• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.58-58
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• 2017

The advent of next generation sequencing technology has elicited plenty of sequencing data available in agriculturally relevant plant species. For most crop species, it is too expensive to obtain the whole genome sequence data with sufficient coverage. Thus, many approaches have been developed to bring down the cost of NGS. Genotyping-by-sequencing (GBS) is a cost-effective genotyping method for complex genetic populations. GBS can be used for the analysis of genomic selection (GS), genome-wide association study (GWAS) and constructing haplotype and genetic linkage maps in a variety of plant species. For efficiently dealing with plant GBS data, the TASSEL-GBS pipeline is one of the most popular choices for many researchers. TASSEL-GBS is JAVA based a software package to obtain genotyping data from raw GBS sequences. Here, we describe application of GBS and bioinformatics pipeline of TASSEL-GBS for analyzing plant genetics data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2491-2499
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• 2015

Recently, the most popular technique to determine the Genotype, genetic features of individual organisms, is the GBS based on SNP from sequences determined by NGS. As analyzing the sequences by the GBS, TASSEL is the most used program to identify the genotypes. But, TASSEL has limitation that it uses only the partial sequences that is obtained by NGS. We tried to improve the efficiency in use of the sequences in order to solve the limitation. So, we constructed new data sets by quality checking, filtering the unused sequences with error rate below 0.1% and clipping the sequences considering the location of barcode and enzyme. As a result, approximately over 17% of the SNP detection efficiency was increased. In this paper, we suggest the method and the applied programs in order to detect more SNPs by using the disused sequences.

• Plant Breeding and Biotechnology
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• v.6 no.4
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• pp.434-443
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• 2018

Genotyping-by-sequencing (GBS) has been used as a viable single nucleotide polymorphism (SNP) validation method that provides reduced representation sequencing by using restriction endonucleases. Although GBS makes it possible to perform marker discovery and genotyping simultaneously with reasonable costs and a simple molecular biology workflow, the standard TASSEL-GBS pipeline was designed for homozygous groups, and genotyping of heterozygous groups is more complicated. To addresses this problem, we developed a GBS pipeline for heterozygous groups that called KNU-GBS pipeline, specifically for apple (Malus domestica). Using KNU-GBS pipeline, we constructed a genetic linkage map consisting of 1,053 SNP markers distributed over 17 linkage groups encompassing a total of 1350.1 cM. The novel GBS pipeline for heterozygous groups will be useful for marker-assisted breeding programs, and diverse heterozygous genome analyses.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.57-57
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• 2017

Chrysanthemum is one of the most important floral crop in Korea produced about 7 billion dollars (1 billion for pot and 6 billion for cutting) in 2013. However, it is difficult to breed and to do genetic study because 1) it is highly self-incompatible, 2) it is outcrossing crop having heterozygotes, and 3) commercial cultvars are hexaploid (2n = 6x = 54). Although low-density genetic map and QTL study were reported, it is not enough to apply for the marker assisted selection and other genetic studies. Therefore, we are trying to make high-density genetic mapping using GBS with about 100 $F_1s$ of C. boreale that is oHohhfd diploid (2n = 2x = 18, about 2.8Gb) instead of commercial culitvars. Since Chrysanthemum is outcrossing, two-way pseudo-testcross model would be used to construct genetic map. Also, genotype-by-sequencing (GBS) would be utilized to generate sufficient number of markers and to maximize genomic representation in a cost effective manner. Those completed sequences would be analyzed with TASSEL-GBS pipeline. In order to reduce sequence error, only first 64 sequences, which have almost zero percent error, would be incorporated in the pipeline for the analysis. In addition, to reduce errors that is common in heterozygotes crops caused by low coverage, two rare cutters (NsiI and MseI) were used to increase sequence depth. Maskov algorithm would also used to deal with missing data. Further, sparsely placed markers on the physical map would be used as anchors to overcome problems caused by low coverage. For this purpose, were generated from transcriptome of Chrysanthemum using MISA program. Among those, 10 simple sequence repeat (SSR) markers, which are evenly distributed along each chromosome and polymorphic between two parents, would be selected.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.62-62
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• 2019

