RESEARCH ARTICLE Open Access

Quantitative trait loci analysis of Verticilliumwilt resistance in interspecific backcrosspopulations of Gossypium hirsutum ×Gossypium barbadenseYuzhen Shi1, Baocai Zhang1, Aiying Liu1, Wentan Li1, Junwen Li1, Quanwei Lu1, Zhen Zhang1, Shaoqi Li1,Wankui Gong1, Haihong Shang1, Juwu Gong1, Tingting Chen1, Qun Ge1, Tao Wang1, Heqin Zhu1, Zhi Liu2

and Youlu Yuan1*

Abstract

Background: Verticillium wilt (VW) caused by Verticillium dahliae (Kleb) is one of the most destructive diseases ofcotton. The identification of highly resistant QTLs or genes in the whole cotton genome is quite important fordeveloping a VW-resistant variety and for further molecular design breeding.

Results: In the present study, BC1F1, BC1S1, and BC2F1 populations derived from an interspecific backcross betweenthe highly resistant line Hai1 (Gossypium barbadense L.) and the susceptible variety CCRI36 (G. hirsutum L.) as therecurrent parent were constructed. Quantitative trait loci (QTL) related to VW resistance were detected in the wholecotton genome using a high-density simple sequence repeat (SSR) genetic linkage map from the BC1F1 population,with 2292 loci covering 5115.16 centiMorgan (cM) of the cotton (AD) genome, and the data concerning VWresistance that were obtained from four dates of BC2F1 in the artificial disease nursery and one date of BC1S1 andBC2F1 in the field. A total of 48 QTLs for VW resistance were identified, and 37 of these QTLs had positive additiveeffects, which indicated that the G. barbadense alleles increased resistance to VW and decreased the disease index(DI) by about 2.2–10.7. These QTLs were located on 19 chromosomes, in which 33 in the A subgenome and 15QTLs in the D subgenome. The 6 QTLs were found to be stable. The 6 QTLs were consistent with those identifiedpreviously, and another 42 were new, unreported QTLs, of which 31 QTLs were from G. barbadense. By meta-analysis, 17 QTL hotspot regions were identified and 10 of them were new, unreported hotspot regions. 29 QTLs inthis paper were in 12 hotspot regions and were all from G. barbadense.

Conclusions: These stable or consensus QTL regions warrant further investigation to better understand thegenetics and molecular mechanisms underlying VW resistance. This study provides useful information for furthercomparative analysis and marker-assisted selection in the breeding of disease-resistant cotton. It may also lay animportant foundation for gene cloning and further molecular design breeding for the entire cotton genome.

Keywords: Cotton, Verticillium wilt (VW), Quantitative trait loci (QTL), Interspecific backcross population

* Correspondence: yylcri@126.com1State Key Laboratory of Cotton Biology, Key Laboratory of Biological andGenetic Breeding of Cotton, The Ministry of Agriculture, Institute of CottonResearch, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan,ChinaFull list of author information is available at the end of the article

© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Shi et al. BMC Genomics (2016) 17:877 DOI 10.1186/s12864-016-3128-x

BackgroundCotton is an important economic crop worldwide. Itprovides important natural fibers for the textile industry.Of the two most economically important tetraploid cul-tivated species, Gossypium hirsutum (Upland cotton),which has high yield and wide adaptability, makes upabout 95 % of the total cotton yield worldwide [1]. G.barbadense (sea-island cotton), however, is grown inonly limited areas because of its relatively low yield andlimited adaptability, despite its strong resistance toVerticillium disease and extra-long, fine, strong, fibers.Cultivated forms of both these species show very differ-ent traits regarding yield, fiber quality, disease resistance,environmental adaptation, and other traits [2].Verticillium wilt (VW) is one of the important diseases

of cotton (G. hirsutum L.) worldwide. It is caused byVerticillium dahliae (Kleb.), a soil-borne fungal patho-gen that has a broad range of hosts and moves amongthem using a variety of mechanisms. It has high patho-genicity and can survive for long periods [3]. Infectedplants usually exhibit symptoms of marginal chlorosis ornecrosis in leaves, discoloration of the stem vascularbundles, and even full defoliation and plant death. Se-vere infection results in significant reduction of fiberyield and quality [2, 4]. Worldwide, the disease was firstreported in Virginia in 1914 [5]. Today, it is found in al-most all cotton growing areas worldwide. This diseasebroke out in China in 1993, resulting in the infection ofapproximately 80 % of the cotton crop in the seriouslyinfected region of cotton in North China and lint yieldlosses of 100 million kg in the whole China in that year[6, 7]. Another VW outbreak occurred in major cotton-producing regions in China, including the Yellow Riverand the Northwest in 2002 and 2003. In 2010, the yieldloss caused by VW was 0.31 % of the total cotton yieldin the U.S. [8], and losses have reached as high as 3–5 %in New Mexico [4]. The VW has not been effectivelycontrolled mainly due to its biology characteristics, theindeterminacy of the genetic mechanism of resistance toVW and the lack of highly resistant commercial Uplandcotton varieties, except for some modern Acala cottoncultivars developed in California and New Mexico [4].Planting a resistant cultivar has long been considered

the most practical, economic, and effective means ofdecreasing losses from VW. However, sources of VW re-sistance in cotton are very limited and no source of her-itable immunity has been found in Upland cotton [4, 9].Many G. barbadense genotypes are known to carry highlevels of resistance to VW [4, 10, 11], but its resistancehas not been successfully transferred into commercialUpland cotton due to hybrid breakdown except forintrogressed breeding lines [4, 12, 13]. Using conven-tional breeding, breeders have made interspecific crossesbetween Upland cotton and sea-island cotton to improve

the VW resistance of Upland cotton for many years, butno breakthrough has been reported because of the nega-tive genetic correlation between lint yield and fiber qual-ity, between lint yield and disease resistance, as well aslinkage drag and hybrid breakdown [14]. This makes itchallenging for breeders to realize the synchronous im-provement of fiber quality, yield, and disease resistance.However, the development of molecular quantitativegenetics has made it possible to locate the quantitativetrait loci (QTL) for yield, fiber quality, and disease resist-ance, thus facilitating the use of marker-assisted selec-tion (MAS) for genetic improvement. With theassistance of tightly linked markers to VW resistance, itis possible to transfer the resistance genes from sea-island cotton to Upland cotton.In recent years, a great deal of progress has been made

in mapping VW resistance genes and QTLs in cotton.Many genetic linkage maps have been constructed, andQTLs have been identified for VW resistance in cottonfrom interspecific populations of G. hirsutum ×G.barbadense [2, 15–21] and from G. hirsutum intraspe-cific populations [22–27]. Some QTLs have also beendetected by association mapping using a natural popula-tion, chromosome segment introgression lines and mo-lecular mapping based on restriction-site associatedDNA (RAD) sequencing technology using a RIL popula-tion [17, 28, 29]. These provided some information forfurther study of the QTLs/genes of VW resistance. How-ever, most of genetic linkage maps used to identify QTLsfor VW resistance in all these studies offered no morethan 60 % coverage of the cotton genome. Although themap reported by Wang et al. covered 3745.9 centi-Morgan (cM), an estimated 74.92 % of the tetraploidcotton genome, there were only 430 marker loci on themap [18]. Constructing a high-density linkage map is ofgreat significance for identifying and studying the genesand QTLs of VW resistance.To introgress the good fiber quality and VW resistance

from G. barbadense into a commercial Upland cottonvariety, we have developed the advanced backcrossingpopulations with the commercial Upland cotton culti-vars (CCRI36) as the recipient parents, and sea-islandcotton (Hai1) as the donor parent [30–32], and devel-oped a high-density simple sequence repeat (SSR) gen-etic linkage map from a BC1F1 population of G.hirsutum ×G. barbadense, which comprised of 2292 lociand covered 5115.16 cM of the cotton AD genome withan average marker interval of 2.23 cM [33]. To the bestof our knowledge, no QTL for VW resistance were iden-tified using any map with more than 2000 SSR lociwhich covered almost the whole cotton AD genome anddata for VW resistance from the different the dates, gen-erations, or environments. In this study, a whole-genome screening strategy was used to map QTLs

Shi et al. BMC Genomics (2016) 17:877 Page 2 of 15

related to VW resistance using data from different popu-lations related to BC1F1, which is quite useful for furtherfine gene mapping, gene cloning, and marker assisted se-lection (MAS) in cotton and for further molecular de-sign breeding.

