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Li G, Che J, Gong J, Duan L, Zhang Z, Jiang X, Xu P, Fan S, Gong W, Shi Y, Liu A, Li J, Li P, Pan J, Deng X, Yuan Y, Shang H. Quantitative Trait Locus Mapping for Plant Height and Branch Number in CCRI70 Recombinant Inbred Line Population of Upland Cotton (Gossypium hirsutum). PLANTS (BASEL, SWITZERLAND) 2024; 13:1509. [PMID: 38891318 PMCID: PMC11174691 DOI: 10.3390/plants13111509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 05/08/2024] [Accepted: 05/21/2024] [Indexed: 06/21/2024]
Abstract
Upland cotton accounts for a high percentage (95%) of the world's cotton production. Plant height (PH) and branch number (BN) are two important agronomic traits that have an impact on improving the level of cotton mechanical harvesting and cotton yield. In this research, a recombinant inbred line (RIL) population with 250 lines developed from the variety CCRI70 was used for constructing a high-density genetic map and identification of quantitative trait locus (QTL). The results showed that the map harbored 8298 single nucleotide polymorphism (SNP) markers, spanning a total distance of 4876.70 centimorgans (cMs). A total of 69 QTLs for PH (9 stable) and 63 for BN (11 stable) were identified and only one for PH was reported in previous studies. The QTLs for PH and BN harbored 495 and 446 genes, respectively. Combining the annotation information, expression patterns and previous studies of these genes, six genes could be considered as potential candidate genes for PH and BN. The results could be helpful for cotton researchers to better understand the genetic mechanism of PH and BN development, as well as provide valuable genetic resources for cotton breeders to manipulate cotton plant architecture to meet future demands.
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Affiliation(s)
- Gangling Li
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China; (G.L.); (J.C.)
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Jincan Che
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China; (G.L.); (J.C.)
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
| | - Juwu Gong
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Li Duan
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, College of Life Science, Henan University, Kaifeng 475001, China
| | - Zhen Zhang
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Xiao Jiang
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Peng Xu
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Senmiao Fan
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Wankui Gong
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Yuzhen Shi
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Aiying Liu
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Junwen Li
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Pengtao Li
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Jingtao Pan
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Xiaoying Deng
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Youlu Yuan
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China; (G.L.); (J.C.)
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
| | - Haihong Shang
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450001, China; (G.L.); (J.C.)
- National Key Laboratory of Cotton Bio-Breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; (J.G.); (L.D.); (X.J.); (P.X.); (S.F.); (W.G.); (A.L.); (J.L.); (P.L.); (J.P.); (X.D.)
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Darmanov MM, Makamov AK, Ayubov MS, Khusenov NN, Buriev ZT, Shermatov SE, Salakhutdinov IB, Ubaydullaeva KA, Norbekov JK, Kholmuradova MM, Narmatov SE, Normamatov IS, Abdurakhmonov IY. Development of Superior Fibre Quality Upland Cotton Cultivar Series 'Ravnaq' Using Marker-Assisted Selection. FRONTIERS IN PLANT SCIENCE 2022; 13:906472. [PMID: 35677232 PMCID: PMC9168987 DOI: 10.3389/fpls.2022.906472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 05/03/2022] [Indexed: 05/24/2023]
Abstract
Marker-assisted selection (MAS) helps to shorten breeding time as well as reduce breeding resources and efforts. In our MAS program, we have targeted one of previously reported LD-blocks with its simple sequence repeat (SSR) marker(s), putatively associated with, at least, four different fibre quality QTLs such as fibre length, strength, micronaire and uniformity. In order to transfer targeted QTLs from a donor genotype to a cultivar of choice, we selected G. hirsutum donor genotypes L-141 and LN-1, possessing a fibre quality trait-associated LD-block from the chromosome 7/16. We crossed the donor lines with local elite G. hirsutum cultivars 'Andijan-35' and 'Mekhnat' as recipients. As a result, two segregating populations on LD-block of interest containing fibre QTLs were developed through backcrossing (BC) of F1 hybrids with their relative recipients (used as recurrent parents) up to five generations. In each BC and segregating BC1-5F1 populations, a transfer of targeted LD-block/QTLs was monitored using a highly polymorphic SSR marker, BNL1604 genotype. The homozygous cultivar genotypes with superior fibre quality and agronomic traits, bearing a targeted LD-block of interest, were individually selected from self-pollinated BC5F1 (BC5F2-5) population plants using the early-season PCR screening analysis of BNL1604 marker locus and the end-of-season fibre quality parameters. Only improved hybrids with superior fibre quality compared to original recipient parent were used for the next cycle of breeding. We successfully developed two novel MAS-derived cotton cultivars (named as 'Ravnaq-1' and 'Ravnaq-2') of BC5F5 generations. Both novel MAS cultivars possessed stronger and longer fibre as well as improved fibre uniformity and micronaire compared to the original recurrent parents, 'Andijan-35' and 'Mekhnat'. Our efforts demonstrated a precise transfer of the same LD-block with, at least, four superior fibre QTLs in the two independent MAS breeding experiments exploiting different parental genotypes. Results exemplify the feasibility of MAS in cotton breeding.
