Gene Expression database of Normal and Tumor tissues 2 (GENT2) is an updated version of GENT, which has provided a user-friendly search platform for gene expression patterns across different normal and tumor tissues compiled from public gene expression data sets. We refactored GENT2 with recent technologies such as Apache Lucene indexing for fast search and Google Web Toolkit (GWT) framework for a user-friendly web interface. Now, GENT2 contains more than 68,000 samples and has several new useful functions. First, GENT2 now provides gene expression across 72 different tissues compared to 57 in GENT. Second, with increasing importance of tumor subtypes, GENT2 provides an option to study the differential expression and its prognostic significance based on tumor subtypes. Third, whenever available, GENT2 provides prognostic information of a gene of interest. Fourth, GENT2 provides a meta-analysis of survival information to provide users more reliable prognostic value of a gene of interest. In conclusion, with these significant improvements, GENT2 will continue to be a useful tool to a wide range of researchers. GENT2 is freely available at http://gent2.appex.kr .

The giant freshwater prawn, Macrobrachium rosenbergii, a sexually dimorphic decapod crustacean is currently the world’s most economically important cultured freshwater crustacean species. Despite its economic importance, there is currently a lack of genomic resources available for this species, and this has limited exploration of the molecular mechanisms that control the M. rosenbergii sex-differentiation system more widely in freshwater prawns. Here, we present the first hybrid transcriptome from M. rosenbergii applying RNA-Seq technologies directed at identifying genes that have potential functional roles in reproductive-related traits. A total of 13,733,210 combined raw reads (1720 Mbp) were obtained from Ion-Torrent PGM and 454 FLX. Bioinformatic analyses based on three state-of-the-art assemblers, the CLC Genomic Workbench, Trans-ABySS, and Trinity, that use single and multiple k-mer methods respectively, were used to analyse the data. The influence of multiple k-mers on assembly performance was assessed to gain insight into transcriptome assembly from short reads. After optimisation, de novo assembly resulted in 44,407 contigs with a mean length of 437 bp, and the assembled transcripts were further functionally annotated to detect single nucleotide polymorphisms and simple sequence repeat motifs. Gene expression analysis was also used to compare expression patterns from ovary and testis tissue libraries to identify genes with potential roles in reproduction and sex differentiation. The large transcript set assembled here represents the most comprehensive set of transcriptomic resources ever developed for reproduction traits in M. rosenbergii, and the large number of genetic markers predicted should constitute an invaluable resource for future genetic research studies on M. rosenbergii and can be applied more widely on other freshwater prawn species in the genus Macrobrachium.

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.

Amphibians and fish show considerable regeneration potential via dedifferentiation of somatic cells into blastemal cells. In terms of dedifferentiation, in vitro cellular reprogramming has been proposed to share common processes with in vivo tissue regeneration, although the details are elusive. Here, we identified the cytoskeletal linker protein desmoplakin (Dsp) as a common factor mediating both reprogramming and regeneration. Our analysis revealed that Dsp expression is elevated in distinct intermediate cells during in vitro reprogramming. Knockdown of Dsp impedes in vitro reprogramming into induced pluripotent stem cells and induced neural stem/progenitor cells as well as in vivo regeneration of zebrafish fins. Notably, reduced Dsp expression impairs formation of the intermediate cells during cellular reprogramming and tissue regeneration. These findings suggest that there is a Dsp-mediated evolutionary link between cellular reprogramming in mammals and tissue regeneration in lower vertebrates and that the intermediate cells may provide alternative approaches for mammalian regenerative therapy.

Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations, particularly in women. EGFR mutations and anaplastic lymphoma kinase (ALK) fusions are major genetic alterations observed in NSLA, and NSLA with these alterations have been well studied and can be treated with targeted therapies. To provide insights into the molecular profile of NSLA without EGFR and ALK alterations (NENA), we selected 141 NSLA tissues and performed proteogenomic characterization, including whole genome sequencing (WGS), transcriptomic, methylation EPIC array, total proteomic, and phosphoproteomic analyses. Forty patients with NSLA harboring EGFR and ALK alterations and seven patients with NENA with microsatellite instability were excluded. Genome analysis revealed that TP53 (25%), KRAS (22%), and SETD2 (11%) mutations and ROS1 fusions (14%) were the most frequent genetic alterations in NENA patients. Proteogenomic impact analysis revealed that STK11 and ERBB2 somatic mutations had broad effects on cancer-associated genes in NENA. DNA copy number alteration analysis identified 22 prognostic proteins that influenced transcriptomic and proteomic changes. Gene set enrichment analysis revealed estrogen signaling as the key pathway activated in NENA. Increased estrogen signaling was associated with proteogenomic alterations, such as copy number deletions in chromosomes 14 and 21, STK11 mutation, and DNA hypomethylation of LLGL2 and ST14. Finally, saracatinib, an Src inhibitor, was identified as a potential drug for targeting activated estrogen signaling in NENA and was experimentally validated in vitro. Collectively, this study enhanced our understanding of NENA NSLA by elucidating the proteogenomic landscape and proposed saracatinib as a potential treatment for this patient population that lacks effective targeted therapies. Significance: The proteogenomic landscape in never-smoker lung cancer without known driver mutations reveals prognostic proteins and enhanced estrogen signaling that can be targeted as a potential therapeutic strategy to improve patient outcomes.