As a dominant mangrove species, Kandelia obovata is distributed in an intertidal marsh with an active H₂S release. Whether H₂S participates in the salt tolerance of mangrove plants is still ambiguous, although increasing evidence has demonstrated that H₂S functions in plant responses to multiple abiotic stresses. In this study, NaHS was used as an H₂S donor to investigate the regulatory mechanism of H₂S on the salt tolerance of K. obovata seedlings by using a combined physiological and proteomic analysis. The results showed that the reduction in photosynthesis (Pn) caused by 400 mM of NaCl was recovered by the addition of NaHS (200 μM). Furthermore, the application of H₂S enhanced the quantum efficiency of photosystem II (PSII) and the membrane lipid stability, implying that H₂S is beneficial to the survival of K. obovata seedlings under high salinity. We further identified 37 differentially expressed proteins by proteomic approaches under salinity and NaHS treatments. Among them, the proteins that are related to photosynthesis, primary metabolism, stress response and hormone biosynthesis were primarily enriched. The physiological and proteomic results highlighted that exogenous H₂S up-regulated photosynthesis and energy metabolism to help K. obovata to cope with high salinity. Specifically, H₂S increased photosynthetic electron transfer, chlorophyll biosynthesis and carbon fixation in K. obovata leaves under salt stress. Furthermore, the abundances of other proteins related to the metabolic pathway, such as antioxidation (ascorbic acid peroxidase (APX), copper/zinc superoxide dismutase (CSD2), and pancreatic and duodenal homeobox 1 (PDX1)), protein synthesis (heat-shock protein (HSP), chaperonin family protein (Cpn) 20), nitrogen metabolism (glutamine synthetase 1 and 2 (GS2), GS1:1), glycolysis (phosphoglycerate kinase (PGK) and triosephosphate isomerase (TPI)), and the ascorbate–glutathione (AsA–GSH) cycle were increased by H₂S under high salinity. These findings provide new insights into the roles of H₂S in the adaptations of the K. obovata mangrove plant to high salinity environments.

Acid rain (AR), a serious environmental issue, severely affects plant growth and development. As the gymnosperms of conifer woody plants, Pinus massoniana (AR-sensitive) and Taxus wallichiana var. mairei (AR-resistant) are widely distributed in southern China. Under AR stress, significant necrosis and collapsed lesions were found in P. massoniana needles with remarkable yellowing and wilting tips, whereas T. wallichiana var. mairei did not exhibit chlorosis and visible damage. Due to the activation of a large number of stress-related genes and the synthesis of various functional proteins to counteract AR stress, it is important to study the differences in AR-tolerance mechanisms by comparative proteomic analysis of tolerant and sensitive species. This study revealed a total of 65 and 26 differentially expressed proteins that were identified in P. massoniana and T. wallichiana var. mairei, respectively. Among them, proteins involved in metabolism, photosynthesis, signal transduction and transcription were drastically down-regulated in P. massoniana, whereas most of the proteins participating in metabolism, cell structure, photosynthesis and transcription were increased in T. wallichiana var. mairei. These results suggest the distinct patterns of protein expression in the two woody species in response to AR, allowing a deeper understanding of diversity on AR tolerance in forest tree species.

Background: Analysing genomes of animal model organisms is widely used for understanding the genetic basis of complex traits and diseases, such as obesity, for which only a few mouse models exist, however, without their lean counterparts. Objective: To analyse genetic differences in the unique mouse models of polygenic obesity (Fat line) and leanness (Lean line) originating from the same base population and established by divergent selection over more than 60 generations. Methods: Genetic variability was analysed using WGS. Variants were identified with GATK and annotated with Ensembl VEP. g.Profiler, WebGestalt, and KEGG were used for GO and pathway enrichment analysis. miRNA seed regions were obtained with miRPathDB 2.0, LncRRIsearch was used to predict targets of identified lncRNAs, and genes influencing adipose tissue amount were searched using the IMPC database. Results: WGS analysis revealed 6.3 million SNPs, 1.3 million were new. Thousands of potentially impactful SNPs were identified, including within 24 genes related to adipose tissue amount. SNP density was highest in pseudogenes and regulatory RNAs. The Lean line carries SNP rs248726381 in the seed region of mmu-miR-3086-3p, which may affect fatty acid metabolism. KEGG analysis showed deleterious missense variants in immune response and diabetes genes, with food perception pathways being most enriched. Gene prioritisation considering SNP GERP scores, variant consequences, and allele comparison with other mouse lines identified seven novel obesity candidate genes: 4930441H08Rik, Aff3, Fam237b, Gm36633, Pced1a, Tecrl, and Zfp536. Conclusion: WGS revealed many genetic differences between the lines that accumulated over the selection period, including variants with potential negative impacts on gene function. Given the increasing availability of mouse strains and genetic polymorphism catalogues, the study is a valuable resource for researchers to study obesity.

This review addresses the significant challenge of identifying causal genetic variants within quantitative trait loci (QTLs) for complex traits and diseases. Despite progress in detecting the ever-larger number of such loci, establishing causality remains daunting. We advocate for integrating bioinformatics and multiomics analyses to streamline the prioritization of candidate genes' variants. Our case study on the Pla2g4e gene, identified previously as a positional candidate obesity gene through genetic mapping and expression studies, demonstrates how applying multiomic data filtered through regulatory elements containing SNPs can refine the search for causative variants. This approach can yield results that guide more efficient experimental strategies, accelerating genetic research toward functional validation and therapeutic development.

Horsemeat, known for its high nutritional value and lower environmental impact compared to beef, faces cultural and ethical challenges. Despite its potential, genetic research on horsemeat quality remains limited and no Quantitative Trait Loci (QTLs) have been identified. The aim of this study was to identify and prioritize Single Nucleotide Polymorphism (SNP) markers on the GeneSeek^® GenomicProfiler™ Equine chip for traits related to meat quality. Genes associated with meat quality were identified through a PubMEd search. These were analyzed for SNPs with potential regulatory or functional effects based on Genomic Evolutionary Rate Profiling (GERP) scores, constrained element locations, orthologous regulatory regions in mice and humans, and effects on polyadenylation, miRNA, and transcription factor binding. Further prioritization focused on genes whose orthologs are within QTLs for meat quality traits in other species. Including SNPs in linkage disequilibrium with chip markers from the Animal-SNPAtlas, we identified 27 SNP markers associated with 19 genes. Notable candidates include ALDOA, CS, GOT1, PLIN1, PYGM, and SDHB, linked to metabolic pathways, and MYL11, MYOM1, PDLIM5, RYR3, and TNNT3, associated with muscle structure and development. This research provides genetic insights to improve horsemeat quality and help breeders and smallholder farmers. Integrating these results with larger datasets can improve breeding value predictions and support effective breeding programs.