1 23

Molecular BreedingNew Strategies in Plant Improvement ISSN 1380-3743Volume 34Number 1 Mol Breeding (2014) 34:87-98DOI 10.1007/s11032-014-0019-1

Linkage map construction using InDel andSSR markers and QTL analysis of headingtraits in Brassica oleracea var. capitata L.

Honghao Lv, Qingbiao Wang, YangyongZhang, Limei Yang, Zhiyuan Fang,Xiaowu Wang, Yumei Liu, Mu Zhuang,Yan Lin, Hailong Yu, et al.

1 23

Your article is protected by copyright and all

rights are held exclusively by Springer Science

+Business Media Dordrecht. This e-offprint

is for personal use only and shall not be self-

archived in electronic repositories. If you wish

to self-archive your article, please use the

accepted manuscript version for posting on

your own website. You may further deposit

the accepted manuscript version in any

repository, provided it is only made publicly

available 12 months after official publication

or later and provided acknowledgement is

given to the original source of publication

and a link is inserted to the published article

on Springer's website. The link must be

accompanied by the following text: "The final

publication is available at link.springer.com”.

Linkage map construction using InDel and SSR markersand QTL analysis of heading traits in Brassica oleracea var.capitata L.

Honghao Lv • Qingbiao Wang • Yangyong Zhang • Limei Yang •

Zhiyuan Fang • Xiaowu Wang • Yumei Liu • Mu Zhuang •

Yan Lin • Hailong Yu • Bo Liu

Received: 18 October 2013 / Accepted: 3 January 2014 / Published online: 18 January 2014

� Springer Science+Business Media Dordrecht 2014

Abstract Cabbage heading traits are important

quantitative traits that greatly affect both quality and

yield of cabbage. However, the genetic control of

these traits remains unclear. To detect quantitative

trait loci (QTLs) associated with heading traits, a

double haploid (DH) population with 196 lines was

created from a cabbage hybrid 01–20 9 96–100.

A genetic map with insertion–deletion and simple

sequence repeat markers was constructed based on the

DH population, with a total length of 934.06 cM and

average interval length of 2.3 cM between adjacent

markers. Field experiments in three seasons were

carried out to evaluate the heading traits, including

head mature period (Hm), head weight (Hw), core

length (Cl), head vertical diameter (Hvd), and the ratio

of Cl to Hvd (Cl/Hvd). Using the map and the trait

data, 13 reliable QTLs in total were identified and 5

were found in more than one season based on the

adjusted means of three seasons. Major QTLs were

identified for Hm (R2 = 40.4, LOD = 14.84), Hw

(R2 = 28.6, LOD = 9.83), Cl (R2 = 38.8, LOD =

15.73), Hvd (R2 = 19.2, LOD = 9.26), and Cl/Hvd

(R2 = 38.8, LOD = 12.75). The most significant

QTLs were Hm3.1, Cl3.1, and Cl/Hvd3.1, which were

detected in three seasons with the maximum contri-

bution rate of almost 40 %. Six active regions that

harbored more than one QTL were identified on five

chromosomes, and one of them contained major QTLs

associated with five traits. The QTLs obtained in this

study should be useful for marker-assisted selection in

cabbage breeding and for understanding the genetic

control of these traits.

Keywords Brassica oleracea � Linkage map �Quantitative trait loci � Heading traits

Introduction

Cabbage (Brassica oleracea L. var. capitata) is one of

the most cultivated vegetables worldwide. Cabbage

linkage maps with different types of markers have

been reported previously. From 1990 to 1997, restric-

tion fragment length polymorphism (RFLP) markers

were mainly used (Slocum et al. 1990; Landry 1992;

Camargo and Osborn 1996; Voorrips et al. 1997);

then, from 1997 to 2002, amplified fragment length

Honghao Lv and Qingbiao Wang have contributed equally to

this work.

Electronic supplementary material The online version ofthis article (doi:10.1007/s11032-014-0019-1) contains supple-mentary material, which is available to authorized users.

H. Lv � Q. Wang � Y. Zhang (&) � L. Yang �Z. Fang � X. Wang � Y. Liu � M. Zhuang �Y. Lin � H. Yu � B. Liu

Institute of Vegetables and Flowers, Chinese Academy of

Agricultural Sciences, 12# ZhongGuanCunNandajie

Street, Beijing 100081, China

e-mail: zhangyangyong@caas.cn

123

Mol Breeding (2014) 34:87–98

DOI 10.1007/s11032-014-0019-1

Author's personal copy

polymorphism (AFLP), RFLP and random amplified

polymorphic DNA (RAPD) markers were widely used

(Cheung et al. 1997; Moriguchi et al. 1999; Chen et al.

2002); and from 2004 to the present, more reliable

markers like simple sequence repeat (SSR) (Li et al.

2011), single nucleotide polymorphism (SNP) (Wang

et al. 2012), and insertion–deletions (InDels) gradually

have become more favored as the genome sequence of

cabbage was made available. However, they have

been rarely used in cabbage linkage map construction.

For cabbage, experience indicates that most impor-

tant agronomic traits such as mature period, yield,

plant height and quality follow quantitative inheri-

tance. These traits are useful for plant breeders and the

identification of quantitative trait loci (QTLs) associ-

ated with them can be helpful in cloning and

functional analysis of related genes. QTL studies in

cabbage have focused mainly on disease resistance

(Nagaoka et al. 2010; Kifuji et al. 2013) and flowering

time (Bohuon et al. 1998; Okazaki et al. 2007;

Uptmoor et al. 2008). In spite of the significance of

cabbage heading traits, the genetic control of these

characters has not yet been studied either in cabbage or

in other heading vegetables, for example Chinese

cabbage.

In this study, we designed SSR markers based on

the reference genome sequence and InDel markers

resulting from the whole-genome re-sequencing data

of the two parental lines and used these to construct a

linkage map using a double haploid (DH) population

made up of 196 lines. We also conducted evaluations

in three field experiments to investigate the heading

traits. Based on this map and three seasons’ data, we

aimed to map novel genomic regions and relatively

significant QTL regions influencing heading traits and

to facilitate a better understanding of the genetic

control of these characters.

