Biology subjects

Mestre-Tomas, J.

Publications and source records attributed to Mestre-Tomas, J..

3 recordsLinked to original sources

bioRxiv2024

Pelagic ecosystem responses to changes in seawater conditions during the Middle Pleistocene Transition in the Eastern Mediterranean

AbstractMesopelagic fishes play a crucial role in the global carbon cycle through their diel vertical migration (DVM), but the impacts of neither natural nor anthropogenic climate change on DVM patterns are currently known. Studying the geological past can elucidate changes in DVM patterns under swelling climate pressure and allow estimating the impacts of the current climate crisis. We present a multi-proxy, ecosystem-level assessment of paleoenvironmental changes in the Eastern Mediterranean during the Middle Pleistocene (marine isotope stages MIS 23-18; 923-756 ka B.P.) and use the carbon and oxygen isotopic composition of fossil fish otoliths to assess the impacts of these changes on DVM and their possible implications on the biological pump. Temperature was the primary driver of ecosystem change during MIS 21 interglacial, whereas productivity became a dominant factor in MIS 19 interglacial. Responses of organisms throughout the water column varied. Our results indicate increased productivity across trophic levels during MIS 19, which affected foraminiferal biomasses, but did not inhibit fish DVM. In contrast, the early MIS 21 warming led to a reduction in DVM by mesopelagic fishes and consequently a drop in biological pump efficiency.

systems biology↗

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↗