Transposon dynamics in the emerging oilseed crop Thlaspi arvense.

Genome evolution is partly driven by the mobility of transposable elements (TEs) which often leads to deleterious effects, but their activity can also facilitate genetic novelty and catalyze local adaptation. We explored how the intraspecific diversity of TE polymorphisms might contribute to the broad geographic success and adaptive capacity of the emerging oil crop Thlaspi arvense (field pennycress). We classified the TE inventory based on a high-quality genome assembly, estimated the age of retrotransposon TE families and comprehensively assessed their mobilization potential. A survey of 280 accessions from 12 regions across the Northern hemisphere allowed us to quantify over 90,000 TE insertion polymorphisms (TIPs). Their distribution mirrored the genetic differentiation as measured by single nucleotide polymorphisms (SNPs). The number and types of mobile TE families vary substantially across populations, but there are also shared patterns common to all accessions. Ty3/Athila elements are the main drivers of TE diversity in T. arvense populations, while a single Ty1/Alesia lineage might be particularly important for transcriptome divergence. The number of retrotransposon TIPs is associated with variation at genes related to epigenetic regulation, including an apparent knockout mutation in BROMODOMAIN AND ATPase DOMAIN-CONTAINING PROTEIN 1 (BRAT1), while DNA transposons are associated with variation at the HSP19 heat shock protein gene. We propose that the high rate of mobilization activity can be harnessed for targeted gene expression diversification, which may ultimately present a toolbox for the potential use of transposition in breeding and domestication of T. arvense.

Sensitive protein alignments at tree-of-life scale using DIAMOND.

We are at the beginning of a genomic revolution in which all known species are planned to be sequenced. Accessing such data for comparative analyses is crucial in this new age of data-driven biology. Here, we introduce an improved version of DIAMOND that greatly exceeds previous search performances and harnesses supercomputing to perform tree-of-life scale protein alignments in hours, while matching the sensitivity of the gold standard BLASTP.

noisyR: enhancing biological signal in sequencing datasets by characterizing random technical noise.

High-throughput sequencing enables an unprecedented resolution in transcript quantification, at the cost of magnifying the impact of technical noise. The consistent reduction of random background noise to capture functionally meaningful biological signals is still challenging. Intrinsic sequencing variability introducing low-level expression variations can obscure patterns in downstream analyses. We introduce noisyR, a comprehensive noise filter to assess the variation in signal distribution and achieve an optimal information-consistency across replicates and samples; this selection also facilitates meaningful pattern recognition outside the background-noise range. noisyR is applicable to count matrices and sequencing data; it outputs sample-specific signal/noise thresholds and filtered expression matrices. We exemplify the effects of minimizing technical noise on several datasets, across various sequencing assays: coding, non-coding RNAs and interactions, at bulk and single-cell level. An immediate consequence of filtering out noise is the convergence of predictions (differential-expression calls, enrichment analyses and inference of gene regulatory networks) across different approaches.

Environmental and epigenetic regulation of Rider retrotransposons in tomato.

Transposable elements in crop plants are the powerful drivers of phenotypic variation that has been selected during domestication and breeding programs. In tomato, transpositions of the LTR (long terminal repeat) retrotransposon family Rider have contributed to various phenotypes of agronomical interest, such as fruit shape and colour. However, the mechanisms regulating Rider activity are largely unknown. We have developed a bioinformatics pipeline for the functional annotation of retrotransposons containing LTRs and defined all full-length Rider elements in the tomato genome. Subsequently, we showed that accumulation of Rider transcripts and transposition intermediates in the form of extrachromosomal DNA is triggered by drought stress and relies on abscisic acid signalling. We provide evidence that residual activity of Rider is controlled by epigenetic mechanisms involving siRNAs and the RNA-dependent DNA methylation pathway. Finally, we demonstrate the broad distribution of Rider-like elements in other plant species, including crops. Our work identifies Rider as an environment-responsive element and a potential source of genetic and epigenetic variation in plants.

The Earth BioGenome project: opportunities and challenges for plant genomics and conservation.

