Search bioRxiv⌕ Search

bioRxiv · 10.1101/638106

BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq

Abstract

BackgroundTime consuming computational assembly and quantification of gene expression and splicing analysis from RNA-seq data vary considerably. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants.\n\nResultsA high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts - BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al., 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al., 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5 and 3 UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2,791 differentially alternatively spliced genes and 2,768 transcripts with differential transcript usage.\n\nConclusionA high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rapazote-Flores, P., Bayer, M., Milne, L., Mayer, C.-D., Fuller, J., Guo, W., Hedley, P. E., Morris, J., Halpin, C., Kam, J., McKim, S. M., Zwirek, M., Casao, M. C., Barakate, A., Schreiber, M., Stephen, G., Zhang, R., Brown, J. W., Waugh, R., Simpson, C. G.. 2019-05-16. BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq. https://doi.org/10.1101/638106

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Long-read DNA sequencing reveals global hypomethylation and focal hypermethylation in SDHx-deficient pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGL) are highly heritable neuroendocrine tumors of the autonomic ganglia. Genomic DNA in most cancer cells is hypomethylated. However, DNA in PPGLs secondary to mutations in succinate dehydrogenase complex (SDHx) genes is reportedly hypermethylated due to succinate-mediated inhibition of DNA demethylases. We used nanopore long-read sequencing to characterize the methylome of tumor and white blood cell DNA from SDHx and non-SDHx PPGL patients, alongside normal adrenal medulla. We find that both SDHx and non-SDHx PPGLs are globally hypomethylated, particularly at centromeres. In normal adrenal medulla, CpG islands marked by H3K4 methylation are hypomethylated, whereas CpG islands lacking H3K4 methylation are hypermethylated. In SDHx-related PPGL, some H3K4me-marked CpG islands are hypermethylated, but most are not. We propose that DNA methylation in SDHx-related PPGL reflects the global hypomethylation generally observed in tumors, partly offset by succinate-mediated inhibition of TET DNA demethylases. Opposing effects of succinate may alter the balance between DNA methylation (indirect inhibition of the DNMT3A/B DNA methylases via inhibition of H3K4me demethylases) and DNA demethylation (inhibition of TET DNA demethylases) at active CpG islands.

genomics↗

High piRNA abundance is a hallmark of evolutionarily persistent piRNA-producing loci.

PIWI-interacting RNAs (piRNAs) silence transposons in the germline, and the loci that produce them diverge rapidly between species. Yet, some loci retain both their genomic location and their piRNA production across large evolutionary distances, and the basis for this conservation is unclear. To identify the features that distinguish these persistent loci, we compared piRNA production at orthologous loci in three closely related mouse species, contrasting loci that produce piRNAs in all three species with those that do so in only one. Transposon content and UTR features, often linked to piRNA production, did not distinguish the two groups. Transcription extending beyond gene ends (readthrough) was more frequent at conserved loci, but did not explain conservation once the amount of piRNAs produced was taken into account. Instead, we found that the conserved loci are those that produce the most piRNAs. The same association holds true in human and two other primate species. We speculate that most piRNAs expressed in testis are tolerated molecular noise, and that only the highly expressed minority are likely to be functional.

genomics↗

Epigenome-informed Polymer Modeling Reveals Chromosome Folding Landscapes across Distinct Genetic and Epigenetic Contexts

Three-dimensional (3D) genome organization is critical for gene regulation, enabling long-range interactions between genes and distal regulatory elements. Genomic structural variations and epigenetic differences can perturb this organization, contributing to phenotypic variation and tissue-specific gene regulation. Prior studies have assessed the impact of these genetic and epigenetic changes on 3D genome folding, primarily using population-averaged features such as topologically associating domains and loops. However, growing evidence from single-cell and live-imaging studies indicates that chromosomes are highly dynamic and exist as heterogeneous ensembles of conformations. Here, we applied an epigenetic-state-informed polymer modeling framework to generate chromosomal conformational ensembles directly from cell- and tissue-specific epigenomic data. The resulting ensembles reproduced experimental Hi-C maps across cell lines and tissue types. Comparison of these conformational ensembles revealed that, although polymer dynamics were conserved across cell lines, their folding landscapes diverged. These differences arose primarily from cell-line-specific chromatin-state interaction networks and were concentrated in rare, long-lived contacts. Furthermore, modeling a TAD-boundary-disrupting deletion without re-optimizing the model parameters indicated a shift in the chromatin conformational ensemble from predominantly insulated to predominantly fused states. The modeled deletion also selectively strengthened active chromatin contacts and differentially disrupted enhancer contacts involving neighboring genes. Finally, comparison of two tissue types from the same donor revealed epigenetically driven rewiring of chromatin-state interaction networks. These findings establish chromosomal conformational ensembles as a sensitive readout of genome reorganization across distinct genetic and epigenetic contexts.

genomics↗