scholarly journals Positive selection in noncoding genomic regions of vocal learning birds is associated with genes implicated in vocal learning and speech functions in humans

2021 ◽  
Author(s):  
James A. Cahill ◽  
Joel Armstrong ◽  
Alden Deran ◽  
Carolyn J. Khoury ◽  
Benedict Paten ◽  
...  
Keyword(s):  
Gene Expression ◽  
Positive Selection ◽  
Vocal Communication ◽  
Vocal Learning ◽  
Spoken Language ◽  
Autism Spectrum ◽  
Noncoding Regions ◽  
Brain Gene Expression ◽  
Strong Candidate ◽  
Genomic Regions

Vocal learning, the ability to imitate sounds from conspecifics and the environment, is a key component of human spoken language and learned song in three independently evolved avian groups—oscine songbirds, parrots, and hummingbirds. Humans and each of these three bird clades exhibit specialized behavioral, neuroanatomical, and brain gene expression convergence related to vocal learning, speech, and song. To understand the evolutionary basis of vocal learning gene specializations and convergence, we searched for and identified accelerated genomic regions (ARs), a marker of positive selection, specific to vocal learning birds. We found avian vocal learner-specific ARs, and they were enriched in noncoding regions near genes with known speech functions or brain gene expression specializations in humans and vocal learning birds, including FOXP2, NEUROD6, ZEB2, and MEF2C, and near genes with major neurodevelopmental functions, including NR2F1, NRP2, and BCL11B. We also found enrichment near the SFARI class S genes associated with syndromic vocal communication forms of autism spectrum disorders. These findings reveal strong candidate noncoding regions near genes for the evolutionary adaptations that distinguish vocal learning species from their close vocal nonlearning relatives and provide further evidence of molecular convergence between birdsong and human spoken language.

scholarly journals Behavior-dependent cis regulation reveals genes and pathways associated with bower building in cichlid fishes

2018 ◽  
Vol 115 (47) ◽  
pp. E11081-E11090 ◽  
Author(s):  
Ryan A. York ◽  
Chinar Patil ◽  
Kawther Abdilleh ◽  
Zachary V. Johnson ◽  
Matthew A. Conte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Plasticity ◽  
Genetic Basis ◽  
Specific Expression ◽  
Preferential Expression ◽  
Cichlid Fishes ◽  
Brain Gene Expression ◽  
Genome Wide ◽  
Allele Specific ◽  
Genomic Regions

Many behaviors are associated with heritable genetic variation [Kendler and Greenspan (2006) Am J Psychiatry 163:1683–1694]. Genetic mapping has revealed genomic regions or, in a few cases, specific genes explaining part of this variation [Bendesky and Bargmann (2011) Nat Rev Gen 12:809–820]. However, the genetic basis of behavioral evolution remains unclear. Here we investigate the evolution of an innate extended phenotype, bower building, among cichlid fishes of Lake Malawi. Males build bowers of two types, pits or castles, to attract females for mating. We performed comparative genome-wide analyses of 20 bower-building species and found that these phenotypes have evolved multiple times with thousands of genetic variants strongly associated with this behavior, suggesting a polygenic architecture. Remarkably, F1 hybrids of a pit-digging and a castle-building species perform sequential construction of first a pit and then a castle bower. Analysis of brain gene expression in these hybrids showed that genes near behavior-associated variants display behavior-dependent allele-specific expression with preferential expression of the pit-digging species allele during pit digging and of the castle-building species allele during castle building. These genes are highly enriched for functions related to neurodevelopment and neural plasticity. Our results suggest that natural behaviors are associated with complex genetic architectures that alter behavior via cis-regulatory differences whose effects on gene expression are specific to the behavior itself.

scholarly journals Varying intolerance of gene pathways to mutational classes explain genetic convergence across neuropsychiatric disorders

2016 ◽  
Author(s):  
Shahar Shohat ◽  
Eyal Ben-David ◽  
Sagiv Shifman
Keyword(s):  
Gene Expression ◽  
Genome Wide Association Study ◽  
De Novo ◽  
Expression Patterns ◽  
Neuropsychiatric Disorders ◽  
Autism Spectrum ◽  
Specific Gene ◽  
Missense Mutations ◽  
Loss Of Function ◽  
Brain Gene Expression

