Multiple model species selection for transcriptomics analysis of non-model organisms

A broad-taxa approach as an important concept in ecotoxicological studies and pollution monitoring

Aquatic invertebrates play a pivotal role in (eco)toxicological assessments because they offer ethical, cost-effective and repeatable testing options. Additionally, their significance in the food chain and their ability to represent diverse aquatic ecosystems make them valuable subjects for (eco)toxicological studies. To ensure consistency and comparability across studies, international (eco)toxicology guidelines have been used to establish standardised methods and protocols for data collection, analysis and interpretation. However, the current standardised protocols primarily focus on a limited number of aquatic invertebrate species, mainly from Arthropoda, Mollusca and Annelida. These protocols are suitable for basic toxicity screening, effectively assessing the immediate and severe effects of toxic substances on organisms. For more comprehensive and ecologically relevant assessments, particularly those addressing long-term effects and ecosystem-wide impacts, we recommended the use of a broader diversity of species, since the present choice of taxa exacerbates the limited scope of basic ecotoxicological studies. This review provides a comprehensive overview of (eco)toxicological studies, focusing on major aquatic invertebrate taxa and how they are used to assess the impact of chemicals in diverse aquatic environments. The present work supports the use of a broad-taxa approach in basic environmental assessments, as it better represents the natural populations inhabiting various ecosystems. Advances in omics and other biochemical and computational techniques make the broad-taxa approach more feasible, enabling mechanistic studies on non-model organisms. By combining these approaches with in vitro techniques together with the broad-taxa approach, researchers can gain insights into less-explored impacts of pollution, such as changes in population diversity, the development of tolerance and transgenerational inheritance of pollution responses, the impact on organism phenotypic plasticity, biological invasion outcomes, social behaviour changes, metabolome changes, regeneration phenomena, disease susceptibility and tissue pathologies. This review also emphasises the need for harmonised data-reporting standards and minimum annotation checklists to ensure that research results are findable, accessible, interoperable and reusable (FAIR), maximising the use and reusability of data. The ultimate goal is to encourage integrated and holistic problem-focused collaboration between diverse scientific disciplines, international standardisation organisations and decision-making bodies, with a focus on transdisciplinary knowledge co-production for the One-Health approach.

Comparative Transcriptome Analyses of Different Rheum officinale Tissues Reveal Differentially Expressed Genes Associated with Anthraquinone, Catechin, and Gallic Acid Biosynthesis

Rheum officinale Baill. is an important traditional Chinese medicinal herb, its dried roots and rhizomes being widely utilized to cure diverse diseases. However, previous studies mainly focused on the active compounds and their pharmacological effects, and the molecular mechanism underlying the biosynthesis of these ingredients in R. officinale is still elusive. Here, we performed comparative transcriptome analyses to elucidate the differentially expressed genes (DEGs) in the root, stem, and leaf of R. officinale. A total of 236,031 unigenes with N50 of 769 bp was generated, 136,329 (57.76%) of which were annotated. A total of 5884 DEGs was identified after the comparative analyses of different tissues; 175 and 126 key enzyme genes with tissue-specific expression were found in the anthraquinone, catechin/gallic acid biosynthetic pathway, respectively, and some of these key enzyme genes were verified by qRT-PCR. The phylogeny of the PKS III family in Polygonaceae indicated that probably only PL_741 PKSIII1, PL_11549 PKSIII5, and PL_101745 PKSIII6 encoded PKSIII in the polyketide pathway. These results will shed light on the molecular basis of the tissue-specific accumulation and regulation of secondary metabolites in R. officinale, and lay a foundation for the future genetic diversity, molecular assisted breeding, and germplasm resource improvement of this essential medicinal plant.

Juxtapose: a gene-embedding approach for comparing co-expression networks

BACKGROUND

Gene co-expression networks (GCNs) are not easily comparable due to their complex structure. In this paper, we propose a tool, Juxtapose, together with similarity measures that can be utilized for comparative transcriptomics between a set of organisms. While we focus on its application to comparing co-expression networks across species in evolutionary studies, Juxtapose is also generalizable to co-expression network comparisons across tissues or conditions within the same species.

METHODS

A word embedding strategy commonly used in natural language processing was utilized in order to generate gene embeddings based on walks made throughout the GCNs. Juxtapose was evaluated based on its ability to embed the nodes of synthetic structures in the networks consistently while also generating biologically informative results. Evaluation of the techniques proposed in this research utilized RNA-seq datasets from GTEx, a multi-species experiment of prefrontal cortex samples from the Gene Expression Omnibus, as well as synthesized datasets. Biological evaluation was performed using gene set enrichment analysis and known gene relationships in literature.

RESULTS

We show that Juxtapose is capable of globally aligning synthesized networks as well as identifying areas that are conserved in real gene co-expression networks without reliance on external biological information. Furthermore, output from a matching algorithm that uses cosine distance between GCN embeddings is shown to be an informative measure of similarity that reflects the amount of topological similarity between networks.

CONCLUSIONS

Juxtapose can be used to align GCNs without relying on known biological similarities and enables post-hoc analyses using biological parameters, such as orthology of genes, or conserved or variable pathways.

AVAILABILITY

A development version of the software used in this paper is available at https://github.com/klovens/juxtapose.

Blast2Fish: a reference-based annotation web tool for transcriptome analysis of non-model teleost fish

BACKGROUND

Transcriptome analysis by next-generation sequencing has become a popular technique in recent years. This approach is quite suitable for non-model organism study, as de novo assembly is independent of prior genomic sequences of organisms. De novo sequencing has benefited many studies on commercially important fish species. However, to understand the functions of these assembled sequences, they still need to be annotated with existing sequence databases. By combining Basic Local Alignment Search Tool (BLAST) and Gene Ontology analysis, we were able to identify homologous sequences of assembled sequences and describe their characteristics using pre-defined tags for each gene, though the above conventional annotation results obtained for non-model assembled sequences was still associated with a lack of pre-defined tags and poorly documented records in the database.

RESULTS

We introduced Blast2Fish, a novel approach for performing functional enrichment analysis on non-model teleost fish transcriptome data. The Blast2Fish pipeline was designed to be a reference-based enrichment method. Instead of annotating the BLAST single top hit by a pre-defined gene-to-tag database, we included 500 hits to search related PubMed articles and parse biological terms. These descriptive terms were then sorted and recorded as annotations for the query. The results showed that Blast2Fish was capable of providing meaningful annotations on immunology topics for non-model fish transcriptome analysis.

CONCLUSION

Blast2Fish provides a novel approach for annotating sequences of non-model fish. The reference-based strategy allows annotation to be performed without pre-defined tags for each gene. This method strongly benefits non-model teleost fish studies for gene functional enrichment analysis.