scholarly journals AtRTD2: A Reference Transcript Dataset for accurate quantification of alternative splicing and expression changes in Arabidopsis thaliana RNA-seq data

2016 ◽  
Author(s):  
Runxuan Zhang ◽  
Cristiane P. G. Calixto ◽  
Yamile Marquez ◽  
Peter Venhuizen ◽  
Nikoleta A. Tzioutziou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Experimental Data ◽  
Alternative Splicing ◽  
Rna Seq ◽  
Protein Coding ◽  
Transcript Isoforms ◽  
Transcript Quantification ◽  
Protein Coding Genes ◽  
Genome Wide ◽  
Reference Transcript

AbstractBackgroundAlternative splicing is the major post-transcriptional mechanism by which gene expression is regulated and affects a wide range of processes and responses in most eukaryotic organisms. RNA-sequencing (RNA-seq) can generate genome-wide quantification of individual transcript isoforms to identify changes in expression and alternative splicing. RNA-seq is an essential modern tool but its ability to accurately quantify transcript isoforms depends on the diversity, completeness and quality of the transcript information.ResultsWe have developed a new Reference Transcript Dataset for Arabidopsis (AtRTD2) for RNA-seq analysis containing over 82k non-redundant transcripts, whereby 74,194 transcripts originate from 27,667 protein-coding genes. A total of 13,524 protein-coding genes have at least one alternatively spliced transcript in AtRTD2 such that about 60% of the 22,453 protein-coding, intron-containing genes in Arabidopsis undergo alternative splicing. More than 600 putative U12 introns were identified in more than 2,000 transcripts. AtRTD2 was generated from transcript assemblies of ca. 8.5 billion pairs of reads from 285 RNA-seq data sets obtained from 129 RNA-seq libraries and merged along with the previous version, AtRTD, and Araport11 transcript assemblies. AtRTD2 increases the diversity of transcripts and through application of stringent filters represents the most extensive and accurate transcript collection for Arabidopsis to date. We have demonstrated a generally good correlation of alternative splicing ratios from RNA-seq data analysed by Salmon and experimental data from high resolution RT-PCR. However, we have observed inaccurate quantification of transcript isoforms for genes with multiple transcripts which have variation in the lengths of their UTRs. This variation is not effectively corrected in RNA-seq analysis programmes and will therefore impact RNA-seq analyses generally. To address this, we have tested different genome-wide modifications of AtRTD2 to improve transcript quantification and alternative splicing analysis. As a result, we release AtRTD2-QUASI specifically for use in Quantification of Alternatively Spliced Isoforms and demonstrate that it out-performs other available transcriptomes for RNA-seq analysis.ConclusionsWe have generated a new transcriptome resource for RNA-seq analyses in Arabidopsis (AtRTD2) designed to address quantification of different isoforms and alternative splicing in gene expression studies. Experimental validation of alternative splicing changes identified inaccuracies in transcript quantification due to UTR length variation. To solve this problem, we also release a modified reference transcriptome, AtRTD2-QUASI for quantification of transcript isoforms, which shows high correlation with experimental data.

scholarly journals Tri-methylation of Histone H3 Lysine 4 Facilitates Gene Expression in Ageing Cells

2017 ◽  
Author(s):  
Cristina Cruz ◽  
Monica Della Rosa ◽  
Christel Krueger ◽  
Qian Gao ◽  
Lucy Field ◽  
...  
Keyword(s):  
Gene Expression ◽  
Budding Yeast ◽  
Histone H3 ◽  
Specific Factor ◽  
Protein Coding ◽  
Replicative Lifespan ◽  
Protein Coding Genes ◽  
Genome Wide ◽  
Normal Expression ◽  
Transcriptional Induction

AbstractTranscription of protein coding genes is accompanied by recruitment of COMPASS to promoter-proximal chromatin, which deposits di- and tri-methylation on histone H3 lysine 4 (H3K4) to form H3K4me2 and H3K4me3. Here we determine the importance of COMPASS in maintaining gene expression across lifespan in budding yeast. We find that COMPASS mutations dramatically reduce replicative lifespan and cause widespread gene expression defects. Known repressive functions of H3K4me2 are progressively lost with age, while hundreds of genes become dependent on H3K4me3 for full expression. Induction of these H3K4me3 dependent genes is also impacted in young cells lacking COMPASS components including the H3K4me3-specific factor Spp1. Remarkably, the genome-wide occurrence of H3K4me3 is progressively reduced with age despite widespread transcriptional induction, minimising the normal positive correlation between promoter H3K4me3 and gene expression. Our results provide clear evidence that H3K4me3 is required to attain normal expression levels of many genes across organismal lifespan.

