Association of CDH11 with Autism Spectrum Disorder Revealed by Matched-gene Co-expression Analysis and Mouse Behavioral Studies.
10.1007/s12264-021-00770-0
- Author:
Nan WU
1
;
Yue WANG
2
;
Jing-Yan JIA
1
;
Yi-Hsuan PAN
3
;
Xiao-Bing YUAN
4
Author Information
1. Key Laboratory of Brain Functional Genomics of Shanghai and the Ministry of Education, Institute of Brain Functional Genomics, School of Life Science and the Collaborative Innovation Center for Brain Science, East China Normal University, Shanghai, 200062, China.
2. Hussman Institute for Autism, Baltimore, 21201, USA.
3. Key Laboratory of Brain Functional Genomics of Shanghai and the Ministry of Education, Institute of Brain Functional Genomics, School of Life Science and the Collaborative Innovation Center for Brain Science, East China Normal University, Shanghai, 200062, China. yihsuanp@gmail.com.
4. Key Laboratory of Brain Functional Genomics of Shanghai and the Ministry of Education, Institute of Brain Functional Genomics, School of Life Science and the Collaborative Innovation Center for Brain Science, East China Normal University, Shanghai, 200062, China. xbyuan@brain.ecnu.edu.cn.
- Publication Type:Journal Article
- Keywords:
Autism spectrum disorder;
CDH11;
Gene co-expression analysis;
Matched-gene co-expression analysis
- MeSH:
Animals;
Autism Spectrum Disorder/genetics*;
Brain;
Cadherins/genetics*;
Gene Expression;
Mice;
Mice, Knockout
- From:
Neuroscience Bulletin
2022;38(1):29-46
- CountryChina
- Language:English
-
Abstract:
A large number of putative risk genes for autism spectrum disorder (ASD) have been reported. The functions of most of these susceptibility genes in developing brains remain unknown, and causal relationships between their variation and autism traits have not been established. The aim of this study was to predict putative risk genes at the whole-genome level based on the analysis of gene co-expression with a group of high-confidence ASD risk genes (hcASDs). The results showed that three gene features - gene size, mRNA abundance, and guanine-cytosine content - affect the genome-wide co-expression profiles of hcASDs. To circumvent the interference of these features in gene co-expression analysis, we developed a method to determine whether a gene is significantly co-expressed with hcASDs by statistically comparing the co-expression profile of this gene with hcASDs to that of this gene with permuted gene sets of feature-matched genes. This method is referred to as "matched-gene co-expression analysis" (MGCA). With MGCA, we demonstrated the convergence in developmental expression profiles of hcASDs and improved the efficacy of risk gene prediction. The results of analysis of two recently-reported ASD candidate genes, CDH11 and CDH9, suggested the involvement of CDH11, but not CDH9, in ASD. Consistent with this prediction, behavioral studies showed that Cdh11-null mice, but not Cdh9-null mice, have multiple autism-like behavioral alterations. This study highlights the power of MGCA in revealing ASD-associated genes and the potential role of CDH11 in ASD.
