Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring the relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have now updated the GeneFriends database and website. Here, we present the new version of GeneFriends, which includes gene and transcript co-expression networks based on RNA-seq data from 46 475 human and 34 322 mouse samples. The new database also encompasses tissue-specific gene co-expression networks for 20 human and 21 mouse tissues, dataset-specific gene co-expression maps based on TCGA and GTEx projects and gene co-expression networks for additional seven model organisms (fruit fly, zebrafish, worm, rat, yeast, cow and chicken). GeneFriends is freely available at http://www.genefriends.org/.

One of the important questions in aging research is how differences in transcriptomics are associated with the longevity of various species. Unfortunately, at the level of individual genes, the links between expression in different organs and maximum lifespan (MLS) are yet to be fully understood. Analyses are complicated further by the fact that MLS is highly associated with other confounding factors (metabolic rate, gestation period, body mass, etc.) and that linear models may be limiting. Using gene expression from 41 mammalian species, across five organs, we constructed gene-centric regression models associating gene expression with MLS and other species traits. Additionally, we used SHapley Additive exPlanations and Bayesian networks to investigate the non-linear nature of the interrelations between the genes predicted to be determinants of species MLS. Our results revealed that expression patterns correlate with MLS, some across organs, and others in an organ-specific manner. The combination of methods employed revealed gene signatures formed by only a few genes that are highly predictive towards MLS, which could be used to identify novel longevity regulator candidates in mammals.

Histological evaluation of tissue-engineered products, including hydrogels for cellular encapsulation, is a critical and invaluable tool for assessing the product across multiple stages of its lifecycle from manufacture to implantation. However, many tissue-engineered products are comprised of polymers and hydrogels which are not optimized for use with conventional methods of tissue fixation and histological processing. Routine histology utilizes a combination of chemical fixatives, such as formaldehyde, and solvents such as xylene which have been optimized for use with native biological tissues due to their high protein and lipid content. Previous work has highlighted the challenges associated with processing hydrogels for routine histology due to their high water content and lack of diverse chemical moieties amenable for tissue fixation with traditional fixatives. Thus, hydrogel-based tissue engineering products are prone to histological artifacts during their validation which can lead to challenges in correctly interpreting results. In addition, chemicals used in conventional histological approaches are associated with significant health and environmental concerns due to their toxicity and there is thus an urgent need to identify suitable replacements. Here we use a multifactorial design of experiments approach to identify processing parameters capable of preserving cell-biomaterial interactions in a prototypical hydrogel system: ionically crosslinked calcium alginate. We identify a formalin free fixative which better retains cell-biomaterial interactions and calcium alginate hydrogel integrity as compared to the state-of-the-art formalin-based approaches. In addition, we demonstrate that this approach is compatible with a diversity of manufacturing techniques used to fabricate calcium alginate-based scaffolds for tissue engineering and cell therapy, including histological evaluation of cellular encapsulation in 3D tubes and thin tissue engineering scaffolds (∼50 μm). Furthermore, we show that formalin-free fixation can be used to retain cell-biomaterial interactions and hydrogel architecture in hybrid alginate-gelatin based scaffolds for use with histology and scanning electron microscopy. Taken together, these findings are a significant step forward towards improving histological evaluation of ionically crosslinked calcium alginate hydrogels and help make their validation less toxic, thus more environmentally friendly and sustainable.