The dimorphic diaspore model Aethionema arabicum (Brassicaceae): Distinct molecular and morphological control of responses to parental and germination temperatures.

Plants in habitats with unpredictable conditions often have diversified bet-hedging strategies that ensure fitness over a wider range of variable environmental factors. A striking example is the diaspore (seed and fruit) heteromorphism that evolved to maximize species survival in Aethionema arabicum (Brassicaceae) in which external and endogenous triggers allow the production of two distinct diaspores on the same plant. Using this dimorphic diaspore model, we identified contrasting molecular, biophysical, and ecophysiological mechanisms in the germination responses to different temperatures of the mucilaginous seeds (M+ seed morphs), the dispersed indehiscent fruits (IND fruit morphs), and the bare non-mucilaginous M- seeds obtained by pericarp (fruit coat) removal from IND fruits. Large-scale comparative transcriptome and hormone analyses of M+ seeds, IND fruits, and M- seeds provided comprehensive datasets for their distinct thermal responses. Morph-specific differences in co-expressed gene modules in seeds, as well as in seed and pericarp hormone contents, identified a role of the IND pericarp in imposing coat dormancy by generating hypoxia affecting abscisic acid (ABA) sensitivity. This involved expression of morph-specific transcription factors, hypoxia response, and cell wall remodeling genes, as well as altered ABA metabolism, transport, and signaling. Parental temperature affected ABA contents and ABA-related gene expression and altered IND pericarp biomechanical properties. Elucidating the molecular framework underlying the diaspore heteromorphism can provide insight into developmental responses to globally changing temperatures.

Genomic imprints of unparalleled growth.

Chlorella ohadii was isolated from desert biological soil crusts, one of the harshest habitats on Earth, and is emerging as an exciting new green model for studying growth, photosynthesis and metabolism under a wide range of conditions. Here, we compared the genome of C. ohadii, the fastest growing alga on record, to that of other green algae, to reveal the genomic imprints empowering its unparalleled growth rate and resistance to various stressors, including extreme illumination. This included the genome of its close relative, but slower growing and photodamage sensitive, C. sorokiniana UTEX 1663. A larger number of ribosome-encoding genes, high intron abundance, increased codon bias and unique genes potentially involved in metabolic flexibility and resistance to photodamage are all consistent with the faster growth of C. ohadii. Some of these characteristics highlight general trends in Chlorophyta and Chlorella spp. evolution, and others open new broad avenues for mechanistic exploration of their relationship with growth. This work entails a unique case study for the genomic adaptations and costs of exceptionally fast growth and sheds light on the genomic signatures of fast growth in photosynthetic cells. It also provides an important resource for future studies leveraging the unique properties of C. ohadii for photosynthesis and stress response research alongside their utilization for synthetic biology and biotechnology aims.

EasyGDB: a low-maintenance and highly customizable system to develop genomics portals.

SUMMARY: EasyGDB is an easy-to-implement low-maintenance tool developed to create genomic data management web platforms. It can be used for any species, group of species, or multiple genome or annotation versions. EasyGDB provides a framework to develop a web portal that includes the general information about species, projects and members, and bioinformatics tools such as file downloads, BLAST, genome browser, annotation search, gene expression visualization, annotation and sequence download, and gene ids and orthologs lookup. The code of EasyGDB facilitates data maintenance and update for non-experienced bioinformaticians, using BLAST databases to store and retrieve sequence data in gene annotation pages and bioinformatics tools, and JSON files to customize metadata. EasyGDB is a highly customizable tool. Any section and tool can be enabled or disabled like a switch through a single configuration file. This tool aims to simplify the development of genomics portals in non-model species, providing a modern web style with embedded interactive bioinformatics tools to cover all the common needs derived from genomics projects. AVAILABILITY AND IMPLEMENTATION: The code and manual to use EasyGDB can be found at https://github.com/noefp/easy_gdb.

Aethionema arabicum genome annotation using PacBio full-length transcripts provides a valuable resource for seed dormancy and Brassicaceae evolution research.

Aethionema arabicum is an important model plant for Brassicaceae trait evolution, particularly of seed (development, regulation, germination, dormancy) and fruit (development, dehiscence mechanisms) characters. Its genome assembly was recently improved but the gene annotation was not updated. Here, we improved the Ae. arabicum gene annotation using 294 RNA-seq libraries and 136 307 full-length PacBio Iso-seq transcripts, increasing BUSCO completeness by 11.6% and featuring 5606 additional genes. Analysis of orthologs showed a lower number of genes in Ae. arabicum than in other Brassicaceae, which could be partially explained by loss of homeologs derived from the At-α polyploidization event and by a lower occurrence of tandem duplications after divergence of Aethionema from the other Brassicaceae. Benchmarking of MADS-box genes identified orthologs of FUL and AGL79 not found in previous versions. Analysis of full-length transcripts related to ABA-mediated seed dormancy discovered a conserved isoform of PIF6-ß and antisense transcripts in ABI3, ABI4 and DOG1, among other cases found of different alternative splicing between Turkey and Cyprus ecotypes. The presented data allow alternative splicing mining and proposition of numerous hypotheses to research evolution and functional genomics. Annotation data and sequences are available at the Ae. arabicum DB (https://plantcode.online.uni-marburg.de/aetar_db).

