GSA: Genome Sequence Archive.

With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for managing huge sequence data, here we present Genome Sequence Archive (GSA; http://bigd.big.ac.cn/gsa or http://gsa.big.ac.cn), a data repository for archiving raw sequence data. In compliance with data standards and structures of the International Nucleotide Sequence Database Collaboration (INSDC), GSA adopts four data objects (BioProject, BioSample, Experiment, and Run) for data organization, accepts raw sequence reads produced by a variety of sequencing platforms, stores both sequence reads and metadata submitted from all over the world, and makes all these data publicly available to worldwide scientific communities. In the era of big data, GSA is not only an important complement to existing INSDC members by alleviating the increasing burdens of handling sequence data deluge, but also takes the significant responsibility for global big data archive and provides free unrestricted access to all publicly available data in support of research activities throughout the world.

miRNome Analysis of CML Cells.

Next-generation sequencing technologies have greatly accelerated the biological and medical progression. As one of the applications, miRNA-Seq is invaluable in detecting and characterizing genome-wide miRNAs of either too high or too low abundance. Besides, it can also be used in detecting novel miRNAs. Here, we describe an ab initio analysis of an example chronic myeloid leukemia miRNA sequencing data set to quantify the global expression of miRNAs, detect differential expression and novel miRNAs, and predict target genes. The run time of this protocol may vary depending on the volume of miRNA sequencing data and available computing resources but takes ~5 h of computing time for typical experiments and less than 1 h of hands-on time.

MiR-218 Inhibits Erythroid Differentiation and Alters Iron Metabolism by Targeting ALAS2 in K562 Cells.

microRNAs (miRNAs) are involved in a variety of biological processes. The regulatory function and potential role of miRNAs targeting the mRNA of the 5'-aminolevulinate synthase 2 (ALAS2) in erythropoiesis were investigated in order to identify miRNAs which play a role in erythroid iron metabolism and differentiation. Firstly, the role of ALAS2 in erythroid differentiation and iron metabolism in human erythroid leukemia cells (K562) was confirmed by ALAS2 knockdown. Through a series of screening strategies and experimental validations, it was identified that hsa-miR-218 (miR-218) targets and represses the expression of ALAS2 by binding to the 3'-untranslated region (UTR). Overexpression of miR-218 repressed erythroid differentiation and altered iron metabolism in K562 cells similar to that seen in the ALAS2 knockdown in K562 cells. In addition to iron metabolism and erythroid differentiation, miR-218 was found to be responsible for a reduction in K562 cell growth. Taken together, our results show that miR-218 inhibits erythroid differentiation and alters iron metabolism by targeting ALAS2 in K562 cells.

Databases and web tools for cancer genomics study.

Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community.