Study of gene function based on spatial co-expression in a high-resolution mouse brain atlas

BACKGROUND: The Allen Brain Atlas (ABA) project systematically profiles three-dimensional high-resolution gene expression in postnatal mouse brains for thousands of genes. By unveiling gene behaviors at both the cellular and molecular levels, ABA is becoming a unique and comprehensive neuroscience data source for decoding enigmatic biological processes in the brain. Given the unprecedented volume and complexity of the in situ hybridization image data, data mining in this area is extremely challenging. Currently, the ABA database mainly serves as an online reference for visual inspection of individual genes; the underlying rich information of this large data set is yet to be explored by novel computational tools. In this proof-of-concept study, we studied the hypothesis that genes sharing similar three-dimensional expression profiles in the mouse brain are likely to share similar biological functions. RESULTS: In order to address the pattern comparison challenge when analyzing the ABA database, we developed a robust image filtering method, dubbed histogram-row-column (HRC) algorithm. We demonstrated how the HRC algorithm offers the sensitivity of identifying a manageable number of gene pairs based on automatic pattern searching from an original large brain image collection. This tool enables us to quickly identify genes of similar in situ hybridization patterns in a semi-automatic fashion and consequently allows us to discover several gene expression patterns with expression neighborhoods containing genes of similar functional categories. CONCLUSION: Given a query brain image, HRC is a fully automated algorithm that is able to quickly mine vast number of brain images and identify a manageable subset of genes that potentially shares similar spatial co-distribution patterns for further visual inspection. A three-dimensional in situ hybridization pattern, if statistically significant, could serve as a fingerprint of certain gene function. Databases such as ABA provide valuable data source for characterizing brain-related gene functions when armed with powerful image querying tools like HRC

Study of gene function based on spatial co-expression in a high-resolution mouse brain atlas.

BackgroundThe Allen Brain Atlas (ABA) project systematically profiles three-dimensional high-resolution gene expression in postnatal mouse brains for thousands of genes. By unveiling gene behaviors at both the cellular and molecular levels, ABA is becoming a unique and comprehensive neuroscience data source for decoding enigmatic biological processes in the brain. Given the unprecedented volume and complexity of the in situ hybridization image data, data mining in this area is extremely challenging. Currently, the ABA database mainly serves as an online reference for visual inspection of individual genes; the underlying rich information of this large data set is yet to be explored by novel computational tools. In this proof-of-concept study, we studied the hypothesis that genes sharing similar three-dimensional expression profiles in the mouse brain are likely to share similar biological functions.ResultsIn order to address the pattern comparison challenge when analyzing the ABA database, we developed a robust image filtering method, dubbed histogram-row-column (HRC) algorithm. We demonstrated how the HRC algorithm offers the sensitivity of identifying a manageable number of gene pairs based on automatic pattern searching from an original large brain image collection. This tool enables us to quickly identify genes of similar in situ hybridization patterns in a semi-automatic fashion and consequently allows us to discover several gene expression patterns with expression neighborhoods containing genes of similar functional categories.ConclusionGiven a query brain image, HRC is a fully automated algorithm that is able to quickly mine vast number of brain images and identify a manageable subset of genes that potentially shares similar spatial co-distribution patterns for further visual inspection. A three-dimensional in situ hybridization pattern, if statistically significant, could serve as a fingerprint of certain gene function. Databases such as ABA provide valuable data source for characterizing brain-related gene functions when armed with powerful image querying tools like HRC

Genes involved in the neuronal cAMP signaling pathway share a similar striatum-enriched hybridization profile to

<p><b>Copyright information:</b></p><p>Taken from "Study of gene function based on spatial co-expression in a high-resolution mouse brain atlas"</p><p>http://www.biomedcentral.com/1752-0509/1/19</p><p>BMC Systems Biology 2007;1():19-19.</p><p>Published online 16 Apr 2007</p><p>PMCID:PMC1863433.</p><p></p> Brain images were obtained from the ABA, GenePaint.org, and GENSAT databases. The striatum region is outlined in ABA-2175

Spatial gene expression of the gene variants suggests only the isoform represented by RefSeq NM 028755 may be involved in the striatal cAMP signaling pathway

<p><b>Copyright information:</b></p><p>Taken from "Study of gene function based on spatial co-expression in a high-resolution mouse brain atlas"</p><p>http://www.biomedcentral.com/1752-0509/1/19</p><p>BMC Systems Biology 2007;1():19-19.</p><p>Published online 16 Apr 2007</p><p>PMCID:PMC1863433.</p><p></p> The striatum region is outlined by a red box. Brain images were obtained from the ABA database and the tissue gene expression data were obtained from GNF SymAtlas

