ReviewInternational journal of molecular sciences2016
Nutrigenomics and Beef Quality: A Review about Lipogenesis.
Review in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed, 109 citations in OpenAlex.
- Prenatal Exposure to Different Nitrogen Supplementation Strategies in Beef Cows Enhances Foetal Growth and Induces Transcriptional Adaptations in Offspring Skeletal Muscle.Journal of animal physiology and animal nutrition · 2026Article
- Effects of fattening strategies on carcass traits, meat quality, fatty acid composition, and oxidative stability ofFood chemistry: X · 2026Article
- Early-life vitamin A supplementation modulates the skeletal muscle transcriptome and intramuscular fat deposition in feedlot-finished beef steers.Journal of animal science · 2025Article
- The expression of genes in different sites of gut tract regulates the meat quality of semitendinosus muscle in sheep and goats.Frontiers in veterinary science · 2025Article
- Gene expression profiles in specific skeletal muscles and meat quality characteristics of sheep and goats.Scientific data · 2024Article
- Comprehensive Evaluation of Nutritional, Physicochemical, and Volatile Profiles of Selected Bovine Head Muscles.Foods (Basel, Switzerland) · 2024Article
- Muscle tissue transcriptome of F1 Angus-Nellore bulls and steers feedlot finished: impacts on intramuscular fat deposition.BMC genomics · 2024Article
- DNA Imprinting and Differentially Expressed Genes inEpigenomes · 2024Article
- Performance, Carcass Traits, and Meat Fatty Acid Profile of Post-Weaning and Finishing Zebu Steers on Tropical Pasture with Three Low-Intake Supplementation Strategies.Animals : an open access journal from MDPI · 2024Article
- - Invited Review - Translational gut microbiome research for strategies to improve beef cattle production sustainability and meat quality.Animal bioscience · 2024Article
- Maternal protein supplementation during mid-gestation improves offspring performance and metabolism in beef cows.Journal of animal science · 2024Article
- Long non-coding RNA (LncRNA) and epigenetic factors: their role in regulating the adipocytes in bovine.Frontiers in genetics · 2024Review
- Ruminal microbiota and muscle metabolome characteristics of Tibetan plateau yaks fed different dietary protein levels.Frontiers in microbiology · 2024Article
- Development of nutrigenomic based precision management model for Hanwoo steers.Journal of animal science and technology · 2023Article
- Effect of Cow-Calf Supplementation on Gene Expression, Processes, and Pathways Related to Adipogenesis and Lipogenesis inMetabolites · 2023Article
- Low lysine stimulates adipogenesis through ZFP423 upregulation in bovine stromal vascular cells.Journal of animal science and technology · 2022Article
- The Effects of Prenatal Diet on Calf Performance and Perspectives for Fetal Programming Studies: A Meta-Analytical Investigation.Animals : an open access journal from MDPI · 2022Article
- Performance and muscle lipogenesis of calves born to Nellore cows with different residual feed intake classification.PloS one · 2022Article
- Main regulatory factors of marbling level in beef cattle.Veterinary and animal science · 2021Article
- Genome-wide identification and analysis of long noncoding RNAs in longissimus muscle tissue from Kazakh cattle and Xinjiang brown cattle.Animal bioscience · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of the present review is to discuss the results of published studies that show how nutrition affects the expression of genes involved in lipid metabolism and how diet manipulation might change marbling and composition of fat in beef. Several key points in the synthesis of fat in cattle take place at the molecular level, and the association of nutritional factors with the modulation of this metabolism is one of the recent targets of nutrigenomic research. Within this context, special attention has been paid to the study of nuclear receptors associated with fatty acid metabolism. Among the transcription factors involved in lipid metabolism, the peroxisome proliferator-activated receptors (PPARs) and sterol regulatory element-binding proteins (SREBPs) stand out. The mRNA synthesis of these transcription factors is regulated by nutrients, and their metabolic action might be potentiated by diet components and change lipogenesis in muscle. Among the options for dietary manipulation with the objective to modulate lipogenesis, the use of different sources of polyunsaturated fatty acids, starch concentrations, forage ratios and vitamins stand out. Therefore, special care must be exercised in feedlot feed management, mainly when the goal is to produce high marbling beef.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.