development of indels markers in oilseed rape...

Development of INDELs markers in oilseed rape(Brassica napus L.) using re-sequencing data

Sammina Mahmood . Zhaohong Li .

Xiaopeng Yue . Bo Wang . Jun Chen . Kede Liu

Received: 4 February 2016 / Accepted: 30 May 2016 / Published online: 9 June 2016

� Springer Science+Business Media Dordrecht 2016

Abstract Insertions/deletions (INDELs), a type of

abundant length polymorphisms in the plant genomes,

combine the characteristics of both simple sequence

repeats (SSRs) and single-nucleotide polymorphisms

(SNP), and thus can be developed as desired molecular

markers for genetic studies and crop breeding. There

has been no large-scale characterization of INDELs

variations in Brassica napus yet. In this study, we

identified a total of 538,691 INDELs in size range of

1–10 bp by aligning whole-genome re-sequencing

data of 23 B. napus inbred lines (ILs) to the B. napus

genome sequence of ‘Darmor-bzh.’ Of these, 104,190

INDELs were uniquely mapped on the pseudochro-

mosomes of the reference genome. A set of 595 unique

INDELs of 2–5 bp in length was selected for exper-

imental validation in the 23 ILs. Of these INDELs, 530

(89.01 %) produced a single PCR product and were

single locus. A total of 523 (87.9 %) INDELs were

found polymorphic among the 23 ILs. A genetic

linkage map containing 108 single-locus INDELs and

89 anchor SSR markers was constructed using 188

recombinant ILs. The majority of INDELs markers on

the linkage map showed consistency with the pseu-

dochromosomes of the B. napus cultivar ‘Darmor-

bzh.’ The INDELs variations and markers reported

here will be valuable resources in future for genetic

studies and molecular breeding in oilseed rape.

Keywords Brassica napus � Next-generationsequencing � Insertions/deletions � Single-locusmarker

Introduction

Molecular markers are important tools for a wide

range of genetics and genomics studies such as linkage

map construction, gene mapping, association analysis,

diversity evaluation and marker-assisted selection

(MAS). Molecular marker technology has advanced

from laborious and expensive restriction fragment

length polymorphism (RFLP) to high-throughput

sequence-based markers such as simple sequence

repeat (SSR) and single-nucleotide polymorphism

(SNP). SSRs are versatile type of marker and have

found their own positions in molecular breeding and

genomic studies in many plant species. This is partly

because SSRs are easily detectable by PCR, amenable

to high-throughput analysis, codominantly inherited,

Sammina Mahmood and Zhaohong Li have contributed equally

to this work.

Electronic supplementary material The online version ofthis article (doi:10.1007/s11032-016-0501-z) contains supple-mentary material, which is available to authorized users.

S. Mahmood � Z. Li � X. Yue � B. Wang �J. Chen � K. Liu (&)

National Key Laboratory of Crop Genetic Improvement,

Huazhong Agricultural University, Wuhan 430070, China

e-mail: [email protected]

123

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multi-allelic, highly polymorphic, abundant and

evenly distributed in genomes (Gupta and Varshney

2000), and partly because they can be easily developed

from piles of genomic and expressed DNA sequences.

SNPs are the most abundant variations in the genome

and are an important type of genetic markers for major

crop species. They are abundant, bi-allelic, codomi-

nant and amenable to high-through detection plat-

forms, also important for genetics and genomics

studies. A number of studies have been conducted to

identify SNPs in the genomes of diverse crops (Bekele

et al. 2013; Ching et al. 2002; Delourme et al. 2013;

Huang et al. 2013). However, recent technological

developments demonstrated that SNPs did not capture

all the meaningful genomic variations that contribute

to phenotypic differences. Hence, it is imperative to

develop and use other genome-wide informative

sequence-based genetic markers in order to delineate

functionally important genetic variation for genomics-

assisted crop improvement.

Insertions/deletions (INDELs), after SNPs are the

second major source of structural variations widely

distributed across the genomes of diverse plant

species (Li et al. 2015; Liu et al. 2012; Ollitrault

et al. 2012; Shen et al. 2004; Yang et al. 2014).

INDELs serve as centers of mutagenesis by increasing

nearby mutation rates and thus fuel the evolutionary

process. INDELs like SSRs are also a type of length

polymorphism, originated from a single mutation

event which occurs at a low frequency and is unlikely

to present recurrent mutations. The probability of two

INDELs mutations to occur at the same genetic

position and has exactly the same length is minimal.

Thus, INDELs are generally bi-allelic, single-locus in

nature. Shared INDELs represent identity by des-

cent in phylogenetic analysis (Shedlock and Okada

2000). Unlike SNPs, INDELs have more pronounced

phenotypic effects and generally considered more

deleterious. INDELs have myriad the desirable

inherent genetic characteristics of both SNPs and

SSRs markers, such as codominance, abundance and

random distribution across the genome (Li et al. 2013;

Lv et al. 2014; Mills et al. 2006; Pan et al. 2008) and

hence a valuable complement for both SNPs and SSRs

markers and make their own position in crop genomic

studies. Small INDELs can be analyzed in short

amplicons and genotyped in regular genetics and

breeding laboratories with polyacrylamide gel elec-

trophoresis (PAGE) or microcapillary sequencers in a

high-throughput manner as done with SSRs. Thus,

small INDELs are increasingly receiving attention,

and great efforts have been put on identification and

mapping INDELs in a number of plant species.

Arabidopsis and rice are the two first completely

sequenced plant genomes using the Sanger sequenc-

ing. Genome-wide DNA polymorphisms including

INDELs and SNPs have been identified between the

reference and one re-sequenced genomes, and data-

bases have been constructed for easy selection of

suitable INDELs and SNP markers (Arai-Kichise

et al. 2011; Jander et al. 2002; Shen et al. 2004). The

minimal start-to-finish time of a map-based cloning

project has been shortened significantly with the aid of

such a database, making it possible to identify the

causal mutation within one year from a mutant with

desirable phenotype in Arabidopsis (Jander et al.

2002). With the advent of next-generation sequencing

technologies, many plant species have been

sequenced, re-sequenced, and genome-wide INDELs

mined in these species (Li et al. 2013, 2015; Ollitrault

et al. 2012; Shen et al. 2004; Yang et al. 2014).

Oilseed rape (Brassica napus L., 2n = 38, AACC)

is an economically important oil crop worldwide. It is

an allotetraploid originated from relatively recent

natural interspecific hybridization between the two

diploid progenitors, B. rapa (2n = 20, AA) and B.

oleracea (2n = 18, CC). Several genome sequencing

projects for B. napus and its two diploid progenitors

have been conducted, and a large amount of genomic

and expressed DNA sequences had been released

(Chalhoub et al. 2014; Lim et al. 2006; Liu et al. 2014;

Wang et al. 2011). Extensive efforts have been made

to characterize the distribution patterns of SSRs in the

genomes and to develop thousands of SSR markers in

Brassica species in recent years (Cheng et al. 2009; Li

et al. 2010; Shi et al. 2014; Xu et al. 2010; Wang et al.

2011), which are important genetic resources for gene

mapping and molecular breeding. However, in B.

napus, most of the SSR markers usually display

multiple loci, which make it hard to integrate genetic

linkage maps and compare genes/QTLs detected using

different genetic populations. Thus, we must use the

SSR markers with caution in gene mapping and MAS,

especially in map-based gene cloning. It is necessary

to differentiate which locus of the multi-locus marker

linked to the gene of interest. The single-locus nature

of INDELs could resolve this drawback of multi-locus

SSRs. In recent years, INDELs have been mined in

79 of 13 Mol Breeding (2016) 36:79

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Brassica species. In B. rapa, 6753 INDELs in the gene

spaces have been identified and characterized by re-

sequencing 1398 sequence-tagged sites (STSs) in

eight genotypes (Park et al. 2010). Whole-genome re-

sequencing revealed a total of 108,558 putative short

INDELs (1–5 bp) between two B. rapa varieties,

Chiifu-402-41 and L144 (Li et al. 2013). In addition, a

large number of INDELs markers have been devel-

oped and applied to construct genetic linkage maps

and gene mapping in both B. rapa and B. oleracea (Li

et al. 2013; Lv et al. 2014).

Although INDELs markers have been widely used

in genetics and breeding research in many plant

species, their potential for such purpose has not been

explored in B. napus yet. In this study, we identified a

total of 538,691 small INDELs in size range of

1–10 bp by aligning whole genome re-sequencing

data of 23 B. napus inbred lines to the B. napus

genome sequence of ‘Darmor-bzh.’ A subset of 595

INDELs were validated by PCR amplification of

genomic DNA in the 23 inbred lines, and 108 INDELs

mapped to a genetic linkage map. The main objective

of this study was to identify and develop a set of user

friendly single-locus INDELs markers for genetics

and breeding studies in oilseed rape.

Materials and methods

Plant materials

Twenty-two B. napus inbred lines (ILs) with ample

differences in trait architecture were selected for re-

sequencing and initial polymorphism screening of

INDELs. These ILs have different geographic origins,

i.e. China, Japan, Europe and Canada (Table 1). They

are parents of a nested association mapping (NAM)

population with Zhongshuang 11 (ZS11) as the

common parent, which is a widely cultivated elite

open-pollinated cultivar in China and has been de novo

sequenced by the International Brassica Genome

Sequencing Consortium led by the Oil Crop Research

Institute (OCRI), Chinese Academy of Agriculture

Science. An IL, ‘M201,’ was selected to cross with

‘352’ for the development of recombinant inbred lines

(RILs). ‘M201’ is an IL with high oil content, long

siliques and large seeds, while ‘352’ is an IL with low

oil content, short siliques and small seeds. A popula-

tion consisting of 188 recombination inbred lines

(RILs) was derived from the cross between ‘M201’

and ‘352’ using single seed descent (SSD) method and

selfed to F6 generation. These RILs were used to

construct a genetic linkage map for the confirmation of

marker order and genetic location of INDELs markers

on the pseudochromosomes of B. napus genome.

Construction of whole-genome shotgun libraries

and sequencing

Fresh young leaf samples were collected from these

ILs. Total DNA was extracted by using the

cetyltrimethyl ammonium bromide method. One

microgram (lg) of genomic DNA was sheared to

yield an average size of 500 bp using an ultrasonic

Bioruptor (Diagenode; Liege, Belgium). Short insert

libraries (350–450 bp) of the 22 ILs were constructed

according to the manufacturers’ instructions (Illu-

mina, USA) and sequenced using the Illumina

HiSeq2000 platform to produce paired-end 100-bp

(PE100) reads. To minimize mapping errors, we

removed low-quality PE reads with 30 bases’ Phred

quality score less than Q20 using NGS QC Toolkit

(Patel and Jain 2012). The Illumina sequence data

have been deposited in the NCBI, Sequence Read

Archive (GenBank: SRA045576).

Procedures for INDELs discovery

The genome sequences of B. napus (http://www.

genoscope.cns.fr/brassicanapus), B. rapa (http://

brassicadb.org/brad) and B. oleracea (http://www.

oilcrops.com.cn) were used as reference for short

reads alignment and INDELs mining. The PE100

reads from individual ILs were aligned to the reference

genome sequences using the Burrows–Wheeler

Alignment tool (BWA version 0.7.0) (Li and Durbin

2009) with the following parameters: At most three

mismatches or one gap for each single PE100 read,

with gap extension 1–10 bp. To overcome the inter-

ference of paralogues and homeologues in INDELs

identification, only the reads with both ends uniquely

aligned to and located within a range of appropriate

insert sizes (350–450 bp) on the reference sequences

were kept for downstream analysis. The alignment

Mol Breeding (2016) 36:79 of 13 79

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http://www.genoscope.cns.fr/brassicanapus

http://www.genoscope.cns.fr/brassicanapus

http://brassicadb.org/brad

http://brassicadb.org/brad

http://www.oilcrops.com.cn

http://www.oilcrops.com.cn

results were converted to the BAM format using

SAMTools (version 0.1.18) (Li et al. 2009). Dupli-

cated reads caused by PCR in the process of

sequencing library construction were removed using

Picard package (version 1.91) (http://picard.

sourceforge.net).

INDELs detection was performed by Genome

Analysis Toolkit (GATK, version 2.4-9-g532efad)

(McKenna et al. 2010) and SAMTools. Reads around

INDELs were realigned using the local realignment

tool in GATK to minimize the number of mismatches

and to improve the specificity in variant calling

(DePristo et al. 2011). The base quality was recali-

brated using the base quality score recalibrate (BQSR)

package in GATK. Due to the absence of prior SNP

and INDEL database available for B. napus, the

common variants called by both GATK and SAM-

Tools were selected and used as prior information for

BQSR. INDELs calling for all accessions was

achieved by using the GATK UnifiedGenotyper

module, and the INDELs confidence score greater

than 30 was kept for further analysis.

Development of single-locus INDELs markers

The following criteria was employed for the selection

of INDELs markers. (1) The variation should be

random nucleotide INDELs, rather than simple

sequence length polymorphisms. (2) The INDELs

variations should be 2–5 nucleotides in length for

multiplexing and easy scoring on PAGE or capillary

sequencer. (3) The INDELs should be uniquely

mapped to the reference genome sequences to ensure

that they are of single locus. For this, 150-bp flanking

sequences on both sides of the INDELs mutation sites

were extracted and searched against the reference

genome sequences using the BLAST program with a

search score B 1e-10. If the flanking sequences

matched to multiple sites with more than 60 %

identity, these INDELs were removed from query list.

Table 1 Sequencing data

and short reads mapping to

the genome of B. napus

SW semi-winter, S spring

Variety Raw data (Gb) Mapped (Gb) Origin Growth habit

Zhongza 12.9 10.1 China SW

84001 17.1 13.6 China SW

Zhongshuang2 18.9 15.4 China SW

G1044 16.6 12.1 Japan SW

Baihua 14.9 11.4 Europe S

Quantum 12.9 10.6 Canada S

Chuan91 10.9 9.0 China SW

Huyou9 12.8 9.5 China SW

Bugle 12.7 10.2 Canada S

DH 4 15.7 11.4 China SW

Norin22 11.0 6.7 Europe SW

DH5 11.6 8.7 China SW

G1178 15.0 12.4 Japan SW

CAo3Ho-4 20.5 16.5 Canada SW

2012 13.2 10.1 China SW

Fuyou1 14.7 10.8 China SW

Cao221171 17.1 13.9 China SW

s2 35.2 27.3 China SW

352 17.8 13.6 China SW

264_1 20.7 16.4 China SW

Zheyou7 16.7 12.5 China SW

M201 16.2 13.0 China SW

Zhongshuang11 13.0 11.6 China SW

Average 16.0 12.4

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http://picard.sourceforge.net

http://picard.sourceforge.net

Only uniquely and perfectly matched INDELs were

retained to avoid multiple loci. (4) INDELs distributed

in distances of 1.0–5.0 Mb along the B. napus, B. rapa

and B. oleracea genomes were selected for marker

development.

Experimental validation of INDELs

polymorphism and construction of genetic linkage

map

PCR primers were designed with the following

requirements: primer length ranging from 18 to

23 bp, product length varying from 80 to 200 bp,

melting temperature ranging from 50�C to 70�C with

an optimum around 55�C and GC content ranging

from 30 to 70 % with an optimum around 50 %. To

further ensure that the selected INDELs are single

locus, in silico PCR (Shi et al. 2014) was conducted by

aligning the primers to the reference genome

sequences with the following settings: 2-bp mismatch,

1-bp gap and 50-bp margin. The primer pairs were

synthesized by Generay Biotech Company (Shanghai,

China).

PCR amplifications were performed in a volume of

10 ll containing 50 ng genomic DNA, 1 9 Taq

buffer, 2 mM MgCl2, 0.2 mM dNTPs, 0.2 lM each

primer and 0.25 U Taq DNA polymerase (Fermentas).

