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Prediction categories in the Critical Assessment of Structure Prediction (CASP) experiments change with the need to address specific problems in structure modeling. In CASP15, four new prediction categories were introduced: RNA structure, ligand-protein complexes, accuracy of oligomeric structures and their interfaces, and ensembles of alternative conformations. This paper lists technical specifications for these categories and describes their integration in the CASP data management system.

The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report double-blind assessments of RNA structure predictions in CASP15, the first CASP exercise in which RNA modeling was assessed. Forty two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, who did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and X-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global topology of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as non-canonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.

RNA three-dimensional structures provide rich and vital information for understanding their functions. Recent advances in cryogenic electron microscopy (cryo-EM) allow structure determination of RNAs and ribonucleoprotein (RNP) complexes. However, limited global and local resolutions of RNA cryo-EM maps pose great challenges in tracing RNA coordinates. The Rosetta-based "auto-DRRAFTER" method builds RNA models into moderate-resolution RNA cryo-EM density as part of the Ribosolve pipeline. Here, we describe a step-by-step protocol for auto-DRRAFTER using a glycine riboswitch from Fusobacterium nucleatum as an example. Successful implementation of this protocol allows automated RNA modeling into RNA cryo-EM density, accelerating our understanding of RNA structure-function relationships. Input and output files are being made available at https://github.com/auto-DRRAFTER/springer-chapter .

Pre-mRNA secondary structure is hypothesized to play widespread roles in regulating splicing of eukaryotic introns, but direct detection of such structure in vivo has been challenging. Here, we characterize S. cerevisiae pre-mRNA secondary structures through transcriptome-wide dimethyl sulfate (DMS) probing experiments, enriching for low-abundance pre-mRNA through splicing inhibition. These data enable evaluation of structures predicted in phylogenetic and mutational studies. The data further reveal the widespread formation of zipper stems between the 5’ splice site and branch point, ‘downstream stems’ between the branch point and the 3’ splice site, and previously uncharacterized long stems that distinguish pre-mRNA from spliced mRNA. Structure ensemble prediction for introns across the Saccharomyces genus suggests that these structural patterns appear in all these yeast species. Together, these findings represent the first transcriptome-wide mapping of intron RNA structures and suggest new ideas and model systems for understanding how pre-mRNA folding promotes splicing efficiency and regulation of gene expression.

Background: Aging is considered the most important risk factor for Alzheimer’s disease (AD). Recent research supports the theory that immunotherapy targeting the “oligomeric” forms of amyloid-β (Aβ) may halt the progression of AD. However, previous clinical trial of the vaccine against Aβ, called AN1792, was suspended due to cases of meningoencephalitis in patients. Objective: To develop a peptide sensitized dendritic cells (DCs) vaccine that would target oligomer Aβ and prevent an autoimmune response. Methods: Double transgenic APPswe/PS1ΔE9 (Tg) and C57BL/6J control mice were used in this study. Cytokine expression profile detection, characterization of antisera, brain GSK-3β, LC3 expression, and spatial working memory testing before and post-vaccination were obtained. Results: Epitope prediction indicated that E22W42 could generate 13 new T cell epitopes which can strengthen immunity in aged subjects and silence several T cell epitopes of the wild type Aβ. The silenced T cell epitope could help avoid the autoimmune response that was seen in some patients of the AN-1792 vaccine. The E22W42 not only helped sensitize bone marrow-derived DCs for the development of an oligomeric Aβ-specific antibody, but also delayed memory impairment in the APP/PS1 mouse model. Most importantly, this E22W42 peptide will not alter the DC’s natural immunomodulatory properties. Conclusion: The E22W42 vaccine is possibly safer for patients with impaired immune systems. Since there is increasing evidence that oligomeric form of Aβ are the toxic species to neurons, the E22W42 antibody’s specificity for these “oligomeric” Aβ species could provide the opportunity to produce some clinical benefits in AD subjects.