ResultsDifferences between the parents and phenotypicvariation in the populationsIn 2005, BC2F1 family lines and their parents were evalu-ated for VW resistance both in the artificial disease nur-sery and in the field, BC1S1 family lines and theirparents were also evaluated for VW resistance in thefield. The recurrent parent CCRI 36 was susceptible toVW disease, and the average disease index (DI) was30.6. Hai1 was highly resistant to VW disease with anaverage DI of 0.4. There was a significant difference inresistance to VW disease between the two parents. TheF1 was also highly resistant to VW disease with an aver-age DI of 4.3. The DI of BC2F1 family lines in the artifi-cial disease nursery and in the field and the DI of BC1S1family lines in field exhibited a continuous and normaldistribution consistent with multi-gene inheritance forVW resistance (Figs. 1 and 2). Transgressive segregationtowards to low DI value was observed (Fig. 1).

Construction of the genetic linkage mapThe high-density SSR genetic linkage map was devel-oped from a BC1F1 population of G. hirsutum ×G.barbadense [33]. Briefly, the map comprised 2292 lociand covered 5115.16 cM of the cotton AD genome withan average marker interval of 2.23 cM. The map wasused to detect QTL in the BC1S1 population in the field(BC1S1-FD), BC2F1 population in the field (BC2F1-FD),

and BC2F1 population in the artificial disease nursery(BC2F1-NY).

QTL mapping in BC2F1 population in the artificial diseasenurseryBased on composite interval mapping, a total of 28QTLs of VW resistance were detected in the BC2F1population during four different dates (June 23, July19, August 15, and August 25) in the artificial diseasenursery, with 5.48–16.66 % of the total phenotypicvariation explained. The 28 QTLs were located on 15chromosomes. Chromosome (C) 5 contained 7 QTLs,and C1 and C15 contained 3 QTLs each, C10, C11,and C26 contained 2 QTLs each, and C6, C9, C13,C14, C17, C19, C20, C21, and C22 contained 1 QTLeach. Of these, 19 QTLs had positive additive effects,which indicated that the G. barbadense alleles in-creased VW resistance and decreased the DI by about2.2–7.3 (Fig. 3, Table 1).

QTLs of VW resistance for June 23Six QTLs, qVW-9-1, qVW-10-1, qVW-10-2, qVW-13-1,qVW-14-3 and qVW-19-1, were identified in the BC2F1population in the artificial disease nursery and found on5 chromosomes, each explaining 5.71–10.16 % of thetotal phenotypic variation. All QTLs except qVW-9-1had positive additive effects, which indicated that theHai1 alleles increased VW resistance and decreased VWDI by 3.2–4.3.

QTLs of VW resistance for July 19Nine QTLs, qVW-1-2, qVW-1-3, qVW-5-1, qVW-5-2,qVW-5-3, qVW-5-4, qVW-15-4, qVW-17-1 and qVW-21-1, were detected in the BC2F1 population in the

Fig. 1 Frequency distribution of disease index (DI) in the BC2F1 population in the artificial disease nursery

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artificial disease nursery, each explaining 5.48–12.01 %of the total phenotypic variation. These were located on5 chromosomes, four QTLs were found on Chr5 alone.All QTLs except qVW-15-4 had positive additive effects,which indicated that the Hai1 alleles increased VW re-sistance and decreased VW DI by 2.2–3.4.

QTLs of VW resistance for August 15Eleven QTLs, qVW-1-1, qVW-5-2, qVW-5-3, qVW-5-4,qVW-5-5, qVW-6-1, qVW-11-1, qVW-11-2, qVW-15-3,qVW-26-1 and qVW-26-2, were identified in the BC2F1population in the artificial disease nursery, each explain-ing 6.92–16.66 % of the total phenotypic variation. TheQTLs were located on 6 chromosomes, four on Chr5.All QTLs except qVW-6-1, qVW-15-3, qVW-26-1 andqVW-26-2 had positive additive effects, which indicatedthat the Hai1 alleles increased VW resistance and de-creased VW DI by 5.0–7.3. In addition, qVW-C26-1 andqVW-C26-2 were both located on C26 and explained11.12 and 7.95 % of the phenotypic variation, respect-ively. The CCRI36 alleles increased VW resistance anddecreased VW DI by 5.0 and 5.9, respectively.

QTLs of VW resistance for August 25Five QTLs, including qVW-5-6, qVW-5-7, qVW-15-1,qVW-20-1 and qVW-22-1, were detected in the BC2F1population in the artificial disease nursery and locatedon 4 chromosomes, each explaining 6.93–9.50 % of thetotal phenotypic variation. Two QTLs (qVW-5-6 andqVW-5-7) had positive additive effects, and they werelocated on the same chromosome, C5. They explained9.22 and 7.09 % of the phenotypic variation, respectively.The Hai1 alleles increased VW resistance and decreasedVW DI by 5.8 and 5.1, respectively.

qVW-C5-2, qVW-C5-3 and qVW-C5-4 on C5 were de-tected in the two dates on July 19 and August 15, and werelocalized in the marker intervals PGML03048-DPL0063,DPL0063-DPL0724, and CGR6708a-MGHES06, respect-ively. qVW-C5-2 explained 9.76–11.74 % of the phenotypicvariation, and the G. barbadense allele decreased the DI byabout 3.0–6.0. qVW-C5-3 explained 9.8–13.52 % of thephenotypic variation, and the G. barbadense allele de-creased the DI by about 3.0–6.5. qVW-C5-4 explained12.01–16.66 % of the phenotypic variation, and the G.barbadense allele decreased the DI by about 3.2–7.3.

QTL mapping in BC2F1 and BC1S1 populations in the fieldBased on composite interval mapping, a total of 13QTLs associated with VW resistance, qVW-5-2, qVW-5-3, qVW-5-4, qVW-7-1, qVW-7-2, qVW-7-3, qVW-7-4,qVW-12-1, qVW-12-2, qVW-12-3, qVW-15-2, qVW-15-3 and qVW-26-3, were detected in the BC1S1 popula-tion on September 17, explaining 5.87–13.59 % of thetotal phenotypic variation. These 13 QTLs were locatedon C5, C7, C12, C15 and C26. C7 contained 4 QTLs, C5and C12 contained 3 QTLs each, C15 contained 2 QTLsand C26 contained 1 QTL. All QTLs except qVW–15-2,qVW-15-3, and qVW-26-3 had positive additive effects,which indicated that the G. barbadense allele decreasedthe DI by about 7.2–10.7 (Fig. 3, Table 1).A total of 16 QTLs for VW resistance, qVW-3-1,

qVW-3-2, qVW-3-3, qVW-3-4, qVW-3-5, qVW-3-6,qVW-5-1, qVW-5-2, qVW-5-3, qVW-5-4, qVW-5-5,qVW-8-1, qVW-8-2, qVW-9-2, qVW-14-1 and qVW-14-2, were detected in the BC2F1 population on Septem-ber 17, explaining 5.76–13.46 % of the total phenotypicvariation. The 16 QTLs were located on C3, C5, C8, C9and C14. C3 contained 6 QTLs, C5 contained 5 QTLs,C8 and C14 each contained 2 QTLs and C9 contained 1.

Fig. 2 Frequency distribution of disease index (DI) in the BC1S1 and BC2F1 populations in the field

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Fig. 3 Chromosomal locations of QTLs for Verticillium wilt (VW) resistance in the BC2F1-FD, BC1S1-FD, and BC2F1-NY populations derived from aninterspecific cross of G. hirsutum (CCRI36) × G. barbadense (Hai1)

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Table 1 QTLs of Verticillium wilt (VW) resistance detected during the five dates across two generations

