Differential Gene Expression by RNA-Seq Analysis of the Primo Vessel in the Rabbit Lymph

BackgroundRNA-seq is a useful tool for analysis of gene expression. However, its robustness is greatly affected by a number of artifacts. One of them is the presence of duplicated reads.ResultsTo infer the influence of different methods of removal of duplicated reads on estimation of gene expression in cancer genomics, we analyzed paired samples of hepatocellular carcinoma (HCC) and non-tumor liver tissue. Four protocols of data analysis were applied to each sample: processing without deduplication, deduplication using a method implemented in samtools, and deduplication based on one or two molecular indices (MI). We also analyzed the influence of sequencing layout (single read or paired end) and read length. We found that deduplication without MI greatly affects estimated expression values; this effect is the most pronounced for highly expressed genes.ConclusionThe use of unique molecular identifiers greatly improves accuracy of RNA-seq analysis, especially for highly expressed genes. We developed a set of scripts that enable handling of MI and their incorporation into RNA-seq analysis pipelines. Deduplication without MI affects results of differential gene expression analysis, producing a high proportion of false negative results. The absence of duplicate read removal is biased towards false positives. In those cases where using MI is not possible, we recommend using paired-end sequencing layout.

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SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis

10.1101/021915 ◽

2015 ◽

Author(s):

Benjamin K Johnson ◽

Matthew B Scholz ◽

Tracy K Teal ◽

Robert B Abramovitch

Keyword(s):

Gene Expression ◽

Differential Gene Expression ◽

Quality Analysis ◽

Rna Seq ◽

Sequencing Data ◽

Data Set ◽

Bacterial Rna ◽

Analysis Workflow ◽

Differential Gene ◽

Reference Counting

Summary: SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots. The workflow is implemented in Python for file management and sequential execution of each analysis step and is available for Mac OS X, Microsoft Windows, and Linux. To promote the use of SPARTA as a teaching platform, a web-based tutorial is available explaining how RNA-seq data are processed and analyzed by the software. Availability and Implementation: Tutorial and workflow can be found at sparta.readthedocs.org. Teaching materials are located at sparta-teaching.readthedocs.org. Source code can be downloaded at www.github.com/abramovitchMSU/, implemented in Python and supported on Mac OS X, Linux, and MS Windows. Contact: Robert B. Abramovitch ([email protected]) Supplemental Information: Supplementary data are available online

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Differential gene expression associated with a floral scent polymorphism in the evening primrose Oenothera harringtonii (Onagraceae)

10.1101/2021.01.12.426409 ◽

2021 ◽

Author(s):

Lindsey L. Bechen ◽

Matthew G. Johnson ◽

Geoffrey T. Broadhead ◽

Rachel A. Levin ◽

Rick P. Overson ◽

...

Keyword(s):

Gene Expression ◽

Differential Gene Expression ◽

Floral Scent ◽

Terpene Synthase ◽

Rna Seq ◽

Loss Of Function ◽

Terpene Biosynthesis ◽

Terpene Synthases ◽

Evening Primrose ◽

Differential Gene

AbstractBackgroundPlant volatiles play an important role in both plant-pollinator and plant-herbivore interactions. Intraspecific polymorphisms in volatile production are ubiquitous, but studies that explore underlying differential gene expression are rare. Oenothera harringtonii populations are polymorphic in floral emission of the monoterpene (R)-(-)-linalool; some plants emit (R)-(-)-linalool (linalool+ plants) while others do not (linalool-plants). However, the genes associated with differential production of this floral volatile in Oenothera are unknown. We used RNA-Seq to broadly characterize differential gene expression involved in (R)-(-)-linalool biosynthesis. To identify genes that may be associated with the polymorphism for this trait, we used RNA-Seq to compare gene expression in six different Oenothera harringtonii tissues from each of three linalool+ and linalool-plants.ResultsThree clusters of differentially expressed genes were enriched for terpene synthase activity: two were characterized by tissue-specific upregulation and one by upregulation only in plants with flowers that produce (R)-(-)-linalool. A molecular phylogeny of all terpene synthases identified two putative (R)-(-)-linalool synthase transcripts in Oenothera harringtonii, a single allele of which is found exclusively in linalool+ plants.ConclusionsBy using a naturally occurring polymorphism and comparing different tissues, we were able to identify genes putatively involved in the biosynthesis of (R)-(-)-linalool. Expression of these genes in linalool-plants suggests a regulatory polymorphism, rather than a population-specific loss-of-function allele. Additional terpene biosynthesis-related genes that are up-regulated in plants that emit (R)-(-)-linalool may be associated with herbivore defense, suggesting a potential economy of scale between plant reproduction and defense.

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