scholarly journals Identification of de novo mutations in the Chinese ASD cohort via whole-exome sequencing unveils brain regions implicated in autism

2021 ◽  
Author(s):  
Bo Yuan ◽  
Mengdi Wang ◽  
Xinran Wu ◽  
Peipei Cheng ◽  
Ran Zhang ◽  
...  
Keyword(s):  
Human Brain ◽  
De Novo ◽  
Brain Regions ◽  
Imaging Data ◽  
De Novo Mutations ◽  
Genetic Studies ◽  
Single Cell Sequencing ◽  
Genome Wide ◽  
Whole Exome ◽  
Brain Imaging Data

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and repetitive behaviors. Although hundreds of ASD risk genes, implicated in synaptic formation and transcriptional regulation, have been identified through human genetic studies, the East Asian ASD cohorts is still under-represented in the genome-wide genetic studies. Here we performed whole-exome sequencing on 369 ASD trios including probands and unaffected parents of Chinese origin. Using a joint-calling analytical pipeline based on GATK toolkits, we identified numerous de novo mutations including 55 high-impact variants and 165 moderate-impact variants, as well as de novo copy number variations containing known ASD-related genes. Importantly, combining with single-cell sequencing data from the developing human brain, we found that expression of genes with de novo mutations were specifically enriched in pre-, post-central gyrus (PRC, PC) and banks of superior temporal (BST) regions in the human brain. By further analyzing the brain imaging data with ASD and health controls, we found that the gray volume of the right BST in ASD patients significantly decreased comparing to health controls, suggesting the potential structural deficits associated with ASD. Finally, we found that there was decrease in the seed-based functional connectivity (FC) between BST/PC/PRC and sensory areas, insula, as well as frontal lobes in ASD patients. This work indicated that the combinatorial analysis with genome-wide screening, single-cell sequencing and brain imaging data would reveal brain regions contributing to etiology of ASD.

scholarly journals Identification of de novo mutations in the Chinese ASD cohort via whole-exome sequencing unveils brain regions implicated in autism

2021 ◽  
Author(s):  
Bo Yuan ◽  
Mengdi Wang ◽  
Xinran Wu ◽  
Peipei Cheng ◽  
Ran Zhang ◽  
...  
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
De Novo ◽  
Brain Regions ◽  
Imaging Data ◽  
Genetic Studies ◽  
Single Cell Sequencing ◽  
Genome Wide ◽  
Whole Exome ◽  
Brain Imaging Data

Abstract Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by deficits in social interactions and repetitive behaviors. Although hundreds of ASD risk genes, implicated in synaptic formation and transcriptional regulation, have been identified through human genetic studies, the East Asian ASD cohorts is still under-represented in the genome-wide genetic studies. Here we performed whole-exome sequencing on 369 ASD trios including probands and unaffected parents of Chinese origin. Using a joint-calling analytical pipeline based on GATK toolkits, we identified numerous de novo mutations including 55 high-impact variants and 165 moderate-impact variants, as well as de novo copy number variations containing known ASD-related genes. Importantly, combining with single-cell sequencing data from the developing human brain, we found that expression of genes with de novo mutations were specifically enriched in pre-, post-central gyrus (PRC, PC) and banks of superior temporal (BST) regions in the human brain. By further analyzing the brain imaging data with ASD and health controls, we found that the gray volume of the right BST in ASD patients significantly decreased comparing to health controls, suggesting the potential structural deficits associated with ASD. Finally, we found that there was decrease in the seed-based functional connectivity (FC) between BST/PC/PRC and sensory areas, insula, as well as frontal lobes in ASD patients. This work indicated that the combinatorial analysis with genome-wide screening, single-cell sequencing and brain imaging data would reveal brain regions contributing to etiology of ASD.

scholarly journals Identification of a β-Arrestin 2 Mutation Related to Autism by Whole-Exome Sequencing

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yunfei Tang ◽  
Yamei Liu ◽  
Lei Tong ◽  
Shini Feng ◽  
Dongshu Du ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Developmental Stages ◽  
De Novo ◽  
Repetitive Behavior ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Potential Contribution ◽  
De Novo Mutations ◽  
Whole Exome

