UC San Diego

Contained within the nucleus of each mammalian diploid cell are found two genomes, a maternally and a paternally inherited copy. Recent studies have begun to better characterize the extent of variation between genomes increasing the previous estimates five-fold. These variations are not just located in the large intergenic regions of the genome called gene desserts, but are often found in gene coding sequences and gene regulatory regions. It is becoming increasingly clear that allelic resolution of genomic variation, transcript bias, and protein-DNA interactions is important in understanding the true cellular state of diploid cells. To date, allele- level examination has been left unstudied in large part due to a lack of large-scale technologies capable of resolving alleles. In this work, we describe the development of a novel technology, named RNA Digital Expression Profiling (RDEP), which allows discreet quantification of RNA levels by counting single molecules in a high-throughput array based format. RDEP demonstrated comparable performance to quantitative-PCR when examining small gene changes. Capable of accurately quantifying low abundance genes such as EDN1 in RNA samples isolated from as few as 2̃,000 cells. We further show that we can modify this same methodology to allow detection of individual alleles. We call this modification Allele-specific Digital Expression Profiling (ADEP) and show that we can accurately quantify bias between alleles as small as 5%. This is a significant improvement over established high- throughput technologies, which have difficulty detecting differential allelic bias less than 50% (60:40). We feel that RDEP and ADEP are viable high-throughput technology that allows accurate discreet quantification of RNA and allele transcripts. While a number of genes subjected to such allele-specific regulation have been identified, the underlying mechanisms have remained largely uncharacterized. To this end, it is important to analyze transcription factor binding and chromatin structures at the two parental alleles of each gene. We describe a high- throughput method for identification of allele-specific protein-DNA interactions throughout the genome. This method involves isolation of the transcription factor bound DNA via chromatin immunoprecipitation (ChIP) from cross-linked human cells, followed by detection with SNP genotyping microarrays (ChIP-SNP). We applied this method to human fetal fibroblasts (IMR90) and examined the binding of RNA polymerase complex (RNAP) to a collection of 317,513 SNP sequences in the human genome. Among the 11, 027 heterogeneous SNPs enriched by RNAP, 466 (4.0 %) are occupied by RNAP in an allele-specific manner. Using allele-specific transcription profiling, we found excellent correlation between allele-specific RNAP enrichment and allele-specific gene expression. Our results confirmed allele-specific binding of RNAP to known imprinted loci and provide hundreds of candidates for novel imprinted loci. ChIP-SNP provides a window into understanding transcription by looking at binding of transcription machinery or regulators to DNA in an allele- specific manner