Genotyping by Sequencing-Based Discovery of SNP Markers and Construction of Linkage Map from F<sub>5</sub> Population of Pepper with Contrasting Powdery Mildew Resistance Trait

Manivannan, Abinaya; Choi, Sena; Jun, Tae-Hwan; Yang, Eun-Young; Kim, Jin-Hee; Lee, Eun-Su; Lee, Hye-Eun; Kim, Do-Sun; Ahn, Yul-Kyun

doi:https://doi.org/10.1155/2021/6673010

BioMed Research International

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Abstract Introduction Materials and Methods Results Discussion Conclusions Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2021 | Article ID 6673010 | https://doi.org/10.1155/2021/6673010

Genotyping by Sequencing-Based Discovery of SNP Markers and Construction of Linkage Map from F₅ Population of Pepper with Contrasting Powdery Mildew Resistance Trait

Abinaya Manivannan,¹Sena Choi,¹Tae-Hwan Jun,²Eun-Young Yang,¹Jin-Hee Kim,¹Eun-Su Lee,¹Hye-Eun Lee,¹Do-Sun Kim,¹and Yul-Kyun Ahn³

Academic Editor: Gustavo Graciano Fonseca

Received06 Nov 2020

Revised24 Feb 2021

Accepted09 Mar 2021

Published16 Mar 2021

Abstract

Powdery mildew (PM) is a common fungal disease infecting pepper plants worldwide. Molecular breeding of pepper cultivars with powdery mildew resistance is desirable for the economic improvement of pepper cultivation. In the present study, 188 F₅ population derived from AR1 (PM resistant) and TF68 (PM sensitive) parents were subjected to high-throughput genotyping by sequencing (GBS) for the identification of single nucleotide polymorphism (SNP) markers. Further, the identified SNP markers were utilized for the construction of genetic linkage map and QTL analysis. Overall read mapping percentage of 87.29% was achieved in this study with the total length of mapped region ranging from 2,956,730 to 25,537,525 bp. A total of 41,111 polymorphic SNPs were identified, and a final of 1,841 SNPs were filtered for the construction of a linkage map. A total of 12 linkage groups were constructed corresponding to each chromosome with 1,308 SNP markers with the map length of 2506.8 cM. Further, two QTLs such as Pm-2.1 and Pm-5.1 were identified in chromosomes 2 and 5, respectively, for the PM resistance. Overall, the outcomes of the present endeavor can be utilized for the marker-assisted selection of pepper with powdery mildew-resistant trait.

1. Introduction

Powdery mildew (PM) is a widely occurring disease in Solanaceae plants caused by an obligate fungus Leveillula taurica (Lev.) from the ascomycete family. The incidence of powdery mildew has been rising in both greenhouse and field grown pepper plants [1]. The primary symptom of premature defoliation caused by the fungus drastically reduces the plant growth, yield, and marketing of pepper plants. Moreover, the endophytic nature of L. taurica delimits the use of chemical control measures for disease prevention in an agricultural setting [2]. Therefore, the inevitable requirement of genetic resistance lines to powdery mildew arises. However, the traditional breeding methods for PM resistance may take upwards of 10 years. In order to provide a more rapid solution, the molecular marker-assisted breeding aided by modern sequencing technologies is evolving as the current breeding method of choice. Rapid innovations in genome sequencing platforms, such as next-generation sequencing (NGS), provide numerous opportunities for transcriptome assembly, functional annotation of genes, and identification of molecular markers [3–5]. New software tools in NGS technology enable the cost-effective identification, confirmation, and evaluation of genetic markers on a large scale. Among the NGS approaches, genotyping by sequencing (GBS) has been noted for its wide-range utilization for high-throughput analysis [6]. This process employs restriction enzyme-based complexity reduction coupled with DNA barcoded adapters to generate multiplex libraries of samples for NGS sequencing [7]. GBS has been demonstrated to be robust across a range of species and capable of producing large number of molecular markers which can be utilized for the construction of genetic maps [8]. GBS provides a rapid and low-cost tool for genotyping large populations, allowing breeders to implement genomic selection on a large scale in their breeding programs [9]. The GBS approach renders discovery of polymorphisms and simultaneously obtains the genotypic information across the whole population of interest. This synergistic approach makes GBS a promising and flexible platform for a wide range of species and germplasm sets.

