G4Catchall: A G-quadruplex prediction approach considering atypical features

Investigating G-quadruplex structures in RPGR gene: Implications for understanding X-linked retinal degeneration

Aims

This pilot study investigates the potential pathogenic role of G-quadruplex (G4) structures in RPGR-associated retinal degeneration, starting from a case of suspected X-linked form affected family. We hypothesize that the stabilization of these structures might alter DNA replication and transcription, inducing genetic instability and influencing gene expression.

Main methods

We conducted whole genome amplification experiments and next-generation sequencing to detect the blockade of polymerase activity by G4 structures. Our specific focus was the RPGR gene, which hosts a high concentration of predicted G4-forming motifs and is implicated in most X-linked retinal degeneration cases. To understand the potential interference of G4 structures, we applied computational and 3D molecular modeling to visualize interferences in DNA replication and transcription regulation.

Key findings

Our data confirmed the obstruction of DNA polymerase enzymes by G4 structures, particularly when stabilized by the compound pyridostatin. This obstruction was evident in the reduced amplification of RPGR gene regions and a shift in the start/end sites of putative G4 motifs. Moreover, the modeling indicated a potential disruption of critical promoter elements and RNA polymerase binding, which could drastically alter gene expression.

Significance

Our findings suggest that G4 formation in the RPGR gene could lead to genetic instability and affect the expression of RPGR, contributing to retinal dystrophy. Moreover, this study underscores the broader implications of G4 structures in other genetic disorders. Improved understanding of G4 structures could reveal novel therapeutic targets to combat genetic disorders, promoting the advancement of personalized medicine and precision health.

Toward a Better Understanding of G4 Evolution in the 3 Living Kingdoms

Background

G-quadruplexes (G4s) are secondary structures in DNA and RNA that impact various cellular processes, such as transcription, splicing, and translation. Due to their numerous functions, G4s are involved in many diseases, making their study important. Yet, G4s evolution remains largely unknown, due to their low sequence similarity and the poor quality of their sequence alignments across several species. To address this, we designed a strategy that avoids direct G4s alignment to study G4s evolution in the 3 species kingdoms. We also explored the coevolution between RBPs and G4s.

Methods

We retrieved one-to-one orthologous genes from the Ensembl Compara database and computed groups of one-to-one orthologous genes. For each group, we aligned gene sequences and identified G4 families as groups of overlapping G4s in the alignment. We analyzed these G4 families using Count, a tool to infer feature evolution into a gene or a species tree. Additionally, we utilized these G4 families to predict G4s by homology. To establish a control dataset, we performed mono-, di- and tri-nucleotide shuffling.

Results

Only a few conserved G4s occur among all living kingdoms. In eukaryotes, G4s exhibit slight conservation among vertebrates, and few are conserved between plants. In archaea and bacteria, at most, only 2 G4s are common. The G4 homology-based prediction increases the number of conserved G4s in common ancestors. The coevolution between RNA-binding proteins and G4s was investigated and revealed a modest impact of RNA-binding proteins evolution on G4 evolution. However, the details of this relationship remain unclear.

Conclusion

Even if G4 evolution still eludes us, the present study provides key information to compute groups of homologous G4 and to reveal the evolution history of G4 families.

QUFIND: tool for comparative prediction and mining of G4 quadruplexes overlapping with CpG islands

