Post-translational modifications of proteins are well-established participants in DNA damage response (DDR) pathways, which function in the maintenance of genome integrity. Emerging evidence is starting to reveal the involvement of modifications on RNA in the DDR. RNA modifications are known regulators of gene expression but how and if they participate in DNA repair and genome maintenance has been poorly understood. Here, we review several studies that have now established RNA modifications as key components of DNA damage responses. RNA modifying enzymes and the binding proteins that recognize these modifications localize to and participate in the repair of UV-induced and DNA double-strand break lesions. RNA modifications have a profound effect on DNA-RNA hybrids (R-loops) at DNA damage sites, a structure known to be involved in DNA repair and genome stability. Given the importance of the DDR in suppressing mutations and human diseases such as neurodegeneration, immunodeficiencies, cancer and aging, RNA modification pathways may be involved in human diseases not solely through their roles in gene expression but also by their ability to impact DNA repair and genome stability.

Nearly 200 distinct chemical modifications of RNAs have been discovered to date. Their analysis via direct methods has been possible in abundant RNA species, such as ribosomal, transfer or viral RNA, since several decades. However, their analysis in less abundant RNAs species, especially cellular messenger RNAs, was rendered possible only recently with the advent of high throughput sequencing techniques. Given the growing biomedical interest of the proteins that write, erase and read RNA modifications, ingenious new methods to enrich and identify RNA modifications at base resolution have been implemented, and more efforts are underway to render them more quantitative. Here, we review several crucial modification-specific (bio)chemical approaches and discuss their advantages and shortcomings for exploring the epitranscriptome.

Ribonucleotides within the various RNA molecules in eukaryotes are marked with more than 160 distinct covalent chemical modifications. These modifications include those that occur internally in messenger RNA (mRNA) molecules such as N6-methyladenosine (m6A) and 5-methylcytosine (m5C), as well as those that occur at the ends of the modified RNAs like the non-canonical 5' end nicotinamide adenine dinucleotide (NAD+) cap modification of specific mRNAs. Recent findings have revealed that covalent RNA modifications can impact the secondary structure, translatability, functionality, stability and degradation of the RNA molecules in which they are included. Many of these covalent RNA additions have also been found to be dynamically added and removed through writer and eraser complexes, respectively, providing a new layer of epitranscriptome-mediated post-transcriptional regulation that regulates RNA quality and quantity in eukaryotic transcriptomes. Thus, it is not surprising that the regulation of RNA fate mediated by these epitranscriptomic marks has been demonstrated to have widespread effects on plant development and the responses of these organisms to abiotic and biotic stresses. In this review, we highlight recent progress focused on the study of the dynamic nature of these epitranscriptome marks and their roles in post-transcriptional regulation during plant development and response to environmental cues, with an emphasis on the mRNA modifications of non-canonical 5' end NAD+ capping, m6A and several other internal RNA modifications.

Transfer ribonucleicacids (RNAs) (tRNAs) are essential adaptor molecules for translation. The functions and stability of tRNAs are modulated by their post-transcriptional modifications (tRNA modifications). Each domain of life has a specific set of modifications that include ones shared in multiple domains and ones specific to a domain. In some cases, different tRNA modifications across domains have similar functions to each other. Recent studies uncovered that distinct enzymes synthesize the same modification in different organisms, suggesting that such modifications are acquired through independent evolution. In this short review, I outline the mechanisms by which various modifications contribute to tRNA function, including modulation of decoding and tRNA stability, using recent findings. I also focus on modifications that are synthesized by distinct biosynthetic pathways.

The vertebrate endoderm makes major contributions to the respiratory and gastrointestinal tracts and all associated organs. Zebrafish and humans share a high degree of genetic homology and strikingly similar endodermal organ systems. Combined with a multitude of experimental advantages, zebrafish are an attractive model organism to study endoderm development and disease. Recent functional genomics studies have shed considerable light on the gene regulatory programs governing early zebrafish endoderm development, while advances in biological and technological approaches stand to further revolutionize our ability to investigate endoderm formation, function and disease. Here, we discuss the present understanding of endoderm specification in zebrafish compared to other vertebrates, how current and emerging methods will allow refined and enhanced analysis of endoderm formation, and how integration with human data will allow modeling of the link between non-coding sequence variants and human disease.