SUMMARY Despite the well-accepted view that chronic inflammation contributes to the pathogenesis of Duchenne muscular dystrophy (DMD), the function and regulation of eosinophils remain an unclear facet of type II innate immunity in dystrophic muscle. We report the observation that group 2 innate lymphoid cells (ILC2s) are present in skeletal muscle and are the principal regulators of muscle eosinophils during muscular dystrophy. Eosinophils were elevated in DMD patients and dystrophic mice along with interleukin (IL)-5, a major eosinophil survival factor that was predominantly expressed by muscle ILC2s. We also find that IL-33 was upregulated in dystrophic muscle and was predominantly produced by fibrogenic/adipogenic progenitors (FAPs). Exogenous IL-33 and IL-2 complex (IL-2c) expanded muscle ILC2s and eosinophils, decreased the cross-sectional area (CSA) of regenerating myofibers, and increased the expression of genes associated with muscle fibrosis. The deletion of ILC2s in dystrophic mice mitigated muscle eosinophilia and impaired the induction of IL-5 and fibrosis-associated genes. Our findings highlight a FAP/ILC2/eosinophil axis that promotes type II innate immunity, which influences the balance between regenerative and fibrotic responses during muscular dystrophy., In brief Immune cells that comprise type II innate immunity coalesce to regulate tissue repair and fibrosis. Kastenschmidt et al. report that ILC2s reside in skeletal muscle, are activated in muscular dystrophy, and promote muscle eosinophilia. Stromal progenitors expressed IL-33, which expanded ILC2s and promoted a transcriptional program associated with muscle fibrosis., Graphical Abstract

Aging is considered the most important risk factor for Alzheimer's disease (AD). Recent research supports the theory that immunotherapy targeting the "oligomeric" forms of amyloid-β (Aβ) may halt the progression of AD. However, previous clinical trial of the vaccine against Aβ, called AN1792, was suspended due to cases of meningoencephalitis in patients.To develop a peptide sensitized dendritic cells (DCs) vaccine that would target oligomer Aβ and prevent an autoimmune response.Double transgenic APPswe/PS1ΔE9 (Tg) and C57BL/6J control mice were used in this study. Cytokine expression profile detection, characterization of antisera, brain GSK-3β, LC3 expression, and spatial working memory testing before and post-vaccination were obtained.Epitope prediction indicated that E22W42 could generate 13 new T cell epitopes which can strengthen immunity in aged subjects and silence several T cell epitopes of the wild type Aβ. The silenced T cell epitope could help avoid the autoimmune response that was seen in some patients of the AN-1792 vaccine. The E22W42 not only helped sensitize bone marrow-derived DCs for the development of an oligomeric Aβ-specific antibody, but also delayed memory impairment in the APP/PS1 mouse model. Most importantly, this E22W42 peptide will not alter the DC's natural immunomodulatory properties.The E22W42 vaccine is possibly safer for patients with impaired immune systems. Since there is increasing evidence that oligomeric form of Aβ are the toxic species to neurons, the E22W42 antibody's specificity for these "oligomeric" Aβ species could provide the opportunity to produce some clinical benefits in AD subjects.

Chronic muscle inflammation contributes to the pathogenesis of Duchenne muscular dystrophy (DMD), a lethal muscle disorder attributed to dystrophin gene mutations. However, the function and regulation of eosinophilia, an unappreciated facet of type II innate immunity in dystrophic muscle, remain poorly understood. Here, we report the novel observation that group 2 innate lymphoid cells (ILC2s) are present in skeletal muscle and are the principal regulators of muscle eosinophilia during muscular dystrophy. Eosinophils were elevated in DMD patients and dystrophic mice, along with the major eosinophil survival factor, interleukin-5 (IL-5). ILC2s were present in healthy skeletal muscle, were activated and expanded in number during muscular dystrophy in mice, and were the sole source of IL-5. Muscle ILC2s were expanded by IL-33, which was upregulated in dystrophic muscle and was predominantly produced by fibro/adipogenic progenitor cells (FAPs). Exogenous IL-33 also promoted muscle eosinophilia, which was further augmented by combined treatment with IL-2 complex (IL-2c). The deletion of ILC2s in dystrophic mice prevented eosinophilia and mitigated the IL-33/IL-2c-mediated increase of muscle eosinophils and IL-5 expression. Our findings establish that interactions between FAPs and ILC2s regulate type II innate immunity in dystrophic muscle and promote muscle eosinophilia during muscular dystrophy.