The reaction mixture was initially denatured at 94 �Cfor 3 min, followed by 35 cycles of amplification at

94 �C for 30 s, 56 �C for 30 s and 72 �C for 30 s, and

a final extension at 72 �C for 5 min. PCR products

were separated on denaturing polyacrylamide gels and

staining with silver nitrate.

A genetic map was constructed using JoinMap 3.0

software. The threshold for goodness of fit was set toB

5.0, with a recombination frequency of \0.4. Loci

were assembled into groups with minimum logarithm

of odds (LOD) scores of 2.0. The likelihoods of

different locus-order possibilities for linkage map

were compared and the one having the highest

likelihood was selected for each linkage group. All

genetic distances were expressed in centimorgan (cM)

as derived by the Kosambi function (Kosambi 1944).

In order to assign the INDELs markers to specific

linkage groups (LGs), 89 single-locus SSRs were

selected from previous linkage maps (Cheng et al.

2009; Li et al. 2010; Xu et al. 2010) and used as anchor

markers. LGs from the A and C subgenomes were

designated as A01–A10 and C01–C09, respectively.

Results

Whole-genome re-sequencing of the 22 ILs

Twenty-two ILs were chosen for re-sequencing. The

22 ILs were selected from four clusters based on the

genotypes of 451 single-locus SSR markers and

represented the highest level of diversity in 307

oilseed rape accessions (Xiao et al. 2012). The 22 ILs

are parents of a NAM population consisting of 3200

recombinant inbred lines (RILs) derived from 21

crosses with ZS11 as the common parent. Genomic

libraries with insert size ranging from 350 to 450 bp

were constructed for 22 ILs except for ZS11 and

sequenced on the HiSeq2000 platform. A total of

351.2 GB high-quality sequence data comprised of

1.756 9 109 PE100 reads were as obtained. A range of

54.5–176.0 million reads were generated for individ-

ual ILs, which corresponded to a range of

10.9–35.2 Gb sequence data (Table 1) and a coverage

depth of 9.0–27.3 9 of the B. napus genome (Chal-

houb et al. 2014). A total of 65 million random PE100

reads were in silico generated from the assembled

scaffold sequences of ZS11 (http://www.oilcrops.

com.cn/), which correspond to 13.0 Gb sequence

data (Table 1) and a coverage depth of 10.8 9 B.

napus genome.

Genomic distribution of INDELs variations

The PE100 reads of each IL were mapped to the B.

napus reference sequence of Darmor-bzh using the

BWA software (0.7.0). A total of 538,691 non-

redundant INDELs with 1–10 bp in length were

mined (Table 3). The INDELs could be further

divided into insertions/deletions of single base pair

and multiple base pairs. The single-base INDELs

accounted for 63.6 % with the A and T insertions/

deletions being the most abundant (Table 2). The

frequencies of the two- and three-base random

nucleotide INDELs were 10.5 and 6.1 %, respectively,

with the AT and TA insertions/deletions being the

most abundant. The 4–10 base random nucleotide

INDELs accounted for 16.6 % (Table 2). The average

density in the whole genome of B. napus was 0.63

INDELs/kb DNA (Table 3). The A subgenome had

311,927 INDELs with an average density of 0.99

INDELs/kb, while the C subgenome had 224,752

INDELs with an average density of 0.43 INDELs/kb.

Mol Breeding (2016) 36:79 of 13 79

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http://www.oilcrops.com.cn/

http://www.oilcrops.com.cn/

Chromosome C03 had the largest number of INDELs

(44,149, 0.66 INDELs/kb), and chromosome C05 had

the least number of INDELs (12,058, 0.26 INDELs/kb)

(Table 3). The distribution of INDELs across the

genome was uneven. Some chromosomes such as

chromosome C02, C05, C06, C08 and C09 had much

less INDELs than the average level across the genome.

