We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available.

Heterozygous carriers of germ-line loss-of-function variants in the DNA repair gene PALB2 are at a highly increased lifetime risk for developing breast cancer. While truncating variants in PALB2 are known to increase cancer risk, the interpretation of missense variants of uncertain significance (VUS) is in its infancy. Here we describe the development of a relatively fast and easy cDNA-based system for the semi high-throughput functional analysis of 48 VUS in human PALB2. By assessing the ability of PALB2 VUS to rescue the DNA repair and checkpoint defects in Palb2 knockout mouse embryonic stem (mES) cells, we identify various VUS in PALB2 that impair its function. Three VUS in the coiled-coil domain of PALB2 abrogate the interaction with BRCA1, whereas several VUS in the WD40 domain dramatically reduce protein stability. Thus, our functional assays identify damaging VUS in PALB2 that may increase cancer risk.

Chromatin conformation analyses provide novel insights into how variable segments in the immunoglobulin light chain gene become accessible for recombination in precursor B lymphocytes.