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Theor Appl Genet (2016) 129:1797–1814DOI 10.1007/s00122-016-2741-z

ORIGINAL ARTICLE

Identification of candidate domestication regions in the radish genome based on high‑depth resequencing analysis of 17 genotypes

Namshin Kim1,3 · Young‑Min Jeong2 · Seongmun Jeong1 · Goon‑Bo Kim4 · Seunghoon Baek4 · Young‑Eun Kwon4 · Ara Cho4 · Sang‑Bong Choi4 · Jiwoong Kim5 · Won‑Jun Lim1,3 · Kyoung Hyoun Kim1,3 · Won Park1,3 · Jae‑Yoon Kim1,3 · Jin‑Hyun Kim6 · Bomi Yim2 · Young Joon Lee2 · Byung‑Moon Chun7 · Young‑Pyo Lee7 · Beom‑Seok Park8 · Hee‑Ju Yu2 · Jeong‑Hwan Mun4

Received: 27 November 2015 / Accepted: 4 June 2016 / Published online: 4 July 2016 © Springer-Verlag Berlin Heidelberg 2016

High-depth resequencing and multi-sample genotyp-ing analysis of ten cultivated and seven wild accessions obtained 4.0 million high-quality homozygous single-nucleotide polymorphisms (SNPs)/insertions or deletions. Variation analysis revealed that Asian cultivated radish types are closely related to wild Asian accessions, but are distinct from European/American cultivated radishes, sup-porting the notion that Asian cultivars were domesticated from wild Asian genotypes. SNP comparison between Asian genotypes identified 153 candidate domestication regions (CDRs) containing 512 genes. Network analysis of the genes in CDRs functioning in plant signaling path-ways and biochemical processes identified group of genes related to root architecture, cell wall, sugar metabolism, and glucosinolate biosynthesis. Expression profiling of the genes during root development suggested that domestica-tion-related selective advantages included a main taproot with few branched lateral roots, reduced cell wall rigidity and favorable taste. Overall, this study provides evolution-ary insights into domestication-related genetic selection in radish as well as identification of gene candidates with

Abstract Key message This study provides high‑quality variation data of diverse radish genotypes. Genome‑wide SNP comparison along with RNA‑seq analysis identified can‑didate genes related to domestication that have poten‑tial as trait‑related markers for genetics and breeding of radish.Abstract Radish (Raphanus sativus L.) is an annual root vegetable crop that also encompasses diverse wild species. Radish has a long history of domestication, but the origins and selective sweep of cultivated radishes remain contro-versial. Here, we present comprehensive whole-genome resequencing analysis of radish to explore genomic varia-tion between the radish genotypes and to identify genetic bottlenecks due to domestication in Asian cultivars.

Communicated by I. AP Parkin.

N. Kim and Y.-M. Jeong contributed equally to this work.

Electronic supplementary material The online version of this article (doi:10.1007/s00122-016-2741-z) contains supplementary material, which is available to authorized users.

* Hee-Ju Yu yuheeju@catholic.ac.kr

* Jeong-Hwan Mun munjh@mju.ac.kr

1 Epigenomics Research Center of Genome Institute, Daejeon 34141, Korea

2 Department of Life Science, The Catholic University of Korea, Bucheon 14662, Korea

3 Department of Functional Genomics, Korea University of Science and Technology, Daejeon 34141, Korea

4 Department of Bioscience and Bioinformatics, Myongji University, Yongin 17058, Korea

5 Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea

6 Department of Genetic Engineering, Dong-A University, Busan 49315, Korea

7 Breeding Research Institute, Dongbu Farm Hannong Co. Ltd., Ansung 17503, Korea

8 Department of Genomics, National Academy of Agricultural Science, Rural Development Administration, Wanju 54874, Korea

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the potential to act as trait-related markers for background selection of elite lines in molecular breeding.

Introduction

Radish (Raphanus sativus L.) is a diploid (2n = 18) spe-cies of the Brassicaceae family and a close relative of Bras-sica crops including B. rapa, B. oleracea, and B. nigra. Agronomically, radish is an important root vegetable crop around the world representing approximately 2 % of total world vegetable production at an estimated 7 million tons/year on average (Kopta and Pokluda 2013). The most com-mercially valuable part of the radish is its enlarged taproot, which provides an excellent source of nutrients including sugars, minerals, phytochemicals, and dietary fiber. The radish taproot comes in a variety of sizes, shapes, tex-tures, colors, and sugar contents. Other plant parts includ-ing seedling sprouts, leaves, seed pods, and seeds are also consumed as vegetables or oil sources. The origin of the radish remains unclear. The first record of radish consump-tion in human nutrition dates back to approximately 2000 BC in ancient Egypt. Radish cultivation began in China and Korea in approximately 400 BC, indicating that it is an ancient domesticated species native to both the East-ern Mediterranean and Eastern Asia (Becker 1962; George and Evans 1981; Kaneko and Matsuzawa 1993). Thus, the Middle East, Eastern Mediterranean, and Asian regions are considered possible centers of origin (Warwick 2011). Also, studies based on molecular markers have suggested that domestication of wild radish occurred independently in multiple regions (Yamagishi 2004; Yamagishi and Terachi 2003; Yamane et al. 2005, 2009). Most of the aforemen-tioned studies used a limited number of molecular mark-ers or sequences in chloroplast DNA. However, there has been no detailed investigation into domestication events, and genes selected during domestication have not been explored so far.

Domesticated crop plants differ from their wild pro-genitors with respect to numerous morphological and physiological traits, such as number and size of edible parts, growth habit, plant architecture, seed germination, flowering time, nutrient content, and/or coloration (Abbo et al. 2014). The specific traits selected during domestica-tion can vary depending on the species, nature of the evo-lutionary selection, and number of domestication events. Therefore, identification of domestication-related gene (DRG) candidates is one of the significant challenges in crop genetics. Most DRGs are identified through quantita-tive trait locus mapping along with candidate gene cloning and linkage disequilibrium (LD) analysis using genome-wide association studies. More recently, genome-wide variation analysis based on whole-genome resequencing

of domesticated and wild plants has been used to identify DRGs in cereals and legumes (Chung et al. 2014; Huang et al. 2013; Hufford et al. 2012; Zhou et al. 2015). Selec-tion during domestication frequently leads to a differen-tial loss of genetic diversity at specific genes in targeted genomic regions that control the trait subject to selection. As genetic bottlenecks arise, the advantageous allele is allowed to increase the frequency during selection, and many of the existing genetic variations within and/or around targeted genes are removed from the population in a process called selective sweep (Olsen and Wendel 2013). Thus, searching for genetic bottlenecks associated with losses in variation enables the identification of specific genes or mutations that underlie domestication-related traits. A high-quality reference genome sequence can greatly facilitate genome-wide variation studies for crop improvement. Several methods were developed to identify DRG candidates using variation data. Cross-population composite likelihood ratio test for allele frequency differ-entiation at linked loci was performed to detect selective sweeps (Chen et al. 2010; Hufford et al. 2012; Zhou et al. 2015). Fixation index (Fst) measured difference between two populations and was used to identify artificial selec-tion events in population (Baute et al. 2015; Maldonado Dos Santos et al. 2016). Reduction of diversity (ROD) value was introduced based on comparison of nucleotide diversity between domesticated and wild populations (Xu et al. 2012b). A combination of ROD and Fst measures has been used to screen the candidate regions under selection, because the genomic region with higher ROD value gave higher Fst value (Cao et al. 2014).

The availability of genome-wide variome data for both wild and cultivated genotypes could contribute greatly to our understanding of evolutionary changes in the radish genome. Identification of functional variation selected in cultivated genotypes during domestication can be facili-tated by comparing genomic variation in cultivated geno-types with those of wild genotypes. In this regard, a fully sequenced and annotated reference genome is critical for genomic study of radish populations. We recently con-structed a chromosome-scale genome assembly of an Asian radish cultivar, WK10039 (2n = 18, 510 Mb), for genet-ics and breeding studies of radish (Jeong et al. 2016). The radish genome (Rs1.0) was assembled into 11,389 scaffolds representing 426.2 Mb which cover more than 98 % of the euchromatic gene space. Chromosome assign-ment of sequence scaffolds by intensive genetic mapping onto the reference genetic map (Mun et al. 2015) enabled assembly of the genome sequence into nine chromosome pseudomolecules covering 344 Mb. Annotation of Rs1.0 identified 46,514 protein-coding genes, of which 93.4 % had expression supports. Comparative genome analysis revealed that the radish genome has triplicate subgenomes

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due to whole-genome triplication. The assembly qual-ity of Rs1.0 is outstanding compared with other radish assemblies reported thus far (Kitashiba et al. 2014; Mitsui et al. 2015; Moghe et al. 2014), based on coverage of the entire genome and gene space, contig number and size, and anchoring of the assembly onto chromosomes. Therefore, Rs1.0 can serve as a radish reference genome sequence for genome-wide comparative and population genomics stud-ies. Moreover, access to the high-resolution Rs1.0 genome will provide opportunities for breeding new cultivars and crop improvement.

