Quantifying Genomic Imprinting at Tissue and Cell Resolution in the Brain.
Annie VarraultEmeric DuboisAnne Le DigarcherTristan BouschetPublished in: Epigenomes (2020)
Imprinted genes are a group of ~150 genes that are preferentially expressed from one parental allele owing to epigenetic marks asymmetrically distributed on inherited maternal and paternal chromosomes. Altered imprinted gene expression causes human brain disorders such as Prader-Willi and Angelman syndromes and additional rare brain diseases. Research data principally obtained from the mouse model revealed how imprinted genes act in the normal and pathological brain. However, a better understanding of imprinted gene functions calls for building detailed maps of their parent-of-origin-dependent expression and of associated epigenetic signatures. Here we review current methods for quantifying genomic imprinting at tissue and cell resolutions, with a special emphasis on methods to detect parent-of-origin dependent expression and their applications to the brain. We first focus on bulk RNA-sequencing, the main method to detect parent-of-origin-dependent expression transcriptome-wide. We discuss the benefits and caveats of bulk RNA-sequencing and provide a guideline to use it on F1 hybrid mice. We then review methods for detecting parent-of-origin-dependent expression at cell resolution, including single-cell RNA-seq, genetic reporters, and molecular probes. Finally, we provide an overview of single-cell epigenomics technologies that profile additional features of genomic imprinting, including DNA methylation, histone modifications and chromatin conformation and their combination into sc-multimodal omics approaches, which are expected to yield important insights into genomic imprinting in individual brain cells.
Keyphrases
- single cell
- rna seq
- dna methylation
- genome wide
- gene expression
- copy number
- poor prognosis
- high throughput
- resting state
- white matter
- genome wide identification
- single molecule
- functional connectivity
- mouse model
- binding protein
- long non coding rna
- cerebral ischemia
- transcription factor
- multiple sclerosis
- solid phase extraction
- molecular dynamics simulations
- brain injury
- electronic health record
- adipose tissue
- big data
- deep learning
- neural network
- subarachnoid hemorrhage
- weight gain