Materials and methods

Plant materials and field experiment

The female parental line 01–20 (P1) originated from a

Canadian spring-early-maturing cultivar, while the

male parental line 96–100 (P2) was derived from an

autumn-late-maturing cultivar of Indian origin.

96–100 was crossed with 01–20 to generate F1 plants,

and a DH population consisting of 196 DH lines was

obtained from the F1 plants through isolated micro-

spore cultures (Takahata and Keller 1991).

Three field trials of the 196 DH lines as well as

their parents were carried out over three seasons in

Beijing, China: the first trial in autumn of 2011 was

conducted in an open field of the Shunyi District

(designated 2011a); the second in spring of 2012 in

an open field of the Changping District (2012s); and

the third in autumn of 2012 in a greenhouse in the

Changping District (2012a). A randomized trial

design was adopted in three seasons with two

replications. Each replication/plot consisted of 15

plants.

Data collection and statistical analysis

Three individual plants in each plot were randomly

selected for data collection at the mature stage (when

90 % of the plants of a DH line reached a normal

harvest stage, we deemed that this line was at its

mature stage). At this time, the heads were cut open

through the middle. The agronomic trait evaluation

was performed according to the following standards

(Li and Fang 2007): head mature period (Hm): days

from transplanting to harvesting; head weight (Hw):

weight of the matured cabbage head; core length (Cl):

length of the core in the head; head vertical diameter

(Hvd): height from the base to the top of a matured

cabbage head; in addition, the ratio of Cl to Hvd (Cl/

Hvd) was calculated. The average value for each DH

line was calculated from three plants in each plot. The

overall performance was the average over three

seasons. The adjusted means for the traits were

obtained and used for further analysis.

The broad-sense heritability for the five traits was

calculated as follows: h2 = rg2/(rg

2 ? rge2 /n ? r2/nr),

where rg2 is the genetic variance, rge

2 is genotype-by-

environment interaction, re2 is error variance, n is

number of environments, and r means number of

replications. The estimates of rg2, rge

2 , and re2 were

obtained from an analysis of variance (ANOVA) using

the general linear model procedure of the statistical

software SPSS 12.0 (SPSS Inc., Chicago, IL, USA)

with environment being considered as a random effect.

Pearson’s simple correlation coefficients (r) were

calculated between the traits, using the adjusted

means.

88 Mol Breeding (2014) 34:87–98

123

Author's personal copy

Molecular markers assays

The CTAB method (Saghai Maroof et al. 1984) was

adopted to extract total DNA from all the DH lines and

parental lines. DNA concentration was determined using

a Nanodrop Spectrophotometer ND-100 (Thermo Fisher

Scientific Inc., Wilmington, DE, USA), then diluted to a

working concentration of 40 ng/ll and stored at 4 �C.

The genome sequence of B. oleracea was retrieved

from BRAD, the genomic database for Brassica

(available at http://brassicadb.org), and used as the

reference sequence. 2,173 pairs of SSR primers were

designed from the sequence scaffolds in the reference

genome. A total of 7.2 and 7.1 Gb Illumina pair-end

reads were generated for the parental lines 01–20 (P1)

and 96–100 (P2), respectively, using the sequencing-

by-synthesis method. The reference sequence was

used as a ‘bridge’ to detect sequence polymorphisms

between the parental lines (Liu et al. 2013). To reduce

non-specific amplification, InDels located within

assembled sequences represented by multiple homo-

logues were excluded. In addition, one pair of primers

was chosen every 1,000 kb. In all, 707 pairs of InDel

primers were designed. For all the InDel primers, the

difference in the amplified product length between the

two parental lines was 3–5 bp, with a Tm value of

54–56 �C, GC content of 40–50 %, and amplicon

length of 100–200 bp. Each 20-ll polymerase chain

reaction (PCR) mixture contained 2 ll PCR buffer

(109, Mg2? included), 1.6 ll dNTP (2.5 mM each),

0.4 ll Taq DNA polymerase (2.5 U/ll), 5 ll DNA

template (40 ng/ll), 0.6 ll forward primer (10 lM),

0.6 ll reverse primer (10 lM), and 9.8 ll ddH2O. The

reaction mixture was incubated in a thermal cycler at

94 �C for 5 min, followed by 35 cycles of 94 �C for

30 s, 55 �C for 30 s, and 72 �C for 45 s, and finally

72 �C for 7 min. The PCR products were isolated

through 8 % polyacrylamide gel which was then

subjected to silver staining after running at 160 V for

1.5 h (Brant et al. 1991).

Construction of linkage map and QTL analysis

The linkage map was constructed with JoinMap 4.0

using a minimum logarithm of odds (LOD) score of

4.0 (Van Ooijen 2006). The Kosambi mapping

function was used to obtain the genetic distances

between markers (Kosambi 1944). A v2 test for

goodness-of-fit to the expected 1:1 Mendelian

segregation ratio was carried out to identify the

skewed markers at P \ 0.01.

MapQTL 4.0 (Van Ooijen et al. 2002) was imple-

mented for the QTL analysis using interval mapping

(IM) and multiple-QTL model (MQM). At first, a

1,000-permutation run was performed to estimate the

significance threshold of the test statistics for a QTL

based upon a 5 % experiment-wise error rate. IM of

every 1 cM along the chromosomes was then used to

scan for QTLs with a LOD threshold of 4.0. Markers

that were closely linked to positions with the highest

LOD score were taken as cofactors for MQM analysis.

Loci with the highest LOD scores were assigned as

QTLs. Two-LOD supported intervals were established

as 95 % confidence intervals (Van Ooijen 1992).

Results

Field performance and heading traits inheritance

The phenotypic performances for the parental lines

and the DH population were investigated over three

different environments (three seasons and two loca-

tions). The parents exhibited differences in some

traits. Bi-directional transgression beyond the parental

values was observed for all the five traits (Table 1).

