Genome-wide survey of DNA-binding proteins in Arabidopsis thaliana: analysis of distribution and functions

HybridDBRpred: improved sequence-based prediction of DNA-binding amino acids using annotations from structured complexes and disordered proteins

Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two distinct groups, those trained on binding annotations extracted from structured protein-DNA complexes (structure-trained) vs. intrinsically disordered proteins (disorder-trained). We complete the first empirical analysis of predictive performance across the structure- and disorder-annotated proteins for a representative collection of ten predictors. Majority of the structure-trained tools perform well on the structure-annotated proteins while doing relatively poorly on the disorder-annotated proteins, and vice versa. Several methods make accurate predictions for the structure-annotated proteins or the disorder-annotated proteins, but none performs highly accurately for both annotation types. Moreover, most predictors make excessive cross-predictions for the disorder-annotated proteins, where residues that interact with non-DNA ligand types are predicted as DBRs. Motivated by these results, we design, validate and deploy an innovative meta-model, hybridDBRpred, that uses deep transformer network to combine predictions generated by three best current predictors. HybridDBRpred provides accurate predictions and low levels of cross-predictions across the two annotation types, and is statistically more accurate than each of the ten tools and baseline meta-predictors that rely on averaging and logistic regression. We deploy hybridDBRpred as a convenient web server at http://biomine.cs.vcu.edu/servers/hybridDBRpred/ and provide the corresponding source code at https://github.com/jianzhang-xynu/hybridDBRpred.

Base Excision DNA Repair in Plants: Arabidopsis and Beyond

Base excision DNA repair (BER) is a key pathway safeguarding the genome of all living organisms from damage caused by both intrinsic and environmental factors. Most present knowledge about BER comes from studies of human cells, E. coli, and yeast. Plants may be under an even heavier DNA damage threat from abiotic stress, reactive oxygen species leaking from the photosynthetic system, and reactive secondary metabolites. In general, BER in plant species is similar to that in humans and model organisms, but several important details are specific to plants. Here, we review the current state of knowledge about BER in plants, with special attention paid to its unique features, such as the existence of active epigenetic demethylation based on the BER machinery, the unexplained diversity of alkylation damage repair enzymes, and the differences in the processing of abasic sites that appear either spontaneously or are generated as BER intermediates. Understanding the biochemistry of plant DNA repair, especially in species other than the Arabidopsis model, is important for future efforts to develop new crop varieties.

qNABpredict: Quick, accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids

Protein sequence-based predictors of nucleic acid (NA)-binding include methods that predict NA-binding proteins and NA-binding residues. The residue-level tools produce more details but suffer high computational cost since they must predict every amino acid in the input sequence and rely on multiple sequence alignments. We propose an alternative approach that predicts content (fraction) of the NA-binding residues, offering more information than the protein-level prediction and much shorter runtime than the residue-level tools. Our first-of-its-kind content predictor, qNABpredict, relies on a small, rationally designed and fast-to-compute feature set that represents relevant characteristics extracted from the input sequence and a well-parametrized support vector regression model. We provide two versions of qNABpredict, a taxonomy-agnostic model that can be used for proteins of unknown taxonomic origin and more accurate taxonomy-aware models that are tailored to specific taxonomic kingdoms: archaea, bacteria, eukaryota, and viruses. Empirical tests on a low-similarity test dataset show that qNABpredict is 100 times faster and generates statistically more accurate content predictions when compared to the content extracted from results produced by the residue-level predictors. We also show that qNABpredict's content predictions can be used to improve results generated by the residue-level predictors. We release qNABpredict as a convenient webserver and source code at http://biomine.cs.vcu.edu/servers/qNABpredict/. This new tool should be particularly useful to predict details of protein-NA interactions for large protein families and proteomes.

Genome-wide Identification and Characterization of Heat Shock Protein Family Reveals Role in Development and Stress Conditions in Triticum aestivum L

Heat shock proteins (HSPs) have a significant role in protein folding and are considered as prominent candidates for development of heat-tolerant crops. Understanding of wheat HSPs has great importance since wheat is severely affected by heat stress, particularly during the grain filling stage. In the present study, efforts were made to identify HSPs in wheat and to understand their role during plant development and under different stress conditions. HSPs in wheat genome were first identified by using Position-Specific Scoring Matrix (PSSMs) of known HSP domains and then also confirmed by sequence homology with already known HSPs. Collectively, 753 TaHSPs including 169 TaSHSP, 273 TaHSP40, 95 TaHSP60, 114 TaHSP70, 18 TaHSP90 and 84 TaHSP100 were identified in the wheat genome. Compared with other grass species, number of HSPs in wheat was relatively high probably due to the higher ploidy level. Large number of tandem duplication was identified in TaHSPs, especially TaSHSPs. The TaHSP genes showed random distribution on chromosomes, however, there were more TaHSPs in B and D sub-genomes as compared to the A sub-genome. Extensive computational analysis was performed using the available genomic resources to understand gene structure, gene expression and phylogentic relationship of TaHSPs. Interestingly, apart from high expression under heat stress, high expression of TaSHSP was also observed during seed development. The study provided a list of candidate HSP genes for improving thermo tolerance during developmental stages and also for understanding the seed development process in bread wheat.

