Identification of a novel Shank2 transcriptional variant in Shank2 knockout mouse model of autism spectrum disorder

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders that are highly heterogeneous in clinical symptoms as well as etiologies. Mutations in SHANK2 are associated with ASD and accordingly, Shank2 knockout mouse shows ASD-like behavioral phenotypes, including social deficits. Intriguingly, two lines of Shank2 knockout (KO) mouse generated by deleting different exons (exon 6–7 or exon 7) showed distinct cellular phenotypes. Previously, we compared gene expressions between Shank2 KOs lacking exon 6–7 (e6–7 KO) and KOs lacking exon 7 (e7 KO) by performing RNA-seq. In this study, we expanded transcriptomic analyses to identify novel transcriptional variants in the KO mice. We found prominent expression of a novel exon (exon 4′ or e4) between the existing exons 4 and 5 in the Shank2 e6–7 KO model. Expression of the transcriptional variant harboring this novel exon was confirmed by RT-PCR and western blotting. These findings suggest that the novel variant may function as a modifier gene, which contributes to the differences between the two Shank2 mutant lines. Furthermore, our result further represents an example of genetic compensation that may lead to phenotypic heterogeneity among ASD patients with mutations in the same gene.This work was supported by the National Honor Scientist Program (NRF2012R1A3A1050385) through a grant to B.-K.K.; NRF-2017M3C7A1026959 to Y.-S.L.; NRF-2018H1A2A1061381 to G.P.; NRF-2017M3C9A6047623 to J.-H.L

Elevated contextual fear memory by SIRT6 depletion in excitatory neurons of mouse forebrain

Abstract A class of NAD-dependent protein deacetylases, the Sirtuin (SIRT) family of proteins is involved in aging, cell survival, and neurodegeneration. Recently, SIRT proteins, including SIRT6, have been reported to be important in learning and memory. However, the role of SIRT6 in excitatory brain neurons in cognitive behaviors is not well characterized. We investigated how cognitive behaviors are affected by genetic SIRT6 depletion in excitatory neurons in the mouse forebrain. We generated a conditional knockout (cKO) mouse line by mating two transgenic lines, Floxed SIRT6 and CaMKIIa-Cre. SIRT6 was thus deleted by Cre recombinase in CaMKIIa-expressing excitatory neurons. We performed cognitive behavioral tests, focusing on learning and memory, including contextual fear conditioning and Morris-water maze. The freezing level of SIRT6 cKO before the fear conditioning was comparable to that of wild-type littermate controls, while the freezing level after the conditioning was higher in SIRT6 cKO mice. In contrast, the mice showed normal spatial learning and memory in the Morris-water maze. In addition, anxiety and locomotion were also normal in SIRT6 cKO mice. SIRT6 genetic depletion enhanced contextual fear memory without affecting spatial memory. Since a previous report showed that overexpression of SIRT6 reduced contextual fear memory, our results suggest that the expression level of SIRT6 bi-directionally regulates contextual fear memory in mice

KOSAC: A Full-fledged Korean Sentiment Analysis Corpus

This paper aims to introduce the Korean Sentiment Analysis Corpus named KOSAC. KOSAC is a corpus consisting of 332 news articles taken from the Sejong Syntactic Parsed Corpus. These sentences have been manually-tagged for sentimental features. The corpus includes 7,713 sentence subjectivity tags and 17,615 opinionated expression tags based on the annotation scheme called KSML which reflects the characteristics of the Korean language. The results of sentence subjectivity and polarity classification experiements using the corpus show the wide possibilities of application the KSML scheme and the tagged information of the KOSAC comprehensively to other corpus. What is innovative about our work is that it pulls together both the concept of private states and nested-sources into one linguistic annotation scheme. We believe that this corpus could be used by researchers as a gold standard for various NLP tasks related to sentiment analysis.

Neuronal mechanisms and circuits underlying repetitive behaviors in mouse models of autism spectrum disorder

Autism spectrum disorder (ASD) refers to a broad spectrum of neurodevelopmental disorders characterized by three central behavioral symptoms: impaired social interaction, impaired social communication, and restricted and repetitive behaviors. However, the symptoms are heterogeneous among patients and a number of ASD mouse models have been generated containing mutations that mimic the mutations found in human patients with ASD. Each mouse model was found to display a unique set of repetitive behaviors. In this review, we summarize the repetitive behaviors of the ASD mouse models and variations found in their neural mechanisms including molecular and electrophysiological features. We also propose potential neuronal mechanisms underlying these repetitive behaviors, focusing on the role of the cortico-basal ganglia-thalamic circuits and brain regions associated with both social and repetitive behaviors. Further understanding of molecular and circuitry mechanisms of the repetitive behaviors associated with ASD is necessary to aid the development of effective treatments for these disorders

Abstract Schema and constraints-based matching and merging of Topic Maps

In this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps. Our multi-strategic matching approach consists of a linguistic module and a Topic Map constraints-based module. A linguistic module computes similarities between concepts using morphological analysis, string normalization and tokenization and language-dependent heuristics. A Topic Map constraints-based module takes advantage of several Topic Maps-dependent techniques such as a topic property-based matching, a hierarchy-based matching, and an association-based matching. This is a composite matching procedure and need not generate a cross-pair of all topics from the ontologies because unmatched pairs of topics can be removed by characteristics and constraints of the Topic Maps. Merging between Topic Maps follows the matching operations. We set up the MERGE function to integrate two Topic Maps into a new Topic Map, which satisfies such merge requirements as entity preservation, property preservation, relation preservation, and conflict resolution. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Wikipedia philosophy ontology as input ontologies. Our experiments show that the automatically generated matching results conform to the outputs generated manually by domain experts and can be of great benefit to the following merging operations. Ó 2006 Published by Elsevier Ltd