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Jonoska, N.

Publications and source records attributed to Jonoska, N..

6 recordsLinked to original sources

Human ribomes reveal DNA-embedded ribonucleotides as a new type of epigenetic mark

Ribonucleoside monophosphates (rNMPs) are abundant in DNA, but their distribution and function in human nuclear genomes remain unknown. Here, we mapped nearly one million rNMPs per genome across diverse human cell types, defining a nuclear "ribome" with non-random distribution patterns. rNMPs are enriched in C/G-rich sequences, epigenetically marked regions, and telomeres. Conserved ribonucleotide-enriched zones (REZs) overlap with CpG islands and R-loops. rNMP concentration near transcription start sites (TSSs) correlates positively with gene expression. Wild-type cells display a broader gene-expression range than ribonuclease H2A (RNH2A) knockouts, in which loss of rNMP cleavage causes pronounced retention of embedded rG and strand-biased rC near TSSs, both increasing with gene expression. These findings establish DNA-embedded rNMPs as a novel epigenetic mark that modulates human gene expression.

molecular biology↗

The R-loop Grammar predicts R-loop formation under different topological constraints

R-loops are transient three-stranded nucleic acids that form during transcription when the nascent RNA hybridizes with the template DNA, freeing the DNA non-template strand. There is growing evidence that R-loops play important roles in physiological processes such as control of gene expression, and that they contribute to chromosomal instability and disease. It is known that R-loop formation is influenced by both the sequence and the topology of the DNA substrate, but many questions remain about how R-loops form and the 3-dimensional structures that they adopt. Here we represent an R-loop as a word in a formal grammar called the R-loop grammar and predict R-loop formation. We train the R-loop grammar on experimental data obtained by single-molecule R-loop footprinting and sequencing (SMRF-seq). Despite not containing explicit topological information, the R-loop grammar accurately predicts R-loop formation on plasmids with varying starting topologies and outperforms previous methods in R-loop prediction. Author summaryR-loops are prevalent triple helices that play regulatory roles in gene expression and are involved in various diseases. Our work improves the understanding of the relationship between the nucleotide sequence and DNA topology in R-loop formation. We use a mathematical approach from formal language theory to define an R-loop language and a set of rules to model R-loops as words in that language. We train the resulting R-loop grammar on experimental data of co-transcriptional R-loops formed on different DNA plasmids of varying topology. The model accurately predicts R-loop formation and outperforms prior methods. The R-loop grammar distills the effect of topology versus sequence, thus advancing our understanding of R-loop structure and formation.

genomics↗

Analyzing the link between RNA secondary structures and R-loop formation with tree polynomials

R-loops are a class of non-canonical nucleic acid structures that typically form during transcription when the nascent RNA hybridizes the DNA template strand, leaving the DNA coding strand unpaired. Co-transcriptional R-loops are abundant in nature and biologically relevant. Recent research shows that DNA sequence and topology affect R-loops, yet it remains unclear how these and other factors drive R-loop formation. In this work, we investigate a link between the secondary structure of the nascent RNA and the probability of R-loop formation. We introduce tree-polynomial representations, a class of mathematical objects that enable accurate and efficient data analysis of RNA secondary structures. With tree-polynomials, we establish a strong correlation between the secondary structure of the RNA transcript and the probability of R-loop formation. We identify that branches with short stems separated by multiple bubbles in the RNA secondary structure are associated with the strong correlation and are predictive of R-loop formation.

molecular biology↗

RNA-mediated double-strand break repair in human cells

Double-strand breaks (DSBs) in DNA are challenging lesions to repair. Human cells employ at least three DSB repair mechanisms, with a preference for non-homologous end joining (NHEJ) over homologous recombination (HR) and microhomology-mediated end joining (MMEJ)1,2. In contrast to HR, NHEJ and MMEJ do not utilize a DNA template molecule to recover damaged and/or lost nucleotides2. NHEJ directly ligates broken DNA ends, while MMEJ exploits the alignment of short microhomologies on the DSB sides and is associated with deletions of the sequence between the microhomologies3,4. It is unknown whether and to what extent a transcript RNA has a direct role in DSB-repair mechanisms in mammalian cells. Here, we show that both coding and non-coding transcript RNA facilitates DSB repair in a sequence-specific manner in human cells. Depending on its sequence complementarity with the broken DNA ends, the transcript RNA could promote the repair of a DSB or gap in its DNA gene via NHEJ or MMEJ, or mediate RNA-templated repair. The transcript RNA influences DSB repair by NHEJ and MMEJ even when the transcription level is low. The results demonstrate an unexpected role of transcript RNA in directing the way DSBs are repaired in human cells and maintaining genome stability.

molecular biology↗

SDRAP for annotating scrambled or rearranged genomes

DNA rearrangements are important in various contexts, such as in vertebrate immunity, and cancer genome instability. The single-celled eukaryote Oxytricha trifallax undergoes massive and reproducible genome rearrangement during post-zygotic development, making it a compelling model organism to study DNA rearrangements. To date, computational tools for the extraction and analysis of rearrangement annotations lack transparency and rely on assumptions that may not hold for all analyzed data, leading to irreproducibility of results and loss of information through data filtering or misrepresentation. An implementation of a procedure for the annotation and analysis of DNA rearrangement as a web application is discussed and tested. The resulting annotations provide an improvement over previous annotations in the following manner. (a) SDRAP achieves more complete precursor-product mappings than previous software (b) the software allows for full transparency of all parameters used during the annotation and therefore facilitates reproducible results, and (c) this parameter transparency makes SDRAP suitable for comparison of genomic data from different sources, including cancer genomes. This work introduces a theoretical framework and software to systematically extract and analyze annotations from pairs of genome assemblies corresponding to precursor and product rearrangement data. The software makes no assumptions about the structure of the rearrangements, and permits the user to select parameters to suit the data.

bioinformatics↗

Russian Doll Genes and Complex Chromosome Rearrangements in Oytricha trifallax

Ciliates have two different types of nuclei per cell, with one acting as a somatic, transcriptionally active nucleus (macronucleus; abbr. MAC) and another serving as a germline nucleus (micronucleus; abbr. MIC). Furthermore, Oxytricha trifallax undergoes extensive genome rearrangements during sexual conjugation and post-zygotic development of daughter cells. These rearrangements are necessary because the precursor MIC loci are often both fragmented and scrambled, with respect to the corresponding MAC loci. Such genome architectures are remarkably tolerant of encrypted MIC loci, because RNA-guided processes during MAC development reorganize the gene fragments in the correct order to resemble the parental MAC sequence. Here, we describe the germline organization of several nested and highly scrambled genes in Oxytricha trifallax. These include cases with multiple layers of nesting, plus highly interleaved or tangled precursor loci that appear to deviate from previously described patterns. We present mathematical methods to measure the degree of nesting between precursor MIC loci, and revisit a method for a mathematical description of scrambling. After applying these methods to the chromosome rearrangement maps of O. trifallax we describe cases of nested arrangements with up to five layers of embedded genes, as well as the most scrambled loci in O. trifallax.

genomics↗