The trait value in many DH lines showed inter-

parent variations, while some DH lines exhibited

transgressive variations, suggesting that alleles with

positive effects for these traits were distributed among

the parents. The three seasons’ traits data indicated

that Hm showed significant difference between the

two parental lines in all three seasons, which was

consistent with the fact that 01–20 was an early-

maturing line while 96–100 was a late-maturing one.

However, for Hw, a significant difference between the

parental lines was only observed in 2012s; for Cl, a

significant difference was only observed in 2012a; for

Hvd, significant differences were found in 2011a and

2012a; for Cl/Hvd, significant differences were found

in 2011a and 2012s (Table 1). From the skewness we

could see that in most cases the extent of transgressive

variation was towards the higher rather than the lower

values. Both skewness and kurtosis values of the five

traits were less than 1.0 in the three data sets,

indicating that the segregation pattern of all the five

traits appeared to fit a normal distribution model which

was suitable for QTL identification.

Mol Breeding (2014) 34:87–98 89

123

Author's personal copy

ANOVA was carried out to estimate the effects of

season, genotype, and genotype 9 season (Table 2). A

significant effect of season was observed for all the traits

except Hw and Cl/Hvd at the P\0.01 level. For all the

traits, no significant effect was observed for blocks as well

as genotype 9 season. A significant effect of genotype

was observed for all the traits at the P\0.01 level.

Pearson correlation tests were conducted for the

five traits to evaluate the correlations between any two

of the five traits (Table 3). Positive and significant

correlations were detected between all the measured

traits. The highest correlation was 0.864 between Cl

and Cl/Hvd, and then 0.860 between Hw and Hvd,

indicating the probable existence of a common genetic

control for these traits. Broad-sense heritability of the

five traits ranged from 0.70 to 0.85, indicating that the

genotype 9 season interaction was limited. The her-

itability of Cl/Hvd was the highest, compared to the

lowest of 0.70 for Hw.

Construction of the linkage map

A total of 2,173 pairs of SSR primers and 707 pairs of

InDel primers were used to detect polymorphisms

Table 1 Performance of the parental lines and the DH population for heading traits in three seasons

Environmentsa Traits P1

(mean ± SD)

P2

(mean ± SD)

DH

(mean ± SD)

Range

(mean ± SD)

Skewness Kurtosis

2011a, OF, Shunyi Hm (day) 50 ± 0.67c 72 ± 0.33a 56.27 ± 0.12b 40.0–87.0 0.288 -0.372

Hw (kg) 1.11 ± 0.1a 1.01 ± 0.01a 0.95 ± 0.01a 0.28–2.53 0.231 0.456

Cl (cm) 6.06 ± 0.11a 6.15 ± 0.09a 5.61 ± 0.01a 2.17–9.85 0.511 -0.218

Hvd (cm) 16.2 ± 0.23a 14.62 ± 0.16b 15.69 ± 0.15a 9.68–25.75 0.852 0.041

Cl/Hvd 0.37 ± 0.01b 0.42 ± 0.01a 0.36 ± 0b 0.19–0.60 0.036 -0.001

2012s, OF, Changping Hm (day) 54 ± 0c 71 ± 0a 60.34 ± 0.12b 49–89 0.698 0.105

Hw (kg) 0.7 ± 0.04b 0.89 ± 0.03a 0.76 ± 0.01fb 0.25–1.5 0.659 0.068

Cl (cm) 5.26 ± 0.21a 4.88 ± 0.06a 5.44 ± 0.08a 2.1–11.75 0.891 0.551

Hvd (cm) 13.08 ± 0.4a 13.68 ± 0.24a 13.03 ± 0.09a 8.91–17.2 0.080 -0.032

Cl/Hvd 0.4 ± 0.01a 0.36 ± 0.02b 0.41 ± 0.01a 0.19–0.74 0.713 0.194

2012a, GH, Changping Hm (day) 56.67 ± 0.03c 75.67 ± 0.03a 63.35 ± 0.03b 46–87 0.348 -0.570

Hw (kg) 0.72 ± 0.02fa 0.62 ± 0.04a 0.73 ± 0.01fa 0.26–1.78 0.828 0.419

Cl (cm) 5.73 ± 0.35a 5.1 ± 0.06b 5.84 ± 0.09a 2.38–14.83 0.658 0.699

Hvd (cm) 13.43 ± 0.07a 12.3 ± 0.21b 13.56 ± 0.07a 8.5–21.33 0.576 0.400

Cl/Hvd 0.43 ± 0.03a 0.41 ± 0.01a 0.43 ± 0a 0.22–0.8 0.280 0.486

Values followed by the same letters indicate no significant difference at P = 0.05, based on LSD test

Hm head mature period, Hw head weight, Cl core length, Hvd head vertical diameter, Cl/Hvd the ratio of Cl to Hvd, P1 female

parents, P2 male parentsa Three different test environments: 2011a, OF the plant materials were planted in an open field in autumn, 2011 in the Shunyi

District, Beijing, 2012s, OF the plant materials were planted in an open field in spring, 2012 in the Changping District, Beijing,

2012a, GH the plant materials were planted in a green house in autumn, 2012 in the Changping District, Beijing

Table 2 Analysis of variance

for five measured traits

For abbreviations, see Table 1

* Significant at P \ 0.05 level;

** significant at P \ 0.01 level

Source Mean Square

Hm Hw Cl Hvd Cl/Hvd

Season 1,857.03** 0.17** 7.81** 13.9** 0.023

Block (season) 14.12 0.01 0.22 1.36 0.02

Genotype 158.3** 1.94** 8.41** 251.12** 0.13**

Genotype 9 season 27.61 0.026 0.71 1.58 0.03

Error 0.21 0.12 0.01 0.02 0.002

90 Mol Breeding (2014) 34:87–98

123

Author's personal copy

between the parental lines; 273 pairs of SSR primers

and 261 InDel primers showed polymorphism

between the parents, and in total 152 (7 %) pairs of

SSR primers and 254 (36 %) pairs of InDel primers

with reliable PCR products were selected to genotype

the mapping DH population after removing ambigu-

ous markers. The data was then analyzed using the

JoinMap 4.0 software with a LOD threshold of 4.0 to

construct the linkage map. In total, 406 markers (152

SSRs and 254 InDels) were assigned to nine linkage

groups (LGs), covering a total genetic distance of

934.06 cM with 2.3 cM average length of the interval

between any two adjacent markers (Fig. 1). The nine

linkage groups could be anchored to their correspond-

ing reference chromosomes according to the physical

positions of the markers used in this study. The longest

linkage group (121 cM) was on chromosome 9 and the

shortest (77.99 cM) was on chromosome 7. The

maximum average distance (3.91 cM) was on chro-

mosome 4, and the minimum average distance

(1.56 cM) was on chromosome 3. The number of

markers in different linkage groups varied from 30 to

61; chromosome 3 had the highest number of markers

(61), while chromosome 4 had the lowest number (30).