In this study, we conducted whole-genome resequenc-ing analysis of 17 cultivated and wild radishes using Rs1.0 as a reference genome sequence and identified CDRs accumulated on the radish genome due to domes-tication. We applied a high-depth resequencing approach (>25× genome coverage) for each genotype rather than low-depth sequencing or a pooling strategy, to avoid miss-ing rare variants. Also, we identified DRG candidates from CDRs using high-quality SNP variation among genotypes. Detailed analysis of variation data between cultivated and wild radishes coupled with expression profiling of the genes in CDRs provided unique insights into the genetic selection events that occurred during evolution of the radish genome.

Materials and methods

Plant materials and sequencing

A total of 13 wild and cultivated genotypes were selected from 48 genotypes based on genetic diversity analyzed by 18 InDel markers, geographical origin, and morpho-logical characteristics (Table 1, Supplemental Fig. S1 and S2). Plant samples were self-pollinated for four gen-erations before resequencing analysis. For high-depth resequencing of cultivated and wild radish genotypes, genomic DNA was extracted from the leaves of each plant using a DNeasy Plant Maxi Kit (Qiagen, Valen-cia, CA, USA) and sequenced by Illumina HiSeq (Illu-mina, San Diego, CA, USA) paired-end (PE) sequencing (2 × 100 bp) of libraries with 500-bp inserts according to the manufacturer’s protocols. At least 25× coverage of sequences was generated for each genotype. Also, raw reads of R. sativus cv. Aokubi and cv. Sayatori (Kitashiba et al. 2014) as well as R. raphanistrum (Moghe et al. 2014) were downloaded from the National Center for Biotechnology Information (NCBI). All reads were pre-processed to filter adaptor contamination, low quality, PCR duplicates, and ambiguous (N) residues prior to downstream analysis. The NGS QC Toolkit 2.3.3 (Patel

Table 1 Summary of accessions and Illumina data used in high-depth resequencing analysis

Illumina reads are paired-end reads of 2 × 100 bp

Raphanistroides, Raphanus sativus var. raphanistroides; Wild radish, R. sativus spp.; Raphanistrum, R. raphanistruma NIHHS National Institute of Horticultural and Herbal Science, Korea, NIAS National Institute of Agricultural Sciences, Japan, Dongbu Dongbu Farm Hannong, Co. Ltd., Korea, RDA-GIC, Rural Development Administration-Genebank Information Center, Koreab Genome coverage was calculated with the genome size of WK10039 as 510 Mb (Jeong et al. 2016)

Type Name Root characteristics Origin Source (accession)a Base (Gb) Coverage (X)b

Cultivated WK10039 White, rectangular Korea NIHHS (WK10039) 98.5 192.9

WK10024 Red, transverse elliptic Europe NIHHS (WK10024) 42.2 82.5

Long Scarlet Red, narrow rectangular USA NIAS (JP27291) 13.7 26.9

DB102 Red, circular Europe Dongbu 12.8 25.1

DB104 White, rectangular Korea Dongbu 13.4 26.2

DB109 White, elliptic China Dongbu 14.1 27.7

DB110 Pale green, rectangular China Dongbu 13.1 25.7

DB113 White, long narrow rectangular Japan Dongbu 13.5 26.3

Aokubi White, narrow rectangular Japan Kitashiba et al. (2014) 104.5 204.7

Sayatori White, thin and small Japan Kitashiba et al. (2014) 14.7 28.8

Wild Raphanistroides1 White, branched short obtriangular Japan RDA-GIC (IT234955) 13.9 27.2

Raphanistroides2 White, branched short obtriangular Korea RDA-GIC (IT260989) 14.0 27.3

Raphanistroides3 White, branched short obtriangular Korea RDA-GIC (IT264026) 14.0 27.3

Wild radish1 Pale puple, obtriangular Vietnam RDA-GIC (IT182537) 12.9 25.2

Wild radish2 White, branched obtriangular India RDA-GIC (IT32722) 13.2 25.9

Wild radish3 White, branched long obtriangular India RDA-GIC (IT32723) 14.1 27.2

Raphanistrum Unknown USA Moghe et al. (2014) 20.0 39.1

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and Jain 2012) was used to filter single-end reads using the criteria of 80 % of base pairs having a minimum PHRED quality of 30. Also, the last 20 base pairs of second reads were removed in case of a sudden drop of PHRED quality compared to initial reads.

Read mapping and variation detection

The filtered reads were aligned to Rs1.0 as well as chlo-roplast and mitochondria DNAs using BWA-MEM 0.7.9a (http://arxiv.org/pdf/1303.3997v2.pdf) with parameters of −k13, −c1000, −r10, and −v1. Duplicate alignments were removed by the MarkDuplicates module in Picard 1.114 package (http://broadinstitute.github.io/picard/). To select highly confident alignment, we used stringent filtering parameters of mapping quality (MQ) ≥40 and 99.99 % probability. Realignment around short InDels and genotyping were performed using IndelRealigner and UnifiedGenotyper modules in GATK 3.1.1 (McKenna et al. 2010). Variant filtering parameter for multi-sample genotyping was GQ <20, FS >1.0, and MQ <40. Addi-tional filtering for individual genotyping was performed with the parameters GQ <13, FS >1.0, MQ <40, and DP ≥10. SnpEff 2.0.5 (Cingolani et al. 2012) was used for gene annotation. Variants with InDels, multi-allelic sequence data, and a miss rate greater than 0.5 were removed, and BEAGLE 3.3.2 (Browning and Browning 2007) was used for haplotype analysis. For SNP varia-tion analysis, SNPs without missing sites were selected for further analysis. Because the plant samples were inbred lines and most of the heterozygous SNPs were false positive, only homozygous sites were selected, and pairwise distance matrix was calculated by count-ing total numbers of different alleles between two geno-types using the neighbor joining algorithm with Kimura’s 3-parameter distance model implemented in the APE package (Paradis et al. 2004). MEGA6 (Tamura et al. 2013) was used to draw phylogenetic trees. Pairwise dis-tance matrix was calculated by counting total numbers of different alleles between two genotypes, and multidi-mensional scaling (MDS) for two dimensions was per-formed by R script using the pairwise distance matrix. The MDS plots were drawn using ggplot2 (http://ggplot2.org). To draw LD decay plots, all pairwise correlations between distant SNPs were calculated, and fractions of correlated SNPs were sorted based on their genomic distances. Population genomics parameters, such as Fst [(πbetween−πwithin)/πbetween], nucleotide diversity (θπ), Wat-terson estimator (θω) and ROD (1 − πcultivated/πwild), were calculated as defined previously (Xu et al. 2012b) using a custom script coded by Python programming language.

Identification of candidate domestication regions and expression analysis

Genomic bins were searched in 20 kb windows and those with at least 10 segregating sites for wild and cultivated genotypes were further analyzed. CDRs were selected based on an ROD along with Fst method (Cao et al. 2014; Xu et al. 2012b). All genes in genomic bins across the genome that fell into the criterion with at least one read aligned onto the gene set were selected. Arabidopsis thali-ana orthologs were searched using BLASTX with a cutoff of 1E−4. Expression analysis of the genes in CDRs was performed using Illumina RNA-seq reads that we previ-ously generated (Jeong et al. 2016). PE reads were end-to-end aligned to the coding sequences (CDS) of gene mod-els using Bowtie2 v2.2.3 (Langmead and Salzberg 2012) with default settings. Reads that mapped to multiple loca-tions were excluded. The resulting mapped reads for each gene were normalized using DESeq implemented in the DESeq R/Bioconductor package (Anders and Huber 2010) to obtain gene expression data. The DESeq normalization process estimates scaling factor from the raw data as the median of the ratio, for each gene, of its read count that can be used in downstream statistical analysis procedures such as the detection of differential expression. The data of three biological replicates were pooled, and the average reads per kilobase per million mapped reads (RPKM) val-ues for genes were extracted and analyzed. Patterns of gene expression between tissues and during root development were analyzed using hierarchical clustering analysis of R. Overrepresented gene functions and biological process annotations were identified in each group using Pathway Studio Plant (http://plant.pathwaystudio.com).

Root anatomy

To investigate morphological characteristics during root development, radish roots were examined every week after germination for 10 weeks. Sixty seeds of R. sativus cv. WK10039 were sown in commercial soil (Soil for horti-cultural crops; Dongbu Farm Hannong, Seoul, Korea) and grown in a controlled growth room at 22 °C under a 16-h light and an 8-h dark cycle. Taproots were divided into three parts (top, middle, and bottom) by cutting the root transversely (at two equidistant sites) along its vertical axis. Top sections of roots were collected every week for par-affin sectioning. Root tissues were fixed in FAA solution [50 mL ethanol, 5 mL glacial acetic acid, 10 mL formalde-hyde (37–40 %), 35 mL distilled water] and embedded in paraffin (Paraplast X-TRA, Fisher, NJ, USA) according to modified protocols (Kerk et al. 2003; Ruzin 1999). Paraffin

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sections of roots were cut to a thickness of 10–15 μm using a rotary microtome (RM2235, Leica, Nussloch, Germany). Paraffin slices were dried at 37 °C and rehydrated using xylene, ethanol, and distilled water. All sections were stained in 0.05 % (v/v) toluidine blue O (pH 8.0–8.6), and observed under a light microscope (BX 53F-32S, Olympus, Tokyo, Japan). Images were recorded using a digital cam-era (SPOT RT3 Color; SPOT Imaging Solutions, Sterling Heights, MI, USA).

