Next-Gen GWAS: full 2D epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction.

The problem of missing heritability requires the consideration of genetic interactions among different loci, called epistasis. Current GWAS statistical models require years to assess the entire combinatorial epistatic space for a single phenotype. We propose Next-Gen GWAS (NGG) that evaluates over 60 billion single nucleotide polymorphism combinatorial first-order interactions within hours. We apply NGG to Arabidopsis thaliana providing two-dimensional epistatic maps at gene resolution. We demonstrate on several phenotypes that a large proportion of the missing heritability can be retrieved, that it indeed lies in epistatic interactions, and that it can be used to improve phenotype prediction.

Exploring the brain epitranscriptome: perspectives from the NSAS summit.

Increasing evidence reinforces the essential function of RNA modifications in development and diseases, especially in the nervous system. RNA modifications impact various processes in the brain, including neurodevelopment, neurogenesis, neuroplasticity, learning and memory, neural regeneration, neurodegeneration, and brain tumorigenesis, leading to the emergence of a new field termed neuroepitranscriptomics. Deficiency in machineries modulating RNA modifications has been implicated in a range of brain disorders from microcephaly, intellectual disability, seizures, and psychiatric disorders to brain cancers such as glioblastoma. The inaugural NSAS Challenge Workshop on Brain Epitranscriptomics hosted in Crans-Montana, Switzerland in 2023 assembled a group of experts from the field, to discuss the current state of the field and provide novel translational perspectives. A summary of the discussions at the workshop is presented here to simulate broader engagement from the general neuroscience field.

Smurfness-based two-phase model of ageing helps deconvolve the ageing transcriptional signature.

Ageing is characterised at the molecular level by six transcriptional 'hallmarks of ageing', that are commonly described as progressively affected as time passes. By contrast, the 'Smurf' assay separates high-and-constant-mortality risk individuals from healthy, zero-mortality risk individuals, based on increased intestinal permeability. Performing whole body total RNA sequencing, we found that Smurfness distinguishes transcriptional changes associated with chronological age from those associated with biological age. We show that transcriptional heterogeneity increases with chronological age in non-Smurf individuals preceding the other five hallmarks of ageing that are specifically associated with the Smurf state. Using this approach, we also devise targeted pro-longevity genetic interventions delaying entry in the Smurf state. We anticipate that increased attention to the evolutionary conserved Smurf phenotype will bring about significant advances in our understanding of the mechanisms of ageing.

Modeling early germline immunization after horizontal transfer of transposable elements reveals internal piRNA cluster heterogeneity.

BACKGROUND: A fraction of all genomes is composed of transposable elements (TEs) whose mobility needs to be carefully controlled. In gonads, TE activity is repressed by PIWI-interacting RNAs (piRNAs), a class of small RNAs synthesized by heterochromatic loci enriched in TE fragments, called piRNA clusters. Maintenance of active piRNA clusters across generations is secured by maternal piRNA inheritance providing the memory for TE repression. On rare occasions, genomes encounter horizontal transfer (HT) of new TEs with no piRNA targeting them, threatening the host genome integrity. Naïve genomes can eventually start to produce new piRNAs against these genomic invaders, but the timing of their emergence remains elusive. RESULTS: Using a set of TE-derived transgenes inserted in different germline piRNA clusters and functional assays, we have modeled a TE HT in Drosophila melanogaster. We have found that the complete co-option of these transgenes by a germline piRNA cluster can occur within four generations associated with the production of new piRNAs all along the transgenes and the germline silencing of piRNA sensors. Synthesis of new transgenic TE piRNAs is linked to piRNA cluster transcription dependent on Moonshiner and heterochromatin mark deposition that propagates more efficiently on short sequences. Moreover, we found that sequences located within piRNA clusters can have different piRNA profiles and can influence transcript accumulation of nearby sequences. CONCLUSIONS: Our study reveals that genetic and epigenetic properties, such as transcription, piRNA profiles, heterochromatin, and conversion efficiency along piRNA clusters, could be heterogeneous depending on the sequences that compose them. These findings suggest that the capacity of transcriptional signal erasure induced by the chromatin complex specific of the piRNA cluster can be incomplete through the piRNA cluster loci. Finally, these results have revealed an unexpected level of complexity that highlights a new magnitude of piRNA cluster plasticity fundamental for the maintenance of genome integrity.

The histone demethylase Kdm3 prevents auto-immune piRNAs production in Drosophila.

