A barley pan-transcriptome reveals layers of genotype-dependent transcriptional complexity

Wenbin Guo, Miriam Schreiber, Vanda Marosi, Paolo Bagnaresi, Kenneth J. Chalmers, Brett Chapman, Viet Dang, Christoph Dockter, Anne Fiebig, Agostino Fricano, John Fuller, Allison M. Haaning, Georg Haberer, Axel Himmelbach, Murukarthick Jayakodi, Yong Jia, Morten E. Jørgensen, Nadia Kamal, Peter Langridge, Chengdao LiQiongxian Lu, Thomas Lux, Martin Mascher, Klaus F. X. Mayer, Nicola McCallum, Linda Milne, Gary J. Muehlbauer, Sudharsan Padmarasu, Pai Rosager Pedas, Klaus Pillen, Curtis Pozniak, Kazuhiro Sato, Thomas Schmutzer, Uwe Scholz, Danuta Schüler, Hana Šimková, Birgitte Skadhauge, Nils Stein, Penghao Wang, Ronja Wonneberger, Xiao-Qi Zhang, Guoping Zhang, Luigi Cattivelli, Manuel Spannagl, Micha Bayer (Lead / Corresponding author), Craig Simpson (Lead / Corresponding author), Runxuan Zhang (Lead / Corresponding author), Robbie Waugh (Lead / Corresponding author)

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Abstract

A pan-transcriptome describes the transcriptional and post-transcriptional consequences of genome diversity from multiple individuals within a species, revealing an assortment of functions that drive biological outcomes. We developed a barley pan-transcriptome using twenty inbred genotypes representing domesticated* barley diversity by generating and analysing extensive short- and long-read RNA sequencing datasets from multiple tissues. To overcome single reference bias and facilitate downstream analyses we constructed genotype-specific reference transcript datasets (RTDs) and integrated these into a linear pan-genome framework to create a single pan-RTD. Categorising transcripts based upon presence or absence across genotypes defined them as core (expressed in all), shell (absent in one or more) or cloud (expressed in only one). Focusing on the core we observed significant transcript abundance variation among tissues and between genotypes. We show that drivers of transcript abundance variation in this category include RNA processing, gene copy number, large structural rearrangements and degree of conservation of promotor motifs. We reveal conserved patterns of co-expression module-tissue correlations encompassing distinct biological functions, as well as frequent functional diversification. We complement the pan-transcriptome by integrating extensive and diverse replicated public RNA-seq datasets from the reference cultivar (cv.) Morex into a comprehensive gene-expression atlas
Original languageEnglish
PublisherResearch Square
DOIs
Publication statusPublished - 7 Jan 2024

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