Rare genetic variants are the major cause of Mendelian disorders, yet only half of described genetic diseases have been causally linked to a gene. In addition, the total number of rare genetic diseases is projected to be far greater than that of those already described. Whole-genome sequencing of patients with subsequent genetic and functional analysis is a powerful way to describe these gene anomalies. However, this approach results in tens to hundreds of candidate disease-causative genes, and the identification of additional individuals suffering from the same disorder can be difficult because of rarity and phenotypic heterogeneity. We describe a genetic network–based method to rank candidate genes identified in family-based sequencing studies, termed phenotype informed network (PIN) ranking. Furthermore, we present a case study as an extension of the PIN ranking method in which disease symptoms drive the network ranking and identification of the disease-causative gene. We demonstrate, through simulation, that our method is capable of identifying the correct disease-causative gene in a majority of cases. PIN-rank is available at https://genomics.scripps.edu/pinrank/ . We have developed a method to prioritize candidate disease-causative genes based on symptoms that would be useful for both the prioritization of candidates and the identification of additional subjects. Genet Med 17 11, 859–865.

Recent studies have challenged the long-held belief that recognition is unfailingly degraded by contextual differences between study and test items. In these studies, recognition of pictures presented in silence was better when during study or initial exposure the images were accompanied by a semantically congruent sound rather than silence. In the present study, we sought to examine the generalization of this phenomenon to auditory recognition and found a significant improvement in the recognition of auditory items when coupled with a congruent picture. We discuss these findings within the framework of the redintegration hypothesis of memory retrieval as well as Bayesian inference and learning.

There is considerable debate about the most efficient way to interrogate rare coding variants in association studies. The options include direct genotyping of specific known coding variants in genes or, alternatively, sequencing across the entire exome to capture known as well as novel variants. Each strategy has advantages and disadvantages, but the availability of cost-efficient exome arrays has made the former appealing. Here we consider the utility of a direct genotyping chip, the Illumina HumanExome array (HE), by evaluating its content based on: 1. functionality; and 2. amenability to imputation. We explored these issues by genotyping a large, ethnically diverse cohort on the HumanOmniExpressExome array (HOEE) which combines the HE with content from the GWAS array (HOE). We find that the use of the HE is likely to be a cost-effective way of expanding GWAS, but does have some drawbacks that deserve consideration when planning studies. © 2014 Elsevier B.V.

There have been a number of recent successes in the use of whole genome sequencing and sophisticated bioinformatics techniques to identify pathogenic DNA sequence variants responsible for individual idiopathic congenital conditions. However, the success of this identification process is heavily influenced by the ancestry or genetic background of a patient with an idiopathic condition. This is so because potential pathogenic variants in a patient's genome must be contrasted with variants in a reference set of genomes made up of other individuals' genomes of the same ancestry as the patient. We explored the effect of ignoring the ancestries of both an individual patient and the individuals used to construct reference genomes. We pursued this exploration in two major steps. We first considered variation in the per-genome number and rates of likely functional derived (i.e., non-ancestral, based on the chimp genome) single nucleotide variants and small indels in 52 individual whole human genomes sampled from 10 different global populations. We took advantage of a suite of computational and bioinformatics techniques to predict the functional effect of over 24 million genomic variants, both coding and non-coding, across these genomes. We found that the typical human genome harbors ∼5.5-6.1 million total derived variants, of which ∼12,000 are likely to have a functional effect (∼5000 coding and ∼7000 non-coding). We also found that the rates of functional genotypes per the total number of genotypes in individual whole genomes differ dramatically between human populations. We then created tables showing how the use of comparator or reference genome panels comprised of genomes from individuals that do not have the same ancestral background as a patient can negatively impact pathogenic variant identification. Our results have important implications for clinical sequencing initiatives.

Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with ease – without the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER.