Comparative analysis of skin transcriptome reveals differences of cashmere fineness in different body parts of Inner Mongolia cashmere goats
Bibliographic record
Abstract
OBJECTIVE: The growth and development of secondary hair follicles primarily determine the economic value of cashmere traits, significantly influencing the quality of cashmere fineness. Previous studies have concentrated on the periodic growth regulation of hair follicles in Inner Mongolia cashmere goats (IMCGs), identifying numerous candidate genes that influence cashmere traits. Research on the factors and regulatory mechanisms affecting cashmere fineness in different body parts is currently limited. METHODS: The differences of cashmere fineness traits among different body parts or ages were determined by multiple comparison analysis testing in analysis of variance. RNA-seq and Gene Ontology (GO) & Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used to assess the differentially expressed genes (DEGs) across different body parts of IMCGs. The candidate genes were validated using quantitative realtime polymerase chain reaction techniques. RESULTS: Ages and different body parts had significant effects on cashmere diameter of IMCGs (p<0.05). Cashmere diameter was coarsest in the abdomen, but finest in the neck and back. A total of 2,178 DEGs were specifically screened among four body parts based on cashmere diameter. GO and KEGG analyses showed that these DEGs were mainly enriched in signaling pathways related to hair growth, such as MAPK signaling pathway and extracellular matrix-receptor interaction. The expression of MATN2 and CA12 were consistent with the phenotype of cashmere fineness in different body parts. CONCLUSION: The differences of cashmere fineness among different body parts of IMCGs were investigated through transcriptome and phenotype analysis, which provide a basis for understanding molecular regulation of cashmere growth in cashmere goats. ATN2 and CA12 have been validated as regulatory genes influencing the heterogeneity of cashmere fineness in various parts of IMCGs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".