Best practices on the differential expression analysis of multi-species RNA-seq

Chung, Matthew; Bruno, Vincent M.; Rasko, David A.; Cuomo, Christina A.; Muñoz, José F.; Livny, Jonathan; Shetty, Amol; Mahurkar, Anup; Hotopp, Julie C. Dunning

doi:10.1186/s13059-021-02337-8

Cited by 69 publications

(50 citation statements)

References 153 publications

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“…There are various approaches to define the background of an RNA-seq dataset [ 32 ]. The effect of different filtering methods on differential expression results has been investigated [ 33 ], and provides us with some practical recommendations to avoid sampling biases described by Timmons et al [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Urgent need for consistent standards in functional enrichment analysis

et al. 2022

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Gene set enrichment tests (a.k.a. functional enrichment analysis) are among the most frequently used methods in computational biology. Despite this popularity, there are concerns that these methods are being applied incorrectly and the results of some peer-reviewed publications are unreliable. These problems include the use of inappropriate background gene lists, lack of false discovery rate correction and lack of methodological detail. To ascertain the frequency of these issues in the literature, we performed a screen of 186 open-access research articles describing functional enrichment results. We find that 95% of analyses using over-representation tests did not implement an appropriate background gene list or did not describe this in the methods. Failure to perform p-value correction for multiple tests was identified in 43% of analyses. Many studies lacked detail in the methods section about the tools and gene sets used. An extension of this survey showed that these problems are not associated with journal or article level bibliometrics. Using seven independent RNA-seq datasets, we show misuse of enrichment tools alters results substantially. In conclusion, most published functional enrichment studies suffered from one or more major flaws, highlighting the need for stronger standards for enrichment analysis.

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Section: Discussionmentioning

confidence: 99%

Urgent need for consistent standards in functional enrichment analysis

et al. 2022

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“…Furthermore, methods such as RNA-seq, comparative microarray, next-generation sequencing (NGS), and cDNA suppression subtracted hybridization (SSH) are appropriate for studying the whole transcriptome of pathogenic mycobacterial species. Recently, RNA-seq gene expression studies have shown the ability to capture pictures of the differential expression of transcripts seen in mycobacterium species ( Chung et al., 2021 ). Previous research revealed a new transcriptomic method that used overlapping of chromatin immunoprecipitation sequencing (ChIP-seq) RNAP (RNA Polymerase), and NusA RNA-Seq data to detect sRNA expression in Mtb .…”

Section: Multi-omics Approaches To Study Mycobacterial Diseasesmentioning

confidence: 99%

Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Ahamad

Gupta

Parashar

2022

Front. Cell. Infect. Microbiol.

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Mycobacteria are members of the Actinomycetales order, and they are classified into one family, Mycobacteriaceae. More than 20 mycobacterial species cause disease in humans. The Mycobacterium group, called the Mycobacterium tuberculosis complex (MTBC), has nine closely related species that cause tuberculosis in animals and humans. TB can be detected worldwide and one-fourth of the world’s population is contaminated with tuberculosis. According to the WHO, about two million dies from it, and more than nine million people are newly infected with TB each year. Mycobacterium tuberculosis (M. tuberculosis) is the most potential causative agent of tuberculosis and prompts enormous mortality and morbidity worldwide due to the incompletely understood pathogenesis of human tuberculosis. Moreover, modern diagnostic approaches for human tuberculosis are inefficient and have many lacks, while MTBC species can modulate host immune response and escape host immune attacks to sustain in the human body. “Multi-omics” strategies such as genomics, transcriptomics, proteomics, metabolomics, and deep sequencing technologies could be a comprehensive strategy to investigate the pathogenesis of mycobacterial species in humans and offer significant discovery to find out biomarkers at the early stage of disease in the host. Thus, in this review, we attempt to understand an overview of the mission of “omics” approaches in mycobacterial pathogenesis, including tuberculosis, leprosy, and other mycobacterial diseases.

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“…High-throughput sequencing technologies have been used to explore complex biological and physiological processes of microbes. Transcriptomic analysis based on RNA sequencing is a reliable approach to profile genes that are expressed differently and for understanding the gene network [ 32 ]. Therefore, transcriptomics can provide a system-wide understanding of the complex biological processes of fungi.…”

Section: Introductionmentioning

confidence: 99%

Multi-Omics Techniques for Analysis Antifungal Mechanisms of Lipopeptides Produced by Bacillus velezensis GS-1 against Magnaporthe oryzae In Vitro

Zhang

Zhao

Chen

et al. 2022

IJMS

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Magnaporthe oryzae is a fungal pathogen that causes rice blast, a highly destructive disease. In the present study, the bacteria strain GS-1 was isolated from the rhizosphere soil of ginseng and identified as Bacillus velezensis through 16S rRNA gene sequencing, whole genome assembly, and average nucleotide identity analysis. B. velezensis strain GS-1 exhibited significant antagonistic activity to several plant fungal pathogens. Through whole genome sequencing, 92 Carbohydrate-Active Enzymes and 13 gene clusters that encoded for secondary metabolites were identified. In addition, strain GS-1 was able to produce the lipopeptide compounds, surfactin, fengycin, and plantazolicin. The inhibitory effects of lipopeptide compounds on M. oryzae were confirmed, and the antagonistic mechanism was explored using transcriptomics and metabolomics analysis. Differential expressed genes (DEGs) and differential accumulated metabolites (DAMs) revealed that the inhibition of M. oryzae by lipopeptide produced by GS-1 downregulated the expression of genes involved in amino acid metabolism, sugar metabolism, oxidative phosphorylation, and autophagy. These results may explain why GS-1 has antagonistic activity to fungal pathogens and revealed the mechanisms underlying the inhibitory effects of lipopeptides produced by GS-1 on fungal growth, which may provide a theoretical basis for the potential application of B. velezensis GS-1 in future plant protection.

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Best practices on the differential expression analysis of multi-species RNA-seq

Cited by 69 publications

References 153 publications

Urgent need for consistent standards in functional enrichment analysis

Urgent need for consistent standards in functional enrichment analysis

Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Multi-Omics Techniques for Analysis Antifungal Mechanisms of Lipopeptides Produced by Bacillus velezensis GS-1 against Magnaporthe oryzae In Vitro

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