Accession numbers

All the resequencing data generated in this study have been deposited in the European Nucleotide Archive of EMBL-EBI under accession number of ERP012228 (sample acces-sions ERS853248 to ERS853260). Also, the reference genome assembly (GCA_000801105.2) and relevant infor-mation used in this study can be queried and downloaded from the NCBI BioProject PRJNA239785 and the Radish Genome Database at http://radish-genome.org.

Results

Sequencing and read mapping

To study genomic diversity of R. sativus species, we rese-quenced 13 wild and cultivated genotypes, which were

selected from 48 genotypes based on genetic diversity dis-played by 18 genetic markers (Supplemental Fig. S1) along with geographical origin and morphological characteristics (Table 1). We compared them with Rs1.0 of WK10039 and two (R. sativus cv. Aokubi and cv. Sayatori; Kitashiba et al. 2014) previously reported whole-genome sequences. In this analysis, the R. raphanistrum genome (Moghe et al. 2014) was used as an outgroup. In total, sequence data from ten cultivated and seven wild genotypes’ genomes were ana-lyzed (Table 1). The cultivated genotypes that originated from Europe, Asia, and America have a rectangular- or round-type swollen taproot that is white to red in color, whereas the wild genotypes collected from Asia have highly branched thin roots (see Fig. 1a and Supplemental Fig. S2). At least 97.6 % of PE reads were successfully mapped onto the reference Rs1.0 genome indicating that Rs1.0 covers a wide range of Raphanus genomes including R. raphanis-trum (Table 2). However, the PE reads of WK10039 were unable to cover the remaining 3.3 % (12.1 Mb) of the unmapped region. When the overall read coverage was considered for other genotypes, 11.7–20.4 % of the refer-ence genome (43.5–75.7 Mb) was not covered by any of the reads investigated. Approximately 61.6–73.4 % of unmapped regions in Rs1.0 were characterized as repeti-tive sequences, consisting primarily of long terminal repeat (LTR) retrotransposons, unclassified DNA transposons, and simple sequence repeats. In contrast, less than 0.2 % of the unmapped regions were genic in nature.

a DB109

WK10039

DB104

DB113

Aokubi

Raphanistroides 1

Raphanistroides 3

Wild radish 3

Wild radish 2

DB102

Long Scarlet

Raphanistrum

DB110

WK10024

Sayatori

Raphanistroides 2

Wild radish 1

0.05

culti

vate

d I

wild

cu

ltiva

ted

II

b

cultivated I wild cultivated II

Dimension 1

Dim

ensi

on 2

Fig. 1 Genomic relationship between genotypes of R. sativus. a A neighbor joining tree of nuclear genomes based on high-quality SNPs/InDels for three tentative groups of R. sativus genotypes; cul-tivated I, cultivated II, and wild, with R. raphanistrum serving as

an outgroup. Photographs of a representative plant from each group grown in the field for 2 months are shown in the right margin. b Mul-tidimensional scaling of cultivated (blue circle symbol and red square symbol) and wild (green triangle symbol) genotypes

1802 Theor Appl Genet (2016) 129:1797–1814

1 3

Tabl

e 2

Map

ping

sta

tistic

s of

Illu

min

a re

ads

(2 ×

100

bp)

ont

o th

e R

s1.0

of W

K10

039

PE

pai

red-

end,

CD

S co

ding

seq

uenc

e, L

TR

long

term

inal

rep

eat

a Rea

ds w

ere

filte

red

usin

g N

GSQ

CTo

olki

tb G

aps

wer

e ex

clud

edc S

mal

l In

Del

s le

ss t

han

30 b

p w

ere

excl

uded

, bec

ause

the

y m

ay c

onta

in p

olym

orph

ic v

aria

tions

. Per

cent

ages

fro

m C

DS

to U

ncla

ssifi

ed D

NA

Tra

nspo

son

are

obta

ined

by

divi

sion

of

tota

l un

-ga

pped

bas

es (

371,

607,

736

bp)

Gen

otyp

eTo

tal b

ases

(bp

)To

tal r

eads

Map

ping

rat

e (%

)U

nmap

ped

regi

on (

min

. 30

bp)c

PESi

ngle

Unm

appe

dU

ncov

ered

ge

nom

e (%

)

Tota

l bas

es

(bp)

bC

DS

(%)

Rep

eat

regi

on

(%)

Sim

ple

repe

at

(%)

LTR

ret

ro-

tran

spos

on

(%)

Non

-LT

R

retr

o-tr

ansp

oson

(%

)

DN

A

tran

spos

on

(%)

Unc

lass

ified

D

NA

tr

ansp

oson

(%

)

WK

1003

9a98

,545

,653

,540

487,

849,

770

99.4

70.

350.

183.

2512

,079

,483

0.09

45.9

716

.53

16.6

90.

010.

3111

.76

WK

1002

4a42

,162

,250

,222

208,

724,

011

98.8

70.

750.

3813

.19

49,0

73,1

270.

1567

.39

10.7

940

.20

1.98

1.78

11.2

5

Lon

g sc

arle

t13

,726

,325

,234

71,6

33,4

8798

.91

0.73

0.37

13.0

648

,573

,095

0.15

68.4

310

.89

40.4

62.

031.

7711

.73

DB

102

12,8

30,0

47,8

7666

,781

,528

98.9

30.

710.

3615

.27

56,8

10,1

160.

1569

.20

10.6

741

.24

1.87

2.06

11.7

8

DB

104

13,3

66,0

58,4

4069

,708

,400

99.3

70.

420.

2116

.56

61,6

04,1

980.

1867

.54

10.8

539

.71

1.85

2.05

11.5

8

DB

109

14,1

30,2

78,4

4473

,931

,562

99.2

80.

490.

2516

.73

62,2

47,1

500.

1868

.39

10.5

540

.93

1.99

2.04

11.3

7

DB

110

13,1

30,7

81,5

6068

,473

,340

98.8

50.

770.

3916

.55

61,5

52,3

160.

1867

.82

10.4

040

.51

1.84

2.04

11.5

3

DB

113

13,4

58,8

13,5

2870

,215

,604

99.3

80.

420.

2116

.61

61,7

87,8

150.

1867

.54

10.7

839

.68

1.94

1.96

11.5

8

Aok

ubia

104,

541,

722,

762

517,

533,

281

98.6

40.

900.

4612

.29

45,7

06,6

370.

1961

.58

8.60

37.5

61.

961.

8410

.44

Saya

tori

14,7

01,9

65,4

0073

,509

,827

97.6

01.

580.

8216

.92

62,9

38,8

140.

1769

.69

10.8

041

.40

1.93

2.10

11.8

0

Rap

hani

stro

ides

113

,893

,610

,702

68,7

80,2

5199

.37

0.43

0.21

12.9

448

,138

,690

0.17

67.3

511

.06

39.6

11.

751.

9611

.42

Rap

hani

stro

ides

213

,962

,613

,700

69,1

21,8

5099

.38

0.42

0.21

12.5

546

,680

,747

0.16

67.0

610

.99

39.4

41.

801.

8911

.48

Rap

hani

stro

ides

313

,963

,002

,550

69,1

23,7

7599

.36

0.43

0.22

12.1

745

,266

,958

0.16

65.7

311

.27

38.1

11.

601.

8311

.47

Wild

rad

ish1

12,8

92,5

76,9

3467

,235

,967

99.2

90.

470.

2411

.68

43,4

54,1

800.

1665

.18

11.1

337

.42

1.82

1.93

11.3

5

Wild

rad

ish2

13,2

21,7

97,0

4868

,966

,374

99.2

00.

530.

2711

.80

43,9

15,5

900.

1666

.76

11.0

639

.08

1.93

1.79

11.4

7

Wild

rad

ish3

14,1

31,1

68,3

5869

,956

,279

99.2

80.

480.

2511

.81

43,9

18,3

680.

1566

.29

11.2

138

.23

1.88

1.96

11.5

5

Rap

hani

stru

ma

19,9

71,2

07,0

0099

,856

,035

98.4

21.

040.

5420

.36

75,7

34,4

030.