Development of INDELs markers

The 150-bp flanking sequences on both sides of the

target INDELs were searched against the reference

Table 2 Number of INDELs with different length of

nucleotides

INDEL length Nucleotides Number

Single bases (63.6 %) A 138,449

C 33,194

G 32,799

T 138,242

Two bases (10.5 %) AA 1226

AC 3592

AG 5315

AT 12,732

CA 2024

CC 446

CG 804

CT 3319

GA 2484

GC 872

GG 448

GT 1994

TA 11,557

TC 4809

TG 3861

TT 1226

Three bases (6.1 %) AAA 172

AAC 483

AAG 691

AAT 646

ACA 220

ACC 133

ACG 132

ACT 198

AGA 256

AGC 137

GAA 602

GAC 185

TAA 642

GAG 340

TAC 378

TAG 304

GAT 322

TAT 681

GCA 117

GCC 58

TCA 369

GCG 44

TCC 227

Others 25,323

Table 2 continued

INDEL length Nucleotides Number

4–10 bases (16.6 %) 89,572

Total 538,691

Table 3 Number of INDELs distributed on each chromosome

Chromosome Length (Mb) No. of INDELs INDELs/kb

chrA01 26.0 25,566 0.99

chrA02 26.4 23,082 0.87

chrA03 35.8 44,063 1.23

chrA04 20.6 25,506 1.24

chrA05 26.1 26,008 1.00

chrA06 26.7 33,009 1.24

chrA07 26.1 31,635 1.21

chrA08 21.1 23,103 1.10

chrA09 38.0 35,529 0.93

chrA10 19.7 21,898 1.11

chrAnn 48.7 22,528 0.46

A subgenome 315.2 311,927

chrC01 43.2 21,564 0.50

chrC02 51.4 25,158 0.49

chrC03 67.1 44,149 0.66

chrC04 53.4 21,665 0.41

chrC05 46.9 12,058 0.26

chrC06 40.6 13,685 0.34

chrC07 47.7 21,334 0.45

chrC08 43.0 20,079 0.47

chrC09 52.9 20,074 0.38

chrCnn 80.7 24,986 0.31

chrUnn 8.3 2012 0.24

C subgenome 535.2 224,752

Total 850.3 538,691 0.63

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genomes using BLASTn program (e value was set as

1e-10) to screen for unique INDELs. A total of

104,190 INDELs were uniquely matched to only one

position on the reference genomes, which were ideal

for marker development. To investigate the authen-

ticity of these identified INDELs, a subset of 595

unique INDELs distributed along chromosomes with

intervals of 1–5 Mb selected for experimental valida-

tion (Supplementary Table 1). PCR primers were

designed to amplify the INDELs variations. PCR

products were amplified from the 23 ILs and separated

on PAGE. Of these 595 INDELs, 592 (99.5 %)

successfully amplified, while only three (0.5 %)

failed. Of the 592 amplified INDELs, 530 (89.1 %)

only amplified a single PCR product, which are

putative single-locus markers, and 62 (10.4 %) ampli-

fied two or more PCR products. A subset of 523

(87.9 %) INDELs verified to be polymorphic in the 23

ILs, indicating that the majority of INDELs polymor-

phisms discovered was correct. Of the polymorphic

INDELs, 478 detected two alleles in the 23 ILs, and

only 39 and 6 detected three and four alleles,

respectively. In the 478 bi-allelic INDELs, 416 were

codominant and 62 dominant.

Genetic mapping of INDELs

To highlight the usefulness of these INDELs markers,

a segregating population containing 188 RILs derived

from the cross ‘M201’ 9 ‘352’ was used to construct

a genetic map. Of the 595 INDELs, 134 showed

polymorphisms between ‘M201’ and ‘352.’ The

polymorphic INDELs were subjected to population

assay. All polymorphic INDELs segregated as codom-

inant single-locus markers and were very useful for

multiplexed loading. A genetic map containing 108

single-locus INDELs and 89 anchor SSR markers was

constructed. The linkage map consisted of 19 linkage

groups (LGs) and covered a total length of 1356.9 cM.

The distribution of INDELs markers across the 19

chromosomes was uneven. Chromosome C03 had the

maximum number of INDELs markers (22), followed

by A08 (8) and C04 (8). C08 had the least number of

INDELs markers (1). The genetic map showed good

colinearity with the pseudochromosomes of B. rapa

and B. oleracea with some inversions on chromo-

somes A4, A5, A6, A8, C3, C4 and C6 (Fig. 1). Seven

INDELs markers (ID31437, ID68635, ID71342,

ID71337, ID70476, ID70404 and ID94273) were

mapped on chromosomes different from the pseu-

dochromosomes of B. rapa and B. oleracea. Among

these markers, ID71342, ID71337, ID70476, ID70404

and ID94273, all mapped to the C03 chromosome

which was consistent with the pseudochromosomes of

the B. napus reference genome of ‘Darmor-bzh.’

These results suggested that the scaffolds conferring

these INDELs may be mis-assembled or mis-assigned

in the B. oleracea draft reference genome. It is also

possible that chromosome re-arrangements occurred

during diploidization after the hybridization of B. rapa

and B. oleracea.

Discussion

INDELs have been proved to be a simple and efficient

marker type in plant species (Pan et al. 2008; Pacurar

et al. 2012; Zeng et al. 2013). A large number of

INDELs have been identified in several plant species

including Arabidopsis, rice, citrus, pepper, tomato and

B. rapa using whole-genome re-sequencing data (Li

et al. 2013, 2015; Ollitrault et al. 2012; Pacurar et al.

2012; Yang et al. 2014; Zeng et al. 2013). Although the

oilseed rape genome sequences have been widely used

for SSR discovery (Cheng et al. 2009; Li et al. 2012;

Wang et al. 2011), large-scale identification of

INDELs has not been reported yet. In this study, we

identified 538,691 INDEL variations with 1–10 bp in

length by mapping re-sequencing data to the reference

genome sequence of the B. napus cultivar ‘Darmor-

bzh.’ Given that the PE readswere 100 bp in length, we

only mined INDELs in the size range of 1–10 bp to

avoid mis-alignment, which definitely lead to an

underestimation of the real distribution of INDELs in

theB. napus genome. The average density across theB.

napus genome was estimated to be 0.63 INDELs/kb,

which is much higher than that in the human genome

(Mills et al. 2006), but lower than that in the rice

genome (Shen et al. 2004). The density of INDELs in

the A subgenome (0.99 INDELs/kb) was significantly

higher than that in the C subgenome (0.43 INDELs/kb)

(Table 3) and also much higher than that identified in

the B. rapa genome (0.43 INDELs/kb) (Li et al. 2013).

