for review only - university of toronto t-space...for review only 1 potential snps related to...

For Review Only

Potential SNPs related to microspore culture in Raphanus

sativus based on a single-marker analysis

Journal: Canadian Journal of Plant Science

Manuscript ID CJPS-2017-0333.R3

Manuscript Type: Article

Date Submitted by the Author: 28-Feb-2018

Complete List of Authors: Chung, Yong Suk Lee, Yun Gyeong Silva, Renato Park, Suhyoung Park, Min Young Lim, Y.

Choi, Sang Chul Kim, Changsoo

Keywords: Genotype-by-sequencing, Single marker analysis, Regeration, Microspore, Radish

https://mc.manuscriptcentral.com/cjps-pubs

Canadian Journal of Plant Science

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Potential SNPs related to microspore culture in Raphanus sativus based on a single-

marker analysis

Yong Suk Chung1,2, Yun Gyeong Lee2, Renato Rodrigues Silva3, Suhyoung Park4, Min Young

Park4,5, Yong Pyo Lim5, Sang Chul Choi2, and Changsoo Kim2*

1Department of Plant Resources and Environment, College of Applied Life Sciences, Jeju

National University, Jeju, 63243, Republic of Korea

2Department of Crop Science, College of Life Sciences, Chungnam National University,

Daejeon, 34134, Republic of Korea

3Institute of Mathematics and Statistics, Federal University of Goiás, Goiânia, Brazil

4National institute of Horticultural & Herbal Science, Rural Development Administration,

Wanju, 55365, Republic of Korea

5Department of Horticulture, College of Life Sciences, Chungnam National University,

Daejeon, 34134, Republic of Korea

Yong Suk Chung and Yungyeong Lee have contributed equally to this work.

*Corresponding author

Email: [email protected]

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Abstract

Radish (Raphanus sativus) is an economically important crop grown for its edible roots and

leaves. It is a self-incompatible, outcrossing species making the production of homozygous

lines and the development of breeding populations difficult. However, this can be overcome

with haploids production techniques using isolated microspores providing the rapid

production of homozygous lines for breeding. Thus, it would be useful to identify radishes

with a high regeneration rate from microspore culture. In the current study, 96 radish

cultivars or germplasms were evaluated for high regeneration rates. Also, a single-marker

analysis (SMA) was applied to detect single nucleotide polymorphisms (SNPs) potentially

associated with this trait using genotype-by-sequencing (GBS) technology. The regeneration

rate from microspore culture of 96 lines showed a wide range from 0 to 269.5 percent. From

the SMA, fifty-two markers were detected at the p-value of 0.001, and a total of 11 physically

nearby genes with high levels of similarity in various species were identified as candidates

for high regeneration rates. This result could be used for clarifying the genetic basis

underlying these traits and developing molecular markers associated with regeneration rates

and would be beneficial to generating homozygous inbred lines.

Keywords genotype-by-sequencing (GBS) · regeneration rate · doubled haploid (DH) ·

single nucleotide polymorphism · phylogeny tree · microspore

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Introduction

Radish (Raphanus sativus) belongs to the Brassicaceae family which includes many

economically important plants, such as Chinese cabbage, cabbage, and oilseed rape. It is a

diploid plant (2n = 2x = 18) with an estimated genome size of 530 mega base pairs (Mb)

(Marie and Brown 1993). It is an economically important crop grown for its edible roots and

leaves. The cultivated radish is distributed worldwide and contains large morphological and

agro-ecological variations (Yamagishi and Terachi 2003).

Radish is a self-incompatible, outcrossing species (Sampson 1957). In consequence,

it is difficult to produce homozygous lines to develop breeding populations. However, this

can be bypassed using doubled haploids (DHs) by virtue of technologies like anther culture or

isolated microspores, providing the rapid production of homozygous lines for breeding self-

incompatible outcrossing lines, which are typical in Brassica vegetables (Cardoza and

Stewart, 2004). Various techniques for microspore culture have been reported for Brassica

species (Palmer et al. 1996). However, the success rate of Brassica microspore culture is very

low and genotype-dependent (Palmer et al. 1996). Furthermore, it is generally well known

that radish is one of the most difficult crops to regenerate microspore in tissue culture and this

ability to regenerate plants through tissue culture using microspores is heritable (Curtis 2003;

Zhang and Takahata 2001), indicating that the trait may be, to some extent, genetically

regulated.

The success of producing DHs mainly depends on genotype, microspore stage, and

cultural conditions of microspore in Brassica species (Cardoza and Stewart Jr 2004). So far,

the technologies for making DHs have focused on culture conditions such as temperature and

as well as on chemicals like colchicine for better efficiency (Charne et al. 1988; Chen and

Beversdorf 1992; Lionneton et al. 2001). Homozygous DHs provide advantageous methods

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for genetic studies and for breeding crops that cannot be self-pollinated, such as radish

(Forster et al. 2007). Nonetheless, the double haploid approach has some drawbacks such as a

high extent of segregation-distortion and the expression of lethal phenotypes, 'especially in

cross pollinated species (Devaux et al. 1995).

In Brassicaceae, the genome sequences of Arabidopsis thaliana and Brassica rapa

have been completed, and the function of many genes have been characterized (Yu et al.

2016). Following QTL analysis, synteny maps between these species offered a powerful tool

for the identification of candidate genes. With the rapid development of next generation

sequencing (NGS) technologies, whole-genome sequence analyses for various crops can be

accomplished in a short time (Metzker 2010). The draft sequences of a Japanese radish

cultivar, Aokubi, was published, comprising a total of 76,592 scaffolds covering 402 Mb,

with 116 Mb of these assigned to chromosomes by incomplete genome assembly (Kitashiba

et al. 2014). Using NGS, genotype-by-sequencing (GBS) technology that can simultaneously

perform molecular marker discovery, and genotyping has been developed and applied to the

sequencing of multiplexed samples (He et al. 2014; Kim et al. 2016; Poland and Rife 2012).

GBS is a novel application of NGS protocols for discovering and genotyping single

nucleotide polymorphisms (SNPs) in crop genomes and populations by constructing reduced

representation libraries. SNPs found by GBS could be applied to a single-marker analysis

(SMA) for target traits in non-structured populations thanks to its power to generate

thousands of credible SNPs in a single run. The combination of the draft sequences of a

Japanese radish cultivar genome and the SNPs associated with the target traits would increase

the power to identify molecular markers and candidate genes based on previously reported

information.

Here, we are interested in using GBS and SMA to find putative SNPs responsible for

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the regeneration of radish plants from microspore culture. The objectives of this study were

to identify genotypes with high regeneration rates from microspore culture and to develop

molecular markers to enhance the efficiency to develop DHs for the establishment of inbred

lines in radish. Hence, some accessions used for the current study will be used as parental

lines for constructing F2 mapping populations for the detailed investigation of regeneration

rates.

Materials and methods

Plant material

Total 96 radish accessions were selected for microspore culture at the National Institute of

Horticultural and Herbal Science, Jeonju, Korea between 2015 (Supplementary Table 1). The

various regeneration rates of these resources are shown in Supplementary Table 1. Individual

radish cultivars or lines were planted and vernalized in the previous year before collecting

buds for microspore culture. Vernalization was done in the cold chamber at 5 °C (±1°C) for

10 weeks. And then transferred to a greenhouse maintained at 25 °C to induce the

bolting for the flower bud collected.

Microspore culture and regeneration rate

Microspore culture was conducted according to Na et al. (2009) with some

modifications. Flower buds were collected when a couple of flowers were blossoming.

Among those buds, 2-3 mm of each closed bud segment were selected and wrapped in

sterilized gauze. Each wrapping included 30 buds to be dipped in 1% of sodium

hypochlorite (NaOCl) solution for 15 minutes. Then, the wrapping was washed three

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times in sterilized water for 3 minutes. The washed buds were ground with mortar and

pestle in 2-3 mL basal NLN medium (Lichter 1982; Nitsch and Nitsch 1967) supplemented

with 13 % sucrose and filtrated through 45 µm metal mesh. The ground buds were then

suspended in 30 ml of NLN medium. Suspension was centrifuged at 1,000 rpm for 3

minutes to separate microspores. Then, the supernatant was removed and NLN medium

was added to repeat the previous step twice. The separated microspores were suspended in