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Chandnani R, Kim C, Patel JD, Guo H, Shehzad T, Wallace JG, He D, Zhang Z, Adhikari J, Khanal S, Chee PW, Paterson AH. Identification of small effect quantitative trait loci of plant architectural, flowering, and early maturity traits in reciprocal interspecific introgression population in cotton. FRONTIERS IN PLANT SCIENCE 2022; 13:981682. [PMID: 36061803 PMCID: PMC9433993 DOI: 10.3389/fpls.2022.981682] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 07/26/2022] [Indexed: 05/13/2023]
Abstract
Plant architecture, flowering time and maturity traits are important determinants of yield and fiber quality of cotton. Genetic dissection of loci determining these yield and quality components is complicated by numerous loci with alleles conferring small differences. Therefore, mapping populations segregating for smaller numbers and sizes of introgressed segments is expected to facilitate dissection of these complex quantitative traits. At an advanced stage in the development of reciprocal advanced backcross populations from crosses between elite Gossypium hirsutum cultivar 'Acala Maxxa' (GH) and G. barbadense 'Pima S6' (GB), we undertook mapping of plant architectural traits, flowering time and maturity. A total of 284 BC4F1 and BC4F2 progeny rows, 120 in GH and 164 in GB background, were evaluated for phenotype, with only 4 and 3 (of 7) traits showing significant differences among progenies. Genotyping by sequencing yielded 3,186 and 3,026 SNPs, respectively, that revealed a total of 27 QTLs in GH background and 22 in GB, for plant height, days to flowering, residual flowering at maturity and maturity. More than of 90% QTLs identified in both backgrounds had small effects (%PV < 10), supporting the merit of this population structure to reduce background noise and small effect QTLs. Germplasm developed in this study may serve as potential pre-breeding material to develop improved cotton cultivars.
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Affiliation(s)
- Rahul Chandnani
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
| | - Changsoo Kim
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
- Department of Crop Science, College of Agriculture and Life Sciences, Chungnam National University, Daejeon, South Korea
| | - Jinesh D. Patel
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
| | - Hui Guo
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
| | - Tariq Shehzad
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
| | - Jason G. Wallace
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, United States
| | - Daohua He
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Zhengsheng Zhang
- College of Agronomy and Biotechnology, Southwest University, Chongqing, China
| | - Jeevan Adhikari
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
| | - Sameer Khanal
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
| | - Peng W. Chee
- NESPAL Molecular Cotton Breeding Laboratory, The University of Georgia, Tifton, GA, United States
| | - Andrew H. Paterson
- Plant Genome Mapping Laboratory, The University of Georgia, Athens, GA, United States
- *Correspondence: Andrew H. Paterson,
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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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Knoch D, Abbadi A, Grandke F, Meyer RC, Samans B, Werner CR, Snowdon RJ, Altmann T. Strong temporal dynamics of QTL action on plant growth progression revealed through high-throughput phenotyping in canola. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:68-82. [PMID: 31125482 PMCID: PMC6920335 DOI: 10.1111/pbi.13171] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 05/13/2019] [Accepted: 05/15/2019] [Indexed: 05/08/2023]
Abstract
A major challenge of plant biology is to unravel the genetic basis of complex traits. We took advantage of recent technical advances in high-throughput phenotyping in conjunction with genome-wide association studies to elucidate genotype-phenotype relationships at high temporal resolution. A diverse Brassica napus population from a commercial breeding programme was analysed by automated non-invasive phenotyping. Time-resolved data for early growth-related traits, including estimated biovolume, projected leaf area, early plant height and colour uniformity, were established and complemented by fresh and dry weight biomass. Genome-wide SNP array data provided the framework for genome-wide association analyses. Using time point data and relative growth rates, multiple robust main effect marker-trait associations for biomass and related traits were detected. Candidate genes involved in meristem development, cell wall modification and transcriptional regulation were detected. Our results demonstrate that early plant growth is a highly complex trait governed by several medium and many small effect loci, most of which act only during short phases. These observations highlight the importance of taking the temporal patterns of QTL/allele actions into account and emphasize the need for detailed time-resolved analyses to effectively unravel the complex and stage-specific contributions of genes affecting growth processes that operate at different developmental phases.
