Ask about this productRelated genes to: ATXN7L2 antibody
- Gene:
- ATXN7L2 NIH gene
- Name:
- ataxin 7 like 2
- Previous symbol:
- -
- Synonyms:
- MGC46534, FLJ00381
- Chromosome:
- 1p13.3
- Locus Type:
- gene with protein product
- Date approved:
- 2004-08-18
- Date modifiied:
- 2016-10-05
Related products to: ATXN7L2 antibody
Related articles to: ATXN7L2 antibody
- Chronotype, a manifestation of circadian rhythms, affects morning or evening preferences and ease of getting up. This study explores the genetic basis of morning chronotype and ease of getting up, focusing on the G-protein-coupled receptor locus, GPR61. - Source: PubMed
Publication date: 2025/05/18
Tchio CynthiaWilliams Jonathan STaylor HermanOllila Hanna MSaxena Richa - Chronotype, a manifestation of circadian rhythms, affects morning or evening preferences and ease of getting-up. This study explores the genetic basis of morning chronotype and ease of getting-up, focusing on the G protein-coupled receptor locus, GPR61. - Source: PubMed
Publication date: 2024/11/25
Tchio CynthiaWilliams JonathanTaylor HermanOllila HannaSaxena Richa - Polyglutamine (polyQ) spinocerebellar ataxias (SCAs) comprise a group of autosomal dominant neurodegenerative disorders caused by (CAG/CAA) expansions. The elongated stretches of adjacent glutamines alter the conformation of the native proteins inducing neurotoxicity, and subsequent motor and neurological symptoms. Although the etiology and neuropathology of most polyQ SCAs have been extensively studied, only a limited selection of therapies is available. Previous studies on SCA1 demonstrated that ATXN1L, a human duplicated gene of the disease-associated ATXN1, alleviated neuropathology in mice models. Other SCA-associated genes have paralogs (i.e., copies at different chromosomal locations derived from duplication of the parental gene), but their functional relevance and potential role in disease pathogenesis remain unexplored. Here, we review the protein homology, expression pattern, and molecular functions of paralogs in seven polyQ dominant ataxias-SCA1, SCA2, MJD/SCA3, SCA6, SCA7, SCA17, and DRPLA. Besides ATXN1L, we highlight ATXN2L, ATXN3L, CACNA1B, ATXN7L1, ATXN7L2, TBPL2, and RERE as promising functional candidates to play a role in the neuropathology of the respective SCA, along with the parental gene. Although most of these duplicates lack the (CAG/CAA) region, if functionally redundant, they may compensate for a partial loss-of-function or dysfunction of the wild-type genes in SCAs. We aim to draw attention to the hypothesis that paralogs of disease-associated genes may underlie the complex neuropathology of dominant ataxias and potentiate new therapeutic strategies. - Source: PubMed
Publication date: 2023/10/16
Felício Danieladu Mérac Tanguy RubatAmorim AntónioMartins Sandra - The identification of gene expression-based biomarkers for major depressive disorder (MDD) continues to be an important challenge. In order to identify candidate biomarkers and mechanisms, we apply statistical and machine learning feature selection to an RNA-Seq gene expression dataset of 78 unmedicated individuals with MDD and 79 healthy controls. We identify 49 genes by LASSO penalized logistic regression and 45 genes at the false discovery rate threshold 0.188. The MDGA1 gene has the lowest P-value (4.9e-5) and is expressed in the developing brain, involved in axon guidance, and associated with related mood disorders in previous studies of bipolar disorder (BD) and schizophrenia (SCZ). The expression of MDGA1 is associated with age and sex, but its association with MDD remains significant when adjusted for covariates. MDGA1 is in a co-expression cluster with another top gene, ATXN7L2 (ataxin 7 like 2), which was associated with MDD in a recent GWAS. The LASSO classification model of MDD includes MDGA1, and the model has a cross-validation accuracy of 79%. Another noteworthy top gene, IRF2BPL, is in a close co-expression cluster with MDGA1 and may be related to microglial inflammatory states in MDD. Future exploration of MDGA1 and its gene interactions may provide insights into mechanisms and heterogeneity of MDD. - Source: PubMed
Publication date: 2022/10/10
Li Yijie JamieKresock ElizabethKuplicki RayusSavitz JonathanMcKinney Brett A - As the main product of livestock, muscle itself plays an irreplaceable role in maintaining animal body movement and regulating metabolism. Therefore, it is of great significance to explore its growth, development and regeneration to improve the meat yield and quality of livestock. In this study, we attempted to use RNA-seq and ATAC-seq techniques to identify differentially expressed genes (DEGs) specifically expressed in bovine skeletal muscle as potential candidates for studying the regulatory mechanisms of muscle development. Microarray data from 8 tissue samples were selected from the GEO database for analysis. First, we obtained gene modules related to each tissue through WGCNA analysis. Through Gene Ontology (GO) functional annotation, the module of lightyellow (ME) was closely related to muscle development, and 213 hub genes were screened as follow-up research targets. Further, the difference analysis showed that, except for PREB, all other candidate hub genes were up-regulated (muscle group vs. other-group). ATAC-seq analysis showed that muscle-specific accessible chromatin regions were mainly located in promoter of genes related to muscle structure development (GO:0061061), muscle cell development (GO:0055001) and muscle system process (GO:0003012), which were involved in cAMP, CGMP-PKG, MAPK, and other signaling pathways. Next, we integrated the results of RNA-seq and ATAC-seq analysis, and 54 of the 212 candidate hub genes were identified as key regulatory genes in skeletal muscle development. Finally, through motif analysis, 22 of the 54 key genes were found to be potential target genes of transcription factor MEF2C. Including , and . This provides a potential reference for studying the molecular mechanism of skeletal muscle development in mammals. - Source: PubMed
Publication date: 2022/08/11
Wang JianfangLi BingzhiYang XinranLiang ChengchengRaza Sayed Haidar AbbasPan YuetingZhang KeZan Linsen