Genome and Gene Expression Data Analysis

Cytoplasmic polyadenylation-mediated translational control of maternal mRNAs directs maternal-to-zygotic transition

Published date : 08 Jan 2018

In the earliest stages of animal development following fertilization, maternally deposited mRNAs direct biological processes to the point of zygotic genome activation (ZGA). These maternal mRNAs undergo cytoplasmic polyadenylation (CPA), suggesting translational control of their activation. To elucidate the biological role of CPA during embryogenesis, we performed genome-wide polysome profiling at several stages of zebrafish development. Our analysis revealed a correlation between CPA and polysome-association dynamics, demonstrating a coupling of translation to the CPA of maternal mRNAs.

type
Journal Paper
journal
Development, 8 Jan 2018, Vol 145, Issue 1, doi: 10.1242/dev.159566
Impact Factor
5.843

Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma

Published date : 12 Dec 2017

Currently, molecular markers are not used when determining the prognosis and treatment strategy for patients with hepatocellular carcinoma (HCC). In the present study, we proposed that the identification of common pro-oncogenic pathways in primary tumors (PT) and adjacent non-malignant tissues (AT) typically used to predict HCC patient risks may result in HCC biomarker discovery. We examined the genome-wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients.

type
Journal Paper
journal
Molecular Oncology, 8 Nov 2017, doi: 10.1002/1878-0261.12153
Impact Factor
5.314

Single-cell gene expression analysis reveals regulators of distinct cell subpopulations among developing human neurons

Published date : 13 Oct 2017

The stochastic dynamics and regulatory mechanisms that govern differentiation of individual human neural precursor cells (NPC) into mature neurons are currently not fully understood. Here, we used single-cell RNA-sequencing (scRNA-seq) of developing neurons to dissect/identify NPC subtypes and critical developmental stages of alternative lineage specifications.

type
Journal Paper
journal
Genome Research 2017, 27, Pg 1783-1794, doi: 10.1101/gr.223313.117
Impact Factor
11.922

Identification of common oncogenic and early developmental pathways in the ovarian carcinomas controlling by distinct prognostically significant microRNA subsets

Published date : 03 Oct 2017

BACKGROUND:
High-grade serous ovarian carcinoma (HG-SOC) is the dominant tumor histologic type in epithelial ovarian cancers, exhibiting highly aberrant microRNA expression profiles and diverse pathways that collectively determine the disease aggressiveness and clinical outcomes. However, the functional relationships between microRNAs, the common pathways controlled by the microRNAs and their prognostic and therapeutic significance remain poorly understood.

METHODS:

type
Journal Paper
journal
BMC Genomics. 2017; 18(Suppl 6): 692, doi: 10.1186/s12864-017-4027-5
Impact Factor
11.922

Mathematical Modeling of Avidity Distribution and Estimating General Binding Properties of Transcription Factors from Genome-Wide Binding Profiles

Published date : 29 Aug 2017

The shape of the experimental frequency distributions (EFD) of diverse molecular interaction events quantifying genome-wide binding is often skewed to the rare but abundant quantities. Such distributions are systematically deviated from standard power-law functions proposed by scale-free network models suggesting that more explanatory and predictive probabilistic model(s) are needed.

type
Book/Book Chapter
journal
Biological Networks and Pathway Analysis, Methods in Molecular Biology, Vol. 1613, Pg 193-276, doi: 10.1007/978-1-4939-7027-8_9

Mathematical Modeling of Avidity Distribution and Estimating General Binding Properties of Transcription Factors from Genome-Wide Binding Profiles

Published date : 29 Aug 2017

The shape of the experimental frequency distributions (EFD) of diverse molecular interaction events quantifying genome-wide binding is often skewed to the rare but abundant quantities. Such distributions are systematically deviated from standard power-law functions proposed by scale-free network models suggesting that more explanatory and predictive probabilistic model(s) are needed.

type
Book/Book Chapter
journal
Biological Networks and Pathway Analysis, Methods in Molecular Biology, vol. 1613, Pg 193-276, doi: 10.1007/978-1-4939-7027-8_9

EGF hijacks miR-198/FSTL1 wound-healing switch and steers a two-pronged pathway toward metastasis

Published date : 21 Aug 2017

Epithelial carcinomas are well known to activate a prolonged wound-healing program that promotes malignant transformation. Wound closure requires the activation of keratinocyte migration via a dual-state molecular switch. This switch involves production of either the anti-migratory microRNA miR-198 or the pro-migratory follistatin-like 1 (FSTL1) protein from a single transcript; miR-198 expression in healthy skin is down-regulated in favor of FSTL1 upon wounding, which enhances keratinocyte migration and promotes re-epithelialization.

type
Journal Paper
journal
The Journal of Experimental Medicine, 2017,doi: 10.1084/jem.20170354
Impact Factor
11.991

Benchmarking selected computational gene network growing tools in context of virus-host interactions

Published date : 19 Jul 2017

Several available online tools provide network growing functions where an algorithm utilizing different data sources suggests additional genes/proteins that should connect an input gene set into functionally meaningful networks. Using the well-studied system of influenza host interactions, we compare the network growing function of two free tools GeneMANIA and STRING and the commercial IPA for their performance of recovering known influenza A virus host factors previously identified from siRNA screens.

type
Journal Paper
journal
Scientific Reports, 2017 Jul 19;7(1):5805. doi: 10.1038/s41598-017-06020-6
Impact Factor
4.259

A novel community driven software for functional enrichment analysis of extracellular vesicles data

Published date : 26 May 2017

Bioinformatics tools are imperative for the in depth analysis of heterogeneous high-throughput data. Most of the software tools are developed by specific laboratories or groups or companies wherein they are designed to perform the required analysis for the group. However, such software tools may fail to capture “what the community needs in a tool”. Here, we describe a novel community-driven approach to build a comprehensive functional enrichment analysis tool. Using the existing FunRich tool as a template, we invited researchers to request additional features and/or changes.

type
Journal Paper
journal
Journal of Extracellular Vesicles 2017, Vol. 6, 2017, Issue 1, doi: 10.1080/20013078.2017.1321455
Impact Factor
4.259

Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification

Published date : 01 Mar 2017

Robust prognostic gene signatures and therapeutic targets are difficult to derive from expression profiling because of the significant heterogeneity within breast cancer (BC) subtypes. Here, we performed forward genetic screening in mice using Sleeping Beauty transposon mutagenesis to identify candidate BC driver genes in an unbiased manner, using a stabilized N-terminal truncated β-catenin gene as a sensitizer. We identified 134 mouse susceptibility genes from 129 common insertion sites within 34 mammary tumors.

type
Journal Paper
journal
Proceedings of the National Academy of Sciences of the Unites States of America, PNAS, Vol. 114, No. 11, E2215–E2224, doi: 10.1073/pnas.1701512114
Impact Factor
9.661