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CRM discovery beyond model insects

  • Purdue University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

9 Scopus citations

Abstract

Although the number of sequenced insect genomes numbers in the hundreds, little is known about gene regulatory sequences in any species other than the well-studied Drosophila melanogaster. We provide here a detailed protocol for using SCRMshaw, a computational method for predicting cis-regulatory modules (CRMs, also “enhancers”) in sequenced insect genomes. SCRMshaw is effective for CRM discovery throughout the range of holometabolous insects and potentially in even more diverged species, with true-positive prediction rates of 75% or better. Minimal requirements for using SCRMshaw are a genome sequence and training data in the form of known Drosophila CRMs; a comprehensive set of the latter can be obtained from the SCRMshaw download site. For basic applications, a user with only modest computational know-how can run SCRMshaw on a desktop computer. SCRMshaw can be run with a single, narrow set of training data to predict CRMs regulating a specific pattern of gene expression, or with multiple sets of training data covering a broad range of CRM activities to provide an initial rough regulatory annotation of a complete, newly-sequenced genome.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages117-139
Number of pages23
DOIs
StatePublished - 2019

Publication series

NameMethods in Molecular Biology
Volume1858
ISSN (Print)1064-3745

Keywords

  • Enhancer prediction
  • Genome annotation
  • Non-model insects
  • Regulatory genomics
  • Transcriptional gene regulation

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