Genome integrity of the animal germline is protected from transposable element activity by PIWI-interacting RNAs (piRNAs). While piRNA biogenesis is intensively explored, little is known about the genetical determination of piRNA clusters, the genomic sources of piRNAs. Using a bimodal epigenetic state piRNA cluster (BX2), we identified the histone demethylase Kdm3 as being able to prevent a cryptic piRNA production. In the absence of Kdm3, dozens of coding gene-containing regions become genuine germline dual-strand piRNA clusters. Eggs laid by Kdm3 mutant females show developmental defects phenocopying loss of function of genes embedded into the additional piRNA clusters, suggesting an inheritance of functional ovarian "auto-immune" piRNAs. Antagonizing piRNA cluster determination through chromatin modifications appears crucial to prevent auto-immune genic piRNAs production.

The ribose methylation enzyme FTSJ1 has a conserved role in neuron morphology and learning performance.

FTSJ1 is a conserved human 2'-O-methyltransferase (Nm-MTase) that modifies several tRNAs at position 32 and the wobble position 34 in the anticodon loop. Its loss of function has been linked to X-linked intellectual disability (XLID), and more recently to cancers. However, the molecular mechanisms underlying these pathologies are currently unclear. Here, we report a novel FTSJ1 pathogenic variant from an X-linked intellectual disability patient. Using blood cells derived from this patient and other affected individuals carrying FTSJ1 mutations, we performed an unbiased and comprehensive RiboMethSeq analysis to map the ribose methylation on all human tRNAs and identify novel targets. In addition, we performed a transcriptome analysis in these cells and found that several genes previously associated with intellectual disability and cancers were deregulated. We also found changes in the miRNA population that suggest potential cross-regulation of some miRNAs with these key mRNA targets. Finally, we show that differentiation of FTSJ1-depleted human neural progenitor cells into neurons displays long and thin spine neurites compared with control cells. These defects are also observed in Drosophila and are associated with long-term memory deficits. Altogether, our study adds insight into FTSJ1 pathologies in humans and flies by the identification of novel FTSJ1 targets and the defect in neuron morphology.

Gene regulatory network inference methodology for genomic and transcriptomic data acquired in genetically related heterozygote individuals.

MOTIVATION: Inferring gene regulatory networks in non-independent genetically related panels is a methodological challenge. This hampers evolutionary and biological studies using heterozygote individuals such as in wild sunflower populations or cultivated hybrids. RESULTS: First, we simulated 100 datasets of gene expressions and polymorphisms, displaying the same gene expression distributions, heterozygosities and heritabilities as in our dataset including 173 genes and 353 genotypes measured in sunflower hybrids. Secondly, we performed a meta-analysis based on six inference methods [least absolute shrinkage and selection operator (Lasso), Random Forests, Bayesian Networks, Markov Random Fields, Ordinary Least Square and fast inference of networks from directed regulation (Findr)] and selected the minimal density networks for better accuracy with 64 edges connecting 79 genes and 0.35 area under precision and recall (AUPR) score on average. We identified that triangles and mutual edges are prone to errors in the inferred networks. Applied on classical datasets without heterozygotes, our strategy produced a 0.65 AUPR score for one dataset of the DREAM5 Systems Genetics Challenge. Finally, we applied our method to an experimental dataset from sunflower hybrids. We successfully inferred a network composed of 105 genes connected by 106 putative regulations with a major connected component. AVAILABILITY AND IMPLEMENTATION: Our inference methodology dedicated to genomic and transcriptomic data is available at https://forgemia.inra.fr/sunrise/inference_methods. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Non-Coding RNA Journal Club: Highlights on Recent Papers-10.

We are delighted to share with you our seventh Journal Club and highlight some of the most interesting papers published recently [...].

tRNA Fragments Populations Analysis in Mutants Affecting tRNAs Processing and tRNA Methylation.

tRNA fragments (tRFs) are a class of small non-coding RNAs (sncRNAs) derived from tRNAs. tRFs are highly abundant in many cell types including stem cells and cancer cells, and are found in all domains of life. Beyond translation control, tRFs have several functions ranging from transposon silencing to cell proliferation control. However, the analysis of tRFs presents specific challenges and their biogenesis is not well understood. They are very heterogeneous and highly modified by numerous post-transcriptional modifications. Here we describe a bioinformatic pipeline (tRFs-Galaxy) to study tRFs populations and shed light onto tRNA fragments biogenesis in Drosophila melanogaster. Indeed, we used small RNAs Illumina sequencing datasets extracted from wild type and mutant ovaries affecting two different highly conserved steps of tRNA biogenesis: 5'pre-tRNA processing (RNase-P subunit Rpp30) and tRNA 2'-O-methylation (dTrm7_34 and dTrm7_32). Using our pipeline, we show how defects in tRNA biogenesis affect nuclear and mitochondrial tRFs populations and other small non-coding RNAs biogenesis, such as small nucleolar RNAs (snoRNAs). This tRF analysis workflow will advance the current understanding of tRFs biogenesis, which is crucial to better comprehend tRFs roles and their implication in human pathology.

tRNA 2'-O-methylation by a duo of TRM7/FTSJ1 proteins modulates small RNA silencing in Drosophila.

