Allegro: Analyzing Expression and Sequence in Concert to Discover Regulatory Programs

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2009 Jan 20

PMID 19151090

Citations 23

Authors

Yonit Halperin

Chaim Linhart

Igor Ulitsky

Ron Shamir

Affiliations

Soon will be listed here.

Abstract

A major goal of system biology is the characterization of transcription factors and microRNAs (miRNAs) and the transcriptional programs they regulate. We present Allegro, a method for de-novo discovery of cis-regulatory transcriptional programs through joint analysis of genome-wide expression data and promoter or 3' UTR sequences. The algorithm uses a novel log-likelihood-based, non-parametric model to describe the expression pattern shared by a group of co-regulated genes. We show that Allegro is more accurate and sensitive than existing techniques, and can simultaneously analyze multiple expression datasets with more than 100 conditions. We apply Allegro on datasets from several species and report on the transcriptional modules it uncovers. Our analysis reveals a novel motif over-represented in the promoters of genes highly expressed in murine oocytes, and several new motifs related to fly development. Finally, using stem-cell expression profiles, we identify three miRNA families with pivotal roles in human embryogenesis.

Citing Articles

Quantifying the tissue-specific regulatory information within enhancer DNA sequences.

Benner P, Vingron M NAR Genom Bioinform. 2021; 3(4):lqab095.

PMID: 34729474 PMC: 8557370. DOI: 10.1093/nargab/lqab095.

NF-Y Subunits Overexpression in HNSCC.

Bezzecchi E, Bernardini A, Ronzio M, Miccolo C, Chiocca S, Dolfini D Cancers (Basel). 2021; 13(12).

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NF-YA Overexpression in Lung Cancer: LUAD.

Bezzecchi E, Ronzio M, Semeghini V, Andrioletti V, Mantovani R, Dolfini D Genes (Basel). 2020; 11(2).

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NF-YA Overexpression in Lung Cancer: LUSC.

Bezzecchi E, Ronzio M, Dolfini D, Mantovani R Genes (Basel). 2019; 10(11).

PMID: 31744190 PMC: 6895822. DOI: 10.3390/genes10110937.

Analysis of Genomic Sequence Motifs for Deciphering Transcription Factor Binding and Transcriptional Regulation in Eukaryotic Cells.

Boeva V Front Genet. 2016; 7:24.

PMID: 26941778 PMC: 4763482. DOI: 10.3389/fgene.2016.00024.

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