Autism spectrum disorder (ASD) is a complex neurological disease characterized by impaired social communication and interaction skills, rigid behavior, decreased interest, and repetitive activities. The disease has a high degree of genetic heterogeneity, and the genetic cause of ASD in many autistic individuals is currently unclear. In this study, we report a patient with ASD whose clinical features included social interaction disorder, communication disorder, and repetitive behavior. We examined the patient’s genetic variation using whole-exome sequencing technology and found new de novo mutations. After analysis and evaluation, ARRB2 was identified as a candidate gene. To study the potential contribution of the ARRB2 gene to the human brain development and function, we first evaluated the expression profile of this gene in different brain regions and developmental stages. Then, we used weighted gene coexpression network analysis to analyze the associations between ARRB2 and ASD risk genes. Additionally, the spatial conformation and stability of the ARRB2 wild type and mutant proteins were examined by simulations. Then, we further established a mouse model of ASD. The results showed abnormal ARRB2 expression in the mouse ASD model. Our study showed that ARRB2 may be a risk gene for ASD, but the contribution of de novo ARRB2 mutations to ASD is unclear. This information will provide references for the etiology of ASD and aid in the mechanism-based drug development and treatment.

scholarly journals Schizophrenia risk conferred by protein-coding de novo mutations

2018 ◽  
Author(s):  
Daniel P. Howrigan ◽  
Samuel A. Rose ◽  
Kaitlin E. Samocha ◽  
Menachem Fromer ◽  
Felecia Cerrato ◽  
...  
Keyword(s):  
Risk Factors ◽  
De Novo ◽  
Single Gene ◽  
Epileptic Encephalopathy ◽  
Evolutionary Constraint ◽  
De Novo Mutations ◽  
Protein Coding ◽  
Genome Wide ◽  
Whole Exome ◽  
Affected Parent

AbstractProtein-coding de novo mutations (DNMs) in the form of single nucleotide changes and short insertions/deletions are significant genetic risk factors for autism, intellectual disability, developmental delay, and epileptic encephalopathy. In contrast, the burden of DNMs has thus far only had a modest documented impact on schizophrenia (SCZ) risk. Here, we analyze whole-exome sequence from 1,695 SCZ affected parent-offspring trios from Taiwan along with DNMs from 1,077 published SCZ trios to better understand the contribution of coding DNMs to SCZ risk. Among 2,772 SCZ affected probands, the increased burden of DNMs is modest. Gene set analyses show that the modest increase in risk from DNMs in SCZ probands is concentrated in genes that are either highly brain expressed, under strong evolutionary constraint, and/or overlap with genes identified as DNM risk factors in other neurodevelopmental disorders. No single gene meets the criteria for genome-wide significance, but we identify 16 genes that are recurrently hit by a protein-truncating DNM, which is a 3.15-fold higher rate than mutation model expectation of 5.1 genes (permuted 95% CI=1-10 genes, permuted p=3e-5). Overall, DNMs explain only a small fraction of SCZ risk, and this risk is polygenic in nature suggesting that coding variation across many different genes will be a risk factor for SCZ in the population.

scholarly journals A Systematic Review on Extreme Phenotype Strategies to Search for Rare Variants in Genetic Studies of Complex Disorders

2020 ◽  
Author(s):  
Sana Amanat ◽  
Teresa Requena ◽  
Jose Antonio Lopez-Escamez
Keyword(s):  
Systematic Review ◽  
Candidate Genes ◽  
Rare Variants ◽  
De Novo ◽  
Complex Diseases ◽  
De Novo Mutations ◽  
Genetic Studies ◽  
Complex Disorders ◽  
Extreme Phenotype ◽  
Age Related

Exome sequencing has been commonly used in rare diseases by selecting multiplex families or singletons with an extreme phenotype (EP) to search for rare variants in coding regions. The EP strategy covers both extreme ends of a disease spectrum and it has been also used to investigate the contribution of rare variants to heritability in complex clinical traits. We have conducted a systematic review to find evidence supporting the use of EP strategies to search for rare variants in genetic studies of complex diseases, to highlight the contribution of rare variation to the genetic structure of multiallelic conditions. After performing the quality assessment of the retrieved records, we selected 19 genetic studies considering EP to demonstrate genetic association. All the studies successfully identified several rare variants, de novo mutations and many novel candidate genes were also identified by selecting an EP. There is enough evidence to support that the EP approach in patients with an early onset of the disease can contribute to the identification of rare variants in candidate genes or pathways involved in complex diseases. EP patients may contribute to a better understanding of the underlying genetic architecture of common heterogeneous disorders such as tinnitus or age-related hearing loss.

scholarly journals Topological Segmentation of Time-Varying Functional Connectivity Highlights the Role of Preferred Cortical Circuits

2020 ◽  
Author(s):  
Jacob Billings ◽  
Manish Saggar ◽  
Shella Keilholz ◽  
Giovanni Petri
Keyword(s):  
Functional Connectivity ◽  
Brain Function ◽  
Persistent Homology ◽  
Brain Regions ◽  
Topological Data Analysis ◽  
Time Varying ◽  
Imaging Data ◽  
Experimental Conditions ◽  
Common Time ◽  
Brain Imaging Data

Functional connectivity (FC) and its time-varying analogue (TVFC) leverage brain imaging data to interpret brain function as patterns of coordinating activity among brain regions. While many questions remain regarding the organizing principles through which brain function emerges from multi-regional interactions, advances in the mathematics of Topological Data Analysis (TDA) may provide new insights into the brain’s spontaneous self-organization. One tool from TDA, “persistent homology”, observes the occurrence and the persistence of n-dimensional holes presented in the metric space over a dataset. The occurrence of n-dimensional holes within the TVFC point cloud may denote conserved and preferred routes of information flow among brain regions. In the present study, we compare the use of persistence homology versus more traditional TVFC metrics at the task of segmenting brain states that differ across a common time-series of experimental conditions. We find that the structures identified by persistence homology more accurately segment the stimuli, more accurately segment volunteer performance during experimentally defined tasks, and generalize better across volunteers. Finally, we present empirical and theoretical observations that interpret brain function as a topological space defined by cyclic and interlinked motifs among distributed brain regions, especially, the attention networks.

Linking brain imaging signals to visual perception

2013 ◽  
Vol 30 (5-6) ◽  
pp. 229-241 ◽  
Author(s):  
ANDREW E. WELCHMAN ◽  
ZOE KOURTZI
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Imaging Data ◽  
Neural Basis ◽  
3D Perception ◽  
Multimodal Data ◽  
Psychological States ◽  
Perceptual Judgments ◽  
Brain Circuits ◽  
Brain Imaging Data

AbstractThe rapid advances in brain imaging technology over the past 20 years are affording new insights into cortical processing hierarchies in the human brain. These new data provide a complementary front in seeking to understand the links between perceptual and physiological states. Here we review some of the challenges associated with incorporating brain imaging data into such “linking hypotheses,” highlighting some of the considerations needed in brain imaging data acquisition and analysis. We discuss work that has sought to link human brain imaging signals to existing electrophysiological data and opened up new opportunities in studying the neural basis of complex perceptual judgments. We consider a range of approaches when using human functional magnetic resonance imaging to identify brain circuits whose activity changes in a similar manner to perceptual judgments and illustrate these approaches by discussing work that has studied the neural basis of 3D perception and perceptual learning. Finally, we describe approaches that have sought to understand the information content of brain imaging data using machine learning and work that has integrated multimodal data to overcome the limitations associated with individual brain imaging approaches. Together these approaches provide an important route in seeking to understand the links between physiological and psychological states.

scholarly journals An Autism Spectrum Disorder Adaptive Identification Based on the Elimination of Brain Connections: A Proof of Long-Range Underconnectivity

2021 ◽  
Author(s):  
Fatima zahra Benabdallah ◽  
Ahmed Drissi El Maliani ◽  
Dounia Lotfi ◽  
Rachid Jennane ◽  
Mohammed El hassouni
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Long Range ◽  
Data Exchange ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Imaging Data ◽  
Brain Imaging Data

