Dataset Information

RNA-Seq reveals different mRNA abundance of transporters and their alternative transcript isoforms during liver development.

ABSTRACT: During development, the maturation of liver transporters is essential for chemical elimination in newborns and children. One cannot compare the real abundance of transcripts by conventional messenger RNA (mRNA) profiling methods; in comparison, RNA-Seq provides a "true quantification" of transcript counts and an unbiased detection of novel transcripts. The purpose of this study was to compare the mRNA abundance of liver transporters and seek their novel transcripts during liver development. Livers from male C57BL/6J mice were collected at 12 ages from prenatal to adulthood. The transcriptome was determined by RNA-Seq, with transcript abundance estimated by Cufflinks. Among 498 known transporters, the ontogeny of 62 known critical xenobiotic transporters was examined in detail. The cumulative mRNAs of the uptake transporters increased more than the efflux transporters in livers after birth. A heatmap revealed three ontogenic patterns of these transporters, namely perinatal (reaching maximal expression before birth), adolescent (about 20 days), and adult enriched (about 60 days of age). Before birth, equilibrative nucleoside transporter 1 was the transporter with highest expression in liver (29%), followed by breast cancer resistance protein (Bcrp) (26%). Within 1 day after birth, the mRNAs of these two transporters decreased markedly, and Ntcp became the transporter with highest expression (52%). In adult liver, the transporters with highest expression were organic cation transporter 1 and Ntcp (23% and 22%, respectively). Three isoforms of Bcrp with alternate leading exons were identified (E1a, E1b, and E1c), with E1b being the major isoform. In conclusion, this study reveals the mRNA abundance of transporters in liver and demonstrates that the expression of liver transporters is both age and isoform specific.

SUBMITTER: Cui JY

PROVIDER: S-EPMC3355312 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

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RNA-Seq reveals different mRNA abundance of transporters and their alternative transcript isoforms during liver development.

Cui Julia Yue JY Gunewardena Sumedha S SS Yoo Byunggil B Liu Jie J Renaud Helen J HJ Lu Hong H Zhong Xiao-bo XB Klaassen Curtis D CD

Toxicological sciences : an official journal of the Society of Toxicology 20120327 2

During development, the maturation of liver transporters is essential for chemical elimination in newborns and children. One cannot compare the real abundance of transcripts by conventional messenger RNA (mRNA) profiling methods; in comparison, RNA-Seq provides a "true quantification" of transcript counts and an unbiased detection of novel transcripts. The purpose of this study was to compare the mRNA abundance of liver transporters and seek their novel transcripts during liver development. Live ...[more]

PMID: 22454430

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Project description:Alternative splicing leverages genomic content by allowing the synthesis of multiple transcripts and, by implication, protein isoforms, from a single gene. However, estimating the abundance of transcripts produced in a given tissue from short sequencing reads is difficult and can result in both the construction of transcripts that do not exist, and the failure to identify true transcripts. An alternative approach is to catalog the events that make up isoforms (splice junctions and exons). We present here the Event Analysis (EA) approach, where we project transcripts onto the genome and identify overlapping/unique regions and junctions. In addition, all possible logical junctions are assembled into a catalog. Transcripts are filtered before quantitation based on simple measures: the proportion of the events detected, and the coverage. We find that mapping to a junction catalog is more efficient at detecting novel junctions than mapping in a splice aware manner. We identify 99.8% of true transcripts while iReckon identifies 82% of the true transcripts and creates more transcripts not included in the simulation than were initially used in the simulation. Using PacBio Iso-seq data from a mouse neural progenitor cell model, EA detects 60% of the novel junctions that are combinations of existing exons while only 43% are detected by STAR. EA further detects ?5,000 annotated junctions missed by STAR. Filtering transcripts based on the proportion of the transcript detected and the number of reads on average supporting that transcript captures 95% of the PacBio transcriptome. Filtering the reference transcriptome before quantitation, results in is a more stable estimate of isoform abundance, with improved correlation between replicates. This was particularly evident when EA is applied to an RNA-seq study of type 1 diabetes (T1D), where the coefficient of variation among subjects (n = 81) in the transcript abundance estimates was substantially reduced compared to the estimation using the full reference. EA focuses on individual transcriptional events. These events can be quantitate and analyzed directly or used to identify the probable set of expressed transcripts. Simple rules based on detected events and coverage used in filtering result in a dramatic improvement in isoform estimation without the use of ancillary data (e.g., ChIP, long reads) that may not be available for many studies.

Dataset Information

RNA-Seq reveals different mRNA abundance of transporters and their alternative transcript isoforms during liver development.

Publications

RNA-Seq reveals different mRNA abundance of transporters and their alternative transcript isoforms during liver development.

Similar Datasets

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