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Acta Agronomica Sinica ›› 2019, Vol. 45 ›› Issue (2): 196-203.doi: 10.3724/SP.J.1006.2019.84100


Development and evaluation of InDel markers in cotton based on whole-genome re-sequencing data

Mi WU,Nian WANG,Chao SHEN,Cong HUANG,Tian-Wang WEN,Zhong-Xu LIN()   

  1. National Key Laboratory of Crop Genetic Improvement / College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
  • Received:2018-07-19 Accepted:2018-10-08 Online:2019-02-12 Published:2018-11-16
  • Contact: Zhong-Xu LIN E-mail:linzhongxu@mail.hzau.edu.cn
  • Supported by:
    This study was supported by the Technology Innovation Program of Hubei Province(2018ABA082)


Insertion and deletion (InDel) are abundant forms of genetic variation in the genome. InDel has been recognized as an ideal source for marker development due to its high-density distribution and genotyping efficiency. In this study, the whole genome re-sequencing data of 262 upland cotton accessions were applied to identify 3206 InDel markers, and 320 markers with uniform distribution across the genome were selected to be evaluated. Eighty-seven polymorphic markers were identified, accounting for 26.88% of screened markers. A total of 160 allelic loci were detected using the 87 polymorphic markers in the 262 upland cotton accessions with an average polymorphic information content (PIC) of 0.3073 (ranging from 0.0836 to 0.3750) and an average genetic diversity of 0.3876 (ranging from 0.0874 to 0.5000), indicating a relatively low genetic diversity. Population structure analysis revealed extensive admixture and identified two subgroups, clustering analysis and principal component analysis supported the subgroups identified by STRUCTURE. Association analysis were performed by MLM (Mixed linear model), and 65 marker loci were associated with fiber quality traits (P < 0.01), explaining 2.57%-8.12% of the phenotypic variation. Genome-wide and gel based InDel markers developed based on re-sequencing data in this study provide a facile tool for cotton germplasm resources research and molecular marker assisted selection breeding.

Key words: Upland cotton, InDel marker, genetic diversity, population structure, association analysis

Fig. 1

Amplification products of marker HAU_ID_D11-01 in some accessions"

Fig. 2

Lines chart of K value with ln P(D) value and ΔK value A: Line chart of ln P(D) value with change of K; B: Line chart of ΔK value with change of K."

Fig. 3

Population structure of 262 upland cotton accessions based on InDel markers"

Fig. 4

PCA plots of 262 upland cotton accessions based on InDel markers NIR: Northwestern Inland Region of China; NSEMR: Northern Specific Early Maturation Region of China; SCR: South China Region; SU: Former Soviet Union; USA: American; YRR: Yellow River Region of China; YtRR: Yangtze River Region of China."

Fig. 5

Phylogenetic tree of the accessions based on genetic distance Red lines: group 1, including 182 accessions; Green lines: group 2, including 80 accessions."

Table 1

Markers associated with multi-traits"

