SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms.

SQANTI3 is a tool designed for the quality control, curation and annotation of long-read transcript models obtained with third-generation sequencing technologies. Leveraging its annotation framework, SQANTI3 calculates quality descriptors of transcript models, junctions and transcript ends. With this information, potential artifacts can be identified and replaced with reliable sequences. Furthermore, the integrated functional annotation feature enables subsequent functional iso-transcriptomics analyses.

Intravitreal injection of a rationally designed AAV capsid library in non-human primate identifies variants with enhanced retinal transduction and neutralizing antibody evasion.

Adeno-associated virus (AAV) continues to be the gold standard vector for therapeutic gene delivery and has proven especially useful for treating ocular disease. Intravitreal injection (IVtI) is a promising delivery route because it increases accessibility of gene therapies to larger patient populations. However, data from clinical and non-human primate (NHP) studies utilizing currently available capsids indicate that anatomical barriers to AAV and pre-existing neutralizing antibodies can restrict gene expression to levels that are "sub-therapeutic" in a substantial proportion of patients. Here, we performed a combination of directed evolution in NHPs of an AAV2-based capsid library with simultaneous mutations across six surface-exposed variable regions and rational design to identify novel capsid variants with improved retinal transduction following IVtI. Following two rounds of screening in NHP, enriched variants were characterized in intravitreally injected mice and NHPs and shown to have increased transduction relative to AAV2. Lead capsid variant, P2-V1, demonstrated an increased ability to evade neutralizing antibodies in human vitreous samples relative to AAV2 and AAV2.7m8. Taken together, this study further contributed to our understanding of the selective pressures associated with retinal transduction via the vitreous and identified promising novel AAV capsid variants for clinical consideration.

A comprehensive study of a 29-capsid AAV library in a non-human primate central nervous system.

Non-human primates (NHPs) are a preferred animal model for optimizing adeno-associated virus (AAV)-mediated CNS gene delivery protocols before clinical trials. In spite of its inherent appeal, it is challenging to compare different serotypes, delivery routes, and disease indications in a well-powered, comprehensive, multigroup NHP experiment. Here, a multiplex barcode recombinant AAV (rAAV) vector-tracing strategy has been applied to a systemic analysis of 29 distinct, wild-type (WT), AAV natural isolates and engineered capsids in the CNS of eight macaques. The report describes distribution of each capsid in 15 areas of the macaques' CNS after intraparenchymal (putamen) injection, or cerebrospinal fluid (CSF)-mediated administration routes (intracisternal, intrathecal, or intracerebroventricular). To trace the vector biodistribution (viral DNA) and targeted tissues transduction (viral mRNA) of each capsid in each of the analyzed CNS areas, quantitative next-generation sequencing analysis, assisted by the digital-droplet PCR technology, was used. The report describes the most efficient AAV capsid variants targeting specific CNS areas after each route of administration using the direct side-by-side comparison of WT AAV isolates and a new generation of rationally designed capsids. The newly developed bioinformatics and visualization algorithms, applicable to the comparative analysis of several mammalian brain models, have been developed and made available in the public domain.

SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms.

The emergence of long-read RNA sequencing (lrRNA-seq) has provided an unprecedented opportunity to analyze transcriptomes at isoform resolution. However, the technology is not free from biases, and transcript models inferred from these data require quality control and curation. In this study, we introduce SQANTI3, a tool specifically designed to perform quality analysis on transcriptomes constructed using lrRNA-seq data. SQANTI3 provides an extensive naming framework to describe transcript model diversity in comparison to the reference transcriptome. Additionally, the tool incorporates a wide range of metrics to characterize various structural properties of transcript models, such as transcription start and end sites, splice junctions, and other structural features. These metrics can be utilized to filter out potential artifacts. Moreover, SQANTI3 includes a Rescue module that prevents the loss of known genes and transcripts exhibiting evidence of expression but displaying low-quality features. Lastly, SQANTI3 incorporates IsoAnnotLite, which enables functional annotation at the isoform level and facilitates functional iso-transcriptomics analyses. We demonstrate the versatility of SQANTI3 in analyzing different data types, isoform reconstruction pipelines, and sequencing platforms, and how it provides novel biological insights into isoform biology. The SQANTI3 software is available at https://github.com/ConesaLab/SQANTI3 .

A roadmap for the functional annotation of protein families: a community perspective.

Over the last 25 years, biology has entered the genomic era and is becoming a science of 'big data'. Most interpretations of genomic analyses rely on accurate functional annotations of the proteins encoded by more than 500 000 genomes sequenced to date. By different estimates, only half the predicted sequenced proteins carry an accurate functional annotation, and this percentage varies drastically between different organismal lineages. Such a large gap in knowledge hampers all aspects of biological enterprise and, thereby, is standing in the way of genomic biology reaching its full potential. A brainstorming meeting to address this issue funded by the National Science Foundation was held during 3-4 February 2022. Bringing together data scientists, biocurators, computational biologists and experimentalists within the same venue allowed for a comprehensive assessment of the current state of functional annotations of protein families. Further, major issues that were obstructing the field were identified and discussed, which ultimately allowed for the proposal of solutions on how to move forward.

Removal of Endotoxin from rAAV Samples Using a Simple Detergent-Based Protocol.

Endotoxin is the most common contaminant found in protein samples. Even a small amount of endotoxin can induce strong allergic reaction and death of a host organism. Endotoxin is also often detected in recombinant adeno-associated virus (rAAV) stocks prepared in research laboratories using off-the-shelf reagents; purifying rAAV stocks from endotoxin using commercial reagents sometimes results in significant titer loss. The problem is exacerbated due to the recently expanded diversity of rAAV serotypes and capsid variants, which, due to their variable capsid surface charge, display differential affinity toward endotoxin. In this paper, we describe a simple universal protocol of purifying vector stocks irrespective of AAV serotype. The protocol is based on subjecting endotoxin-contaminated rAAV to mild detergent treatment, followed by repeated buffer-exchange washing and concentrating viral stock by low-speed centrifugation. Multiple assays were employed to test the physical and biological equivalency of the viral stocks before and after purification. The described protocol has been routinely utilized to purify vector stocks contaminated at levels as high as >1,000 endotoxin units (EU)/mL to produce viral vectors with practically undetectable levels of endotoxin (<2.5 EU/mL), with the titer's recovery in the range of 50%-100%.