16p11.2 microdeletion imparts transcriptional alterations in human iPSC-derived models of early neural development.
Julien George RothKristin L MuenchAditya AsokanVictoria M MallettHui GaiYogendra VermaStephen WeberCarol CharltonJonas L FowlerKyle M LohRicardo E DolmetschTheo D PalmerPublished in: eLife (2020)
Microdeletions and microduplications of the 16p11.2 chromosomal locus are associated with syndromic neurodevelopmental disorders and reciprocal physiological conditions such as macro/microcephaly and high/low body mass index. To facilitate cellular and molecular investigations into these phenotypes, 65 clones of human induced pluripotent stem cells (hiPSCs) were generated from 13 individuals with 16p11.2 copy number variations (CNVs). To ensure these cell lines were suitable for downstream mechanistic investigations, a customizable bioinformatic strategy for the detection of random integration and expression of reprogramming vectors was developed and leveraged towards identifying a subset of 'footprint'-free hiPSC clones. Transcriptomic profiling of cortical neural progenitor cells derived from these hiPSCs identified alterations in gene expression patterns which precede morphological abnormalities reported at later neurodevelopmental stages. Interpreting clinical information-available with the cell lines by request from the Simons Foundation Autism Research Initiative-with this transcriptional data revealed disruptions in gene programs related to both nervous system function and cellular metabolism. As demonstrated by these analyses, this publicly available resource has the potential to serve as a powerful medium for probing the etiology of developmental disorders associated with 16p11.2 CNVs.
Keyphrases
- induced pluripotent stem cells
- copy number
- gene expression
- mitochondrial dna
- intellectual disability
- body mass index
- genome wide
- endothelial cells
- dna methylation
- single cell
- poor prognosis
- transcription factor
- zika virus
- autism spectrum disorder
- public health
- single molecule
- electronic health record
- healthcare
- social media
- label free
- quality improvement
- big data
- molecular dynamics simulations
- pluripotent stem cells
- health information
- weight gain
- risk assessment
- genome wide identification