Serine/arginine-rich splicing factors belong to a class of intrinsically disordered proteins

Serine/arginine-rich (SR) splicing factors play an important role in constitutive and alternative splicing as well as during several steps of RNA metabolism. Despite the wealth of functional information about SR proteins accumulated to-date, structural knowledge about the members of this family is very limited. To gain a better insight into structure-function relationships of SR proteins, we performed extensive sequence analysis of SR protein family members and combined it with ordered/disordered structure predictions. We found that SR proteins have properties characteristic of intrinsically disordered (ID) proteins. The amino acid composition and sequence complexity of SR proteins were very similar to those of the disordered protein regions. More detailed analysis showed that the SR proteins, and their RS domains in particular, are enriched in the disorder-promoting residues and are depleted in the order-promoting residues as compared to the entire human proteome. Moreover, disorder predictions indicated that RS domains of SR proteins were completely unstructured. Two different classification methods, the charge-hydropathy measure and the cumulative distribution function (CDF) of the disorder scores, were in agreement with each other, and they both strongly predicted members of the SR protein family to be disordered. This study emphasizes the importance of the disordered structure for several functions of SR proteins, such as for spliceosome assembly and for interaction with multiple partners. In addition, it demonstrates the usefulness of order/disorder predictions for inferring protein structure from sequence

Unfoldomics of human diseases: linking protein intrinsic disorder with diseases

<p>Abstract</p> <p>Background</p> <p>Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) lack stable tertiary and/or secondary structure yet fulfills key biological functions. The recent recognition of IDPs and IDRs is leading to an entire field aimed at their systematic structural characterization and at determination of their mechanisms of action. Bioinformatics studies showed that IDPs and IDRs are highly abundant in different proteomes and carry out mostly regulatory functions related to molecular recognition and signal transduction. These activities complement the functions of structured proteins. IDPs and IDRs were shown to participate in both one-to-many and many-to-one signaling. Alternative splicing and posttranslational modifications are frequently used to tune the IDP functionality. Several individual IDPs were shown to be associated with human diseases, such as cancer, cardiovascular disease, amyloidoses, diabetes, neurodegenerative diseases, and others. This raises questions regarding the involvement of IDPs and IDRs in various diseases.</p> <p>Results</p> <p>IDPs and IDRs were shown to be highly abundant in proteins associated with various human maladies. As the number of IDPs related to various diseases was found to be very large, the concepts of the disease-related unfoldome and unfoldomics were introduced. Novel bioinformatics tools were proposed to populate and characterize the disease-associated unfoldome. Structural characterization of the members of the disease-related unfoldome requires specialized experimental approaches. IDPs possess a number of unique structural and functional features that determine their broad involvement into the pathogenesis of various diseases.</p> <p>Conclusion</p> <p>Proteins associated with various human diseases are enriched in intrinsic disorder. These disease-associated IDPs and IDRs are real, abundant, diversified, vital, and dynamic. These proteins and regions comprise the disease-related unfoldome, which covers a significant part of the human proteome. Profound association between intrinsic disorder and various human diseases is determined by a set of unique structural and functional characteristics of IDPs and IDRs. Unfoldomics of human diseases utilizes unrivaled bioinformatics and experimental techniques, paves the road for better understanding of human diseases, their pathogenesis and molecular mechanisms, and helps develop new strategies for the analysis of disease-related proteins.</p

Intrinsic Disorder Is a Common Feature of Hub Proteins from Four Eukaryotic Interactomes

Recent proteome-wide screening approaches have provided a wealth of information about interacting proteins in various organisms. To test for a potential association between protein connectivity and the amount of predicted structural disorder, the disorder propensities of proteins with various numbers of interacting partners from four eukaryotic organisms (Caenorhabditis elegans, Saccharomyces cerevisiae, Drosophila melanogaster, and Homo sapiens) were investigated. The results of PONDR VL-XT disorder analysis show that for all four studied organisms, hub proteins, defined here as those that interact with ≥10 partners, are significantly more disordered than end proteins, defined here as those that interact with just one partner. The proportion of predicted disordered residues, the average disorder score, and the number of predicted disordered regions of various lengths were higher overall in hubs than in ends. A binary classification of hubs and ends into ordered and disordered subclasses using the consensus prediction method showed a significant enrichment of wholly disordered proteins and a significant depletion of wholly ordered proteins in hubs relative to ends in worm, fly, and human. The functional annotation of yeast hubs and ends using GO categories and the correlation of these annotations with disorder predictions demonstrate that proteins with regulation, transcription, and development annotations are enriched in disorder, whereas proteins with catalytic activity, transport, and membrane localization annotations are depleted in disorder. The results of this study demonstrate that intrinsic structural disorder is a distinctive and common characteristic of eukaryotic hub proteins, and that disorder may serve as a determinant of protein interactivity

Full-length isoform transcriptome of the developing human brain provides further insights into autism.

