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Wu J, Mao L, Tao J, Wang X, Zhang H, Xin M, Shang Y, Zhang Y, Zhang G, Zhao Z, Wang Y, Cui M, Wei L, Song X, Sun X. Dynamic Quantitative Trait Loci Mapping for Plant Height in Recombinant Inbred Line Population of Upland Cotton. FRONTIERS IN PLANT SCIENCE 2022; 13:914140. [PMID: 35769288 PMCID: PMC9235862 DOI: 10.3389/fpls.2022.914140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 05/06/2022] [Indexed: 06/15/2023]
Abstract
Plant height (PH) is a key plant architecture trait for improving the biological productivity of cotton. Ideal PH of cotton is conducive to lodging resistance and mechanized harvesting. To detect quantitative trait loci (QTL) and candidate genes of PH in cotton, a genetic map was constructed with a recombinant inbred line (RIL) population of upland cotton. PH phenotype data under nine environments and three best linear unbiased predictions (BLUPs) were used for QTL analyses. Based on restriction-site-associated DNA sequence (RAD-seq), the genetic map contained 5,850 single-nucleotide polymorphism (SNP) markers, covering 2,747.12 cM with an average genetic distance of 0.47 cM. Thirty-seven unconditional QTL explaining 1.03-12.50% of phenotypic variance, including four major QTL and seven stable QTL, were identified. Twenty-eight conditional QTL explaining 3.27-28.87% of phenotypic variance, including 1 major QTL, were identified. Importantly, five QTL, including 4 stable QTL, were both unconditional and conditional QTL. Among the 60 PH QTL (including 39 newly identified), none of them were involved in the whole period of PH growth, indicating that QTL related to cotton PH development have dynamic expression characteristics. Based on the functional annotation of Arabidopsis homologous genes and transcriptome data of upland cotton TM-1, 14 candidate genes were predicted within 10 QTL. Our research provides valuable information for understanding the genetic mechanism of PH development, which also increases the economic production of cotton.
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Affiliation(s)
- Jing Wu
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Lili Mao
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Jincai Tao
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest Agriculture and Forestry University, Xianyang, China
| | - Xiuxiu Wang
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Haijun Zhang
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Ming Xin
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Yongqi Shang
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Yanan Zhang
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Guihua Zhang
- Heze Academy of Agricultural Sciences, Heze, China
| | | | - Yiming Wang
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Mingshuo Cui
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Liming Wei
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Xianliang Song
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
| | - Xuezhen Sun
- State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Taian, China
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Geng X, Sun G, Qu Y, Sarfraz Z, Jia Y, He S, Pan Z, Sun J, Iqbal MS, Wang Q, Qin H, Liu J, Liu H, Yang J, Ma Z, Xu D, Yang J, Zhang J, Li Z, Cai Z, Zhang X, Zhang X, Zhou G, Li L, Zhu H, Wang L, Pang B, Du X. Genome-wide dissection of hybridization for fiber quality- and yield-related traits in upland cotton. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 104:1285-1300. [PMID: 32996179 PMCID: PMC7756405 DOI: 10.1111/tpj.14999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 07/14/2020] [Accepted: 09/03/2020] [Indexed: 06/11/2023]
Abstract
An evaluation of combining ability can facilitate the selection of suitable parents and superior F1 hybrids for hybrid cotton breeding, although the molecular genetic basis of combining ability has not been fully characterized. In the present study, 282 female parents were crossed with four male parents in accordance with the North Carolina II mating scheme to generate 1128 hybrids. The parental lines were genotyped based on restriction site-associated DNA sequencing and 306 814 filtered single nucleotide polymorphisms were used for genome-wide association analysis involving the phenotypes, general combining ability (GCA) values, and specific combining ability values of eight fiber quality- and yield-related traits. The main results were: (i) all parents could be clustered into five subgroups based on population structure analyses and the GCA performance of the female parents had significant differences between subgroups; (ii) 20 accessions with a top 5% GCA value for more than one trait were identified as elite parents for hybrid cotton breeding; (iii) 120 significant single nucleotide polymorphisms, clustered into 66 quantitative trait loci, such as the previously reported Gh_A07G1769 and GhHOX3 genes, were found to be significantly associated with GCA; and (iv) identified quantitative trait loci for GCA had a cumulative effect on GCA of the accessions. Overall, our results suggest that pyramiding the favorable loci for GCA may improve the efficiency of hybrid cotton breeding.
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Affiliation(s)
- Xiaoli Geng
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Gaofei Sun
- Anyang Institute of TechnologyAnyang455000China
| | - Yujie Qu
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Zareen Sarfraz
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Yinhua Jia
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Shoupu He
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
| | - Zhaoe Pan
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Junling Sun
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Muhammad S. Iqbal
- Cotton Research StationAyub Agricultural Research InstituteFaisalabad38000Pakistan
| | - Qinglian Wang
- Henan Institute of Science and TechnologyXinxiang453003China
| | - Hongde Qin
- Cash Crop InstituteHubei Academy of Agricultural SciencesWuhan430000China
| | - Jinhai Liu
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Hui Liu
- Jing Hua Seed Industry Technologies IncJingzhou434000China
| | - Jun Yang
- Cotton Research Institute of Jiangxi ProvinceJiujiang332000China
| | - Zhiying Ma
- Key Laboratory of Crop Germplasm Resources of HebeiHebei Agricultural UniversityBaoding071000China
| | - Dongyong Xu
- Guoxin Rural Technical Service AssociationHejian062450China
| | - Jinlong Yang
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | | | - Zhikun Li
- Key Laboratory of Crop Germplasm Resources of HebeiHebei Agricultural UniversityBaoding071000China
| | - Zhongmin Cai
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Xuelin Zhang
- Hunan Cotton Research InstituteChangde415000China
| | - Xin Zhang
- Henan Institute of Science and TechnologyXinxiang453003China
| | - Guanyin Zhou
- Zhongmian Cotton Seed Industry Technology Co., LtdZhengzhou455001China
| | - Lin Li
- Zhongli Company of ShandongDongying257000China
| | - Haiyong Zhu
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Liru Wang
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Baoyin Pang
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
| | - Xiongming Du
- State Key Laboratory of Cotton BiologyInstitute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang455000China
- Zhengzhou Research BaseState Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhou455001China
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Shimazaki H, Ono A, Tsuruga M, Ueki A, Koseki-Kuno S, Toyoda T, Saito K, Sawakami K, Kariya M, Segawa O, Nakamura K, Koizuka M, Kuno A. GlycoBIST: A System for Automatic Glycan Profiling of a Target Protein Using Milli-Bead Array in a Tip. ACTA ACUST UNITED AC 2020; 99:e103. [PMID: 32073758 DOI: 10.1002/cpps.103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Lectin is a biomolecule that recognizes a specific part of glycans and, thus, has been used widely as a probe for glycoprotein analysis. Owing to the wide repertoire in nature combined with the recent two decades of advances in microarray technology, the multiplexed use of lectins has been widely used for glycan profiling of endogenous proteins. Because protein glycosylation is recognized as being biologically important and is expected to be a reliable disease marker, lectin microarray analysis with highly sensitive detection has been used to discover disease-relevant glycosylation alterations. However, the conventional system is limited to research purposes; thus, its implementation in clinical settings is warranted. Here, we provide an automatic glycan profiling method using GlycoBIST. A unique array format is used for 10-plexed lectin-glycoprotein interaction analysis on 1-mm-sized beads, which are arranged vertically in a capillary-shaped plastic tip. Using a one-boxed autopipetting machine, the whole process (including interaction, washing, and detection) is performed automatically and serially, resulting in reproducible measurements. In this article, a typical method for glycan profiling of a purified glycoprotein and the fabrication of GlycoBIST tips is explained. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Fabrication of a GlycoBIST tip Basic Protocol 2: Automatic profiling of a target glycoprotein using GlycoBIST.
