Sequence characterization, tissue-specific expression and polymorphism of the porcine intestinal-type fatty acid binding protein gene
Bibliographic record
Abstract
The intestinal fatty-acid-binding protein (IFABP) shows binding specificity for long-chain fatty acids and is proposed to be involved in the uptake of dietary fatty acids and their intracellular transport. In this study, the full-length cDNA of porcine I-FABP gene was obtained by the rapid amplification of cDNA ends (RACE). The nucleotide sequence and the predicted protein sequence share high sequence identity with its mammalian counterparts. Northern hybridization and semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR) revealed that porcine I-FABP is expressed in all 12 tissues studied (heart, brain, kidney, skeletal muscle, testis, liver, skin, small intestine, fat, stomach, lymph and pituitary), but a transcript of approximate 620 bp is more abundant in small intestine than in other tissues. The full-length genomic DNA of the porcine I-FABP gene was amplified by PCR. The coding region of the pig IFABP gene is organized in four exons and spans an approximate 3.5-kb genomic region. Comparative sequencing of four pig breeds revealed a single nucleotide polymorphism (SNP) within exon 1 of which an A→G substitution at codon 21 changes a codon for lysine into a codon for arginine. The distribution of allele and genotype frequencies differed significantly between indigenous Chinese Zang, Dahe and Yanan breeds (higher frequencies of A and AA) and Western Large White breed (higher frequencies of G and GG, P < 0.01). The association analysis using five pig populations suggested that A21G polymorphism was associated with intramuscular fat content, indicating that the I-FABP gene A21G SNP can be a potential molecular marker for intramuscular fat content. Key words: Association analysis, cloning, gene expression, I-FABP gene, polymorphism, porcine
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".