GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts

A Molecular Signature of Proteinuria in Glomerulonephritis

Proteinuria is the most important predictor of outcome in glomerulonephritis and experimental data suggest that the tubular cell response to proteinuria is an important determinant of progressive fibrosis in the kidney. However, it is unclear whether proteinuria is a marker of disease severity or has a direct effect on tubular cells in the kidneys of patients with glomerulonephritis. Accordingly we studied an in vitro model of proteinuria, and identified 231 “albumin-regulated genes” differentially expressed by primary human kidney tubular epithelial cells exposed to albumin. We translated these findings to human disease by studying mRNA levels of these genes in the tubulo-interstitial compartment of kidney biopsies from patients with IgA nephropathy using microarrays. Biopsies from patients with IgAN (n = 25) could be distinguished from those of control subjects (n = 6) based solely upon the expression of these 231 “albumin-regulated genes.” The expression of an 11-transcript subset related to the degree of proteinuria, and this 11-mRNA subset was also sufficient to distinguish biopsies of subjects with IgAN from control biopsies. We tested if these findings could be extrapolated to other proteinuric diseases beyond IgAN and found that all forms of primary glomerulonephritis (n = 33) can be distinguished from controls (n = 21) based solely on the expression levels of these 11 genes derived from our in vitro proteinuria model. Pathway analysis suggests common regulatory elements shared by these 11 transcripts. In conclusion, we have identified an albumin-regulated 11-gene signature shared between all forms of primary glomerulonephritis. Our findings support the hypothesis that albuminuria may directly promote injury in the tubulo-interstitial compartment of the kidney in patients with glomerulonephritis

Vol. 22 no. 7 2006, pages 897–899 BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btl025

single channel microarray dat

The Australian Store.Synchrotron Data Management Service for Macromolecular Crystallography

Store.Synchrotron is a service for management and publication of diffraction data from the macromolecular crystallography (MX) beamlines of the Australian Synchrotron.<br><br>Proceedings of the 15^th International Conference on Accelerator and Large Experimental Control Systems (ICALEPCS 2015) conference in Melbourne, Australia from 17 - 23 October 2015 at the Melbourne Convention and Exhibition Centre (MCEC)

Role for MKL1 in megakaryocytic maturation

Megakaryoblastic leukemia 1 (MKL1), identified as part of the t(1;22) translocation specific to acute megakaryoblastic leukemia, is highly expressed in differentiated muscle cells and promotes muscle differentiation by activating serum response factor (SRF). Here we show that Mkl1 expression is up-regulated during murine megakaryocytic differentiation and that enforced overexpression of MKL1 enhances megakaryocytic differentiation. When the human erythroleukemia (HEL) cell line is induced to differentiate with 12-O-tetradecanoylphorbol 13-acetate, overexpression of MKL1 results in an increased number of megakaryocytes with a concurrent increase in ploidy. MKL1 overexpression also promotes megakaryocytic differentiation of primary human CD34+ cells cultured in the presence of thrombopoietin. The effect of MKL1 is abrogated when SRF is knocked down, suggesting that MKL1 acts through SRF. Consistent with these findings in human cells, knockout of Mkl1 in mice leads to reduced platelet counts in peripheral blood, and reduced ploidy in bone marrow megakaryocytes. In conclusion, MKL1 promotes physiologic maturation of human and murine megakaryocytes