DNA Base Excision Repair in Plants: An Unfolding Story With Familiar and Novel Characters

Base excision repair (BER) is a critical genome defense pathway that deals with a broad range of non-voluminous DNA lesions induced by endogenous or exogenous genotoxic agents. BER is a complex process initiated by the excision of the damaged base, proceeds through a sequence of reactions that generate various DNA intermediates, and culminates with restoration of the original DNA structure. BER has been extensively studied in microbial and animal systems, but knowledge in plants has lagged behind until recently. Results obtained so far indicate that plants share many BER factors with other organisms, but also possess some unique features and combinations. Plant BER plays an important role in preserving genome integrity through removal of damaged bases. However, it performs additional important functions, such as the replacement of the naturally modified base 5-methylcytosine with cytosine in a plant-specific pathway for active DNA demethylation.

Kodoja: A workflow for virus detection in plants using k-mer analysis of RNA-sequencing data

RNA-sequencing of plant material allows for hypothesis-free detection of multiple viruses simultaneously. This methodology relies on bioinformatics workflows for virus identification. Most workflows are designed for human clinical data, and few go beyond sequence mapping for virus identification. We present a new workflow (Kodoja) for the detection of plant virus sequences in RNA-sequence data. Kodoja uses k-mer profiling at the nucleotide level and sequence mapping at the protein level by integrating two existing tools Kraken and Kaiju. Kodoja was tested on three existing RNA-seq datasets from grapevine, and two new RNA-seq datasets from raspberry. For grapevine, Kodoja was shown to be more sensitive than a method based on contig building and blast alignments (27 viruses detected compared to 19). The application of Kodoja to raspberry, showed that field-grown raspberries were infected by multiple viruses, and that RNA-seq can identify lower amounts of virus material than reverse transcriptase PCR. This work enabled the design of new PCR-primers for detection of Raspberry yellow net virus and Beet ringspot virus. Kodoja is a sensitive method for plant virus discovery in field samples and enables the design of more accurate primers for detection. Kodoja is available to install through Bioconda and as a tool within Galaxy.

Viral Diagnostics in Plants Using Next Generation Sequencing: Computational Analysis in Practice

Viruses cause significant yield and quality losses in a wide variety of cultivated crops. Hence, the detection and identification of viruses is a crucial facet of successful crop production and of great significance in terms of world food security. Whilst the adoption of molecular techniques such as RT-PCR has increased the speed and accuracy of viral diagnostics, such techniques only allow the detection of known viruses, i.e., each test is specific to one or a small number of related viruses. Therefore, unknown viruses can be missed and testing can be slow and expensive if molecular tests are unavailable. Methods for simultaneous detection of multiple viruses have been developed, and (NGS) is now a principal focus of this area, as it enables unbiased and hypothesis-free testing of plant samples. The development of NGS protocols capable of detecting multiple known and emergent viruses present in infected material is proving to be a major advance for crops, nuclear stocks or imported plants and germplasm, in which disease symptoms are absent, unspecific or only triggered by multiple viruses. Researchers want to answer the question "how many different viruses are present in this crop plant?" without knowing what they are looking for: RNA-sequencing (RNA-seq) of plant material allows this question to be addressed. As well as needing efficient nucleic acid extraction and enrichment protocols, virus detection using RNA-seq requires fast and robust bioinformatics methods to enable host sequence removal and virus classification. In this review recent studies that use RNA-seq for virus detection in a variety of crop plants are discussed with specific emphasis on the computational methods implemented. The main features of a number of specific bioinformatics workflows developed for virus detection from NGS data are also outlined and possible reasons why these have not yet been widely adopted are discussed. The review concludes by discussing the future directions of this field, including the use of bioinformatics tools for virus detection deployed in analytical environments using cloud computing.

Ancestor of land plants acquired the DNA-3-methyladenine glycosylase (MAG) gene from bacteria through horizontal gene transfer

The origin and evolution of land plants was an important event in the history of life and initiated the establishment of modern terrestrial ecosystems. From water to terrestrial environments, plants needed to overcome the enhanced ultraviolet (UV) radiation and many other DNA-damaging agents. Evolving new genes with the function of DNA repair is critical for the origin and radiation of land plants. In bacteria, the DNA-3-methyladenine glycosylase (MAG) recognizes of a variety of base lesions and initiates the process of the base excision repair for damaged DNA. The homologs of MAG gene are present in all major lineages of streptophytes, and both the phylogenic and sequence similarity analyses revealed that green plant MAG gene originated through an ancient horizontal gene transfer (HGT) event from bacteria. Experimental evidence demonstrated that the expression of the maize ZmMAG gene was induced by UV and zeocin, both of which are known as DNA-damaging agents. Further investigation revealed that Streptophyta MAG genes had undergone positive selection during the initial evolutionary period in the ancestor of land plants. Our findings demonstrated that the ancient HGT of MAG to the ancestor of land plants probably played an important role in preadaptation to DNA-damaging agents in terrestrial environments.