75 ml of NLN medium at a density of 40,000 microspores to l ml. Then, microspore

suspension was dispensed in four petri dishes (60 × 15 mm), followed by sealing with

parafilm. One bud, which was suspended in 2.5 ml of NLN medium, was subjected to a high

temperature treatment to induce embryogenesis. It was subjected to 30 °C regime for 48

hours. It was then moved to 25 °C for at least 2 weeks in darkness. After this treatment,

dishes were cultured under the light, on a shaker at 70 ~ 80 rpm, at 25 °C and induced

embryos were counted with bare eyes two to three days later. These counted embryos

were defined as the embryos from the microspores which were collected in the early

step. Regeneration rate was calculated as follows:

Regeneration rate = (the total number of induced embryos from microspore

culture / the total number of used buds in each line × 100,000) × 100

GBS library construction

A GBS library was constructed based on Poland and Rife (2012) with slight

modifications. The GBS libraries were constructed in 96-plex using the P384A adaptor set

(Poland et al 2012). Genomic DNA was co-digested with two restriction enzymes, NsiI-HF

(New England Biolabs, Ipswich, MA, United States) and MseI (Enzynomics, Daejeon,

Korea), and barcoded adapters were ligated to individual samples. Ninety six samples were

pooled by plate into a single 15 ml falcon tube and cleaned using a phenol-chloroform-

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isoamyl- alcohol (PCI) extraction method and re-precipitated with 2-propanol. The cleaned

sample was size-selected with AMPure XP beads (Beckman Coulter, High Wycombe, UK) to

clean out small fragments such as primers. The size-selected sample was then amplified by

polymerase chain reaction (PCR). The PCR product was size-selected once again to become a

final product in the GBS library. This library was checked for quality control using Library

Quant Illumina Kit (KAPA Biosystems, MA, U.S.A.) according to manufacturer’s

specification.

Genotyping 96 entries

Raw FASTQ files containing multiplexed reads from a barcoded library were obtained from

Illumina HiSeq2000. The FASTlinkQ files were deposited in NCBI’s SRA database

(SRR5804111). The radish reference genome was downloaded from NODAI Radish genome

database (http://www.nodai-genome-d.org/) (Mitsui et al. 2015) and indexed with Burrows-

Wheeler Aligner (BWA) (Li and Durbin 2009). For sequence analysis and genotyping, the

GBS SNP-Calling Reference Optional Pipeline (GBS-SNP-CROP,

https://github.com/halelab/GBS-SNP-CROP) (Melo et al. 2016) was used. First, adaptors and

low-quality sequences were trimmed using Trimmomatic v.0.33 (Bolger et al. 2014). The

trimmed reads were then aligned to the reference genome with the BWA-mem algorithm (Li

and Durbin 2009). Aligned sequences were indexed and sorted by SAMtools (Li et al. 2009).

For generating the final SNP genotyping matrix, only high-confidence SNPs which passed

stringent genotyping filtering criteria were collected. Recommended filtering options include

a minimum depth for calling homozygotes (mnHoDepth)/ heterozygotes (mnHetDepth), a

minimum acceptable proportion of genotyped individuals to retain a SNP (mnCall), and a

maximum average depth of acceptable SNP (mxAvgDepth). The actual parameters used in

this study are mnHoDepth = 5, mnHetDepth =3, mnCall =0.75 and mxAvgDepth=200.

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Estimating linkage disequilibrium (LD)

For 18,071 SNPs, pairwise linkage disequilibrium (r�) within sliding window size 50 was

calculated using Tassel version 5.0 (Bradbury et al., 2007). The decay of Linkage

disequilibrium (r�) over distance in base pairs (bp) was estimated Hill and Weir expectation

of r� between adjacent sites (Hill and Weir, 1988). With a low level of mutation and finite

sample size n, the expectation becomes the following (Remington et al., 2001):

E�r�� = � 10 + ��2 + ��11 + �� 1 +

�3 + ��12 + 12� + ��2 + ��11 + ��

The expected value of r� under drift-recombination equilibrium isE�r�� = 1/�1 + ��, where n is the effective population size, C is the recombination parameter between sites, and

C = 4Nc(Sved, 1971). To fit equation to the data, nonlinear least squares (nls) model, in R

package were used (Marroni et al., 2011).