From the past decade, DNA-based molecular markers are employed in plant breeding for genetic diversity and genome association analyses in several plants [10]. Major advancements in sequencing technology and bioinformatics methodologies prompted a transition from conventional genetics-based breeding to modern genomics-based marker-assisted breeding. Among the molecular markers, SNPs have been utilized for the genome-wide studies [11, 12]. NGS technologies have identified genome-wide SNPs in several crops, such as mung bean [13], barley [14], castor [15], cabbage [16], and grape [17]. One of the primary uses of DNA markers in molecular breeding is in the construction of linkage maps for diverse crop species. Molecular linkage maps and QTL mapping are valuable tools for characterizing the schematic view of loci associated with agronomically important quantitative traits like disease resistance. According to Qian et al. [18], the localization of resistance loci on linkage maps and identification linked of polymorphic DNA sequences greatly improve marker-assisted selection. Pepper is a widely consumed horticultural crop in Solanaceae which also includes other major vegetables such as potato, tomato, and eggplant. Peppers are used as vegetable, condiment, spice, medicine, coloring agent, and source of vitamins [4]. The most common cultivated pepper species are Capsicum annuum, C. frutescens, C. chinense, C. pubescens, and C. baccatum [19]. In pepper, several thousand SNP markers associated with various traits such as disease resistance [20], flowering [21], and pungency [22] have been discovered. Moreover, the genomics-based improvement of pepper has been enhanced after the release of pepper reference genome (C. annuum cv. CM334) with a genomic size of 3.48 Gb by Kim et al. [23]. The present study deals with the GBS-based discovery of SNP markers, construction of genetic linkage map, and QTL analysis from 188 F₅ population obtained from pepper cultivars with contrasting powdery mildew resistance traits.

2. Materials and Methods

2.1. Plant Materials and Phenotypic Evaluation of Disease Resistance

Two cultivars of pepper AR1 (PM-resistant line) and TF68 (PM susceptible line) were grown in a greenhouse at the National Institute of Horticultural and Herbal Science, Rural Development Administration (RDA), Jeonju, Republic of Korea. The 188 F₅ lines were produced by self-pollinating from F₁ lines to F₄ lines [24]. A total of 188 F₅ population (single seed descendants) were selected for the present study. The plants were infected and scored according to Ahn et al. [19]; in detail, the plants were maintained in between the powdery mildew-affected plants in a polyvinyl house and grown for two weeks. After infection, the severity of the disease has been assessed from 0 to 4 scale (0: highly resistant, 1: resistant, 2: moderate, 3: sensitive, and 4: highly sensitive) (Supplementary Figure 1) based on the percentage of plants infected. The cultivars “Saengryeg 211” (PM sensitive) and “11PM37” (PM resistant) were used as controls.

2.2. Genotyping by Sequencing Analysis

The genomic DNA was isolated from the young leaves using the CTAB method according to our previous report [19]. The quantity and quality of DNA were assessed before the GBS library construction. A total of 188 F₅ population were subjected to GBS analysis (SEEDERS, Daejeon, Korea). ApeK1 was employed for the genome reduction. Further, the digested fragments (approximately 100-400 bp) were sequenced using HiSeq 2000 system (Illumina, San Diego, CA, USA) according to Elshire et al. [9]. Demultiplexing has been performed using the barcode sequence, and adapter sequence removal and sequence quality trimming were performed. Adapter trimming was performed using cutadapt v. 1.8.3 [25], and sequence quality trimming has been performed using DynamicTrim and LengthSort of SolexaQA v.1.13 [26].

