Aberrant DNA methylation, as an epigenetic marker of cancer, influences tumor development and progression. We downloaded publicly available DNA methylation and gene expression datasets of matched cancer and normal pairs from the Cancer Genome Atlas Data Portal and performed a systematic computational analysis. This study has three aims to screen genes that show hypermethylation and downregulated patterns in colorectal cancers, to identify differentially methylated regions in one of these genes, SFRP1, and to test whether the SFRP genes affect survival or not. Our results show that 31 hypermethylated genes had a negative correlation with gene expression. Among them, SFRP1 had a differentially methylated pattern at each methylation site. We also show that SFRP1 may be a potential biomarker for colorectal cancer survival.
Colorectal Neoplasms* ; Computer Simulation* ; Dataset ; DNA Methylation ; Epigenomics ; Gene Expression ; Genome ; Methylation ; Survival Analysis

No abstract available.
Ultrasonography*

A wave of new technologies has created opportunities for the cost-effective generation of high-throughput profiles of biological systems, foreshadowing a "data-driven science" era. The large variety of data available from biological research is also a rich resource that can be used for innovative endeavors. However, we are facing considerable challenges in big data deposition, integration, and translation due to the complexity of biological data and its production at unprecedented exponential rates. To address these problems, in 2020, the Korean government officially announced a national strategy to collect and manage the biological data produced through national R&D fund allocations and provide the collected data to researchers. To this end, the Korea Bioinformation Center (KOBIC) developed a new biological data repository, the Korea BioData Station (K-BDS), for sharing data from individual researchers and research programs to create a data-driven biological study environment. The K-BDS is dedicated to providing free open access to a suite of featured data resources in support of worldwide activities in both academia and industry.

An endolichenic fungus,Xylaria grammica strain EL000614, showed strong nematicidal effects against plant pathogenic nematode, Meloidogyne incognita by producing grammicin. We report genome assembly of X. grammica EL000614 comprised of 25 scaffolds with a total length of 54.73 Mb, N50 of 4.60 Mb, and 99.8% of BUSCO completeness. GC contents of this genome were 44.02%. Gene families associated with biosynthesis of secondary metabolites or regulatory proteins were identified out of 13,730 gene models predicted.

An endolichenic fungus, Xylaria grammica strain EL000614, showed strong nematicidal effects against plant pathogenic nematode, Meloidogyne incognita by producing grammicin.We report genome assembly of X. grammica EL000614 comprised of 25 scaffolds with a total length of 54.73 Mb, N50 of 4.60 Mb, and 99.8% of BUSCO completeness. GC contents of this genome were 44.02%. Gene families associated with biosynthesis of secondary metabolites or regulatory proteins were identified out of 13,730 gene models predicted.

An endolichenic fungus,Xylaria grammica strain EL000614, showed strong nematicidal effects against plant pathogenic nematode, Meloidogyne incognita by producing grammicin. We report genome assembly of X. grammica EL000614 comprised of 25 scaffolds with a total length of 54.73 Mb, N50 of 4.60 Mb, and 99.8% of BUSCO completeness. GC contents of this genome were 44.02%. Gene families associated with biosynthesis of secondary metabolites or regulatory proteins were identified out of 13,730 gene models predicted.

An endolichenic fungus, Xylaria grammica strain EL000614, showed strong nematicidal effects against plant pathogenic nematode, Meloidogyne incognita by producing grammicin.We report genome assembly of X. grammica EL000614 comprised of 25 scaffolds with a total length of 54.73 Mb, N50 of 4.60 Mb, and 99.8% of BUSCO completeness. GC contents of this genome were 44.02%. Gene families associated with biosynthesis of secondary metabolites or regulatory proteins were identified out of 13,730 gene models predicted.