iTRAQ-Based Quantitative Proteomics Identifies Potential Regulatory Proteins Involved in Chicken Eggshell Brownness
Bibliographic record
Abstract
Brown eggs are popular in many countries and consumers regard eggshell brownness as an important indicator of egg quality. However, the potential regulatory proteins and detailed molecular mechanisms regulating eggshell brownness have yet to be clearly defined. In the present study, we performed quantitative proteomics analysis with iTRAQ technology in the shell gland epithelium of hens laying dark and light brown eggs to investigate the candidate proteins and molecular mechanisms underlying variation in chicken eggshell brownness. The results indicated 147 differentially expressed proteins between these two groups, among which 65 and 82 proteins were significantly up-regulated in the light and dark groups, respectively. Functional analysis indicated that in the light group, the down-regulated iron-sulfur cluster assembly protein (Iba57) would decrease the synthesis of protoporphyrin IX; furthermore, the up-regulated protein solute carrier family 25 (mitochondrial carrier; adenine nucleotide translocator), member 5 (SLC25A5) and down-regulated translocator protein (TSPO) would lead to increased amounts of protoporphyrin IX transported into the mitochondria matrix to form heme with iron, which is supplied by ovotransferrin protein (TF). In other words, chickens from the light group produce less protoporphyrin IX, which is mainly used for heme synthesis. Therefore, the exported protoporphyrin IX available for eggshell deposition and brownness is reduced in the light group. The current study provides valuable information to elucidate variation of chicken eggshell brownness, and demonstrates the feasibility and sensitivity of iTRAQ-based quantitative proteomics analysis in providing useful insights into the molecular mechanisms underlying brown eggshell pigmentation.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".