Regulation of gene expression relies on the activity of specialized genomic elements, enhancers or silencers, distributed over sometimes large distance from their target gene promoters. A significant part of vertebrate genomes consists in such regulatory elements, but their identification and that of their target genes remains challenging, due to the lack of clear signature at the nucleotide level. For many years the main hallmark used for identifying functional elements has been their sequence conservation between genomes of distant species, indicative of purifying selection. More recently, genome-wide biochemical assays have opened new avenues for detecting regulatory regions, shifting attention away from evolutionary constraints. Here, we review the respective contributions of comparative genomics and biochemical assays for the definition of regulatory elements and their targets and advocate that both sequence conservation and preserved synteny, taken as signature of functional constraint, remain essential tools in this task.

In recent years, remarkable progress has been made toward understanding the three-dimensional (3D) organisation of genomes and the influence of genome organisation on gene regulation. Although 3D genome organisation probably plays a crucial role in embryo development, animal studies addressing the developmental roles of chromosome topology are only just starting to emerge. Zebrafish, an important model system for early development, have already contributed important advances in understanding the developmental consequences of perturbation in 3D genome organisation. Zebrafish have been used to determine the effects of mutations in proteins responsible for 3D genome organisation: cohesin and CTCF. In this review, we highlight research to date from zebrafish that has provided insight into how 3D genome organisation contributes to tissue-specific gene regulation and embryo development.

Glaucoma is a disease with characteristic optic neuropathy and loss of vision, leading to blindness, and primary open-angle glaucoma (POAG) is the most common glaucoma type throughout the world. Genetic susceptibility is the main factor in POAG, and most susceptibility genes cause changes in microRNA expression and function, thereby leading to POAG occurrence and development. Increasing evidence indicates that many microRNAs are involved in the regulation of intraocular pressure (IOP) and play an important role in the increase in IOP in POAG. Additionally, microRNA is closely related to optic nerve damage factors (mechanical stress, hypoxia and inflammation). This review discusses the effect of single-nucleotide polymorphisms in POAG-related genes on microRNA and the value of microRNA in the diagnosis and treatment of POAG.

Gut microbes have attracted much more attentions in the recent decade since their essential roles in the development of metabolic diseases, cancer and neurological diseases. Considerable evidence indicates that the metabolism of gut microbes exert influences on intestinal homeostasis and human diseases. Here, we first reviewed two mainstream sequencing technologies involving 16s rRNA sequencing and metagenomic sequencing for gut microbes, and data analysis methods assessing alpha and beta diversity. Next, we introduced some observational studies reflecting that many factors, such as lifestyle and intake of diets, drugs, contribute to gut microbes' quantity and diversity. Then, metabolites produced by gut microbes were presented to understand that gut microbes exert on host homeostasis in the intestinal epithelium and immune system. Finally, we focused on the molecular mechanism of gut microbes on the occurrence and development of several common diseases. In-depth knowledge of the relationship among interventions, gut microbes and diseases might provide new insights in to disease prevention and treatment.

Deep learning has been increasingly used in bioinformatics, especially in sequence-based protein prediction tasks, as large amounts of biological data are available and deep learning techniques have been developed rapidly in recent years. For sequence-based protein prediction tasks, the selection of a suitable model architecture is essential, whereas sequence data representation is a major factor in controlling model performance. Here, we summarized all the main approaches that are used to represent protein sequence data (amino acid sequence encoding or embedding), which include end-to-end embedding methods, non-contextual embedding methods and embedding methods that use transfer learning and others that are applied for some specific tasks (such as protein sequence embedding based on extracted features for protein structure predictions and graph convolutional network-based embedding for drug discovery tasks). We have also reviewed the architectures of various types of embedding models theoretically and the development of these types of sequence embedding approaches to facilitate researchers and users in selecting the model that best suits their requirements.