Neurogenesis is the process by which undifferentiated progenitor cells develop into mature and functional neurons. Defects in neurogenesis are associated with neurodevelopmental and neuropsychiatric disorders; therefore, elucidating the molecular mechanisms underlying neurogenesis can advance our understanding of the pathophysiology of these disorders and facilitate the discovery of novel therapeutic targets. In this study, we performed a comparative transcriptomic analysis to identify common targets of the proneural transcription factors Neurog1/2 and Ascl1 during neurogenesis of human and mouse stem cells. We successfully identified C3orf70 as a novel common target gene of Neurog1/2 and Ascl1 during neurogenesis. Using in situ hybridization, we demonstrated that c3orf70a and c3orf70b, two orthologs of C3orf70, were expressed in the midbrain and hindbrain of zebrafish larvae. We generated c3orf70 knockout zebrafish using CRISPR/Cas9 technology and demonstrated that loss of c3orf70 resulted in significantly decreased expression of the mature neuron markers elavl3 and eno2. We also found that expression of irx3b, a zebrafish ortholog of IRX3 and a midbrain/hindbrain marker, was significantly reduced in c3orf70 knockout zebrafish. Finally, we demonstrated that neurobehaviors related to circadian rhythm and altered light–dark conditions were significantly impaired in c3orf70 knockout zebrafish. These results suggest that C3orf70 is involved in neural and neurobehavioral development and that defects in C3orf70 may be associated with midbrain/hindbrain-related neurodevelopmental and neuropsychiatric disorders.

Neurogenesis is the process by which undifferentiated progenitor cells convert into mature and functional neurons. Impairments in neurogenesis are associated with neurodevelopmental and neuropsychiatric disorders. Elucidating the molecular mechanisms underlying neurogenesis can stimulate further understanding of the pathophysiology and the discovery of novel therapeutic targets for these disorders. In this study, we performed a comparative transcriptomic analysis to reveal common targets of the proneural transcription factors, Neurog1/2 or Ascl1, during neurogenesis of human and mouse stem cells. We successfully identified C3orf70 as a novel common target of Neurog1/2 and Ascl1 during neurogenesis. Two orthologs of C3orf70 were expressed in the midbrain and hindbrain of zebrafish larvae. We generated c3orf70 knockout zebrafish using CRISPR/Cas9. The expression of the mature neuron markers elavl3 and eno2 was significantly decreased in c3orf70 knockout zebrafish. The expression of irx3b, a zebrafish ortholog of IRX3 and a midbrain/hindbrain marker, was significantly reduced in c3orf70 knockout zebrafish. Neurobehaviors related to circadian rhythm and changing light-dark conditions were significantly impaired in c3orf70 knockout zebrafish. These results suggested that C3orf70 is involved in neural and neurobehavioral development. Defects in C3orf70 may be associated with midbrain/hindbrain-related neurodevelopmental and neuropsychiatric disorders. Poster Sessions

Background: While the efficacy of selective serotonin reuptake inhibitor (SSRI) has been widely accepted in major depressive disorder (MDD), mechanisms of the therapeutic action and individual variation in the efficacy remain to be fully elucidated. The purpose of this study was to identify the SSRI-target network that might be relevant to the therapeutic mechanism and the efficacy. Methods: From a public database (Gene Expression Omnibus), we downloaded three transcriptome datasets (GSE43261, GSE54568, and GSE54571). GSE43261 analyzed the transcriptome response of fluoxetine, a SSRI, in dentate gyrus of fluoxetine-responsive and resistant mice model of MDD. GSE54568 and GSE54571 analyzed the transcriptome in dorsolateral prefrontal cortex and anterior cingulate cortex, respectively, of MDD patients. We analyzed these transcriptome datasets using weighted gene co-expression network analysis to identify networks significantly relevant to fluoxetine-responsive MDD mice and MDD patients. Results: We were able to identify three gene co-expression networks significantly relevant to fluoxetine-responsive MDD mice and MDD patients. Comparison of the three networks revealed a common network consisting of 26 genes, including BDNF and RGS4. Both BDNF and RGS4 have been related to the therapeutic effects of SSRI. Conclusions: The gene co-expression network identified in this study may be relevant to the therapeutic mechanism and the efficacy of SSRI.

Polycystic kidney disease (PKD) is characterized by cystic expansion of the kidneys, which can lead to kidney failure. PKD affects one in ∼ 1000 people worldwide and is commonly caused by defects in polycystin 1 (PKD1), polycystin 2 (PKD2), or polycystic kidney and hepatic disease 1 (PKHD1). However, there are variability in the symptom and progression of PKD caused by same mutation in these causative genes, suggesting that there may be many other genes involved in the pathogenesis of PKD. In this study, we performed comparative transcriptome analysis of three mammalian PKD datasets (PKD caused by knockout of PKD1, PKHD1, or AQP11) downloaded from a public database. We were able to identify two down-regulated and six up-regulated genes including osteopontin in common among the three different PKD models. In silico analysis of the promoters of these six up-regulated genes revealed that transcription factors HNF4 and RXRA might be involved in the up-regulation of these genes. Osteropontin, HNF4 and RXRA have been associated with the pathogenesis of PKD, supporting the validity of the approach used in this study. We now analyze the relationship between these dysregulated genes and the pathogenesis of PKD using zebrafish.

Background: While the efficacy of selective serotonin reuptake inhibitor (SSRI) has been widely accepted in major depressive disorder (MDD), mechanisms of the therapeutic action in the efficacy remain to be fully elucidated. The purpose of this study was to identify the SSRI-target network that might be relevant to the therapeutic mechanism. Methods: From a public database, we downloaded transcriptome datasets (MDD patients and model mice) and analyzed the transcriptome response of fluoxetine (FLX). We analyzed these transcriptome datasets using weighted gene co-expression network analysis to identify networks significantly relevant to FLX-responsive MDD mice and patients. In order to ascertain whether the identified network worked also in vivo, we performed in situ hybridization using zebrafish larvae treated FLX. Results: We were able to identify three gene co-expression networks significantly relevant to FLX-responsive MDD mice and patients. Comparison of the three networks revealed a common network consisting of 26 genes, including BDNF and RGS4. Both BDNF and RGS4 have been related to the therapeutic effects of SSRI. Conclusions: The gene co-expression network identified in this study may be relevant to the therapeutic mechanism and the efficacy of SSRI.