1373

.43

11.6

542

.72

2.16

2.24

12.6

9

1803Theor Appl Genet (2016) 129:1797–1814

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Genetic selection of Asian cultivated radish

A total of 4,033,588 homozygous SNPs/InDels were iden-tified by multi-sample genotyping of all 17 resequencing samples (Table 3). The heterozygous SNP rate for each genotype (proportion of heterozygous SNPs in a genome) was less than 0.04 %, with one heterozygous variant for every 2500 bp in the genome on average. WK10039 itself mapped onto the Rs1.0 showed 33,153 SNPs/InDels, 94 % of which were located in repetitive sequence regions, pre-sumably due to sequencing or assembly errors as well as highly similar repetitive sequences widespread in the genome. R. raphanistrum showed the most diverse geno-types with 1,682,946 SNPs/InDels (40 % out of total num-ber). Interestingly, European/American red root cultivars such as WK10024, Long Scarlet, and DB102 had almost twice as many SNP/InDel variants, whereas there were no differences between Asian white root cultivars and Asian wild genotypes. The transition/transversion (Ti/Tv) ratio in R. sativus species was 1.41–1.45, which was slightly higher than that of B. napus (1.39) and B. rapa (1.0–1.45) reported previously (Bus et al. 2012; Park et al. 2010). Pairwise distances analysis using the neighbor joining algorithm and MDS also indicated that the Asian geno-types (cultivated I and wild) were more closely related to each other than European/American cultivars (cultivated II) (Fig. 1). Cultivated I had the biggest LD decay curve followed by wild and cultivated II genotypes, respectively (Supplemental Fig. S3). Estimation of genome diversity values using θπ (degree of polymorphism within a popu-lation) and θω (estimating mutation rate within a popula-tion) for each subgroup demonstrated that the genomic differentiation of cultivated II (θπ = 1.22 × 10−3 and θω = 1.64 × 10−3) was >1.4 times higher than that of cul-tivated I (θπ = 0.85 × 10−3 and θω = 0.94 × 10−3) with respect to the entire genome, whereas those of wild gen-otypes (θπ = 0.97 × 10−3 and θω = 1.11 × 10−3) were slightly higher than cultivated I (Supplemental Table S1). Similarly, the genotype difference calculated as Fst was lowest between cultivated I and wild (Fst = 0.10) but high-est between cultivated I and cultivated II (Fst = 0.37; Sup-plemental Table S2).

The genomic regions putatively selected during domes-tication can be speculated by several independent meas-ures. For example, reduced genomic variations within spe-cific genomic regions provide evidence of domestication, because continuous selection reduces genomic diversity around favored alleles having advantageous traits. These regions can be identified by evaluating ROD along with Fst (Cao et al. 2014; Xu et al. 2012b). We, thus, sought to identify regions putatively selected during domesti-cation of the Asian cultivars based on comparison with Asian wild genotypes using a 20-kb genomic bin, which

covered approximately 2–3 genes within a given genomic region (Fig. 2). In the previous studies from rice (Xu et al. 2012b) and soybean (Chung et al. 2014), ROD cutoff val-ues were selected to identify CDRs covering 5–10 % of the genomes. However, considering low genomic diversity between Asian genotypes (Fst = 0.10), we applied a strict cutoff parameter of ROD ≥0.95 and Z(Fst) ≥1.5 to select CDRs representing approximately 1 % of protein-coding genes of the genome (Supplemental Fig. S4). The distri-bution of genomic bins for −log10(1 − ROD) and Z(Fst) showed that most of the bins distributed near-zero values in Y axes, indicating that the difference between any two gen-otypes was small. Overall, CDRs were widespread across the genome regardless of polyploidy events. The longest CDR was located in R2 (140 kb), comprising 13 protein-coding genes. A total of 512 genes (1.1 % of the protein-coding genes) in 153 CDRs were identified, and approxi-mately 23 % of the genes were on chromosome R2, while R3 contained only 5 % of these genes (Supplemental Table S3).

Characterization of the genes in candidate domestication regions

Database search of 512 genes in CDRs detected homologs for 425 genes, and the remaining 87 genes were assigned as radish-specific. BLASTP searching of the 512 genes against known domestication genes from various crop spe-cies (E value cutoff at 1E−10, query and subject coverage >40 %) identified five radish genes homologous to cell wall invertase related to grain filling in rice, MYB transcrip-tion factors for coloration in orange, soybean, and grape, and MADS box flowering time genes in maize, barley, and B. rapa (Supplemental Table S4). To better understand the functional roles of the genes in CDRs for radish, we per-formed functional annotation of the genes based on gene ontology (GO). Functional enrichment analysis based on GO databases demonstrated that the most frequent Biologi-cal Process terms among the genes in CDRs were “other cellular processes” and “other metabolic processes” fol-lowed by “response to stress.” Likewise, the three most frequent Molecular Function terms were “other binding,” “hydrolase activity,” and “protein binding,” while the Cellu-lar Component terms consisted of “other cytoplasmic com-ponents,” “other intracellular components,” and “nucleus” (Fig. 3). Overrepresented groups of genes functioning in common signaling pathways and gene expression network were identified using network pathway mapping based on the Pathway Studio Plant. Network analysis of 398 A. thaliana orthologs for 512 genes in CDRs of radish with additional expanded connections identified several highly associated genes involved in processes of hormone action (ARAC1, KNAT2, and EIL1), gene expression (HY5, HFR1,

1804 Theor Appl Genet (2016) 129:1797–1814

1 3

Tabl

e 3

Sum

mar

y of

hom

ozyg

ous

SNP

and

InD

el v

aria

tions

in c

ultiv

ated

and

wild

rad

ishe

s

Rap

hani

stro

ides

, Rap

hanu

s sa

tivu

s va

r. ra

phan

istr

oide

s; W

ild r

adis

h, R

. sat

ivus

spp

.; R

apha

nist

rum

, R. r

apha

nist

rum

a Het

eroz

ygou

s SN

P ra

te, p

ropo

rtio

n of

het

eroz

ygou

s SN

Ps in

a g

enom

eb T

i, tr

ansi

tion;

Tv,

tran

sver

sion

c Var

iant

s fr

om W

K10

039

wer

e ex

clud

ed

Type

sN

ame

SNP

InD

elSN

P +

InD

elO

vera

ll

vari

atio

nH

eter

o-T

i/Tvb

Sile

nce

Non

sens

eM

isse

nse

Splic

ing

site

In-f

ram

eFr

ames

hift

Cod

on c

hang

eIn

tron

Non

-gen

icSN

P ra

te (

%)a

Cul

tivat

edW

K10

039

163

1022

130

1438

013

1,14

531

,177

33,1

530.

010.

76

WK

1002

473

,708

568

49,8

0060

32,

093

2,01

31,

317

62,1

6577

9,07

397

1,34

00.

021.

41

Lon

g Sc

arle

t68

,347

449

44,1

4452

31,

926

1,60

91,

210

51,7

6062

8,97

179

8,93

90.

031.

42

DB

102

77,3

3548

549

,170

533

2,13

01,

691

1,27

957

,463

679,

097

869,

183

0.04

1.41

DB

104

34,7

9020

821

,682

261

995

934

554

23,1

8227

5,40

435

8,01

00.

011.

44

DB

109

45,0

7629

528

,435

338

1,25

81,

115

754

30,7

5837

6,54

448

4,57

30.

011.

43

DB

110

35,9

0421

122

,601

281

1,01

888

664

324

,002

291,

464

377,

010

0.01

1.42

DB

113

42,3

4324

926

,084

301

1,18

21,

039

766

29,0

4134

4,62

344

5,62

80.

011.

42

Aok

ubi

44,5

0634

129

,731

361

1,33

21,

379

914

34,3

6445

3,36

056

6,28

80.

011.

41

Saya

tori

40,4

7628

726

,055

302

997

977

632

31,2

3538

4,29

348

5,25

40.

011.

42

Wild

Rap

hani

stro

ides

135

,641

239

23,0

2228

296

796

460

226

,436

323,

870

412,

023

0.02

1.42

Rap

hani

stro

ides

230

,487

227

19,9

1525

077

390

351

622

,745

296,

135

371,

951

0.02

1.44

Rap

hani

stro

ides

337

,491

253

23,9

5927

892

598

961

427

,251

340,

445

432,

205

0.02

1.43

Wild

rad

ish1

30,8

7417

119

,401

233

795

838

541

22,0

9227

2,37

134

7,31

60.

021.

43

Wild

rad

ish2

35,4

3821

923

,084

271

988

898

619

26,6

0433

2,56

342

0,68

40.

031.

44

Wild

rad

ish3

36,6

8223

523

,925

279

1,05

599

965

128

,823

358,

197

450,

846

0.03

1.45

Rap

hani

stru

m12

7,16

71,

062

86,2

311,

122

3,11

62,

951

1,89

812

1,92

51,

337,

474

1,68

2,94

60.

021.

37

Tota

lc29

6,57

82,

898

206,

187

2,52

18,

426

8,01

85,

280

256,

192

3,24

7,48

84,

033,

588

–1.

40

1805Theor Appl Genet (2016) 129:1797–1814

1 3

and TIFY1), and transport (NRT2:1 and SKD1) (Fig. 4). For biochemical pathway of AraCyc, genes implicated in glu-cosinolate biosynthesis (F12G12.14, MQD19.2, CYP83A1, and SOT7), glutathione biosynthesis (GSH1 and GSH2), and sucrose and starch metabolism (F5A18.9, F23N19.3, APL2, and CWINV5) were also identified (Supplemental Table S5).

