Aldosterone [HRP]

Background French beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria. Results A population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency. Conclusions The combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.

Triphenyltin has been classified as an endocrine disruptor. However, whether triphenyltin interferes with the adrenal glands during puberty remains unknown. Here, we reported the effects of triphenyltin on the adrenal glands in rats. Male Sprague Dawley rats (age of 35 days) were orally administered with 0, 0.5, 1, or 2 mg/kg/day triphenyltin for 18 days. Triphenyltin significantly lowered corticosterone levels at 1 and 2 mg/kg and adrenocorticotropic hormone at 2 mg/kg. The RNA-Seq analysis detected multiple differentially expressed genes. Four down-regulated genes were transcription factor genes (Nr4a1, Nr4a2, Nr4a3, and Ppard), which might be associated with the suppression of the adrenal cortex function. RNA-seq and qPCR showed that triphenyltin dose-dependently down-regulated the expression of the genes for cholesterol transport and biosynthesis, including Scarb1, Ldlr, Hmgcsl, Hmgcr, and Hsd17b7. Further Western blotting revealed that it lowered NR4A1, PPRAD, LDLR, and HMGCS1 protein levels. We treated H295R adrenal cells with 1-100 nM triphenyltin for 72 h. Triphenyltin induced significant higher ROS production at 100 nM and did not induce apoptosis at 10 and 100 nM. In conclusion, triphenyltin inhibits production of corticosterone via blocking the expression of cholesterol uptake transporters and cholesterol biosynthesis.