G-quadruplexes (G4s) are secondary structures in DNA that have been shown to be involved in gene regulation. They play a vital role in the cellular processes and several pathogens including bacteria, fungi, and viruses have also been shown to possess G4s that help them in their pathogenesis. Additionally, cross-talk among the CpG islands and G4s has been shown to influence biological processes. The virus-encoded G4s are affected by the mutational landscape leading to the formation/deletion of these G4s. Therefore, understanding and predicting these multivariate effects on traditional and non-traditional quadruplexes forms an important area of research, that is, yet to be investigated. We have designed a user-friendly webserver QUFIND (http://soodlab.com/qufinder/) that can predict traditional as well as non-traditional quadruplexes in a given sequence. QUFIND is connected with ENSEMBL and NCBI so that the sequences can be fetched in a real-time manner. The algorithm is designed in such a way that the user is provided with multiple options to customize the base (A, T, G, or C), size of the stem (2-5), loop length (1-30), number of bulges (1-5) as well as the number of mismatches (0-2) enabling the identification of any of the secondary structure as per their interest. QUFIND is designed to predict both CpG islands as well as G4s in a given sequence. Since G4s are very short as compared to the CpG islands, hence, QUFIND can also predict the overlapping G4s within CpG islands. Therefore, the user has the flexibility to identify either overlapping or non-overlapping G4s along with the CpG islands. Additionally, one section of QUFIND is dedicated to comparing the G4s in two viral sequences. The visualization is designed in such a manner that the user is able to see the unique quadruplexes in both the input sequences. The efficiency of QUFIND is calculated on G4s obtained from G4 high throughput sequencing data (n = 1000) or experimentally validated G4s (n = 329). Our results revealed that QUFIND is able to predict G4-quadruplexes obtained from G4-sequencing data with 90.06% prediction accuracy whereas experimentally validated quadruplexes were predicted with 97.26% prediction accuracy.

Structural and Functional Classification of G-Quadruplex Families within the Human Genome

G-quadruplexes (G4s) are short secondary DNA structures located throughout genomic DNA and transcribed RNA. Although G4 structures have been shown to form in vivo, no current search tools that examine these structures based on previously identified G-quadruplexes and filter them based on similar sequence, structure, and thermodynamic properties are known to exist. We present a framework for clustering G-quadruplex sequences into families using the CD-HIT, MeShClust, and DNACLUST methods along with a combination of Starcode and BLAST. Utilizing this framework to filter and annotate clusters, 95 families of G-quadruplex sequences were identified within the human genome. Profiles for each family were created using hidden Markov models to allow for the identification of additional family members and generate homology probability scores. The thermodynamic folding energy properties, functional annotation of genes associated with the sequences, scores from different prediction algorithms, and transcription factor binding motifs within a family were used to annotate and compare the diversity within and across clusters. The resulting set of G-quadruplex families can be used to further understand how different regions of the genome are regulated by factors targeting specific structures common to members of a specific cluster.

A CpG island promoter drives the CXXC5 gene expression

CXXC5 is a member of the zinc-finger CXXC family that binds to unmethylated CpG dinucleotides. CXXC5 modulates gene expressions resulting in diverse cellular events mediated by distinct signaling pathways. However, the mechanism responsible for CXXC5 expression remains largely unknown. We found here that of the 14 annotated CXXC5 transcripts with distinct 5' untranslated regions encoding the same protein, transcript variant 2 with the highest expression level among variants represents the main transcript in cell models. The DNA segment in and at the immediate 5'-sequences of the first exon of variant 2 contains a core promoter within which multiple transcription start sites are present. Residing in a region with high G-C nucleotide content and CpG repeats, the core promoter is unmethylated, deficient in nucleosomes, and associated with active RNA polymerase-II. These findings suggest that a CpG island promoter drives CXXC5 expression. Promoter pull-down revealed the association of various transcription factors (TFs) and transcription co-regulatory proteins, as well as proteins involved in histone/chromatin, DNA, and RNA processing with the core promoter. Of the TFs, we verified that ELF1 and MAZ contribute to CXXC5 expression. Moreover, the first exon of variant 2 may contain a G-quadruplex forming region that could modulate CXXC5 expression.