The largest interval between markers was 16.8 cM on

chromosome 4 between scaffold21720 and scaf-

fold24097. Overall, the marker distribution was rela-

tively even on the nine chromosomes.

Based on a v2 test for goodness-of-fit to the

expected 1:1 Mendelian segregation ratio at

P \ 0.01, 220 skewed markers (54.2 %) were found.

140 out of 220 skewed markers were from the parent

01–20 (P1). Though there were markers distorting

significantly from the expected 1:1 segregation ratio,

there was adequate distribution of markers in different

linkage groups. This result was similar to the previous

reports in other DH populations of Brassica crops

(Foisset et al. 1996; Voorrips et al. 1997).

QTL identification of heading traits in cabbage

MapQTL 4.0 software was used for QTL analysis and

locations of QTLs are indicated by bars and arrows to

the right of the linkage groups (Fig. 1). A total of 30

QTLs with a LOD threshold of 4.0 were detected, with

each explaining 7–40.4 % of the phenotype variation;

six of the QTLs were detected in more than one

season; 75 % of the QTLs had contribution rates (CRs)

higher than 10 % (Table 4). The most significant

QTLs were Hm3.1, Cl3.1, and Cl/Hvd3.1, and each of

them was detected in three seasons with the CR of

almost 40 %. Moreover, all the three markers showed

positive effect, indicating that the parent 96–100 at

these loci contributed to the favorable alleles.

Two QTLs for the head mature period were

identified, located on chromosomes 1 and 3. These

QTLs together explained 20.5, 40.4, and 27.3 % of the

phenotypic variation in 2011a, 2012s, and 2012a,

respectively, and the effect of each QTL ranged from

13 to 40.4 % in three seasons. Of them, Hm3.1 was

detected in three seasons as the major QTL with a

maximum CR of 40.4 %, and only in 2012a was

another QTL Hm1.1 with minor effect identified.

Hm3.1 showed positive additive effect, indicating that

the parent 96–100 at this locus mostly increased Hm.

Six QTLs for head weight were identified on

chromosomes 1, 2, 3, 6, and 9, together accounting for

25.7, 28.6, and 29.6 % of the phenotypic variation in

2011a, 2012s, and 2012a, respectively, and the effect

of each QTL ranged from 9.7 to 28.6 % in three

seasons. Most of the alleles increasing Hw were

contributed by 01–20; the most significant one was

Hw3.1, explaining 28.6 % of the phenotypic variance

in 2012s. However, no QTL for Hw was detected in

more than one season, but Hw1.1 and Hw1.2 were the

close loci of chromosome 1 in two seasons (2011a and

2012a), which showed detection of a common region

associated with Hw, although Hw varied greatly in

different seasons due to the environment differences.

Three QTLs for core length were detected on

chromosomes 2, 3, and 7, together explaining 43.8,

47.6, and 33.6 % of the phenotypic variation in 2011a,

2012s, and 2012a, respectively, and the effect of each

QTL ranged from 6.6 to 38.8 % in three seasons. Two

Table 3 Correlation (Pearson) between five phenotypic traits

over three seasons

Traits Hm Hw Cl Hvd Cl/Hvd

Hm 0.546** 0.673** 0.528** 0.519**

Hw 0.619** 0.860** 0.251**

Cl 0.609** 0.864**

Hvd 0.147*

h2a 0.77 0.70 0.75 0.83 0.85

For abbreviations, see Table 1

* Significant at P \ 0.05 level; ** significant at P \ 0.01 levela Broad-sense heritability of measured traits

Mol Breeding (2014) 34:87–98 91

123

Author's personal copy

Fig. 1 Genetic linkage map based on a population of 196 DH

lines of cabbage and positions of QTLs associated with heading

traits in cabbage. Marker locations are listed to the right and

recombination distances (cM) to the left of each linkage group.

Locations of QTLs are indicated by names, bars and arrows to

the right of the linkage groups. Numbers 1–6 indicate the six

active regions. Hm head mature period, Hw head weight, Cl core

length, Hvd head vertical diameter, Cl/Hvd the ratio of Cl to

Hvd. The length of a bar indicates the two-LOD confidence

interval (QTLs with no bar indicates that only one flanking

marker was found with a LOD score C4.0). Arrows indicate the

relative effect of the 96–100 allele with upward for increasing

and downward for decreasing

92 Mol Breeding (2014) 34:87–98

123

Author's personal copy

Ta

ble

4Id

enti

fica

tio

no

fQ

TL

sas

soci

ated

wit

hh

ead

ing

trai

tsin

cab

bag

eu

sin

ga

B.

ole

race

aD

Hp

op

ula

tio

nin

thre

ese

aso

ns

Tra

itS

easo

nQ

TL

aC

hr.

