CyVerse: Cyberinfrastructure for open science.

CyVerse, the largest publicly-funded open-source research cyberinfrastructure for life sciences, has played a crucial role in advancing data-driven research since the 2010s. As the technology landscape evolved with the emergence of cloud computing platforms, machine learning and artificial intelligence (AI) applications, CyVerse has enabled access by providing interfaces, Software as a Service (SaaS), and cloud-native Infrastructure as Code (IaC) to leverage new technologies. CyVerse services enable researchers to integrate institutional and private computational resources, custom software, perform analyses, and publish data in accordance with open science principles. Over the past 13 years, CyVerse has registered more than 124,000 verified accounts from 160 countries and was used for over 1,600 peer-reviewed publications. Since 2011, 45,000 students and researchers have been trained to use CyVerse. The platform has been replicated and deployed in three countries outside the US, with additional private deployments on commercial clouds for US government agencies and multinational corporations. In this manuscript, we present a strategic blueprint for creating and managing SaaS cyberinfrastructure and IaC as free and open-source software.

Genotyping-by-sequencing and ecological niche modeling illuminate phylogeography, admixture, and Pleistocene range dynamics in quaking aspen (Populus tremuloides).

Populus tremuloides is the widest-ranging tree species in North America and an ecologically important component of mesic forest ecosystems displaced by the Pleistocene glaciations. Using phylogeographic analyses of genome-wide SNPs (34,796 SNPs, 183 individuals) and ecological niche modeling, we inferred population structure, ploidy levels, admixture, and Pleistocene range dynamics of P. tremuloides, and tested several historical biogeographical hypotheses. We found three genetic lineages located mainly in coastal-Cascades (cluster 1), east-slope Cascades-Sierra Nevadas-Northern Rockies (cluster 2), and U.S. Rocky Mountains through southern Canadian (cluster 3) regions of the P. tremuloides range, with tree graph relationships of the form ((cluster 1, cluster 2), cluster 3). Populations consisted mainly of diploids (86%) but also small numbers of triploids (12%) and tetraploids (1%), and ploidy did not adversely affect our genetic inferences. The main vector of admixture was from cluster 3 into cluster 2, with the admixture zone trending northwest through the Rocky Mountains along a recognized phenotypic cline (Utah to Idaho). Clusters 1 and 2 provided strong support for the "stable-edge hypothesis" that unglaciated southwestern populations persisted in situ since the last glaciation. By contrast, despite a lack of clinal genetic variation, cluster 3 exhibited "trailing-edge" dynamics from niche suitability predictions signifying complete northward postglacial expansion. Results were also consistent with the "inland dispersal hypothesis" predicting postglacial assembly of Pacific Northwestern forest ecosystems, but rejected the hypothesis that Pacific-coastal populations were colonized during outburst flooding from glacial Lake Missoula. Overall, congruent patterns between our phylogeographic and ecological niche modeling results and fossil pollen data demonstrate complex mixtures of stable-edge, refugial locations, and postglacial expansion within P. tremuloides. These findings confirm and refine previous genetic studies, while strongly supporting a distinct Pacific-coastal genetic lineage of quaking aspen.

Retrograde Induction of phyB Orchestrates Ethylene-Auxin Hierarchy to Regulate Growth.

Exquisitely regulated plastid-to-nucleus communication by retrograde signaling pathways is essential for fine-tuning of responses to the prevailing environmental conditions. The plastidial retrograde signaling metabolite methylerythritol cyclodiphosphate (MEcPP) has emerged as a stress signal transduced into a diverse ensemble of response outputs. Here, we demonstrate enhanced phytochrome B protein abundance in red light-grown MEcPP-accumulating ceh1 mutant Arabidopsis (Arabidopsis thaliana) plants relative to wild-type seedlings. We further establish MEcPP-mediated coordination of phytochrome B with auxin and ethylene signaling pathways and uncover differential hypocotyl growth of red light-grown seedlings in response to these phytohormones. Genetic and pharmacological interference with ethylene and auxin pathways outlines the hierarchy of responses, placing ethylene epistatic to the auxin signaling pathway. Collectively, our findings establish a key role of a plastidial retrograde metabolite in orchestrating the transduction of a repertoire of signaling cascades. This work positions plastids at the zenith of relaying information coordinating external signals and internal regulatory circuitry to secure organismal integrity.

RNA-Seq analysis of soft rush (Juncus effusus): transcriptome sequencing, de novo assembly, annotation, and polymorphism identification.

BACKGROUND: Juncus effusus L. (family: Juncaceae; order: Poales) is a helophytic rush growing in temperate damp or wet terrestrial habitats and is of almost cosmopolitan distribution. The species has been studied intensively with respect to its interaction with co-occurring plants as well as microbes being involved in major biogeochemical cycles. J. effusus has biotechnological value as component of Constructed Wetlands where the plant has been employed in phytoremediation of contaminated water. Its genome has not been sequenced. RESULTS: In this study we carried out functional annotation and polymorphism analysis of de novo assembled RNA-Seq data from 18 genotypes using 249 million paired-end Illumina HiSeq reads and 2.8 million 454 Titanium reads. The assembly comprised 158,591 contigs with a mean contig length of 780 bp. The assembly was annotated using the dammit! annotation pipeline, which queries the databases OrthoDB, Pfam-A, Rfam, and runs BUSCO (Benchmarking Single-Copy Ortholog genes). In total, 111,567 contigs (70.3%) were annotated with functional descriptions, assigned gene ontology terms, and conserved protein domains, which resulted in 30,932 non-redundant gene sequences. Results of BUSCO and KEGG pathway analyses were similar for J. effusus as for the well-studied members of the Poales, Oryza sativa and Sorghum bicolor. A total of 566,433 polymorphisms were identified in transcribed regions with an average frequency of 1 polymorphism in every 171 bases. CONCLUSIONS: The transcriptome assembly was of high quality and genome coverage was sufficient for global analyses. This annotated knowledge resource can be utilized for future gene expression analysis, genomic feature comparisons, genotyping, primer design, and functional genomics in J. effusus.

The role of a class III gibberellin 2-oxidase in tomato internode elongation.

A network of environmental inputs and internal signaling controls plant growth, development and organ elongation. In particular, the growth-promoting hormone gibberellin (GA) has been shown to play a significant role in organ elongation. The use of tomato as a model organism to study elongation presents an opportunity to study the genetic control of internode-specific elongation in a eudicot species with a sympodial growth habit and substantial internodes that can and do respond to external stimuli. To investigate internode elongation, a mutant with an elongated hypocotyl and internodes but wild-type petioles was identified through a forward genetic screen. In addition to stem-specific elongation, this mutant, named tomato internode elongated -1 (tie-1) is more sensitive to the GA biosynthetic inhibitor paclobutrazol and has altered levels of intermediate and bioactive GAs compared with wild-type plants. The mutation responsible for the internode elongation phenotype was mapped to GA2oxidase 7, a class III GA 2-oxidase in the GA biosynthetic pathway, through a bulked segregant analysis and bioinformatic pipeline, and confirmed by transgenic complementation. Furthermore, bacterially expressed recombinant TIE protein was shown to have bona fide GA 2-oxidase activity. These results define a critical role for this gene in internode elongation and are significant because they further the understanding of the role of GA biosynthetic genes in organ-specific elongation.

Read Mapping and Transcript Assembly: A Scalable and High-Throughput Workflow for the Processing and Analysis of Ribonucleic Acid Sequencing Data.

Next-generation RNA-sequencing is an incredibly powerful means of generating a snapshot of the transcriptomic state within a cell, tissue, or whole organism. As the questions addressed by RNA-sequencing (RNA-seq) become both more complex and greater in number, there is a need to simplify RNA-seq processing workflows, make them more efficient and interoperable, and capable of handling both large and small datasets. This is especially important for researchers who need to process hundreds to tens of thousands of RNA-seq datasets. To address these needs, we have developed a scalable, user-friendly, and easily deployable analysis suite called RMTA (Read Mapping, Transcript Assembly). RMTA can easily process thousands of RNA-seq datasets with features that include automated read quality analysis, filters for lowly expressed transcripts, and read counting for differential expression analysis. RMTA is containerized using Docker for easy deployment within any compute environment [cloud, local, or high-performance computing (HPC)] and is available as two apps in CyVerse's Discovery Environment, one for normal use and one specifically designed for introducing undergraduates and high school to RNA-seq analysis. For extremely large datasets (tens of thousands of FASTq files) we developed a high-throughput, scalable, and parallelized version of RMTA optimized for launching on the Open Science Grid (OSG) from within the Discovery Environment. OSG-RMTA allows users to utilize the Discovery Environment for data management, parallelization, and submitting jobs to OSG, and finally, employ the OSG for distributed, high throughput computing. Alternatively, OSG-RMTA can be run directly on the OSG through the command line. RMTA is designed to be useful for data scientists, of any skill level, interested in rapidly and reproducibly analyzing their large RNA-seq data sets.

Network Analysis Reveals a Role for Salicylic Acid Pathway Components in Shade Avoidance.

Plants have sophisticated mechanisms for sensing neighbor shade. To maximize their ability to compete for light, plants respond to shade through enhanced elongation and physiological changes. The shade avoidance response affects many different organs and growth stages, yet the signaling pathways underlying this response have mostly been studied in seedlings. We assayed transcriptome changes in response to shade across a 2-d time course in the wild type and 12 Arabidopsis (Arabidopsis thaliana) mutants. The resulting temporal map of transcriptional responses to shade defines early and late responses in adult plants, enabling us to determine connections between key signaling genes and downstream responses. We found a pervasive and unexpectedly strong connection between shade avoidance and genes related to salicylic acid, suggesting salicylic acid signaling to be an important shade avoidance growth regulator. We tested this connection and found that several mutants disrupting salicylic acid levels or signaling were defective in shade avoidance. The effect of these mutations on shade avoidance was specific to petiole elongation; neither hypocotyl nor flowering time responses were altered, thereby defining important stage-specific differences in the downstream shade avoidance signaling pathway. Shade treatment did not change salicylic acid levels, indicating that the mediation of shade avoidance by salicylic acid is not dependent on the modulation of salicylic acid levels. These results demonstrate that salicylic acid pathway genes also are key components of petiole shade avoidance.

Improved RNA-seq Workflows Using CyVerse Cyberinfrastructure.

RNA-seq is a vital method for understanding gene structure and expression patterns. Typical RNA-seq analysis protocols use sequencing reads of length 50 to 150 nucleotides for alignment to the reference genome and assembly of transcripts. The resultant transcripts are quantified and used for differential expression and visualization. Existing tools and protocols for RNA-seq are vast and diverse; given their differences in performance, it is critical to select an analysis protocol that is scalable, accurate, and easy to use. Tuxedo, a popular alignment-based protocol for RNA-seq analysis, has been updated with HISAT2, StringTie, StringTie-merge, and Ballgown, and the updated protocol outperforms its predecessor. Similarly, new pseudo-alignment-based protocols like Kallisto and Sleuth reduce runtime and improve performance. However, these tools are challenging for researchers lacking command-line experience. Here, we describe two new RNA-seq analysis protocols, in which all tools are deployed on CyVerse Cyberinfrastructure with user-friendly graphical user interfaces, and validate their performance using plant RNA-seq data. © 2018 by John Wiley & Sons, Inc.

Using RNA-Seq for Genomic Scaffold Placement, Correcting Assemblies, and Genetic Map Creation in a Common Brassica rapa Mapping Population.

Brassica rapa is a model species for agronomic, ecological, evolutionary, and translational studies. Here, we describe high-density SNP discovery and genetic map construction for a B. rapa recombinant inbred line (RIL) population derived from field collected RNA sequencing (RNA-Seq) data. This high-density genotype data enables the detection and correction of putative genome misassemblies and accurate assignment of scaffold sequences to their likely genomic locations. These assembly improvements represent 7.1-8.0% of the annotated B. rapa genome. We demonstrate how using this new resource leads to a significant improvement for QTL analysis over the current low-density genetic map. Improvements are achieved by the increased mapping resolution and by having known genomic coordinates to anchor the markers for candidate gene discovery. These new molecular resources and improvements in the genome annotation will benefit the Brassicaceae genomics community and may help guide other communities in fine-tuning genome annotations.

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms.

