<i>Dwarf and High Tillering1</i> represses rice tillering through mediating the splicing of <i>D14</i> pre-mRNA

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Strigolactones (SLs) constitute a class of plant hormones that regulate many aspects of plant development, including repressing tillering in rice (Oryza sativa). However, how SL pathways are regulated is still poorly understood. Here, we describe a rice mutant dwarf and high tillering1 (dht1), which exhibits pleiotropic phenotypes (such as dwarfism and increased tiller numbers) similar to those of mutants defective in SL signaling. We show that DHT1 encodes a monocotyledon-specific hnRNP-like protein that acts as a previously unrecognized intron splicing factor for many precursor mRNAs (pre-mRNAs), including for the SL receptor gene D14. We find that the dht1 (DHT1I232F) mutant protein is impaired in its stability and RNA binding activity, causing defective splicing of D14 pre-mRNA and reduced D14 expression, and consequently leading to the SL signaling-defective phenotypes. Overall, our findings deepen our understanding of the functional diversification of hnRNP-like proteins and establish a connection between posttranscriptional splicing and SL signaling in the regulation of plant development.

Related collections

Most cited references 78

Record: found
Abstract: found
Article: found

Is Open Access

Trimmomatic: a flexible trimmer for Illumina sequence data

Anthony M. Bolger, Marc Lohse, Bjoern Usadel (2014)

Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.

0 comments Cited 16424 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

STAR: ultrafast universal RNA-seq aligner.

Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)

Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

0 comments Cited 14119 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

Mark Robinson, Davis J. McCarthy, Gordon K. Smyth (2009)

Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au