Expression of domestication‑related gene candidates in radish roots

To determine the expression characteristics of the 512 radish genes, we used RNA-seq analysis of each gene in five tissues, namely, seedling, leaf, root, anther, and pistil. All but seven of the genes were expressed in at least one of the tissue types investigated. A total of 475 genes were expressed in all tissues, and only 6 genes (4 genes at vege-tative tissues and 2 genes at anther) exhibited tissue speci-ficity (Fig. 5 and Supplemental Table S6). Of particular interest, none of the genes were preferentially expressed in the root, suggesting that the genes in CDRs play roles not only in the root but also in aerial parts of radish. Con-sidering the fact that root traits such as size, shape, and nutrient content are highly important for breeding radish cultivars, we also investigated gene expression during root development (Fig. 6). To correlate gene expression with specific stages of development, morphological changes occurring in root were monitored for 10 weeks from ger-mination (Fig. 6a; Supplemental Fig. S5). Initially, root diameter did not increase from germination to 2-week-old plants, and cross-sections at this stage showed a central protostele consisting of primary phloem cells and pro-toxylem. At 3 weeks after germination, roots started to enlarge slowly, and a pericycle was evident between the stele and cortex in 4-week-old roots. The stele expanded outward into the cortex cell layer as a result of secondary growth at 5 weeks post-germination, and the cortex cells gradually collapsed up to 8 weeks post-germination. Sub-sequently, the taproot was filled with xylem and phloem tissues, which provide cells for thickening or storage. The root diameter increased rapidly approximately three-fold by 9 weeks post-germination, and a secondary cambium was evident in 10-week-old roots. Expression profiling at 8 weeks of root development followed by hierarchical clustering analysis resolved the 512 genes in CDRs into 8 clusters. Figure 6b shows an overview of expression for each of the 8 clusters presented as a heatmap, with a graph depicting aggregate average expression values for each time point (Supplemental Table S7). According to our analysis, two groups of genes were transcription-ally induced or repressed in response to taproot develop-ment. Although the average expression level was differ-ent, genes in cluster 3 and 5 (group I) were upregulated,

whereas those in cluster 6, 7, and 8 (group II) were down-regulated according to root development.

To identify overrepresented groups of genes functioning in common biological processes correlated with root devel-opment, we utilized Pathway Studio Plant and manually curated the output. Here, we wish to emphasize the nota-ble transcriptional responses of genes associated with root architecture and cellular metabolism during development (Fig. 7 and Supplemental Table S8). Specifically, group I genes are implicated in vascular tissue development includ-ing phloem and xylem development, negative regulation of lateral root development, and cell wall loosening. Genes related to cytokinin and auxin signaling, oxidative stress, and sugar and starch synthesis were also included in this group. The expression of most genes was highly up-regu-lated between 5 and 6 weeks post-germination, consist-ent with the beginning expansion of the stele. In contrast, group II was enriched for genes involved in lateral root and root hair development, cell wall synthesis, and sugar degra-dation. Genes for heavy metal ion or nitrate transport and glucosinolate synthesis were also enriched in this group. Downregulation of these genes may be coordinated to swell the taproot, to reduce lateral root and root hair develop-ment, and to lower accumulation of toxic metal ions and bitter or pungent metabolites.

Discussion

Decoding the evolution history of a crop species is a major challenge. In this study, we generated high-depth sequence data for diverse radish genotypes to elucidate evolutionary events related to domestication. Resequenc-ing analysis revealed that the reference genome coverage by reads from different genotypes including R. raphanis-trum (98–99 %) was higher and much less variable than those of soybean (86–97 %; Chung et al. 2014) and rice (79–94 %; Xu et al. 2012b). This result indicated that the overall portion of genotype-specific or diverged sequences between the genotypes and even between species (R. sati-vus vs. R. raphanistrum) is smaller in Raphanus com-pared with other crop species. Considering the sequence characteristics as shown in Table 2, we assumed that most regions of Rs1.0 uncovered by resequencing analysis may have originated from repetitive mobile elements, which may have been subject to recent movement and mutation. Otherwise, resequencing data (Illumina sequencing) could not completely cover the reference genome assembly (454 and PacBio RSII sequencing; Jeong et al. 2016) presum-ably due to differences in sequencing chemistry. Based on variation data, cultivated radishes appear to have been domesticated independently both in Asia and Europe from their respective wild relatives. With respect to inference of

1806 Theor Appl Genet (2016) 129:1797–1814

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R1 R2 R3 R4 R5 R6 R7 R8 R9 R0

b

Z(F s

t)

R1 R2 R3 R4 R5 R6 R7 R8 R9 R0

d

(wild

) 10

-3

R1 R2 R3 R4 R5 R6 R7 R8 R9 R0

a

-log 1

0(1-

RO

D)

c

R1 R2 R3 R4 R5 R6 R7 R8 R9 R0

(cul

tivat

ed I)

10

-3

e

1807Theor Appl Genet (2016) 129:1797–1814

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the origin of domestication of cultivated radishes and con-sistent with the results of the present study, Yamane et al. (2009) reported that there have been at least three inde-pendent domestication events, and also that the Asian cul-tivated type is distinct from the Mediterranean (European) cultivated type based on 25 chloroplast SSR loci. Although the number of accessions was limited, our data suggested that Asian cultivated and wild genotypes are distinct from the European/American cultivated types, and that Asian cultivated types are closely related to Asian wild geno-types. , the wild relatives of Asian cultivated types might be a wild species of R. sativus including R. sativus var. raphanistroides rather than wild R. raphanistrum. Mul-tiple domestication of radish might be a result of parallel evolution of functionally equivalent phenotypes, so called

Fig. 3 Functional classification of 512 genes in CDRs based on gene ontology mapping using GO Biological Process, GO Cellular Component, and GO Molecular Function term databases

Fig. 2 Genome-wide analysis of nucleotide diversity and selec-tion. Distribution of reduction of diversity (ROD) values (a) and Z-transformed fixation index (Fst) values (b) for cultivated I relative to wild genotypes in 20-kb windows drawn based on 20 % sliding. ROD = 0.95 corresponds to −log10(1 − ROD) = 1.3. Distribution plots showing θπ for cultivated I (c) and Asian wild genotypes (d). ROD is defined as 1 − πcultivated/πwild. Because cultivated I and Asian wild genotypes are closely related to one another (Fst = 0.10), most of dots locate zero in Y axis (a, b). Candidate domestication regions (CDRs) are selected based on the following criteria: ROD ≥0.95 and Z(Fst) ≥1.5. e Location of genes in CDRs identified in the rad-ish genome. Black lines on the outside circle represent the genes in CDRs. Chromosomes are shown in three colors representing differ-ent fractionation patterns of triplicate sub-genome blocks (red, least fractionated blocks, green, medium fractionated blocks; blue, most fractionated blocks; Jeong et al. 2016). Inner circle shows intercon-nection of paralogs in the radish genome with colored lines. Size bars indicate 10 with 5 Mb steps. R1–R9 indicate chromosome pseu-domolecules, whereas R0 represents unanchored scaffolds

◂

1808 Theor Appl Genet (2016) 129:1797–1814

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‘parallel adaptation’ (Ralph and Coop 2010). Meanwhile, the genetic bottleneck by domestication of Asian radish is likely not extensive, because the genetic differentiation between Asian cultivated types and Asian wild genotypes (Fst = 0.10) is approximately four times lower than that between Asian cultivated types and European/Ameri-can cultivated types (Fst = 0.37). Consistently, a lack of significant genetic bottlenecks in radish was reported in a previous study based on diversity of 8 allozymes in 24 open-pollinated cultivated and 4 wild radishes, where wild populations were clustered within cultivars (Ellstrand and Marshall 1985). The relatively small number of genetic bottlenecks in Asian cultivated types compared to Asian wild genotypes can probably be a result of bidirectional gene flow between cultivated and wild genotypes due to outcrossing or breeding practices as well as short dura-tion of domestication. Small genetic bottleneck was also observed in another biennial root crop, carrot, where intro-gression from wild carrots reduced genetic diversity of cultivars (Iorizzo et al. 2013; Rong et al. 2014).

