Biology subjects

Almeida, I.

Publications and source records attributed to Almeida, I..

3 recordsLinked to original sources

bioRxiv2024

HyDRA: a pipeline for integrating long- and short-read RNAseq data for custom transcriptome assembly

BackgroundShort-read RNA sequencing (RNAseq) has widely been used to sequence RNA from a wide range of different tissues, developmental stages and species. However, the technology is limited by inherent biases and its inability to capture full-length transcripts. Long-read RNAseq overcomes these issues by providing reads that can span multiple exons, resolve complex repetitive regions and the capability to cover entire transcripts. Unfortunately, this technology is still prone to higher error rates. Noncoding RNA transcripts are highly specific to different cell types and tissues and remain underrepresented in current reference annotations. This problem is exacerbated by the dismissal of sequenced reads that align to genomic regions that do not contain annotated transcripts, resulting in approximately half of the expressed transcripts being overlooked in transcriptional studies. ResultsWe have developed a pipeline, named HyDRA (Hybrid de novo RNA assembly), which combines the precision of short reads with the structural resolution of long reads, enhancing the accuracy and reliability of custom transcriptome assemblies. Deep, short- and long-read RNAseq data derived from ovarian and fallopian tube samples were used to develop, validate and assess the efficacy of HyDRA. We identified more than 50,000 high-confidence long noncoding RNAs, most of which have not been previously detected using traditional methods. ConclusionsHyDRAs assembly performed more than 40% better than a similar assembly obtained with the top-ranked stand-alone de novo transcriptome short-read-only assembly tool and over 30% better than one obtained with the best-in-class multistep short-read-only approach. Although long-read sequencing is rapidly advancing, the vast availability of short-read RNAseq data will ensure that hybrid approaches like the one implemented in HyDRA continue to be relevant, allowing the discovery of high-confidence transcripts within specific cell types and tissues. As the practice of performing hybrid de novo transcriptome assemblies becomes commonplace, HyDRA will advance the annotation of coding and noncoding transcripts and expand our knowledge of the noncoding genome.

bioinformatics↗

bioRxiv2024

OligoY pipeline for full Y chromosome painting

MotivationThe standard protocol for designing probes used in full chromosome fluorescent labeling experiments does not include repetitive sequences to avoid off-target hybridization. Due to the Y chromosomes highly repetitive nature, most assembly nowadays still have heavily fragmented and incomplete Y sequences. Among these, the remaining non-repetitive sequences are insufficient to design probes and efficiently perform FISH Oligopaint assays, since they do not cover most regions of the chromosome. Ergo, cytogenetic studies with the Y are sparse, and analysis such as its function throughout the cell cycle and insights into its evolutionary history and relationships with other regions of the genome remain poorly studied. ResultsIn this work, we introduce a new pipeline for designing FISH Oligopaint probes for the Y chromosome of any species of interest. OligoY pipeline uses open-source tools, enriches the amount of contigs assigned to the Y chromosome from the draft assembly, and effectively uses repetitive sequences unique to the target chromosome to design probes. Throughout all of its steps, the pipeline guarantees the user the autonomy to choose parameters, thus maximizing overall efficiency of cytogenetic experiments. After extensive in silico and in situ tests and validations with Drosophila melanogaster, we showed for the first time a pipeline for probe design that significantly increases previous Y chromosome staining with no off-target signal. AvailabilityThe pipeline is available at https://github.com/isabela42/OligoY.

bioinformatics↗

bioRxiv2024

Decoding Music-Evoked Valence and Arousal: Unraveling the Neural Correlates of Naturalistic Music Characteristics through fMRI

Music can convey basic emotions, such as joy and sadness, and more complex ones, such as tenderness or nostalgia. Its effects on emotion regulation and reward have attracted much attention in cognitive and affective neuroscience. Understanding the neural correlates of music-evoked emotions may guide the development of neurorehabilitation interventions based on music. Here, we used fMRI to examine the relationship between the classification of music excerpts regarding perceived valence and arousal and their neural correlates. Twenty participants were scanned while listening to 96 musical excerpts, which were classified beforehand into four categories as a function of valence (positive vs. negative) and arousal (high vs. low). Differences in valence and arousal modulated activity in cortical regions, most noticeably the music-specific subregions of the auditory cortex, but also in the thalamus and regions of the reward network such as the amygdala. Using multivoxel pattern analysis, we created a computational model able to decode the valence and arousal of the music excerpts significantly above chance. We further explored how a set of musical features relate to brain activity in valence-, arousal-, reward-, and auditory-related ROIs. The results emphasize the differential involvement of musical features in the brain, notably expressive features such as Vibrato and Tonal and Spectral dissonance in valence, arousal, and reward brain networks, while a broader set of features modulate sensory auditory networks. Using ecologically valid music stimuli, we contribute to the definition of the neural substrates of music listening and evoked emotions. Moreover, the definition of the musical features that modulate specific brain networks paves the way to developing novel music-based neurorehabilitation strategies.

neuroscience↗