scholarly journals Identifying inaccuracies in gene expression estimates from unstranded RNA-seq data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mikhail Pomaznoy ◽  
Ashu Sethi ◽  
Jason Greenbaum ◽  
Bjoern Peters
Keyword(s):  
Gene Expression ◽  
Differential Expression Analysis ◽  
Cell Types ◽  
Library Preparation ◽  
Rna Seq ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Machine Learning Model ◽  
Specific Manner ◽  
Library Preparation Protocol

Abstract RNA-seq methods are widely utilized for transcriptomic profiling of biological samples. However, there are known caveats of this technology which can skew the gene expression estimates. Specifically, if the library preparation protocol does not retain RNA strand information then some genes can be erroneously quantitated. Although strand-specific protocols have been established, a significant portion of RNA-seq data is generated in non-strand-specific manner. We used a comprehensive stranded RNA-seq dataset of 15 blood cell types to identify genes for which expression would be erroneously estimated if strand information was not available. We found that about 10% of all genes and 2.5% of protein coding genes have a two-fold or higher difference in estimated expression when strand information of the reads was ignored. We used parameters of read alignments of these genes to construct a machine learning model that can identify which genes in an unstranded dataset might have incorrect expression estimates and which ones do not. We also show that differential expression analysis of genes with biased expression estimates in unstranded read data can be recovered by limiting the reads considered to those which span exonic boundaries. The resulting approach is implemented as a package available at https://github.com/mikpom/uslcount.

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

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Paulo Rapazote-Flores ◽  
Micha Bayer ◽  
Linda Milne ◽  
Claus-Dieter Mayer ◽  
John Fuller ◽  
...  
Keyword(s):  
Gene Expression ◽  
Splice Junction ◽  
Rna Seq ◽  
Rt Pcr ◽  
High Quality ◽  
Transcript Quantification ◽  
Reference Transcript ◽  
Alternatively Spliced ◽  
Time Required ◽  
Comprehensive Reference

Abstract Background The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. 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. Results A 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. Nature; 544: 427–433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20–28, 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, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage. Conclusion A 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.

scholarly journals The value of genotype-specific reference for transcriptome analyses

2021 ◽  
Author(s):  
Wenbin Guo ◽  
Max Coulter ◽  
Robbie Waugh ◽  
Runxuan Zhang
Keyword(s):  
Alternative Splicing ◽  
Reference Genome ◽  
Transcriptome Assembly ◽  
Specific Reference ◽  
Rna Seq ◽  
High Quality ◽  
Common Reference ◽  
Transcript Quantification ◽  
Gene Level ◽  
Reference Transcript

High quality transcriptome assembly using short reads from RNA-seq data still heavily relies upon reference-based approaches, of which the primary step is to align RNA-seq reads to a single reference genome of haploid sequence. However, it is increasingly apparent that while different genotypes within a species share core genes, they also contain variable numbers of specific genes that are only present a subset of individuals. Using a common reference may thus lead to a loss of genotype-specific information in the assembled transcript dataset and the generation of erroneous, incomplete or misleading transcriptomics analysis results. With the recent development of pan-genome information in many species, it is important that we understand the limitations of single genotype references for transcriptomics analysis. In this study, we quantitively evaluated the advantages of using genotype-specific reference genomes for transcriptome assembly and analysis using cultivated barley as a model. We mapped barley cultivar Barke RNA-seq reads to the Barke genome and to the cultivar Morex genome (common barley genome reference) to construct a genotype specific Reference Transcript Dataset (sRTD) and a common Reference Transcript Datasets (cRTD), respectively. We compared the two RTDs according to their transcript diversity, transcript sequence and structure similarity and the accuracy they provided for transcript quantification and differential expression analysis. Our evaluation shows that the sRTD has a significantly higher diversity of transcripts and alternative splicing events. Despite using a high-quality reference genome for assembly of the cRTD, we miss ca. 40% transcripts present in the sRTD and cRTD only has ca. 70% true assemblies. We found that the sRTD is more accurate for transcript quantification as well as differential expression and differential alternative splicing analysis. However, gene level quantification and comparative expression analysis are less affected by the source RTD, which indicates that analysing transcriptomic data at the gene level may be a reasonable compromise when a high-quality genotype-specific reference is not available.

scholarly journals Functional and transcriptional profiling of non-coding RNAs in yeast reveal context-dependent phenotypes and widespread in trans effects on the protein regulatory network

2020 ◽  
Author(s):  
Laura Natalia Balarezo-Cisneros ◽  
Steven Parker ◽  
Marcin G Fraczek ◽  
Soukaina Timouma ◽  
Ping Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Environmental Conditions ◽  
Mode Of Action ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Genome Wide ◽  
In Trans ◽  
Non Coding Rnas ◽  
The Impact

AbstractNon-coding RNAs (ncRNAs), including the more recently identified Stable Unannotated Transcripts (SUTs) and Cryptic Unstable Transcripts (CUTs), are increasingly being shown to play pivotal roles in the transcriptional and post-transcriptional regulation of genes in eukaryotes. Here, we carried out a large-scale screening of ncRNAs in Saccharomyces cerevisiae, and provide evidence for SUT and CUT function. Phenotypic data on 372 ncRNA deletion strains in 23 different growth conditions were collected, identifying ncRNAs responsible for significant cellular fitness changes. Transcriptome profiles were assembled for 18 haploid ncRNA deletion mutants and 2 essential ncRNA heterozygous deletants. Guided by the resulting RNA-seq data we analysed the genome-wide dysregulation of protein coding genes and non-coding transcripts. Novel functional ncRNAs, SUT125, SUT126, SUT035 and SUT532 that act in trans by modulating transcription factors were identified. Furthermore, we described the impact of SUTs and CUTs in modulating coding gene expression in response of different environmental conditions, regulating important biological process such as respiration (SUT125, SUT126, SUT035, SUT432), steroid biosynthesis (CUT494, SUT530, SUT468) or rRNA processing (SUT075 and snR30). Overall, this data captures and integrates the regulatory and phenotypic network of ncRNAs and protein coding genes, providing genome-wide evidence of the impact of ncRNAs on cellular homeostasis.Author SummaryThe yeast genome contains 25% of non-coding RNA molecules (ncRNAs), which do not translate into proteins but are involved in regulation of gene expression. ncRNAs can affect nearby genes by physically interfering with their transcription (cis mode of action), or they interact with DNA, proteins or others RNAs to regulate the expression of distant genes (trans mode of action). Examples of cis-acting ncRNAs have been broadly described, however genome-wide studies to identify functional trans-acting ncRNAs involved in global gene regulation are still lacking. Here, we used the ncRNA yeast deletion collection to score their impact on cellular function in different environmental conditions. A group of 20 ncRNAs mutants with broad fitness diversity were selected to investigate their effect on the protein and ncRNA expression network. We showed a high correlation between altered phenotypes and global transcriptional changes, in an environmental dependent manner. We confirmed the widespread trans acting expressional regulation of ncRNAs in the genome and their role in affecting transcription factors. These findings support the notion of the involvement on ncRNAs in fine tuning the cellular expression via regulations of TFs, as an advantageous RNA-mediated mechanism that can be fast and cost-effective for the cells.

scholarly journals Comparative genomics of muskmelon reveals a potential role for retrotransposons in the modification of gene expression

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Ryoichi Yano ◽  
Tohru Ariizumi ◽  
Satoko Nonaka ◽  
Yoichi Kawazu ◽  
Silin Zhong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fruit Ripening ◽  
Expression Patterns ◽  
Rna Seq ◽  
Protein Coding ◽  
Genome Wide ◽  
Oxford Nanopore ◽  
Melon Genome ◽  
Number Variation ◽  
Genome Assemblies

AbstractMelon exhibits substantial natural variation especially in fruit ripening physiology, including both climacteric (ethylene-producing) and non-climacteric types. However, genomic mechanisms underlying such variation are not yet fully understood. Here, we report an Oxford Nanopore-based high-grade genome reference in the semi-climacteric cultivar Harukei-3 (378 Mb + 33,829 protein-coding genes), with an update of tissue-wide RNA-seq atlas in the Melonet-DB database. Comparison between Harukei-3 and DHL92, the first published melon genome, enabled identification of 24,758 one-to-one orthologue gene pairs, whereas others were candidates of copy number variation or presence/absence polymorphisms (PAPs). Further comparison based on 10 melon genome assemblies identified genome-wide PAPs of 415 retrotransposon Gag-like sequences. Of these, 160 showed fruit ripening-inducible expression, with 59.4% of the neighboring genes showing similar expression patterns (r > 0.8). Our results suggest that retrotransposons contributed to the modification of gene expression during diversification of melon genomes, and may affect fruit ripening-inducible gene expression.

scholarly journals High temporal resolution RNA-seq time course data reveals mammalian lncRNA activation mirrors neighbouring protein-coding genes

