Biology subjects

Pardo-Palacios, F.

Publications and source records attributed to Pardo-Palacios, F..

3 recordsLinked to original sources

bioRxiv2023

SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark

Long-read RNA-seq has emerged as a powerful tool for transcript discovery, even in well-annotated organisms. However, assessing the accuracy of different methods in identifying annotated and novel transcripts remains a challenge. Here, we present SQANTI-SIM, a versatile utility that wraps around popular long-read simulators to allow precise management of transcript novelty based on the structural categories defined by SQANTI3. By selectively excluding specific transcripts from the reference dataset, SQANTI-SIM effectively emulates scenarios involving unannotated transcripts. Furthermore, the tool provides customizable features and supports the simulation of additional types of data, representing the first multi-omics simulation tool for the lrRNA-seq field. We demonstrate the effectiveness of SQANTI-SIM by benchmarking five transcriptome reconstruction pipelines using the simulated data.

bioinformatics↗

bioRxiv2023

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.

bioinformatics↗

bioRxiv2021

The evolution of splicing: transcriptome complexity and transcript distances implemented in TranD

Alternative splicing contributes to organismal complexity. Comparing transcripts between and within species is an important first step toward understanding questions about how evolution of transcript structure changes between species and contributes to sub-functionalization. These questions are confounded with issues of data quality and availability. The recent explosion of affordable long read sequencing of mRNA has considerably widened the ability to study transcriptional variation in non-model species. In this work, we develop a computational framework that uses nucleotide resolution distance metrics to compare transcript models for structural phenotypes: total transcript length, intron retention, donor/acceptor site variation, alternative exon cassettes, alternative 5/3 UTRs are each scored qualitatively and quantitatively in terms of number of nucleotides. For a single annotation file, all differences among transcripts within a gene are summarized and transcriptome-level complexity metrics: number of variable nucleotides, unique exons per gene, exons per transcript, and transcripts per gene are calculated. To compare two transcriptomes on the same co-ordinates, a weighted total distance between pairs of transcripts for the same gene is calculated. The weight function proposed has larger penalties for intron retention and exon skipping than alternative donor/acceptor sites. Minimum distances can be used to identify both transcript pairs and transcripts missing structural elements in either of the two annotations. This enables a broad range of functionality from comparing sister species to comparing different methods of building and summarizing transcriptomes. Importantly, the philosophy here is to output metrics, enabling others to explore the nucleotide-level distance metrics. Single transcriptome annotation summaries and pairwise comparisons are implemented in a new tool, TranD, distributed as a PyPi package and in the open-source web-based Galaxy (www.galaxyproject.org) platform.

genomics↗