bM

ark

erc

Inte

rval

(cM

)dL

OD

R2

(%)e

Ad

df

Hm

12

aH

m1

.11

scaf

fold

35

4–

20

81

15

1.6

–5

2.1

6.7

71

3–

3.9

9

12

aH

m3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

7.1

31

4.3

3.9

2

11

aH

m3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

5.9

92

0.5

4.3

5

12

sH

m3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

14

.84

40

.44

.3

Mea

ng

Hm

1.1

1sc

affo

ld3

54

–2

08

11

51

.6–

52

.14

.96

9.0

–2

.84

Hm

3.1

3sc

affo

ld3

97

82

–In

del

84

88

.0–

90

.89

.49

18

.93

.81

Hw

12

aH

w1

.11

Ind

el4

81

–sc

affo

ld1

83

76

55

.9–

56

.35

.83

10

.8–

0.0

9

11

aH

w1

.21

Ind

el3

99

–sc

affo

ld1

50

51

59

.4–

60

.04

.77

14

.3–

0.1

3

12

aH

w2

.12

Ind

el6

61

27

.24

.26

9.7

–0

.07

12

sH

w3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

9.8

32

8.6

0.1

5

12

aH

w6

.16

Ind

el5

87

–5

88

78

.5–

80

.34

.94

9.1

0.0

8

11

aH

w9

.19

Ind

el3

63

72

.03

.88

11

.4–

0.1

1

Mea

nH

w1

.11

Ind

el4

81

–sc

affo

ld1

83

76

55

.9–

56

.36

.11

1–

0.0

9

Hw

3.1

3sc

affo

ld3

97

82

–In

del

84

88

.0–

90

.83

.04

4.9

0.0

6

Hw

6.1

6In

del

58

7–

58

87

8.5

–8

0.3

4.7

8.4

0.0

8

Hw

9.1

9In

del

36

37

2.0

4.3

77

.9–

0.0

7

Cl

12

aC

l2

.12

Ind

el4

84

–6

61

12

.6–

27

.24

.05

6.6

–0

.54

11

aC

l2

.12

Ind

el4

84

–6

61

12

.6–

27

.25

.92

12

.2–

0.5

6

12

aC

l3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

14

.12

71

.11

11

aC

l3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

7.3

31

.60

.98

12

sC

l3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

15

.73

38

.81

.26

12

sC

l7

.17

Ind

el2

05

–5

93

42

.3–

43

.34

.73

8.8

–0

.57

Mea

nC

l3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

14

.63

01

.08

Hv

d1

2s

Hvd

1.1

1In

del

48

1–

scaf

fold

18

37

65

5.9

–5

6.3

4.5

81

0–

0.5

7

11

aH

vd1

.21

Ind

el3

99

–sc

affo

ld1

50

51

59

.4–

60

.04

.52

11

–1

.11

12

aH

vd2

.12

Ind

el4

84

–6

61

12

.6–

27

.21

0.8

41

7.7

–1

.04

11

aH

vd2

.12

Ind

el4

84

–6

61

12

.6–

27

.25

.33

16

–1

.23

12

sH

vd3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

9.2

61

9.2

0.7

2

12

sH

vd5

.15

scaf

fold

43

45

8–

Ind

el6

49

65

.3–

65

.64

.61

0.1

0.5

2

11

aH

vd5

.25

Ind

el1

23

–2

99

72

.7–

73

.64

.73

11

.51

.09

12

aH

vd6

.16

Ind

el5

87

–5

88

78

.5–

80

.37

.72

10

.60

.88

Mea

nH

vd1

.11

Ind

el4

81

–sc

affo

ld1

83

76

55

.9–

56

.37

.67

10

.7–

0.8

5

Hvd

2.1

2In

del

48

4–

66

11

2.6

–2

7.2

10

.38

18

–1

.00

Hvd

6.1

6In

del

58

7–

58

87

8.5

–8

0.3

6.9

9.5

0.7

9

Mol Breeding (2014) 34:87–98 93

123

Author's personal copy

Ta

ble

4co

nti

nu

ed

Tra

itS

easo

nQ

TL

aC

hr.

bM

ark

erc

Inte

rval

(cM

)dL

OD

R2

(%)e

Ad

df

Cl/

Hv

d1

2a

Cl/

Hvd

3.1

3sc

affo

ld3

97

82

–In

del

84

88

.0–

90

.82

0.0

53

2.4

0.0

7

11

aC

l/H

vd3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

12

.75

38

.80

.05

12

sC

l/H

vd3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

16

.33

32

.50

.07

12

aC

l/H

vd5

.15

Ind

el6

51

–sc

affo

ld4

11

00

66

.4–

66

.71

2.4

91

7.6

–0

.05

12

sC

l/H

vd5

.15

Ind

el6

51

–sc

affo

ld4

11

00

66

.4–

66

.77

.77

12

.4–

0.0

4

12

sC

l/H

vd7

.17

Ind

el1

83

27

.84

.54

7–

0.0

3

Mea

nC

l/H

vd3

.13

scaf

fold

39

78

2–

Ind

el8

48

8.0

–9

0.8

20

.89

30

.60

.06

Cl/

Hvd

5.1

5In

del

65

1–

scaf

fold

41

10

06

6.4

–6

6.7

11

.69

14

.7–

0.0

4

Cl/

Hvd

7.1

7In

del

18

32

7.8

4.0

15

.2–

0.0

2

Fo

rab

bre

via

tio

ns,

see

Tab

le1

aQ

TL

nam

esar

ein

dic

ated

astr

ait

nam

efo

llo

wed

by

chro

mo

som

en

um

ber

and

po

siti

on

bC

hro

mo

som

en

um

ber

cP

eak

mar

ker

or

mar

ker

inte

rval

dP

osi

tio

no

fth

ep

eak

mar

ker

or

mar

ker

inte

rval

eP

rop

ort

ion

of

the

ph

eno

typ

icv

aria

nce

exp

lain

edb

yea

chQ

TL

fA

dd

itiv

eef

fect

:p

osi

tiv

ead

dit

ivit

yin

dic

ated

that

96

–1

00

carr

ies

the

alle

lefo

ran

incr

ease

inth

etr

ait

val

ue,

wh

ile

neg

ativ

ead

dit

ivit

ym

ean

sth

at0

1–

20

carr

ies

the

alle

lefo

ran

incr

ease

inth

e

trai

tv

alu

eg

Ro

bu

stQ

TL

sin

dic

ated

by

the

mea

nv

alu

eso

fth

etr

aits

ov

er3

yea

rs

94 Mol Breeding (2014) 34:87–98

123

Author's personal copy

of the QTLs were detected in more than one season.

