Fine mapping the soybean foxglove aphid resistance gene Raso2 in soybean using 180K Axiom® SoyaSNP genotyping assay

Ju Seok Lee,Sungmin Kim,Sumin Park,Kyungryun Kim,Mijung Cho,Eunsil Kim,Jin Kyo Jung,Jeong-Dong Lee,Jung-Kyung Moon,Namshin Kim,Soon-chun Jeong,Sungtaeg Kang 한국육종학회 2015 한국육종학회 심포지엄 Vol.2015 No.07

Foxglove aphid, Aulacorthum solani (Kaltenbach), is a Hemipteran insect that infected a wide variety of plants worldwide and caused serious yield losses in crops. The foxglove aphid resistance gene, Raso2 was previously mapped from PI 366121 (Glycine soja Sieb. and Zucc.) to a 26cM marker interval on soybean chromosome 7. The development of additional genetic markers, which are mapped closer to Raso2 were required to accurately position the gene to improve the effectiveness of marker assisted selection. The objective of this study was to narrow down the putative QTL region, which is responsible to foxglove aphid resistance in PI366121 using recently developed high-density 180K Axiom SoyaSNP genotyping array. One hundred and forty one F8-derived F12 recombinant inbred lines developed from a cross of susceptible Williams 82 and resistant PI 366121, were used to generate a fine map of Raso2 interval. The phenotyping of antibiosis and antixenosis was done through choice and no-choice assays with total plant damage (TPD) and primary infestation leaf damage (PLD). The composite interval mapping analysis showed that the physical interval between two flanking makers, which was corresponding to Raso2, was narrowed down to 500kb on the Williams 82 genome assembly (Glyma2.0), instead of 4Mb in the previous report using Goldengate assay. In the Raso2 interval, there are about 60 candidate genes, including 4 of NBS-containing putative R genes. This result could be useful in breeding for new foxglove aphid resistant soybean cultivars.

Genetic Differences between Physical Injury Patients With and Without Post-traumatic Syndrome: Focus on Secondary Findings and Potential Variants Revealed by Whole Exome Sequencing

Hee-Ju Kang,Ho-Yeon Lee,Ki-Tae Kim,Ju-Wan Kim,Ju-Yeon Lee,Sung-Wan Kim,Jung Chul Kim,Il-Seon Shin,Namshin Kim,김재민 대한정신약물학회 2021 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.19 No.4

Objective: Sudden traumatic physical injuries often cause psychological distress, which may be associated with chronic disability. Although considerable effort has been expended to identify genetic predictors of post-traumatic stress disorder (PTSD) after traumatic events, genetic predictors of psychological distress in response to severe physical injuries have been yet to be elucidated using whole exome sequencing (WES). Here, the genetic architecture of post-traumatic syndrome (PTS), which encompasses a broad range of psychiatric disorders after traumatic events including depression, anxiety disorder, acute stress disorder, and PTSD, was explored using WES in severely physically injured patients, focusing on secondary findings and potential PTS-related variants. Methods: In total, 141 severely physically injured patients were consecutively recruited, and PTS was evaluated within 1 month of the injury. Secondary findings were analyzed according to PTS status. To identify PTS-related variants, genome-wide association analyses and the optimal sequencing kernel association test were performed. Results: Of the 141 patients, 88 (62%) experienced PTS. There were 108 disease-causing variants in severely physically injured patients. As secondary findings, the stress- and inflammation-related signaling pathways were enriched in the PTS patients, while the glucose metabolism pathway was enriched in those without PTS. However, no significant PTS-related variants were identified. Conclusion: Our findings suggest that genetic alterations in stress and inflammatory pathways might increase the likelihood of PTS immediately after severe physical injury. Future studies with larger samples and longitudinal designs are needed.

