng
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
| | - Yuzhen Shi
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
| | - Youlu Yuan
- School of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, China
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, China
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12
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Zenda T, Liu S, Dong A, Li J, Wang Y, Liu X, Wang N, Duan H. Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value. FRONTIERS IN PLANT SCIENCE 2021; 12:774994. [PMID: 34925418 PMCID: PMC8672198 DOI: 10.3389/fpls.2021.774994] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/08/2021] [Indexed: 05/17/2023]
Abstract
Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.
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Affiliation(s)
- Tinashe Zenda
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
- Department of Crop Science, Faculty of Agriculture and Environmental Science, Bindura University of Science Education, Bindura, Zimbabwe
| | - Songtao Liu
- Academy of Agriculture and Forestry Sciences, Hebei North University, Zhangjiakou, China
| | - Anyi Dong
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Jiao Li
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Yafei Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Xinyue Liu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Nan Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Huijun Duan
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
- Department of Crop Genetics and Breeding, College of Agronomy, Hebei Agricultural University, Baoding, China
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Zhang J, Wedegaertner T. Genetics and Breeding for Glandless Upland Cotton With Improved Yield Potential and Disease Resistance: A Review. FRONTIERS IN PLANT SCIENCE 2021; 12:753426. [PMID: 34691130 PMCID: PMC8526788 DOI: 10.3389/fpls.2021.753426] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 09/14/2021] [Indexed: 05/28/2023]
Abstract
Glandless cotton (devoid of toxic gossypol) can be grown as a triple-purpose crop for fiber, feeds, and food (as an oil and protein source). However, its sensitivity to insect pests and its low yield due to the lack of breeding activities has prevented the realization of its potential in commercial seed production and utilization. Since the mid-1990s, the commercialization of bollworm and budworm resistant Bt cotton and the eradication of boll weevils and pink bollworms have provided an opportunity to revitalize glandless cotton production in the United States. The objectives of this study were to review the current status of genetics and breeding for glandless cotton, with a focus on the progress in breeding for glandless Upland cotton in New Mexico, United States. Because there existed a 10-20% yield gap between the best existing glandless germplasm and commercial Upland cultivars, the breeding of glandless Upland cultivars with improved yield and disease resistance was initiated at the New Mexico State University more than a decade ago. As a result, three glandless Upland cultivars, i.e., long-staple Acala 1517-18 GLS, medium staple NuMex COT 15 GLS, and NuMex COT 17 GLS with Fusarium wilt race 4 resistance were released. However, to compete with the current commercial glanded cotton, more breeding efforts are urgently needed to introduce different glandless traits (natural mutations, transgenic or genome-editing) into elite cotton backgrounds with high yields and desirable fiber quality.
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Affiliation(s)
- Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, United States
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14
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Shi Y, Liu A, Li J, Zhang J, Li S, Zhang J, Ma L, He R, Song W, Guo L, Lu Q, Xiang X, Gong W, Gong J, Ge Q, Shang H, Deng X, Pan J, Yuan Y. Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:2075-2093. [PMID: 32185421 PMCID: PMC7311500 DOI: 10.1007/s00122-020-03578-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 03/07/2020] [Indexed: 05/29/2023]
Abstract
Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.
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Affiliation(s)
- Yuzhen Shi
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Aiying Liu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Junwen Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Shaoqi Li
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jinfeng Zhang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Liujun Ma
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Rui He
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Weiwu Song
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Lixue Guo
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Quanwei Lu
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xianghui Xiang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Wankui Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Juwu Gong
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Qun Ge
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Haihong Shang
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Xiaoying Deng
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Jingtao Pan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China
| | - Youlu Yuan
- State Key Laboratory of Cotton Biology, Key Laboratory of Biological and Genetic Breeding of Cotton, The Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, 455000, Henan, China.
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