A Conserved Stem Loop Motif in the 5′Untranslated Region Regulates Transforming Growth Factor-β1 Translation

Transforming growth factor-β1 (TGF-β1) regulates cellular proliferation, differentiation, migration, and survival. The human TGF-β1 transcript is inherently poorly translated, and translational activation has been documented in relation to several stimuli. In this paper, we have sought to identify in cis regulatory elements within the TGF-β1 5′Untranslated Region (5′UTR). In silico analysis predicted formation of stable secondary structure in a G/C-rich element between nucleotides +77 to +106, and demonstrated that this element is highly conserved across species. Circular dichroism spectroscopy confirmed the presence of secondary structure in this region. The proximal 5′UTR was inhibitory to translation in reporter gene experiments, and mutation of the secondary structure motif increased translational efficiency. Translational regulation of TGF-β1 mRNA is linked to altered binding of YB-1 protein to its 5′UTR. Immunoprecipitation-RT-qPCR demonstrated a high basal association of YB-1 with TGF-β1 mRNA. However, mutation of the secondary structure motif did not prevent interaction of YB-1 with the 5′UTR, suggesting that YB-1 binds to this region due to its G/C-rich composition, rather than a specific, sequence-dependent, binding site. These data identify a highly conserved element within the TGF-β1 5′UTR that forms stable secondary structure, and is responsible for the inherent low translation efficiency of this cytokine

PHDcleav: A SVM based method for predicting human Dicer cleavage sites using sequence and secondary structure of miRNA precursors

Background: Dicer, an RNase III enzyme, plays a vital role in the processing of pre-miRNAs for generating the miRNAs. The structural and sequence features on pre-miRNA which can facilitate position and efficiency of cleavage are not well known. A precise cleavage by Dicer is crucial because an inaccurate processing can produce miRNA with different seed regions which can alter the repertoire of target genes.Results: In this study, a novel method has been developed to predict Dicer cleavage sites on pre-miRNAs using Support Vector Machine. We used the dataset of experimentally validated human miRNA hairpins from miRBase, and extracted fourteen nucleotides around Dicer cleavage sites. We developed number of models using various types of features and achieved maximum accuracy of 66% using binary profile of nucleotide sequence taken from 5p arm of hairpin. The prediction performance of Dicer cleavage site improved significantly from 66% to 86% when we integrated secondary structure information. This indicates that secondary structure plays an important role in the selection of cleavage site. All models were trained and tested on 555 experimentally validated cleavage sites and evaluated using 5-fold cross validation technique. In addition, the performance was also evaluated on an independent testing dataset that achieved an accuracy of ~82%.Conclusion: Based on this study, we developed a webserver PHDcleav (http://www.imtech.res.in/raghava/phdcleav/) to predict Dicer cleavage sites in pre-miRNA. This tool can be used to investigate functional consequences of genetic variations/SNPs in miRNA on Dicer cleavage site, and gene silencing. Moreover, it would also be useful in the discovery of miRNAs in human genome and design of Dicer specific pre-miRNAs for potent gene silencing.Peer reviewedBiochemistry and Molecular Biolog

The lncRNA landscape of breast cancer reveals a role for DSCAM-AS1 in breast cancer progression

Molecular classification of cancers into subtypes has resulted in an advance in our understanding of tumour biology and treatment response across multiple tumour types. However, to date, cancer profiling has largely focused on protein-coding genes, which comprise <1% of the genome. Here we leverage a compendium of 58,648 long noncoding RNAs (lncRNAs) to subtype 947 breast cancer samples. We show that lncRNA-based profiling categorizes breast tumours by their known molecular subtypes in breast cancer. We identify a cohort of breast cancer-associated and oestrogen-regulated lncRNAs, and investigate the role of the top prioritized oestrogen receptor (ER)-regulated lncRNA, DSCAM-AS1. We demonstrate that DSCAM-AS1 mediates tumour progression and tamoxifen resistance and identify hnRNPL as an interacting protein involved in the mechanism of DSCAM-AS1 action. By highlighting the role of DSCAM-AS1 in breast cancer biology and treatment resistance, this study provides insight into the potential clinical implications of lncRNAs in breast cancer

Archaeal genetics – the third way

For decades, archaea were misclassified as bacteria on account of their prokaryotic morphology. Molecular phylogeny eventually revealed that archaea, like bacteria and eukaryotes, are a fundamentally distinct domain of life. Genome analyses have confirmed that archaea share many features with eukaryotes, particularly in information processing, and therefore can serve as streamlined models for understanding eukaryotic biology. Biochemists and structural biologists have embraced the study of archaea but geneticists have been more wary, despite the fact that genetic techniques for archaea are quite sophisticated. It is high time for geneticists to start asking fundamental questions about our distant relatives