QTL Gen. Date Env. C Position (cM) Nearest Marker Marker interval LOD Additive effect PV%

qVW-C1-1 BC2F1 8.15 DN C1 42.7 DPL0692 DPL0692-NAU3744b 3.5 5 7.88

qVW-C1-2 BC2F1 7.19 DN C1 89.5 CGR6870 BNL2921-CGR6870 4.2 3.4 10.43

qVW-C1-3 BC2F1 7.19 DN C1 141.6 PGML0280 NAU5163-CGR6803a 2.6 2.8 7.11

qVW-C3-1 BC2F1 9.17 FD C3 94.2 MUSB0087 MUSB0087-PGML03765 3.3 5.7 7.32

qVW-C3-2 BC2F1 9.17 FD C3 98 CER0028 NAU1286-DPL0232 4.3 6.5 9.57

qVW-C3-3 BC2F1 9.17 FD C3 101.3 DPL0232 DPL0232-PGML03195 3.3 6.2 8.76

qVW-C3-4 BC2F1 9.17 FD C3 105.3 HAU1022 TMB1898-DPL0224 5.6 7.2 11.33

qVW-C3-5 BC2F1 9.17 FD C3 109.6 CICR0034 CICR0034-NAU2297 4.2 6.7 9.94

qVW-C3-6 BC2F1 9.17 FD C3 113.8 HAU1396 NAU2297-DPL0321 3.9 6.1 8.16

qVW-C5-1 BC2F1 7.19 DN C5 30.5 CIR224b DPL0274a-PGML03048 3.3 2.7 8.1

BC2F1 9.17 FD C5 30.5 CIR224b 5.2 7 10.91

qVW-C5-2 BC1S1 9.17 FD C5 32.3 CIR102 PGML03048-DPL0063 6.2 10.7 13.59

BC2F1 9.17 FD C5 32.3 CIR102 5.9 7.5 12.31

BC2F1 7.19 DN C5 32.4 CIR102 4.1 3 9.76

BC2F1 8.15 DN C5 32.4 CIR102 4.7 6 11.74

qVW-C5-3 BC2F1 8.15 DN C5 38.2 HAU0746 DPL0063-DPL0724 5.5 6.5 13.52

BC1S1 9.17 FD C5 38.2 HAU0746 6 10.6 13.13

BC2F1 9.17 FD C5 38.2 HAU0746 6.5 7.9 13.46

BC2F1 7.19 DN C5 38.6 HAU0746 4.1 3 9.8

qVW-C5-4 BC1S1 9.17 FD C5 39.8 PGML02063 CGR6708a-MGHES06 4.8 9.5 10.83

BC2F1 7.19 DN C5 39.8 PGML02063 5.1 3.2 12.01

BC2F1 8.15 DN C5 39.8 PGML02063 6.9 7.3 16.66

BC2F1 9.17 FD C5 41.2 PGML02063 4.6 6.8 10.13

qVW-C5-5 BC2F1 8.15 DN C5 45 DPL0138 MGHES06-DPL0241 4.6 6.1 11.63

BC2F1 9.17 FD C5 45 DPL0138 3.6 5.8 7.72

qVW-C5-6 BC2F1 8.25 DN C5 155.8 HAU0215 DPL0908a-NAU3824a 3.3 5.8 9.22

qVW-C5-7 BC2F1 8.25 DN C5 168.6 CGR5925a COT010-NAU2296b 2.9 5.1 7.09

qVW-C6-1 BC2F1 8.15 DN C6 0.5 NAU5038 NAU5038-CGR5128b 2.9 −4.9 7.13

qVW-C7-1 BC1S1 9.17 FD C7 75.3 CGR6894b DPL0136-NAU1048 2.8 7.2 6.05

qVW-C7-2 BC1S1 9.17 FD C7 85 NAU2002 NAU1048-COT096a 3.5 7.9 7.38

qVW-C7-3 BC1S1 9.17 FD C7 88.1 CGR6381 COT096a-NAU1763 3.4 7.8 7.08

qVW-C7-4 BC1S1 9.17 FD C7 100.4 DC40253 NAU1483-DC40253 4 9.2 10.09

qVW-C8-1 BC2F1 9.17 FD C8 67.4 HAU3346a PGML01704-BNL3257 3 5.1 5.76

qVW-C8-2 BC2F1 9.17 FD C8 79.7 CER0152c CER0152c-NAU2086a 3.3 6.7 8.43

qVW-C9-1 BC2F1 6.23 DN C9 61.1 MUSB0009 DPL0783-Gh112 2.7 −3.5 6.86

qVW-C9-2 BC2F1 9.17 FD C9 117.1 STV177 HAU2730b-HAU0361 3.6 5.7 7.07

qVW-C10-1 BC2F1 6.23 DN C10 150.7 NAU2869 NAU2869-HAU0230a 2.8 3.8 8.09

qVW-C10-2 BC2F1 6.23 DN C10 161 CGR6818 NAU4910-CIR166 2.9 3.2 5.77

qVW-C11-1 BC2F1 8.15 DN C11 63.9 NAU5461b MUSS281-NAU5621a 5.5 6.7 13.83

qVW-C11-2 BC2F1 8.15 DN C11 70.6 NAU5461a NAU5621a-CICR0283 4.7 6.1 11.54

qVW-C12-1 BC1S1 9.17 FD C12 103.5 HAU0734 DPL01491-DPL0400 2.7 9.3 7.53

qVW-C12-2 BC1S1 9.17 FD C12 107.8 HAU0107 DPL0400-Gh188 3.7 8.9 7.75

qVW-C12-3 BC1S1 9.17 FD C12 109.9 NAU4889 Gh188-NAU3713 3.6 10.2 8.94

qVW-C13-1 BC2F1 6.23 DN C13 47.3 CICR0382 DPL0754-BNL2449 3.4 3.4 6.62

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All 16 QTLs had positive additive effects, which indi-cated that the G. barbadense allele decreased the DI byabout 5.1–7.9 (Fig. 3, Table 1).

Stability of QTLs over multiple generations, environmentsand datesA total of 48 QTLs of VW resistance were detected inthe BC2F1 and BC1S1 populations and the five dates.These were located on 19 chromosomes. C5 contained 7QTLs, C3 contained 6 QTLs, C7 and C15 each con-tained 4 QTLs, C1, C12, C14 and C26 each contained 3QTLs, C8, C9, C10 and C11 each contained 2 QTLs,and C6, C13, C17, C19, C20, C21 and C22 each con-tained 1 QTL. Of these, 37 QTLs (77.08 %) had positiveadditive effects, which indicated that the G. barbadenseallele decreased the DI (Fig. 3, Table 1).Of these 48 QTLs, 3 QTLs (qVW-C5-2, qVW-C5-3,

qVW-C5-4) were detected in two generations (BC2F1,BC1S1), in two environments (the field, the artificial dis-ease nursery) and in the three dates (July 19, August 15and September 17), explaining 9.76–16.66 % of thephenotypic variation. The Hai1 allele decreased the DIby approximately 3.0–10.7, increasing VW disease resist-ance. One QTL (qVW-C5-1) was simultaneously de-tected in both environments in the artificial diseasenursery and in the field for BC2F1, explaining 8.10–10.91 % of the phenotypic variation, and the Hai1 alleledecreased the DI by approximately 2.7–7.0. One QTL(qVW-C5-5) was also simultaneously detected in twoenvironments or dates on August 15 in the artificial dis-ease nursery and on September 17 in the field for BC2F1,

explaining 7.72–11.63 % of the phenotypic variation.The Hai1 allele decreased the DI by approximately 5.8–6.1 (Figs. 3 and 4, Table 1). One QTL (qVW-C15-3) wassimultaneously detected on September 17 in BC1S1 in thefield and in BC2F1 on August 15 in the artificial diseasenursery, explaining 6.05–6.92 % of the phenotypic vari-ation. And the CCRI36 allele decreased the DI by about4.8–7.1. A total of six QTLs were stably detected in differ-ent generations, environments, and/or different dates.These stable QTLs could be used for MAS breeding.

Meta-analysis of QTLsIn the Meta-analysis, a total of 17 QTL hotspot regionswere identified on 13 chromosomes of the consensusmap, including C3, C5, C7, C8, C9, C12, C14, C15, C17,C19, C20, C21 and C26 (Fig. 5, Table 2). 7 QTL hotspotregions (c5-VW-Hotspot-2, c7-VW-Hotspot-1, c7-VW-Hotspot-2, c8-VW-Hotspot-1, c19-VW-Hotspot-1, c21-VW-Hotspot-1 and c26-VW-Hotspot-1) were consistentwith those identified previously by Zhang et al. and Said etal. [13, 34] (Table 2), and the other ten were new, unre-ported hotspot regions. Two QTL hotspot regions wereon C5, C7, C9 and C19, respectively. Of 17 QTL hotspotregions, c3-VW-Hotspot-1, c5-VW-Hotspot-1, c8-VW-Hotspot-1 and c26-VW-Hotspot-1 had more QTLs.36 QTLs from this paper were distributed in 15 hot-

spot regions, 29 of them were in 12 hotspot regions andwere all from G. barbadense (Table 3). It showed thatQTL-rich regions on the map of CCRI36 × Hai1 BC1F1were consistent with the QTL hotspot regions (Table 3,Additional file 1). These consensus QTL regions (QTL-

