Редактирование: FGF6 (раздел)

==Publications==

{{medline-entry
|title=Genome-wide associations and detection of potential candidate genes for direct genetic and maternal genetic effects influencing dairy cattle body weight at different ages.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/30727969
|abstract=Body weight (BW) at different ages are of increasing importance in dairy cattle breeding schemes, because of their strong correlation with energy efficiency traits, and their impact on cow health, longevity and farm economy. In total, 15,921 dairy cattle from 56 large-scale test-herds with BW records were genotyped for 45,613 single nucleotide polymorphisms (SNPs). This dataset was used for genome-wide association studies (GWAS), in order to localize potential candidate genes for direct and maternal genetic effects on BW recorded at birth (BW0), at 2 to 3 months of age (BW23), and at 13 to 14 months of age (BW1314). The first 20 principal components ([[PC]]) of the genomic relationship matrix ([Formula: see text]) grouped the genotyped cattle into three clusters. In the statistical models used for GWAS, correction for population structure was done by including polygenic effects with various genetic similarity matrices, such as the pedigree-based relationship matrix ([Formula: see text]), the [Formula: see text]-matrix, the reduced [Formula: see text]-matrix LOCO (i.e. exclusion of the chromosome on which the candidate SNP is located), and LOCO plus chromosome-wide [[PC]]. Inflation factors for direct genetic effects using [Formula: see text] and LOCO were larger than 1.17. For [Formula: see text] and LOCO plus chromosome-wide [[PC]], inflation factors were very close to 1.0. According to Bonferroni correction, ten, two and seven significant SNPs were detected for the direct genetic effect on BW0, BW23, and BW1314, respectively. Seventy-six candidate genes contributed to direct genetic effects on BW with four involved in growth and developmental processes: [[FGF6]], [[FGF23]], [[TNNT3]], and [[OMD]]. For maternal genetic effects on BW0, only three significant SNPs (according to Bonferroni correction), and four potential candidate genes, were identified. The most significant SNP on chromosome 19 explained only 0.14% of the maternal de-regressed proof variance for BW0. For correction of population structure in GWAS, we suggest a statistical model that considers LOCO plus chromosome-wide [[PC]]. Regarding direct genetic effects, several SNPs had a significant effect on BW at different ages, and only two SNPs on chromosome 5 had a significant effect on all three BW traits. Thus, different potential candidate genes regulate BW at different ages. Maternal genetic effects followed an infinitesimal model.
|mesh-terms=* Aging
* Animals
* Body Weight
* Cattle
* Extracellular Matrix Proteins
* Female
* Fibroblast Growth Factors
* Genome-Wide Association Study
* Male
* Polymorphism, Single Nucleotide
* Proteoglycans
* Quantitative Trait Loci
* Troponin T

|full-text-url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366057
}}
{{medline-entry
|title=Regulation of skeletal muscle stem cells by fibroblast growth factors.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/28249356
|abstract=Fibroblast growth factors (FGFs) are essential for self-renewal of skeletal muscle stem cells (satellite cells) and required for maintenance and repair of skeletal muscle. Satellite cells express high levels of FGF receptors 1 and 4, low levels of FGF receptor 3, and little or no detectable FGF receptor 2. Of the multiple FGFs that influence satellite cell function in culture, [[FGF2]] and [[FGF6]] are the only members that regulate satellite cell function in vivo by activating ERK MAPK, p38α/β MAPKs, [[PI3]] kinase, PLCγ and STATs. Regulation of FGF signaling is complex in satellite cells, requiring Syndecan-4, a heparan sulfate proteoglycan, as well as ß1-integrin and fibronectin. During aging, reduced responsiveness to FGF diminishes satellite cell self-renewal, leading to impaired skeletal muscle regeneration and depletion of satellite cells. Mislocalization of ß1-integrin, reductions in fibronectin, and alterations in heparan sulfate content all contribute to reduced FGF responsiveness in satellite cells. How these cell surface proteins regulate satellite cell self-renewal is incompletely understood. Here we summarize the current knowledge, highlighting the role(s) for FGF signaling in skeletal muscle regeneration, satellite cell behavior, and age-induced muscle wasting. Developmental Dynamics 246:359-367, 2017. © 2017 Wiley Periodicals, Inc.
|mesh-terms=* Aging
* Animals
* Cell Self Renewal
* Fibroblast Growth Factors
* Humans
* Muscle, Skeletal
* Satellite Cells, Skeletal Muscle
* Signal Transduction
* Stem Cells
|keywords=* FGF
* regeneration
* satellite cell
* skeletal muscle
* stem cell
|full-text-url=https://sci-hub.do/10.1002/dvdy.24495
}}