This workflow allows novice researchers to leverage advanced computational resources such as cloud computing to carry out pairwise comparative transcriptomics. It also serves as a primer for biologists to develop data scientist computational skills, e.g. executing bash commands, visualization and management of large data sets. All command line code and further explanations of each command or step can be found on the wiki (https://wiki.cyverse.org/wiki/x/dgGtAQ). The Discovery Environment and Atmosphere platforms are connected together through the CyVerse Data Store. As such, once the initial raw sequencing data has been uploaded there is no more need to transfer large data files over an Internet connection, minimizing the amount of time needed to conduct analyses. This protocol is designed to analyze only two experimental treatments or conditions. Differential gene expression analysis is conducted through pairwise comparisons, and will not be suitable to test multiple factors. This workflow is also designed to be manual rather than automated. Each step must be executed and investigated by the user, yielding a better understanding of data and analytical outputs, and therefore better results for the user. Once complete, this protocol will yield de novo assembled transcriptome(s) for underserved (non-model) organisms without the need to map to previously assembled reference genomes (which are usually not available in underserved organism). These de novo transcriptomes are further used in pairwise differential gene expression analysis to investigate genes differing between two experimental conditions. Differentially expressed genes are then functionally annotated to understand the genetic response organisms have to experimental conditions. In total, the data derived from this protocol is used to test hypotheses about biological responses of underserved organisms.

Evolinc: A Tool for the Identification and Evolutionary Comparison of Long Intergenic Non-coding RNAs.

Long intergenic non-coding RNAs (lincRNAs) are an abundant and functionally diverse class of eukaryotic transcripts. Reported lincRNA repertoires in mammals vary, but are commonly in the thousands to tens of thousands of transcripts, covering ~90% of the genome. In addition to elucidating function, there is particular interest in understanding the origin and evolution of lincRNAs. Aside from mammals, lincRNA populations have been sparsely sampled, precluding evolutionary analyses focused on their emergence and persistence. Here we present Evolinc, a two-module pipeline designed to facilitate lincRNA discovery and characterize aspects of lincRNA evolution. The first module (Evolinc-I) is a lincRNA identification workflow that also facilitates downstream differential expression analysis and genome browser visualization of identified lincRNAs. The second module (Evolinc-II) is a genomic and transcriptomic comparative analysis workflow that determines the phylogenetic depth to which a lincRNA locus is conserved within a user-defined group of related species. Here we validate lincRNA catalogs generated with Evolinc-I against previously annotated Arabidopsis and human lincRNA data. Evolinc-I recapitulated earlier findings and uncovered an additional 70 Arabidopsis and 43 human lincRNAs. We demonstrate the usefulness of Evolinc-II by examining the evolutionary histories of a public dataset of 5,361 Arabidopsis lincRNAs. We used Evolinc-II to winnow this dataset to 40 lincRNAs conserved across species in Brassicaceae. Finally, we show how Evolinc-II can be used to recover the evolutionary history of a known lincRNA, the human telomerase RNA (TERC). These latter analyses revealed unexpected duplication events as well as the loss and subsequent acquisition of a novel TERC locus in the lineage leading to mice and rats. The Evolinc pipeline is currently integrated in CyVerse's Discovery Environment and is free for use by researchers.

The Divergence of Flowering Time Modulated by FT/TFL1 Is Independent to Their Interaction and Binding Activities.

FLOWERING LOCUS T (FT) and TERMINAL FLOWER1 (TFL1) proteins share highly conserved amino acid residues but they play opposite regulatory roles in promoting and repressing the flowering response, respectively. Previous substitution models and functional analysis have identified several key amino acid residues which are critical for the promotion of flowering. However, the precise relationship between naturally occurring FT/TFL1 homologs and the mechanism of their role in flowering is still unclear. In this study, FT/TFL1 homologs from eight Rosaceae species, namely, Spiraea cantoniensis, Pyracantha fortuneana, Photinia serrulata, Fragaria ananassa, Rosa hybrida, Prunus mume, Prunus persica and Prunus yedoensis, were isolated. Three of these homologs were further characterized by functional analyses involving site-directed mutagenesis. The results showed that these FT/TFL1 homologs might have diverse functions despite sharing a high similarity of sequences or crystal structures. Functional analyses were conducted for the key FT amino acids, Tyr-85 and Gln-140. It revealed that TFL1 homologs cannot promote flowering simply by substitution with key FT amino acid residues. Mutations of the IYN triplet motif within segment C of exon 4 can prevent the FT homolog from promoting the flowering. Furthermore, physical interaction of FT homologous or mutated proteins with the transcription factor FD, together with their lipid-binding properties analysis, showed that it was not sufficient to trigger flowering. Thus, our findings revealed that the divergence of flowering time modulating by FT/TFL1 homologs is independent to interaction and binding activities.

Bringing your tools to CyVerse Discovery Environment using Docker.

