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

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

Authors
Guo, W., Schreiber, M., Marosi, V.B., Bagnaresi, P., Jørgensen, M.E., Braune, K.B.,  Chalmers, K., Chapman, B., Dang, V., Dockter, Ch., Fiebig, A., Fincher, G.B., Fricano, A., Fuller, J., Haaning, A., Haberer, G., Himmelbach, A., Jayakodi, M., Jia, Y., Kamal, N., Langridge, P., Li, Ch., Lu, Q., Lux, T., Mascher, M., Mayer, K.F.X., McCallum, N.,  Milne, L., Muehlbauer, G.J., Nielsen, M.T.S., Padmarasu, S., Pedas, P.R., Pillen, K.,  Pozniak, C.,  Rasmussen, M.W., Sato, K., Schmutzer, T., Scholz, U., Schüler, D.,  Šimková, H., Skadhauge, B., Stein, N., Thomsen, N.W., Voss, C., Wang, P.,  Wonneberger, R., Zhang, X.-Q., Zhang, G., Cattivelli, L., Spannagl, M., Bayer, M.,  Simpson, C., Zhang, R., Waugh, R.
Year
2025
Journal
Nature Genetics
Volume
57
Pages
441-450
DOI
10.1038/s41588-024-02069-y

Abstract

A pan-transcriptome describes the transcriptional and post-transcriptional consequences of genome diversity from multiple individuals within a species. We developed a barley pan-transcriptome using 20 inbred genotypes representing domesticated barley diversity by generating and analyzing short- and long-read RNA-sequencing datasets from multiple tissues. To overcome single reference bias in transcript quantifcation, we constructed genotype-specifc reference transcript datasets (RTDs) and integrated these into a linear pan-genome framework to create a pan-RTD, allowing transcript categorization as core, shell or cloud. Focusing on the core (expressed in all genotypes), we observed signifcant transcript abundance variation among tissues and between genotypes driven partly by RNA processing, gene copy number, structural rearrangements and conservation of promotor motifs. Network analyses revealed conserved co-expression module::tissue correlations and frequent functional diversifcation. To complement the pan-transcriptome, we constructed a comprehensive cultivar (cv.) Morex gene-expression atlas and illustrate how these combined datasets can be used to guide biological inquiry.