One of the recent interests in crop researches is improv-ing nutrient efficiency for sustainable agriculture. Nutrient efficiency of crop species can be enhanced by changing root architecture (reviewed in Li et al. 2016). Compared to most annual crop species, cultivars of biennial root crops includ-ing radish and carrot develop less branched fleshy root than wild accessions. This finding suggests that selection during domestication of root crops might have enhanced root swelling for nutrient acquisition but suppressed root branching or lateral root formation. Therefore, genome-wide analysis of CDRs in radish provides an opportu-nity to identify genes involved in plant root architecture changes or improvement of root traits in crops. In the pre-sent study, we identified 512 genes in CDRs. These genes have not been fully validated, and further efforts will be pursued through an integrative analysis based on genome-wide association study and transcriptome-wide association study. Among the 512 DRG candidates, only 5 matched to domestication genes identified in cereal, legume, fruit, or vegetable crop species. This result suggested that CDRs

HY5

NRT2:1

EIL1 TIFY1

HFR1

KNAT2

ARAC1

SKD1

Fig. 4 Network diagram of 398 A. thaliana orthologs for 512 genes in CDRs of radish. Network was predicted by Pathway Studio Plant. Shapes of lines indicate association between two proteins by binding,

direct regulation, promotor binding, and regulation. Highly associ-ated genes (ARAC1, NRT2:1, HY5, SKD1, HFR1, KNAT2, EIL1, and TIFY1) are marked

1809Theor Appl Genet (2016) 129:1797–1814

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may contain novel domestication genes of cultivated rad-ish. Indeed, the majority of domestication genes have been reported from cereals, legumes, and fruit crops distantly related to radish. With respect to the 5 DRG candidates homologous to known domestication genes from other crop species, two were homologs of rice GIF1, which is a cell wall invertase that functions in starch filling in rice grain, a strong sugar sink. The storage taproot is a major sink in radish which begins to develop early as a result of thick-ening of the hypocotyl. Invertase and sucrose synthase are believed to be key enzymes influencing sink activity and development of storage roots including radish (Rouhier and Usuda 2001; Sergeeva et al. 2006; Sturm and Tang 1999; Usuda et al. 1999). Recent RNA-seq analysis during tap-root development of a Japanese cultivar revealed transcrip-tional activation of sucrose synthases and low expression of cell wall and cytoplasmic invertases, but no vacuolar invertase was identified in the genome (Mitsui et al. 2015). Incidentally, the radish invertases identified as DRG candi-dates in this study included both cell wall (Rs229260) and vacuolar types (Rs487190). The overall expression level of the cell wall type invertase was relatively low, whereas the vacuolar type was highly expressed from the seedlings stage to 3-week-old roots, but decreased thereafter dur-ing root thickening. This pattern of expression was corre-lated with starch degradation related genes (Rs409770 and Rs056530), but opposite to upregulation of a starch synthe-sis related gene (Rs021360), suggesting that domestication

selection had a significant impact on the high sugar and starch content in the radish storage taproot. Similar expres-sion patterns for genes related to carbohydrate metabolism have been reported in several crop species including potato (Kloosterman et al. 2005), sweet potato (Firon et al. 2013), and Rehmannia glutinosa (Sun et al. 2015), consistent with their development of large storage organs.

Of particular importance, one of the main biological processes that pathway analysis revealed for certain DRG candidates was related to root architecture. Growth of the taproot in radish begins with thickening of the hypocotyl and the upper part of the root as a result of radial growth in the cambial zone (Ting and Wren 1980). Auxins and cytokinins have been suggested to play an important role in cambial growth of storage roots. Recently, R. sativus orthologs of A. thaliana cytokinin-related genes enriched in cambium were surveyed (Jang et al. 2015), although none of these genes appeared in our list of DRG can-didates, suggesting that the genes responsible for cam-bium growth were not selected or fixed by domestication. Instead, the DRG candidates consisted primarily of genes involved in root growth and lateral root development. One category of genes regulating hypocotyl growth and root development included photomorphogenesis-promoting fac-tors HY5 (Rs160560) and HFR1 (Rs252530). These genes were expressed from seedlings to swollen root without a significant expression change. Other highly associated genes included NRT2:1 (Rs408390) and EIL1 (Rs107440).

1

2

3

4

5

6

7

8

Seedling Leaf Root Anther Pistil

Cluster 1 Cluster 2

Cluster 3 Cluster 4

6retsulC5retsulC

8retsulC7retsulC

012345

012345

012345

012345

012345

012345

012345

012345

Fig. 5 Expression of 512 genes in CDRs in various radish tissues. Hierarchical clustering of 512 genes in CDRs based on RNA-seq experiment was performed, where the average RPKM value of a given gene from three independent biological replicates across sam-

ples was used as a normalization factor. The heatmap depicts eight groups of genes showing differential expression patterns. The line graphs show the average relative expression value of all genes in each group

1810 Theor Appl Genet (2016) 129:1797–1814

1 3

As a high affinity nitrate transporter, NRT2:1 represses the initiation of the lateral roots, especially in relation with high nitrate conditions (Remans et al. 2006). Also, NRT2:1 is known to act in a negative feedback loop with ethylene biosynthesis and signaling while EIL1 induced under low nitrate conditions (Zheng et al. 2013). Consistent with these reports, radish NRT2:1 exhibited a dual induction at the young root stage and again during the thickening stage while radish EIL1 expression was gradually decreased. Interestingly, lateral root development under the control of NRT2:1 can be suppressed by high levels of sucrose suggesting developmental crosstalk between nitrogen and carbon in root (Remans et al. 2006). Homologs of A. thali-ana RHD1 (Rs089570), RHD3 (Rs229310), and RHD6 (Rs094790) genes were also identified. RHD3 is a large GTP-binding protein that is evolutionarily conserved and required for regulating the synthesis and expansion of the

cell wall (Hu et al. 2003). Transgenic overexpression of RHD3 homologs in poplar confers overwhelming growth of the main adventitious root with more lateral roots, indicating its roles in lateral root development (Xu et al. 2012a). Therefore, downregulation of radish RHD3 during root development might be related to reduced lateral root development. Also, RHD6 is a bHLH transcription factor that participates in root hair formation (Bruex et al. 2012), whereas RHD1 is a UDP-D-glucuronate 4-epimerase that regulates cell wall composition and sugar storage by alter-ing the partitioning of carbohydrates under limiting nitro-gen conditions (Guevara et al. 2014; Seifert et al. 2002). Because root branching, development of lateral roots, and dense root hair are unfavorable traits in root crops such as radish, we anticipate that the morphological plasticity of root architecture for nutrient availability may be sup-pressed in domesticated cultivars.

a w01w8w6w4w2

co

c pi

x p x co pi x

p

pe c

p

pd sx sp

pd ep ep

co vt pi

ep

012345

012345

012345

012345

012345

345678

012345

012345

Cluster 1 Cluster 2

Cluster 3 Cluster 4

Cluster 5 Cluster 6

Cluster 7 Cluster 8

1

2

3

4

5

6

7

8

1W 2W 3W 4W 5W 6W 7W 8W

b

Fig. 6 Expression of 512 genes in CDRs during root development. a Cross-sections of the radish root. Roots of 1–10-week-old plants were cross-sectioned and investigated. The outer cortex was ruptured and removed, and the periderm was exposed in 8-week-old plants. Size bars represent 500 μm. b Hierarchical clustering of 512 genes in CDRs based on RNA-seq analysis during root development from 1 to 8 weeks, where the average RPKM value of a given gene from

three independent biological replicates across samples was used as a normalization factor. The heatmap depicts eight groups of genes with differential patterns of expression. The line graphs show the average relative expression value of all genes in each group. c cambium, co cortex, ep epidermis, p phloem, pd periderm, pe pericycle, pi pith, sp secondary phloem, sx secondary xylem, vt vascular tissue, x xylem

1811Theor Appl Genet (2016) 129:1797–1814

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It is noteworthy that genes involved in vascular devel-opment, cell wall synthesis and modification, and oxidative stress were also enriched among the genes in CDRs. The swollen taproot consists primarily of secondary xylem and phloem tissues, and upregulation of the vascular develop-ment-related DRG candidates (Rs056148, Rs486510, and Rs423130) was observed beginning with root thickening. In contrast, homologs of TBLs (Rs075060, Rs391720, Rs446230, and Rs528680), UDP-glucosyl transferases (Rs073620, Rs073640, and Rs063070), and galacturono-syltransferases (Rs413400 and Rs116730) or pectinacety-lesterase (Rs431740), which participate in the synthesis of cell wall cellulose, lignin, and pectin, respectively, exhib-ited markedly decreased expression during root thicken-ing. A similar pattern of expression was observed for the cell elongation repressor (Rs208860), whereas expan-sin (Rs560790) was significantly induced at the thicken-ing stage. Downregulation of lignin biosynthesis pathway genes has also been reported in sweet potato (Firon et al.