AbstractGenetic susceptibility to Intellectual disability (ID), autism spectrum disorder (ASD) and schizophrenia (SCZ) often arises from mutations in the same genes, suggesting that they share common mechanisms. We studied genes with de novo mutations in the three disorders and genes implicated by SCZ genome-wide association study (GWAS). Using biological annotations and brain gene expression, we show that mutation class explains enrichment patterns more than specific disorder. Genes with loss of function mutations and genes with missense mutations were enriched with different pathways, shared with genes intolerant to mutations. Specific gene expression patterns were found for each disorder. ID genes were preferentially expressed in fetal cortex, ASD genes also in fetal cerebellum and striatum, and genes associated with SCZ were most significantly enriched in adolescent cortex. Our study suggests that convergence across neuropsychiatric disorders stems from vulnerable pathways to genetic variations, but spatiotemporal activity of genes contributes to specific phenotypes.

scholarly journals Identification and analysis of vocal communication pathways in birds through inducible gene expression

2004 ◽  
Vol 76 (2) ◽  
pp. 243-246 ◽  
Author(s):  
Claudio V. Mello
Keyword(s):  
Gene Expression ◽  
Auditory Processing ◽  
Vocal Communication ◽  
Vocal Learning ◽  
Early Gene ◽  
Brain Areas ◽  
Control Brain ◽  
Activity Dependent ◽  
The Brain ◽  
Inducible Gene

The immediate-early gene zenk is an activity-dependent gene highly induced in auditory processing or vocal motor control brain areas when birds engage in hearing or producing song, respectively. Studies of the expression of zenk in songbirds and other avian groups will be reviewed here briefly, with a focus on how this analysis has generated new insights on the brain pathways and mechanisms involved in perceptual and motor aspects of vocal communication and vocal learning.

scholarly journals Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Jun Wang ◽  
Liangjiang Wang
Keyword(s):  
Gene Expression ◽  
Random Forest ◽  
Gene Expression Data ◽  
Autism Spectrum ◽  
Expression Data ◽  
Risk Genes ◽  
Sequence Features ◽  
Brain Gene Expression ◽  
Transcript Sequence ◽  
Non Coding Rnas

Abstract Background Autism spectrum disorders (ASD) refer to a range of neurodevelopmental conditions, which are genetically complex and heterogeneous with most of the genetic risk factors also found in the unaffected general population. Although all the currently known ASD risk genes code for proteins, long non-coding RNAs (lncRNAs) as essential regulators of gene expression have been implicated in ASD. Some lncRNAs show altered expression levels in autistic brains, but their roles in ASD pathogenesis are still unclear. Results In this study, we have developed a new machine learning approach to predict candidate lncRNAs associated with ASD. Particularly, the knowledge learnt from protein-coding ASD risk genes was transferred to the prediction and prioritization of ASD-associated lncRNAs. Both developmental brain gene expression data and transcript sequence were found to contain relevant information for ASD risk gene prediction. During the pre-training phase of model construction, an autoencoder network was implemented for a representation learning of the gene expression data, and a random-forest-based feature selection was applied to the transcript-sequence-derived k-mers. Our models, including logistic regression, support vector machine and random forest, showed robust performance based on tenfold cross-validations as well as candidate prioritization with hypothetical loci. We then utilized the models to predict and prioritize a list of candidate lncRNAs, including some reported to be cis-regulators of known ASD risk genes, for further investigation. Conclusions Our results suggest that ASD risk genes can be accurately predicted using developmental brain gene expression data and transcript sequence features, and the models may provide useful information for functional characterization of the candidate lncRNAs associated with ASD.

scholarly journals Maternal immune activation dysregulation of the fetal brain transcriptome and relevance to the pathophysiology of autism spectrum disorder

2016 ◽  
Author(s):  
Michael V. Lombardo ◽  
Hyang Mi Moon ◽  
Jennifer Su ◽  
Theo D. Palmer ◽  
Eric Courchesne ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Autism Spectrum Disorder ◽  
Translation Initiation ◽  
Immune Activation ◽  
Fetal Brain ◽  
Autism Spectrum ◽  
Brain Gene Expression ◽  
Maternal Immune Activation ◽  
Increased Risk