Comparative transcriptomics identifies candidate genes involved in the evolutionary transition from dehiscent to indehiscent fruits in Lepidium (Brassicaceae).

BACKGROUND: Fruits are the seed-bearing structures of flowering plants and are highly diverse in terms of morphology, texture and maturation. Dehiscent fruits split open upon maturation to discharge their seeds while indehiscent fruits are dispersed as a whole. Indehiscent fruits evolved from dehiscent fruits several times independently in the crucifer family (Brassicaceae). The fruits of Lepidium appelianum, for example, are indehiscent while the fruits of the closely related L. campestre are dehiscent. Here, we investigate the molecular and genetic mechanisms underlying the evolutionary transition from dehiscent to indehiscent fruits using these two Lepidium species as model system. RESULTS: We have sequenced the transcriptomes and small RNAs of floral buds, flowers and fruits of L. appelianum and L. campestre and analyzed differentially expressed genes (DEGs) and differently differentially expressed genes (DDEGs). DEGs are genes that show significantly different transcript levels in the same structures (buds, flowers and fruits) in different species, or in different structures in the same species. DDEGs are genes for which the change in expression level between two structures is significantly different in one species than in the other. Comparing the two species, the highest number of DEGs was found in flowers, followed by fruits and floral buds while the highest number of DDEGs was found in fruits versus flowers followed by flowers versus floral buds. Several gene ontology terms related to cell wall synthesis and degradation were overrepresented in different sets of DEGs highlighting the importance of these processes for fruit opening. Furthermore, the fruit valve identity genes FRUITFULL and YABBY3 were among the DEGs identified. Finally, the microRNA miR166 as well as the TCP transcription factors BRANCHED1 (BRC1) and TCP FAMILY TRANSCRIPTION FACTOR 4 (TCP4) were found to be DDEGs. CONCLUSIONS: Our study reveals differences in gene expression between dehiscent and indehiscent fruits and uncovers miR166, BRC1 and TCP4 as candidate genes for the evolutionary transition from dehiscent to indehiscent fruits in Lepidium.

An overview of bioinformatics, genomics, and transcriptomics resources for bryophytes.

Bryophytes are useful models for the study of plant evolution, development, plant-fungal symbiosis, stress responses, and gametogenesis. Additionally, their dominant haploid gametophytic phase makes them great models for functional genomics research, allowing straightforward genome editing and gene knockout via CRISPR or homologous recombination. Until 2016, however, the only bryophyte genome sequence published was that of Physcomitrium patens. Throughout recent years, several other bryophyte genomes and transcriptome datasets became available, enabling better comparative genomics in evolutionary studies. The increase in the number of bryophyte genome and transcriptome resources available has yielded a plethora of annotations, databases, and bioinformatics tools to access the new data, which covers the large diversity of this clade and whose biology comprises features such as association with arbuscular mycorrhiza fungi, sex chromosomes, low gene redundancy, or loss of RNA editing genes for organellar transcripts. Here we provide a guide to resources available for bryophytes with regards to genome and transcriptome databases and bioinformatics tools.

PEATmoss (Physcomitrella Expression Atlas Tool): a unified gene expression atlas for the model plant Physcomitrella patens.

Physcomitrella patens is a bryophyte model plant that is often used to study plant evolution and development. Its resources are of great importance for comparative genomics and evo-devo approaches. However, expression data from Physcomitrella patens were so far generated using different gene annotation versions and three different platforms: CombiMatrix and NimbleGen expression microarrays and RNA sequencing. The currently available P. patens expression data are distributed across three tools with different visualization methods to access the data. Here, we introduce an interactive expression atlas, Physcomitrella Expression Atlas Tool (PEATmoss), that unifies publicly available expression data for P. patens and provides multiple visualization methods to query the data in a single web-based tool. Moreover, PEATmoss includes 35 expression experiments not previously available in any other expression atlas. To facilitate gene expression queries across different gene annotation versions, and to access P. patens annotations and related resources, a lookup database and web tool linked to PEATmoss was implemented. PEATmoss can be accessed at https://peatmoss.online.uni-marburg.de.

A blind and independent benchmark study for detecting differeally methylated regions in plants.

