Molecular insights into Pashmina fiber production: comparative skin transcriptomic analysis of Changthangi goats and sheep.

Ladakh, one of the highest inhabited regions globally, hosts the unique Changthangi goat, renowned for producing Pashmina, the world's most luxurious natural fiber. In comparison, the fiber derived from Changthangi sheep is considered next only to Pashmina. This research endeavors to compare the skin transcriptome profiles of Changthangi goats and Changthangi sheep, aiming to discern the molecular determinants behind the recognition of Changthangi goats as the source of Pashmina. Drawing upon previously conducted studies, a collective of 225 genes correlated with fiber characteristics were extracted from the differentially expressed genes noticed between the two species (p-value of ≤ 0.05 and a log2 fold change of ≥ 1.5). These genes were analyzed using DAVID software to understand their biological functions and to identify enriched KEGG and Reactome pathways. The protein-protein interaction networks were constructed using Cytoscape, cytoHubba, and STRING to focus on key genes and infer their biological significance. Comparative transcriptome analysis revealed significantly higher expression of genes involved in signaling pathways like Wnt, MAPK, PI3K-Akt, Hedgehog, associated with fiber development and quality in Changthangi goats. These pathways play crucial roles in hair follicle (HF) formation, maintenance of epidermal stem cells, and fiber characteristics. Findings also highlight the enrichment of cell adhesion molecules and ECM-receptor interaction, emphasizing their roles in HF structure, growth, and signaling. This investigation offers an in-depth understanding of the molecular intricacies governing Pashmina production in Changthangi goats, providing valuable insights into their unique genetic makeup and underlying mechanisms influencing the exceptional quality of Pashmina fibers.

Comprehensive evaluation and validation of optimal reference genes for normalization of qPCR data in different caprine tissues.

BACKGROUND: Quantitative real-time PCR (qPCR) is a highly reliable method for validating gene expression data in molecular studies due to its sensitivity, specificity, and efficiency. To ensure accurate qPCR results, it's essential to normalize the expression data using stable reference genes. METHODS: This study aimed to identify suitable reference genes for qPCR studies in goats by evaluating 18 candidate reference genes (ACTB, BACH1, B2M, GAPDH, HMBS, HPRT1, PGK1, PPIA, PPIB, RPLP0, RPL19, RPS9, RPS15, RPS28, SDHA, TBP, UXT, and YWHAZ) in 10 different caprine tissues (heart, intestine, kidney, liver, lung, muscle, rumen, skin, spleen, and testis). An integrated tool called RefFinder, which incorporates various algorithms like NormFinder, GeNorm, BestKeeper, and ΔCt, was used to assess the stability of expression among these genes. RESULTS: After thorough analysis, ACTB, PPIB, and B2M emerged as the most stable reference genes, while RPL19, RPS15, and RPS9 were found to be the least stable. The suitability of the selected internal control genes was further validated through target gene analysis, confirming their efficacy in ensuring accurate gene expression profiling in goats. CONCLUSION: The study determined that the geometric average of ACTB, PPIB, and B2M creates an appropriate normalization factor for gene expression studies in goat tissues.

Identification and validation of stable reference genes for expression profiling of target genes in diverse ovine tissues.

Quantitative PCR (qPCR) is a widely-used technique for quantifying the expression of target genes across various tissues, as well as under different pathological and physiological conditions. One of the challenges associated with this method is the need to identify optimal reference genes (RGs) that maintain consistent expression levels under diverse experimental settings, thereby ensuring accurate biological interpretation. In this study, we conducted a thorough analysis of 18 candidate RGs (ACTB, BACH1, B2M, GAPDH, HMBS, HPRT1, PGK1, PPIA, PPIB, RPLP0, RPL19, RPS9, RPS15, RPS28, SDHA, TBP, UXT, and YWHAZ) across 10 ovine tissues (muscle, skin, kidney, liver, intestine, rumen, lung, testis, heart, and spleen) obtained from five individual sheep. We aimed to identify genes with stable expression across these tissues. A literature-based survey helped us shortlist candidate genes representing various functional classes from multiple livestock species. We employed four algorithms: geNorm, NormFinder, BestKeeper, and Delta Ct (ΔCt), to rank these genes based on their stability. A consistent trend in the rankings was observed across these different algorithms. RefFinder was then used for a comprehensive ranking, integrating the outputs from the various methods. ACTB, PPIB, BACH1, and B2M emerged as the most stable RGs, while RPS9, RPS15, and PGK1 displayed variable expression. We validated our findings through qPCR analysis of four target genes (ACTN2, CRYAB, DLK1, and TRIM54) in the skin samples from two different sheep breeds. Based on these results, we recommend ACTB, PPIB, BACH1, and B2M as reliable internal control genes for qPCR experiments involving diverse ovine tissues.