Effect of Next-Generation Exome Sequencing Depth for Discovery of Diagnostic Variants

Kim, Kyung,Seong, Moon-Woo,Chung, Won-Hyong,Park, Sung Sup,Leem, Sangseob,Park, Won,Kim, Jihyun,Lee, KiYoung,Park, Rae Woong,Kim, Namshin Korea Genome Organization 2015 Genomics & informatics Vol.13 No.2

Sequencing depth, which is directly related to the cost and time required for the generation, processing, and maintenance of next-generation sequencing data, is an important factor in the practical utilization of such data in clinical fields. Unfortunately, identifying an exome sequencing depth adequate for clinical use is a challenge that has not been addressed extensively. Here, we investigate the effect of exome sequencing depth on the discovery of sequence variants for clinical use. Toward this, we sequenced ten germ-line blood samples from breast cancer patients on the Illumina platform GAII(x) at a high depth of ${\sim}200{\times}$. We observed that most function-related diverse variants in the human exonic regions could be detected at a sequencing depth of $120{\times}$. Furthermore, investigation using a diagnostic gene set showed that the number of clinical variants identified using exome sequencing reached a plateau at an average sequencing depth of about $120{\times}$. Moreover, the phenomena were consistent across the breast cancer samples.

ASmodeler: gene modeling of alternative splicing from genomic alignment of mRNA, EST and protein sequences

Kim, Namshin,Shin, Seokmin,Lee, Sanghyuk Oxford University Press 2004 Nucleic acids research Vol.32 No.suppl2

<P>Alternative splicing is in important mechanism of modulating gene function and expression which greatly expands transcriptome diversity. ASmodeler is a novel web-based utility that finds gene models including alternative splicing events from genomic alignment of mRNA, EST and protein sequences. User-supplied sequences are aligned against the genome map using the BLAT and SIM4 programs. Resulting exon connectivity is analyzed by applying graph-theoretic methods to build all possible gene models including splice variants. The algorithm essentially combines the genome-based sequence clustering and transcript assembly procedures in a coherent fashion. In addition to the user-supplied sequences, UniGene clusters and many well-known gene predictions such as Genscan, Ensembl and Acembly may be included in gene modeling. The current implementation supports human, mouse and rat genomes. ASmodeler is available at http://genome.ewha.ac.kr/ECgene/ASmodeler/.</P>

ASePCR: alternative splicing electronic RT–PCR in multiple tissues and organs

Kim, Namshin,Lim, Dajeong,Lee, Sanghyuk,Kim, Heebal Oxford University Press 2005 Nucleic acids research Vol.33 No.2

<P>RT–PCR is one of the most powerful and direct methods to detect transcript variants due to alternative splicing (AS) that increase transcript diversity significantly in vertebrates. ASePCR is an efficient web-based application that emulates RT–PCR in various tissues. It estimates the amplicon size for a given primer pair based on the transcript models identified by the reverse e-PCR program of the NCBI. The tissue specificity of each PCR band is deduced from the tissue information of expressed sequence tag (EST) sequences compatible with each transcript structure. The output page shows PCR bands like a gel electrophoresis in various tissues. Each band in the output picture represents a putative isoform that could happen in a tissue-specific manner. It also shows the EST alignment and tissue information in the genome browser. Furthermore, the user can compare the AS patterns of orthologous genes in other species. The ASePCR, available at , supports the transcriptome models of the RefSeq, Ensembl, ECgene and AceView for human, mouse, rat and chicken genomes. It will be a valuable web resource to explore the transcriptome diversity associated with different tissues and organs in multiple species.</P>

ECgene: genome annotation for alternative splicing

Kim, Pora,Kim, Namshin,Lee, Younghee,Kim, Bumjin,Shin, Youngah,Lee, Sanghyuk Oxford University Press 2005 Nucleic acids research Vol.33 No.1

<P>ECgene provides annotation for gene structure, function and expression, taking alternative splicing events into consideration. The gene-modeling algorithm combines the genome-based expressed sequence tag (EST) clustering and graph-theoretic transcript assembly procedures. The website provides several viewers and applications that have many unique features useful for the analysis of the transcript structure and gene expression. The summary viewer shows the gene summary and the essence of other annotation programs. The genome browser and the transcript viewer are available for comparing the gene structure of splice variants. Changes in the functional domains by alternative splicing can be seen at a glance in the transcript viewer. We also provide two unique ways of analyzing gene expression. The SAGE tags deduced from the assembled transcripts are used to delineate quantitative expression patterns from SAGE libraries available publically. Furthermore, the cDNA libraries of EST sequences in each cluster are used to infer qualitative expression patterns. It should be noted that the ECgene website provides annotation for the whole transcriptome, not just the alternatively spliced genes. Currently, ECgene supports the human, mouse and rat genomes. The ECgene suite of tools and programs is available at http://genome.ewha.ac.kr/ECgene/.</P>