MOTIVATION: Bisulfite sequencing (BS-seq) is a state-of-the-art technique for investigating methylation of the DNA to gain insights into the epigenetic regulation. Several algorithms have been published for identification of differentially methylated regions (DMRs). However, the performances of the individual methods remain unclear and it is difficult to optimally select an algorithm in application settings. RESULTS: We analyzed BS-seq data from four plants covering three taxonomic groups. We first characterized the data using multiple summary statistics describing methylation levels, coverage, noise, as well as frequencies, magnitudes and lengths of methylated regions. Then, simulated datasets with most similar characteristics to real experimental data were created. Seven different algorithms (metilene, methylKit, MOABS, DMRcate, Defiant, BSmooth, MethylSig) for DMR identification were applied and their performances were assessed. A blind and independent study design was chosen to reduce bias and to derive practical method selection guidelines. Overall, metilene had superior performance in most settings. Data attributes, such as coverage and spread of the DMR lengths, were found to be useful for selecting the best method for DMR detection. A decision tree to select the optimal approach based on these data attributes is provided. The presented procedure might serve as a general strategy for deriving algorithm selection rules tailored to demands in specific application settings. AVAILABILITY AND IMPLEMENTATION: Scripts that were used for the analyses and that can be used for prediction of the optimal algorithm are provided at https://github.com/kreutz-lab/DMR-DecisionTree. Simulated and experimental data are available at https://doi.org/10.6084/m9.figshare.11619045. CONTACT: ckreutz@imbi.uni-freiburg.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Usability of reference-free transcriptome assemblies for detection of differential expression: a case study on Aethionema arabicum dimorphic seeds.

BACKGROUND: RNA-sequencing analysis is increasingly utilized to study gene expression in non-model organisms without sequenced genomes. Aethionema arabicum (Brassicaceae) exhibits seed dimorphism as a bet-hedging strategy - producing both a less dormant mucilaginous (M+) seed morph and a more dormant non-mucilaginous (NM) seed morph. Here, we compared de novo and reference-genome based transcriptome assemblies to investigate Ae. arabicum seed dimorphism and to evaluate the reference-free versus -dependent approach for identifying differentially expressed genes (DEGs). RESULTS: A de novo transcriptome assembly was generated using sequences from M+ and NM Ae. arabicum dry seed morphs. The transcripts of the de novo assembly contained 63.1% complete Benchmarking Universal Single-Copy Orthologs (BUSCO) compared to 90.9% for the transcripts of the reference genome. DEG detection used the strict consensus of three methods (DESeq2, edgeR and NOISeq). Only 37% of 1533 differentially expressed de novo assembled transcripts paired with 1876 genome-derived DEGs. Gene Ontology (GO) terms distinguished the seed morphs: the terms translation and nucleosome assembly were overrepresented in DEGs higher in abundance in M+ dry seeds, whereas terms related to mRNA processing and transcription were overrepresented in DEGs higher in abundance in NM dry seeds. DEGs amongst these GO terms included ribosomal proteins and histones (higher in M+), RNA polymerase II subunits and related transcription and elongation factors (higher in NM). Expression of the inferred DEGs and other genes associated with seed maturation (e.g. those encoding late embryogenesis abundant proteins and transcription factors regulating seed development and maturation such as ABI3, FUS3, LEC1 and WRI1 homologs) were put in context with Arabidopsis thaliana seed maturation and indicated that M+ seeds may desiccate and mature faster than NM. The 1901 transcriptomic DEG set GO-terms had almost 90% overlap with the 2191 genome-derived DEG GO-terms. CONCLUSIONS: Whilst there was only modest overlap of DEGs identified in reference-free versus -dependent approaches, the resulting GO analysis was concordant in both approaches. The identified differences in dry seed transcriptomes suggest mechanisms underpinning previously identified contrasts between morphology and germination behaviour of M+ and NM seeds.

The Tomato Expression Atlas.

SUMMARY: With the development of new high-throughput DNA sequencing technologies and decreasing costs, large gene expression datasets are being generated at an accelerating rate, but can be complex to visualize. New, more interactive and intuitive tools are needed to visualize the spatiotemporal context of expression data and help elucidate gene function. Using tomato fruit as a model, we have developed the Tomato Expression Atlas to facilitate effective data analysis, allowing the simultaneous visualization of groups of genes at a cell/tissue level of resolution within an organ, enhancing hypothesis development and testing in addition to candidate gene identification. This atlas can be adapted to different types of expression data from diverse multicellular species. AVAILABILITY AND IMPLEMENTATION: The Tomato Expression Atlas is available at http://tea.solgenomics.net/ . Source code is available at https://github.com/solgenomics/Tea . CONTACT: jr286@cornell.edu or lam87@cornell.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.