txtools: an R package facilitating analysis of RNA modifications, structures, and interactions.

We present txtools, an R package that enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with transcriptomic representation. txtools' main inputs are BAM files and a transcriptome annotation, and the main output is a table, capturing mismatches, deletions, and the number of reads beginning and ending at each nucleotide in the transcriptomic space. txtools further facilitates downstream visualization and analyses. We showcase, using examples from the epitranscriptomic field, how a few calls to txtools functions can yield insightful and ready-to-publish results. txtools is of broad utility also in the context of structural mapping and RNA:protein interaction mapping. By providing a simple and intuitive framework, we believe that txtools will be a useful and convenient tool and pave the path for future discovery. txtools is available for installation from its GitHub repository at https://github.com/AngelCampos/txtools.

Dissecting the sequence and structural determinants guiding m6A deposition and evolution via inter- and intra-species hybrids.

BACKGROUND: N6-methyladenosine (m6A) is the most abundant mRNA modification, and controls mRNA stability. m6A distribution varies considerably between and within species. Yet, it is unclear to what extent this variability is driven by changes in genetic sequences ('cis') or cellular environments ('trans') and via which mechanisms. RESULTS: Here we dissect the determinants governing RNA methylation via interspecies and intraspecies hybrids in yeast and mammalian systems, coupled with massively parallel reporter assays and m6A-QTL reanalysis. We find that m6A evolution and variability is driven primarily in 'cis', via two mechanisms: (1) variations altering m6A consensus motifs, and (2) variation impacting mRNA secondary structure. We establish that mutations impacting RNA structure - even when distant from an m6A consensus motif - causally dictate methylation propensity. Finally, we demonstrate that allele-specific differences in m6A levels lead to allele-specific changes in gene expression. CONCLUSIONS: Our findings define the determinants governing m6A evolution and diversity and characterize the consequences thereof on gene expression regulation.

Multiplexed profiling facilitates robust m6A quantification at site, gene and sample resolution.

N6-methyladenosine (m6A) is the most prevalent modification of messenger RNA in mammals. To interrogate its functions and dynamics, there is a critical need to quantify m6A at three levels: site, gene and sample. Current approaches address these needs in a limited manner. Here we develop m6A-seq2, relying on multiplexed m6A-immunoprecipitation of barcoded and pooled samples. m6A-seq2 allows a big increase in throughput while reducing technical variability, requirements of input material and cost. m6A-seq2 is furthermore uniquely capable of providing sample-level relative quantitations of m6A, serving as an orthogonal alternative to mass spectrometry-based approaches. Finally, we develop a computational approach for gene-level quantitation of m6A. We demonstrate that using this metric, roughly 30% of the variability in RNA half life in mouse embryonic stem cells can be explained, establishing m6A as a main driver of RNA stability. m6A-seq2 thus provides an experimental and analytic framework for dissecting m6A-mediated regulation at three different levels.

Tolerance to Oxidative Stress in Budding Yeast by Heterologous Expression of Catalases A and T from Debaryomyces hansenii.

The function of catalases A and T from the budding yeast Saccharomyces cerevisiae (ScCta1 and ScCtt1) is to decompose hydrogen peroxide (H2O2) to mitigate oxidative stress. Catalase orthologs are widely found in yeast, suggesting that scavenging H2O2 is crucial to avoid the oxidative damage caused by reactive oxygen species (ROS). However, the function of catalase orthologs has not yet been experimentally characterized in vivo. Here, we heterologously expressed Debaryomyces hansenii DhCTA1 and DhCTT1 genes, encoding ScCta1 and ScCtt1 orthologs, respectively, in a S. cerevisiae acatalasemic strain (cta1Δ ctt1Δ). We performed a physiological analysis evaluating growth, catalase activity, and H2O2 tolerance of the strains grown with glucose or ethanol as carbon source, as well as under NaCl stress. We found that both genes complement the catalase function in S. cerevisiae. Particularly, the strain harboring DhCTT1 showed improved growth when ethanol was used as carbon source both in the absence or presence of salt stress. This phenotype is attributed to the high catalase activity of DhCtt1 detected at the exponential growth phase, which prevents intracellular ROS accumulation and confers oxidative stress resistance.

Deciphering the "m6A Code" via Antibody-Independent Quantitative Profiling.

N6-methyladenosine (m6A) is the most abundant modification on mRNA and is implicated in critical roles in development, physiology, and disease. A major limitation has been the inability to quantify m6A stoichiometry and the lack of antibody-independent methodologies for interrogating m6A. Here, we develop MAZTER-seq for systematic quantitative profiling of m6A at single-nucleotide resolution at 16%-25% of expressed sites, building on differential cleavage by an RNase. MAZTER-seq permits validation and de novo discovery of m6A sites, calibration of the performance of antibody-based approaches, and quantitative tracking of m6A dynamics in yeast gametogenesis and mammalian differentiation. We discover that m6A stoichiometry is "hard coded" in cis via a simple and predictable code, accounting for 33%-46% of the variability in methylation levels and allowing accurate prediction of m6A loss and acquisition events across evolution. MAZTER-seq allows quantitative investigation of m6A regulation in subcellular fractions, diverse cell types, and disease states.