Sequencing them all. That is the ambitious goal of the recently launched Earth BioGenome project (Proceedings of the National Academy of Sciences of the United States of America, 115, 4325-4333), which aims to produce reference genomes for all eukaryotic species within the next decade. In this perspective, we discuss the opportunities of this project with a plant focus, but highlight also potential limitations. This includes the question of how to best capture all plant diversity, as the green taxon is one of the most complex clades in the tree of life, with over 300 000 species. For this, we highlight four key points: (i) the unique biological insights that could be gained from studying plants, (ii) their apparent underrepresentation in sequencing efforts given the number of threatened species, (iii) the necessity of phylogenomic methods that are aware of differences in genome complexity and quality, and (iv) the accounting for within-species genetic diversity and the historical aspect of conservation genetics.

SecretSanta: flexible pipelines for functional secretome prediction.

Motivation: The secretome denotes the collection of secreted proteins exported outside of the cell. The functional roles of secreted proteins include the maintenance and remodelling of the extracellular matrix as well as signalling between host and non-host cells. These features make secretomes rich reservoirs of biomarkers for disease classification and host-pathogen interaction studies. Common biomarkers are extracellular proteins secreted via classical pathways that can be predicted from sequence by annotating the presence or absence of N-terminal signal peptides. Several heterogeneous command line tools and web-interfaces exist to identify individual motifs, signal sequences and domains that are either characteristic or strictly excluded from secreted proteins. However, a single flexible secretome-prediction workflow that combines all analytic steps is still missing. Results: To bridge this gap the SecretSanta package implements wrapper and parser functions around established command line tools for the integrative prediction of extracellular proteins that are secreted via classical pathways. The modularity of SecretSanta enables users to create tailored pipelines and apply them across the whole tree of life to facilitate comparison of secretomes across multiple species or under various conditions. Availability and implementation: SecretSanta is implemented in the R programming language and is released under GPL-3 license. All functions have been optimized and parallelized to allow large-scale processing of sequences. The open-source code, installation instructions and vignette with use case scenarios can be downloaded from https://github.com/gogleva/SecretSanta. Supplementary information: Supplementary data are available at Bioinformatics online.

myTAI: evolutionary transcriptomics with R.

Motivation: Next Generation Sequencing (NGS) technologies generate a large amount of high quality transcriptome datasets enabling the investigation of molecular processes on a genomic and metagenomic scale. These transcriptomics studies aim to quantify and compare the molecular phenotypes of the biological processes at hand. Despite the vast increase of available transcriptome datasets, little is known about the evolutionary conservation of those characterized transcriptomes. Results: The myTAI package implements exploratory analysis functions to infer transcriptome conservation patterns in any transcriptome dataset. Comprehensive documentation of myTAI functions and tutorial vignettes provide step-by-step instructions on how to use the package in an exploratory and computationally reproducible manner. Availability and implementation: The open source myTAI package is available at https://github.com/HajkD/myTAI and https://cran.r-project.org/web/packages/myTAI/index.html. Contact: hgd23@cam.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

Biomartr: genomic data retrieval with R.

Motivation: Retrieval and reproducible functional annotation of genomic data are crucial in biology. However, the current poor usability and transparency of retrieval methods hinders reproducibility. Here we present an open source R package, biomartr , which provides a comprehensive easy-to-use framework for automating data retrieval and functional annotation for meta-genomic approaches. The functions of biomartr achieve a high degree of clarity, transparency and reproducibility of analyses. Results: The biomartr package implements straightforward functions for bulk retrieval of all genomic data or data for selected genomes, proteomes, coding sequences and annotation files present in databases hosted by the National Center for Biotechnology Information (NCBI) and European Bioinformatics Institute (EMBL-EBI). In addition, biomartr communicates with the BioMart database for functional annotation of retrieved sequences. Comprehensive documentation of biomartr functions and five tutorial vignettes provide step-by-step instructions on how to use the package in a reproducible manner. Availability and Implementation: The open source biomartr package is available at https://github.com/HajkD/biomartr and https://cran.r-project.org/web/packages/biomartr/index.html . Contact: hgd23@cam.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

A transcriptomic hourglass in plant embryogenesis.