Potential G-quadruplexes and i-Motifs in the SARS-CoV-2

Quadruplex structures have been identified in a plethora of organisms where they play important functions in the regulation of molecular processes, and hence have been proposed as therapeutic targets for many diseases. In this paper we report the extensive bioinformatic analysis of the SARS-CoV-2 genome and related viruses using an upgraded version of the open-source algorithm G4-iM Grinder. This version improves the functionality of the software, including an easy way to determine the potential biological features affected by the candidates found. The quadruplex definitions of the algorithm were optimized for SARS-CoV-2. Using a lax quadruplex definition ruleset, which accepts amongst other parameters two residue G- and C-tracks, 512 potential quadruplex candidates were discovered. These sequences were evaluated by their in vitro formation probability, their position in the viral RNA, their uniqueness and their conservation rates (calculated in over seventeen thousand different COVID-19 clinical cases and sequenced at different times and locations during the ongoing pandemic). These results were then compared subsequently to other Coronaviridae members, other Group IV (+)ssRNA viruses and the entire viral realm. Sequences found in common with other viral species were further analyzed and characterized. Sequences with high scores unique to the SARS-CoV-2 were studied to investigate the variations amongst similar species. Quadruplex formation of the best candidates were then confirmed experimentally. Using NMR and CD spectroscopy, we found several highly stable RNA quadruplexes that may be suitable therapeutic targets for the SARS-CoV-2.

"Protein aggregates" contain RNA and DNA, entrapped by misfolded proteins but largely rescued by slowing translational elongation

All neurodegenerative diseases feature aggregates, which usually contain disease-specific diagnostic proteins; non-protein constituents, however, have rarely been explored. Aggregates from SY5Y-APP_Sw neuroblastoma, a cell model of familial Alzheimer's disease, were crosslinked and sequences of linked peptides identified. We constructed a normalized "contactome" comprising 11 subnetworks, centered on 24 high-connectivity hubs. Remarkably, all 24 are nucleic acid-binding proteins. This led us to isolate and sequence RNA and DNA from Alzheimer's and control aggregates. RNA fragments were mapped to the human genome by RNA-seq and DNA by ChIP-seq. Nearly all aggregate RNA sequences mapped to specific genes, whereas DNA fragments were predominantly intergenic. These nucleic acid mappings are all significantly nonrandom, making an artifactual origin extremely unlikely. RNA (mostly cytoplasmic) exceeded DNA (chiefly nuclear) by twofold to fivefold. RNA fragments recovered from AD tissue were ~1.5-to 2.5-fold more abundant than those recovered from control tissue, similar to the increase in protein. Aggregate abundances of specific RNA sequences were strikingly differential between cultured SY5Y-APP_Sw glioblastoma cells expressing APOE3 vs. APOE4, consistent with APOE4 competition for E-box/CLEAR motifs. We identified many G-quadruplex and viral sequences within RNA and DNA of aggregates, suggesting that sequestration of viral genomes may have driven the evolution of disordered nucleic acid-binding proteins. After RNA-interference knockdown of the translational-procession factor EEF2 to suppress translation in SY5Y-APP_Sw cells, the RNA content of aggregates declined by >90%, while reducing protein content by only 30% and altering DNA content by ≤10%. This implies that cotranslational misfolding of nascent proteins may ensnare polysomes into aggregates, accounting for most of their RNA content.

Whole Genome Identification of Potential G-Quadruplexes and Analysis of the G-Quadruplex Binding Domain for SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has become a global public health emergency. G-quadruplex, one of the non-canonical secondary structures, has shown potential antiviral values. However, little is known about the G-quadruplexes of the emerging SARS-CoV-2. Herein, we characterized the potential G-quadruplexes in both positive and negative-sense viral strands. The identified potential G-quadruplexes exhibited similar features to the G-quadruplexes detected in the human transcriptome. Within some bat- and pangolin-related betacoronaviruses, the G-tracts rather than the loops were under heightened selective constraints. We also found that the amino acid sequence similar to SUD (SARS-unique domain) was retained in SARS-CoV-2 but depleted in some other coronaviruses that can infect humans. Further analysis revealed that the amino acid residues related to the binding affinity of G-quadruplexes were conserved among 16,466 SARS-CoV-2 samples. Moreover, the dimer of the SUD-homology structure in SARS-CoV-2 displayed similar electrostatic potential patterns to the SUD dimer from SARS. Considering the potential value of G-quadruplexes to serve as targets in antiviral strategy, our fundamental research could provide new insights for the SARS-CoV-2 drug discovery.