Table 1 QTLs of Verticillium wilt (VW) resistance detected during the five dates across two generations (Continued)

qVW-C14-1 BC2F1 9.17 FD C14 81.6 C2-0079 NAU3499-CGR6550 4.4 6.4 8.7

qVW-C14-2 BC2F1 9.17 FD C14 88.9 PGML02953b CGR6550-CICR0377 2.9 5.5 6.43

qVW-C14-3 BC2F1 6.23 DN C14 184.6 NAU5465 SHIN-0659b-CICR0052 2.6 3.2 5.71

qVW-C15-1 BC2F1 8.25 DN C15 43.9 CGR5834 NAU3177-HAU3050a 3.8 −5.8 9.5

qVW-C15-2 BC1S1 9.17 FD C15 141.9 NAU0861 NAU3680-DPL0437 2.6 −7 5.87

qVW-C15-3 BC1S1 9.17 FD C15 152 TMB1664 COT059-PGML02824a 2.9 −7.1 6.05

BC2F1 8.15 DN C15 155.5 PGML02824b TMB1664-CGR6308b 2.9 −4.8 6.92

qVW-C15-4 BC2F1 7.19 DN C15 161.2 CGR5056a PGML02824a-CER0013 3.4 −2.9 9.02

qVW-C17-1 BC2F1 7.19 DN C17 5.3 HAU0800a CGR6905-DC40292 2.6 2.2 5.48

qVW-C19-1 BC2F1 6.23 DN C19 185.6 HAU1385b DPL0192-NAU5489 4.5 4.3 10.16

qVW-C20-1 BC2F1 8.25 DN C20 22.2 CICR0254 CIR094-NAU4071 3.6 −5.6 9.01

qVW-C21-1 BC2F1 7.19 DN C21 111.3 Gh074a CICR0046-DC40250 4.2 3.1 9.99

qVW-C22-1 BC2F1 8.25 DN C22 149.7 CER0139b TMB0206-CICR0438 2.8 −5 6.93

qVW-C26-1 BC2F1 8.15 DN C26 164.5 DPL0915 PGML04562-DPL0915 3.9 −5.9 11.12

qVW-C26-2 BC2F1 8.15 DN C26 169.4 NAU3905 NAU4914-PGML04182 3.5 −5 7.95

qVW-C26-3 BC1S1 9.17 FD C26 172.4 CGR6759 DPL0890-PGML02118 3 −7.4 6.48

Note: 8.15 means that the DI was investigated at August 15; DN the artificial disease nursery, FD the field, Gen generation, Env environment, C chromosome, PV%phenotypic variation explained; positive additive effect indicates that the locus derived from Hai1 decreased the value of DI

Shi et al. BMC Genomics (2016) 17:877 Page 7 of 15

rich regions and QTL hotspot regions) could be worthyof further research and used for MAS.

DiscussionMap used to identify QTLs for Verticillium wilt (VW)resistanceTo identify QTL associated with VW resistance from G.barbadense, some genetic maps were developed from

crosses between G. hirsutum and G. barbadense or G.hirsutum and an introgressed line. For example, Zhanget al. detected QTLs for VW resistance based on a 392SSR polymorphic loci linkage map covering 2895 cM orabout 57.90 % of the cotton genome using the BIL popu-lation of SG 747 × Giza 75 [13]. Fang et al. constructed a292-marker genetic linkage map for the BIL populationof SG 747 × Pima S-7 [15]. It covered 1226 cM or about

Fig. 4 Graphic display of QTLs related to VW resistance within the 26.6 cM–48.4 cM interval on C5 using WinQTLCart 2.0 based on theinterspecific backcross populations of CCRI36 × Hai1

mQTL-C3

0,00 CICR07641,86 NAU09972,70 HAU08832,86 CIR3323,57 MUSS1624,81 CIR1336,11 HAU11927,68 HAU21278,58 cgr59969,88 At1811,16 MUSS49212,41 BNL024413,63 DPL019514,86 Gate4AE0516,16 pVNC02117,39 14-6599R18,68 Gh12919,87 TMB039521,08 E6M5_16122,33 BNL344123,62 JESPR30324,82 CICR003426,29 NAU229727,39 HAU019529,34 DPL029133,60 HAU340333,74 A174835,64 NAU610436,66 PGML0095037,79 UCcot10105_15139,85 NAU301640,69 NAU283642,87 pAR47643,17 cgr572944,00 PGML0330744,74 HAU029245,95 cgr562047,13 Y20148,53 CGR562049,61 Gate4DC1151,30 NAU3083

55,21 Gate1AF02

57,14 MUCS547

62,62 Unig25G0762,62 pAR01_56

mQTL-C5

0,00 DPL00147,78 CIR3769,80 PGML0431715,10 PGML0435018,70 COT13025,60 DPL024728,78 CIR06729,07 pAR93130,50 CIR22432,91 CIR10233,96 A113536,63 TMB1296

38,82 DPL0022

40,54 NAU1015

42,62 JESPR20444,82 DC3004847,33 DC2016349,34 Gh21151,77 HAU140453,67 DPL090856,28 E2M7_9658,05 E6M1_28860,12 BNL399562,30 E3M5_31264,52 CGR592567,09 E6M4_19269,71 NAU229671,61 A169173,88 E4M5_40075,89 NAU313878,40 JESPR06580,66 CIR23581,93 E31M53-M116.384,19 BNL403087,45 NAU115188,52 HAU149690,71 PGML0093993,51 TMB077095,61 SWU125098,71 E31M2-M87.8101,01 CGR5553

108,71 CIR328109,11 NAU2948

mQTL-C7

0,00 SWU04735,30 DPL0364b8,60 CGR511919,94 NAU93322,70 PGML0419829,20 NAU403030,24 UCcg11240_81630,58 PVNC127

32,75 SHIN-1585

34,94 Unig06B10

36,97 pAR01_25

39,09 Unig23C07

41,92 CIR320

44,20 SHIN-0376a

46,02 CGR651248,15 NAU093350,52 G118553,12 BNL153154,87 COT048b

57,29 DPL013659,35 pAR07A0261,63 CICR037564,72 NAU200266,26 A118269,10 UCcg10921_20270,68 HAU148373,45 JESPR06575,32 Gate1AH0477,63 BNL058079,86 Gate2DD0282,07 UCcg11001_18584,32 CGR606186,50 CICR028788,76 me3em5-21590,98 E2M2_22593,25 MUSB044195,57 pAR19997,93 Unig26C04100,39 Gate1AA05102,44 Unig25H02104,57 CMS37106,96 pAR057109,78 PGML03114112,98 PGML01916

mQTL-C8

0,00 NAU33244,04 CIR2445,60 HAU18996,70 DPL074911,04 G111413,05 A141213,90 SHIN-015315,69 E4M7_16116,20 HAU178217,44 HAU118119,02 NAU1017

21,96 BNL355622,86 E3M6_14924,37 STV02826,26 CGR514527,98 PGML0170430,24 E8M2_20431,84 CGR552133,78 E1M5_8535,27 E8M6_22037,27 E1M5_16740,27 E2M7_17041,27 E2M2_34045,27 CG2447,27 pVNC149

53,27 CG0453,27 pAR95057,27 JESPR230

67,27 CIR34367,27 A165868,27 BNL164670,27 G110174,27 E2M6_159

89,27 G1276

mQTL-C9

0,00 BNL17078,00 E4M5_14011,00 E5M7_29013,00 A173714,00 DPL023816,00 E41M4-M401.519,10 NAU546822,48 NAU353826,51 E7M4_19229,07 NAU641832,06 NAU310136,77 E6M8_26938,74 BNL116242,28 CG06a45,03 E3M5_24048,79 NAU315951,54 E1M7_17055,02 MUCS57859,05 E1M4-M128.561,81 MUSB104064,39 JESPR27468,32 E43M52-M72.871,07 E1M4-M197.575,57 HAU281078,58 BNL377982,04 BNL167284,30 CICR033487,80 MUSS54790,57 HAU036195,69 NAU080597,53 E3M1_450102,34 HAU3218104,20 MUSS316106,83 Gh495109,97 A1471113,38 MUCS426116,63 NAU0882119,87 BNL1414123,24 MUSS083126,35 MGHES46129,74 NAU1046133,95 NAU0864137,63 DPL0514144,15 PXP3_7147,51 NAU1193149,15 CG21155,15 At60

162,63 DPLO524

mQTL-C12

0,00 CM05012,60 TMB079913,90 NAU525214,96 CIR04215,00 NAU356115,60 C2-011116,70 NAU386217,96 JESPR30020,20 HAU312720,96 CIR27221,82 pAR03_42