AbstractMaternal immune activation (MIA) via infection during pregnancy is known to increase risk for autism spectrum disorder (ASD). However, it is unclear how MIA disrupts fetal brain gene expression in ways that may explain this increased risk. Here we examine how MIA dysregulates fetal brain gene expression near the end of the first trimester of human gestation in ways relevant to ASD-associated pathophysiology. MIA downregulates expression of ASD-associated genes, with the largest enrichments in genes known to harbor rare highly penetrant mutations. MIA also downregulates expression of many genes also known to be persistently downregulated in ASD cortex later in life and which are canonically known for roles in affecting prenatally-late developmental processes at the synapse. Transcriptional and translational programs that are downstream targets of highly ASD-penetrant FMR1 and CHD8 genes are also heavily affected by MIA. MIA strongly upregulates expression of a large number of genes involved in translation initiation, cell cycle, DNA damage, and proteolysis processes that affect multiple key neural developmental functions. Upregulation of translation initiation is common to and preserved in gene network structure with the ASD cortical transcriptome throughout life and has downstream impact on cell cycle processes. The cap-dependent translation initiation gene, EIF4E, is one of the most MIA-dysregulated of all ASD-associated genes and targeted network analyses demonstrate prominent MIA-induced transcriptional dysregulation of mTOR and EIF4E-dependent signaling. This dysregulation of translation initiation via alteration of the Tsc2-mTor-Eif4e-axis was further validated across MIA rodent models. MIA may confer increased risk for ASD by dysregulating key aspects of fetal brain gene expression that are highly relevant to pathophysiology affecting ASD.

scholarly journals Deep evolutionary conservation of autism-related genes

2017 ◽  
Vol 114 (36) ◽  
pp. 9653-9658 ◽  
Author(s):  
Hagai Y. Shpigler ◽  
Michael C. Saul ◽  
Frida Corona ◽  
Lindsey Block ◽  
Amy Cash Ahmed ◽  
...  
Keyword(s):  
Gene Expression ◽  
Honey Bee ◽  
Molecular Mechanisms ◽  
Autism Spectrum ◽  
Insect Brain ◽  
Social Pathology ◽  
Brain Gene Expression ◽  
Gene Expression Signatures ◽  
High Level ◽  
Sociobiological Theory

E. O. Wilson proposed in Sociobiology that similarities between human and animal societies reflect common mechanistic and evolutionary roots. When introduced in 1975, this controversial hypothesis was beyond science’s ability to test. We used genomic analyses to determine whether superficial behavioral similarities in humans and the highly social honey bee reflect common molecular mechanisms. Here, we report that gene expression signatures for individual bees unresponsive to various salient social stimuli are significantly enriched for autism spectrum disorder-related genes. These signatures occur in the mushroom bodies, a high-level integration center of the insect brain. Furthermore, our finding of enrichment was unique to autism spectrum disorders; brain gene expression signatures from other honey bee behaviors do not show this enrichment, nor do datasets from other human behavioral and health conditions. These results demonstrate deep conservation for genes associated with a human social pathology and individual differences in insect social behavior, thus providing an example of how comparative genomics can be used to test sociobiological theory.

scholarly journals LSD1 enzyme inhibitor TAK-418 unlocks aberrant epigenetic machinery and improves autism symptoms in neurodevelopmental disorder models

2021 ◽  
Vol 7 (11) ◽  
pp. eaba1187
Author(s):  
Rina Baba ◽  
Satoru Matsuda ◽  
Yuuichi Arakawa ◽  
Ryuji Yamada ◽  
Noriko Suzuki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enzyme Activity ◽  
Neurodevelopmental Disorders ◽  
Neurodevelopmental Disorder ◽  
Specific Inhibitor ◽  
Autism Spectrum ◽  
Poly I:C ◽  
Control Of Gene Expression ◽  
Epigenetic Machinery ◽  
The Brain

Persistent epigenetic dysregulation may underlie the pathophysiology of neurodevelopmental disorders, such as autism spectrum disorder (ASD). Here, we show that the inhibition of lysine-specific demethylase 1 (LSD1) enzyme activity normalizes aberrant epigenetic control of gene expression in neurodevelopmental disorders. Maternal exposure to valproate or poly I:C caused sustained dysregulation of gene expression in the brain and ASD-like social and cognitive deficits after birth in rodents. Unexpectedly, a specific inhibitor of LSD1 enzyme activity, 5-((1R,2R)-2-((cyclopropylmethyl)amino)cyclopropyl)-N-(tetrahydro-2H-pyran-4-yl)thiophene-3-carboxamide hydrochloride (TAK-418), almost completely normalized the dysregulated gene expression in the brain and ameliorated some ASD-like behaviors in these models. The genes modulated by TAK-418 were almost completely different across the models and their ages. These results suggest that LSD1 enzyme activity may stabilize the aberrant epigenetic machinery in neurodevelopmental disorders, and the inhibition of LSD1 enzyme activity may be the master key to recover gene expression homeostasis. TAK-418 may benefit patients with neurodevelopmental disorders.

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