Time filter

Source Type

Suigen, South Korea

Kim K.M.,Sungkyunkwan University | Park J.-H.,Insilicogen Inc. | Bhattacharya D.,Rutgers University | Yoon H.S.,Sungkyunkwan University
International Journal of Systematic and Evolutionary Microbiology | Year: 2014

First-generation Sanger DNA sequencing revolutionized science over the past three decades and the current next-generation sequencing (NGS) technology has opened the doors to the next phase in the sequencing revolution. Using NGS, scientists are able to sequence entire genomes and to generate extensive transcriptome data from diverse photosynthetic eukaryotes in a timely and cost-effective manner. Genome data in particular shed light on the complicated evolutionary history of algae that form the basis of the food chain in many environments. In the Eukaryotic Tree of Life, the fact that photosynthetic lineages are positioned in four supergroups has important evolutionary consequences. We now know that the story of eukaryotic photosynthesis unfolds with a primary endosymbiosis between an ancestral heterotrophic protist and a captured cyanobacterium that gave rise to the glaucophytes, red algae and Viridiplantae (green algae and land plants). These primary plastids were then transferred to other eukaryotic groups through secondary endosymbiosis. A red alga was captured by the ancestor(s) of the stramenopiles, alveolates (dinoflagellates, apicomplexa, chromeridae), cryptophytes and haptophytes, whereas green algae were captured independently by the common ancestors of the euglenophytes and chlorarachniophytes. A separate case of primary endosymbiosis is found in the filose amoeba Paulinella chromatophora, which has at least nine heterotrophic sister species. Paulinella genome data provide detailed insights into the early stages of plastid establishment. Therefore, genome data produced by NGS have provided many novel insights into the taxonomy, phylogeny and evolutionary history of photosynthetic eukaryotes. © 2014 IUMS. Source

Shin G.-H.,Insilicogen Inc. | Shin G.-H.,TU Berlin | Veen M.,Focus Ingredients GmbH | Stahl U.,TU Berlin | And 2 more authors.
Yeast | Year: 2012

Saccharomyces cerevisiae strains with deregulated sterol and fatty acid biosynthesis pathways were analysed for sterol and fatty acid content and mRNA profiles, with the aim of identifying interactions between lipid biosynthesis pathways. Acetyl CoA carboxylase ACC1 and fatty acid synthases FAS1/FAS2 were overexpressed in wild-type and squalene-overproducing strains. ACC1 overexpression led to decreased fatty acid content in the squalene-overproducing strain (factor of 0.7), while sterols and squalene were increased (factor of 1.5). In the wild-type strain, ACC1 overexpression led to increased levels of both fatty acids and squalene/sterols (factors of 4.0 and 1.7, respectively). This parallel activation of the two pathways seems to be due to transcriptional co-regulation of ACC1 and HMG1. While FAS1 and FAS2 overexpression had no effect in the wild-type strain, FAS2 overexpression induced significant increase of sterols and squalene (factors of 7.2 and 1.3, respectively) and a concomitant decrease of both saturated and unsaturated fatty acids in the squalene-overproducing strain (factor of 0.6). The microarray expression profiles showed that genes upregulated in ACC1-overexpressing strains are FAS1, ERG11, ERG28, ERG5, ERG2 and ERG20, supporting the observed increase of zymosterol and saturated fatty acids. The high ACC1 expression level due to overexpression correlated with increased transcript levels of sphingolipid and sterol biosynthesis genes. The relationship between was shown using the Pathway Studio™ program. © 2012 John Wiley & Sons, Ltd. Source

Kang B.-C.,Insilicogen Inc. | Sur Z.-W.,Bayer AG | Park C.,Kwangwoon University | Cho M.-G.,Dongseo University
Biochip Journal | Year: 2010