Marker locus
Position (bp)
HAU_ID_A01-15 A01 93250996 FUHML, FU, SF
HAU_ID_A03-09 A03 57007522 FE, FU, SF
HAU_ID_A08-06 A08 39475602 FE, MV
HAU_ID_A08-07 A08 47285210 FE, MV
HAU_ID_A08-14 A08 98729870 FU, SF
HAU_ID_A09-04 A09 23151235 FUHML, FS
HAU_ID_A10-01 A10 1109653 MV, SF
HAU_ID_A10-09 A10 57152725 FS, FU, MV
HAU_ID_D01-10 D01 43635771 FS, FU
HAU_ID_D02-01 D02 1069504 FUHML, FE
HAU_ID_D02-08 D02 45682280 MV, SF
HAU_ID_D04-07 D04 47451029 FE, MV
HAU_ID_D06-06 D06 35163294 FUHML, FU, SF
HAU_ID_D06-07 D06 39113925 FUHML, FU, SF
HAU_ID_D07-04 D07 23469098 FU, SF
HAU_ID_D07-09 D07 47924875 FUHML, FS, FE, FU, SF
HAU_ID_D09-10 D09 49075327 FUHML, SF
HAU_ID_D11-13 D11 65414930 FE, SF
HAU_ID_D12-10 D12 51191458 FUHML, FS, FU, SF
[1] 喻树迅 . 中国棉花产业百年发展历程. 农学学报, 2018, ( 1):85-91.
Yu S X . The development of cotton production in the recent hundred years of China. J Agric, 2018, ( 1):85-91 (in Chinese with English abstract).
[2] 董承光, 王娟, 周小凤, 马晓梅, 李生秀, 余渝, 李保成 . 基于表型性状的陆地棉种质资源遗传多样性分析. 植物遗传资源学报, 2016,17:438-446.
doi: 10.13430/j.cnki.jpgr.2016.03.006
Dong C G, Wang J, Zhou X F, Ma X M, Li S X, Yu Y, Li B C . Evaluation on genetic diversity of cotton germplasm resources (Gossypium hirsutum L.) on morphological characters. J Plant Genet Resour, 2016,17:438-446 (in Chinese with English abstract).
doi: 10.13430/j.cnki.jpgr.2016.03.006
[3] Dong C G, Wang J, Yu Y, Li B C, Chen Q J . Association mapping and favourable QTL alleles for fibre quality traits in Upland cotton (Gossypium hirsutum L.). J Genet, 2018,97:e1-e12.
doi: 10.1007/s12041-017-0878-4 pmid: 29700269
[4] Huang C, Shen C, Wen T W, Gao B, Zhu D, Li X, Ahmed M M, Li D, Lin Z X . SSR-based association mapping of fiber quality in upland cotton using an eight-way MAGIC population. Mol Genet Genomics, 2018,293:793-805.
doi: 10.1007/s00438-018-1419-4 pmid: 29392407
[5] Sahu P K, Mondal S, Sharma D, Vishwakarma G, Kumar V, Das B K . InDel marker based genetic differentiation and genetic diversity in traditional rice (Oryza sativa L.) landraces of Chhattisgarh, India. PLoS One, 2017,12:e0188864.
doi: 10.1371/journal.pone.0188864 pmid: 29190790
[6] Liu J, Qu J T, Yang C, Tang D G, Li J W, Lan H, Rong T Z . Development of genome-wide insertion and deletion markers for maize, based on next-generation sequencing data. BMC Genomics, 2015,16:601.
doi: 10.1186/s12864-015-1797-5 pmid: 4535256
[7] Liu B, Wang Y, Zhai W, Deng J, Wang H, Cui Y, Cheng F, Wang X W, Wu J . Development of InDel markers for Brassica rapa based on whole-genome re-sequencing. Theor Appl Genet, 2013,126:231-239.
doi: 10.1007/s00122-012-1976-6 pmid: 22972202
[8] Zhang T, Hu Y, Jiang W, Fang L, Guan X, Chen J, Zhang J, Saski C A, Scheffler B E, Stelly D M . Sequencing of allotetraploid cotton (Gossypium hirsutum L. acc. TM-1) provides a resource for fiber improvement. Nat Biotechnol, 2015,33:531-537.
[9] Wang M J, Tu L L, Min L, Lin Z X, Wang P C, Yang Q Y, Ye Z X, Shen C, Li J Y, Zhang X L . Asymmetric subgenome selection and cis-regulatory divergence during cotton domestication. Nat Genet, 2017,49:579-587.
doi: 10.1038/ng.3807 pmid: 28263319
[10] Huang C, Nie X H, Shen C, You C Y, Li W, Zhao W X, Zhang X L, Lin Z X . Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome-wide association study using high-density SNPs. Plant Biotechnol J, 2017,15:1374-1386.
doi: 10.1111/pbi.12722 pmid: 5633765
[11] Nie X H, Huang C, You C Y, Li W, Zhao W X, Shen C, Zhang B B, Wang H T, Yan Z H, Dai B S, Wang M J, Zhang X L, Lin Z X . Genome-wide SSR-based association mapping for fiber quality in nation-wide upland cotton inbreed cultivars in China. BMC Genomics, 2016,17:352.
doi: 10.1186/s12864-016-2662-x pmid: 4866303
[12] Rozen S, Skaletsky H . Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol, 2000,132:365-386.
doi: 10.1385/1-59259-192-2:365
[13] Li X M, Yuan D J, Wang H T, Chen X M, Wang B, Lin Z X, Zhang X L . Increasing cotton genome coverage with polymorphic SSRs as revealed by SSCP. Genome, 2012,55:459-470.
doi: 10.1139/g2012-032 pmid: 22670804
[14] Botstein D, White R L, Skolnick M, Davis R W . Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet, 1980,32:314-331.
[15] Letunic I, Bork P . Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucl Acids Res, 2016,44:W242-W245.
doi: 10.1093/nar/gkw290 pmid: 4987883
[16] Pritchard J K, Stephens M, Donnelly P . Inferences of population structure using multilocus genotype data. Genetics, 2000,155:945-959.