Animal and plant development starts with a constituting phase called embryogenesis, which evolved independently in both lineages. Comparative anatomy of vertebrate development--based on the Meckel-Serrès law and von Baer's laws of embryology from the early nineteenth century--shows that embryos from various taxa appear different in early stages, converge to a similar form during mid-embryogenesis, and again diverge in later stages. This morphogenetic series is known as the embryonic 'hourglass', and its bottleneck of high conservation in mid-embryogenesis is referred to as the phylotypic stage. Recent analyses in zebrafish and Drosophila embryos provided convincing molecular support for the hourglass model, because during the phylotypic stage the transcriptome was dominated by ancient genes and global gene expression profiles were reported to be most conserved. Although extensively explored in animals, an embryonic hourglass has not been reported in plants, which represent the second major kingdom in the tree of life that evolved embryogenesis. Here we provide phylotranscriptomic evidence for a molecular embryonic hourglass in Arabidopsis thaliana, using two complementary approaches. This is particularly significant because the possible absence of an hourglass based on morphological features in plants suggests that morphological and molecular patterns might be uncoupled. Together with the reported developmental hourglass patterns in animals, these findings indicate convergent evolution of the molecular hourglass and a conserved logic of embryogenesis across kingdoms.

Post-embryonic Hourglass Patterns Mark Ontogenetic Transitions in Plant Development.

The historic developmental hourglass concept depicts the convergence of animal embryos to a common form during the phylotypic period. Recently, it has been shown that a transcriptomic hourglass is associated with this morphological pattern, consistent with the idea of underlying selective constraints due to intense molecular interactions during body plan establishment. Although plants do not exhibit a morphological hourglass during embryogenesis, a transcriptomic hourglass has nevertheless been identified in the model plant Arabidopsis thaliana Here, we investigated whether plant hourglass patterns are also found postembryonically. We found that the two main phase changes during the life cycle of Arabidopsis, from embryonic to vegetative and from vegetative to reproductive development, are associated with transcriptomic hourglass patterns. In contrast, flower development, a process dominated by organ formation, is not. This suggests that plant hourglass patterns are decoupled from organogenesis and body plan establishment. Instead, they may reflect general transitions through organizational checkpoints.

Evidence for active maintenance of phylotranscriptomic hourglass patterns in animal and plant embryogenesis.

The developmental hourglass model has been used to describe the morphological transitions of related species throughout embryogenesis. Recently, quantifiable approaches combining transcriptomic and evolutionary information provided novel evidence for the presence of a phylotranscriptomic hourglass pattern across kingdoms. As its biological function is unknown it remains speculative whether this pattern is functional or merely represents a nonfunctional evolutionary relic. The latter would seriously hamper future experimental approaches designed to test hypotheses regarding its function. Here, we address this question by generating transcriptome divergence index (TDI) profiles across embryogenesis of Danio rerio, Drosophila melanogaster, and Arabidopsis thaliana. To enable meaningful evaluation of the resulting patterns, we develop a statistical test that specifically assesses potential hourglass patterns. Based on this objective measure we find that two of these profiles follow a statistically significant hourglass pattern with the most conserved transcriptomes in the phylotypic periods. As the TDI considers only recent evolutionary signals, this indicates that the phylotranscriptomic hourglass pattern is not a rudiment but possibly actively maintained, implicating the existence of some linked biological function associated with embryogenesis in extant species.

Patterns of gene expression during Arabidopsis flower development from the time of initiation to maturation.