Abstract Autism spectrum disorder (ASD) is theoretically characterized by alterations in functional connectivity between brain regions. Many works presented approaches to determine informative patterns that help to predict autism from typical development. However, most of the proposed pipelines are not specifically designed for the autism problem, i.e they do not corroborate with autism theories about functional connectivity. In this paper, we propose a framework that takes into account the properties of local connectivity and long range under-connectivity in the autistic brain. The originality of the proposed approach is to adopt elimination as a technique in order to well emerge the autistic brain connectivity alterations, and show how they contribute to differentiate ASD from controls. Experimental results conducted on the large multi-site Autism Brain Imaging Data Exchange (ABIDE) show that our approach provides accurate prediction up to 70% and succeeds to prove the existence of deficits in the long-range connectivity in the ASD subjects brains.

scholarly journals Paternally inherited noncoding structural variants contribute to autism

2017 ◽  
Author(s):  
William M. Brandler ◽  
Danny Antaki ◽  
Madhusudan Gujral ◽  
Morgan L. Kleiber ◽  
Michelle S. Maile ◽  
...  
Keyword(s):  
De Novo ◽  
Fetal Brain ◽  
Wide Distribution ◽  
Autism Spectrum ◽  
Structural Variants ◽  
De Novo Mutations ◽  
Whole Genome Analysis ◽  
Protein Coding ◽  
Genome Wide ◽  
Exome Aggregation Consortium

AbstractThe genetic architecture of autism spectrum disorder (ASD) is known to consist of contributions from gene-disrupting de novo mutations and common variants of modest effect. We hypothesize that the unexplained heritability of ASD also includes rare inherited variants with intermediate effects. We investigated the genome-wide distribution and functional impact of structural variants (SVs) through whole genome analysis (≥30X coverage) of 3,169 subjects from 829 families affected by ASD. Genes that are intolerant to inactivating variants in the exome aggregation consortium (ExAC) were depleted for SVs in parents, specifically within fetal-brain promoters, UTRs and exons. Rare paternally-inherited SVs that disrupt promoters or UTRs were over-transmitted to probands (P = 0.0013) and not to their typically-developing siblings. Recurrent functional noncoding deletions implicate the gene LEO1 in ASD. Protein-coding SVs were also associated with ASD (P = 0.0025). Our results establish that rare inherited SVs predispose children to ASD, with differing contributions from each parent.

scholarly journals Development and Characterization of SSR Markers in the Gossypium Barbadense Genome

2021 ◽  
Author(s):  
Wenjuan ZHONG ◽  
Can YUAN ◽  
Zhengjie CHEN ◽  
Yonghang ZHOU ◽  
Siwei Chen ◽  
...  
Keyword(s):  
Ssr Markers ◽  
De Novo ◽  
Low Cost ◽  
Fiber Quality ◽  
Gossypium Barbadense ◽  
Pcr Analysis ◽  
Genetic Studies ◽  
Genome Wide ◽  
User Friendly

Abstract BackgroundThe fiber quality and resistance traits of Gossypium barbadense are considerably better than that of other Gossypium species. Simple sequence repeats (SSRs) are user friendly, low cost markers widely used in genetic studies. However, most SSRs have been developed from G. hirsutum, G. arboreum, and G. raimondii; no genome-wide SSRs have been developed from G. barbadense.The de novo sequences of G. barbadense cv. Xinhai21 were utilized to develop SSR markers and scanned to detect SSRs using the MIcroSAtellite (http://pgrc.ipk-gatersleben.de/misa/) identification tool. And then in silico PCR analysis was conducted to evaluate these primers polymorphism in five Gossypium species.ResultsIn total, 85,582 SSRs were identified with different motifs. 153,560 primer pairs were successfully designed for 73,419 SSRs. In silico analysis, we found that 8,466 primer pairs of 3,288 SSRs yielded one product (monomorphic) simultaneously in five Gossypium species. two Gossypium species (30 G. hirsutum and 27 G. barbadense accessions) were successfully separated by 300 primer pairs with the polymorphism information content (PIC) ranging from 0.00 to 0.93. ConclusionThese newly developed SSR markers will be helpful for the construction of genetic linkage maps, genetic diversity analyses, QTL mapping, and molecular breeding of Gossypium species.

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