• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.79-86
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• 2006

Recently the tagSNP selection problem has been researched for reducing the cost of association studies between human's diversities and SNPs. General approach for this problem is that all of SNPs are separated into appropriate blocks and then tagSNPs are chosen in each block. Marsel in this paper is the system that involved the concept of linkage disequilibrium for overcoming the problem that the existing block partitioning approaches have short of biological meanings. In most approaches, the contiguous regions, which recombinations have LD coefficient |D'| and then tagSNP selection step is performed. And MarSel guarantees the minimum tagSNP selection using entropy-based optimal selection algorithm when tagSNPs are chosen in each block, and enables chromosome-level association studies using efficient memory management technique when input is very large-scale dataset that is impossible to be processed in the existing systems.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.493-500
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• 2008

In this paper, we first construct a mathematical model for tagSNP selection based on LD measure $r^2$, then aiming at this kind of model, we develop an efficient algorithm, which is called approximate greedy algorithm. This algorithm is able to make up the disadvantage of the greedy algorithm for tagSNP selection. The key improvement of our approximate algorithm over greedy algorithm lies in that it adds local replacement(or local search) into the greedy search, tagSNP is replaced with the other SNP having greater similarity degree with it, and the local replacement is performed several times for a tagSNP so that it can improve the tagSNP set of the local precinct, thereby improve tagSNP set of whole precinct. The computational results prove that our approximate greedy algorithm can always find more efficient solutions than greedy algorithm, and improve the tagSNP set of whole precinct indeed.

• Journal of Plant Biotechnology
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• v.47 no.3
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• pp.218-226
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• 2020

This report describes methods for selecting informative single nucleotide polymorphisms (SNPs), and the development of an online Solanaceae genome database, using 234 tomato resequencing data entries deposited in the NCBI SRA database. The 126 accessions of Solanum lycopersicum, 68 accessions of Solanum lycopersicum var. cerasiforme, and 33 accessions of Solanum pimpinellifolium, which are frequently used for breeding, and some wild-species tomato accessions were included in the analysis. To select tag-SNPs, we identified 29,504,960 SNPs in 234 tomatoes and then separated the SNPs in the genic and intergenic regions according to gene annotation. All tag-SNP were selected from non-synonymous SNPs among the SNPs present in the gene region and, as a result, we obtained tag-SNP from 13,845 genes. When there were no non-synonymous SNPs in the gene, the genes were selected from synonymous SNPs. The total number of tag-SNPs selected was 27,539. To increase the usefulness of the information, a Solanaceae genome database website, TGsol (http://tgsol. seeders.co.kr/), was constructed to allow users to search for detailed information on resources, SNPs, haplotype, and tag-SNPs. The user can search the tag-SNP and flanking sequences for each gene by searching for a gene name or gene position through the genome browser. This website can be used to efficiently search for genes related to traits or to develop molecular markers.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.279-285
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• 2004

In the disease association study, the tagSNP selection problem is important at the view of time and cost. We developed the new tagSNP selection system that has also facilities for the haplotype reconstruction and missing data processing. In our system, we improved biological meanings using LD coefficients as well as dynamic programming method. And our system has capability of processing large -scale dataset, such as the total SNPs on a chromosome. We have tested our system with various dataset from daly et al., patil et al., HapMap Project, artificial dataset, and so on.

• Korean Journal of Agricultural Science
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• v.45 no.3
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• pp.385-400
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• 2018

Marker-assisted backcrossing (MABC) is useful for selecting offspring with a highly recovered genetic background for a recurrent parent at early generation unlike rice and other field crops. Molecular marker sets applicable to practical MABC are scarce in vegetable crops including tomatoes. In this study, we used the National Center for Biotechnology Information- short read archive (NCBI-SRA) database that provided the whole genome sequences of 234 tomato accessions and selected 27,680 tag-single nucleotide polymorphisms (tag-SNPs) that can identify haplotypes in the tomato genome. From this SNP dataset, a total of 143 tag-SNPs that have a high polymorphism information content (PIC) value (> 0.3) and are physically evenly distributed on each chromosome were selected as a MABC marker set. This marker set was tested for its polymorphism in each pairwise cross combination constructed with 124 of the 234 tomato accessions, and a relatively high number of SNP markers polymorphic for the cross combination was observed. The reliability of the MABC SNP set was assessed by converting 18 SNPs into Luna probe-based high-resolution melting (HRM) markers and genotyping nine tomato accessions. The results show that the SNP information and HRM marker genotype matched in 98.6% of the experiment data points, indicating that our sequence analysis pipeline for SNP mining worked successfully. The tag-SNP set for the MABC developed in this study can be useful for not only a practical backcrossing program but also for cultivar identification and F1 seed purity test in tomatoes.