ChimerDB 2.0—a knowledgebase for fusion genes updated

Kim, Pora,Yoon, Suhyeon,Kim, Namshin,Lee, Sanghyun,Ko, Minjeong,Lee, Haeseung,Kang, Hyunjung,Kim, Jaesang,Lee, Sanghyuk Oxford University Press 2010 Nucleic acids research Vol.38 No.suppl1

<P>Chromosome translocations and gene fusions are frequent events in the human genome and have been found to cause diverse types of tumor. ChimerDB is a knowledgebase of fusion genes identified from bioinformatics analysis of transcript sequences in the GenBank and various other public resources such as the Sanger cancer genome project (CGP), OMIM, PubMed and the Mitelman’s database. In this updated version, we significantly modified the algorithm of identifying fusion transcripts. Specifically, the new algorithm is more sensitive and has detected 2699 fusion transcripts with high confidence. Furthermore, it can identify interchromosomal translocations as well as the intrachromosomal deletions or inversions of large DNA segments. Importantly, results from the analysis of next-generation sequencing data in the short read archives are incorporated as well. We updated and integrated all contents (GenBank, Sanger CGP, OMIM, PubMed publications and the Mitelman’s database), and the user-interface has been improved to support diverse types of searches and to enhance the user convenience especially in browsing PubMed articles. We also developed a new alignment viewer that should facilitate examining reliability of fusion transcripts and inferring functional significance. We expect ChimerDB 2.0, available at http://ercsb.ewha.ac.kr/fusiongene, to be a valuable tool in identifying biomarkers and drug targets.</P>

ERRATUM: Acknowledgments Correction

Kim, Jiwoong,Lee, Yun-Gyeong,Kim, Namshin Korea Genome Organization 2013 Genomics & informatics Vol.11 No.2

ECgene: genome-based EST clustering and gene modeling for alternative splicing.

Kim, Namshin,Shin, Seokmin,Lee, Sanghyuk Cold Spring Harbor Laboratory Press 2005 Genome Research Vol.15 No.4

<P>With the availability of the human genome map and fast algorithms for sequence alignment, genome-based EST clustering became a viable method for gene modeling. We developed a novel gene-modeling method, ECgene (Gene modeling by EST Clustering), which combines genome-based EST clustering and the transcript assembly procedure in a coherent and consistent fashion. Specifically, ECgene takes alternative splicing events into consideration. The position of splice sites (i.e., exon-intron boundaries) in the genome map is utilized as the critical information in the whole procedure. Sequences that share any splice sites are grouped together to define an EST cluster in a manner similar to that of the genome-based version of the UniGene algorithm. Transcript assembly is achieved using graph theory that represents the exon connectivity in each cluster as a directed acyclic graph (DAG). Distinct paths along exons correspond to possible gene models encompassing all alternative splicing events. EST sequences in each cluster are subclustered further according to the compatibility with gene structure of each splice variant, and they can be regarded as clone evidence for the corresponding isoform. The reliability of each isoform is assessed from the nature of cluster members and from the minimum number of clones required to reconstruct all exons in the transcript.</P>

Bioinformatics Interpretation of Exome Sequencing: Blood Cancer

Kim, Jiwoong,Lee, Yun-Gyeong,Kim, Namshin Korea Genome Organization 2013 Genomics & informatics Vol.11 No.1

We had analyzed 10 exome sequencing data and single nucleotide polymorphism chips for blood cancer provided by the PGM21 (The National Project for Personalized Genomic Medicine) Award program. We had removed sample G06 because the pair is not correct and G10 because of possible contamination. In-house software somatic copy-number and heterozygosity alteration estimation (SCHALE) was used to detect one loss of heterozygosity region in G05. We had discovered 27 functionally important mutations. Network and pathway analyses gave us clues that NPM1, GATA2, and CEBPA were major driver genes. By comparing with previous somatic mutation profiles, we had concluded that the provided data originated from acute myeloid leukemia. Protein structure modeling showed that somatic mutations in IDH2, RASGEF1B, and MSH4 can affect protein structures.