Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

Soneson, Charlotte; Love, Michael I.; Robinson, Mark D.

doi:10.12688/f1000research.7563.1

Cited by 2,615 publications

(1,024 citation statements)

References 34 publications

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“…A set of quasitranscripts was built for the genome and the eGFP, zeocin resistance, and pUC-origin sequences from the plasmids added. Transcripts then were quantified with Salmon and tximport (64), and the edgeR (65) package (R 3.3.3 software) was used to import and normalize the counts across the data sets in R. This gave a transcripts per million (TPM) value for each gene which should, assuming an even mapping distribution across the genome, be equivalent to one copy for most genes and then can be compared against the levels of the plasmid genes to see if they are present at a higher copy number. More details about how we calculated copy number are given in Data Set S7 in the supplemental material.…”

Section: Methodsmentioning

confidence: 99%

Effect of Plasmid Design and Type of Integration Event on Recombinant Protein Expression in Pichia pastoris

Vogl

Gebbie

Palfreyman

et al. 2018

Appl Environ Microbiol

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Pichia pastoris (syn. Komagataella phaffii) is one of the most common eukaryotic expression systems for heterologous protein production. Expression cassettes are typically integrated in the genome to obtain stable expression strains. In contrast to Saccharomyces cerevisiae, where short overhangs are sufficient to target highly specific integration, long overhangs are more efficient in P. pastoris and ectopic integration of foreign DNA can occur. Here, we aimed to elucidate the influence of ectopic integration by high-throughput screening of Ͼ700 transformants and whole-genome sequencing of 27 transformants. Different vector designs and linearization approaches were used to mimic the most common integration events targeted in P. pastoris. Fluorescence of an enhanced green fluorescent protein (eGFP) reporter protein was highly uniform among transformants when the expression cassettes were correctly integrated in the targeted locus. Surprisingly, most nonspecifically integrated transformants showed highly uniform expression that was comparable to specific integration, suggesting that nonspecific integration does not necessarily influence expression. However, a few clones (Ͻ10%) harboring ectopically integrated cassettes showed a greater variation spanning a 25-fold range, surpassing specifically integrated reference strains up to 6-fold. High-expression strains showed a correlation between increased gene copy numbers and high reporter protein fluorescence levels. Our results suggest that for comparing expression levels between strains, the integration locus can be neglected as long as a sufficient numbers of transformed strains are compared. For expression optimization of highly expressible proteins, increasing copy number appears to be the dominant positive influence rather than the integration locus, genomic rearrangements, deletions, or single-nucleotide polymorphisms (SNPs).IMPORTANCE Yeasts are commonly used as biotechnological production hosts for proteins and metabolites. In the yeast Saccharomyces cerevisiae, expression cassettes carrying foreign genes integrate highly specifically at the targeted sites in the genome. In contrast, cassettes often integrate at random genomic positions in nonconventional yeasts, such as Pichia pastoris (syn. Komagataella phaffii). Hence, cells from the same transformation event often behave differently, with significant clonal variation necessitating the screening of large numbers of strains. The importance of this study is that we systematically investigated the influence of integration events in more than 700 strains. Our findings provide novel insight into clonal variation in P. pastoris and, thus, how to avoid pitfalls and obtain reliable results. The underlying mechanisms may also play a role in other yeasts and hence could be generally relevant for recombinant yeast protein production strains.KEYWORDS integration, Pichia pastoris, protein expression, genome analysis T he yeast Pichia pastoris (syn. Komagataella phaffii) is widely used for heterologous protein p...

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Section: Methodsmentioning

confidence: 99%

Effect of Plasmid Design and Type of Integration Event on Recombinant Protein Expression in Pichia pastoris

Vogl

Gebbie

Palfreyman

et al. 2018

Appl Environ Microbiol

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“…For Sailfish and Salmon, outputs were converted to a Sleuth-ready format using wasabi [55]. For Kallisto, Sailfish, Salmon, and BitSeq, transcript-level values were condensed to gene-level values using tximport prior to evaluating gene-level differential expression [56]. For all differential expression analyses performed at the transcript-level, significant transcripts were converted to the corresponding gene for performance evaluation, such that if a single transcript was called as differentially expressed, the corresponding gene was also called differentially expressed.…”