[17] Earl D A, Vonholdt B M . STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour, 2012,4:359-361.
doi: 10.1007/s12686-011-9548-7
[18] Evanno G, Regnaut S, Goudet J . Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol, 2010,14:2611-2620.
[19] Bradbury P J, Zhang Z, Kroon D E, Casstevens T M, Ramdoss Y, Buckler E S . TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007,23:2633-2635.
doi: 10.1093/bioinformatics/btm308 pmid: 17586829
[20] Wu D H, Wu H P, Wang C S, Tseng H Y, Hwu K K . Genome-wide InDel marker system for application in rice breeding and mapping studies. Euphytica, 2013,192:131-143.
doi: 10.1007/s10681-013-0925-z
[21] Wang H, Jin X, Zhang B, Shen C, Lin Z . Enrichment of an intraspecific genetic map of upland cotton by developing markers using parental RAD sequencing. DNA Res, 2015,22:147-160.
doi: 10.1093/dnares/dsu047 pmid: 4401325
[22] Lin Z X, Zhang Y X, Zhang X L, Guo X P . A high-density integrative linkage map for Gossypium hirsutum. Euphytica, 2009,166:35-45.
[23] Liu R Z, Wang B H, Guo W Z, Qin Y S, Wang L G, Zhang Y M, Zhang T Z . Quantitative trait loci mapping for yield and its components by using two immortalized populations of a heterotic hybrid in Gossypium hirsutum L. Mol Breed, 2012,29:297-311.
doi: 10.1007/s11032-011-9547-0
[24] Fang D D, Li P, Thyssen G, Hinze L L, Percy R G . A microsatellite-based genome-wide analysis of genetic diversity and linkage disequilibrium in Upland cotton (Gossypium hirsutum L.). Euphytica, 2013,191:391-401.
[25] Wen T W, Wu M, Shen C, Gao B, Zhu D, Zhang X L, You C Y, Lin Z X . Linkage and association mapping reveals the genetic basis of brown fibre (Gossypium hirsutum). Plant Biotechnol J, 2018,16:1654-1666.
doi: 10.1111/pbi.12902
[26] Ai X, Liang Y, Wang J, Zheng J, Gong Z, Guo J, Li X, Qu Y . Genetic diversity and structure of elite cotton germplasm (Gossypium hirsutum L.) using genome-wide SNP data. Genetica, 2017,145:409-416.
doi: 10.1007/s10709-017-9976-8 pmid: 28755130
[27] Tyagi P, Gore M A, Bowman D T, Campbell B T, Udall J A, Kuraparthy V . Genetic diversity and population structure in the US Upland cotton (Gossypium hirsutum L.). Theor Appl Genet, 2014,127:283-295.
doi: 10.1007/s00122-013-2217-3 pmid: 24170350
[28] Flint-Garcia S A, Thornsberry J M, Buckler E S . Structure of linkage disequilibrium in plants. Annu Rev Plant Biol, 2003,54:357-374.
doi: 10.1146/annurev.arplant.54.031902.134907
[29] Zhang Z W, Ersoz E, Lai C Q, Todhunter R J, Tiwari H K, Gore M A, Bradbury P J, Yu J M, Arnett D K, Ordovas J M, Buckler E S . Mixed linear model approach adapted for genome-wide association studies. Nat Genet, 2010,4:355-360.
doi: 10.1038/ng.546 pmid: 20208535
[30] Ma Z Y, He S P, Wang X F, Sun J L, Zhang Y, Zhang G Y, Wu L Q, Li Z K, Liu Z H, Sun G F, Du X M . Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield. Nat Genet, 2018,50:803-813.
doi: 10.1038/s41588-018-0119-7 pmid: 29736016
[31] Zhang S W, Feng L C, Xing L T, Yang B, Gao X, Zhu X F, Zhang T Z, Zhou B L . New QTLs for lint percentage and boll weight mined in introgression lines from two feral landraces into Gossypium hirsutum acc TM-1. Plant Breed, 2016,135:90-101.
doi: 10.1111/pbr.12337
[32] Fang L, Wang Q, Hu Y, Jia Y H, Chen J D, Liu B L, Zhang Z Y, Guan X Y, Chen S Q, Zhou B L, Du X M . Genomic analyses in cotton identify signatures of selection and loci associated with fiber quality and yield traits. Nat Genet, 2017,49:1089-1098.
doi: 10.1038/ng.3887 pmid: 28581501
[33] Islam M S, Thyssen G N, Jenkins J N, Zeng L, Delhom C D, McCarty J C, Deng D D, Hinchliffe D J, Jones D C, Fang D D . A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton. BMC Genomics, 2016,17:903.
doi: 10.1186/s12864-016-3249-2
[34] Sun Z W, Wang X F, Liu Z W, Gu Q S, Zhang Y, Li Z K, Ke H F, Yang J, Wu J H, Wu L Q, Zhang G Y, Zhang C Y, Ma Z Y . Genome-wide association study discovered genetic variation and candidate genes of fibre quality traits in Gossypium hirsutum L. Plant Biotechnol J, 2017,15:982-996.
doi: 10.1111/pbi.12693 pmid: 28064470
[35] Liu Z H, Zhu L, Shi H Y, Chen Y, Zhang J M, Zheng Y, Li X B . Cotton GASL genes encoding putative gibberellin- regulated proteins are involved in response to GA signaling in fiber development. Mol Biol Rep, 2013,40:4561-4570.
doi: 10.1007/s11033-013-2543-1 pmid: 23645033
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