Joseph M. Paggi

Identification of new branch points and unconventional introns in Saccharomyces cerevisiae

Spliced messages constitute one-fourth of expressed mRNAs in the yeast Saccharomyces cerevisiae, and most mRNAs in metazoans. Splicing requires 5 splice site (5SS), branch point (BP), and 3 splice site (3SS) elements, but the role of the BP in splicing control is poorly understood because BP identification remains difficult. We developed a high-throughput method, Branch-seq, to map BPs and 5SSs of isolated RNA lariats. Applied to S. cerevisiae, Branch-seq detected 76% of expressed, annotated BPs and identified a comparable number of novel BPs. We performed RNA-seq to confirm associated 3SS locations, identifying some 200 novel splice junctions, including an AT-AC intron. We show that several yeast introns use two or even three different BPs, with effects on 3SS choice, protein coding potential, or RNA stability, and identify novel introns whose splicing changes during meiosis or in response to stress. Together, these findings show unanticipated complexity of splicing in yeast.

Structure of the µ-opioid receptor–G i protein complex

The μ-opioid receptor (μOR) is a G-protein-coupled receptor (GPCR) and the target of most clinically and recreationally used opioids. The induced positive effects of analgesia and euphoria are mediated by μOR signalling through the adenylyl cyclase-inhibiting heterotrimeric G protein Gi. Here we present the 3.5u2009Å resolution cryo-electron microscopy structure of the μOR bound to the agonist peptide DAMGO and nucleotide-free Gi. DAMGO occupies the morphinan ligand pocket, with its Nxa0terminus interacting with conserved receptor residues and its Cxa0terminus engaging regions important for opioid-ligand selectivity. Comparison of the μOR–Gi complex to previously determined structures of other GPCRs bound to the stimulatory G protein Gs reveals differences in the position of transmembrane receptor helix 6 and in the interactions between the G protein α-subunit and the receptor core. Together, these results shed light on the structural features that contribute to the Gi protein-coupling specificity of the µOR.A cryo-electron structure of the µ-opioid receptor in complex with the peptide agonist DAMGO and the inhibitory G protein Gi reveals structural determinants of its G protein-binding specificity.

Crystal structure of the natural anion-conducting channelrhodopsin Gt ACR1

The naturally occurring channelrhodopsin variant anion channelrhodopsin-1 (ACR1), discovered in the cryptophyte algae Guillardia theta, exhibits large light-gated anionxa0conductance and high anionxa0selectivity when expressed in heterologous settings, properties that support its use as an optogenetic tool to inhibit neuronal firing with light. However, molecular insight into ACR1 is lacking owing to the absence of structural information underlying light-gated anion conductance. Here we present the crystal structure of G. theta ACR1 at 2.9xa0Å resolution. The structure reveals unusual architectural features that span the extracellular domain, retinal-binding pocket, Schiff-base region, and anion-conduction pathway. Together with electrophysiological and spectroscopic analyses, these findings reveal the fundamental molecular basis of naturally occurring light-gated anion conductance, and provide a framework for designing the next generation of optogenetic tools.The crystal structure of anion channelrhodopsin-1 (ACR1) from the algae Guillardia theta provides insights into the basis of anion conductance.

HISAT-genotype: Next Generation Genomic Analysis Platform on a Personal Computer

Rapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses of human genomes. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT-genotype, for representing and searching an expanded model of the human reference genome, in which a comprehensive catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a very fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate HISAT-genotype’s accuracy for HLA typing, a critical task in human organ transplantation, and for the DNA fingerprinting tests widely used in forensics. In both applications, HISAT-genotype not only improves upon earlier computational methods, but matches or exceeds the accuracy of laboratory-based assays. One Sentence Summary HISAT-genotype is a software platform that has the ability to genotype all the genes in an individual’s genome within a few hours on a desktop computer.

