Towards parsimonious generative modeling of RNA families.

Generative probabilistic models emerge as a new paradigm in data-driven, evolution-informed design of biomolecular sequences. This paper introduces a novel approach, called Edge Activation Direct Coupling Analysis (eaDCA), tailored to the characteristics of RNA sequences, with a strong emphasis on simplicity, efficiency, and interpretability. eaDCA explicitly constructs sparse coevolutionary models for RNA families, achieving performance levels comparable to more complex methods while utilizing a significantly lower number of parameters. Our approach demonstrates efficiency in generating artificial RNA sequences that closely resemble their natural counterparts in both statistical analyses and SHAPE-MaP experiments, and in predicting the effect of mutations. Notably, eaDCA provides a unique feature: estimating the number of potential functional sequences within a given RNA family. For example, in the case of cyclic di-AMP riboswitches (RF00379), our analysis suggests the existence of approximately 1039 functional nucleotide sequences. While huge compared to the known <4000 natural sequences, this number represents only a tiny fraction of the vast pool of nearly 1082 possible nucleotide sequences of the same length (136 nucleotides). These results underscore the promise of sparse and interpretable generative models, such as eaDCA, in enhancing our understanding of the expansive RNA sequence space.

Comparative histological analysis of spleens in pediatric patients with hemolytic anemias: Insights into the pathophysiological mechanisms of spleen destruction in sickle cell anemia.

While sickle cell anemia (SCA) and hereditary spherocytosis (HS) share common features of increased spleen erythrophagocytosis due to increased red blood cell (RBC) turnover, SCA is specifically characterized by susceptibility to infections. In this study, histological lesions in the spleens of pediatric patients with SCA were analyzed, in close correlation with past clinical history and comparatively to HS, healthy and transfused ß-thalassemia patients (TDT). An evaluation of red pulp elementary lesions (red pulp fibrosis, iron deposition, number of Gandy-Gamna, and RBC trapping) combined into a severity score was established, as well as B-cell follicles analysis. Quantification on digitalized slides of iron deposition, RBC trapping, and red pulp fibrosis was additionally performed. Spleens from 22 children with SCA, eight with HS, eight with TDT, and three healthy controls (HC) were analyzed. Median age at splenectomy was not different between SCA and HS patients, 6.05 years (range: 4.5-16.0) versus 4.75 (range: 2.2-9.5). Marked heterogeneity was found in SCA spleens in contrast to other conditions. Contrary to previous reports, B-cell follicles were generally preserved in SCA. While RBC trapping was significantly increased in both SCA and HS (compared to TDT and HC), quantitative fibrosis and overall red pulp severity score were significantly increased in SCA spleens compared to other conditions. Moreover, there was an inverse correlation between quantitative fibrosis and number of B-cell follicles, linking these two compartments as well as spleen fibrosis to infectious susceptibility in SCA, potentially through impaired red pulp macrophage scavenging and B-cell subpopulations defects.

Abiogenesis through gradual evolution of autocatalysis into template-based replication.

How life emerged from inanimate matter is one of the most intriguing questions posed to modern science. Central to this research are experimental attempts to build systems capable of Darwinian evolution. RNA catalysts (ribozymes) are a promising avenue, in line with the RNA world hypothesis whereby RNA pre-dated DNA and proteins. Since evolution in living organisms relies on template-based replication, the identification of a ribozyme capable of replicating itself (an RNA self-replicase) has been a major objective. However, no self-replicase has been identified to date. Alternatively, autocatalytic systems involving multiple RNA species capable of ligation and recombination may enable self-reproduction. However, it remains unclear how evolution could emerge in autocatalytic systems. In this review, we examine how experimentally feasible RNA reactions catalysed by ribozymes could implement the evolutionary properties of variation, heredity and reproduction, and ultimately allow for Darwinian evolution. We propose a gradual path for the emergence of evolution, initially supported by autocatalytic systems leading to the later appearance of RNA replicases.

Systematic benchmarking of single-cell ATAC-sequencing protocols.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

RNA diversification by a self-reproducing ribozyme revealed by deep sequencing and kinetic modelling.

We demonstrate that a recombinase ribozyme achieves multiple functions in the same reaction network: self-reproduction, iterative elongation and circularization of other RNAs, leading to synthesis of diverse products predicted by a kinetic model. This shows that key mechanisms can be integrated and controlled toward Darwinian evolution in RNA reaction networks.