Genome-wide survey of putative RNA-binding proteins encoded in the human proteome

RNA-binding proteins (RBPs) are involved in various post-transcriptional gene regulatory processes and are also functionally important members of the ribosome and the spliceosome. However, RBPs and their interactions with RNA are less well-studied in comparison to DNA-binding proteins. We have classified the existing RBP structures, available in complexes with RNA and RNA/DNA hybrids, into different structural families and created Hidden Markov Models (HMMs). These structure-centric family HMMs, along with the sequence-centric family HMMs, were used as a primary database to systematically search the human proteome for the presence of putative RBPs. We have found more than 2600 gene products with RBP signatures in humans, of which around 28% are likely to bind to RNA but not DNA, whereas 9% might bind to both RNA and DNA. 11% of them do not contain an explicit functional annotation yet. Nearly 30% of the putative RBPs are exclusively nuclear, 15% have known disease associations and around 30% are enzymes. Around 40% of the proteins identified in this study are novel and have not been reported by recent large-scale studies on human RBPs.

Expansion Mechanisms and Evolutionary History on Genes Encoding DNA Glycosylases and Their Involvement in Stress and Hormone Signaling

DNA glycosylases catalyze the release of methylated bases. They play vital roles in the base excision repair pathway and might also function in DNA demethylation. At least three families of DNA glycosylases have been identified, which included 3′-methyladenine DNA glycosylase (MDG) I, MDG II, and HhH-GPD (Helix–hairpin–Helix and Glycine/Proline/aspartate (D)). However, little is known on their genome-wide identification, expansion, and evolutionary history as well as their expression profiling and biological functions. In this study, we have genome-widely identified and evolutionarily characterized these family members. Generally, a genome encodes only one MDG II gene in most of organisms. No MDG I or MDG II gene was detected in green algae. However, HhH-GPD genes were detectable in all available organisms. The ancestor species contain small size of MDG I and HhH-GPD families. These two families were mainly expanded through the whole-genome duplication and segmental duplication. They were evolutionarily conserved and were generally under purifying selection. However, we have detected recent positive selection among the Oryza genus, which might play roles in species divergence. Further investigation showed that expression divergence played important roles in gene survival after expansion. All of these family genes were expressed in most of developmental stages and tissues in rice plants. High ratios of family genes were downregulated by drought and fungus pathogen as well as abscisic acid (ABA) and jasmonic acid (JA) treatments, suggesting a negative regulation in response to drought stress and pathogen infection through ABA- and/or JA-dependent hormone signaling pathway.

Profiling of the Early Nitrogen Stress Response in the Diatom Phaeodactylum tricornutum Reveals a Novel Family of RING-Domain Transcription Factors

Diatoms often inhabit highly variable habitats where they are confronted with a wide variety of stresses, frequently including starvation of nutrients such as nitrogen. In this study, the transcriptome of the model diatom Phaeodactylum tricornutum was profiled during the onset of nitrogen starvation by RNA sequencing, and overrepresented motifs were determined in promoters of genes that were early and strongly up-regulated during the nitrogen stress response. One of these motifs could be bound by a nitrogen starvation-inducible RING-domain protein termed RING-GAF-Gln-containing protein (RGQ1), which was shown to act as a transcription factor and belongs to a previously uncharacterized family that is conserved in heterokont algae.

Collation and analyses of DNA-binding protein domain families from sequence and structural databanks

DNA-protein interactions govern several high fidelity cellular processes like DNA-replication, transcription, DNA repair, etc. Proteins that have the ability to recognise and bind DNA sequences can be classified either according to their DNA-binding motif or based on the sequence of the target nucleotides. We have collated the DNA-binding families by integrating information from both protein sequence family and structural databases. This resulted in a dataset of 1057 DNA-binding protein domain families. Their family properties (the number of members, percent identity distribution and length of members) and domain architectures were examined. Further, sequence domain families were mapped to structures in the protein databank (PDB) and the protein domain structure classification database (SCOP). The DNA-binding families, with no structural information, were clustered together into potential superfamilies based on sequence associations. On the basis of functions attributed to DNA-binding protein folds, we observe that a majority of the DNA-binding proteins follow divergent evolution. This study can serve as a basis for annotation and distribution of DNA-binding proteins in genome(s) of interest. The entire collated set of DNA-binding protein domains is available for download as Hidden Markov Models.

Phosphorylation-dependent regulation of plant chromatin and chromatin-associated proteins

In eukaryotes, most of the DNA is located in the nucleus where it is organized with histone proteins in a higher order structure as chromatin. Chromatin and chromatin-associated proteins contribute to DNA-related processes such as replication and transcription as well as epigenetic regulation. Protein functions are often regulated by PTMs among which phosphorylation is one of the most abundant PTM. Phosphorylation of proteins affects important properties, such as enzyme activity, protein stability, or subcellular localization. We here describe the main specificities of protein phosphorylation in plants and review the current knowledge on phosphorylation-dependent regulation of plant chromatin and chromatin-associated proteins. We also outline some future challenges to further elucidate protein phosphorylation and chromatin regulation.