Alternative splicing plays an important role in brain development, but its global contribution to human neurodevelopmental diseases (NDDs) requires further investigation. Here we examine the relationships between splicing isoform expression in the brain and de novo loss-of-function mutations from individuals with NDDs. We analyze the full-length isoform transcriptome of the developing human brain and observe differentially expressed isoforms and isoform co-expression modules undetectable by gene-level analyses. These isoforms are enriched in loss-of-function mutations and microexons, are co-expressed with a unique set of partners, and have higher prenatal expression. We experimentally test the effect of splice-site mutations and demonstrate exon skipping in five NDD risk genes, including SCN2A, DYRK1A, and BTRC. Our results suggest that the splice site mutation in BTRC reduces translational efficiency, likely affecting Wnt signaling through impaired degradation of β-catenin. We propose that functional effects of mutations should be investigated at the isoform- rather than gene-level resolution

Inferring the molecular and phenotypic impact of amino acid variants with MutPred2

Identifying pathogenic variants and underlying functional alterations is challenging. To this end, we introduce MutPred2, a tool that improves the prioritization of pathogenic amino acid substitutions over existing methods, generates molecular mechanisms potentially causative of disease, and returns interpretable pathogenicity score distributions on individual genomes. Whilst its prioritization performance is state-of-the-art, a distinguishing feature of MutPred2 is the probabilistic modeling of variant impact on specific aspects of protein structure and function that can serve to guide experimental studies of phenotype-altering variants. We demonstrate the utility of MutPred2 in the identification of the structural and functional mutational signatures relevant to Mendelian disorders and the prioritization of de novo mutations associated with complex neurodevelopmental disorders. We then experimentally validate the functional impact of several variants identified in patients with such disorders. We argue that mechanism-driven studies of human inherited disease have the potential to significantly accelerate the discovery of clinically actionable variants

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases

Microduplications of 16p11.2 are associated with schizophrenia

Recurrent microdeletions and microduplications of a 600 kb genomic region of chromosome 16p11.2 have been implicated in childhood-onset developmental disorders1-3. Here we report the strong association of 16p11.2 microduplications with schizophrenia in two large cohorts. In the primary sample, the microduplication was detected in 12/1906 (0.63%) cases and 1/3971 (0.03%) controls (P=1.2×10-5, OR=25.8). In the replication sample, the microduplication was detected in 9/2645 (0.34%) cases and 1/2420 (0.04%) controls (P=0.022, OR=8.3). For the series combined, microduplication of 16p11.2 was associated with 14.5-fold increased risk of schizophrenia (95% C.I. [3.3, 62]). A meta-analysis of multiple psychiatric disorders showed a significant association of the microduplication with schizophrenia, bipolar disorder and autism. The reciprocal microdeletion was associated only with autism and developmental disorders. Analysis of patient clinical data showed that head circumference was significantly larger in patients with the microdeletion compared with patients with the microduplication (P = 0.0007). Our results suggest that the microduplication of 16p11.2 confers substantial risk for schizophrenia and other psychiatric disorders, whereas the reciprocal microdeletion is associated with contrasting clinical features

Microduplications of 16p11.2 are associated with schizophrenia

Recurrent microdeletions and microduplications of a 600-kb genomic region of chromosome 16p11.2 have been implicated in childhood-onset developmental disorders1,2,3. We report the association of 16p11.2 microduplications with schizophrenia in two large cohorts. The microduplication was detected in 12/1,906 (0.63%) cases and 1/3,971 (0.03%) controls (P = 1.2 × 10−5, OR = 25.8) from the initial cohort, and in 9/2,645 (0.34%) cases and 1/2,420 (0.04%) controls (P = 0.022, OR = 8.3) of the replication cohort. The 16p11.2 microduplication was associated with a 14.5-fold increased risk of schizophrenia (95% CI (3.3, 62)) in the combined sample. A meta-analysis of datasets for multiple psychiatric disorders showed a significant association of the microduplication with schizophrenia (P = 4.8 × 10−7), bipolar disorder (P = 0.017) and autism (P = 1.9 × 10−7). In contrast, the reciprocal microdeletion was associated only with autism and developmental disorders (P = 2.3 × 10−13). Head circumference was larger in patients with the microdeletion than in patients with the microduplication (P = 0.0007)