Construction of phylogenic tree

A maximum-likelihood phylogenetic tree based on the SNP data was constructed using

SNPhylo (Lee et al. 2014). The SNPhylo filters SNP datasets with 5% minor allele frequency

(MAF) and 20% missing data. An additional function includes the removal of redundant

SNPs based on linkage disequilibrium (LD) information. Optionally, the SNPhylo performs

multiple sequence alignment using MUSCLE (Edgar 2004). Then, a maximum-likelihood

tree was constructed by DNAML embedded in the PHYLIP (Felsenstein 1989). Finally, a

newick file and a phylogenic tree image were automatically generated using default

parameters.

Population analysis with STRUCTURE version 2.3.4

STRUCTURE (Pritchard et al. 2000) software version 2.3.4 was used to detect the

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subpopulation structure. This program implements a model-based clustering method for

inferring population structure using multi-locus genotypic data. For selecting best K,

STRUCTURE HARVESTER was used (Earl 2012). It is a program for visualizing

STRUCTURE output and implementing the Evanno method (Earl 2012). A STRUCTURE

plot was then visualized with STRUTURE PLOT (Ramasamy et al. 2014).

Single marker analysis

A marker-trait analysis (MTA) was performed by a single-marker analysis approach (Lynch

and Walsh 1998; Soller et al. 1976). This method consisted of fitting a regression model and

running an F test analysis of variance (ANOVA) at each marker locus with the statistical

model given by:

�� + 1� = �� + �� + �� + !� where yi is the regeneration rate of pollen culture; ��is the intercept of the model;

��is the additive effect; ��is an explanatory variable that assumes -1, 0, and 1 if the marker

is coded as A, H, and B, respectively; ��is the dominance effect; �� is other explanatory

variable that assumes 1 if the marker were coded as H and -1/2 otherwise; and !� is the

random error.

Locating SNPs within genes

The location of each SNPs within the scaffold of the radish genome (http://www.nodai-

genome-d.org/) was compared to the locations of those genes found by the annotation from

BLAST results. Only those SNPs within the genes in the scaffolds were considered as

candidate genes related to the regeneration trait. SNPRelate, parallel computing

toolset(Zheng et al. 2012), was used for relatedness and principal component analysis (PCA)

of SNP data using Identity-By-Descent measures.

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Results and discussion

Genotyping

The sequencing of the GBS library consisting of 96 radish accessions resulted in a total

305,013,185 raw read pairs. Average length of read was 101 bp. The percentage of usable

paired reads was 95.9%. A total of 39,957 SNPs was obtained with an average depth of 37.15.

After filtering SNPs with MAF > 0.05 and allowing fewer than 10 missing genotypes per

SNP, a total of 18,071 SNPs were used for downstream analyses.

LD decay

Average distance between markers was 152 kb (calculated by the total intervals of markers in

physical distance divided by the number of SNPs) and average LD (r�) was 0.708 in the

samples of current study. The rate of LD decay varies depending on species because it is

dependent on multiple factors such as the population size, the number of founding

chromosomes in the population, and the number of generations for which the population has

existed (Bush and Moore, 2012). Among those, population mating patterns and admixture can

strongly influence LD. In general, LD decays more rapidly in outcrossing species like radish

as compared to selfing species because recombination is less effective in selfing species,

where individuals are more likely to be homozygous, than in outcrossing species (Long et al.,

1998). In the current study, LD decayed rapidly within 15 kb (Fig. 1). Our results showing

moderate LD decays indicate the resolution is not highly acceptable, considering the mode of

reproduction is outcrossing (Rafalski, 2002). This may be caused by the limited genetic

background of each accession. Thus, those SNPs detected may not be suitable to capture all

the variation in our samples but the coverage of SNPs across the whole genome was still

reasonable. This led us to use SMA rather than genome wide association study (GWAS).

Subpopulation structure

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To infer evolutionary relationships among 96 radish samples, a maximum likelihood

phylogenic tree was constructed using SNPhylo (Lee et al., 2014). A total of 3,327 SNPs,

obtained after removing redundant SNPs from initial 18,071 SNPs based on LD block

information, were used to construct the tree (Fig.2). The branch styles and colors of the tree

were modified using MEGA7 software (Kumar et al. 2016).

To investigate population structure, STRUCTURE (Pritchard et al. 2000) was

performed using a subset of a 3,327 filtered SNP dataset of all 96 samples. Linkage

disequilibrium was assumed to be absent in the filtered SNP dataset after SNPRelated (Zheng

et al. 2012) filtering in the SNPhylo (Lee et al. 2014) pipeline. The estimation of clusters (K)

was performed in 20 replications using K values from 2 to 10. According to the best K value

(Evanno’s methods) (Evanno et al. 2005), 8 subpopulations were defined in the 96 radish

accessions used in the current study.

The result from STRUCTURE showed mixture origins among accessions which we

used in this study, implying that there are not clear differences among them (Fig. 3).

Cultivation of the radish has a long history (Smart and Simmonds 1995). Another

theory about the origin of the radish is that it was domesticated from the Mediterranean area

and spread to East Asia and Europe (Wang et al. 2008). However, none of these ideas gives

definitive evidence o n i t s o r i g i ns because they are mostly based on morphological

observations and have no convincing basis in genetic, cytological, or molecular data.

Overall, the origin of radish has not been clarified not only due to the long history but

also due to diversity of cultivated radishes (Lewis-Jones et al. 1982). However, a study

showed that cultivated radishes have multiple origins (Yamagishi and Terachi 2003). During

their domestication, the root of radishes was the focus for selection and they have a wide

variation in shape although there also are variations in color and size of roots. Ellstrand and

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Marshall (1985) reported that domesticated radish retained a population structure similar to

that of wild populations based on allozyme variation within and among varieties of R. sativa.

This is supported by Pistrick (1987) who reported that all of the taxa of wild and

cultivated species might be included in R. sativus. Consequently, there were no significant

differences in the average genetic diversity among cultivars collected from Europe, North

Africa, the Middle East, and South and East Asia across all loci (Wang et al. 2008), indicating

that no clear bottleneck effect occurred during segregation of these groups (Wang et al. 2008).

In addition to the fact that enough seeds might have been transferred from one area to another,

there maybe have not been so much breeding effect which could had reduced genetic

diversity. This could be not only because enough seeds might have been transferred from one

area to another during the distribution process to conserve biodiversity (Wang et al. 2008),

but also because radishes is an outcrossing and open-pollination system (Brown 1978).

Therefore, the regeneration-rate-oriented sampling in this study rather than a core-collection-

sampling should not be an issue.

Regeneration rate and SMA

Regeneration rates from microspores of each individual line had a wide variation

(Supplementary Table 1). As stated above, entries in the current study include enough

diversity to observe a wide range of regeneration rates. Notably, the lines with regeneration

rates below 10 % were 63, while those above 50% were only 6 out 96 entries. These

regeneration rate characteristics (low rate and genotype-dependence) are consistent with the

report by Palmer et al. (1996). This indirectly reflects that the regeneration rate was not the

selection target in radish cultivars or germplasms.

Out of 52 SNPs associated with regeneration rates based on SMA at p-value less than

0.001 (Table 1), SMA using the regeneration rate trait data found several SNPs, which are

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within the genes imbedded in the scaffold, involved in the most important activities that take

place during embryogenesis such as programmed cell death (SNP8594), copper ion

regulation (SNP6450, SNP6451, and SNP6454), chromatin-remodeling (SNP9872), and cell

cycle arrest (SNP10352 and SNP15840). Among those, two SNPs (SNP6450 and SNP6454)

were very significant at p-value less than 0.0001 and on SNP (SNP6451) was very significant

at p-value less than 0.00001, which were related with copper ion regulation. In addtion,

SNP8508 and SNP8512 (p-value 0.00000001 and 0.0000000001, respectively) would be

worth to be investigated further although no genes were associated with. This will be

discussed further below. Among 52 SNPs, 16 were physically close to the genes reported as

candidate genes for regeneration rates in other species. Those may be linked to genes for

unique pathways unlike other species in the very specific experimental condition in this study.

The SMA generally provides a rough estimate of genotype-phenotype associations. Thus, it

will be necessary to further investigate those 16 SNPs by analyzing quantitative trait loci

(QTL) using biparental populations by crossing accessions with extremely opposite

regeneration rates.