2013; Sirju-Charran and Wickham 1988) and Rehmannia glutinosa (Sun et al. 2015), in which lignification was pro-posed as a major limitation for tuberization, suggesting that reduction of the lignin biosynthesis pathway facilitates an increased carbon flow into carbohydrate metabolism. Inter-estingly, expression of genes related to oxidative stress was also increased during root development. Peroxidase plays multiple roles such as lignification of cell wall and xylem differentiation, as well as promoting cell wall loosening and cell elongation. These contrasting roles are regulated by multiple internal and external factors (reviewed in Pas-sardi et al. 2004). Considering downregulation of lignin and pectin synthesis pathway genes at the taproot thicken-ing stage, increased expression of peroxidases likely con-tributes to cell elongation and vascular development rather than consolidation of the cell wall in the swollen taproot. In this regard, a less lignified taproot might have been selected during domestication because the cell wall is an important determinant of tissue texture. Indeed, because a swollen or

ba

vascular development Rs056140 vascular development Rs486510 phloem development Rs423130 xylem/phloem formation Rs560790 expansin Rs208860 cell elongation repressor

1w 2w 3w 4w 5w 6w 7w 8w

oxidative stress Rs306040 abiotic stress Rs391740 peroxidase Rs391750 Rs379420 Rs069130 glutathione Rs022310 thioredoxin Rs391350

1w 2w 3w 4w 5w 6w 7w 8w

lateral root / root hair Rs408390 repressor of Rs238900 lateral root initiation Rs022460 Rs510250 Rs425560 Rs107440 lateral root development Rs383990 Rs229310 root hair development Rs094790 root hair initiation

1w 2w 3w 4w 5w 6w 7w 8w

sugar metabolism Rs524940 nucleotidesugar metabolism Rs089570 Rs408410 nucleotidesugar synthesis Rs021360 starch synthesis Rs208770 nucleotidesugar transport Rs062990 sugar transport Rs409770 starch degradation Rs056530 Rs487190 sucrose catabolic process

1w 2w 3w 4w 5w 6w 7w 8w

cell wall Rs472960 cell wall loosening Rs160480 cellulose hydrolysis Rs022350 cell wall biogenesis in vessel Rs075060 cell wall cellulose synthesis Rs391720 Rs446230 Rs528680 Rs528620 lignification Rs073620 lignin synthesis Rs073640 Rs063070 Rs413400 pectin synthesis Rs431740 Rs116730 Rs383870 cell wall patterning

1w 2w 3w 4w 5w 6w 7w 8w

nutrient Rs139150 sulfate transport Rs117990 iron transport Rs414850 Rs229230 copper transport Rs081310 Rs292480 heavy metal transport Rs069190 Rs402190 response to iron Rs450260 nitrate Rs443790 Rs040070 cysteine biosynthesis

1w 2w 3w 4w 5w 6w 7w 8w

cytokinin / auxin

Rs056180 cytokinin signaling Rs428510 cytokinin synthesis Rs150900 auxin-responsive protein Rs423150

1w 2w 3w 4w 5w 6w 7w 8w

glucosinolate Rs433960 myrosinase Rs433990 Rs520310 GS transport Rs212900 GS synthesis Rs413390

1w 2w 3w 4w 5w 6w 7w 8w

Color Key

-1 0 1

Fig. 7 Temporal dynamics of gene expression during root develop-ment. Heatmaps depict expression patterns of selected categories of domestication-related gene candidates related to root architecture (a) and metabolism (b). Heatmap values represent the relative expression

value (Z-transformed average RPKM values; Supplemental Table S8) across time. The horizontal axis is a time course of root development from 1 to 8 weeks

1812 Theor Appl Genet (2016) 129:1797–1814

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enlarged root is often seen in many biennial and perennial plants including wild radishes, the selective advantages of the DRG candidates during domestication of radish con-sisted of a main taproot with few or no branched lateral roots and reduced cell wall rigidity for efficient swelling or favorable taste (i.e. high sugar and low pungent glucosi-nolate content), which are typical characteristics of market-able Asian cultivars. Therefore, the comprehensive func-tional study of the DRG candidates identified in this study will serve as a foundation to delineate their roles during radish taproot development. The molecular markers devel-oped from these genes will be highly useful for background selection of the recurrent parent lines. In conclusion, our results provide an opportunity for sequence-level mapping of genes related to agronomic traits, and will be a valuable resource for phylogenomic and breeding studies of radish, benefitting both plant biologists and breeders.

Author contribution statement JHM and HJY con-ceived the projects, designed research, analyzed data, and wrote manuscript. NK and YMJ performed the experi-ments, analyzed data, and wrote the manuscript. SJ, JK, WJL, KHK, WP, JYK, and JHK performed population genomics and RNA-Seq analyses. GBK, SB, YEK, AC, BY, and YJL participated in data analysis. BMC and YPL prepared plant samples. SBC and BSP participated in man-uscript preparation.

Acknowledgments This work was supported by grants from the Next-Generation Biogreen21 program (PJ01108601 to JHM and PJ01108602 to HJY) and the National Academy of Agricultural Sci-ence (PJ009795 to JHM), Rural Development Administration, Korea. We appreciate Genebank Information Center, RDA, Korea and National Institute of Agricultural Sciences, Japan for providing seeds of radish accessions.

Compliance with ethical standards

Ethical standards The authors declare that the experiments complied with current laws of the country in which they were performed.

Conflict of interest The authors declare that they have no conflict of interest.

References

Abbo S, Pinhasi van-Oss R, Gopher A, Saranga Y, Ofner I, Peleg Z (2014) Plant domestication versus crop evolution: a concep-tual framework for cereals and grain legumes. Trends Plant Sci 19:351–360

Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11:R106

Baute G, Kane N, Grassa C, Lai Z, Rieseberg L (2015) Genome scans reveal candidate domestication and improvement genes in culti-vated sunflower, as well as post-domestication introgression with wild relatives. New Phytol 206:830–838

Becker B (1962) Rettich und Radies. Handb Pflanzenzücht 6:23–78Browning S, Browning B (2007) Rapid and accurate haplotype phas-

ing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084–1097

Bruex A, Kainkaryam R, Wieckowski Y, Kang Y, Bernhardt C, Xia Y, Zheng X, Wang J, Lee M, Benfey P, Woolf P, Schiefelbein J (2012) A gene regulatory network for root epidermis cell differ-entiation in Arabidopsis. PLoS Genet 8:e1002446

Bus A, Hecht J, Huettel B, Reinhardt R, Stich B (2012) High-through-put polymorphism detection and genotyping in Brassica napus using next-generation RAD sequencing. BMC Genom 13:281

Cao K, Zheng Z, Wang L, Liu X, Zhu G, Fang W, Cheng S, Zeng P, Chen C, Wang X, Xie M, Zhong X, Wang X, Zhao P, Bian C, Zhu Y, Zhang J, Ma G, Chen C, Li Y, Hao F, Li Y, Huang G, Li Y, Li H, Guo J, Xu X, Wang J (2014) Comparative population genomics reveals the domestication history of the peach, Prunus persica, and human influences on perennial fruit crops. Genome Biol 15:415

Chen H, Patterson N, Reich D (2010) Population differentiation as a test for selective sweeps. Genome Res 20:393–402

Chung W-H, Jeong N, Kim J, Lee W, Lee Y-G, Lee S-H, Yoon W, Kim J-H, Choi I-Y, Choi H-K, Moon J-K, Kim N, Jeong S-C (2014) Population structure and domestication revealed by high-depth resequencing of Korean cultivated and wild soybean genomes. DNA Res 21:153–167

Cingolani P, Platts A, Wang IL, Coon M, Nguyen T, Wang L, Land SJ, Lu X, Ruden DM (2012) A program for annotating and pre-dicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6:80–92

Ellstrand N, Marshall D (1985) The impact of domestication on distri-bution of allozyme variation within and among cultivars of rad-ish, Raphanus sativus L. Theor Appl Genet 69:393–398

Firon N, LaBonte D, Villordon A, Kfir Y, Solis J, Lapis E, Perlman T, Doron-Faigenboim A, Hetzroni A, Althan L, Nadir L (2013) Transcriptional profiling of sweet potato (Ipomoea batatas) roots indicates down-regulation of lignin biosynthesis and up-regula-tion of starch biosynthesis at an early stage of storage root for-mation. BMC Genom 14:460

George R, Evans D (1981) A classification of winter radish cultivars. Euphytica 30:483–492

Guevara D, El-Kereamy A, Yaish M, Mei-Bi Y, Rothstein S (2014) Functional characterization of the rice UDP-glucose 4-epimerase 1, OsUGE1: a potential role in cell wall carbohydrate partition-ing during limiting nitrogen conditions. PLoS One 9:e96158

Hu Y, Zhong R, Wr Morrison, Ye Z (2003) The Arabidopsis RHD3 gene is required for cell wall biosynthesis and actin organization. Planta 217:912–921

Huang X, Lu T, Han B (2013) Resequencing rice genomes: an emerg-ing new era of rice genomics. Trends Genet 29:225–232

Hufford M, Xu X, van Heerwaarden J, Pyhäjärvi T, Chia J, Cartwright R, Elshire R, Glaubitz J, Guill K, Kaeppler S, Lai J, Morrell P, Shannon L, Song C, Springer N, Swanson-Wagner R, Tiffin P, Wang J, Zhang G, Doebley J, McMullen M, Ware D, Buck-ler E, Yang S, Ross-Ibarra J (2012) Comparative population genomics of maize domestication and improvement. Nat Genet 44:808–811

Iorizzo M, Senalik D, Ellison S, Grzebelus D, Cavagnaro P, Allender C, Brunet J, Spooner D, Van Deynze A, Simon P (2013) Genetic structure and domestication of carrot (Daucus carota subsp. sati-vus) (Apiaceae). Am J Bot 100:930–938

Jang G, Lee J, Rastogi K, Park S, Oh S, Lee J (2015) Cytokinin-dependent secondary growth determines root biomass in radish (Raphanus sativus L.). J Exp Bot 66:4607–4619

