Jason S. Cumbie

High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes.

In plants, microRNAs (miRNAs) comprise one of two classes of small RNAs that function primarily as negative regulators at the posttranscriptional level. Several MIRNA genes in the plant kingdom are ancient, with conservation extending between angiosperms and the mosses, whereas many others are more recently evolved. Here, we use deep sequencing and computational methods to identify, profile and analyze non-conserved MIRNA genes in Arabidopsis thaliana. 48 non-conserved MIRNA families, nearly all of which were represented by single genes, were identified. Sequence similarity analyses of miRNA precursor foldback arms revealed evidence for recent evolutionary origin of 16 MIRNA loci through inverted duplication events from protein-coding gene sequences. Interestingly, these recently evolved MIRNA genes have taken distinct paths. Whereas some non-conserved miRNAs interact with and regulate target transcripts from gene families that donated parental sequences, others have drifted to the point of non-interaction with parental gene family transcripts. Some young MIRNA loci clearly originated from one gene family but form miRNAs that target transcripts in another family. We suggest that MIRNA genes are undergoing relatively frequent birth and death, with only a subset being stabilized by integration into regulatory networks.

Genome-Wide Profiling and Analysis of Arabidopsis siRNAs

Eukaryotes contain a diversified set of small RNA-guided pathways that control genes, repeated sequences, and viruses at the transcriptional and posttranscriptional levels. Genome-wide profiles and analyses of small RNAs, particularly the large class of 24-nucleotide (nt) short interfering RNAs (siRNAs), were done for wild-type Arabidopsis thaliana and silencing pathway mutants with defects in three RNA-dependent RNA polymerase (RDR) and four Dicer-like (DCL) genes. The profiling involved direct analysis using a multiplexed, parallel-sequencing strategy. Small RNA-generating loci, especially those producing predominantly 24-nt siRNAs, were found to be highly correlated with repetitive elements across the genome. These were found to be largely RDR2- and DCL3-dependent, although alternative DCL activities were detected on a widespread level in the absence of DCL3. In contrast, no evidence for RDR2-alternative activities was detected. Analysis of RDR2- and DCL3-dependent small RNA accumulation patterns in and around protein-coding genes revealed that upstream gene regulatory sequences systematically lack siRNA-generating activities. Further, expression profiling suggested that relatively few genes, proximal to abundant 24-nt siRNAs, are regulated directly by RDR2- and DCL3-dependent silencing. We conclude that the widespread accumulation patterns for RDR2- and DCL3-dependent siRNAs throughout the Arabidopsis genome largely reflect mechanisms to silence highly repeated sequences.

Genome-Wide Analysis of the RNA-DEPENDENT RNA POLYMERASE6/DICER-LIKE4 Pathway in Arabidopsis Reveals Dependency on miRNA- and tasiRNA-Directed Targeting

Posttranscriptional RNA silencing of many endogenous transcripts, viruses, and transgenes involves the RNA-DEPENDENT RNA POLYMERASE6/DICER-LIKE4 (RDR6/DCL4)-dependent short interfering RNA (siRNA) biogenesis pathway. Arabidopsis thaliana contains several families of trans-acting siRNAs (tasiRNAs) that form in 21-nucleotide phased arrays through the RDR6/DCL4-dependent pathway and that negatively regulate target transcripts. Using deep sequencing technology and computational approaches, the phasing patterns of known tasiRNAs and tasiRNA-like loci from across the Arabidopsis genome were analyzed in wild-type plants and silencing-defective mutants. Several gene transcripts were found to be routed through the RDR6/DCL4-dependent pathway after initial targeting by one or multiple miRNAs or tasiRNAs, the most conspicuous example of which was an expanding clade of genes encoding pentatricopeptide repeat (PPR) proteins. Interestingly, phylogenetic analysis using Populus trichocarpa revealed evidence for small RNA–mediated regulatory mechanisms within a similarly expanded group of PPR genes. We suggest that posttranscriptional silencing mechanisms operate on an evolutionary scale to buffer the effects of rapidly expanding gene families.