The following are the SNPs detected within genes embedded in the scaffold of the radish

genome (http://www.nodai-genome-d.org/) in the current study. The SNP8594 was found

within the gene encoding ring-h2 finger protein atl1-like in the scaffold of the radish genome.

ATL1 is a positive regulator of programmed cell death (Serrano et al. 2014). Programmed cell

death plays an important role at the late stages of microspore-derived embryo development

(Maraschin et al. 2005). Chromatin condensation and DNA degradation are accompanied by

an increase in the activity of other enzymes. The orchestration of such a cell death program is

linked to the elimination of the small generative domain, and further embryogenesis is carried

out by the large vegetative domain.

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The SNP6450, SNP6451, and SNP6454 were found within the gene encoding cox19

family protein (having Coiled Coil-Helix-Coiled Coil-Helix motifs). It has been proposed that

the conserved cysteine residues of the CHCH motif in Cox19 mediate as ligands for copper

ions (Nobrega et al. 2002; Smits et al. 2007). In general, copper is included in plant tissue

culture media at low concentrations but has a crucial role as a cofactor of several key

enzymes. There is a report that copper at 10 µM, which is higher than the concentration of

copper in general medium, significantly enhanced shoot regeneration of wheat, triticale, and

tobacco (Purnhauser and Gyulai 1993). The level of copper appears to be key to promoting

plant regeneration but the effect of copper on plant regeneration depends on the type of in

vitro culture and the cultivars tested (Szafrańska et al. 2011). However, as in wheat, triticale,

and tobacco, copper could be an important element for higher regeneration rate in radish

judging from the association of those detected SNPs with cox19 family protein.

The SNP4477 was found within the leucine aminopeptidase 1 (lap-1) based on the

BLAST results. Leucine aminopeptidase (LAP) is an aminoacyl-peptide hydrolase that

catalyzes the removal of amino acids from the N-terminus of a peptide or protein Matsui et al.

2006). LAPs are known to play critical roles in many cellular ‘housekeeping’ functions,

including the maturation of proteins, digestive and intracellular protein metabolism, and

hormone regulation (Taylor 1993). However, very high embryo recovery rate was observed in

the cultivar bearing lap-1 according to Orton and Browers (1985), implying that it may be

associated with embryogenesis.

The SNP4965, SNP4669, SNP4670, SNP4671, and SNP13203 were found within

the gene encoding ribonuclease h-like protein. RNases H1/H2 participate in DNA replication

(Arudchandran et al. 2000). RNases H also have been suggested to be involved in removing

the RNA of RNA-DNA hybrids, particularly the primers of Okazaki fragments in lagging-

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strand DNA synthesis (Kogoma and Foster 1998). This protein is known to be related to

mitochondrial DNA replication during embryogenesis in mouse (Cerritelli and Crouch 2009).

Furthermore, vegetative cells of pollen always have to re-enter the cell cycle before

embryogenesis can occur and embryogenic cultures can be started with microspores from late

Gl to G2-phase (Hause and Hause 1996). Hause and Hause (1996) showed that the dynamics

of the replication with respect to microspore-derived embryogenesis was revealed based on

nuclear DNA synthesis using their qualitative and quantitative analyses of nuclear DNA

synthesis. The SNP9872 was found within the gene encoding a helicase-like protein.

Members of large helicase-like grouping can be subdivided according to particular motif

variations into two large subdivisions - superfamily I (SF-I) and superfamily II (SF-II)

(Petukhova et al. 1999; Tan et al. 1999; Van Komen et al. 2000). Several members of the SF-

II superfamily of helicase-like proteins have been shown to alter the twisting of DNA

fragments. Most recently, this has expanded to include certain ATP-dependent chromatin-

remodeling activities (Flaus and Owen-Hughes 2001), which is one of the important phase

for regeneration.

The SNP10352 was found within the DNA replication licensing factor

minichromosome maintenance 5 (mcm5-like. MCM5) is one of seven MCM family members,

which are highly conserved in eukaryotes (Mlechkovich and Frenkel 2007). Uncovering the

role of proteins in the MCM family may hold the key to understanding how DNA is replicated

once per cell cycle (Kearsey et al. 1996). In yeast, mcm1 exhibits a temperature-dependent

cell-cycle arrest, which is also the important phase of regeneration. The mcm5-a-like protein

may have a similar function to mcm1 considering that the MCM family shares similar

functions; this is worthwhile to investigate further.