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Affiliation(s)
- Hiroko Shimazaki
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Ayaka Ono
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Masako Tsuruga
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Aya Ueki
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Shiori Koseki-Kuno
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Takako Toyoda
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | - Kozue Saito
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
| | | | - Minoru Kariya
- Precision System Science, Kamihongou, Matsudo, Chiba, Japan
| | - Osamu Segawa
- Precision System Science, Kamihongou, Matsudo, Chiba, Japan
| | | | | | - Atsushi Kuno
- Glycoscience and Glycotechnology Research Group, Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
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Ma J, Pei W, Ma Q, Geng Y, Liu G, Liu J, Cui Y, Zhang X, Wu M, Li X, Li D, Zang X, Song J, Tang S, Zhang J, Yu S, Yu J. QTL analysis and candidate gene identification for plant height in cotton based on an interspecific backcross inbred line population of Gossypium hirsutum × Gossypium barbadense. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:2663-2676. [PMID: 31236630 DOI: 10.1007/s00122-019-03380-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 06/14/2019] [Indexed: 05/24/2023]
Abstract
We constructed the first high-quality and high-density genetic linkage map for an interspecific BIL population in cotton by specific-locus amplified fragment sequencing for QTL mapping. A novel gene GhPIN3 for plant height was identified in cotton. Ideal plant height (PH) is important for improving lint yield and mechanized harvesting in cotton. Most published genetic studies on cotton have focused on fibre yield and quality traits rather than PH. To facilitate the understanding of the genetic basis in PH, an interspecific backcross inbred line (BIL) population of 250 lines derived from upland cotton (Gossypium hirsutum L.) CRI36 and Egyptian cotton (G. barbadense L.) Hai7124 was used to construct a high-density genetic linkage map for quantitative trait locus (QTL) mapping. The high-density genetic map harboured 7,709 genotyping-by-sequencing (GBS)-based single nucleotide polymorphism (SNP) markers that covered 3,433.24 cM with a mean marker interval of 0.67 cM. In total, ten PH QTLs were identified and each explained 4.27-14.92% of the phenotypic variation, four of which were stable as they were mapped in at least two tests or based on best linear unbiased prediction in seven field tests. Based on functional annotation of orthologues in Arabidopsis and transcriptome data for the genes within the stable QTL regions, GhPIN3 encoding for the hormone auxin efflux carrier protein was identified as a candidate gene located in the stable QTL qPH-Dt1-1 region. A qRT-PCR analysis showed that the expression level of GhPIN3 in apical tissues was significantly higher in four short-statured cotton genotypes than that in four tall-statured cotton genotypes. Virus-induced gene silencing cotton has significantly increased PH when the expression of the GhPIN3 gene was suppressed.
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Affiliation(s)
- Jianjiang Ma
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
- College of Agriculture, Northwest A&F University, Yangling, 712100, Shanxi, China
| | - Wenfeng Pei
- Xinjiang Research Base, State Key Laboratory of Cotton Biology, Xinjiang Agricultural University, Urumqi, 830001, China
| | - Qifeng Ma
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Yanhui Geng
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Guoyuan Liu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Ji Liu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Yupeng Cui
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Xia Zhang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Xingli Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Dan Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - XinShan Zang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Jikun Song
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Shurong Tang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 880033, USA.
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
- College of Agriculture, Northwest A&F University, Yangling, 712100, Shanxi, China.