Docker has become a very popular container-based virtualization platform for software distribution that has revolutionized the way in which scientific software and software dependencies (software stacks) can be packaged, distributed, and deployed. Docker makes the complex and time-consuming installation procedures needed for scientific software a one-time process. Because it enables platform-independent installation, versioning of software environments, and easy redeployment and reproducibility, Docker is an ideal candidate for the deployment of identical software stacks on different compute environments such as XSEDE and Amazon AWS. CyVerse's Discovery Environment also uses Docker for integrating its powerful, community-recommended software tools into CyVerse's production environment for public use. This paper will help users bring their tools into CyVerse Discovery Environment (DE) which will not only allows users to integrate their tools with relative ease compared to the earlier method of tool deployment in DE but will also help users to share their apps with collaborators and release them for public use.

A Genomic Analysis of Factors Driving lincRNA Diversification: Lessons from Plants.

Transcriptomic analyses from across eukaryotes indicate that most of the genome is transcribed at some point in the developmental trajectory of an organism. One class of these transcripts is termed long intergenic noncoding RNAs (lincRNAs). Recently, attention has focused on understanding the evolutionary dynamics of lincRNAs, particularly their conservation within genomes. Here, we take a comparative genomic and phylogenetic approach to uncover factors influencing lincRNA emergence and persistence in the plant family Brassicaceae, to which Arabidopsis thaliana belongs. We searched 10 genomes across the family for evidence of > 5000 lincRNA loci from A. thaliana From loci conserved in the genomes of multiple species, we built alignments and inferred phylogeny. We then used gene tree/species tree reconciliation to examine the duplication history and timing of emergence of these loci. Emergence of lincRNA loci appears to be linked to local duplication events, but, surprisingly, not whole genome duplication events (WGD), or transposable elements. Interestingly, WGD events are associated with the loss of loci for species having undergone relatively recent polyploidy. Lastly, we identify 1180 loci of the 6480 previously annotated A. thaliana lincRNAs (18%) with elevated levels of conservation. These conserved lincRNAs show higher expression, and are enriched for stress-responsiveness and cis-regulatory motifs known as conserved noncoding sequences (CNSs). These data highlight potential functional pathways and suggest that CNSs may regulate neighboring genes at both the genomic and transcriptomic level. In sum, we provide insight into processes that may influence lincRNA diversification by providing an evolutionary context for previously annotated lincRNAs.

Genetic architecture, biochemical underpinnings and ecological impact of floral UV patterning.

Floral attraction traits can significantly affect pollinator visitation patterns, but adaptive evolution of these traits may be constrained by correlations with other traits. In some cases, molecular pathways contributing to floral attraction are well characterized, offering the opportunity to explore loci potentially underlying variation among individuals. Here, we quantify the range of variation in floral UV patterning (i.e. UV 'bulls-eye nectar guides) among crop and wild accessions of Brassica rapa. We then use experimental crosses to examine the genetic architecture, candidate loci and biochemical underpinnings of this patterning as well as phenotypic manipulations to test the ecological impact. We find qualitative variation in UV patterning between wild (commonly lacking UV patterns) and crop (commonly exhibiting UV patterns) accessions. Similar to the majority of crops, recombinant inbred lines (RILs) derived from an oilseed crop × WI fast-plant® cross exhibit UV patterns, the size of which varies extensively among genotypes. In RILs, we further observe strong statistical-genetic and QTL correlations within petal morphological traits and within measurements of petal UV patterning; however, correlations between morphology and UV patterning are weak or nonsignificant, suggesting that UV patterning is regulated and may evolve independently of overall petal size. HPLC analyses reveal a high concentration of sinapoyl glucose in UV-absorbing petal regions, which, in concert with physical locations of UV-trait QTLs, suggest a regulatory and structural gene as candidates underlying observed quantitative variation. Finally, insects prefer flowers with UV bulls-eye patterns over those that lack patterns, validating the importance of UV patterning in pollen-limited populations of B. rapa.

Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange.

Shade avoidance components and pathways in adult plants revealed by phenotypic profiling.

