Sleep and Performance Research Center
Sleep, Development and Autism Spectrum Disorders
LUCIA PEIXOTO, PH.D.
University of Pennsylvania, 2009, Biology
Areas of Interest
Factors that drive severity in the Autism Spectrum, with a focus on the role of sleep in neurodevelopment disorders. How sleep and learning affect epigenetic and transcriptional regulation in Autism.
Several studies have demonstrated that sleep problems occur in ASD at a much higher rate than in typical development, affecting 40-80% of this population. These problems include significant delays in sleep onset, multiple night awakenings and overall less sleep. Sleep problems are a good predictor of severity of core ASD diagnostic symptoms, such as communication deficits and repetitive behaviors. Despite a rapidly growing number of studies documenting sleep problems in ASD, little is known about its exact nature and underlying mechanisms. To advance the study of sleep in ASD, we decided to focus on Shank3, a high confidence gene candidate linked to ASD.
My lab uses genomic and candidate gene approaches to study neurodevelopmental disabilities, in particular Autism Spectrum Disorders (ASD). The research focuses on factors that affect to the greatest extent the quality of life of affected individuals and their families, as is the case with learning and sleep impairments associated with ASD. We use both animal models as well as patient data. In our recent work published in ELife, we showed that mutations in Shank3, a high confidence autism gene candidate, lead to difficulty falling asleep, low quality sleep and deregulation of circadian transcription factors. We are currently investigating the molecular basis of the sleep impairments in Shank3 mutant mice, including the role of 3D chromatin regulation. We are also investigating the role of sleep in postnatal brain development and the emergence of the sleep phenotype in Shank3 mutant mice.
A parallel interest in the lab is reproducible bioinformatic research. Applying methodology aimed at ensuring reproducibility of transcriptome studies (see Peixoto et al., Nucleic acids research 2015) we have been able to shed new light into alternative splicing during memory consolidation and define the gene expression changes that are linked to recovery from sleep loss (published in BMC genomics). To ensure reproducibility of differential epigenomic studies, we have developed a new approach (DEScan) to analyze data from epigenomic experiments (such as chromatin accessibility or histone modifications) with multiple biological replicates. Using high-throughput sequencing and DEScan to study how learning affects chromatin accessibility in the mouse brain we showed that learning recapitulates development at the epigenetic level, highlighting regulatory regions associated with ASD. This work was published as the cover of Science Signaling in January 2018.
Staff and Trainees
- Hannah Schoch, Ph.D. (Post-Doctoral Fellow)
- Kristan Singletary, Ph.D. (Lab Manager/Research Specialist)
- Taylor Wintler, BS (Medical Student)
- Elizabeth Medina, BA (Graduate Student)
- Erika English, BS (Graduate Student)
- Kaitlyn Ford (Research Intern)
- Cortical EEG
- Animal Behavior
- Gene expression analysis (qPCR, microarray, RNAseq)
- Immunofluorescence assays
- Western blots
- National Institutes of Health
- Washington Research Foundation
Tutorials and Software
- Tutorial for reproducible RNA-seq data analysis: https://github.com/drisso/peixoto2015_tutorial
- Software for differential Epigenomic Analysis:
- DEScan: https://github.com/jnkoberstein/DEScan
- DEScan2 (R/Bioconductor package): https://bioconductor.org/packages/release/bioc/html/DEScan2.html