Guo, Wenbin; Schreiber, Miriam; Marosi, Vanda B.; Bagnaresi, Paolo; Jorgensen, Morten Egevang; Braune, Katarzyna B.; Chalmers, Ken; Chapman, Brett; Dang, Viet; Dockter, Christoph; Fiebig, Anne; Fincher, Geoffrey B.; Fricano, Agostino; Fuller, John; Haaning, Allison; Haberer, Georg; Himmelbach, Axel; Jayakodi, Murukarthick; Jia, Yong; Kamal, Nadia; Langridge, Peter; Li, Chengdao; Lu, Qiongxian; Lux, Thomas; Mascher, Martin; Mayer, Klaus F. X.; Mccallum, Nicola; Milne, Linda; Muehlbauer, Gary J.; Nielsen, Martin T. S.; Padmarasu, Sudharsan; Pedas, Pai Rosager; Pillen, Klaus; Pozniak, Curtis; Rasmussen, Magnus W.; Sato, Kazuhiro; Schmutzer, Thomas; Scholz, Uwe; Schueler, Danuta; Simkova, Hana; Skadhauge, Birgitte; Stein, Nils; Thomsen, Nina W.; Voss, Cynthia; Wang, Penghao; Wonneberger, Ronja; Zhang, Xiao-Qi; Zhang, Guoping; Cattivelli, Luigi; Spannagl, Manuel; Bayer, Micha; Simpson, Craig; Zhang, Runxuan; Waugh, Robbie A barley pan-transcriptome reveals layers of genotype-dependent transcriptional complexity Artikel In: NATURE GENETICS, Bd. 57, Nr. 2, 2025, ISSN: 1061-4036. @article{WOS:001411678300001,
title = {A barley pan-transcriptome reveals layers of genotype-dependent transcriptional complexity},
author = {Wenbin Guo and Miriam Schreiber and Vanda B. Marosi and Paolo Bagnaresi and Morten Egevang Jorgensen and Katarzyna B. Braune and Ken Chalmers and Brett Chapman and Viet Dang and Christoph Dockter and Anne Fiebig and Geoffrey B. Fincher and Agostino Fricano and John Fuller and Allison Haaning and Georg Haberer and Axel Himmelbach and Murukarthick Jayakodi and Yong Jia and Nadia Kamal and Peter Langridge and Chengdao Li and Qiongxian Lu and Thomas Lux and Martin Mascher and Klaus F. X. Mayer and Nicola Mccallum and Linda Milne and Gary J. Muehlbauer and Martin T. S. Nielsen and Sudharsan Padmarasu and Pai Rosager Pedas and Klaus Pillen and Curtis Pozniak and Magnus W. Rasmussen and Kazuhiro Sato and Thomas Schmutzer and Uwe Scholz and Danuta Schueler and Hana Simkova and Birgitte Skadhauge and Nils Stein and Nina W. Thomsen and Cynthia Voss and Penghao Wang and Ronja Wonneberger and Xiao-Qi Zhang and Guoping Zhang and Luigi Cattivelli and Manuel Spannagl and Micha Bayer and Craig Simpson and Runxuan Zhang and Robbie Waugh},
doi = {10.1038/s41588-024-02069-y},
issn = {1061-4036},
year = {2025},
date = {2025-02-01},
urldate = {2025-02-01},
journal = {NATURE GENETICS},
volume = {57},
number = {2},
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
quantification, we constructed genotype-specific 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
significant 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 diversification. 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.},
keywords = {Gene expression, Pan-genome, Pan-transcriptome, Plant genetics, RNA sequencing},
pubstate = {published},
tppubtype = {article}
}
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
quantification, we constructed genotype-specific 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
significant 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 diversification. 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. |