2021 ◽  
Author(s):  
Walter Muskovic ◽  
Eva Slavich ◽  
Ben Maslen ◽  
Dominik Kaczorowski ◽  
Joseph Cursons ◽  
...  
Keyword(s):  
Gene Expression ◽  
Temporal Resolution ◽  
Time Course ◽  
Human Cells ◽  
Careful Examination ◽  
High Temporal Resolution ◽  
Rna Seq ◽  
Protein Coding ◽  
Lncrna Expression ◽  
Protein Coding Genes

Background: The advent of next-generation sequencing revealed extensive transcription beyond protein-coding genes, identifying tens of thousands of long non-coding RNAs (lncRNAs). Selected functional examples raised the possibility that lncRNAs, as a class, may maintain broad regulatory roles. Compellingly, lncRNA expression is strongly linked with adjacent protein-coding gene expression, suggesting a potential cis-regulatory function. Evidence for these regulatory roles may be obtained through careful examination of the precise timing of lncRNA expression relative to adjacent protein-coding genes. Results: Where causal cis-regulatory relationships exist, lncRNA activation is expected to precede changes in adjacent target gene expression. Using an RNA-seq time course of uniquely high temporal resolution, we profiled the expression dynamics of several thousand lncRNAs and protein-coding genes in synchronized, transitioning human cells. Our findings reveal lncRNAs are expressed synchronously with adjacent protein-coding genes. Analysis of lipopolysaccharide-activated mouse dendritic cells revealed the same temporal relationship observed in transitioning human cells. Conclusion: Our findings suggest broad-scale cis-regulatory roles for lncRNAs are not common. The strong association between lncRNAs and adjacent genes may instead indicate an origin as transcriptional by-products from active protein-coding gene promoters and enhancers.

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

2019 ◽  
Author(s):  
Paulo Rapazote-Flores ◽  
Micha Bayer ◽  
Linda Milne ◽  
Claus-Dieter Mayer ◽  
John Fuller ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Genome ◽  
Splice Junction ◽  
Rna Seq ◽  
Rt Pcr ◽  
High Quality ◽  
Transcript Quantification ◽  
Reference Transcript ◽  
Alternatively Spliced ◽  
Comprehensive Reference

AbstractBackgroundTime 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.ResultsA 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.ConclusionA 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.

scholarly journals Genome-wide characterization of differential transcript usage in Arabidopsis thaliana

2017 ◽  
Author(s):  
Dries Vaneechoutte ◽  
April R. Estrada ◽  
Ying-Chen Lin ◽  
Ann E. Loraine ◽  
Klaas Vandepoele
Keyword(s):  
Arabidopsis Thaliana ◽  
Alternative Splicing ◽  
Single Gene ◽  
Simulated Data ◽  
Protein Sequences ◽  
Response To Treatment ◽  
Rna Seq ◽  
Protein Coding ◽  
Genome Wide ◽  
High Consistency

SUMMARYAlternative splicing and the usage of alternate transcription start- or stop sites allows a single gene to produce multiple transcript isoforms. Most plant genes express certain isoforms at a significantly higher level than others, but under specific conditions this expression dominance can change, resulting in a different set of dominant isoforms. These events of Differential Transcript Usage (DTU) have been observed for thousands of Arabidopsis thaliana, Zea mays and Vitis vinifera genes and have been linked to development and stress response. However, the characteristics of these genes, nor the implications of DTU on their protein coding sequences or functions, are currently well understood. Here we present a dataset of isoform dominance and DTU for all genes in the AtRTD2 reference transcriptome based on a protocol that was benchmarked on simulated data and validated through comparison with a published RT-PCR panel. We report DTU events for 8,148 genes across 206 public RNA-Seq samples and find that protein sequences are affected in 22% of the cases. The observed DTU events show high consistency across replicates and reveal reproducible patterns in response to treatment and development. We also demonstrate that genes with different evolutionary ages, expression breadths, and functions show large differences in the frequency at which they undergo DTU and in the effect that these events have on their protein sequences. Finally, we showcase how the generated dataset can be used to explore DTU events for genes of interest or to find genes with specific DTU in samples of interest.SIGNIFICANCE STATEMENTDifferential transcript usage through alternative splicing has been reported for thousands of genes in plants, yet genome-wide datasets to study the implications for gene functions are thus far not available. Here we present the first reference dataset of isoform dominance and differential transcript usage for Arabidopsis thaliana based on 206 public RNA-Seq samples and provide insights in the occurrence and functional consequences of alternative splicing.

Sign in / Sign up

Export Citation Format

Share Document