Jeong Y-M, Kim N, Ahn B, Oh M, Chung W-H, Chung H, Jeong S, Lim K-B, Hwang Y-J, Kim G-B, Baek S, Choi S-B, Hyung

1813Theor Appl Genet (2016) 129:1797–1814

1 3

D-J, Lee S-W, Sohn S-H, Kwon S-J, Jin M, Seol Y-J, Chae W, Choi K, Park B-S, Yu H-J, Mun J-H (2016) Elucidating the trip-licated ancestral genome structure of radish based on chromo-some-level comparison with the Brassica genomes. Theor Appl Genet 129:1357–1372

Kaneko Y, Matsuzawa Y (1993) Radish (Raphanus sativus L.). Perga-mon Press Ltd., Oxford

Kerk N, Ceserani T, Tausta S, Sussex I, Nelson T (2003) Laser cap-ture microdissection of cells from plant tissues. Plant Physiol 132:27–35

Kitashiba H, Li F, Hirakawa H, Kawanabe T, Zou Z, Hasegawa Y, Tonosaki K, Shirasawa S, Fukushima A, Yokoi S, Takahata Y, Kakizaki T, Ishida M, Okamoto S, Sakamoto K, Shirasawa K, Tabata S, Nishio T (2014) Draft sequences of the radish (Raphanus sativus L.) genome. DNA Res 21:481–490

Kloosterman B, Vorst O, Hall R, Visser R, Bachem C (2005) Tuber on a chip: differential gene expression during potato tuber develop-ment. Plant Biotechnol J 3:505–519

Kopta T, Pokluda R (2013) Yields, quality and nutritional parameters of radish (Raphanus sativus) cultivars when grown in organically in Czech Republic. Hort Sci 40:16–21

Langmead B, Salzberg S (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359

Li X, Zeng R, Liao H (2016) Improving crop nutrient efficiency through root architecture modifications. J Integr Plant Biol 58:193–202

Maldonado Dos Santos J, Valliyodan B, Joshi T, Khan S, Liu Y, Wang J, Vuong T, Oliveira M, Marcelino-Guimarães F, Xu D, Nguyen H, Abdelnoor R (2016) Evaluation of genetic variation among Brazilian soybean cultivars through genome resequencing. BMC Genom 17:110

McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernyt-sky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo M (2010) The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303

Mitsui Y, Shimomura M, Komatsu K, Namiki N, Shibata-Hatta M, Imai M, Katayose Y, Mukai Y, Kanamori H, Kurita K, Kagami T, Wakatsuki A, Ohyanagi H, Ikawa H, Minaka N, Nakagawa K, Shiwa Y, Sasaki T (2015) The radish genome and comprehensive gene expression profile of tuberous root formation and develop-ment. Sci Rep 5:10835

Moghe G, Hufnagel D, Tang H, Xiao Y, Dworkin I, Town C, Con-ner J, Shiu S (2014) Consequences of whole-genome triplication as revealed by comparative genomic analyses of the wild radish Raphanus raphanistrum and three other Brassicaceae species. Plant Cell 26:1925–1937

Mun J-H, Chung H, Chung W-H, Oh M, Jeong Y-M, Kim N, Ahn B, Park B-S, Park S, Lim K-B, Hwang Y-J, Yu H-J (2015) Construc-tion of a reference genetic map of Raphanus sativus based on genotyping by whole-genome resequencing. Theor Appl Genet 128:259–272

Olsen K, Wendel J (2013) A bountiful harvest: genomic insights into crop domestication phenotypes. Annu Rev Plant Biol 64:47–70

Paradis E, Claude J, Strimmer K (2004) APE: analysis of phylogenet-ics and evolution in R language. Bioinformatics 20:289–290

Park S, Yu H-J, Mun J-H, Lee S (2010) Genome-wide discovery of DNA polymorphism in Brassica rapa. Mol Genet Genomics 283:135–145

Passardi F, Penel C, Dunand C (2004) Performing the paradoxical: how plant peroxidases modify the cell wall. Trends Plant Sci 9:534–540

Patel R, Jain M (2012) NGS QC Toolkit: a toolkit for quality control of next generation sequencing data. PLoS One 7:e30619

Ralph P, Coop G (2010) Parallel adaptation: one or many waves of advance of an advantageous allele? Genetics 186:647–668

Remans T, Nacry P, Pervent M, Girin T, Tillard P, Lepetit M, Gojon A (2006) A central role for the nitrate transporter NRT2.1 in the integrated morphological and physiological responses of the root system to nitrogen limitation in Arabidopsis. Plant Physiol 140:909–921

Rong J, Lammers Y, Strasburg J, Schidlo N, Ariyurek Y, de Jong T, Klinkhamer P, Smulders M, Vrieling K (2014) New insights into domestication of carrot from root transcriptome analyses. BMC Genom 15:895

Rouhier H, Usuda H (2001) Spatial and temporal distribution of sucrose synthase in the radish hypocotyl in relation to thickening growth. Plant Cell Physiol 42:583–593

Ruzin S (1999) Plant microtechnique and microscopy. Oxford Uni-versity Press, New York

Seifert G, Barber C, Wells B, Dolan L, Roberts K (2002) Galactose biosynthesis in Arabidopsis: genetic evidence for substrate chan-neling from UDP-D-galactose into cell wall polymers. Curr Biol 12:1840–1845

Sergeeva L, Keurentjes J, Bentsink L, Vonk J, van der Plas L, Koorn-neef M, Vreugdenhil D (2006) Vacuolar invertase regulates elon-gation of Arabidopsis thaliana roots as revealed by QTL and mutant analysis. Proc Natl Acad Sci USA 103:2994–2999

Sirju-Charran G, Wickham L (1988) The development of alternative storage sink sites in sweet potato Ipomoea batatas. Ann Bot 61:99–102

Sturm A, Tang G (1999) The sucrose-cleaving enzymes of plants are crucial for development, growth and carbon partitioning. Trends Plant Sci 4:401–407

Sun P, Xiao X, Duan L, Guo Y, Qi J, Liao D, Zhao C, Liu Y, Zhou L, Li X (2015) Dynamic transcriptional profiling provides insights into tuberous root development in Rehmannia glutinosa. Front Plant Sci 6:396

Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol 30:2725–2729

Ting F, Wren M (1980) Storage organ development in radish (Raphanus sativus L.). 1. A comparison of development in seed-lings and rooted cuttings of two contrasting varieties. Ann Bot 46:267–276

Usuda H, Demura T, Shimogawara K, Fukuda H (1999) Develop-ment of sink capacity of the “storage root” in a radish cultivar with a high ratio of “storage root” to shoot. Plant Cell Physiol 40:369–377

Warwick S (2011) Brassicaceae in Agriculture. In: Schmidt R, Ban-croft I (eds) Genetics and Genomics of the Brassicaceae. Springer, Gatersleben, pp 33–66

Xu M, Xie W, Huang M (2012a) Overexpression of PeRHD3 alters the root architecture in Populus. Biochem Biophys Res Commun 424:239–244

Xu X, Liu X, Ge S, Jensen J, Hu F, Li X, Dong Y, Gutenkunst R, Fang L, Huang L, Li J, He W, Zhang G, Zheng X, Zhang F, Li Y, Yu C, Kristiansen K, Zhang X, Wang J, Wright M, McCouch S, Nielsen R, Wang J, Wang W (2012b) Resequencing 50 acces-sions of cultivated and wild rice yields markers for identifying agronomically important genes. Nat Biotechnol 30:105–111

Yamagishi H (2004) Assessment of cytoplasmic polymorphisms by PCR-RFLP of the mitochondrial orfB region in wild and culti-vated radishes (Raphanus). Plant Breed 123:141–144

Yamagishi H, Terachi T (2003) Multiple origins of cultivated rad-ishes as evidenced by a comparison of the structural variations in mitochondrial DNA of Raphanus. Genome 46:89–94

Yamane K, Lu N, Ohnishi O (2005) Chloroplast DNA variations of cultivated radish and its wild relatives. Plant Sci 168:627–634

Yamane K, Lu N, Ohnishi O (2009) Multiple origins and high genetic diversity of cultivated radish inferred from polymorphism in chloroplast simple sequence repeats. Breed Sci 59:55–65

1814 Theor Appl Genet (2016) 129:1797–1814

1 3

Zheng D, Han X, An Y, Guo H, Xia X, Yin W (2013) The nitrate transporter NRT2.1 functions in the ethylene response to nitrate deficiency in Arabidopsis. Plant Cell Environ 36:1328–1337

Zhou Z, Jiang Y, Wang Z, Gou Z, Lyu J, Li W, Yu Y, Shu L, Zhao Y, Ma Y, Fang C, Shen Y, Liu T, Li C, Li Q, Wu M, Wang M, Wu

Y, Dong Y, Wan W, Wang X, Ding Z, Gao Y, Xiang H, Zhu B, Lee S, Wang W, Tian Z (2015) Resequencing 302 wild and cul-tivated accessions identifies genes related to domestication and improvement in soybean. Nat Biotechnol 33:408–414