The IFIH1-A946T risk variant promotes diabetes in a sex-dependent manner

Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic islet β-cells are attacked by the immune system, resulting in insulin deficiency and hyperglycemia. One of the top non-synonymous single-nucleotide polymorphisms (SNP) associated with T1D is in the interferon-induced helicase C domain-containing protein 1 (IFIH1), which encodes an anti-viral cytosolic RNA sensor. This SNP results in an alanine to threonine substitution at amino acid 946 (IFIH1A946T) and confers an increased risk for several autoimmune diseases, including T1D. We hypothesized that the IFIH1A946T risk variant, (IFIH1R) would promote T1D pathogenesis by stimulating type I interferon (IFN I) signaling leading to immune cell alterations. To test this, we developed Ifih1R knock-in mice on the non-obese diabetic (NOD) mouse background, a spontaneous T1D model. Our results revealed a modest increase in diabetes incidence and insulitis in Ifih1R compared to non-risk Ifih1 (Ifih1NR) mice and a significant acceleration of diabetes onset in Ifih1R females. Ifih1R mice exhibited a significantly enhanced interferon stimulated gene (ISG) signature compared to Ifih1NR, indicative of increased IFN I signaling. Ifih1R mice exhibited an increased frequency of plasma cells as well as tissue-dependent changes in the frequency and activation of CD8+ T cells. Our results indicate that IFIH1R may contribute to T1D pathogenesis by altering the frequency and activation of immune cells. These findings advance our knowledge on the connection between the rs1990760 variant and T1D. Further, these data are the first to demonstrate effects of Ifih1R in NOD mice, which will be important to consider for the development of therapeutics for T1D

DataSheet_1_The IFIH1-A946T risk variant promotes diabetes in a sex-dependent manner.pdf

Type 1 diabetes (T1D) is an autoimmune disease in which pancreatic islet β-cells are attacked by the immune system, resulting in insulin deficiency and hyperglycemia. One of the top non-synonymous single-nucleotide polymorphisms (SNP) associated with T1D is in the interferon-induced helicase C domain-containing protein 1 (IFIH1), which encodes an anti-viral cytosolic RNA sensor. This SNP results in an alanine to threonine substitution at amino acid 946 (IFIH1A946T) and confers an increased risk for several autoimmune diseases, including T1D. We hypothesized that the IFIH1A946T risk variant, (IFIH1R) would promote T1D pathogenesis by stimulating type I interferon (IFN I) signaling leading to immune cell alterations. To test this, we developed Ifih1R knock-in mice on the non-obese diabetic (NOD) mouse background, a spontaneous T1D model. Our results revealed a modest increase in diabetes incidence and insulitis in Ifih1R compared to non-risk Ifih1 (Ifih1NR) mice and a significant acceleration of diabetes onset in Ifih1R females. Ifih1R mice exhibited a significantly enhanced interferon stimulated gene (ISG) signature compared to Ifih1NR, indicative of increased IFN I signaling. Ifih1R mice exhibited an increased frequency of plasma cells as well as tissue-dependent changes in the frequency and activation of CD8+ T cells. Our results indicate that IFIH1R may contribute to T1D pathogenesis by altering the frequency and activation of immune cells. These findings advance our knowledge on the connection between the rs1990760 variant and T1D. Further, these data are the first to demonstrate effects of Ifih1R in NOD mice, which will be important to consider for the development of therapeutics for T1D.</p

Human KCNQ5 de novo Mutations Underlie Epilepsy and Intellectual Disability

We identified six novel de novo human KCNQ5 variants in children with motor/language delay, intellectual disability (ID) and/or epilepsy by whole-exome sequencing. These variants comprised of two nonsense and four missense alterations, were functionally characterized by electrophysiology in HEK293/CHO cells, together with four previously reported KCNQ5 missense variants (Lehman, et al., 2017). Surprisingly, all eight missense variants resulted in gain-of-function (GOF) due to hyperpolarized voltage-dependence of activation or slowed deactivation kinetics, while the two nonsense variants were confirmed to be loss-of-function (LOF). One severe GOF allele (P369T) was tested and found to extend a dominant GOF effect to heteromeric KCNQ5/3 channels. Clinical presentations were associated with altered KCNQ5 channel gating: Milder presentations with LOF or smaller GOF shifts in voltage-dependence (DV50= ~-15 mV), and severe presentations with larger GOF shifts in voltage-dependence (DV50= ~-30 mV). To examine LOF pathogenicity, two Kcnq5 LOF mouse lines were created using CRISPR/Cas9. Both lines exhibited handling- and thermal-induced seizures, and abnormal cortical EEGs consistent with epileptiform activity. Our study thus provides evidence for in vivo KCNQ5 LOF pathogenicity and strengthens the contribution of both LOF and GOF mutations to global pediatric neurological impairment, including ID/epilepsy