5' Untranslated Region Elements Show High Abundance and Great Variability in Homologous ABCA Subfamily Genes

The 12 members of the ABCA subfamily in humans are known for their ability to transport cholesterol and its derivatives, vitamins, and xenobiotics across biomembranes. Several ABCA genes are causatively linked to inborn diseases, and the role in cancer progression and metastasis is studied intensively. The regulation of translation initiation is implicated as the major mechanism in the processes of post-transcriptional modifications determining final protein levels. In the current bioinformatics study, we mapped the features of the 5' untranslated regions (5'UTR) known to have the potential to regulate translation, such as the length of 5'UTRs, upstream ATG codons, upstream open-reading frames, introns, RNA G-quadruplex-forming sequences, stem loops, and Kozak consensus motifs, in the DNA sequences of all members of the subfamily. Subsequently, the conservation of the features, correlations among them, ribosome profiling data as well as protein levels in normal human tissues were examined. The 5'UTRs of ABCA genes contain above-average numbers of upstream ATGs, open-reading frames and introns, as well as conserved ones, and these elements probably play important biological roles in this subfamily, unlike RG4s. Although we found significant correlations among the features, we did not find any correlation between the numbers of 5'UTR features and protein tissue distribution and expression scores. We showed the existence of single nucleotide variants in relation to the 5'UTR features experimentally in a cohort of 105 breast cancer patients. 5'UTR features presumably prepare a complex playground, in which the other elements such as RNA binding proteins and non-coding RNAs play the major role in the fine-tuning of protein expression.

Transcriptomic Changes in Endothelial Cells Triggered by Na,K-ATPase Inhibition: A Search for Upstream Na+i/K+i Sensitive Genes

Stimulus-dependent elevation of intracellular Ca²⁺ affects gene expression via well-documented calmodulin-mediated signaling pathways. Recently, we found that the addition of extra- and intracellular Ca²⁺ chelators increased, rather than decreased, the number of genes expressed, and that this is affected by the elevation of [Na⁺]_i/[K⁺]_i-ratio. This assumes the existence of a novel Na⁺_i/K⁺_i-mediated Ca²⁺_i-independent mechanism of excitation-transcription coupling. To identify upstream Na⁺_i/K⁺_i-sensitive genes, we examined the kinetics of transcriptomic changes in human umbilical vein endothelial cells (HUVEC) subjected to Na,K-ATPase inhibition by ouabain or K⁺-free medium. According to our data, microRNAs, transcription factors, and proteins involved in immune response and inflammation might be considered as key components of Na⁺_i/K⁺_i-mediated excitation-transcription coupling. Special attention was focused on the FOS gene and the possible mechanism of transcription regulation via G-quadruplexes, non-canonical secondary structures of nucleic acids, whose stability depends on [Na⁺]_i/[K⁺]_i-ratio. Verification of the [Na⁺]_i/[K⁺]_i-sensitive transcription regulation mechanism should be continued in forthcoming studies.

Development of dual-emission cluster of Ag atoms for genetically modified organisms detection

A DNA-silver nanocluster with two distinct emissions is devised, in which this unique modality has been exploited to develop a novel nanosensor for transgenic DNA detection. TEM and fluorescence analysis revealed the formation of Ag nanoclusters with a size of around 2 nm, which exhibit dual-emissions at 550 nm (green) and 630 nm (red). Moreover, in the presence of the target sequence (CaMV 35S promoter) from the transgenic plant, the nanoclusters showed an enhancement in the green emission and a reduction in the red emission. This property provided a ratiometric-sensing platform which lacks unavoidable noises. The ratio of green to red fluorescence emission (G/R) of the nanoclusters exhibited a linear relation with the target concentration in the range 10 to 1000 nM. However, the control DNA did not affect this ratio, which clearly confirmed the selective response of the designed nanosensor. This sensing platform had a detection limit of 1.5 nM and identified the DNA of transgenic soybeans within a short time. The mechanistic evaluation of the nanoclusters further revealed the role of protonated cytosine bases in the dual emission behavior. Finally, unique features of the designed nanosensor may improve the current approaches for the development and manufacturing of GMO detection tools.