Computational and analytical framework for small RNA profiling by high-throughput sequencing

The advent of high-throughput sequencing (HTS) methods has enabled direct approaches to quantitatively profile small RNA populations. However, these methods have been limited by several factors, including representational artifacts and lack of established statistical methods of analysis. Furthermore, massive HTS data sets present new problems related to data processing and mapping to a reference genome. Here, we show that cluster-based sequencing-by-synthesis technology is highly reproducible as a quantitative profiling tool for several classes of small RNA from Arabidopsis thaliana. We introduce the use of synthetic RNA oligoribonucleotide standards to facilitate objective normalization between HTS data sets, and adapt microarray-type methods for statistical analysis of multiple samples. These methods were tested successfully using mutants with small RNA biogenesis (miRNA-defective dcl1 mutant and siRNA-defective dcl2 dcl3 dcl4 triple mutant) or effector protein (ago1 mutant) deficiencies. Computational methods were also developed to rapidly and accurately parse, quantify, and map small RNA data.

Update of ASRP: the Arabidopsis Small RNA Project database

Development of the Arabidopsis Small RNA Project (ASRP) Database, which provides information and tools for the analysis of microRNA, endogenous siRNA and other small RNA-related features, has been driven by the introduction of high-throughput sequencing technology. To accommodate the demands of increased data, numerous improvements and updates have been made to ASRP, including new ways to access data, more efficient algorithms for handling data, and increased integration with community-wide resources. New search and visualization tools have also been developed to improve access to small RNA classes and their targets. ASRP is publicly available through a web interface at http://asrp.cgrb.oregonstate.edu/db/

Distinct Expression Patterns of Natural Antisense Transcripts in Arabidopsis

It has been shown that overlapping cis-natural antisense transcripts (cis-NATs) can form a regulatory circuit in which small RNAs derived from one transcript regulate stability of the other transcript, which manifests itself as anticorrelated expression. However, little is known about how widespread antagonistic expression of cis-NATs is. We have determined how frequently cis-NAT pairs, which make up 7.4% of annotated transcription units in the Arabidopsis (Arabidopsis thaliana) genome, show anticorrelated expression patterns. Indeed, global expression profiles of pairs of cis-NATs on average have significantly lower pairwise Pearson correlation coefficients than other pairs of neighboring genes whose transcripts do not overlap. However, anticorrelated expression that is greater than expected by chance is found in only a small number of cis-NAT pairs. The degree of anticorrelation does not depend on the length of the overlap or on the distance of the 5′ ends of the transcripts. Consistent with earlier findings, cis-NATs do not exhibit an increased likelihood to give rise to small RNAs, as determined from available small RNA sequences and massively parallel signature sequencing tags. However, the overlapping regions of cis-NATs appeared to be enriched for small RNA loci compared to nonoverlapping regions. Furthermore, expression of cis-NATs was not disproportionately affected in various RNA-silencing mutants. Our results demonstrate that there is a trend toward anticorrelated expression of cis-NAT pairs in Arabidopsis, but currently available data do not produce a strong signature of small RNA-mediated silencing for this process.

The Genome of Tolypocladium inflatum: Evolution, Organization, and Expression of the Cyclosporin Biosynthetic Gene Cluster