Map-based gene cloning relies on the availability of

a large number of genetic markers with information of

position in the genome. PCR-based INDELs are

extensively used markers in initial mapping when

Mol Breeding (2016) 36:79 of 13 79

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ID2ID1027ID1764ID2004ID2193ID2214ID2707ID3166ID3610

ID3895ID3618

ID 3914ID4003ID4112ID4124ID4142ID4207

ID4349ID4294

ID4381ID4683ID4701ID5022

ID5178ID5514ID5637

ID5132

ID5694

ID5929ID5733

ID5949ID6234ID6307ID6315ID6334

0.1

3.41.8

4.74.2

4.86.67.99.39.4

11.111.412.013.4

13.713.5

14.414.815.215.517.017.118.419.219.420.921.121.822.323.123.2

26.226.025.824.7

A1

0

0.8

6.3

43.2

22.7

44.4

87.7

99.9

106.5

ID2

BRGMS125

ID1027

SSR655

ID2004

ID4683

ID5022

BrGMS2692

ID3914

A1

A2ID6435ID6905ID7279

BrGMS1411ID7968ID8362ID8646ID8702ID9178

ID9309ID9513ID9670ID9698ID9710ID9761ID10058ID10217ID10569ID10593ID10753ID10960ID11119

ID9289

ID7497

ID7856

0.32.0

5.73.7

6.97.78.7

10.511.611.714.2

15.215.1

16.217.517.817.918.719.820.523.423.724.8

26.925.9

ID7592

ID6905

ID10217

ID7968

BrGMS103

BnGMS635

ID8646

BrGMS31040

10

25

29

36

42

45

54

A2

ID11131ID11486ID12079

ID13400ID13663ID14010ID14457ID14502ID14891ID14917ID15834ID16574ID16775ID17250ID17506ID17513ID18115ID18590ID18884ID19212ID19782ID19790ID20295ID20793ID20794

ID12519

ID12945

0.11.6

4.43.2

5.45.56.98.09.2

10.110.3

11.211.1

12.914.615.617.318.218.319.821.021.922.7

29.127.327.225.824.524.4

ID12930

ID21395

A3

BrGMS1478

ID13400

BrGMS2498

ID14010

BnEMS472

BrGMS2685

BrGMS3279

BrGMS2903

ID18884

BrGMS3076

BrGMS2821

ID19790

BrGMS008

109.8

116.2

140.1

025.5

46.9

51.6

57.4

66.1

71.7

74.6

75.1

89.3

A3

A4

ID220870.71.5

3.01.6

3.43.83.95.26.26.86.9

8.67.8

8.89.39.7

10.010.911.612.313.213.514.0

19.117.816.615.715.614.6

19.2

ID22285ID22289


ID22840

ID23001ID22945

ID26966ID26967

A4

ID22840

ID22289

BrGMS2649

ID23997

ID24413

ID24354

BoGMS2573

BrGMS4369

ID26967

ID229450

4.4

5.9

17.8

20.2

27.7

28.7

46.8

50.3

79


ID26981ID26983ID27211ID27679

ID27826ID27825

0.10.2

2.41.3

2.82.94.24.35.37.17.5

8.47.7

8.89.7

10.811.512.113.514.315.416.316.9

23.322.320.819.818.918.1

24.3ID32842ID32968

A5

A5

0

17

18

21

21

25

25

27

28

28

31

35

BrGMS2847

BrGMS1807

ID31674

BrGMS2252

BrGMS3495

ID29688

ID29776

ID30147

ID30719

ID28572

ID32200

BrGMS23494

A6

BrGMS2087

SSR47BnEMS340SSR388ID35553BrGMS1894BoGMS1664BrGMS4161BrGMS1834ID36933ID37745ID37517ID31437ID39226ID39466BrGMS2086

BrGMS3613020.731.731.834.936.342.142.944.146.048.750.263.078.580.492.494.2

ID33237ID33622ID33987


ID34933

ID35553

12.5

ID35209

0.51.3

4.02.2

4.95.76.46.58.38.59.7

11.510.6

12.4

13.113.714.415.216.217.118.719.3

23.123.020.820.720.120.0

24.5ID40646ID41350

A6

Fig. 1 Genetic linkage map constructed with INDELs and

anchor SSR markers. For each linkage group, the left panel of

the figure is the pseudochromosome of B. rapa and B. oleracea.

On the left of the pseudochromosome is the physical position

(Mb). On the right of the pseudochromosome is the name of

INDELs markers. INDELs markers in italic font represent not

amplification; INDELs markers in boldface type represent no

polymorphism; INDELs markers in boldface italic font repre-

sent multi-locus; INDELs markers in regular font represent

polymorphism marker. The right panel of the figure represents

genetic linkagemap showing the position of 113 INDELs and 89

anchor SSR markers based on 188 RILs. On the right of the

linkage map is the name of INDELs and anchoring markers. On

the left of the linkage map is the distance of markers in

centimorgan (cM); black lines between the pseudochromosomes

and linkage maps represent relative position of the same

INDELsmarkers. INDELsmarkers underlined in the right panel

of the figure represent the same genetic position of marker in

both maps

79 of 13 Mol Breeding (2016) 36:79

123

using map-based cloning strategy to identify unknown

genes in Arabidopsis (Jander et al. 2002) and rice

(Shen et al. 2004; Zeng et al. 2013). Bulked segregant

analysis (BSA) combined with evenly distributed

high-quality INDELs markers enables the mapping of

a gene in an unprecedented speed than ever before

(Lukowitz et al. 2000). Once the gene is mapped,

further fine mapping in completely sequenced plant

species just requires enlarging the segregating popu-

lation and selecting more molecular markers currently

available or developed from the genome-wide DNA

polymorphism databases such as in Arabidopsis and

rice (Jander et al. 2002; Shen et al. 2004). In this study,

538,691 INDELs with 1–10 bp length were identified

in the B. napus genome, which are sufficiently

adequate for map-based cloning in oilseed rape. More

importantly, all INDELs have known genetic position

in relation to the reference genome, which makes it

possible to develop INDELs markers within target

genome regions and thus will speed up map-based

cloning and marker-assisted trait selection in oilseed

rape.