S-CAP extends clinical-grade pathogenicity prediction to genetic variants that affect RNA splicing

There are over 15,000 known variants that cause human inherited disease by disrupting RNA splicing. While several in silico methods such as CADD, EIGEN and LINSIGHT are commonly used to predict the pathogenicity of noncoding variants, we introduce S-CAP, a tool developed specially for splicing which is better able to effectively distinguish pathogenic splicing-relevant variants from benign variants. S-CAP is a novel splicing pathogenicity predictor that reduces the number of splicing-relevant variants of uncertain significance in patient exomes by 41%, a nearly 3-fold improvement over existing noncoding pathogenicity measures while correctly classifying known pathogenic splicing-relevant variants with a clinical-grade 95% sensitivity.

A sequence-based, deep learning model accurately predicts RNA splicing branchpoints

Experimental detection of RNA splicing branchpoints is difficult. To date, high-confidence experimental annotations exist for 18% of 3 splice sites in the human genome. We develop a deep-learning-based branchpoint predictor, LaBranchoR, which predicts a correct branchpoint for at least 75% of 3 splice sites genome-wide. Detailed analysis of cases in which our predicted branchpoint deviates from experimental data suggests a correct branchpoint is predicted in over 90% of cases. We use our predicted branchpoints to identify a novel sequence element upstream of branchpoints consistent with extended U2 snRNA base-pairing, show an association between weak branchpoints and alternative splicing, and explore the effects of genetic variants on branchpoints. We provide genome-wide branchpoint annotations and in silico mutagenesis scores at http://bejerano.stanford.edu/labranchor.

Numerous recursive sites contribute to accuracy of splicing in long introns in flies

Recursive splicing, a process by which a single intron is removed from pre-mRNA transcripts in multiple distinct segments, has been observed in a small subset of Drosophila melanogaster introns. However, detection of recursive splicing requires observation of splicing intermediates that are inherently unstable, making it difficult to study. Here we developed new computational approaches to identify recursively spliced introns and applied them, in combination with existing methods, to nascent RNA sequencing data from Drosophila S2 cells. These approaches identified hundreds of novel sites of recursive splicing, expanding the catalog of recursively spliced fly introns by 4-fold. A subset of recursive sites were validated by RT-PCR and sequencing. Recursive sites occur in most very long (> 40 kb) fly introns, including many genes involved in morphogenesis and development, and tend to occur near the midpoints of introns. Suggesting a possible function for recursive splicing, we observe that fly introns with recursive sites are spliced more accurately than comparably sized non-recursive introns.

Intron Length and Recursive Sites are Major Determinants of Splicing Efficiency in Flies

The dynamics of gene expression may impact regulation, and RNA processing can be rate limiting. To assess rates of pre-mRNA splicing, we used a short, progressive metabolic labeling/RNA sequencing strategy to estimate the intron half-lives of ~30,000 fly introns, revealing strong correlations with several gene features. Splicing rates varied with intron length and were fastest for modal intron lengths of 60-70 nt. We also identified hundreds of novel recursively spliced segments, which were associated with much faster and also more accurate splicing of the long introns in which they occur. Surprisingly, the introns in a gene tend to have similar splicing half-lives and longer first introns are associated with faster splicing of subsequent introns. Our results indicate that genes have different intrinsic rates of splicing, and suggest that these rates are influenced by molecular events at gene 5’ ends, likely tuning the dynamics of developmental gene expression.Production of most eukaryotic mRNAs requires splicing of introns from pre-mRNA. The splicing reaction requires definition of splice sites, which are initially recognized in either intron-spanning (intron definition) or exon-spanning (exon definition) pairs. To understand how exon and intron length and splice site recognition mode impact splicing, we measured splicing rates genome-wide in Drosophila, using metabolic labeling/RNA sequencing and new mathematical models to estimate rates. We found that the modal intron length range of 60-70 nt represents a local maximum of splicing rates, but that much longer exon-defined introns are spliced even faster and more accurately. Surprisingly, we observed low variation in splicing rates across introns in the same gene, suggesting the presence of gene-level influences, and we identified multiple gene level variables associated with splicing rate. Together our data suggest that developmental and stress response genes may have preferentially evolved exon definition in order to enhance rates of splicing.