Bacterial leaf blight(BLB), caused by X. oryzae pv. oryzae(Xoo), is one of the most destructive diseases of rice due to its high epidemic potential. Understanding BLB resistance at a genetic level is important to further improve the rice breeding that provides one of the best approaches to control BLB disease. In the present investigation, a collection of 192 accessions was used in the genome-wide association study (GWAS) for BLB resistance loci against four Korean races of Xoo that were represented by the prevailing BLB isolates under Xoo differential system. A total of 192 accessions of rice germplasm were selected on the basis of the bioassay using four isolated races of Xoo such as K1 and K2. The selected accessions was used to prepare 384-plex genotyping by sequencing (GBS) libraries and Illumina HiSeq 2000 pairedend read was used for GBS sequencing. GWAS was conducted using TASSEL 5.0. The TASSEL program uses a mixed linear model (MLM). The results of the bioassay using a selected set of 192 accessions showed that a large number of accessions (93.75%) were resistant to K1 race and K2 resistant germplasm proportion remained between 66.67. The genotypic data produced SNP matrix for a total of 293,379 SNPs. After imputation the missing data was removed, which exhibited 34,724 SNPs for association analysis. GWAS results showed strong signals of association at a threshold of [-log10(P-value)] more than 5 (K1 and K2) for nine of the 39 SNPs, which are plausible candidate loci of resistance genes. These SNP loci were positioned on rice chromosome 2, 9, and 11 for K1 and K2 races. The significant loci detected have also been illustrated and make the CPAS markers for NBS-LRR type disease resistance protein, SNARE domain containing protein, Histone deacetylase 19, NADP-dependent oxidoreductase, and other expressed and unknown proteins. Our results provide a better understanding of the distribution of genetic variation of BLB resistance to Korean pathogen races and breeding of resistant rice.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.19-19
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• 2019

유전체 전장 연관분석 (GWAS)은 단일염기다형성(SNP)의 유전자형과 표현형 간의 통계적인 연관성을 분석함으로써 품종 선발용 SNP Marker 개발에 응용되고 있다. 본 연구에서는 Tano Red와 Ruby seedless 교배실생 278 계통을 대상으로 여러 과실 특성에 따른 관련 SNP를 동정함으로써 육종 선발에 필요한 DNA marker 개발에 필요한 기초 유전 자료를 얻고자 하였다. 한 계통 당 5~10개의 포도알을 선택하여 과립중, 과육탄성, 과피탄성, 과육경도, 과피경도, 과립당 종자갯수, 과립당 종자무게 및 인장강도를 측정하였다. 각 개체는 Genotyping by sequencing (GBS) 방법으로 Sequencing하여 Reference genome (Vitis vinifera PN40024 12X v2.)과 mapping 하였다. MAF (Minor allele frequency) >5%, Missing Data <30% 의 조건을 가진 SNPs 만 1차 선발하여 TASSEL과 GAPIT 프로그램으로 GWAS 분석을 하였다. Manhattan plot 결과 과립중 형질에서는 33개, 과립당 종자무게 25개와 인장강도에서는 20개의 통계학적으로 유의한 SNPs 가 선발되었고, 특이적으로 이들 모두 18번 염색체에서 발견되었다. 그러나 나머지 형질에서는 유의한 차이를 보이는 SNPs를 선발하지 못하였다. 과실의 인장강도는 수확 후 저장성과 유통과정에 영향을 미치기 때문에 Marker 개발을 통한 품종선별이 중요하다. 향후 이러한 특성과 본 연구를 통해 동정된 SNPs 의 상관관계를 구체적으로 연구하여 Marker 개발에 활용하고자 한다.