ArticleTropical animal health and production2020
Bioinformatics analysis of candidate genes for milk production traits in water buffalo (Bubalus bubalis).
Article in Tropical animal health and production, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Evaluation of Ovsynch versus modified Ovsynch program on pregnancy rate in water buffaloes: a meta-analysis.Tropical animal health and production · 2021Pooled it
- TWAS revealed significant causal loci for milk production and its composition in Murrah buffaloes.Scientific reports · 2023Article
- Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle.Animals : an open access journal from MDPI · 2021Article
- Milk production potential and reproductive performance of Egyptian buffalo cows.Tropical animal health and production · 2021Article
- Identification, molecular characteristics, and tissue differential expression ofArchives animal breeding · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Water buffalo (Bubalus bubalis) is an important livestock species in developing countries due to its contribution to meat, milk production, and a certain form of labor. However, the genetic potential of buffalo milk production traits has not been fully exploited. To date, 516 candidate genes associated with milk production traits of buffalo have been identified. The present study aimed to explore the possible molecular mechanisms underlying milk production traits of this species through functional genomics analysis of these candidate genes by using different bioinformatics tools. Gene ontology (GO) analysis indicated that these candidate genes were associated with complex biological processes, such as cell proliferation and mitotic nuclear division. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis demonstrated that these candidate genes were enriched in multiple signaling pathways, such as AMPK, ErbB, Toll-like receptor, and Jak-STAT. In addition, one function module consisting of 57 nodes and 139 edges were identified from the protein-protein interaction (PPI) network. GO analysis showed that the 57 candidate genes in this function module were enriched in three main biological processes, including homeostasis, metabolism, and cell response. These three distinct biological processes are well known for regulating mammary gland activities, which explained clearly the mechanism underlying milk production traits. This study provides a novel perspective for better understanding of the biological processes linked with milk production traits. This knowledge is conducive to the improvement of milk yield and composition of this species.
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.