2'-O-Methylation (Nm) represents one of the most common RNA modifications. Nm affects RNA structure and function with crucial roles in various RNA-mediated processes ranging from RNA silencing, translation, self versus non-self recognition to viral defense mechanisms. Here, we identify two Nm methyltransferases (Nm-MTases) in Drosophila melanogaster (CG7009 and CG5220) as functional orthologs of yeast TRM7 and human FTSJ1. Genetic knockout studies together with MALDI-TOF mass spectrometry and RiboMethSeq mapping revealed that CG7009 is responsible for methylating the wobble position in tRNAPhe, tRNATrp and tRNALeu, while CG5220 methylates position C32 in the same tRNAs and also targets additional tRNAs. CG7009 or CG5220 mutant animals were viable and fertile but exhibited various phenotypes such as lifespan reduction, small RNA pathways dysfunction and increased sensitivity to RNA virus infections. Our results provide the first detailed characterization of two TRM7 family members in Drosophila and uncover a molecular link between enzymes catalyzing Nm at specific tRNAs and small RNA-induced gene silencing pathways.

Environmentally-Induced Transgenerational Epigenetic Inheritance: Implication of PIWI Interacting RNAs.

Environmentally-induced transgenerational epigenetic inheritance is an emerging field. The understanding of associated epigenetic mechanisms is currently in progress with open questions still remaining. In this review, we present an overview of the knowledge of environmentally-induced transgenerational inheritance and associated epigenetic mechanisms, mainly in animals. The second part focuses on the role of PIWI-interacting RNAs (piRNAs), a class of small RNAs involved in the maintenance of the germline genome, in epigenetic memory to put into perspective cases of environmentally-induced transgenerational inheritance involving piRNA production. Finally, the last part addresses how genomes are facing production of new piRNAs, and from a broader perspective, how this process might have consequences on evolution and on sporadic disease development.

RNA 2'-O-Methylation (Nm) Modification in Human Diseases.

Nm (2'-O-methylation) is one of the most common modifications in the RNA world. It has the potential to influence the RNA molecules in multiple ways, such as structure, stability, and interactions, and to play a role in various cellular processes from epigenetic gene regulation, through translation to self versus non-self recognition. Yet, building scientific knowledge on the Nm matter has been hampered for a long time by the challenges in detecting and mapping this modification. Today, with the latest advancements in the area, more and more Nm sites are discovered on RNAs (tRNA, rRNA, mRNA, and small non-coding RNA) and linked to normal or pathological conditions. This review aims to synthesize the Nm-associated human diseases known to date and to tackle potential indirect links to some other biological defects.

Dual-layer transposon repression in heads of Drosophila melanogaster.

piRNA-mediated repression of transposable elements (TE) in the germline limits the accumulation of mutations caused by their transposition. It is not clear whether the piRNA pathway plays a role in adult, nongonadal tissues in Drosophila melanogaster. To address this question, we analyzed the small RNA content of adult Drosophila melanogaster heads. We found that the varying amount of piRNA-sized, ping-pong positive molecules in heads correlates with contamination by gonadal tissue during RNA extraction, suggesting that most of the piRNAs detected in heads originate from gonads. We next sequenced the heads of wild-type and piwi mutants to address whether piwi loss of function would affect the low amount of piRNA-sized, ping-pong negative molecules that are still detected in heads hand-checked to avoid gonadal contamination. We find that loss of piwi does not significantly affect these 24-28 nt RNAs. Instead, we observe increased siRNA levels against the majority of Drosophila TE families. To determine the effect of this siRNA level change on transposon expression, we sequenced the transcriptome of wild-type, piwi, dicer-2 and piwi, dicer-2 double-mutant heads. We find that RNA expression levels of the majority of TE in piwi or dicer-2 mutants remain unchanged and that TE transcripts increase only in piwi, dicer-2 double-mutants. These results lead us to suggest a dual-layer model for TE repression in adult somatic tissues. Piwi-mediated gene silencing established during embryogenesis constitutes the first layer of TE repression whereas Dicer-2-dependent siRNA-mediated silencing provides a backup mechanism to repress TEs that escape silencing by Piwi.

The Emerging Field of Epitranscriptomics in Neurodevelopmental and Neuronal Disorders.

