Miyako, K. | Search bioRxiv

bioRxiv2023

TCF7L2: a potential key regulator of antidepressant effects on hippocampal astrocytes in depression model mice

AimClinical and preclinical studies suggest that hippocampal astrocyte dysfunction is involved in the pathophysiology of depression; however, the underlying molecular mechanisms remain unclear. Here, we attempted to identify the hippocampal astrocytic transcripts associated with antidepressant effects in a mouse model of depression. MethodsWe used a chronic corticosterone-induced mouse model of depression to assess the behavioral effects of amitriptyline, a tricyclic antidepressant. Hippocampal astrocytes were isolated using fluorescence-activated cell sorting, and RNA sequencing was performed to evaluate the transcriptional profiles associated with depressive effects and antidepressant responses. ResultsDepression model mice exhibited typical depression-like behaviors that improved after amitriptyline treatment; the depression group mice also had significantly reduced GFAP-positive astrocyte numbers in hippocampal subfields. Comprehensive transcriptome analysis of hippocampal astrocytes showed opposing responses to amitriptyline in depression group and control mice, suggesting the importance of using the depression model. Transcription factor 7 like 2 (TCF7L2) was the only upstream regulator gene altered in depression model mice and restored in amitriptyline-treated depression model mice. In fact, TCF7L2 expression was significantly decreased in the depression group. The level of TCF7L2 long non-coding RNA, which controls mRNA expression of the TCF7L2 gene, was also significantly decreased in this group and recovered after amitriptyline treatment. The Gene Ontology biological processes associated with astrocytic TCF7L2 included proliferation, differentiation, and cytokine production. ConclusionWe identified TCF7L2 as a gene associated with depression- and antidepressant-like behaviors in response to amitriptyline in hippocampal astrocytes. Our findings could provide valuable insights into the mechanism of astrocyte-mediated antidepressant effects.

neuroscience↗

bioRxiv2022

Exome-wide benchmark of difficult-to-sequence regions using short-read next-generation DNA sequencing

Next-generation DNA sequencing (NGS) in short-read mode has been recently used for genetic testing in various clinical settings. NGS data accuracy is crucial in clinical settings, and several reports regarding quality control of NGS data, focusing mostly on establishing NGS sequence read accuracy, have been published thus far. Variant calling is another critical source of NGS errors that remains mostly unexplored despite its established significance. In this study, we used a machine-learning-based method to establish an exome-wide benchmark of difficult-to-sequence regions using 10 genome sequence features on the basis of real-world NGS data accumulated in The Genome Aggregation Database (gnomAD) of the human reference genome sequence (GRCh38/hg38). We used the obtained metrics, designated "UNMET score," along with other lines of structural information of the human genome to identify difficult-to-sequence genomic regions using conventional NGS. Thus, the UNMET score could provide appropriate caveats to address potential sequential errors in protein-coding exons of the human reference genome sequence GRCh38/hg38 in clinical sequencing.

genomics↗