Whole-transcriptome RNA sequencing reveals global expression dynamics and ceRNA regulatory networks related to hair follicle development and melanogenesis in goats

Objective Domestic animals, fur is a product of long-term selection by humans and the natural environment. It is generally used to distinguish between different breeds. This study aims to dissect the molecular mechanisms underlying the distinct fur characteristics of goats, particularly focusing on the molecular and regulatory differences between the Dazu Black Goat (DBG) and the Inner Mongolia Cashmere Goat (IMCG). Through whole-transcriptome analysis, we aim to identify differentially expressed RNAs and construct a ceRNA network to reveal the genetic regulation of goat hair follicle development and melanin production. Methods Skin, hair, and cashmere samples were collected from DBG (n = 15) and IMCG (n = 17) to assess hair follicle density, length, diameter, and melanin content. Whole-transcriptome sequencing of skin tissues from DBG (n = 3) and IMCG (n = 3) identified 50,652 RNAs. Differential expression analysis was performed on mRNAs, lncRNAs, miRNAs, and circRNAs. Results IMCG exhibited significantly higher hair follicle density, hair length, and cashmere diameter than DBG (p < 0.01), whereas DBG had significantly thicker hair and higher melanin content (p < 0.01). A total of 640 differentially expressed RNAs were identified, including 157 mRNAs, 234 lncRNAs, 72 miRNAs, and 177 circRNAs. These were enriched in pathways related to melanogenesis, hair follicle development, and GO terms such as collagen fiber organization and pigmentation. ceRNA networks constructed from differentially expressed RNAs revealed key regulatory mechanisms of coat color and hair traits. Conclusion Whole-transcriptome sequencing revealed expression profiles and ceRNA networks involved in hair follicle development and melanogenesis in goats. These findings provide insights into the roles of coding and non-coding RNAs in fur traits, supporting future breeding strategies and textile applications

Identification of key genes regulating brown adipose tissue thermogenesis in goat kids (Capra hircus) by using weighted gene co-expression network analysis

Brown adipose tissue (BAT) is crucial for the maintenance of body temperature in newborn animals through non-shivering thermogenesis (NST). However, which kind key genes involved in the regulation of BAT thermogenesis and the internal regulation mechanism of heat production in goat BAT were still unclear. In this study, we analyzed the perirenal adipose tissue transcriptome of Dazu black goats from 0, 7, 14, 21 and 28 days after birth using weighted gene co-expression network analysis (WGCNA) to identify key genes involved in the thermogenesis of BAT. Genes were classified into 22 co-expression modules by WGCNA. The turquoise module exhibited high gene expression in D0, with generally lower expression in the later dates. This pattern is consistent with the rapid color, morphological, and thermogenic changes observed in perirenal adipose tissue shortly after birth. GO functional annotation revealed that the genes in the turquoise module were significantly enriched in the mitochondrion, mitochondrial protein-containing complex, cytoplasm, and mitochondrial inner membrane. KEGG pathway enrichment analysis indicated that these genes were predominantly enriched in the signaling pathways of oxidative phosphorylation, thermogenesis, and TCA cycle. By combining the gene co-expression network analysis of the turquoise module genes and the differentially expression genes (DEG) analysis, we identified 5 candidate key genes (ACO2, MRPS27, IMMT, MRPL12, and TUFM) involved in regulation of perirenal adipose tissue thermogenesis. This finding offer candidate genes that in the regulation of BAT thermogenesis and body temperature maintenance in goat kids

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

© The Author(s) 2017 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/ genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.Peer reviewedFinal Published versio

Insulin resistance and dyslipidemia in low-birth-weight goat kids

Low birth weight (LBW) impairs the development and health of livestock by affecting postnatal growth performance and metabolic health in adulthood. Previous studies on indigenous goats in southwest China showed that LBW goat kids had higher mortality and morbidity rates, including hepatic dyslipidemia and liver damage. However, the mechanism of insulin resistance affecting lipid metabolism under LBW conditions remains unclear. In this study, we conducted in vivo glucose-insulin metabolic studies, measured biochemical parameters, and analyzed related regulatory pathways. Both glucose tolerance tests and insulin tolerance tests indicated insulin resistance in LBW goat kids compared to controls (p &lt; 0.05). The marker of insulin resistance, homeostasis model assessment (HOMA), was 2.85-fold higher in LBW than in control goats (p &lt; 0.01). Additionally, elevated levels of free fatty acids in both plasma and skeletal muscle were observed in LBW goats compared to normal birth weight (NBW) goats (p &lt; 0.05). Transcriptome analysis revealed impairments in lipid metabolism and insulin signaling in LBW goats. The observed lipid accumulation was associated with the upregulation of genes linked to fatty acid uptake and transport (FABP3), fatty acid oxidation (PPARA), triacylglycerol synthesis (LPIN1 and DGAT1), oxidative stress (ANKRD2), and insulin resistance (PGC1α). Furthermore, the insulin receptor substrate 2 (IRS2) was lower in the liver of LBW goat kids (p &lt; 0.05). While there was no change in insulin function in skeletal muscle, LBW may lead to lipid accumulation in skeletal muscle by interfering with insulin function in the liver. These findings collectively impact the health and growth performance of livestock

Effects of Drought and Flooding on Growth and Physiology of Cinnamomum camphora Seedlings

In the context of climate change, future patterns of precipitation are expected to increase the intensity and frequency of drought and flooding stress. This is also likely to result in more frequent flooding&ndash;drought alternation events. Drought and flooding stress can have negative effects on tree morphology, physiology, and biochemistry, which can potentially pose long-term threats to tree survival and further disrupt the stability of forest ecosystems. However, it remains unclear how trees would cope with these stressors and their alternations through growth and physiology responses. Potted seedlings of C. camphora were grown under a rainout shelter in the field with four water treatments for 40 days: well-watered (WW), drought stress (DS), flooding stress (FS) and flooding&ndash;drought alternation (FDF). Growth, leaf gas exchange, water potential, and biochemical traits were measured. Results show different seedling growth patterns under drought and flooding stress. Drought increased the root-to-shoot ratio (+25%) but flooding favored leaf growth (+33%). Decreases in photosynthesis under drought and flooding were mainly related to stomatal limitations, accompanied by abscisic acid accumulation under drought but not under flooding. Drought reduced water potential, and flooding&ndash;drought alternation only decreased water potential in its drought phase. Flooding treatment had no effect on water potential. Drought treatment increased the proline concentrations (+74%) and carbon isotopic composition (+3.7%), but all treatments had no effect on the concentrations of elements in leaves. Drought stress led to carbon depletion in both stem and root, whereas flooding stress primarily induced carbon depletion in the root. Flooding&ndash;drought alternation was accompanied by complex physiological responses, including physiological recovery when the stress (flood, drought) was relieved. Our results have shown the different effects of drought and flooding on the growth and physiology of C. camphora seedlings, emphasizing the need to consider specific water stress conditions in future studies and providing a theoretical basis for better management of this tree species in urban areas under variable rainfall patterns