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Affiliation(s)
- Dominic Knoch
- Molecular Genetics/HeterosisLeibniz Institute of Plant Genetics and Crop Plant Research (IPK)SeelandGermany
| | - Amine Abbadi
- Norddeutsche Pflanzenzucht Innovation GmbH (NPZi)HoltseeGermany
| | - Fabian Grandke
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
| | - Rhonda C. Meyer
- Molecular Genetics/HeterosisLeibniz Institute of Plant Genetics and Crop Plant Research (IPK)SeelandGermany
| | - Birgit Samans
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
- Present address:
Technische Hochschule Mittelhessen (THM), University of Applied SciencesFachbereich Gesundheit35390GiessenGermany
| | - Christian R. Werner
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
- Present address:
The Roslin InstituteUniversity of EdinburghEaster Bush CampusMidlothianEH25 9RGUK
| | - Rod J. Snowdon
- Department of Plant BreedingResearch Centre for BiosystemsLand Use and Nutrition (iFZ)Justus‐Liebig‐University GiessenGiessenGermany
| | - Thomas Altmann
- Molecular Genetics/HeterosisLeibniz Institute of Plant Genetics and Crop Plant Research (IPK)SeelandGermany
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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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Shared Genomic Regions Underlie Natural Variation in Diverse Toxin Responses. Genetics 2018; 210:1509-1525. [PMID: 30341085 PMCID: PMC6283156 DOI: 10.1534/genetics.118.301311] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Accepted: 10/16/2018] [Indexed: 01/25/2023] Open
Abstract
Phenotypic complexity is caused by the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis often find that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci (QTL). Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 82 QTL that underlie variation in responses to these toxins, and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These QTL hotspots could represent common factors impacting toxin responses. We went further to generate near-isogenic lines and chromosome substitution strains, and then experimentally validated these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation.
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Su J, Li L, Zhang C, Wang C, Gu L, Wang H, Wei H, Liu Q, Huang L, Yu S. Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:1299-1314. [PMID: 29497767 DOI: 10.1007/s00122-018-3079-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 02/24/2018] [Indexed: 05/04/2023]
Abstract
Thirty significant associations between 22 SNPs and five plant architecture component traits in Chinese upland cotton were identified via GWAS. Four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits. A candidate gene, Gh_D03G0922, might be responsible for plant height in upland cotton. A compact plant architecture is increasingly required for mechanized harvesting processes in China. Therefore, cotton plant architecture is an important trait, and its components, such as plant height, fruit branch length and fruit branch angle, affect the suitability of a cultivar for mechanized harvesting. To determine the genetic basis of cotton plant architecture, a genome-wide association study (GWAS) was performed using a panel composed of 355 accessions and 93,250 single nucleotide polymorphisms (SNPs) identified using the specific-locus amplified fragment sequencing method. Thirty significant associations between 22 SNPs and five plant architecture component traits were identified via GWAS. Most importantly, four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits, and these SNPs were harbored in one linkage disequilibrium block. Furthermore, 21 candidate genes for plant architecture were predicted in a 0.95-Mb region including the four peak SNPs. One of these genes (Gh_D03G0922) was near the significant SNP D03_31584163 (8.40 kb), and its Arabidopsis homologs contain MADS-box domains that might be involved in plant growth and development. qRT-PCR showed that the expression of Gh_D03G0922 was upregulated in the apical buds and young leaves of the short and compact cotton varieties, and virus-induced gene silencing (VIGS) proved that the silenced plants exhibited increased PH. These results indicate that Gh_D03G0922 is likely the candidate gene for PH in cotton. The genetic variations and candidate genes identified in this study lay a foundation for cultivating moderately short and compact varieties in future Chinese cotton-breeding programs.