Cl3.1, as the major QTL, explained 27–38.8 % of the

phenotypic variance over three seasons and the

96–100 allele at the locus Cl3.1 increased Cl in three

seasons.

Eight QTLs for head vertical diameter were

detected on chromosomes 1, 2, 3, 5, and 6. These

QTLs explained 38.5, 39.3, and 28.3 % of the

phenotypic variation in 2011a, 2012s, and 2012a,

respectively, and the effect of each QTL ranged from

10 to 19.2 % in three seasons. Hvd2.1 with a CR of

17.7 % was detected in two seasons.

Three QTLs were detected for Cl/Hvd on chromo-

somes 3, 5, and 7, together explaining 32.4, 50, and

51.9 % in 2011a, 2012s, and 2012a, respectively, and

the effect of each QTL ranged from 7 to 38.8 % in

three seasons. Two of them could be detected in more

than one season. Cl/Hvd3.1, as the major QTL,

explained 27 to 38.8 % of the phenotypic variance

over three seasons and the 96–100 allele at the locus

Cl/Hvd3.1 increased Cl/Hvd in three seasons.

A joint analysis was also conducted for the QTLs,

with each trait using the adjusted means of the three

seasons’ trait values. The number of some QTLs

reduced significantly after the mean value of the three

seasons was used to detect the QTLs: Hw from 5 to 4,

Cl from 3 to 1, and Hvd from 7 to 3. This might be an

effective way to exclude some QTLs with minor

effects and others which may have been detected by

chance in a certain season. The results indicate that the

robust QTLs could still be detected when we used the

mean value of the traits over three seasons.

Active region analysis

From the positions of the QTLs, six active regions

harboring more than one QTL were identified and

indicated on five different chromosomes (Fig. 1).

These regions were distributed on chromosome 1, 2, 3,

5, and 6. The shortest region of 0.6 cM was located on

chromosome 1 between scaffold354 and scaf-

fold18376; the longest one of 14.6 cM was on

chromosome 2 between Indel484 and Indel661.

The most significant active region, 3, was a 2.8-cM

segment located at scaffold39782–Indel84 on chro-

mosome 3 containing five QTLs that were associated

with all five traits. Three of the five QTLs were

detected in three seasons. This region was anchored to

a 1.78-Mb genomic region harboring 173 genes.

The genes occurring in the 2.8-cM region were

analyzed. Half of the analyzed sequences are for genes

with functions that are still unknown according to the

Gene Ontology annotation obtained from BRAD.

Supplement Table 1 shows parts of the genes with

known functions. We observed that some interesting

genes might have connections with cabbage heading

traits, such as Bol008547 and Bol016111, which

function as components of photosynthesis. However,

we were unsure whether these genes contributed any

genetic control of the heading traits.

Discussion

Linkage map of B. oleracea

Genetic maps are of great significance in inheritance

research, gene mapping, and function analysis. Recent

developments in next-generation sequencing technol-

ogies have greatly advanced the development of SSR,

SNP, and InDel markers. However, both SSR markers

and SNP markers have many shortcomings. When

SSRs are applied to PCR and PAGE analysis, com-

plicated and unreliable types of electrophoresis bands

often occur, which cause genotyping errors that affect

further data analysis (Ellegren 2004). As for SNPs,

they are costly and some special equipment is required

for high-throughput genotyping (Syvanen 2004).

InDel markers, with many advantages, are attracting

more and more attention in recent years. The avail-

ability of many plant genome sequences as well as the

massive re-sequencing data allows us to obtain the

InDels easily through bioinformatic methods. Another

advantage is that the electrophoresis bands are more

reliable with single distinguishable bands of about

100–200 bp, which reduces the genotyping errors

greatly (Vali et al. 2008).

To date, about nine genetic linkage maps for

cabbage have been constructed. Most of these maps

were based on an F2 population derived from an inter-

subspecies cross using SSR or SNP markers. Here, we

report the first cabbage linkage map primarily using

InDel markers in a DH population with 196 lines

derived from an intra-subspecies cross of cabbage.

This is in comparison to a recently published SSR-

based map (Li et al. 2011) and the SNP-based map

(Wang et al. 2012). SSR and InDel markers were

designed based on the reference genome sequence and

Mol Breeding (2014) 34:87–98 95

123

Author's personal copy

whole-genome re-sequencing data of the two parental

lines. The generated map contained nine linkage

groups, with 406 markers covering 934.06 cM and an

average interval length of 2.3 cM, and the marker

distribution was relatively even on the nine chromo-

somes. The linkage groups could be assigned to

corresponding chromosomes based on the position of

the markers. The map created in our study was a

medium-density one which was comparable with

those maps published in recent years. A high percent-

age of skewed markers (54.2 %) were found in our

study, which was comparable with 64 % skewed

markers observed by Voorrips et al. (1997), and this is

common in DH populations due to probable selection

during microspore culture (Foisset et al. 1996).

QTL research in cabbage

QTL research and marker-assisted selection (MAS)

are developing fast and are widely used in the breeding

of plants such as wheat (Singh et al. 2004), potato

(Gebhardt et al. 2006), and cabbage (Chen et al. 2013).

Though some QTLs have been identified in cabbage,

research is still at a preliminary stage because QTL

cloning has not yet been reported and functional

analysis studies are rare. To date, the interest in

cabbage QTLs has been focused mainly on fertility

(Wang et al. 2000), plant size (Lan and Paterson

2001), plant regeneration (Holme et al. 2004), flow-

ering time (Bohuon et al. 1998; Okazaki et al. 2007;

Uptmoor et al. 2008), clubroot resistance (Nagaoka

et al. 2010), and black rot resistance (Kifuji et al.

2013).

For cabbage breeders, heading traits such as head

weight, core length, and head mature period are

important characteristics that affect not only the yield,

but also the quality of cabbage. However, no QTL

studies for these traits have been reported until now.