22,76 DPL0443

23,87 Gh188

25,33 pAR04_13

26,28 BNL1679

27,50 CICR0393

28,75 E1M6_16229,82 NAU088431,15 E5M2_18532,28 E43M3-M139.233,45 E2M6_13834,62 BNL359936,62 JESPR27037,62 E7M5_27038,62 BNL262139,62 E43M4-M193.240,62 E42M2-M309.2

44,62 BNL3261

47,62 MUSB1117

51,62 E4M5_500

59,62 E6M5_103

mQTL-C14

0,00 NAU22650,00 NAU08952,80 DPL05106,43 CGR55446,80 BNL08348,90 pAR4928,90 G11249,67 BNL023610,03 Coau3L1114,83 CGR566817,29 pAR17518,96 TMB083620,15 STV09720,53 PGML0354620,93 DPL091923,43 HAU307124,63 NAU373324,72 NAU320924,99 P05_06

25,88 CIR381

27,18 Y128227,54 HAU3236

28,34 STV030

29,25 CIR030

30,05 HAU1527

30,85 E43M54-M226.6

31,71 JESPR16532,56 LXP4333,39 Gate3BF0134,27 HAU016735,15 E1M54-M195.236,14 TMJ09-27036,93 E1M2-M74.238,25 BNL353338,46 NAU631639,35 BNL401740,30 HAU121942,31 NAU2173

mQTL-C15

0,00 NAU40730,96 NAU04581,29 NAU31022,42 HAU24893,66 MGHES435,20 TME03-1756,65 HAU10588,07 pAR9359,70 NAU241911,40 E31M55-M109.012,65 E8M3_13214,12 Gate1AH0915,92 TMB028317,64 TMB118118,68 TMB122420,53 pAR09921,94 TME000323,31 NAU517225,21 HAU142726,30 Gh35028,16 HAU249029,40 HAU027130,78 NAU361533,46 NAU662435,15 DOW08935,68 NAU298536,85 JESPR02438,69 TMB037539,88 PGML0270341,35 A110942,95 BNL292044,73 TMF12-19546,16 Y129547,57 CIR30749,05 TMB149250,87 DPL054252,04 NAU635153,51 CMS2155,53 DPL034656,47 BNL145458,34 P02_5859,56 MUSS08561,05 E7M5_12162,64 Gh56564,04 MUCS41065,59 NAU149568,32 MUCS15270,84 MUSS563

75,59 NAU2440

mQTL-C17

0,00 MUSB00739,39 NAU080510,97 CICR044712,22 MGHES1712,23 CLU155813,72 PGML0312614,29 HAU080015,11 CLU416516,66 CLU55418,63 DC4029218,95 PGML0230819,90 TMB126821,74 DPL024522,19 CIR37523,63 NAU102824,29 CIR25125,44 HAU3318

26,84 NAU276127,81 Y1285

29,02 E7M1_25230,21 E3M6_23331,27 MUSS114

32,37 E6M15-250

33,53 NAU635634,69 JESPR10135,98 DPL020037,12 MUSS07338,92 NAU663439,89 CLU414041,40 A158341,82 NAU0855

49,03 Coau2M03

53,31 pGH457

56,34 Gafb11P0456,34 pAR01_5657,28 G107158,11 HAU0119 mQTL-C19

0,00 CICR08511,40 CIR4154,10 HAU01125,76 NAU365611,40 PGML0201413,40 E4M3_27217,30 NAU340521,70 CGR615125,60 DPL014029,64 PGML0435033,17 NAU289438,18 HAU306940,51 NAU488444,34 CGR581450,39 NAU334353,47 COT03756,98 HAU021660,33 CGR551064,86 Gh22969,09 DPL044474,32 BNL106476,24 BNL302980,15 CICR061686,20 JESPR23090,34 NAU527393,78 DPL021096,52 CGR6128100,30 HAU2616103,92 CICR0333108,31 DPL0040111,75 DPL0143118,38 NAU2874124,64 At47125,27 NAU5489127,93 DPL0174132,52 CIR168137,40 Gh354140,46 A1432146,33 E5M5_280148,02 DPL0908152,41 PGML03762155,54 NAU6466160,38 Gh447163,72 BNL3535167,58 BNL3347174,58 pAR03_41175,58 MUSS138179,38 HAU1785183,48 PGML01289188,58 E3M4_164191,58 E3M3_420195,58 CIR344199,58 E43M3-M287.5203,72 NAU3095212,88 DC40425214,68 BNL3089216,28 HAU1400 mQTL-C20

0,00 NAU04531,68 A12141,78 CGR51064,98 CMS216,45 DOW0597,68 HAU105811,00 TMB099913,01 A175815,86 Gate1DG0416,70 pGH48619,09 Gate4CA0521,39 NAU254324,22 NAU535925,91 NAU222528,86 HAU310130,73 NAU329732,90 NAU106635,64 PGML0312437,57 HAU270041,26 BNL257042,22 E1M6-38044,60 Gate3DD0147,09 TMB082349,38 MUSS14351,68 MUSS07053,68 NAU346456,42 NAU646559,21 DOW06161,58 JESPR16763,08 A168265,92 BNL125367,55 CIR06369,96 TMB088972,33 Gh56474,48 BNL367077,30 E1M51-M258.079,34 TMB183181,59 MUSS34783,93 DPL022586,06 NAU340488,75 NAU621590,69 DPL002692,99 NAU128095,54 G121898,25 NAU3137101,05 MUSS271102,27 NAU2888105,29 NAU4881107,08 NAU6179109,38 DPL0350111,78 Gh277114,32 HAU2543116,17 HAU1267118,96 E4M3_108120,81 BNL2553124,34 E3M2_174126,21 E3M2_172 mQTL-C21

0,00 DPL032011,30 MUSS53211,80 NAU486513,20 CICR018714,26 NAU312714,29 CGR511315,31 NAU337716,83 CGR574718,49 CICR071719,39 HAU101820,82 CGR509721,58 NAU400322,76 E1M6_44023,98 DPL0582

25,12 P01_42

26,40 Unig06C04

27,74 E6M5-260

28,90 NAU3374

30,19 NAU341531,37 NAU265332,56 pAR16333,80 CG2235,27 BNL013736,81 pAR10E1037,53 NAU138638,76 NAU201639,95 CGR559741,18 A140042,41 Y4020-24543,66 NAU643144,96 HAU179446,20 E31M7-M311.347,74 CER015348,73 HAU259249,94 TMH05-45051,15 DPL090454,21 CGR540054,27 BNL3402

58,77 HAU128359,14 HAU180959,27 CICR028260,34 DC40316

67,37 MUSS246

mQTL-C26

0,00 NAU11004,50 HAU18454,70 NAU29208,30 NAU4925

13,20 DC4008013,50 CICR032313,80 HAU194216,10 NAU409020,48 CIR02721,18 MUSB026423,50 DPL024328,00 DPL056929,60 DPL088831,40 PGML0081133,20 NAU235635,32 DPL081737,85 BNL351040,34 NAU312742,59 DPL019045,07 DPL057347,38 E4M5_6949,85 CICR087652,81 NAU270154,52 pAR80757,45 E3M4-M91.659,46 CLU75961,76 CG0364,16 CIR29166,55 CLU87769,23 Unig23G0871,53 pAR04_1473,78 CGR675976,32 Unig25D1178,96 Gate4DD0681,38 G103383,49 PGML0460485,82 NAU309388,68 Gate3DE0190,80 G104593,20 HAU008795,59 DPL045199,90 CIR122100,52 DPL0917102,84 Unig28D06105,17 E2M5_74107,74 Gate4AC11110,42 HAU0908113,02 CGR5152115,59 CLU1257120,06 UCcg11329_228120,86 TMB1648

131,15 HAU0751

Fig. 5 QTLs and QTL hotspots for Verticillium wilt (VW) resistance on the consensus map by a meta-analysis