Analogous to DNA methylation and histone modifications, RNA modifications represent a novel layer of regulation of gene expression. The dynamic nature and increasing number of RNA modifications offer new possibilities to rapidly alter gene expression upon specific environmental changes. Recent lines of evidence indicate that modified RNA molecules and associated complexes regulating and "reading" RNA modifications play key roles in the nervous system of several organisms, controlling both, its development and function. Mutations in several human genes that modify transfer RNA (tRNA) have been linked to neurological disorders, in particular to intellectual disability. Loss of RNA modifications alters the stability of tRNA, resulting in reduced translation efficiency and generation of tRNA fragments, which can interfere with neuronal functions. Modifications present on messenger RNAs (mRNAs) also play important roles during brain development. They contribute to neuronal growth and regeneration as well as to the local regulation of synaptic functions. Hence, potential combinatorial effects of RNA modifications on different classes of RNA may represent a novel code to dynamically fine tune gene expression during brain function. Here we discuss the recent findings demonstrating the impact of modified RNAs on neuronal processes and disorders.

Positioning Europe for the EPITRANSCRIPTOMICS challenge.

The genetic alphabet consists of the four letters: C, A, G, and T in DNA and C,A,G, and U in RNA. Triplets of these four letters jointly encode 20 different amino acids out of which proteins of all organisms are built. This system is universal and is found in all kingdoms of life. However, bases in DNA and RNA can be chemically modified. In DNA, around 10 different modifications are known, and those have been studied intensively over the past 20 years. Scientific studies on DNA modifications and proteins that recognize them gave rise to the large field of epigenetic and epigenomic research. The outcome of this intense research field is the discovery that development, ageing, and stem-cell dependent regeneration but also several diseases including cancer are largely controlled by the epigenetic state of cells. Consequently, this research has already led to the first FDA approved drugs that exploit the gained knowledge to combat disease. In recent years, the ~150 modifications found in RNA have come to the focus of intense research. Here we provide a perspective on necessary and expected developments in the fast expanding area of RNA modifications, termed epitranscriptomics.

Mutations in Cytosine-5 tRNA Methyltransferases Impact Mobile Element Expression and Genome Stability at Specific DNA Repeats.

The maintenance of eukaryotic genome stability is ensured by the interplay of transcriptional as well as post-transcriptional mechanisms that control recombination of repeat regions and the expression and mobility of transposable elements. We report here that mutations in two (cytosine-5) RNA methyltransferases, Dnmt2 and NSun2, impact the accumulation of mobile element-derived sequences and DNA repeat integrity in Drosophila. Loss of Dnmt2 function caused moderate effects under standard conditions, while heat shock exacerbated these effects. In contrast, NSun2 function affected mobile element expression and genome integrity in a heat shock-independent fashion. Reduced tRNA stability in both RCMT mutants indicated that tRNA-dependent processes affected mobile element expression and DNA repeat stability. Importantly, further experiments indicated that complex formation with RNA could also contribute to the impact of RCMT function on gene expression control. These results thus uncover a link between tRNA modification enzymes, the expression of repeat DNA, and genomic integrity.

Reverse engineering highlights potential principles of large gene regulatory network design and learning.

Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 104 genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data (Escherichia coli K14 network reconstruction using network and transcriptomic data), we show that the formalism used to build FRANK can to some extent be a reasonable model for gene regulatory networks in real cells.

Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the Arabidopsis thaliana root.

Plants form the basis of the food webs that sustain animal life. Exogenous factors, such as nutrients and sunlight, and endogenous factors, such as hormones, cooperate to control both the growth and the development of plants. We assessed how Arabidopsis thaliana integrated nutrient and hormone signaling pathways to control root growth and development by investigating the effects of combinatorial treatment with the nutrients nitrate and ammonium; the hormones auxin, cytokinin, and abscisic acid; and all binary combinations of these factors. We monitored and integrated short-term genome-wide changes in gene expression over hours and long-term effects on root development and architecture over several days. Our analysis revealed trends in nutrient and hormonal signal crosstalk and feedback, including responses that exhibited logic gate behavior, which means that they were triggered only when specific combinations of signals were present. From the data, we developed a multivariate network model comprising the signaling molecules, the early gene expression modulation, and the subsequent changes in root phenotypes. This multivariate network model pinpoints several genes that play key roles in the control of root development and may help understand how eukaryotes manage multifactorial signaling inputs.

Isolation of small interfering RNAs using viral suppressors of RNA interference.

The tombusvirus P19 VSR (viral suppressor of RNA interference) binds siRNAs with high affinity, whereas the Flockhouse Virus (FHV) B2 VSR binds both long double-stranded RNA (dsRNA) and small interfering RNAs (siRNAs). Both VSRs are small proteins and function in plant and animal cells. Fusing a Nuclear Localization Signal (NLS) to the N-terminus shifts the localization of the VSR from cytoplasmic to nuclear, allowing researchers to specifically probe the subcellular distribution of siRNAs, and to investigate the function of nuclear and cytoplasmic siRNAs. This chapter provides a detailed protocol for the immunoprecipitation of siRNAs bound to epitope-tagged VSR and subsequent analysis by 3'-end-labeling using cytidine-3',5'-bis phosphate ([5'-(32)P]pCp) and northern blotting.