Here, for the first time, we identified QTLs associated

with the traits of head weight, head vertical diameter,

core length, and head mature period using a DH

population based on agronomic trait data collected in

three seasons. In all, 13 reliable QTLs were detected

and five were found in more than one season. Three

major QTLs identified were Hm3.1, Cl3.1, and Cl/

Hvd3.1, all of which were detected in three seasons

with the CR of almost 40 %. These QTLs will be

helpful in identifying genes related to these traits and

in MAS for cabbage breeders.

We also conducted a joint analysis for all QTLs

with each trait using the adjusted means of the three

seasons’ trait value and 13 QTLs in total were detected

in this way. The number of QTLs for some traits was

reduced significantly, but all the major QTLs were

retained. As some QTLs might be spurious and could

be detected only by chance in a certain season, this

might be an effective way to exclude some QTLs with

minor effects and others which may be relatively

spurious so that the reliable QTLs could be retained.

Breeding effects of important genomic regions

To produce excellent parental lines, breeders constantly

select for traits such as disease resistance, high yield, and

quality. Constant artificial selection of particular traits

can reduce the genetic diversity in many genomic

regions, resulting in some good variation being retained

and other variation being eliminated (Palaisa et al. 2004).

Therefore, it is important to study elite parental lines and

varieties derived from them to identify genomic regions

that control important agronomic traits, and the detection

of QTLs that control these traits is one way to achieve

this (Andolfatto 2001; Lukens and Doebley 2001).

The effects of breeding programs on important

genomic regions have been studied in many crops

including wheat (Pestsova and Roder 2002; Christo-

pher et al. 2007), maize (Lukens and Doebley 2001;

Palaisa et al. 2004), and soybean (Lam et al. 2010). In

our study, six genomic regions with QTLs that were

associated with several important traits were also

identified in cabbage. This might facilitate MAS in

genomic region-specific breeding.

Interesting genes in the active regions

In our study, we discovered six active regions with more

than one QTL. Specifically, a 2.8-cM region with QTLs

associated with all five heading traits was detected, and

this region was anchored to a 1.78-Mb region on

chromosome 3 that harbored 173 genes. These regions

may become the focus of research to identify related

genes and may be used to improve breeding efficiency.

We analyzed the genes that fell into the most significant

region; half of the genes’ functions were still unknown,

and there were some interesting genes that might have

connections with cabbage heading traits, such as

Bol008547 and Bol016111 functioning as components

of photosynthesis. However, further work still needs to

96 Mol Breeding (2014) 34:87–98

123

Author's personal copy

be done in order to elucidate the genetic control of

heading traits in cabbage.

Acknowledgments This work was financially supported by

grants from Major State Basic Research Development Program

(973 Program, 2012CB113906), the National Natural Science

Foundation of China (31272180), the National High

Technology Research and Development Program of China

(863 Program, 2012AA100102, 2012AA100202), the Key

Projects in the National Science & Technology Pillar Program

during the Twelfth Five-Year Plan Period (2012BAD02B01),

and the earmarked fund for the Modern Agro-Industry

Technology Research System, China (nycytx-35-gw01). The

work reported here was done in the Key Laboratory of Biology

and Genetic Improvement of Horticultural Crops, Ministry of

Agriculture, Beijing 100081, China.

References

Andolfatto P (2001) Adaptive hitchhiking effects on genome

variability. Curr Opin Genet Dev 11:635–641

Bohuon EJR, Ramsay LD, Craft JA, Arthur AE, Marshall DF,

Lydiate DJ, Kearsey MJ (1998) The association of flowering

time quantitative trait loci with duplicated regions and can-

didate loci in Brassica oleracea. Genetics 150:393–401

Brant JB, Gustavo CA, Peter MG (1991) Fast and sensitive

silver staining of DNA in polyacrylamide gels. Anal Bio-

chem 196:80–83

Camargo LEA, Osborn TC (1996) Mapping loci controlling

flowering time in Brassica oleracea. Theor Appl Genet

92(5):610–616

Chen S, Wang X, Fang Z, Cheng Z, Sun P (2002) Construction

of molecular linkage map of Brassica oleracea var. al-

boglabra 9 B. oleracea var. capitata by RAPD analysis.

Acta Horticulturae Sinica 29(3):229–232

Chen C, Zhuang M, Fang ZY, Wang QB, Zhang YY, Liu YM,

Yang LM, Cheng F (2013) A co-dominant marker BoE332

applied to marker-assisted selection of homozygous male-

sterile plants in cabbage (Brassica oleracea var. capitata

L.). J Integr Agric 12(4):596–602

Cheung W, Champagne G, Hubert N, Landry B (1997) Com-

parison of the genetic maps of Brassica napus and Brassica

oleracea. Theor Appl Genet 94(5):569–582

Christopher M, Mace E, Jordan D, Rodgers D, McGwan P,

Delacy L, Banks P, Sheppard J, Butler D, Poulsen D (2007)