2.3. Discovery and Annotation of SNP Markers

The reads were aligned to the pepper reference genome using the Burrows-Wheeler Aligner (BWA 0.6.1-r104) program [27]. The default values for mapping have been used, except for seed length , maximum differences in the seed , number of threads , maximum number of gap extensions , mismatch penalty , gap open penalty , and gap extension penalty . Mapped reads were extracted from the BAM file using SAMtools 0.1.16. An in-house script for the biallelic loci has been employed to select significant sites in the called SNP positions, and the SNP matrix was constructed by eliminating the miscalled SNP positions through SNP comparison among samples [28]. Further, the SNPs were classified into homozygous (SNP read ), heterozygous (), and others (homozygous/heterozygous; could not be distinguished by type) based on their position [5]. The polymorphic SNPs between two samples with sufficient sequences on both sides of the SNP site, without structural variation, were noted adjacent to the SNP site. The SNPs were further filtered using the criteria of missing rate of <30% and minor allele frequency (>20%). The flanking sequences (600 bp) of the identified SNPs were used as the query for the Blastn-based homology search.

2.4. Linkage Map Construction and QTL Analysis

A single genetic map was developed from both parents using JoinMap 4.1 [29] with regression mapping algorithm. The population type “RI3” was employed. A minimum log likelihood (LOD) score of 8.0 was used, and the recombination rates were converted into the Kosambi mapping function to determine the map distance in centimorgans. The chi-square test () was employed to eliminate the skewed SNPs, and the markers displaying identical segregation or more than five missing data points were filtered. MapChart 2.2 [30] was used for the visualization of the final genetic map. For the identification of QTLs, MapQTL 6.0 [31] was employed. The multiple QTL mapping (MQM) was performed to evaluate the association between the markers identified and the trait for powdery mildew disease resistance. The genome-wide threshold significance (LOD) was set to 4.5 with 1,000 permutation tests.

3. Results

3.1. Phenotypic Evaluation of Disease Resistance in 188 F₅ Population

A total of 188 F₅ population were inoculated with the fungus, and the disease symptoms occurred after 20 days of inoculation. The disease index (DI) was classified in the scale of 0-4 denoting resistance to sensitive based on the percentage of plants affected (Figure 1). Among the 188 F₅ population, the majority of the population displayed moderate DI with 33% followed by sensitive DI (20%). The resistant and highly resistant DI was observed in 18% and 11% of the population, respectively.

3.2. Genotyping by Sequencing (GBS) Analysis of 188 F₅ Population

The overall summary of the GBS data is provided in Supplementary Table 1. In the parental lines, a total length of raw reads 2,289,576,676 bp has been obtained for AR1 which has been trimmed to 1,520,510.658 bp and the overall 1,557,295,366 bp length of raw reads was trimmed to 1,014,880,396 bp in TF68, respectively. Moreover, the total and the trimmed length of reads in the F₅ population ranged from 49,469,194 bp to 2,328,589, 744 bp and 33,288,497 bp to 1,547,088,780 bp, respectively. The percentage of trimmed to raw reads of about 78.25 to 85.49% has been observed among the F₅ population. Subsequently, the clean reads of each sample that have been demultiplexed and trimmed were mapped to the reference genome with the read mapping percentage of 69.89% and 89.16% for AR1 and TF68, respectively. However, the overall read mapping percentage of 87.29% has been acquired in this study with the total length of mapped region ranging from 2,956,730 to 25,537,525 bp. Among the F₅ population, the overall reference genome coverage obtained is 0.534% with the range of 0.11 to 0.93%.

3.3. Discovery of SNP Markers

After the alignment of reads to the reference genome, the raw SNPs were detected and the SNP matrix has been generated between parental lines and 188 F₅ population using raw SNPs of each sample (Supplementary Table 2). The average number of SNPs for each sample was 32,303; among them, 23,380 SNPs were homozygous and 3,369 SNPs were heterozygous types followed by 5,554 other types of SNPs. In detail, AR1 consisted of 81,223 total SNPs which comprised 75,784 homozygous SNPs, 1,664 heterozygous SNPs, and 3,775 other SNPs. Similarly, a total of 43,453 SNPs which can be further classified into homozygous (38,741), heterozygous (1,481), and others (3,231) have been identified in TF68. The total SNPs in the F₅ population varied between 5,673 and 67,510 with the majority of homozygous SNPs followed by other types and heterozygous SNPs. From the SNP matrix constructed from the data obtained from 188 F₅ population, a total of 529,145 SNP loci were identified which were further filtered to 41,111 polymorphic SNPs (minimum ), and after the elimination of SNPs using the missing data (<30%) and minor allele frequency () criteria, 1,841 SNPs remained as the final SNPs for the construction of a genetic map (Table 1). The details of the SNP position in reference genome along with the parental lines and genotype data constructed using the final filtered 1,841 SNPs for 188 population are provided in supplementary dataset 3. The genotype data suggested the clustering of SNPs with the TF68 parental line with 29.1% (b) and AR1 (a) with 20.5%and 17.3% of h type involving both parents.