• Development and Reproduction
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• v.18 no.4
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• pp.275-286
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• 2014

To successful molecular breeding, identification and functional characterization of breeding related genes and development of molecular breeding techniques using DNA markers are essential. Although the development of a useful marker is difficult in the aspect of time, cost and effort, many markers are being developed to be used in molecular breeding and developed markers have been used in many fields. Single nucleotide polymorphisms (SNPs) markers were widely used for genomic research and breeding, but has hardly been validated for screening functional genes in olive flounder. We identified single nucleotide polymorphisms (SNPs) from expressed sequence tag (EST) database in olive flounder; out of a total 4,327 ESTs, 693 contigs and 514 SNPs were detected in total EST, and these substitutions include 297 transitions and 217 transversions. As a result, 144 SNP markers were developed on the basis of 514 SNP to selection of useful gene region, and then applied to each of eight wild and culture olive flounder (total 16 samples). In our experimental result, only 32 markers had detected polymorphism in sample, also identified 21 transitions and 11 transversions, whereas indel was not detected in polymorphic SNPs. Heterozygosity of wild and cultured olive flounder using the 32 SNP markers is 0.34 and 0.29, respectively. In conclusion, we identified SNP and polymorphism in olive flounder using newly designed marker, it supports that developed markers are suitable for SNP detection and diversity analysis in olive flounder. The outcome of this study can be basic data for researches for immunity gene and characteristic with SNP.

• Genomics & Informatics
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• v.5 no.4
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• pp.188-193
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• 2007

The Functional Element SNPs Database (FESD) categorizes functional elements in human genic regions and provides a set of single nucleotide polymorphisms (SNPs) located within each area. Users may select a set of SNPs in specific functional elements with haplotype information and obtain flanking sequences for genotyping. Our previous version of FESD has been improved in several ways. We regenerated all the data in FESD II from recently updated source data such as HapMap, UCSC GoldenPath, dbSNP, OMIM, and $TRANSFAC^{(R)}$. Users can obtain information about tagSNPs and simulate LD blocks for each gene from four ethnicities in the HapMap project on the fly. FESD II employs a Java/JSP web interface for better platform portability and higher speed than PHP in the previous version. As a result, FESD II provides its users with more powerful information about functional element SNPs of human ethnicities.

• Korean Journal of Poultry Science
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• v.41 no.1
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• pp.29-37
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• 2014

The Feather Color of chicken is considered as most obvious, and the purpose of this study is to identify the genotype following the SNP of MC1R, MITF and TYRP1, which are genes related to Feather Color, and develop a SNP marker that can be classified per breed. When a haplotype is observed through the combination of markers, a Korean Native Chicken can especially be distinguished when it is a CGG type in the SNP combination of the MC1R gene. In case of the TAG, TGG and TAA types, only Araucana was identified, and for the CAA type, Leghorn could specifically be distinguished. In the SNP combination of TYRP1 gene, only Leghorn was differentiated in case of the TTTCA and CCTCA types, and only Silky Fowl was identified in case of the CTTTA type. The SNP combination of MC1R gene enabled for Korean Native Chicken, Leghorn, and Araucana to be distinguished and each of the SNP and combination of TYRP1 gene allowed for all 4 breeds to be classified. If many researches are conducted about genetic polymorphism between breeds, then it is considered that the differences between breeds will be understood from a molecular biological aspect instead of simply distinguishing the breeds through Feather Color.

• The Korea Genome Conference
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• 2006.09a
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• pp.46-46
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• 2006

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.253-255
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• 2004

인간(human)에게 나타나는 다양성(variation)은 인체의 유전체(genome) 안에서 발생된 SNP(Single Nucleotide Polymorphism)에 의해 나타난다고 알려져 있다. 유전체내의 SNP과 다양성에 대한 연관 연구(Associate study)를 할 때에 약 30여 억 개로 추정되는 염기서열(DNA sequence)물 모두 분석한다면 많은 비용과 시간을 필요로 할 것이다. 이런 비용과 시간을 줄이기 위친 적은 수의 대표 SNP(=tagSNP)을 찾는 연구가 현재 진행 중이다. 우리는 LD계수｜D;｜을 block 분할에 이용하여 생물학적인 의미를 부여한 후, 전산적인 최적해를 찾는 접근을 이용했다. 또한, 기존 연구에서는 large-scale data에 대한 처리가 불가능해서 chromosome의 일부분의 데이터에 대해서안 분석이 시도되었다. 더욱 광범위한 분석을 위해서 chromosome 단위의 처리가 필요하다. 우리는 chromosome단위의 SNP data를 한 번에 처리가 가능한 시스템인 MarSel를 구현하였다