No abstract

Exon skipping using antisense oligonucleotides (ASOs) has recently proven to be a powerful tool for mRNA splicing modulation. Several exon-skipping ASOs have been approved to treat genetic diseases worldwide. However, a significant challenge is the difficulty in selecting an optimal sequence for exon skipping. The efficacy of ASOs is often unpredictable, because of the numerous factors involved in exon skipping. To address this gap, we have developed a computational method using machine-learning algorithms that factors in many parameters as well as experimental data to design highly effective ASOs for exon skipping. eSkip-Finder (https://eskip-finder.org) is the first web-based resource for helping researchers identify effective exon skipping ASOs. eSkip-Finder features two sections: (i) a predictor of the exon skipping efficacy of novel ASOs and (ii) a database of exon skipping ASOs. The predictor facilitates rapid analysis of a given set of exon/intron sequences and ASO lengths to identify effective ASOs for exon skipping based on a machine learning model trained by experimental data. We confirmed that predictions correlated well with in vitro skipping efficacy of sequences that were not included in the training data. The database enables users to search for ASOs using queries such as gene name, species, and exon number.

Significance Duchenne muscular dystrophy (DMD) is a fatal disorder of progressive body-wide muscle weakness, considered the most common muscular dystrophy worldwide. Most patients have out-of-frame deletions in the DMD gene, leading to dystrophin absence in muscle. There is no cure for DMD, but exon skipping is emerging as a potential therapy that uses antisense oligonucleotides to convert out-of-frame to in-frame mutations, enabling the production of truncated, partially functional dystrophin. Currently approved exon skipping therapies, however, have limited applicability and efficacy. Here, we developed a more economical approach to skip DMD exons 45 to 55 (a strategy that could treat nearly half of all DMD patients) and identified DG9 peptide conjugation as a powerful way to improve exon skipping efficiencies in vivo.

AbstractCombining scientific data over a long-time period is necessary to understand the diversity, population trends, and conservation importance of any taxa in a global and regional scale. Bangladesh is located in a biodiversity hotspot region, however, till date, only few animal groups has been extensively investigated at a nation-wide scale. Although being one of the earliest and well-known insect groups, the knowledge on Odonata of this region remains rudimentary and dispersed. To resolve this issue, we have developed an online database for the Odonata of Bangladesh. We have compiled data from our last four years field study, from previously published research articles, field guides, and also collected data from citizen scientists regarding Bangladeshi odonates. Odonata of Bangladesh database (http://www.odobd.org) contains information on morphology, abundance, gene and protein sequences, local and global distribution and conservation status of the Odonata of Bangladesh. The database also demonstrates gender specified photographs with descriptions for better understanding for the novice researchers and naturalists. Odonata of Bangladesh database provides a comprehensive source for meta-analyses in ecology, conservation biology, and genetic research.

Combining scientific data over a long-time period is necessary for generating large-scale datasets, which are an essential component of comparative analysis for understanding evolutionary processes. Furthermore, monitoring temporal and spatial distributions of animals at a global and regional scale is essential for studying climate change driven extinction risks. Regional and global datasets focusing on different animal groups are on the rise to meet such challenges. Although being one of the earliest and best-known insect groups, the data on Odonata remains rudimentary and dispersed, especially in the South Asian region. Bangladesh, being located within a biodiversity hotspot, possesses a large number of odonate species and many of them are endemic to the South Asian region. We have developed an online database for the Odonata of Bangladesh by compiling and digitizing data from our last four years of field studies, from previously published research articles and field guides, and also by collecting data from citizen scientists. The Odonata of Bangladesh database (accessible at http://www.odobd.org) contains phenotypic, genotypic, photographic, taxonomic, biogeographic and faunistic data of the Odonata of Bangladesh. The database will be a valuable resource for understanding diversity, distributions, extinction risks and conservation planning of the Odonata of Bangladesh. Finally, phenotypic, spatial and temporal data of Odonata of Bangladesh datasets can be integrated with other regional datasets for analyzing macroevolutionary trends and to monitor the effect of climate change on odonates.