3.4. Construction of Genetic Linkage Map and QTL Analysis

A total of 12 linkage groups were constructed with 1,308 SNP markers selected from the final filtered SNPs covering the total linkage map length of 2506.8 cM (Table 2, Figure 2). Among the linkage group, the highest number of SNP markers (150) has been mapped in the LG03 and the lowest number of markers has been noted in the LG06 (33). Moreover, the LG05 consisted of SNPs positioned with the lowest map length of 120.2 cM and LG01with the highest map length of 265.4 cM. In order to investigate the QTLs related to powdery mildew disease resistance, the genetic linkage map constructed was utilized along with the phenotype disease index data obtained for the 188 pepper population. The multiple QTL mapping approach revealed two significant QTLs for powdery mildew resistance such as Pm-2.1 and Pm-5.1 in 188 individuals of F₅ population (Table 3). Both identified QTLs were minor QTLs with phenotypic variation () less than 10% (Pm-2.1: 9.6% and Pm-5.1: 9.7%). The identified QTLs were mapped onto the genetic map of pepper (Figure 2). The LOD scores obtained for the identified QTLs were 5.55 and 5.64 for Pm-2.1 and Pm-5.1, respectively, which were greater than the LOD threshold (4.5) (Figure 3). The QTL Pm-2.1 was located between 179.9 and 182.6 cM and Pm-5.1 between 9.4 and 10.0 cM in chromosomes 2 and 5, respectively. Alleles conferring resistance to powdery mildew resistance were attributed by the resistant parent (“AR1”) because of the identified additive effects. Further, the annotation of the flanking SNP markers based on the homology search denoted that the flanking sequence corresponding to the SNP165140859-SNP167455530 position in chromosome 2 was identified as uncharacterized noncoding RNA. Further, the sequence similarity analysis of flanking marker identified in chromosome 5 (SNP4731636-SNP233077832) corresponded to the leucine-rich repeat (LRR) receptor-like serine/threonine-protein kinases.

4. Discussion

Advancements in the field of next-generation sequencing and its allied high-throughput technologies have revolutionized the discovery and genotyping of single nucleotide polymorphic markers in horticultural crops. In the present study, the genomes of 190 capsicum lines including the two parental cultivars with contrasting powdery mildew resistance traits have been reduced using the ApekI for GBS library construction. The ApekI restriction enzyme is selected due to its methylation sensitivity and the ability to excise the gene-rich area in the genome [32]. Further, the GBS library was constructed and sequenced using the Illumina HiSeq 2000 platform. The average of total number of raw reads (586,469,230 bp) in the present study has been higher than the reads reported by Pereira-Dias et al. [33]. Also, the percentage of trimmed to raw reads in the F₅ population ranged between 78.25 and 85.49%. The trimmed reads were mapped to the reference genome with overall mapping percentage of 87.29% with 0.534% genome coverage. The GBS-generated sequence library was utilized for the discovery of SNP markers in the F₅ population. According to Oh et al. [34], the GBS-based SNPs aided in the anchoring of high-resolution genetic map in Pyrus pyrifolia with high accuracy.

SNPs are considered as the marker of choice because of its wide range of advantages such as ease of automation for large-scale assays, accuracy, and diallelic nature. Due to the robustness of NGS technologies, several researchers have developed SNP markers from peppers [3, 4]. However, the SNPs identified in the current endeavor could render the vital marker sets for the breeding of powdery mildew-resistant varieties since the F₅ population employed for the SNP identification has been derived from the interspecific breeding of sexually incompatible pepper species. In general, the progenies of interspecific breeding inherit economically important traits such as quality of fruits, resistance to diseases, and high composition of vital metabolites [35]. Similarly, the GBS-based SNP markers have been employed for the breeding of watermelon with Fusarium wilt resistance [36] and rubber trees [6] with resistance against fungal diseases. Moreover, the large number of SNPs discovered was majorly classified into homozygous type, illustrating that the sequence of reference genome could be produced from homozygous loci. Construction of the linkage map renders the initial basement for the QTL mapping. Previous studies have reported the construction of genetic map in pepper using both conventional methods and NGS-based methods in inter- and intraspecific capsicum varieties [37, 38]. However, the NGS-based mapping approach aids in the detection of large number of marker which facilitate the creation of high-density genetic maps. Recently, the high-resolution genetic map and QTL mapping of flowering traits have been constructed using the F₂ population obtained from the interspecific cross between C. annuum and C. chinense [19].

In the present study, the linkage map was constructed using a total of 1,308 SNP markers distributed throughout the pepper genome. Similarly, a GBS-based identification of SNP markers was utilized for the construction of genetic linkage map and QTL identification for cucumber mosaic virus resistance in pepper plants [39]. In addition, the genetic linkage map was utilized for the identification of QTLs using the multiple QTL mapping approach. The MQM analysis produced two QTLs Pm-2.1 and Pm-5.1 in chromosomes 2 and 5, respectively. Previous reports have illustrated the utilization of MQM-based QTL markers in peppers [40, 41]. According to Eun et al. [39], the CMV resistance QTL has been identified in chromosomes 5 and 10. Recent study by Siddique et al. [42] has identified the QTLs associated with the Phytophthora capsici resistance in pepper. The report evidenced the presence of QTLs related to disease resistance in chromosomes 2 and 5. In addition, the presence of three major QTLs conferring broad spectrum resistance to Phytophthora capsici was mapped to chromosome 5 [42]. Similarly, the annotation of flanking SNP markers resulted in the identification of LRR receptor-like serine/threonine-protein kinases which have been widely studied for its disease resistance in pepper. Previous reports also suggested the identification of QTL regions flanked by the SNP markers in LRR-related genes rendering disease resistance in pepper against Phytophthora capsici [42].

Overall, the outcomes of the present study can be utilized for the development of molecular markers for the marker-assisted breeding of pepper with powdery mildew resistance.

5. Conclusions

The present study illustrated the genotyping by sequencing-based SNP marker discovery in 188 F₅ pepper population derived from C. annuum with contrasting powdery mildew disease resistance characteristics. The disease resistance has been evaluated in all the lines, and the SNP markers identified have been annotated to understand the essential role in their associated genes. Moreover, SNPs identified have been utilized for the construction of the genetic linkage map. Further, the QTLs associated with the powdery mildew resistance have been identified. Overall, the outcomes of the present endeavor can be utilized for the development of molecular markers for the marker-assisted breeding of pepper with powdery mildew resistance.

Data Availability

No data were used to support this study.

Conflicts of Interest

The authors declare no conflict of interest.

Authors’ Contributions

Tae-Hwan Jun and Yul-Kyun Ahn were responsible for conceptualization; Sena Choi, Eun-Young Yang, and Yul-Kyun Ahn were responsible for data curation; Jinhee Kim, Eunsu Lee, Hye-Eun Lee, Do-Sun Kim, and Yul-Kyun Ahn were responsible for formal analysis; Yul-Kyun Ahn was responsible for funding acquisition; Abinaya Manivannan was responsible for methodology; Abinaya Manivannan was responsible for writing the original draft. Abinaya Manivannan and Sena Choi equally contributed to this work.

Acknowledgments

This research work was supported by the Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01106801), Rural Development Administration, Republic of Korea.

Supplementary Materials

Supplementary Table 1: the complete GBS statistics of pepper population employed in the present study. Supplementary Table 2: the list of SNP markers discovered and classified into homozygous, heterozygous, and others in all the pepper population employed in this study. Supplementary data 3: the list of genotype data observed for the 188 population using the 1,841 final filtered SNP markers. Supplementary Figure 1: phenotype of the plants used for scoring the disease index in 0-4 scale. (Supplementary Materials)

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Copyright © 2021 Abinaya Manivannan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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