A document search in PubMed is certainly one of the most exhaustive ways for finding information related to any biological or biomedical topic. However, a keyword search in this database that is not specific enough will provide a number of results that exceeds by far an amount of documents the user can read through one by one. In this work, we therefore present a new document clustering tool called Med- Clus for bioinformaticians in order to make a keyword search result from PubMed more concise by grouping such a set of documents into clusters. MedClus contains two modules. First, a pre-clustering module that creates the data matrix. This matrix contains term-document frequencies according to the TF*IDF method and optional weights. These weights are given by comparing the term list with the MeSH terms contained in the related MEDLINE abstracts. Second, it contains a clustering module, which is based on a Non-negative Matrix Factorization algorithm that finds an approximate factorization of the data matrix. This application was tested in different experiments evaluating its performance and reliability. Based on these results, a list of recommended ranges for crucial parameters such as the number of clusters was edited in order to constitute an user assistance for the application of Med- Clus. Finally, some results were analyzed by scientists from the field of medicine and biology, who evaluated the relevance of the terms and the existence of a relation between them. MedClus is a tool that is able to re-structure the result list of a keyword search for documents in PubMed. This is done by extracting terms before and finding latent semantics during the clustering process. Also, it optionally applies weights to terms that also appear as MeSH terms in at least one of the MEDLINE abstracts. Therefore, it helps users to refine a search result in PubMed via term-based clustering in order to economize time and efforts. At this development stage, the software is suitable for experienced users such as bioinformaticians, database administrators and developers. Also Web service for Semantic Toxicogenomics Knowledgebase, available at http://stkb2. labkm.net, has applied this technology to provide comprehensive and accurate relations between chemical and toxicological contexts. © The Korean BioChip Society and Springer 2010. Source

Subramaniyam S.,Kyung Hee University | Subramaniyam S.,Insilicogen Inc. | Mathiyalagan R.,Kyung Hee University | Natarajan S.,Kyung Hee University | And 4 more authors.
Gene | Year: 2014

Panax ginseng Meyer is one of the major medicinal plants in oriental countries belonging to the Araliaceae family which are the primary source for ginsenosides. However, very few genes were characterized for ginsenoside pathway, due to the limited genome information. Through this study, we obtained a comprehensive transcriptome from adventitious roots, which were treated with methyl jasmonic acids for different time points (control, 2. h, 6. h, 12. h, and 24. h) and sequenced by RNA 454 pyrosequencing technology. Reference transcriptome 39,304,529 (0.04. GB) was obtained from 5,724,987,880 bases (5.7. GB) of 22 libraries by de novo assembly and 35,266 (58.5%) transcripts were annotated with biological schemas (GO and KEGG). The digital gene expression patterns were obtained from in vitro grown adventitious root sequences which mapped to reference, from that, 3813 (6.3%) unique transcripts were involved in ≥. 2 fold up and downregulations. Finally, candidates for ginsenoside pathway genes were predicted from observed expression patterns. Among them, 30 transcription factors, 20 cytochromes, and 11 glycosyl transferases were predicted as ginsenoside candidates. These data can remarkably expand the existing transcriptome resources of Panax, especially to predict existence of gene networks in P. ginseng. The entity of the data provides a valuable platform to reveal more on secondary metabolism and abiotic stresses from P. ginseng in vitro grown adventitious roots. © 2014 Elsevier B.V. Source

Rengaraj D.,Seoul National University | Rengaraj D.,Chung - Ang University | Lee S.I.,Seoul National University | Park T.S.,Seoul National University of Science and Technology | And 7 more authors.
BMC Genomics | Year: 2014

Background: Genes, RNAs, and proteins play important roles during germline development. However, the functions of non-coding RNAs (ncRNAs) on germline development remain unclear in avian species. Recent high-throughput techniques have identified several classes of ncRNAs, including micro RNAs (miRNAs), small-interfering RNAs (siRNAs), and PIWI-interacting RNAs (piRNAs). These ncRNAs are functionally important in the genome, however, the identification and annotation of ncRNAs in a genome is challenging. The aim of this study was to identify different types of small ncRNAs particularly piRNAs, and the role of piRNA pathway genes in the protection of chicken primordial germ cells (PGCs). Results: At first, we performed next-generation sequencing to identify ncRNAs in chicken PGCs, and we performed ab initio predictive analysis to identify putative piRNAs in PGCs. Then, we examined the expression of three repetitive sequence-linked piRNAs and 14 genic-transcript-linked piRNAs along with their linked genes using real-time PCR. All piRNAs and their linked genes were highly expressed in PGCs. Subsequently, we knocked down two known piRNA pathway genes of chicken, PIWI-like protein 1 (CIWI) and 2 (CILI), in PGCs using siRNAs. After knockdown of CIWI and CILI, we examined their effects on the expression of six putative piRNA-linked genes and DNA double-strand breakage in PGCs. The knockdown of CIWI and CILI upregulated chicken repetitive 1 (CR1) element and RAP2B, a member of RAS oncogene family, and increased DNA double-strand breakage in PGCs. Conclusions: Our results increase the understanding of PGC-expressed piRNAs and the role of piRNA pathway genes in the protection of germ cells. © 2014 Rengaraj et al. Source

Discover hidden collaborations