ABSTRACT
The National Agricultural Biotechnology Information Center (NABIC) constructed an agricultural biology-based infrastructure and developed a biological information-based database. The major functions of the NABIC are focused on biotechnological developments for agricultural bioinformatics and providing a web-based service to construct bioinformatics workflows easily, such as protein function prediction and genome systems biology programs. The NABIC has concentrated on the functional genomics of major crops, building an integrated biotechnology database for agro-biotech information that focuses on the proteomics of major agricultural resources, such as rice, Chinese cabbage, rice Ds-tagging lines, and microorganisms.
Subject(s)
Humans , Asian People , Biotechnology , Brassica , Computational Biology , Genome , Genomics , Information Centers , Proteomics , Systems BiologyABSTRACT
The Korean Rice Ds-tagging lines Database (KRDD) is designed to provide information about Ac/Ds insertion lines and activation tagging lines using japonica rice. This database has provided information on 18,158 Ds lines, which includes the ID, description, photo image, sequence information, and gene characteristics. The KRDD is visualized using a web-based graphical view, and anonymous users can query and browse the data using the search function. It has four major menus of web pages: (i) a Blast Search menu of a mutant line; Blast from rice Ds-tagging mutant lines; (ii) a primer design tool to identify genotypes of Ds insertion lines; (iii) a Phenotype menu for Ds lines, searching by identification name and phenotype characteristics; and (iv) a Management menu for Ds lines.
Subject(s)
Anonyms and Pseudonyms , Genotype , PhenotypeABSTRACT
We have constructed the Rice Genome Information Service System (RGISS), which is an information service system of the Oryza sativa L. ssp. japonica (rice) genome, using the released version of rice Build 3.0 pseudomolecules based on the Ensembl architecture. The nonredundant library, composed of 3,360 clones of BACs, PACs, and fosmids, was used to construct supercontigs. RGISS contains 50,717 annotated genes from GenBank, 56,161 predicted genes from FgeneSH, and information on 9,587 markers, which includes STS, SSR, and EST-based RFLP. The 20,180 ESTs sequenced by the Korea National Institute of Agricultural Biotechnology (NIAB) were aligned and mapped into 168,792 exons. By gene ontology analysis, the classified protein numbers in the rice genome were 6158, 4531, and 12,364 proteins, which were mapped to molecular function, cellular component, and biological process, respectively.
Subject(s)
Biological Phenomena , Biotechnology , Clone Cells , Databases, Nucleic Acid , Exons , Expressed Sequence Tags , Gene Ontology , Genome , Information Services , Korea , Polymorphism, Restriction Fragment Length , OryzaABSTRACT
Molecular approaches, internal transcribed spacer(ITS) sequences of ribosomal DNA, and Universal Rice Primer Polymerase Chain Reaction(URP-PCR) were used to investigate the genetic diversity, taxonomic complexity, and relationships of Trichoderma species in mushroom farms. Forty-one isolates of 13 Trichoderma spp. were used in this study and clustered into eight groups. The DNA fingerprint patterns and ITS1 region sequence alignment data showed similar results, but not in some species, such as T. virens, T. atroviride, T. harzianum, and T. aureoviride. Results of this study have proven that the morphology-based taxonomic system has some limitations in terms of classification. The data obtained in this study would be a good index for classifying indistinguishable Trichoderma strains.
Subject(s)
Agaricales , Classification , DNA Fingerprinting , DNA , DNA, Ribosomal , Genetic Variation , Korea , Sequence Alignment , TrichodermaABSTRACT
In order to investigate biodiversity and establish identification system for Phytophthora spp. in Korea, a variety of band pattern was produced by using the URP (universal rice primer). The fingerprint patterns of Phytophthora spp. showed many common and variable fragments according to their isolates in distinct genotypes. In particular, P. drechsleri was classified into four distinct types (I to IV). P. drechsleri (KACC 40498 and KACC 40499) and P. cryptogea (KACC 40413) appeared to have almost equal bands despite their being different species. Ninety isolates of Phytophthora spp. were clustered into 13 groups based on UPGMA (unweighted pair group method with arithmetic means) analysis. These DNA fingerprinting data would be helpful for inter- and intra-species identification of Phytophthora species.