Anti-ZNF24 (C-terminal) polyclonal antibody

Alopecia with mental retardation syndrome (APMR) is a rare autosomal recessive disorder characterized by total or partial absence of hair from the scalp and other parts of the body and associated with mental retardation. Previously, we have reported the mapping of two alopecia and mental retardation genes (APMR1 and APMR2) on human chromosome 3. In the present study, after excluding both of these loci through linkage analysis, a whole genome scan was performed by genotyping 396 polymorphic microsatellite markers located on 22 autosomes and the X and Y chromosomes. A disease locus was mapped to a 10.9 cM region, flanked by markers D18S866 and D18S811, on chromosome 18q11.2-q12.2. A maximum two-point LOD score of 3.03 at theta = 0.0 was obtained with marker D18S1102. Multipoint linkage analysis resulted in maximum LOD scores of 4.03 with several markers in the candidate region. According to the Rutgers combined linkage-physical map of the human genome (build 36) this region covers 12.17 Mb. DNA sequence analysis of nine candidate genes including DSC3, DSC1, DSG1, DSG4, DSG3, ZNF397, ZNF271, ZNF24 and ZNF396 did not reveal any sequence variants in the affected individuals of the family presented here.

Background: Joint modeling and analysis of phenotypic, genotypic and transcriptomic data have the potential to uncover the genetic control of gene activity and phenotypic variation, as well as shed light on the manner and extent of connectedness among these variables. Current studies mainly report associations, i.e. undirected connections among variables without causal interpretation. Knowledge regarding causal relationships among genes and phenotypes can be used to predict the behavior of complex systems, as well as to optimize management practices and selection strategies. Here, we performed a multistep procedure for inferring causal networks underlying carcass fat deposition and muscularity in pigs using multi-omics data obtained from an F-2 Duroc x Pietrain resource pig population. Results: We initially explored marginal associations between genotypes and phenotypic and expression traits through whole-genome scans, and then, in genomic regions with multiple significant hits, we assessed gene-phenotype network reconstruction using causal structural learning algorithms. One genomic region on SSC6 showed significant associations with three relevant phenotypes, off-midline10th-rib backfat thickness, loin muscle weight, and average intramuscular fat percentage, and also with the expression of seven genes, including ZNF24, SSX2IP, and AKR7A2. The inferred network indicated that the genotype affects the three phenotypes mainly through the expression of several genes. Among the phenotypes, fat deposition traits negatively affected loin muscle weight. Conclusions: Our findings shed light on the antagonist relationship between carcass fat deposition and lean meat content in pigs. In addition, the procedure described in this study has the potential to unravel gene-phenotype networks underlying complex phenotypes.