Shi et al. BMC Genomics (2016) 17:877 Page 8 of 15

27 % of the cotton genome. Yang et al. constructed twogenetic linkage maps [19]. One of these included 35 link-age groups with an average distance between twomarkers of 8.7 cM with 219 SSR loci. They covered1772.5 cM or approximately 31.93 % of the tetraploidcotton genome from BC1 of Hai 7124 × Junmian 1. An-other genetic linkage map with 420 genome-wide lociusing F2 of Hai 7124 × Junmian 1, with an average dis-tance of 7.3 cM per marker covered 2726.9 cM or ap-proximately 49.10 % of the tetraploid cotton genome.Wang et al. constructed a genetic linkage map with 430marker loci using F2 population of XinLuZao1 ×Hai7124, with an average distance of 8.71 cM permarker and covered 3745.9 cM, which is an estimated74.92 % of the total recombination length of the tetra-ploid cotton genome [18]. Bolek et al. constructed elevenlinkage groups using an F2 population derived from theinterspecific cross of Pima S-7 and Acala 44, consistingof 35 markers and spanning 531 cM (approximately10.62 % of the tetraploid cotton genome) with an aver-age distance of 15.17 cM [2]. Gao et al. constructed agenetic linkage map with 99 marker loci using an F2population of Handan208 × Pima90 [20]. It had an aver-age distance of 18.61 cM per marker and covered1842.8 cM or approximately 36.8 % of the tetraploid cot-ton genome. Fang et al. constructed a genetic linkagemap with 882 marker loci using the RIL population ofTM-1 × NM24016 [16]. It had an average distance of7.06 cM per marker and covered 2267 cM, which is anestimated 55.7 % of the total recombination length ofthe tetraploid cotton genome. NM24016 is an inbred

Upland cotton line with considerable but stable intro-gression from several G. barbadense lines. Ning et al.constructed a genetic linkage map with 279 marker lociusing a RIL population of Prema × 86–1 in which Premawas an introgressed line from G. thurberi and G. barba-dense [23]. This map covered 1576.25 cM, which is anestimated 35.42 % of the total recombination length ofthe tetraploid cotton genome. Using the same popula-tion, Wang et al. constructed a molecular map based onrestriction-site associated DNA (RAD) sequencing tech-nology, covering 3499.69 cM, which is an estimated69.99 % of the total recombination length of the tetra-ploid cotton genome [29].In addition, some genetic maps have also been devel-

oped using intraspecific populations of G. hirsutum toidentify QTL for VW resistance. Zhang et al. con-structed a genetic linkage map with 141 marker lociusing an F2 population of LHB22 × JM11 [22]. It had anaverage distance of 8.11 cM per marker and covered1143.1 cM, which is an estimated 22.86 % of the tetra-ploid cotton genome. Jiang et al. constructed a geneticlinkage map using F2 segregating population of 60182 ×Junmian 1, with 139 loci, covering 1165 cM [24]. It hadan average distance of 8.38 cM between two markers, or25.89 % of the length of the cotton genome. Ge et al.constructed a genetic linkage map with 122 marker lociusing an F2 population of Chang96 × Junmian 1 [25]. Ithad 33 linkages and covered 1172.7 cM or approxi-mately 23.5 % of the tetraploid cotton genome. Wang etal. constructed a genetic linkage map with 10 markerloci using F2 population of Lumianyan22 × Luyuan343

Table 2 QTL hotspots identified for Verticillium wilt (VW) resistance on the consensus map by meta-analysis

Hotspot name C Position (cM) No. of QTLs No. of QTLs in this paper Reported previously

c3-VW-Hotspot-1 C3 16–28 cM 7 6

c5-VW-Hotspot-1 C5 28–43 cM 7 5

c5-VW-Hotspot-2 C5 47–68 cM 5 2 Zhang et al. 2015 [13] and Said et al. 2015 [34]

c7-VW-Hotspot-1 C7 43–59 cM 4 1 Zhang et al. 2015 [13]

c7-VW-Hotspot-2 C7 64–85 cM 5 3 Zhang et al. 2015 [13]

c8-VW-Hotspot-1 C8 17–34 cM 8 2 Zhang et al. 2015 [13]

c9-VW-Hotspot-1 C9 55–85 cM 6 1

c9-VW-Hotspot-2 C9 124–147 cM 5 0

c12-VW-Hotspot-1 C12 17–26 cM 4 3

c14-VW-Hotspot-1 C14 26–43 cM 5 3

c15-VW-Hotspot-1 C15 42–63 cM 6 3

c17-VW-Hotspot-1 C17 11–36 cM 4 1

c19-VW-Hotspot-1 C19 1–26 cM 5 0 Zhang et al. 2015 [13]

c19-VW-Hotspot-2 C19 120–132 cM 4 1

c20-VW-Hotspot-1 C20 1–26 cM 4 1

c21-VW-Hotspot-1 C21 30–44 cM 6 1 Zhang et al. 2015 [13]

c26-VW-Hotspot-1 C26 54–79 cM 9 3 Zhang et al. 2015 [13]

Shi et al. BMC Genomics (2016) 17:877 Page 9 of 15

[26]. It had three linkages and covered 108.9 cM. Yanget al. constructed a genetic linkage map with 115 markerloci using an RIL population of 5026 × Li 8 [27]. It had20 linkage groups and covered 560.1 cM or approxi-mately 11.2 % of the tetraploid cotton genome.Only 1–18 QTLs for VW resistance were detected

using these maps in previous reports. In the previous re-ports, most of these linkage maps used to identify QTLsassociated with VW resistance had no more than 2000SSR markers and covered less than 60 % of the cottongenome [2, 15, 16, 19, 22–24]. It is difficult to identifymore QTLs for VW resistance from G. barbadense usingthe limited number of markers and low coverage of thewhole cotton genome.In this study, the genetic map comprised 2292 SSR

marker loci and covered 5115.16 cM of the cotton gen-ome [33]. A total of 48 QTLs for VW resistance weredetected and distributed on 19 chromosomes. Thisshowed that more QTLs for VW were found and locatedin more chromosomes and were mapped to a narrowerinterval with tightly linked markers using our map thanmaps of the traits reported in previous papers.

Distribution of QTLs through the whole genomeQTL clusters of different fiber quality and disease resistancehave also been observed in previous studies [1, 35–41]. Thecurrent results showed some QTL-rich regions on C3, C5,C7, C12, C15 and C26 for VW resistance. Six QTLs weredetected within a C3 region (93–114 cM) betweenMUSB0087 and DPL0321. A C5 region (27–47 cM) be-tween DPL0274a and DPL0241 harbored 5 QTLs and a C7region (75–100 cM) between DPL0136 and DC40253 car-ried 4 QTLs. Three QTLs each were found within a specificrange on C12 (93–112 cM) between DPL01491 andNAU3713, within a specific range on C15 (141–165 cM)between NAU3680 and CER0013, and within a specific

Table 3 QTLs identified using interspecific backcrosspopulations on the map of CCRI36 × Hai1 BC1F1 and thecorresponding hotspots

On the map of CCRI36× Hai1 BC1F1

On the consensus map

QTL-rich regions QTL Direction Hotspot nameand range

qVW-C1-1 Hai1

qVW-C1-2 Hai1

qVW-C1-3 Hai1

C3-VW-QTL-rich-1: 93–114 cM

qVW-C3-1 Hai1 c3-VW-Hotspot-1: 16–28 cM

qVW-C3-2 Hai1

qVW-C3-3 Hai1

qVW-C3-4 Hai1

qVW-C3-5 Hai1

qVW-C3-6 Hai1

C5-VW-QTL-rich-1: 27–47 cM

qVW-C5-1 Hai1 c5-VW-Hotspot-1: 28–43 cM

qVW-C5-2 Hai1

qVW-C5-3 Hai1

qVW-C5-4 Hai1

qVW-C5-5 Hai1

qVW-C5-6 Hai1 c5-VW-Hotspot-2: 47–68 cM

qVW-C5-7 Hai1

qVW-C6-1 CCRI36

C7-VW-QTL-rich-1: 75–100 cM

qVW-C7-1 Hai1 c7-VW-Hotspot-1: 43–59 cM

qVW-C7-2 Hai1 c7-VW-Hotspot-2: 64–85 cM

qVW-C7-3 Hai1

qVW-C7-4 Hai1

qVW-C8-1 Hai1 c8-VW-Hotspot-1: 17–34 cM

qVW-C8-2 Hai1

qVW-C9-1 CCRI36

qVW-C9-2 Hai1 c9-VW-Hotspot-1: 55–85 cM

qVW-C10-1 Hai1

qVW-C10-2 Hai1

qVW-C11-1 Hai1

qVW-C11-2 Hai1

C12-VW-QTL-rich-1: 93–112 cM

qVW-C12-1 Hai1 c12-VW-Hotspot-2: 17–26 cM

qVW-C12-2 Hai1

qVW-C12-3 Hai1

qVW-C13-1 Hai1

qVW-C14-1 Hai1 c14-VW-Hotspot-1: 26–43 cM

qVW-C14-2 Hai1

qVW-C14-3 Hai1

qVW-C15-1 CCRI36

C15-VW-QTL-rich-1: 141–165 cM

qVW-C15-2 CCRI36 c15-VW-Hotspot-1: 42–63 cM

qVW-C15-3 CCRI36

Table 3 QTLs identified using interspecific backcrosspopulations on the map of CCRI36 × Hai1 BC1F1 and thecorresponding hotspots (Continued)