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
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Ma J, Geng Y, Pei W, Wu M, Li X, Liu G, Li D, Ma Q, Zang X, Yu S, Zhang J, Yu J. Genetic variation of dynamic fiber elongation and developmental quantitative trait locus mapping of fiber length in upland cotton (Gossypium hirsutum L.). BMC Genomics 2018; 19:882. [PMID: 30522448 PMCID: PMC6282333 DOI: 10.1186/s12864-018-5309-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 11/25/2018] [Indexed: 02/04/2023] Open
Abstract
Background In upland cotton (Gossypium hirsutum L.), genotypes with the same mature fiber length (FL) might possess different genes and exhibit differential expression of genes related to fiber elongation at different fiber developmental stages. However, there is a lack of information on the genetic variation influencing fiber length and its quantitative trait loci (QTLs) during the fiber elongation stage. In this study, a subset of upland cotton accessions was selected based on a previous GWAS conducted in China and grown in multiple environments to determine the dynamic fiber length at 10, 15, 20, and 25 days post-anthesis (DPA) and maturity. The germplasm lines were genotyped with the Cotton 63 K Illumina single-nucleotide polymorphism (SNP) array for GWAS. Results A total of 25, 38, 57, 89 and 88 SNPs showed significant correlations with fiber length at 10, 15, 20 and 25 DPA and maturity, respectively. In addition, 60 more promising SNPs were detected in at least two tests and two FL developmental time points, and 20 SNPs were located within the confidence intervals of QTLs identified in previous studies. The fastest fiber-length growth rates were obtained at 10 to 15 DPA in 69 upland cotton lines and at 15 to 20 DPA in 14 upland cotton accessions, and 10 SNPs showed significant correlations with the fiber-length growth rate. A combined transcriptome and qRT-PCR analysis revealed that two genes (D10G1008 and D13G2037) showed differential expression between two long-fiber genotypes and two short-fiber genotypes. Conclusions This study provides important new insights into the genetic basis of the time-dependent fiber-length trait and reveals candidate SNPs and genes for improving fiber length in upland cotton. Electronic supplementary material The online version of this article (10.1186/s12864-018-5309-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jianjiang Ma
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shanxi, China.,State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Yanhui Geng
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Wenfeng Pei
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Man Wu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Xingli Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Guoyuan Liu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Dan Li
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Qifeng Ma
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - XinShan Zang
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China
| | - Shuxun Yu
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shanxi, China. .,State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
| | - Jinfa Zhang
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, 880033, USA.
| | - Jiwen Yu
- State Key Laboratory of Cotton Biology, Cotton Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.
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Ma L, Zhao Y, Wang Y, Shang L, Hua J. QTLs Analysis and Validation for Fiber Quality Traits Using Maternal Backcross Population in Upland Cotton. FRONTIERS IN PLANT SCIENCE 2017; 8:2168. [PMID: 29312408 PMCID: PMC5744017 DOI: 10.3389/fpls.2017.02168] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Accepted: 12/11/2017] [Indexed: 05/04/2023]
Abstract
Cotton fiber is renewable natural fiber source for textile. Improving fiber quality is an essential goal for cotton breeding project. In present study, F14 recombinant inbred line (RIL) population was backcrossed by the maternal parent to obtain a backcross (BC) population, derived from one Upland cotton hybrid. Three repetitive field trials were performed by randomized complete block design with two replicates in three locations in 2015, together with the BC population, common male parent and the RIL population. Totally, 26 QTLs in BC population explained 5.00-14.17% of phenotype variation (PV) and 37 quantitative trait loci (QTL) were detected in RIL population explaining 5.13-34.00% of PV. Seven common QTLs detected simultaneously in two populations explained PV from 7.69 to 23.05%. A total of 20 QTLs in present study verified the previous results across three environments in 2012. Particularly, qFL-Chr5-2 controlling fiber length on chromosome 5 explained 34.00% of PV, while qFL-Chr5-3 only within a 0.8 cM interval explained 13.93% of PV on average in multiple environments. These stable QTLs explaining great variation offered essential information for marker-assisted selection (MAS) to improve fiber quality traits. Lots of epistasis being detected in both populations acted as one of important genetic compositions of fiber quality traits.
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Affiliation(s)
- Lingling Ma
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
| | - Yanpeng Zhao
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
| | - Yumei Wang
- Department of Cotton Breeding, Institute of Cash Crops, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Lianguang Shang
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
| | - Jinping Hua
- Laboratory of Cotton Genetics, Genomics and Breeding, College of Agronomy and Biotechnology/Beijing Key Laboratory of Crop Genetic Improvement/Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, China Agricultural University, Beijing, China
- *Correspondence: Jinping Hua
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