Shade from neighboring plants limits light for photosynthesis; as a consequence, plants have a variety of strategies to avoid canopy shade and compete with their neighbors for light. Collectively the response to foliar shade is called the shade avoidance syndrome (SAS). The SAS includes elongation of a variety of organs, acceleration of flowering time, and additional physiological responses, which are seen throughout the plant life cycle. However, current mechanistic knowledge is mainly limited to shade-induced elongation of seedlings. Here we use phenotypic profiling of seedling, leaf, and flowering time traits to untangle complex SAS networks. We used over-representation analysis (ORA) of shade-responsive genes, combined with previous annotation, to logically select 59 known and candidate novel mutants for phenotyping. Our analysis reveals shared and separate pathways for each shade avoidance response. In particular, auxin pathway components were required for shade avoidance responses in hypocotyl, petiole, and flowering time, whereas jasmonic acid pathway components were only required for petiole and flowering time responses. Our phenotypic profiling allowed discovery of seventeen novel shade avoidance mutants. Our results demonstrate that logical selection of mutants increased success of phenotypic profiling to dissect complex traits and discover novel components.

Polymorphism identification and improved genome annotation of Brassica rapa through Deep RNA sequencing.

The mapping and functional analysis of quantitative traits in Brassica rapa can be greatly improved with the availability of physically positioned, gene-based genetic markers and accurate genome annotation. In this study, deep transcriptome RNA sequencing (RNA-Seq) of Brassica rapa was undertaken with two objectives: SNP detection and improved transcriptome annotation. We performed SNP detection on two varieties that are parents of a mapping population to aid in development of a marker system for this population and subsequent development of high-resolution genetic map. An improved Brassica rapa transcriptome was constructed to detect novel transcripts and to improve the current genome annotation. This is useful for accurate mRNA abundance and detection of expression QTL (eQTLs) in mapping populations. Deep RNA-Seq of two Brassica rapa genotypes-R500 (var. trilocularis, Yellow Sarson) and IMB211 (a rapid cycling variety)-using eight different tissues (root, internode, leaf, petiole, apical meristem, floral meristem, silique, and seedling) grown across three different environments (growth chamber, greenhouse and field) and under two different treatments (simulated sun and simulated shade) generated 2.3 billion high-quality Illumina reads. A total of 330,995 SNPs were identified in transcribed regions between the two genotypes with an average frequency of one SNP in every 200 bases. The deep RNA-Seq reassembled Brassica rapa transcriptome identified 44,239 protein-coding genes. Compared with current gene models of B. rapa, we detected 3537 novel transcripts, 23,754 gene models had structural modifications, and 3655 annotated proteins changed. Gaps in the current genome assembly of B. rapa are highlighted by our identification of 780 unmapped transcripts. All the SNPs, annotations, and predicted transcripts can be viewed at http://phytonetworks.ucdavis.edu/.

Comparative transcriptomics reveals patterns of selection in domesticated and wild tomato.

Although applied over extremely short timescales, artificial selection has dramatically altered the form, physiology, and life history of cultivated plants. We have used RNAseq to define both gene sequence and expression divergence between cultivated tomato and five related wild species. Based on sequence differences, we detect footprints of positive selection in over 50 genes. We also document thousands of shifts in gene-expression level, many of which resulted from changes in selection pressure. These rapidly evolving genes are commonly associated with environmental response and stress tolerance. The importance of environmental inputs during evolution of gene expression is further highlighted by large-scale alteration of the light response coexpression network between wild and cultivated accessions. Human manipulation of the genome has heavily impacted the tomato transcriptome through directed admixture and by indirectly favoring nonsynonymous over synonymous substitutions. Taken together, our results shed light on the pervasive effects artificial and natural selection have had on the transcriptomes of tomato and its wild relatives.

Accurate timekeeping is controlled by a cycling activator in Arabidopsis.

Transcriptional feedback loops are key to circadian clock function in many organisms. Current models of the Arabidopsis circadian network consist of several coupled feedback loops composed almost exclusively of transcriptional repressors. Indeed, a central regulatory mechanism is the repression of evening-phased clock genes via the binding of morning-phased Myb-like repressors to evening element (EE) promoter motifs. We now demonstrate that a related Myb-like protein, REVEILLE8 (RVE8), is a direct transcriptional activator of EE-containing clock and output genes. Loss of RVE8 and its close homologs causes a delay and reduction in levels of evening-phased clock gene transcripts and significant lengthening of clock pace. Our data suggest a substantially revised model of the circadian oscillator, with a clock-regulated activator essential both for clock progression and control of clock outputs. Further, our work suggests that the plant clock consists of a highly interconnected, complex regulatory network rather than of coupled morning and evening feedback loops. DOI:http://dx.doi.org/10.7554/eLife.00473.001.