검색결과

검색조건
좁혀보기
검색필터
결과 내 재검색

간행물

    분야

      발행연도

      -

        검색결과 8

        2.
        2013.12 구독 인증기관 무료, 개인회원 유료
        Many countries have implemented genetic evaluation for fertility traits in recent years. In particular, reproductive trait is a complex trait and need to require a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with reproductive trait, we applied a weighted gene co-expression network ana-lysis from expression value of bovine genes. We identified three co-expressed modules associated with reproductive trait from bovine microarray data. Hub genes (ZP4, FHL2 and EGR4) were determined in each module; they were topologically centered with statistically significant value in the gene co-expression network. We were able to find the highly co-expressed gene pairs with a correlation coefficient. Finally, the crucial functions of co-expressed modules were reported from functional enrichment analysis. We suggest that the network-based approach in livestock may an important method for analyzing the complex effects of candidate genes associated with economic traits like repro-duction.
        4,000원
        3.
        2013.07 서비스 종료(열람 제한)
        In order to better understand the biological systems that are affected in response to cosmic ray, we conducted the weighted gene co-expression network analysis with module detection method. By using the Pearson’s correlation coefficient value, we were evaluated the complex gene-gene functional interactions between 680 CR-response probes from integrated microarray datasets, which included large-scale transcriptional profiling of 918 microarray samples. These probes were divided into 6 distinct modules that contained 20 enriched function such as oxidoreductase activity, response to stimulus and stress, and hydrolase activity. Especially, module 1 and 2 commonly showed the enriched annotation categories such as oxidoreductase activity, including the enriched cis-regulatory elements known as ROS specific regulator. These results suggest in module1 and 2 that ROS-mediated irradiation response pathway are affected by CR. We found the 243 irradiation-dependent probes, which were exhibited the similarities of differentially expressed patterns in various irradiation microarray datasets, and RT-PCR for confirmations of several irradiation-dependent genes were exhibited the similar expressed patterns in rice by CR, gamma ray and Ion beam treatments. Interestingly, these genes were differentially expressed by non-gravity. Moreover, we were identified the co-regulations between several irradiation-dependent genes and functional interacted genes in the CR-responsive network by various GA treatments such as different conditions of dose and treatment time. These results of network-based analysis might provide a clue to understanding the complex biological system of CR.
        4.
        2012.07 서비스 종료(열람 제한)
        Ionizing radiation is known to cause chromosomal alterations such as inversions and deletions and affects gene expression within the plant genome. To monitor the genome-wide transcriptome changes by ionizing radiation, we used rice Affimetrix GeneChip microarray to identify genes that are up- or down regulated by gamma-ray (200 Gy, 60Co source), cosmic-ray and ion beam (40 Gy, 220 MeV carbon ion). The overall expression patterns between gamma-ray and ion beam were similar but cosmic-ray was regulated differently. Combined results from all 3 radiations identified 27 up-regulated genes and 188 down regulated genes. These results mean the induction of similar mechanism changes in treatments of gamma ray and ion beam. However the different expression in treatment of cosmic-ray might be due to the other environmental conditions. Among the commonly up- or down- regulated genes, we chose highly up- or down- regulated several genes and confirmed its regulation in response to ionizing radiation exposure by RT-PCR analysis. Moreover, we showed that specific co-expression networks of candidate radio marker genes by ARACNE algorithm. Our results present profiles of gene expression related to different ionizing radiation and marker gene to predict sensitivity to ionizing radiation, such as GS (glutelin subunit) and FBX322.