Introduction
Single-nucleotide polymorphisms (SNPs) are the most frequently found variations in DNA (Brookes, Reference Brookes1999) and are valuable markers for high-throughput genetic mapping and analysis of genetic variations in crop plants (Deleu et al., Reference Deleu, Esteras, Roig, Genzález-To, Fernández-Siva, Gonzalez-Ibeas, Blanca, Aranda, Arús, Nuez, Monforte, Pićo and Garcia-Mas2009). The discovery of SNP markers based on transcribed regions has become a common phenomenon in plants because of the large number of expressed sequence tags (ESTs) available in databases (Deleu et al., Reference Deleu, Esteras, Roig, Genzález-To, Fernández-Siva, Gonzalez-Ibeas, Blanca, Aranda, Arús, Nuez, Monforte, Pićo and Garcia-Mas2009), and EST–SNPs have been successfully mined from EST databases in non-model species such as tomato (Yamamoto et al., Reference Yamamoto, Tsugane, Watanabe, Yano, Maeda, Kuwata, Torki, Ban, Nishimura and Shibata2005). However, SNPs are by far the most prevalent forms of genetic variation in genome (Ching et al., Reference Ching, Caldwell, Jung, Dolan, Smith, Tingey, Morgante and Rafalski2002) and are quite often directly responsible for the allelic variation in target trait.
Chinese cabbage, Brassica rapa ssp. pekinensis, is one of the most widely cultivated annual vegetable crops. A native to Europe and East Asia, it is an important resource for breeding programmes because of its diploid nature and small genome size (529 Mb; Johnston et al., Reference Johnston, Pepper, Hall, Chen, Hodnett, Drabek, Lopez and Price2005). It exhibits wide morphological variation, including the leafy type (Chinese cabbage and pakchoi), turnip type (vegetable turnip) and oil type (yellow sarson). It has been considered to be a model species for genetic studies and numerous whole-genome sequencing projects (http://www.brassica.info) fulfilling the need of a simple genetic system with favourable genetic attributes for research on Brassica species. A selective breeding programme focusing on the improvement of important agronomic traits (e.g. disease resistance and quality) requires the development of a large number of DNA markers for the detection of quantitative trait loci (QTL) and marker-assisted selection to speed up the breeding process and to increase the selection efficiency. Disease-resistant varieties with improved quality suitable for cultivation are required when a new variety is delivered as a result of these breeding programmes. Although many crops and cultivars have been screened and selected for the resistance to pathogens, varieties with multiple resistance characteristics are required.
This study was carried out to develop SNP markers related to leaf traits linked to disease resistance in the doubled haploid (DH; VCS13M) populations, including 77 DH lines derived from a cross between the two leafy types of B. rapa varieties, ‘VC40’ [DH, CR+ (clubroot), TuMV+ (turnip mosaic virus), SR − (soft rot), Heading] and ‘SR5’ (DH, CR − , TuMV − , SR+). Both are DH lines and the parents of well-characterized DH mapping populations that segregate for resistance to CR, major leaf trait linked to TuMV and SR, and agriculturally important traits of B. rapa, such as head formation.
Materials and methods
Plant materials and DNA extraction
Leaf material of 20-d-old plants was used for genomic DNA extraction with the DNeasy Plant DNA Kit (Qiagen, Hilden, Germany) following the manufacturer's protocol. Relative purity and concentration were estimated using a ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA), and the final concentration of the sample was adjusted to 20 ng/μl.
Functional analysis, primer design and polymerase chain reaction (PCR)
In total, 21,311 SNPs and 6753 indels were developed using the gene space of B. rapa genome by re-sequencing 1398 sequence-tagged sites (Park et al., Reference Park, Yu, Mun and Lee2010). The sequences of 7645 of 21,311 SNPs, which were linked to disease resistance based on the B. rapa genome and which aligned to the bacterial artificial chromosome (BAC) sequences of B. rapa, were obtained using FGENESH (www.softberry.com) based on a B. rapa matrix to confirm the positions of the SNPs and to analyse the information according to the position of corresponding genes. Biological function analysis of the predicted genes using UniProt database was carried out by extraction of protein sequences of corresponding genes from BAC sequences collected in B. rapa Genome Project (http://www.brassica-rapa.org/BRGP/chromosomeSequence.jsp). Functional analysis was conducted using Munich Information Center for Protein Sequences (MIPS), Functional Catalogue (FunCat), Gene Ontology (GO) and Clusters of Orthologous Groups. The primers were designed from flanking exon sequences using Primer3 program (Rozen and Skaletsky, Reference Rozen, Skaletsky, Krawetz and Misener2000; Park et al., Reference Park, Yu, Mun and Lee2010). Amplification was carried out in a total volume of 20 μl containing 40 ng of genomic DNA as template, 0.5 μM of forward and reverse primers, and 2 × GoTaq® Green Master Mix (Promega, Madison, WI, USA) following the manufacturer's protocols using Eppendorf Thermocycler (Eppendorf, Hamburg, Germany). Electrophoresis on 1.0% agarose gel with ethidium bromide confirmed the presence of amplified products.
Results and discussion
The GO annotation results were obtained based on 7645 SNP sequences linked to disease resistance and sequence data of B. rapa genome registered in the NCBI database using BLAST. Genes were assigned to cellular components, molecular functions and biological processes. Among such genes, 125 were linked to leaf traits and 270 to root functions (Fig. 1(a)). The 125 leaf trait-related genes were classified into four groups of functional catalogue, viz. (1) leaf development, (2) leaf morphogenesis, (3) leaf senescence, (4) leaf vascular tissue pattern (Fig. 1(b)). Of the 7645 SNPs, 141 disease resistance-linked SNPs related to 125 leaf trait-linked genes were selected. Of these 141 SNPs, 63 were screened after removing overlapping sequences. Among the 63 PCR-amplifiable SNP–HRM primers, a total of 20 polymorphic SNP primers (Table S1, available online) were selected based on the presence of single bands as a result of polymorphism test using the parents of DH population. These SNP primers could be further used for the detection of QTL and fine mapping studies and could prove useful for the development of disease resistance markers and high-quality breeding of Chinese cabbage.
Function annotation by Gene Ontology (GO) mapping and distribution of the sequences of (a) Brassica rapa genome registered in the NCBI database and sequences of 7645 single-nucleotide polymorphisms (SNPs). (b) Leaf traits of 7645 SNP primer sequences.
This study reports the development of new SNP markers for leaf traits linked to disease resistance in B. rapa. As a large amount of genome sequence data has been made available in the public domain, the rapid advances in development and application of molecular tools are transforming plant biology. The ultimate goal is to gain a greater understanding of the biology underlying the observations and to apply this knowledge to improve the quality and yield of crop plants. One bottleneck in the application of molecular tools to crop improvement is the ability to manage the increasing quantity and diversity of data being produced by the advancing technologies. Advanced bioinformatics and computational tools are enabling the integration of increasingly diverse plant data types, from heritable traits associated with different varieties to the sequence and expression of genes and genomes. Tools that enable the interrogation of these complex data lead to valuable associations, which may then be tested in the laboratory and the field and lead to the development of improved crops through enhanced, marker-assisted breeding strategies or the application of transgenic technologies (Edwards and Batley, Reference Edwards and Batley2004). The polymorphic markers developed in this study will be useful for QTL fine mapping, genomics-based breeding and genetic association studies in B. rapa, which will eventually be applicable for developing disease-resistant cultivars.
Supplementary material
To view supplementary material for this article, please visit http://dx.doi.org/10.1017/S1479262114000288
