title: IDP-ASE: haplotyping and quantifying allele-specific expression at the gene and gene isoform level by hybrid sequencing.
abstract: Allele-specific expression (ASE) is a fundamental problem in studying gene regulation and diploid transcriptome profiles, with two key challenges: (i) haplotyping and (ii) estimation of ASE at the gene isoform level. Existing ASE analysis methods are limited by a dependence on haplotyping from laborious experiments or extra genome/family trio data. In addition, there is a lack of methods for gene isoform level ASE analysis. We developed a tool, IDP-ASE, for full ASE analysis. By innovative integration of Third Generation Sequencing (TGS) long reads with Second Generation Sequencing (SGS) short reads, the accuracy of haplotyping and ASE quantification at the gene and gene isoform level was greatly improved as demonstrated by the gold standard data GM12878 data and semi-simulation data. In addition to methodology development, applications of IDP-ASE to human embryonic stem cells and breast cancer cells indicate that the imbalance of ASE and non-uniformity of gene isoform ASE is widespread, including tumorigenesis relevant genes and pluripotency markers. These results show that gene isoform expression and allele-specific expression cooperate to provide high diversity and complexity of gene regulation and expression, highlighting the importance of studying ASE at the gene isoform level. Our study provides a robust bioinformatics solution to understand ASE using RNA sequencing data only.
authors.affiliation: Department of Biostatistics, University of Iowa, Iowa City, IA 52242, USA.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Deonovic
authors.affiliation: Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA.|Key laboratory of Genetics Network Biology, Collaborative Innovation Center of Genetics and Development, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.|University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Yunhao
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA.
authors.forename: Jason
authors.initials: J
authors.lastname: Weirather
authors.affiliation: Key laboratory of Genetics Network Biology, Collaborative Innovation Center of Genetics and Development, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Xiu-Jie
authors.initials: XJ
authors.lastname: Wang
authors.affiliation: Department of Biostatistics, University of Iowa, Iowa City, IA 52242, USA.|Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA.
authors.forename: Kin Fai
authors.initials: KF
authors.lastname: Au
mesh_terms: D000483:Alleles; D005786:Gene Expression Regulation; D006239:Haplotypes; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D000066449:Human Embryonic Stem Cells / Q000166:cytology / Q000378:metabolism; D006801:Humans; D061986:MCF-7 Cells; D059368:RNA Isoforms / Q000235:genetics* / Q000378:metabolism; D012333:RNA, Messenger / Q000235:genetics* / Q000378:metabolism; D017423:Sequence Analysis, RNA; D059467:Transcriptome
chemical_list: D059368:RNA Isoforms; D012333:RNA, Messenger