ATM suppresses c-Myc overexpression in the mammary epithelium in response to estrogen.

ATM gene mutation carriers are predisposed to estrogen-receptor-positive breast cancer (BC). ATM prevents BC oncogenesis by activating p53 in every cell; however, much remains unknown about tissue-specific oncogenesis after ATM loss. Here, we report that ATM controls the early transcriptional response to estrogens. This response depends on topoisomerase II (TOP2), which generates TOP2-DNA double-strand break (DSB) complexes and rejoins the breaks. When TOP2-mediated ligation fails, ATM facilitates DSB repair. After estrogen exposure, TOP2-dependent DSBs arise at the c-MYC enhancer in human BC cells, and their defective repair changes the activation profile of enhancers and induces the overexpression of many genes, including the c-MYC oncogene. CRISPR/Cas9 cleavage at the enhancer also causes c-MYC overexpression, indicating that this DSB causes c-MYC overexpression. Estrogen treatment induced c-Myc protein overexpression in mammary epithelial cells of ATM-deficient mice. In conclusion, ATM suppresses the c-Myc-driven proliferative effects of estrogens, possibly explaining such tissue-specific oncogenesis.

A Survey of Web-Based Chemogenomic Data Resources.

Chemogenomics is a comparatively nascent branch dealing with the effects of drugs and chemicals on molecular level systems. With the emergence of this new epoch, the quantity of data sources is also unprecedentedly increasing. Despite having a plethora of a databases, the variation in bioactivity measurement as well as bias toward specific protein studies, varied computational procedures and redundant information make data mining tedious, especially for newcomers in the field. In this chapter, we give an overview of hands-on data collection and domains of applicability from some useful Web-based chemogenomic resources that are accessible with nothing more than a Web browser. This overview can help assist users in acquiring chemogenomic datasets for their project at hand.

Chemogenomic Active Learning's Domain of Applicability on Small, Sparse qHTS Matrices: A Study Using Cytochrome P450 and Nuclear Hormone Receptor Families.

Computational models for predicting the activity of small molecules against targets are now routinely developed and used in academia and industry, partially due to public bioactivity databases. While models based on bigger datasets are the trend, recent studies such as chemogenomic active learning have shown that only a fraction of data is needed for effective models in many cases. In this article, the chemogenomic active learning method is discussed and used to newly analyze public databases containing nuclear hormone receptor and cytochrome P450 enzyme family bioactivity. In addition to existing results on kinases and G-protein coupled receptors, results here demonstrate the active learning methodology's effectiveness on extracting informative ligand-target pairs in sparse data scenarios. Experiments to assess the domain of the applicability demonstrate the influence of ligand profiles of similar targets within the family.

High-Throughput Sequencing Reveals Diverse Sets of Conserved, Nonconserved, and Species-Specific miRNAs in Jute.

MicroRNAs play a pivotal role in regulating a broad range of biological processes, acting by cleaving mRNAs or by translational repression. A group of plant microRNAs are evolutionarily conserved; however, others are expressed in a species-specific manner. Jute is an agroeconomically important fibre crop; nonetheless, no practical information is available for microRNAs in jute to date. In this study, Illumina sequencing revealed a total of 227 known microRNAs and 17 potential novel microRNA candidates in jute, of which 164 belong to 23 conserved families and the remaining 63 belong to 58 nonconserved families. Among a total of 81 identified microRNA families, 116 potential target genes were predicted for 39 families and 11 targets were predicted for 4 among the 17 identified novel microRNAs. For understanding better the functions of microRNAs, target genes were analyzed by Gene Ontology and their pathways illustrated by KEGG pathway analyses. The presence of microRNAs identified in jute was validated by stem-loop RT-PCR followed by end point PCR and qPCR for randomly selected 20 known and novel microRNAs. This study exhaustively identifies microRNAs and their target genes in jute which will ultimately pave the way for understanding their role in this crop and other crops.

In silico analysis reveals the presence of a large number of Ankyrin repeat containing proteins in Ectocarpus siliculosus.

Proteins with Ankyrin repeat motifs (ANK) are found to be associated with diverse biological processes and molecular functions in most of the studied organisms. Several studies have been done on the ANK-motif containing proteins of various model species, but similar studies on their counterparts in brown algae are not available. In this study, we have identified a total of 1,372 ankyrin repeats in 339 proteins of the model brown algae Ectocarpus siliculosus and the consensus sequence of the ANK repeats was determined. The proteins were classified into eight different subfamilies depending on their structural diversity. The data provided in this study may provide useful basis for future reverse genetics analysis of the members of this family.