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Affiliation(s)
- Junji Su
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
- Cotton Research Institute, Xinjiang Academy of Agricultural and Reclamation Science/Northwest Inland Region Key Laboratory of Cotton Biology and Genetic Breeding, Ministry of Agriculture, Shihezi, China
| | - Libei Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
| | - Chi Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
| | - Caixiang Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
| | - Lijiao Gu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
| | - Hantao Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
| | - Hengling Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
| | - Qibao Liu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China
| | - Long Huang
- Shanghai Majorbio Bio-pharm Biotechnology Co. Ltd., Shanghai, China
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China.
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Liu YJ, Gao SQ, Tang YM, Gong J, Zhang X, Wang YB, Zhang LP, Sun RW, Zhang Q, Chen ZB, Wang X, Guo CJ, Zhang SQ, Zhang FT, Gao JG, Sun H, Yang WB, Wang WW, Zhao CP. Transcriptome analysis of wheat seedling and spike tissues in the hybrid Jingmai 8 uncovered genes involved in heterosis. PLANTA 2018; 247:1307-1321. [PMID: 29504038 DOI: 10.1007/s00425-018-2848-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Accepted: 01/12/2018] [Indexed: 05/23/2023]
Abstract
Transcriptome analysis was carried out for wheat seedlings and spikes from hybrid Jingmai 8 and both inbred lines to unravel mechanisms underlying heterosis. Heterosis, known as one of the most successful strategies for increasing crop yield, has been widely exploited in plant breeding systems. Despite its great importance, the molecular mechanism underlying heterosis remains elusive. In the present study, RNA sequencing (RNA-seq) was performed on the seedling and spike tissues of the wheat (Triticum aestivum) hybrid Jingmai 8 (JM8) and its homozygous parents to unravel the underlying mechanisms of wheat heterosis. In total, 1686 and 2334 genes were identified as differentially expressed genes (DEGs) between the hybrid and the two inbred lines in seedling and spike tissues, respectively. Gene Ontology analysis revealed that DEGs from seedling tissues were significantly enriched in processes involved in photosynthesis and carbon fixation, and the majority of these DEGs expressed at a higher level in JM8 compared to both inbred lines. In addition, cell wall biogenesis and protein biosynthesis-related pathways were also significantly represented. These results confirmed that a combination of different pathways could contribute to heterosis. The DEGs between the hybrid and the two inbred progenitors from the spike tissues were significantly enriched in biological processes related to transcription, RNA biosynthesis and molecular function categories related to transcription factor activities. Furthermore, transcription factors such as NAC, ERF, and TIF-IIA were highly expressed in the hybrid JM8. These results may provide valuable insights into the molecular mechanisms underlying wheat heterosis.
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Affiliation(s)
- Yong-Jie Liu
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Shi-Qing Gao
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
| | - Yi-Miao Tang
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Jie Gong
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Xiao Zhang
- Hebei Normal University, Shijiazhuang, 050024, China
| | - Yong-Bo Wang
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Li-Ping Zhang
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Ren-Wei Sun
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
- Beijing University of Agriculture, Beijing, 100036, China
| | - Quan Zhang
- Shandong Normal University, Jinan, 250014, China
| | - Zhao-Bo Chen
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Xiang Wang
- Huazhong Agricultural University, Wuhan, 430070, China
| | | | - Sheng-Quan Zhang
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Feng-Ting Zhang
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Jian-Gang Gao
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Hui Sun
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Wei-Bing Yang
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Wei-Wei Wang
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China
| | - Chang-Ping Zhao
- Beijing Engineering Research Center for Hybrid Wheat, The Municipal Key Laboratory of the Molecular Genetics of Hybrid Wheat, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
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