Section: Methodsmentioning

confidence: 99%

Empirical assessment of analysis workflows for differential expression analysis of human samples using RNA-Seq

et al. 2017

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BackgroundRNA-Seq has supplanted microarrays as the preferred method of transcriptome-wide identification of differentially expressed genes. However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major processing steps: read alignment, expression modeling, and identification of differentially expressed genes. Although some studies have benchmarked these tools against gold standard gene expression sets, few have evaluated their performance in concert with one another. Additionally, there is a general lack of testing of such tools on real-world, physiologically relevant datasets, which often possess qualities not reflected in tightly controlled reference RNA samples or synthetic datasets.ResultsHere, we evaluate 219 combinatorial implementations of the most commonly used analysis tools for their impact on differential gene expression analysis by RNA-Seq. A test dataset was generated using highly purified human classical and nonclassical monocyte subsets from a clinical cohort, allowing us to evaluate the performance of 495 unique workflows, when accounting for differences in expression units and gene- versus transcript-level estimation. We find that the choice of methodologies leads to wide variation in the number of genes called significant, as well as in performance as gauged by precision and recall, calculated by comparing our RNA-Seq results to those from four previously published microarray and BeadChip analyses of the same cell populations. The method of differential gene expression identification exhibited the strongest impact on performance, with smaller impacts from the choice of read aligner and expression modeler. Many workflows were found to exhibit similar overall performance, but with differences in their calibration, with some biased toward higher precision and others toward higher recall.ConclusionsThere is significant heterogeneity in the performance of RNA-Seq workflows to identify differentially expressed genes. Among the higher performing workflows, different workflows exhibit a precision/recall tradeoff, and the ultimate choice of workflow should take into consideration how the results will be used in subsequent applications. Our analyses highlight the performance characteristics of these workflows, and the data generated in this study could also serve as a useful resource for future development of software for RNA-Seq analysis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1457-z) contains supplementary material, which is available to authorized users.

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“…Remaining reads were pseudoaligned to the human transcriptome (as per GRCh38.84 GTF file downloaded from Ensembl on 08/03/2016) and transcript abundances quantified using Kallisto (v0.44.0) 41 . The tximport R package (v1.8.0) 42 was then used to summarise transcript abundances to the gene level.…”

Section: Methodsmentioning

confidence: 99%

A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder

et al. 2018

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Lithium is the first-line treatment for bipolar affective disorder (BPAD) but two-thirds of patients respond only partially or not at all. The reasons for this high variability in lithium response are not well understood. Transcriptome-wide profiling, which tests the interface between genes and the environment, represents a viable means of exploring the molecular mechanisms underlying lithium response variability. Thus, in the present study we performed co-expression network analyses of whole-blood-derived RNA-seq data from n = 50 lithium-treated BPAD patients. Lithium response was assessed using the well-validated ALDA scale, which we used to define both a continuous and a dichotomous measure. We identified a nominally significant correlation between a co-expression module comprising 46 genes and lithium response represented as a continuous (i.e., scale ranging 0–10) phenotype (cor = −0.299, p = 0.035). Forty-three of these 46 genes had reduced mRNA expression levels in better lithium responders relative to poorer responders, and the central regulators of this module were all mitochondrially-encoded (MT-ND1, MT-ATP6, MT-CYB). Accordingly, enrichment analyses indicated that genes involved in mitochondrial functioning were heavily over-represented in this module, specifically highlighting the electron transport chain (ETC) and oxidative phosphorylation (OXPHOS) as affected processes. Disrupted ETC and OXPHOS activity have previously been implicated in the pathophysiology of BPAD. Our data adds to previous evidence suggesting that a normalisation of these processes could be central to lithium’s mode of action, and could underlie a favourable therapeutic response.

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Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

Cited by 2,615 publications

References 34 publications

Effect of Plasmid Design and Type of Integration Event on Recombinant Protein Expression in Pichia pastoris

Effect of Plasmid Design and Type of Integration Event on Recombinant Protein Expression in Pichia pastoris

Empirical assessment of analysis workflows for differential expression analysis of human samples using RNA-Seq

A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder

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