BACKGROUND: The formation of flowers is one of the main model systems to elucidate the molecular mechanisms that control developmental processes in plants. Although several studies have explored gene expression during flower development in the model plant Arabidopsis thaliana on a genome-wide scale, a continuous series of expression data from the earliest floral stages until maturation has been lacking. Here, we used a floral induction system to close this information gap and to generate a reference dataset for stage-specific gene expression during flower formation. RESULTS: Using a floral induction system, we collected floral buds at 14 different stages from the time of initiation until maturation. Using whole-genome microarray analysis, we identified 7,405 genes that exhibit rapid expression changes during flower development. These genes comprise many known floral regulators and we found that the expression profiles for these regulators match their known expression patterns, thus validating the dataset. We analyzed groups of co-expressed genes for over-represented cellular and developmental functions through Gene Ontology analysis and found that they could be assigned specific patterns of activities, which are in agreement with the progression of flower development. Furthermore, by mapping binding sites of floral organ identity factors onto our dataset, we were able to identify gene groups that are likely predominantly under control of these transcriptional regulators. We further found that the distribution of paralogs among groups of co-expressed genes varies considerably, with genes expressed predominantly at early and intermediate stages of flower development showing the highest proportion of such genes. CONCLUSIONS: Our results highlight and describe the dynamic expression changes undergone by a large number of genes during flower development. They further provide a comprehensive reference dataset for temporal gene expression during flower formation and we demonstrate that it can be used to integrate data from other genomics approaches such as genome-wide localization studies of transcription factor binding sites.

Transcriptional dynamics of two seed compartments with opposing roles in Arabidopsis seed germination.

Seed germination is a critical stage in the plant life cycle and the first step toward successful plant establishment. Therefore, understanding germination is of important ecological and agronomical relevance. Previous research revealed that different seed compartments (testa, endosperm, and embryo) control germination, but little is known about the underlying spatial and temporal transcriptome changes that lead to seed germination. We analyzed genome-wide expression in germinating Arabidopsis (Arabidopsis thaliana) seeds with both temporal and spatial detail and provide Web-accessible visualizations of the data reported (vseed.nottingham.ac.uk). We show the potential of this high-resolution data set for the construction of meaningful coexpression networks, which provide insight into the genetic control of germination. The data set reveals two transcriptional phases during germination that are separated by testa rupture. The first phase is marked by large transcriptome changes as the seed switches from a dry, quiescent state to a hydrated and active state. At the end of this first transcriptional phase, the number of differentially expressed genes between consecutive time points drops. This increases again at testa rupture, the start of the second transcriptional phase. Transcriptome data indicate a role for mechano-induced signaling at this stage and subsequently highlight the fates of the endosperm and radicle: senescence and growth, respectively. Finally, using a phylotranscriptomic approach, we show that expression levels of evolutionarily young genes drop during the first transcriptional phase and increase during the second phase. Evolutionarily old genes show an opposite pattern, suggesting a more conserved transcriptome prior to the completion of germination.

Uncovering gene-family founder events during major evolutionary transitions in animals, plants and fungi using GenEra.

We present GenEra ( https://github.com/josuebarrera/GenEra ), a DIAMOND-fueled gene-family founder inference framework that addresses previously raised limitations and biases in genomic phylostratigraphy, such as homology detection failure. GenEra also reduces computational time from several months to a few days for any genome of interest. We analyze the emergence of taxonomically restricted gene families during major evolutionary transitions in plants, animals, and fungi. Our results indicate that the impact of homology detection failure on inferred patterns of gene emergence is lineage-dependent, suggesting that plants are more prone to evolve novelty through the emergence of new genes compared to animals and fungi.

Sensitive inference of alignment-safe intervals from biodiverse protein sequence clusters using EMERALD.

Sequence alignments are the foundations of life science research, but most innovation so far focuses on optimal alignments, while information derived from suboptimal solutions is ignored. We argue that one optimal alignment per pairwise sequence comparison is a reasonable approximation when dealing with very similar sequences but is insufficient when exploring the biodiversity of the protein universe at tree-of-life scale. To overcome this limitation, we introduce pairwise alignment-safety to uncover the amino acid positions robustly shared across all suboptimal solutions. We implement EMERALD, a software library for alignment-safety inference, and apply it to 400k sequences from the SwissProt database.

Canalization of genome-wide transcriptional activity in Arabidopsis thaliana accessions by MET1-dependent CG methylation.

