Dataset Information

Computational derivation of a molecular framework for hair follicle biology from disease genes.

ABSTRACT: Knowledge about genetic drivers of disease increases the efficiency of interpreting patient DNA sequence and helps to identify and prioritize biological points of intervention. Discoveries of genes with single mutations exerting substantial phenotypic impact reliably provide new biological insight, although such approaches tend to generate knowledge that is disjointed from the complexity of biological systems governed by elaborate networks. Here we sought to facilitate diagnostic sequencing for hair disorders and assess the underlying biology by compiling an archive of 684 genes discovered in studies of monogenic disorders and identifying molecular annotations enriched by them. To demonstrate utility for this dataset, we performed two data driven analyses. First, we extracted and analyzed data implicating enriched signaling pathways and identified previously unrecognized contributions from Hippo signaling. Second, we performed hierarchical clustering on the entire dataset to investigate the underlying causal structure of hair disorders. We identified 35 gene clusters representing genetically derived biological modules that provide a foundation for the development of a new disease taxonomy grounded in biology, rather than clinical presentations alone. This Resource will be useful for diagnostic sequencing in patients with diseases affecting the hair follicle, improved characterization of hair follicle biology, and methods development in precision medicine.

SUBMITTER: Severin RK

PROVIDER: S-EPMC5701154 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Computational derivation of a molecular framework for hair follicle biology from disease genes.

Severin Rachel K RK Li Xinwei X Qian Kun K Mueller Andreas C AC Petukhova Lynn L

Scientific reports 20171124 1

Knowledge about genetic drivers of disease increases the efficiency of interpreting patient DNA sequence and helps to identify and prioritize biological points of intervention. Discoveries of genes with single mutations exerting substantial phenotypic impact reliably provide new biological insight, although such approaches tend to generate knowledge that is disjointed from the complexity of biological systems governed by elaborate networks. Here we sought to facilitate diagnostic sequencing for ...[more]

PMID: 29176608

Similar Datasets

Project description:Hu sheep lambskin comes from a specific breed of sheep of China. Hu sheep are considered a protected breed by the Chinese government. The hair follicles of these sheep have three types of waves, large, medium, and small. There are only few histological reports of Hu sheep lambskin, and there are no modern molecular or biological studies, so the molecular mechanisms underlying the formation of hair follicles with different patterns are not currently known. The aim of this article was to study the molecular mechanism of the formation of these types of hair follicles in Hu sheep. Histological and microscopic analysis indicated that the number of follicles with small waves was not significantly higher than the number of follicles with large waves (P>0.05). The diameters of primary and secondary small-wave follicles were significantly smaller than those of large-wave follicles (P<0.05; P<0.01). The ratio between the number primary follicles and the number of secondary follicles was significantly higher among small-wave follicles than among large-wave follicles (P<0.05). Differentially expressed genes in the skin tissue were screened using an Agilent gene chip and RT-PCR. Differential expression analysis revealed 3 groups of large waves and small waves; 1067, 2071, and 3879 differentially expressed genes; and 137 genes common to all 3 groups. Differentially expressed genes were classified using gene ontology. They were found to be mainly involved in cell differentiation, proliferation, apoptosis, growth, immune response, and ion transport. RT-PCR results of 4 differentially expressed genes were consistent with gene chip results. Combined with related literature, our results suggest that BMP7, MMP2, SNAI1, SFXN1, CDKNIC, MT3, and POU1F1 may have important effects on the formation of large-wave and small-wave hair follicles. This study may enrich knowledge of hair follicle development, and may identify the genes responsible for the formation of hair follicles with different patterns.

Dataset Information

Computational derivation of a molecular framework for hair follicle biology from disease genes.

Publications

Computational derivation of a molecular framework for hair follicle biology from disease genes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets