Statesmanship Without a State: The Life and Legacy of Chaim Weizmann

The Carl and Dorothy Bennett Lecture in Judaic Studies delivered by Dr. Jehuda Reinharz, President of Brandeis University.https://digitalcommons.fairfield.edu/bennettcenter-posters/1197/thumbnail.jp

Automatic Exploration of the Natural Variability of RNA Non-Canonical Geometric Patterns with a Parameterized Sampling Technique

Motivation. Recurrent substructures in RNA, known as 3D motifs, consist of networks of base pair interactions and are critical to understanding the relationship between structure and function. Their structure is naturally expressed as a graph which has led to many graph-based algorithms to automatically catalog identical motifs found in 3D structures. Yet, due to the complexity of the problem, state-of-the-art methods are often optimized to find exact matches, limiting the search to a subset of potential solutions, or do not allow explicit control over the desired variability. Results. We developed FuzzTree, a method able to efficiently sample approximate instances of an RNA motif, abstracted as a subgraph within a target RNA structure. It is the first method that allows explicit control over (1) the admissible geometric variability in the interactions; (2) the number of missing edges; and (3) the introduction of discontinuities in the backbone given close distances in the 3D structure. Our tool relies on a multidimensional Boltzmann sampling, having complexity parameterized by the treewidth of the requested motif. We applied our method to the well-known internal loop Kink-Turn motif, which can be divided into 12 subgroups. Given only the graph representing the main Kink-Turn subgroup, FuzzTree retrieved over 3/4 of all kink-turns. We also highlighted two occurrences of new sampled patterns. Our tool is available as free software and can be customized for different parameters and types of graphs

Combining structure probing data on RNA mutants with evolutionary information reveals RNA-binding interfaces

International audienceSystematic structure probing experiments (e.g. SHAPE) of RNA mutants such as the mutate-and-map protocol give us a direct access into the genetic robustness of ncRNA structures. Comparative studies of homologous sequences provide a distinct, yet complementary, approach to analyze structural and functional properties of non-coding RNAs. In this paper, we introduce a formal framework to combine the biochemical signal collected from mutate-and-map experiments, with the evolutionary information available in multiple sequence alignments. We apply neutral theory principles to detect complex long-range dependencies between nucleotides of a single stranded RNA, and implement these ideas into a software called aRNhAck. We illustrate the biological significance of this signal and show that the nucleotides networks calculated with aRNhAck are correlated with nucleotides located in RNA-RNA, RNA-protein, RNA-DNA and RNA-ligand interfaces. aRNhAck is freely available at http://csb.cs.mcgill.ca/arnhack

Using Structural and Evolutionary Information to Detect and Correct Pyrosequencing Errors in Noncoding RNAs.

Extended version of RECOMB'13International audienceThe analysis of the sequence-structure relationship in RNA molecules is not only essential for evolutionary studies but also for concrete applications such as error-correction in next generation sequencing (NGS) technologies. The prohibitive sizes of the mutational and conformational landscapes, combined with the volume of data to process, require efficient algorithms to compute sequence-structure properties. In this article, we address the correction of NGS errors by calculating which mutations most increase the likelihood of a sequence to a given structure and RNA family. We introduce RNApyro, an efficient, linear time and space inside-outside algorithm that computes exact mutational probabilities under secondary structure and evolutionary constraints given as a multiple sequence alignment with a consensus structure. We develop a scoring scheme combining classical stacking base-pair energies to novel isostericity scores and apply our techniques to correct pointwise errors in 5s and 16s rRNA sequences. Our results suggest that RNApyro is a promising algorithm to complement existing tools in the NGS error-correction pipeline

A linear inside-outside algorithm for correcting sequencing errors in structured RNA sequences

International audienceAnalysis of the sequence-structure relationship in RNA molecules are essential to evolutionary studies but also to concrete applications such as error-correction methodologies in sequencing technologies. The prohibitive sizes of the mutational and conformational landscapes combined with the volume of data to proceed require e cient algorithms to compute sequence-structure properties. More speci cally, here we aim to calculate which mutations increase the most the likelihood of a sequence to a given structure and RNA family. In this paper, we introduce RNApyro, an e cient linear-time and space inside-outside algorithm that computes exact mutational probabilities under secondary structure and evolutionary constraints given as a multiple sequence alignment with a consensus structure. We develop a scoring scheme combining classical stacking base pair energies to novel isostericity scales, and apply our techniques to correct point-wise errors in 5s rRNA sequences. Our results suggest that RNApyro is a promising algorithm to complement existing tools in the NGS error-correction pipeline