BACKGROUND: Despite its conserved role on gene expression and transposable element (TE) silencing, genome-wide CG methylation differs substantially between wild Arabidopsis thaliana accessions. RESULTS: To test our hypothesis that global reduction of CG methylation would reduce epigenomic, transcriptomic, and phenotypic diversity in A. thaliana accessions, we knock out MET1, which is required for CG methylation, in 18 early-flowering accessions. Homozygous met1 mutants in all accessions suffer from common developmental defects such as dwarfism and delayed flowering, in addition to accession-specific abnormalities in rosette leaf architecture, silique morphology, and fertility. Integrated analysis of genome-wide methylation, chromatin accessibility, and transcriptomes confirms that MET1 inactivation greatly reduces CG methylation and alters chromatin accessibility at thousands of loci. While the effects on TE activation are similarly drastic in all accessions, the quantitative effects on non-TE genes vary greatly. The global expression profiles of accessions become considerably more divergent from each other after genome-wide removal of CG methylation, although a few genes with diverse expression profiles across wild-type accessions tend to become more similar in mutants. Most differentially expressed genes do not exhibit altered chromatin accessibility or CG methylation in cis, suggesting that absence of MET1 can have profound indirect effects on gene expression and that these effects vary substantially between accessions. CONCLUSIONS: Systematic analysis of MET1 requirement in different A. thaliana accessions reveals a dual role for CG methylation: for many genes, CG methylation appears to canalize expression levels, with methylation masking regulatory divergence. However, for a smaller subset of genes, CG methylation increases expression diversity beyond genetically encoded differences.

A Predictive Approach to Infer the Activity and Natural Variation of Retrotransposon Families in Plants.

Plant genomes harbor a particularly rich landscape of repetitive sequences. Transposable elements (TEs) represent a major fraction of this diversity and are intimately linked with plasticity and evolution of genomes across the tree of life (Fedoroff, Science 338:758-767, 2012). Amplification of Long Terminal Repeats (LTR) retrotransposons have shaped the genomic landscape by reshuffling genomic regions, altering gene expression, and providing new regulatory sequences, some of which have been instrumental for crop domestication and breeding (Lisch, Nat Rev Genet 14:49-61, 2013; Vitte et al., Brief Funct Genomics 13:276-295, 2014). While many retrotransposon families are still active within plant genomes, the repetitive nature of retrotransposons has hindered accurate annotation and kingdom-wide predictive assessment of their activity and molecular evolution. While it is natural for the first approach towards a genome annotation to characterize all regions of the genome and associate them with known structures such as particular genes, transposable elements, or other types of non-coding regions, such efforts can result in a large proportion of false-positive annotations when seeking for active loci. To overcome this issue, the next round of annotation efforts needs to include functional annotations based on rigorously defined sequence structures and protein domain compositions. In the context of retrotransposons, such a functional annotation can enable efforts to mobilize particular retrotransposon families in species living today and harness their mutagenic potency for crop improvement (Paszkowski, Curr Opin Biotechnol 32:200-206, 2015). For this purpose, we present a predictive analytical approach to infer the activity and natural variation of retrotransposon families in plants. This is achieved by applying a combination of software and molecular biology tools we developed for functional annotation, activity monitoring, and the assessment of the population structure of particular retrotransposon families in multiple plant species.

Grafting vigour is associated with DNA de-methylation in eggplant.

In horticulture, grafting is a popular technique used to combine positive traits from two different plants. This is achieved by joining the plant top part (scion) onto a rootstock which contains the stem and roots. Rootstocks can provide resistance to stress and increase plant production, but despite their wide use, the biological mechanisms driving rootstock-induced alterations of the scion phenotype remain largely unknown. Given that epigenetics plays a relevant role during distance signalling in plants, we studied the genome-wide DNA methylation changes induced in eggplant (Solanum melongena) scion using two interspecific rootstocks to increase vigour. We found that vigour was associated with a change in scion gene expression and a genome-wide hypomethylation in the CHH context. Interestingly, this hypomethylation correlated with the downregulation of younger and potentially more active long terminal repeat retrotransposable elements (LTR-TEs), suggesting that graft-induced epigenetic modifications are associated with both physiological and molecular phenotypes in grafted plants. Our results indicate that the enhanced vigour induced by heterografting in eggplant is associated with epigenetic modifications, as also observed in some heterotic hybrids.