The ascomycete fungus Tolypocladium inflatum, a pathogen of beetle larvae, is best known as the producer of the immunosuppressant drug cyclosporin. The draft genome of T. inflatum strain NRRL 8044 (ATCC 34921), the isolate from which cyclosporin was first isolated, is presented along with comparative analyses of the biosynthesis of cyclosporin and other secondary metabolites in T. inflatum and related taxa. Phylogenomic analyses reveal previously undetected and complex patterns of homology between the nonribosomal peptide synthetase (NRPS) that encodes for cyclosporin synthetase (simA) and those of other secondary metabolites with activities against insects (e.g., beauvericin, destruxins, etc.), and demonstrate the roles of module duplication and gene fusion in diversification of NRPSs. The secondary metabolite gene cluster responsible for cyclosporin biosynthesis is described. In addition to genes necessary for cyclosporin biosynthesis, it harbors a gene for a cyclophilin, which is a member of a family of immunophilins known to bind cyclosporin. Comparative analyses support a lineage specific origin of the cyclosporin gene cluster rather than horizontal gene transfer from bacteria or other fungi. RNA-Seq transcriptome analyses in a cyclosporin-inducing medium delineate the boundaries of the cyclosporin cluster and reveal high levels of expression of the gene cluster cyclophilin. In medium containing insect hemolymph, weaker but significant upregulation of several genes within the cyclosporin cluster, including the highly expressed cyclophilin gene, was observed. T. inflatum also represents the first reference draft genome of Ophiocordycipitaceae, a third family of insect pathogenic fungi within the fungal order Hypocreales, and supports parallel and qualitatively distinct radiations of insect pathogens. The T. inflatum genome provides additional insight into the evolution and biosynthesis of cyclosporin and lays a foundation for further investigations of the role of secondary metabolite gene clusters and their metabolites in fungal biology.

GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts.

Variable Suites of Non-effector Genes Are Co-regulated in the Type III Secretion Virulence Regulon across the Pseudomonas syringae Phylogeny

Pseudomonas syringae is a phylogenetically diverse species of Gram-negative bacterial plant pathogens responsible for crop diseases around the world. The HrpL sigma factor drives expression of the major P. syringae virulence regulon. HrpL controls expression of the genes encoding the structural and functional components of the type III secretion system (T3SS) and the type three secreted effector proteins (T3E) that are collectively essential for virulence. HrpL also regulates expression of an under-explored suite of non-type III effector genes (non-T3E), including toxin production systems and operons not previously associated with virulence. We implemented and refined genome-wide transcriptional analysis methods using cDNA-derived high-throughput sequencing (RNA-seq) data to characterize the HrpL regulon from six isolates of P. syringae spanning the diversity of the species. Our transcriptomes, mapped onto both complete and draft genomes, significantly extend earlier studies. We confirmed HrpL-regulation for a majority of previously defined T3E genes in these six strains. We identified two new T3E families from P. syringae pv. oryzae 1_6, a strain within the relatively underexplored phylogenetic Multi-Locus Sequence Typing (MLST) group IV. The HrpL regulons varied among strains in gene number and content across both their T3E and non-T3E gene suites. Strains within MLST group II consistently express the lowest number of HrpL-regulated genes. We identified events leading to recruitment into, and loss from, the HrpL regulon. These included gene gain and loss, and loss of HrpL regulation caused by group-specific cis element mutations in otherwise conserved genes. Novel non-T3E HrpL-regulated genes include an operon that we show is required for full virulence of P. syringae pv. phaseolicola 1448A on French bean. We highlight the power of integrating genomic, transcriptomic, and phylogenetic information to drive concise functional experimentation and to derive better insight into the evolution of virulence across an evolutionarily diverse pathogen species.

NanoCAGE-XL and CapFilter: an approach to genome wide identification of high confidence transcription start sites

BackgroundIdentifying the transcription start sites (TSS) of genes is essential for characterizing promoter regions. Several protocols have been developed to capture the 5′ end of transcripts via Cap Analysis of Gene Expression (CAGE) or linker-ligation strategies such as Paired-End Analysis of Transcription Start Sites (PEAT), but often require large amounts of tissue. More recently, nanoCAGE was developed for sequencing on the Illumina GAIIx to overcome these difficulties.ResultsHere we present the first publicly available adaptation of nanoCAGE for sequencing on recent ultra-high throughput platforms such as Illumina HiSeq-2000, and CapFilter, a computational pipeline that greatly increases confidence in TSS identification. We report excellent gene coverage, reproducibility, and precision in transcription start site discovery for samples from Arabidopsis thaliana roots.ConclusionnanoCAGE-XL together with CapFilter allows for genome wide identification of high confidence transcription start sites in large eukaryotic genomes.