The SNP15840 was found within the gene encoding pelota-like protein. The Pelota

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protein homolog is a protein in humans that is encoded by the PELO gene (Eberhart and

Wasserman 1995; Shamsadin et al. 2000). This gene encodes a protein which contains a

conserved nuclear localization signal. The encoded protein may have a role in

spermatogenesis, cell cycle control, and in meiotic cell division (Eberhart and Wasserman

1995). Eberhart and Wasserman (1995) found that spermatogenesis in pelota and twine

homozygotes in Drosophila is normal until the late meiotic prophase, at which point the cell

cycle arrests due to a lack of spindle formation (Eberhart and Wasserman 1995). Cell cycle

arrest was observed in tobacco and rapeseed microspores (Binarova et al. 1993; Žárský et al.

1992) and this will be discussed further later.

Numerous studies lead to the prediction of the mechanism of microspore

embryogenesis at the molecular level using functional genomics such as microarray-based

transcriptomics for gene discovery in microspore embryogenesis, differential screens,

subtractive hybridization to cDNA microarrays, suppression subtractive hybridization and

metabolomics (Hosp et al. 2007). Nevertheless, the overall picture of the complex regulation

of the developmental switch from the gametophytic to sporophytic pathway during

microspore embryogenesis has not yet emerged even with the large amount of data obtained

from the different model species. However, there are some clues, such as cell cycle arrest and

chromosome re-modelling, suggesting that some common aspects govern the re-

programming of microspores toward becoming embryos (Hosp et al. 2007). Cell cycle arrest

may lead to an early stage of an autophagic response that enables the fittest microspores to

de-differentiate and develop as embryos according to evidence in yeast (Wysocki and Kron

2004). Chromosome re-modelling might be a further requirement in an early stage of

adaptation based on reports of a number of genes involved in chromosome re-organization in

diverse species upon differential screens (Hosp et al. 2007). Reconstruction of the

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cytoskeleton might be involved in the morphological changes from young pollen to

embryogenic cells along with chromosomal alterations. Changes in the transcriptional and

translational machinery are likely to occur. Afterwards, it is assumed that proteins are to be

recycled and selectively destroyed in favor of synthesis of new proteins that are able to better

serve the novel conditions of embryogenic induction (Aubert et al. 1996). During the

transition from multi-cellular structures to embryos, sufficient evidence for the importance of

programmed cell death at late stages of microspore embryo development was found

(Maraschin et al. 2005).

A master gene capable of initiating embryogenic development from microspores has

not been identified so far. It would be unlikely that a single gene could induce a large number

of profound cellular adaptations and changes. Rather, initiating embryogenic development

from microspores is more likely to have a concerted series of events taking place out of

multiple genes during haploid embryo development from microspore. Each event may be

triggered by switches that initiate stress-induced metabolic alterations leading to higher order

changes in chromatin structure and gene expression, and end with the activation of cell-cycle

and regulatory genes (Hosp et al. 2007). Notably, none of the same genes including those

genes associated with the markers found in the current study has been identified in other

species. This could be due to the complexity of the process of microspore embryogenesis.

Indeed, embryo-abundant gene expression is spatially and temporally specific (Reynolds and

Kitto 1992). It is also possibly because of the different stages of microspore embryogenesis

and the limited number of genes analyzed. Different species might have different pathways to

regulate genes for embryogenesis. In addition, the differences in the culturing conditions and

the variations from different buds, even within a single plant, created diverse stress guiding

different pathways for signaling to express different genes. These speculations could be

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supported by circumstantial evidence like the following studies. Lane (1978) reported bud

location effects on regeneration frequency whereas Chuong et al. (1988) showed there is no

bud position effect. Even the effect of sampled-bud location is not consistent based on the

independent research using different species. Furthermore, the position and orientation of the

explant affect the frequency of shoot regeneration and the number of adventitious buds

produced from the regenerated shoots (Zhao et al. 2007). In R. sativus, temperature treatment

and bud size were found to have an effect on plant regeneration (Takahata et al. 1996). In

addition, there might be genotype by environmental effect on the results for the microspore

regeneration rate. All these results indicate the complexity of different gene expression

regulations among different species within plants and among subtle differences of the

incubation condition even within the same plant. This might have led this inconsistent unity

of those genes in the independent studies for embryogenesis. Hence, it would be worth to

establish a sampling method and standard conditions for culture to uncover the mechanisms

underpinning embryogenesis.

The regeneration rates in 96 samples of the current study were low and genotype-

dependent as stated. Here, we found several SNPs which are potentially associated with

genes for the important stages during the regeneration from microspores, including

programmed cell death, copper ion regulation, chromatin-remodeling, and cell cycle arrest.

Our findings could be used to develop molecular markers for regeneration rate. In addition,

those unknown SNPs might lead to new findings for clarifying genes underlying the traits and

for developing molecular markers associated with regeneration rates beneficial to generating

homozygous inbred lines. To achieve this, we are planning to make F2s using two parents

among the 96 entries presented in this study, one with a low regeneration rate and the other

with a high one. This will enable us to find useful markers to screen for candidate lines at

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early growing stages for making DHs in the breeding of R. sativa.

Acknowledgment

This work was supported by Korea Institute of Planning and Evaluation for Technology in

Food, Agriculture, Forestry and Fisheries (IPET) through Golden Seed Project, funded by

Ministry of Agriculture, Food and Rural Affairs (MAFRA) (213006-05-1-WTH11).

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Figure captions

Fig. 1. Plot of linkage disequilibrium (LD, r^2) against distance between SNPs in Radish

genome. Red line show the expected LD decay, estimated by nonlinear regression of

r^2.

Fig. 2. Phylogeny tree of 96 radish entries using SNPs from genotype-by-sequencing. Each

color (orange, yellow, green, blue, purple, violet, magenta, red, and peach)

corresponds to the same color of STRUCTURE result in Figure 3.

Fig. 3. STRUCTURE result of 96 radish entries using SNPs from genotype-by-sequencing.

Each colour (orange, yellow, green, blue, purple, violet, magenta, red, and peach)

corresponds to the same color of phylogeny tree in Figure 2.

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Table 1 SNPs for microspore regeneration rate and their associated candidate genes using single marker analysis in 96 radish entries

Scafold number SNP P-value Sequence Name Sequence Description Blast Top Hit Gene

Name Blast Top Hit E-Value

Rs_scaf1279 SNP2031 3


Rs_scaf14 SNP2725 3





Rs_scaf1707 SNP4477 3 RSG46506.t1 leucine aminopeptidase 1 ARALYDRAFT_48127 0



Rs_scaf182 SNP4965 4 RSG14716.t1 ribonuclease h-like protein AT4G29090 7.99E-31





Rs_scaf21962 SNP6450 4 RSG58882.t1 cox19 family protein (chch motif) 3.16E-06







Rs_scaf25616 SNP7853 3 N/A


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Rs_scaf281 SNP8594 3 RSG19029.t1 ring-h2 finger protein atl1-like AT5G43420 1.89E-132

Rs_scaf29400 SNP8955 5 RSG61521.t1

Rs_scaf297 SNP9014 3 RSG28786.t1 receptor-like protein kinase hsl1-like ARALYDRAFT_48944 0



Rs_scaf324 SNP9872 3 RSG30616.t1 helicase-like protein 4.30E-82

Rs_scaf344 SNP10352 3 RSG21982.t1 dna replication licensing factor mcm5-a-like ARALYDRAFT_48024 0

Rs_scaf4221 SNP11967 8 RSG50121.t1 hypothetical protein SORBIDRAFT_07g01 3.38E-157








Rs_scaf703 SNP15451 3 RSG37752

Rs_scaf703 SNP15452 3 RSG37752



Rs_scaf749 SNP15840 3 RSG37847.t1 protein pelota-like AT3G58390 5.02E-148



Rs_scaf866 SNP17016 3 RSG34684.t1 protein AT1G52950 4.85E-46




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Fig. 1.

189x170mm (150 x 150 DPI)

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Fig. 2.

233x238mm (96 x 96 DPI)

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Fig. 3.

301x65mm (96 x 96 DPI)

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for review only - university of toronto t-space...for review only 1 potential snps related to...

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