RNA molecules undergo a vast array of chemical post-transcriptional modifications (PTMs) that can affect their structure and interaction properties. To date, over 150 naturally occurring PTMs have been identified, however the overwhelming majority of their functions remain elusive. In recent years, a small number of PTMs have been successfully mapped to the transcriptome using experimental approaches relying on high-throughput sequencing. Oxford Nanopore direct-RNA sequencing (DRS) technology has been shown to be sensitive to RNA modifications. We developed and validated Nanocompore, a robust analytical framework to evaluate the presence of modifications in DRS data. To do so, we compare an RNA sample of interest against a non-modified control sample. Our strategy does not require a training set and allows the use of replicates to model biological variability. Here, we demonstrate the ability of Nanocompore to detect RNA modifications at single-molecule resolution in human polyA+ RNAs, as well as in targeted non-coding RNAs. Our results correlate well with orthogonal methods, confirm previous observations on the distribution of N6-methyladenosine sites and provide novel insights into the distribution of RNA modifications in the coding and non-coding transcriptomes. The latest version of Nanocompore can be obtained at https://github.com/tleonardi/nanocompore.
In bird mixed flocks, a prominent species, the so-called nuclear species, improves the cohesion and maintenance of the flocks, while other less conspicuous species are assumed as satellite. In this study we described the composition, as well as examined the existence of both nuclear and satellite species in mixed flocks of a savanna in the Pantanal. The observations were developed using three transects during the dry season of 2002. Bird species abundance and respective rate of participation in mixed flocks were surveyed by transects, while intraspecific sociality, communication, foraging maneuvers of species, and responses to predators were sampled by direct observations. These parameters were evaluated to distinguish nuclear from satellite species. We observed 41 bird mixed flocks, which included from 2 to 17 species of which Suiriri suiriri (Vieillot), one of the most abundant species, was present in most flocks, often represented by 2-4 individuals, whereas most other species occurred lone or in pairs. While foraging by acrobatic maneuvers S. suiriri often gave contact calls, as well as earlier giving alarm calls if faced with a risk of predation. In addition, S. suiriri always started mixed flocks movements. Conversely, most other species were silent and closely inspected the vegetation while foraging. Such species always followed S. suiriri and seldom gave contact calls. Hence, the conspicuous traits exhibited by S. suiriri, potentially, are exploited by the other bird species as cues, which are important references for bird mixed flock cohesion in a savanna in the southern Pantanal.Keywords: bird mixed flocks, nuclear species, Pantanal, Suiriri suiriri, social behavior. Bandos mistos de aves e espécie nuclear em uma savana de ipês no Pantanal ResumoEm bandos mistos de aves, a espécie nuclear possui características que promovem a coesão e manutenção dos bandos, enquanto espécies menos conspícuas são consideradas satélites. Este estudo teve como objetivos descrever a composição, bem como analisar a existência de espécies nucleares e satélites em bandos mistos em um tipo de savana do Pantanal Sul. As observações foram desenvolvidas ao longo de três trajetos durante a estação seca de 2002. A abundância das espécies e respectiva taxa de participação nos bandos mistos foram amostradas através de trajetos, enquanto dados sobre socialidade intra-específica, comunicação, manobras de forrageio e reação a predadores foram obtidos através de observações diretas. Esses parâmetros foram adotados como critérios, para distinguir espécies nucleares de satélites. Foram detectados 41 bandos mistos que incluíram de 2 a 17 espécies, sendo que Suiriri suiriri, uma das espécies mais abundantes na savana de ipês, esteve presente em praticamente todos os bandos, na forma de um par ou grupo de indivíduos que, regularmente, emitiam chamados de contato, enquanto forrageavam executando manobras acrobáticas. Também, emitiram chamados de alarme quando em risco de predação e foram seguidos pelas demais espécies durante os desloc...
Thousands of scientific articles describing genes associated with human diseases are published every week. Computational methods such as text mining and machine learning algorithms are now able to automatically detect these associations. In this study, we used a cognitive computing text-mining application to construct a knowledge network comprised of 3,723 genes and 99 diseases. We then tracked the yearly changes on these networks to analyze how our knowledge has evolved in the past 30 years. Our approach helped to unravel the molecular bases of diseases over time, and to detect shared mechanisms between clinically distinct diseases. It also revealed that multi-purpose therapeutic drugs target genes which are commonly associated with several psychiatric, inflammatory, or infectious disorders. By navigating in this knowledge tsunami, we were able to extract relevant biological information and insights about human diseases.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.