Dataset Information

Unraveling the KNOTTED1 regulatory network in maize meristems (ChIP-seq)

ABSTRACT: KNOTTED1(KN1)-like homeobox (KNOX) transcription factors function in plant meristems, self-renewing structures consisting of stem cells and their immediate daughters. Despite their importance for plant development, the genomic network targeted by KNOX proteins is poorly understood. Using ChIP-seq, we defined the KN1 cistrome in maize inflorescences and found that KN1 binds to several thousand loci. To understand how these binding occupancies correlate with changes in transcriptional regulation, we performed RNA-seq on immature ears and tassels, and compared expression profiles between normal and loss-of-function kn1 plants, in addition to immature leaves from normal and gain-of-function Kn1 plants. We found that 643 of the KN1 targets were modulated in one or multiple tissues, with a strong enrichment for transcription factors (including other homeobox genes) and genes participating in several hormonal pathways, most significantly auxin, implicating KN1 at the crossroads of plant hormone signaling. The loss-of-function kn1 phenotype is reminiscent of auxin mutants and kn1 mis-expression in leaves correlates with increased auxin signaling. Our results demonstrate that KN1 plays a key role in orchestrating the upper levels of a hierarchical gene regulatory network that impacts plant meristem identity and function.

ORGANISM(S): Zea mays

PROVIDER: GSE39161 | GEO | 2012/09/04

SECONDARY ACCESSION(S): PRJNA170127

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Small RNAs (21-24 nt) are pivotal regulators of gene expression that guide both transcriptional and post-transcriptional silencing mechanisms in diverse eukaryotes, including most if not all plants. MicroRNAs (miRNAs) and short interfering RNAs (siRNAs) are the two major types, both of which have a demonstrated and important role in plant development, stress responses and pathogen resistance. In this work, we used a deep sequencing approach (Sequencing-By-Synthesis, or SBS) to develop sequence resources of small RNAs from different maize tissues (including leaves, ears and tassels) collected from wild-type plants of the B73 variety. The high depth of the resulting datasets enabled us to examine in detail critical small RNA features as size distribution, tissue-specific regulation and sequence conservation between different organs in this species. We also developed database resources and a dedicated website (http://smallrna.udel.edu/) with computational tools for allowing other users to identify new miRNAs or siRNAs involved in specific regulatory pathways, verify the degree of conservation of these sequences in other plant species and map small RNAs on genes or larger regions of the maize genome under study. Small RNA libraries were derived from leaves, ears and tassels of maize variety B73 (wild-type). Plants were grown in a flood irrigated plot at the University of Arizona (Tucson, AZ, USA) in 2007 and organs were pooled from several plants for each library. Young leaves were collected from 6-weeks-old seedlings. Post-meiotic immature ears were harvested from 10- and 11-week old plants while pre-meiotic tassels were collected from 8-week old plants. Total RNA was isolated using the Plant RNA Purification Reagent (Invitrogen) and submitted to Illumina (Hayward, CA, http://www.illumina.com) for small RNA library construction using approaches described in (Lu et al., 2007) with minor modifications. The small RNA libraries were sequenced with the Sequencing-By-Synthesis (SBS) technology by Illumina. PERL scripts were designed to remove the adapter sequences and determine the abundance of each distinct small RNA. We thank Lyudmila Sidorenko and Vicki Chandler for providing the plant material and Kan Nobuta for assistance with the computational methods.

Dataset Information

Unraveling the KNOTTED1 regulatory network in maize meristems (ChIP-seq)

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets