Identifying Gene Regulatory Networks in Arabidopsis by In Silico Prediction, Yeast-1-Hybrid, and Inducible Gene Profiling Assays.

Published

Journal Article

A system-wide understanding of gene regulation will provide deep insights into plant development and physiology. In this chapter we describe a threefold approach to identify the gene regulatory networks in Arabidopsis thaliana that function in a specific tissue or biological process. Since no single method is sufficient to establish comprehensive and high-confidence gene regulatory networks, we focus on the integration of three approaches. First, we describe an in silico prediction method of transcription factor-DNA binding, then an in vivo assay of transcription factor-DNA binding by yeast-1-hybrid and lastly the identification of co-expression clusters by transcription factor induction in planta. Each of these methods provides a unique tool to advance our understanding of gene regulation, and together provide a robust model for the generation of gene regulatory networks.

Full Text

Duke Authors

Cited Authors

  • Sparks, EE; Benfey, PN

Published Date

  • January 2016

Published In

Volume / Issue

  • 1370 /

Start / End Page

  • 29 - 50

PubMed ID

  • 26659952

Pubmed Central ID

  • 26659952

Electronic International Standard Serial Number (EISSN)

  • 1940-6029

International Standard Serial Number (ISSN)

  • 1064-3745

Digital Object Identifier (DOI)

  • 10.1007/978-1-4939-3142-2_3

Language

  • eng