The tree tomato (Solanum betaceum Cav.) is an underutilized fruit crop native to the Andean region and phylogenetically related to the tomato and potato. Tree tomato fruits have a high amount of nutrients and bioactive compounds. However, so far there are no studies at the genome or transcriptome level for this species. We performed a de novo assembly and transcriptome annotation for purple-fruited (A21) and an orange-fruited (A23) accessions. A total of 174,252 (A21) and 194,417 (A23) transcripts were assembled with an average length of 851 and 849 bp. A total of 34,636 (A21) and 36,224 (A23) transcripts showed a significant similarity to known proteins. Among the annotated unigenes, 22,096 (A21) and 23,095 (A23) were assigned to the Gene Ontology (GO) term and 14,035 (A21) and 14,540 (A23) were found to have Clusters of Orthologous Group (COG) term classifications. Furthermore, 22,096 (A21) and 23,095 (A23) transcripts were assigned to 155 and 161 (A23) KEGG pathways. The carotenoid biosynthetic process GO terms were significantly enriched in the purple-fruited accession A21. Finally, 68,647 intraspecific single-nucleotide variations (SNVs) and almost 2 million interspecific SNVs were identified. The results of this study provide a wealth of genomic data for the genetic improvement of the tree tomato.

Background: One of the major challenges in addressing multiple sclerosis is to understand its progression trajectory. The pathological process transitions from acute phases predominantly driven by inflammation to progressive clinical profiles where neurodegeneration takes precedence. It is known that sex plays a crucial role in this heterogeneity; females are two to three times more likely to suffer from multiple sclerosis, while males suffer from more rapid neurodegeneration with greater severity. Results: To gain insight into the sex-based molecular differences, we processed single cell datasets from the central nervous system and the peripheral blood, covering the different courses of multiple sclerosis. We generated cell-type specific landscapes, including gene signatures from differentially expressed genes, functional profiling, pathway activation, and cell-cell communication networks for females, males, and their sex differential profiles. Among our findings, we revealed that female neurons may exhibit protective mechanisms against neurodegeneration. In the inflammatory-predominant forms, female immune cells present an inflammatory core driven by the AP-1 transcription factor, while male adaptive immune cells exhibit higher mitochondrial impairment. Conversely, larger differences are reported in CD8+ T cells progressive forms, with males exhibiting cytolytic profiles that may promote neurodegeneration. Complete results can be explored in the interactive webtool https://bioinfo.cipf.es/cbl-atlas-ms/ . Conclusions: We identified cell-type specific sex differences in brain and immune cells that vary in the spectrum of multiple sclerosis. We consider this molecular description a valuable resource to promote future targeted approaches considering the sex of the individual.

In this work, we present a novel integrative analysis of transposable elements (TEs) in 4 single cell RNA-seq (scRNA-seq) datasets of postmortem substancia nigra pars compacta samples of Parkinson Disease (PD) patients matched healthy controls, with the objective of building a cell-type specific trustworthy atlas of TEs that may clarify the role of TEs in sex differences in PD. We have used the soloTE tool to evaluate the TEs expression changes across all snRNA-seq studies identified in our previous systematic review, and then integrated the results using meta-analysis techniques. Finally, we evaluated the possible associations between TEs and protein coding genes by integrating our previous results in this matter with the information of TEs obtained, in order to propose the possible action mechanism by which some of the TEs contribute to PD.

Highlights: • MetaOmixTools is an interactive, web-based platform that streamlines the meta-analysis of ranked feature lists and functional enrichment profiles, including 2 powerful analysis modules: MetaRank and MetaEnrich. • MetaRank generates robust consensus rankings across studies using both weighted (e.g., rank product) and unweighted (e.g., robust rank aggregation) methods. • MetaEnrich performs functional meta-analysis by integrating P values from independent overrepresentation analyses using established statistical approaches. • The platform offers intuitive visualization and reproducible workflows, enabling consistent extraction of biological insights from multistudy omics data.

In recent decades, increasing longevity (among other factors) has fostered a rise in Parkinson’s disease (PD) incidence. Although not exhaustively studied in this devastating disease, the impact of sex represents a critical variable in PD as epidemiological and clinical features differ between males and females. To study sex bias in PD, we conducted a systematic review, tissue-specific meta-analyses of transcriptomic data from the frontal cortex (FC), striatum tissue (ST), and substantia nigra (SN), and a global meta-analysis of all 3 brain regions. We selected 7 PD studies that included sex information, analyzing 267 samples. The tissue-specific meta-analyses linked PD to the enhanced expression of MED31 in the female FC and the dysregulation of 237 genes in the SN. The global meta-analysis detected 15 genes with sex-differential patterns in PD, which participate in mitochondrial function, oxidative stress, neuronal degeneration, and cell death. Furthermore, functional analyses identified pathways, protein-protein interaction networks, and transcription factors that differed by sex. While male PD patients exhibited changes in oxidative stress based on metal ions, inflammation, and angiogenesis, female PD patients exhibited dysfunctions in mitochondrial and lysosomal activity, antigen processing and presentation functions, and glutamic and purine metabolism. Overall, we believe that our findings will provide new insight into the perspective of sex in PD, thereby underscoring the importance of including sex information in future PD studies.

Summary Sex and gender differences in different health scenarios has been thoroughly acknowledged in the literature, and yet, very scarcely analyzed. To fill the gap, here we present MetaFun, which allows to meta-analyze multiple omics datasets with a sex-based perspective, and to combine different datasets to gain major statistical power and to assist the researcher in understanding these sex differences in the diseases under study. Metafun is freely available at bioinfo.cipf.es/metafun Availability and implementation: MetaFun is available under http://bioinfo.cipf.es/metafun. The backend has been implemented in R and Java and the frontend has been developed using Angular. Supplementary information R code available at https://gitlab.com/ubb-cipf/metafunr