Anno genominis XX: 20 years of Arabidopsis genomics

Plant genome information facilitates plant functional genomics

MAIN CONCLUSION

In this review, we give an overview of plant sequencing efforts and how this impacts plant functional genomics research. Plant genome sequence information greatly facilitates the studies of plant biology, functional genomics, evolution of genomes and genes, domestication processes, phylogenetic relationships, among many others. More than two decades of sequencing efforts have boosted the number of available sequenced plant genomes. The first plant genome, of Arabidopsis, was published in the year 2000 and currently, 4604 plant genomes from 1482 plant species have been published. Various large sequence initiatives are running, which are planning to produce tens of thousands of sequenced plant genomes in the near future. In this review, we give an overview on the status of sequenced plant genomes and on the use of genome information in different research areas.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

Mapping the Arabidopsis thaliana proteome in PeptideAtlas and the nature of the unobserved (dark) proteome; strategies towards a complete proteome

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome - the 'dark' proteome. This dark proteome is highly enriched for certain ( e.g. CLE, CEP, IDA, PSY) but not other ( e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life ( e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.

Deciphering Macromolecular Interactions Involved in Abiotic Stress Signaling: A Review of Bioinformatics Analysis

Plant functioning and responses to abiotic stresses largely involve regulations at the transcriptomic level via complex interactions of signal molecules, signaling cascades, and regulators. Nevertheless, all the signaling networks involved in responses to abiotic stresses have not yet been fully established. The in-depth analysis of transcriptomes in stressed plants has become a relevant state-of-the-art methodology to study these regulations and signaling pathways that allow plants to cope with or attempt to survive abiotic stresses. The plant science and molecular biology community has developed databases about genes, proteins, protein-protein interactions, protein-DNA interactions and ontologies, which are valuable sources of knowledge for deciphering such regulatory and signaling networks. The use of these data and the development of bioinformatics tools help to make sense of transcriptomic data in specific contexts, such as that of abiotic stress signaling, using functional biological approaches. The aim of this chapter is to present and assess some of the essential online tools and resources that will allow novices in bioinformatics to decipher transcriptomic data in order to characterize the cellular processes and functions involved in abiotic stress responses and signaling. The analysis of case studies further describes how these tools can be used to conceive signaling networks on the basis of transcriptomic data. In these case studies, particular attention was paid to the characterization of abiotic stress responses and signaling related to chemical and xenobiotic stressors.

Bioinformatic Tools for Exploring the SUMO Gene Network: An Update

Plant sumoylation research has seen significant advances in recent years, particularly since high-throughput proteomic strategies have enabled the discovery of more than one thousand SUMO targets. In the present chapter, we update the previously reported SUMO (small ubiquitin-related modifier) gene network (SGN) to its v4 iteration. SGN is a curated assembly of Arabidopsis thaliana genes that have been functionally associated with sumoylation, from SUMO pathway components to targets and interactors. The enclosed tutorial helps interpret and manage these datasets and details bioinformatic tools that can be used for in silico-based hypothesis generation. The latter include tools for sumoylation site prediction, comparative genomics, and gene network analysis.

Establishment and optimization of a new model organism to study early land plant evolution: Germination, cultivation and oospore variation of Chara braunii Gmelin, 1826

For studying land plant evolution, the establishment and optimization of model organisms representing streptophytic algae, sister to land plants, is essential. Long-term cultivation experiments with Chara braunii S276 were performed over 8 years, since 4 years (Nov. 2018) under constant conditions. Additionally, short-term experiments for optimization of culture conditions were performed with three strains of C. braunii (S276, NIES-1604 and Lausiger Teiche, LaT-2708). Germination success after application of sterilization agents, addition of gibberellic acid and under different incubation conditions with respect to pre-treatment, irradiance regime and substrate was investigated in order to develop protocols for generative cultivation of at least unialgal cultures. The resulting cultivation protocols for C. braunii S276, allowing maintenance of vegetative as well as generative cultures are presented in detail, including protocols for germination induction and growth of sterilized and unsterilized oospores.

Plant genome sequence assembly in the era of long reads: Progress, challenges and future directions

Third-generation long-read sequencing is transforming plant genomics. Oxford Nanopore Technologies and Pacific Biosciences are offering competing long-read sequencing technologies and enable plant scientists to investigate even large and complex plant genomes. Sequencing projects can be conducted by single research groups and sequences of smaller plant genomes can be completed within days. This also resulted in an increased investigation of genomes from multiple species in large scale to address fundamental questions associated with the origin and evolution of land plants. Increased accessibility of sequencing devices and user-friendly software allows more researchers to get involved in genomics. Current challenges are accurately resolving diploid or polyploid genome sequences and better accounting for the intra-specific diversity by switching from the use of single reference genome sequences to a pangenome graph.

Assembling Plant Genomes with Long-Read Sequencing

Continuous improvements in long-read sequencing allow us to tackle increasingly big and complex genomes. Here we present the principles of long-read genome assembly, taking Solanum pennellii nanopore sequencing as an example.

High-quality Arabidopsis thaliana Genome Assembly with Nanopore and HiFi Long Reads

Arabidopsis thaliana is an important and long-established model species for plant molecular biology, genetics, epigenetics, and genomics. However, the latest version of reference genome still contains significant number of missing segments. Here, we report a high-quality and almost complete Col-0 genome assembly with two gaps (Col-XJTU) using combination of Oxford Nanopore Technology ultra-long reads, PacBio high-fidelity long reads, and Hi-C data. The total genome assembly size is 133,725,193 bp, introducing 14.6 Mb of novel sequences compared to the TAIR10.1 reference genome. All five chromosomes of Col-XJTU assembly are highly accurate with consensus quality (QV) scores > 60 (ranging from 62 to 68), which are higher than those of TAIR10.1 reference (QV scores ranging from 45 to 52). We have completely resolved chromosome (Chr) 3 and Chr5 in a telomere-to-telomere manner. Chr4 has been completely resolved except the nucleolar organizing regions, which comprise long repetitive DNA fragments. The Chr1 centromere (CEN1), reportedly around 9 Mb in length, is particularly challenging to assemble due to the presence of tens of thousands of CEN180 satellite repeats. Using the cutting-edge sequencing data and novel computational approaches, we assembled about 4 Mb of sequence for CEN1 and a 3.5-Mb-long CEN2. We investigated the structure and epigenetics of centromeres. We detected four clusters of CEN180 monomers, and found that the centromere-specific histone H3-like protein (CENH3) exhibits a strong preference for CEN180 cluster 3. Moreover, we observed hypomethylation patterns in CENH3-enriched regions. We believe that this high-quality genome assembly, Col-XJTU, would serve as a valuable reference to better understand the global pattern of centromeric polymorphisms, as well as genetic and epigenetic features in plants.