The allotetraploid genome of B. napus contains

many triplicated blocks of paralogous and orthologous

segments within and between subgenomes (Chalhoub

et al. 2014; Cheung et al. 2009; Liu et al. 2014; Udall

et al. 2005) that promote to homeologous pairing in

genome (Cai et al. 2014; Jiang et al. 2011). The

complexity of the B. napus genome renders the multi-

locus nature of most RFLP and SSR markers. Thus,

cautions should be taken while using the multi-locus

markers for fine mapping and marker-assisted selec-

tion. Single-locus INDELs markers could significantly

minimize homoplasy which is usually encountered

BrGMS3929

BrGMS2025

BrGMS3317

BrGMS3912

A8

ID49289

ID48433

ID48970

ID49098

ID50816

ID50750

ID52470

ID53630

0

1.8

2.0

4.9

5.4

6.6

7.0

16.7

20.9

48.8

73.3

20.1

A7

BnEMS620

BrGMS2989

BrGMS3976

ID47045

BoGMS612

ID47527

BrGMS29890

11.8

12.6

33.7

47.5

50.8

56.6

0.71.3

2.92.4

5.95.96.47.68.79.6

10.7

11.311.3

12.212.913.713.814.515.316.016.516.617.5

22.522.020.720.619.417.6

22.623.425.7

ID41705ID41910ID42176


ID42253

ID42605ID42604

ID47527ID47534ID47604ID48062

A70.71.5

3.62.2

4.46.27.07.38.59.6

11.610.7

12.712.813.414.114.516.417.318.218.919.8

20.320.0

ID48192ID48377ID48433

ID49098ID49123ID49289

ID49510ID49511ID49781ID49938ID50274ID50343ID50545ID50750ID50816ID51674ID52115ID52470ID53017ID53390ID53491ID53630

ID48636

ID48970ID48738

A8

ID61378

ID54119ID54270ID54336

2.9

ID57321


ID54565

ID54622ID54612

ID57397ID57708ID57723ID57986ID58314ID58807ID59618ID59627ID60249ID60346ID60375

ID61004

ID57093

3.7

5.24.2

5.86.06.97.98.79.59.6

10.610.5

11.511.513.113.215.816.817.518.219.320.5

24.324.223.222.422.321.3

25.426.027.127.227.828.830.031.431.533.033.233.334.935.037.5

ID60098

A9

A9

BoGMS778

ID54336ID54565ID56008

BrGMS2096BrGMS2248BnEMS857ID57321

BrGMS3064

ID58807BrGMS2161

BrGMS985

BrGMS2581BnGMS319BrGMS2199BrGMS1208BnEMS300

BrGMS3258

041650

52.152.754.867.769.579.189.389.891.992.192.393.997.9100.5101.8

BnEMS214

A10

BoGMS1114

BrGMS2240

ID63723

ID61680

ID61836

ID62141

BnEMS480

4.7

32.5

47.2

50.4

56

64.2

0.71.6

3.72.6

3.95.26.38.69.09.39.8

11.411.0

12.313.314.715.5

ID61680ID61836ID62141


ID62481

ID62612ID62500

A10

Fig. 1 continued

Mol Breeding (2016) 36:79 of 13 79

123

ID66886ID67073ID67265ID67409ID67599ID67771ID68108ID68190ID68319ID68396ID68635ID68854ID68961ID69106ID69211ID69226ID69346ID69381

