Primary data for "Comprehensive gene profiling of the metabolic landscape of humanized livers in mice"

Background & Aims The human liver transcriptome is complex and highly dynamic, e.g. one gene may produce multiple distinct transcripts, each with distinct posttranscriptional modifications. Direct knowledge of transcriptome dynamics, however, is largely obscured by the inaccessibility of the human liver to treatments and the insufficient annotation of the human liver transcriptome at transcript and RNA modification levels. Methods We generated mice that carry humanized livers of identical genetic background and subjected them to representative metabolic treatments. We then analyzed the humanized livers with nanopore single-molecule direct RNA sequencing to determine the expression level, m6A modification and poly(A) tail length of all RNA transcript isoforms. Our system allows for the de novo annotation of human liver transcriptomes to reflect metabolic responses and for the study of transcriptome dynamics in parallel. Results Our analysis uncovered a vast number of novel genes and transcripts. Our transcript-level analysis of human liver transcriptomes also identified a multitude of regulated metabolic pathways that were otherwise invisible using conventional short-read RNA sequencing. We revealed for the first time the dynamic changes in m6A and poly(A) tail length of human liver transcripts, many of which are transcribed from key metabolic genes. Furthermore, we performed comparative analyses of gene regulation between humans and mice, and between two individuals using the liver-specific humanized mice, revealing that transcriptome dynamics are highly species- and genetic background-dependent. Conclusion Our work revealed a complex metabolic response landscape of the human liver transcriptome and provided a novel resource to understand transcriptome dynamics of the human liver in response to physiologically relevant metabolic stimuli (https://caolab.shinyapps.io/human_hepatocyte_landscape/).