qVW-C15-4 CCRI36

qVW-C17-1 Hai1 c17-VW-Hotspot-1: 11–36 cM

qVW-C19-1 Hai1 c19-VW-Hotspot-2: 120–132 cM

qVW-C20-1 CCRI36 c20-VW-Hotspot-1: 1–26 cM

qVW-C21-1 Hai1 c21-VW-Hotspot-1: 30–44 cM

qVW-C22-1 CCRI36

C26-VW-QTL-rich-1: 158–177 cM

qVW-C26-1 CCRI36 c26-VW-Hotspot-1: 54–79 cM

qVW-C26-2 CCRI36

qVW-C26-3 CCRI36

Shi et al. BMC Genomics (2016) 17:877 Page 10 of 15

range on C26 (158–177 cM) between PGML04562 andPGML02118 (Table 1, 3, Fig. 3). Importantly, the 5 QTLsfor VW resistance that clustered on C5 were stably de-tected in different generations, different environments and/or different dates.In this paper, a total of 48 QTLs for VW resistance

were detected in BC1S1 and BC2F1 populations using thehigh-density linkage map and they were distributed on19 chromosomes. Here, 33 (68.75 %) of them were lo-cated in the A subgenome, involving 11 chromosomes(C1, C3, C5, C6, C7, C8, C9, C10, C11, C12 and C13),and 15 QTLs were located on the D subgenome, involv-ing 8 chromosomes (C14, C15, C17, C19, C20, C21, C22and C26). This indicated that the A subgenome har-bored more QTLs or genes for VW resistance than theD subgenome. This was consistent with results reportedby Yang et al. [19], Ning et al. [23], and Bolek et al. [2].However, they are not consistent with the idea that the Dsubgenome makes a greater contribution to genetic con-trol of resistance traits than the A subgenome does [42,43]. This could be relevant to the conclusion that moreQTLs cluster on the A subgenome in this study. It may bebecause different materials were used in different studies.

QTLs for Verticillium wilt (VW) resistance from G.barbadenseIn this paper, a total of 48 QTLs for VW resistance weredetected in two generations (BC2F1, BC1S1) using ahigh-density linkage map. Of these, 37 (77.08 %) QTLshad positive additive effects, which indicated that the G.barbadense allele increased VW resistance and de-creased the DI by about 2.2–10.7. Six QTLs were stablydetected in two different generations and different envi-ronments and dates. Of these, 5 QTLs clustered on C5and 1 was located on C15.The six QTLs detected were found to be on the same

chromosomes or subgenomes reported in previous studies,and they had shared SSR markers [17, 19, 21–23]. qVW-C7-1 located on C7 for VW resistance was the same asYang’s qVL-A7-1 F2 [19], based on shared markers ofNAU1048. qVW-C19-1 may be the same as qVL-D5-1BC1S2592 in Yang et al. [19]. These were linked to thecommon marker BNL1878. qVW-C5-2 was same as QTL(qVW-A5-1) reported by Ning et al. with the linked com-mon marker DC20067 [23]. The qVW-C21-1 here detectedfor VW resistance may be the same as the qVW-c21-1 re-ported in Zhang et al. with the linked common markersHAU0423 and CGR5602 [22]. qVW-C9-2 was assigned tothe same chromosome region as the qFD1711-11-4.01 re-ported by Wu et al. with the linked common markerBNL3031 [21]. qVW-C3-5 may be the same as qRV991-A3-1 in Wang et al. [17]. These were linked to the commonmarker NAU3479. We could not correlate the other QTLsfor VW resistance to those found in other studies due to

the lack of common markers, although some QTLs wereon the same chromosomes [15, 18, 20, 22, 23, 26, 27, 29,36]. The more frequently informative molecular markersare used in the cotton community, the greater the likeli-hood that QTL conditioning VW resistance among variouscotton germplasm lines could be tagged. In this way, theother 42 QTLs for VW resistance could be considerednewly identified by this map.In summary, 6 stable QTLs (qVW-C5-1, qVW-C5-2,

qVW-C5-3, qVW-C5-4, qVW-C5-5, and qVW-C15-3)were detected in two or more populations or dates in thismap and 6 consensus QTLs (qVW-C7-1, qVW-C19-1,qVW-C5-2, qVW-C21-1, qVW-C9-2, qVW-C3-5) werealso reported in the previous studies. These 11 stable orconsensus QTLs (qVW-C5-1, qVW-C5-2, qVW-C5-3,qVW-C5-4, qVW-C5-5, qVW-C15-3, qVW-C7-1, qVW-C19-1, qVW-C21-1, qVW-C9-2, qVW-C3-5) could be usedfor MAS. Among 48 QTLs, there were 42 new unreportedQTLs, of which 31 QTLs were from G. barbadense.By meta-analysis of QTLs, 17 QTL hotspot regions

were identified on 13 chromosomes of the consensusmap (Fig. 5, Table 2). Of them, 7 QTL hotspot regionswere consistent with those identified previously byZhang et al. and Said et al. [13, 34] (Table 2) and another10 were new, unreported hotspot regions. 36 (75 %)QTLs from this paper were distributed in 15 hotspot re-gions, of which 29 QTLs were in 12 hotspot regions andwere all from G. barbadense (Table 3). All QTL-rich re-gions on the map of CCRI36 × Hai1 BC1F1 were consist-ent with the QTL hotspot regions of the consensus map(Table 3, Additional file 1). These consensus QTL re-gions (QTL-rich regions or QTL hotspot regions) couldbe worthy of further research and used for MAS.

Further application of QTLs for Verticillium wilt (VW)resistanceChromosome segment substitution lines (CSSLs) withthe two commercial Upland cotton cultivars (CCRI36and CCRI45) were developed as the recipient parents tointrogress genes and QTLs associated with good fiberquality and VW resistance from G. barbadense into acommercial Upland cotton variety, G. barbadense (Hai1)served as a donor parent. The fiber yield and qualitytraits of these CSSLs have been evaluated in previousworks [30–32, 44–46]. VW resistance in these CSSLs isbeing evaluated. The minor difference between CSSLsand the recurrent parent lies in the donor chromosomesegment from G. barbadense in G. hirsutum geneticbackground, reducing the interference of the geneticbackground. In this way, CSSLs are an ideal material forgenetic studies on quantitative traits. The present studyprovides molecular information for fine gene mapping,gene cloning, gene pyramiding, and marker-assistedbreeding for improving VW resistance and lays a solid

Shi et al. BMC Genomics (2016) 17:877 Page 11 of 15

foundation for further molecular design breeding through-out the cotton genome.

ConclusionsIn the present study, a high-density SSR genetic linkagemap covering the whole cotton genome and data associ-ated with VW resistance from different dates in popula-tions of different generations in the field and in theartificial disease nursery were used to identify QTLs asso-ciated with VW resistance and never-before-reportedQTLs were detected. Here, 48 VW resistance QTLs weremapped based on a 5115.16 cM linkage map with 2292SSR marker loci. This work provides useful informationfor further comparative analysis and improving under-standing of the genetic basis of VW resistance in cotton.Here, six QTLs were found to be stable, of which 5 QTLsclustered on C5 and 1 on C15. In this paper, six QTLswere the same or similar to previously reported QTLs and42 QTLs were new. Of these 42, 31 QTLs were from G.barbadense. 17 QTL hotspot regions for VW resistancewere identified and 10 of them were new, unreported hot-spot regions. 29 QTLs in 12 hotspot regions were all fromG. barbadense. These stable and consensus QTLs provideimportant molecular information for MAS in Upland cot-ton breeding aimed at improving the resistance to VWand may lay a better foundation for gene cloning and fur-ther study.

MethodsPlant materialsThe mapping population with 135 BC1F1 plants was de-rived from an interspecific cross of G. hirsutum(CCRI36) ×G. barbadense (Hai1), in which CCRI36 is asusceptible cultivar (G. hirsutum L.) and Hai1 is a highlyresistant line (G. barbadense L.) with super fiber qualityand the dominant glandless gene [33, 47].The CCRI36× Hai1 F1 was made in Henan Province

during the summer of 2003 and F1 plants, which served asthe male parent, were backcrossed with the recurrent par-ent CCRI36 in Hainan Province. BC1F1 seeds were har-vested during the spring of 2003. In 2004, the glandedplants in the BC1F1 population were pulled out at theseedling stage, and BC1F1 plants, which served as the maleparent, were backcrossed with CCRI36, and the hybridseeds originating from the same BC1F1 plants were har-vested together (BC2F1 seeds were obtained). BC1F1 plantswere self-pollinated and BC1S1 seeds were harvested.