ID69456ID69398


10.911.211.514.5

16.920.3

21.122.122.422.9

24.326.626.728.428.629.329.830.832.433.934.535.737.2

0.71.42.13.23.95.7

16

21

24

10.6

C1

BoGMS2752

BoGMS156517.4

C1SSR123

ID69106

SSR77

ID70531

0

2.3

6.9

3.6

12.9


ID72358ID72429ID72471ID72480ID72570ID72815

ID72244

ID73046

5.911.311.712.512.713.413.813.915.215.51617

21.421.423.924.629.229.93134

34.535.235.736.837.438.138.238.940.842.2

C2

BrGMS3854

BoGMS2239

BoGMS3028

C2

BnEMS287

BnEMS281

ID71991

ID73046

ID71534

ID72815

ID68635

ID71181

0

10.5

15.9

16.3

21

27.9

31.8

38.4

38.7

47.8

52.2


ID76183ID76068

ID76395ID76566ID76805ID77078ID77264ID77416

ID77795ID75404

ID77807ID77902ID78230ID78356ID78523ID78744ID78845ID79097ID79281

ID79679ID79786

ID79883ID79794

ID79961

ID79282ID79446ID79555

ID80103ID80258ID80403ID80533ID80641ID80857ID81001ID81132ID81380ID81444

ID81765ID80103

ID81799ID81935ID82067ID82193ID82430ID80103

2.22.93.95.15.16

6.98.38.99.2

10.510.711.1

12.711.9

13.914.915.717

18.319.3

21.519.9

21.622.524.625.626.427.729.230.931.6

34.835.4

36.535.5

37.4

31.732.833.7

3940.241

42.443.444.945.846.647.848.3

50.649.8

5151.752.754.155.256.2

C3

ID73514ID73711ID71342ID71337ID74413ID74952ID70476ID70404BrGMS2203ID79786ID78356ID78230ID78744

ID79097ID77264

ID79679SSR600ID79555ID79446ID94273ID80857

BoGMS678ID75404

ID82430ID82193

154.7

9.315.116.116.926.326.828.734.454.477.778

82.3100.6102.7104.6106.4106.6107

119.2120.8129.5147.6152.1

0C3

ID84702

ID83180

ID84630

ID83438

BoGMS836

ID83962

ID84316

BnGMS275

ID85015

BoGMS2306

BnGMS359

BoGMS1031

ID84962

SSR45

BoGMS3532

0

2.8

10

13.2

19.3

19.6

22.6

34.3

34.7

36.5

39.6

38.5

37.7

79.7

83.6

C4ID82921ID83127ID83180

ID83438

ID83673

ID83962ID84089ID84125

ID84341

ID84630

ID84862

ID85015

ID83253

ID83626

ID83706ID83832ID83862

ID84171ID84316

ID84442

ID84702

ID84948ID84962

ID85224ID85348ID85625ID85740

1.53.74.24.77.18.2

10.110.711.311.512.112.713

14.215.416.417.119.621.125.526.627

27.528.530.936.237.1

C4

ID86298

ID87883

ID86571

ID86603ID86597

ID87020ID86752


ID87972ID88006ID88085

0.31.82

2.62.1

5.97.17.214

14.314.417.4

19.118

24.921.9

27.126

28.428.831.1

C5

C5

86

75.2

10.1

5.6

0 ID86571

SSR25

ID86752

ID87883

ID87972

C6

ID92336

ID92882

0

1.7

9.1

24

37.1

67.3

80.7 ID88271

BoGMS1727

ID90852

ID90279

BrGMS1476

0.10.31.33

4.24.95.15.87

11.312.112.5

14.313.3

31.8

22.5

41.6

43.3

37.736.2

38.839.8

42.4

34.933.4

3130.229

28.326.725.1

44.5

ID89477

45.6

ID88158ID88187ID88271ID88391

ID88596

ID88528

ID88804ID88671

ID88580

ID88890ID88994ID89046ID89166ID89275

ID89584ID89815ID89851ID89879ID90051

ID90279ID90501ID90692ID90852ID91123

ID90184

ID91391

ID91970ID91670

ID92106ID92336ID92882ID93178

C6

Fig. 1 continued

79 of 13 Mol Breeding (2016) 36:79

123

when using SSR markers. Thus, single-locus INDELs

markers are more user-friendly than SSRs and have

been extensively used in forensic analysis (da Costa

Francez et al. 2012; Murthy et al. 2015; Pereira et al.

2009). In this study, 523 out of 595 INDELs markers

confirmed to be polymorphic among the 23 ILs, and

only 69 INDELs markers were monomorphic, sug-

gesting that the INDELs identified using re-sequenc-

ing data are reliable. The monomorphic INDELs

might be confounded by paralogous or homeologous

sequences. Furthermore, 530 out of 595 (86.9 %)

INDELs were detected to be single locus in the 23

inbred lines. Further survey in a segregating popula-

tion of RILs with 134 polymorphic INDELs markers

confirmed that they are truly single locus. The high

rate of single-locus marker indicated that the screening

for uniqueness is efficient for improving the rate of

single-locus marker. In addition, these INDELs vari-

ations were in the size range of 2–5 bp in length, thus

could be easily separated and scored on PAGE gels

and on capillary sequencers with multiple loadings.

We believe that these INDELs markers identified in

this study will greatly promote gene mapping and

marker-assisted oilseed rape breeding.

Acknowledgments This work was supported by the National

Hi-Tech R&D Program (2013AA102602) and the National

Natural Science Foundation of China (31071452).

Authors’ contribution statement SM, XY and JC performed

the experiments. JC developed the RILs. ZL and BW performed

the bioinformatics analyses. KL, SM and ZL wrote the paper.

KL conceived and supervised this study. The manuscript was

read and approved by all authors.

Compliance with ethical standards

Conflict of interest The authors declare that they have no

conflict of interest.

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ID93774ID93800ID93878ID93948ID94157ID94197ID94273ID94471ID94584ID94607ID94629ID94719ID94850ID94882ID94961ID95017ID95033ID95257ID95348ID95402ID95444ID95484ID95515ID95539ID95579ID95650ID95713ID95797ID95902ID96029ID96116ID96306ID96391ID96471ID96569ID96593

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BoGMS927

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BnEMS612

ID100320

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30.431.333.134.535.73636.63838.8

29.3

ID100980

ID101162ID101040

ID101189ID101380ID101415

ID102178

ID101534ID101598ID101717ID101769ID101806ID101993ID102108


C9

C9

BoGMS1283

ID103265

ID101189

ID101534

SSR548

0

0.5

16.1

21.8

24.5

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