The Fragile X Mental Retardation Protein Regulates RIPK1 and Colorectal Cancer Resistance to Necroptosis

BACKGROUND & AIMS

The fragile X mental retardation protein (FMRP) affects multiple steps of the mRNA metabolism during brain development and in different neoplastic processes. However, the contribution of FMRP in colon carcinogenesis has not been investigated.

METHODS

FMR1 mRNA transcript and FMRP protein expression were analyzed in human colon samples derived from patients with sporadic colorectal cancer (CRC) and healthy subjects. We used a well-established mouse model of sporadic CRC induced by azoxymethane to determine the possible role of FMRP in CRC. To address whether FMRP controls cancer cell survival, we analyzed cell death pathway in CRC human epithelial cell lines and in patient-derived colon cancer organoids in presence or absence of a specific FMR1 antisense oligonucleotide or siRNA.

RESULTS

We document a significant increase of FMRP in human CRC relative to non-tumor tissues. Next, using an inducible mouse model of CRC, we observed a reduction of colonic tumor incidence and size in the Fmr1 knockout mice. The abrogation of FMRP induced spontaneous cell death in human CRC cell lines activating the necroptotic pathway. Indeed, specific immunoprecipitation experiments on human cell lines and CRC samples indicated that FMRP binds receptor-interacting protein kinase 1 (RIPK1) mRNA, suggesting that FMRP acts as a regulator of necroptosis pathway through the surveillance of RIPK1 mRNA metabolism. Treatment of human CRC cell lines and patient-derived colon cancer organoids with the FMR1 antisense resulted in up-regulation of RIPK1.

CONCLUSIONS

Altogether, these data support a role for FMRP  in controlling RIPK1 expression and necroptotic activation in CRC.

How bioinformatics resources work with G4 RNAs

Quadruplexes (G4s) are of interest, which increases with the number of identified G4 structures and knowledge about their biomedical potential. These unique motifs form in many organisms, including humans, where their appearance correlates with various diseases. Scientists store and analyze quadruplexes using recently developed bioinformatic tools—many of them focused on DNA structures. With an expanding collection of G4 RNAs, we check how existing tools deal with them. We review all available bioinformatics resources dedicated to quadruplexes and examine their usefulness in G4 RNA analysis. We distinguish the following subsets of resources: databases, tools to predict putative quadruplex sequences, tools to predict secondary structure with quadruplexes and tools to analyze and visualize quadruplex structures. We share the results obtained from processing specially created RNA datasets with these tools.

Contact: mszachniuk@cs.put.poznan.pl

Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.

A guide to computational methods for G-quadruplex prediction

Guanine-rich nucleic acids can fold into the non-B DNA or RNA structures called G-quadruplexes (G4). Recent methodological developments have allowed the characterization of specific G-quadruplex structures in vitro as well as in vivo, and at a much higher throughput, in silico, which has greatly expanded our understanding of G4-associated functions. Typically, the consensus motif G3+N1-7G3+N1-7G3+N1-7G3+ has been used to identify potential G-quadruplexes from primary sequence. Since, various algorithms have been developed to predict the potential formation of quadruplexes directly from DNA or RNA sequences and the number of studies reporting genome-wide G4 exploration across species has rapidly increased. More recently, new methodologies have also appeared, proposing other estimates which consider non-canonical sequences and/or structure propensity and stability. The present review aims at providing an updated overview of the current open-source G-quadruplex prediction algorithms and straightforward examples of their implementation.