Field evaluation of Verticillium wilt (VW) diseaseresistance for BC2F1 and BC1S1 populationsA field in the Anyang experiment farm at the Instituteof Cotton Research of Chinese Academy of AgriculturalSciences, Anyang, Henan Province, China, had beenconsecutively planted for more than 30 years with

cotton. So it had a relatively high and uniform density ofV. dahliae with both of the defoliating and nondefoliat-ing populations and could be used as a natural nurseryto screen for VW resistance breeding lines. In April2005, 133 BC2F1 and 121 BC1S1 families (BC2F1-FD andBC1S1-FD) and the two parental lines (CCRI36 andHai1) and its F1 were planted in this field in single-rowplots at one replication for per every family and in two-row plots for the two parents and F1. Each row was 8 mlong and 0.8 m wide with 32 plants. The glanded plants inBC2F1 and BC1S1 were pulled out at the seedling stage.

Preparation of inoculum and the artificial disease nurseryevaluation of Verticillium wilt (VW) for BC2F1 populationA defoliant, moderate pathogenic Anyang strain ofVerticillium dahliae, was a dominant pathogenic strain,isolated from the seriously infected field of cotton at An-yang, Henan Province, China. Before sowing cotton, theAnyang strain was cultured with cotton seeds with fuzzat 25 °C for 10 days. And the dry culture was grindedand placed uniformly in the artificial disease nursery,with the inoculum concentration of 45 g of dry cultureper 1 square meter of the disease nursery with conidialcontent of 1 × 108 per 1 g of the dry culture. This inocu-lation procedure yielded a mean DI of ca. 50 on the sus-ceptible check variety in the normal conditions. The VWresistance for the 133 BC2F1 families and their parentswere evaluated on June 23, July 19, August 15, and Au-gust 25 in 2005 in the artificial disease nursery.The artificial disease nursery consists of a series of ce-

ment pools used for the artificial inoculation. Every pool is20 m long and 2.5 m wide. The test was arranged in a ran-domized complete block design (RCBD) with 3 replicatesand one row (plot) for every family. Each row was 2.5 mlong and 0.6 m apart with 15 plants.

PhenotypingThe leaf tissue damage in the seedling and the maturitystages were classified into five grades which is a nationalstandard in Verticillium resistant scoring in China [19,48]. The grades scored as 1 and 2 were considered as re-sistant, and grades 3 and 4 as susceptible to VW.

<25 % chlorotic/necrotic leaves, grades 125–50 % chlorotic/necrotic leaves, grades 250–75 % chlorotic/necrotic leaves, grades 3>75 % chlorotic/necrotic leaves, grades 4

The disease grade of each plant in BC2F1 was recordedby the leaf symptoms on June 23, July 19, August 15,and August 25 in 2005 in the artificial disease nursery.The disease grade of each plant was recorded by the leafsymptoms for BC2F1 and BC1S1 on 17 September in2005 in the experiment field in Anyang. The DI was

Shi et al. BMC Genomics (2016) 17:877 Page 12 of 15

calculated using all plants scores within the family ineach plot, and then the disease index(DI) for per eachfamily was calculated to get the average value using theDI of the three replicates (the phenotype datasets in theAdditional file 2). The DI was calculated as follows:

DI ¼ Σ Ni � ið Þ= N� 4ð Þ½ � � 100; i ¼ 1–4; Ni

¼ numberof plantswith thegrade; N¼ the totalnumberof plants ineach family

DNA extraction, PCR amplification, electrophoresis andmap constructionCotton genomic DNA was extracted from young leavesof the 135 BC1F1 plants and the two parents as de-scribed by Paterson et al. [49]. SSR-PCR was conductedas described by Sun et al. [1] and the PCR productswere electrophoresed and silver-stained according tothe protocol of Zhang et al. [50]. The genotype data-sets are in the Additional file 3. SSR markers wereused to construct a genetic map for BC1F1 populationusing JoinMap 4.0 [51] and the linkage map was pub-lished in 2015 [33].

QTL analysisWe used the Linkage maps with the phenotypic dataof four dates of BC2F1-NY populations and one dateof BC1S1-FD and BC2F1-FD populations to identifyQTLs for VW resistance. QTLs were analyzed usingthe composite interval mapping method [52] andWindows QTL Cartographer 2.5 [53], with a walkspeed of 1 cM, a window size of 10 cM and 5 back-ground control markers. The statistical significance ofthe QTLs identified for the trait was determined byrunning a permutation procedure 1,000 times [54].Positive additive effects indicated that Hai1 alleles de-creased the DI value, increasing the phenotypic valuesof VW resistance, and negative scores indicated thatCCRI 36 decreased the DI value, increasing the valuesof VW resistance. The QTLs were named as follows:(q + trait abbreviation) + chromosome/linkage group +QTL number. QTLs for the same trait across differ-ent generations and dates were considered stablewhen their confidence intervals overlapped.

Meta-analysis of QTLsRecently, Said et al. reported a meta QTL analyses andestablished CottonQTLdb database containing 2274QTL for 66 different QTL trait types [34], including139 QTLs of VW resistance from nine published pa-pers [15, 16, 18, 19, 24–28]. We got the VW resistanceQTL mapping information including their names andCI provided by Said et al. [34]. The other 5 studies forVW resistance QTL mapping were also lately reported

[13, 17, 21–23], including 65 QTLs of VW resistance.Totally, we used 252 QTLs of VW resistance forMeta-analysis, including 48 QTLs identified in ourstudy.A meta-analysis of QTLs for VW resistance was per-

formed using Biomercator V3 software [55]. The de-tailed description for the meta-analysis of QTLs couldbe found in Said et al. [35, 36]. Hotspots were deter-mined manually. Four or more QTLs in an interval of25 cM were considered as a consistent QTL region. Ifthere was more than one trait involved in the QTLs,the region is called a QTL cluster. Otherwise, it iscalled a QTL hotspot for the region involving only onesingle trait [13].

Additional files

Additional file 1: The details of QTLs identified using interspecificbackcross populations on the map of CCRI36 × Hai1 BC1F1 and theircorresponding hotspots. (XLSX 16 kb)

Additional file 2: The phenotype datasets of BC2F1 on June 23, July 19,August 15, and August 25 in 2005 in the artificial disease nursery and ofBC2F1 and BC1S1 on 17 September in 2005 in the field. (XLSX 27 kb)

Additional file 3: The genotype datasets of 135 BC1F1 plants ofCCRI36× Hai1. (XLSX 1247 kb)

AbbreviationsC: chromosome; cM: CentiMorgan; CSSLs: Chromosome substitutionsegment substitution lines; DI: Disease index; MAS: Marker assisted selection;QTL: Quantitative trait loci; SSR: Simple sequence repeat; VW: Verticillium wilt;

AcknowledgementsThis work was funded by the National Natural Science Foundation of China(31101188), the National High Technology Research and DevelopmentProgram of China (2012AA101108), the National Agricultural Science andtechnology innovation project for CAAS and the fund project of Director(1610162015A01). We thank Professor Jinfa Zhang at Department of Plantand Environmental Sciences of New Mexico State University for his help inthis manuscript modification.

Authors’ contributionsYLY conceived the study. And BCZ and YZS performed the experiments. YZSconducted the data analysis and drafted the manuscript. YLY revised themanuscript. AYL and JWL helped with the field experiments. WTL, QWL, ZZand SQL helped with data analyses. YLY, YZS, AYL, JWL, WKG, HHS, JWG, TTC,TW, GQ, HQZ and LZ contributed reagents and materials. All authors readand approved the manuscript.

Competing interestsThe authors declare that they have no competing interests.

Consent for publicationNot applicable.

Ethics approval and consent to participateThis article does not contain any studies with human participants or animalsperformed by any of the authors.

Informed consentInformed consent was obtained from all individual participants included inthe study.

Shi et al. BMC Genomics (2016) 17:877 Page 13 of 15

Author details1State Key Laboratory of Cotton Biology, Key Laboratory of Biological andGenetic Breeding of Cotton, The Ministry of Agriculture, Institute of CottonResearch, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan,China. 2College of Bioscience and Biotechnology, Hunan AgriculturalUniversity, Changsha 410128, Hunan, China.

Received: 20 September 2015 Accepted: 27 September 2016

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