Applications of pedigree-based genome mapping in wheat

and barley breeding programs. Euphytica 154:307–316

Ellegren H (2004) Microsatellites: simple sequences with

complex evolution. Nat Rev Genet 5:435–445

Foisset N, Delourme R, Barret P, Hubert N, Landry BS, Renard

M (1996) Molecular-mapping analysis in Brassica napus

using isozyme, RAPD and RFLP markers on a doubled-

haploid progeny. Theor Appl Genet 93:1017–1025

Gebhardt C, Bellin D, Henselewski H, Lehmann W,

Schwarzfischer J, Valkonen JPT (2006) Marker-assisted

combination of major genes for pathogen resistance in

potato. Theor Appl Genet 112:1458–1464

Holme IB, Torp AM, Hansen LN, Andersen SB (2004) Quantita-

tive trait loci affecting plant regeneration from protoplasts of

Brassica oleracea. Theor Appl Genet 108:1513–1520

Kifuji Y, Hanzawa H, Terasawa Y, Ashutosh, Nishio T

(2013) QTL analysis of black rot resistance in cabbage

using newly developed EST-SNP markers. Euphytica

196:289–295

Kosambi DD (1944) The estimation of map distances from

recombination values. Ann Eugen 12(1):172–175

Lam HM, Xu X, Liu X, Chen WB, Yang GH (2010) Rese-

quencing of 31 wild and cultivated soybean genomes

identifies patterns of genetic diversity and selection. Nat

Genet 42(12):1053–1059

Lan TH, Paterson AH (2001) Comparative mapping of QTLs

determining the plant size of Brassica oleracea. Theor

Appl Genet 103:383–397

Landry B (1992) A genetic map for Brassica oleracea based on

RFLP markers detected with expressed DNA sequences

and mapping of resistance genes to race 2 of Plasmodio-

phora brassicae (Woronin). Genome 35:409–420

Li XX, Fang ZZ (2007) Descriptors and data standards for

cabbage (Brassica oleracea L. var. capitata L. and Bras-

sica oleracea L. var. gemmifera Zenk). China Agriculture

Press, Beijing

Li HH, Chen C, Yang Y, Xu JS, Gu JX, Fu J, Qian XJ, Zhang

SC, Wu JS, Liu KD (2011) Development and genetic

mapping of microsatellite markers from whole genome

shotgun sequences in Brassica oleracea. Mol Breed 28:

585–596

Liu B, Wang Y, Zhai W, Deng J, Wang H, Cui Y, Cheng F,

Wang X, Wu J (2013) Development of InDel markers for

Brassica rapa based on whole-genome re-sequencing.

Theor Appl Genet 126:231–239

Lukens LN, Doebley J (2001) Molecular evolution of the teo-

sinte branched gene among maize and related grasses. Mol

Biol Evol 18:627–638

Moriguchi K, Kimizuka-Takagi C, Ishii K, Nomura K (1999) A

genetic map based on RAPD, RFLP, isozyme, morpho-

logical markers and QTL analysis for clubroot resistance in

Brassica oleracea. Breed Sci 49(4):257–265

Nagaoka T, Doullah MAU, Matsumoto S, Kawasaki S, Ishikawa

T, Hori H, Okazaki K (2010) Identification of QTLs that

control clubroot resistance in Brassica oleracea and com-

parative analysis of clubroot resistance genes between B.

rapa and B. oleracea. Theor Appl Genet 120:1335–1346

Okazaki K, Sakamoto K, Kikuchi R, Saito A, Togashi E, Ku-

ginuki Y, Matsumoto S, Hirai M (2007) Mapping and

characterization of FLC homologs and QTL analysis of

flowering time in Brassica oleracea. Theor Appl Genet

114:595–608

Palaisa K, Morgante M, Tinggey S, Rafalski A (2004) Long-

range patterns of diversity and linkage disequilibrium

surrounding the maize Y1 gene are indicative of an

asymmetric selective sweep. Proc Natl Acad Sci USA

101:9885–9890

Pestsova E, Roder M (2002) Microsatellite analysis of wheat

chromosome 2D allows the reconstruction of chromosomal

inheritance in pedigrees of breeding programmes. Theor

Appl Genet 106:84–91

Saghai Maroof MA, Soliman KM, Jorgensen RA, Allard RW

(1984) Ribosomal DNA spacer-length polymorphisms

Mol Breeding (2014) 34:87–98 97

123

Author's personal copy

in barley: Mendelian inheritance, chromosomal loca-

tion, and population dynamics. Proc Natl Acad Sci USA

81:8014–8018

Singh AL, Basu MS, Singh NB (2004) Mineral disorders of

groundnut. National Research Center for Groundnut

(ICAR), Junagadh, p 85

Slocum M, Figdore S, Kennard W, Suzuki J, Osborn T (1990)

Linkage arrangement of restriction fragment length poly-

morphism loci in Brassica oleracea. Theor Appl Genet

80(1):57–64

Syvanen AC (2004) Accessing genetic variation: genotyping

single nucleotide polymorphisms. Nat Rev Genet 2(12):

930–942

Takahata Y, Keller WA (1991) High frequency embryogenesis

and plant regeneration in isolated microspore culture of

Brassica oleracea L. Plant Sci 74:235–242

Uptmoor R, Schrag T, Hartmut S, Elisabeth E (2008) Crop

model based QTL analysis across environments and QTL

based estimation of time to floral induction and flowering

in Brassica oleracea. Mol Breed 21:205–216

Vali U, Brandstrom M, Johansson M, Ellegren H (2008)

Insertion–deletion polymorphisms (indels) as genetic

markers in natural populations. BMC Genet 9:8

Van Ooijen JW (1992) Accuracy of mapping quantitative trait loci

in autogamous species. Theor Appl Genet 84(7–8):803–811

Van Ooijen JW (2006) JoinMap 4, software for the calculation

of genetic linkage maps in experimental populations. Ky-

azma BV, Wageningen

Van Ooijen JW, Boer MP, Jansen RC, Maliepaard C (2002) Map

QTL 4�0: software for the calculation of QTL positions on

genetic maps. Plant Research International, Wageningen

Voorrips R, Jongerius M, Kanne H (1997) Mapping of two

genes for resistance to clubroot (Plasmodiophora brassi-

cae) in a population of doubled haploid lines of Brassica

oleracea by means of RFLP and AFLP markers. Theor

Appl Genet 94(1):75–82

Wang XW, Fang ZZ, Huang SW, Sun PT, Liu YM, Yang LM,

Zhuang M, Qu DY (2000) An extended random primer

amplified region (ERPAR) marker linked to a dominant

male sterility gene in cabbage (Brassica oleracea var.

capitata). Euphytica 112(3):267–273

Wang W, Huang S, Liu Y, Fang Z, Yang L, Hua W, Yuan S, Liu

S, Sun J, Zhuang M, Zhang Y, Zeng A (2012) Construction

and analysis of a highdensity genetic linkage map in cab-

bage (Brassica oleracea L. var. capitata). BMC Genomics

13:523

98 Mol Breeding (2014) 34:87–98

123

Author's personal copy