RESUMO
Docosahexaenoic acid (DHA) is an essential nutrient for humans and plays a critical role in human development and health. Freshwater fish, such as the common carp (Cyprinus carpio), have a certain degree of DHA biosynthesis ability and could be a supplemental source of human DHA needs. The elongase of very-long-chain fatty acid 5 (Elovl5) is an important enzyme affecting polyunsaturated fatty acid (PUFA) biosynthesis. However, the function and regulatory mechanism of the elovl5 gene related to DHA synthesis in freshwater fish is not clear yet. Previous studies have found that there are two copies of the elovl5 gene, elovl5a and elovl5b, which have different functions. Our research group found significant DHA content differences among individuals in Yellow River carp (Cyprinus carpio var.), and four candidate genes were found to be related to DHA synthesis through screening. In this study, the expression level of elovl5a is decreased in the high-DHA group compared to the low-DHA group, which indicated the down-regulation of elovl5a in the DHA synthesis pathways of Yellow River carp. In addition, using a dual-luciferase reporter gene assay, we found that by targeting the 3'UTR region of elovl5a, miR-26a-5p could regulate DHA synthesis in common carp. After CRISPR/Cas9 disruption of elovl5a, the DHA content in the disrupted group was significantly higher than in the wildtype group; meanwhile, the expression level of elovl5a in the disrupted group was significantly reduced compared with the wildtype group. These results suggest that elovl5a may be down-regulating DHA synthesis in Yellow River carp. This study could provide useful information for future research on the genes and pathways that affect DHA synthesis.
RESUMO
Tetrodotoxin (TTX) is a potent marine neurotoxin that exists in a variety of aquatic and terrestrial organisms. Pufferfish in different habitats show great variation in their TTX contents. Exploring the genes involved in TTX metabolism could contribute to our understanding of the molecular mechanisms underlying TTX accumulation, translocation, and detoxification in pufferfish. In this study, transcriptomic analysis was used to identify the functional genes related to TTX metabolism in the blood, liver, and muscle of the toxic and non-toxic tiger puffer (Takifugu rubripes). A total of 6101 differentially expressed genes (DEGs) were obtained after transcriptomic analysis; of these, 2401 were identified in the blood, 2262 in the liver, and 1438 in the muscle. After enrichment analysis, fourteen genes encoding glutathione S-transferases (GSTs), glutathione peroxidase (GPx), thioredoxins (TXNs), superoxide dismutase (SOD), ATP-binding cassettes (ABCs), apolipoproteins (APOs), inhibitors of apoptosis protein (IAP), and solute carrier (SLC), which are mainly antioxidant enzymes, membrane transporters, or anti-apoptotic factors, were revealed in the blood. Thirty-six genes encoding SLCs, ABCs, long-chain-fatty-acid-CoA ligases (ACSLs), interleukin 6 cytokine family signal transducer (IL6ST), endoplasmic reticulum (ER), and heat shock protein family A (Hsp70) were involved in transmembrane transporter activity and innate immune response. Notably, a large number of slc genes were found to play critical and diverse roles in TTX accumulation and translocation in the liver of T. rubripes. Nine genes from the slc, hsp70, complement C5 (c5), acsl, er, and serpin peptidase inhibitor (serpin) gene families were found to participate in the regulation of protein processing and anti-apoptosis. These results reflect the diverse functions of genes closely related to TTX accumulation, translocation, and detoxification in T. rubripes.
Assuntos
Takifugu , Transcriptoma , Animais , Perfilação da Expressão Gênica , Fígado/metabolismo , Takifugu/genética , Takifugu/metabolismo , Tetrodotoxina/metabolismoRESUMO
Community ecology theory suggests that an individual's phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities.