Optimization of an RNA-Seq Differential Gene Expression Analysis Depending on Biological Replicate Number and Library Size

A comprehensive review of the applications of RNA sequencing in celiac disease research

RNA sequencing (RNA-seq) has undergone substantial advancements in recent decades and has emerged as a vital technique for profiling the transcriptome. The transition from bulk sequencing to single-cell and spatial approaches has facilitated the achievement of higher precision at cell resolution. It provides valuable biological knowledge about individual immune cells and aids in the discovery of the molecular mechanisms that contribute to the development of autoimmune diseases. Celiac disease (CeD) is an autoimmune disorder characterized by a strong immune response to gluten consumption. RNA-seq has led to significantly advanced research in multiple fields, particularly in CeD research. It has been instrumental in studies involving comparative transcriptomics, nutritional genomics and wheat research, cancer research in the context of CeD, genetic and noncoding RNA-mediated epigenetic insights, disease monitoring and biomarker discovery, regulation of mitochondrial functions, therapeutic target identification and drug mechanism of action, dietary factors, immune cell profiling and the immune landscape. This review offers a comprehensive examination of recent RNA-seq technology research in the field of CeD, highlighting future challenges and opportunities for its application.

Yeast eIF2A has a minimal role in translation initiation and uORF-mediated translational control in vivo

Initiating translation of most eukaryotic mRNAs depends on recruitment of methionyl initiator tRNA (Met-tRNAi) in a ternary complex (TC) with GTP-bound eukaryotic initiation factor 2 (eIF2) to the small (40S) ribosomal subunit, forming a 43S preinitiation complex (PIC) that attaches to the mRNA and scans the 5'-untranslated region (5' UTR) for an AUG start codon. Previous studies have implicated mammalian eIF2A in GTP-independent binding of Met-tRNAi to the 40S subunit and its recruitment to specialized mRNAs that do not require scanning, and in initiation at non-AUG start codons, when eIF2 function is attenuated by phosphorylation of its α-subunit during stress. The role of eIF2A in translation in vivo is poorly understood however, and it was unknown whether the conserved ortholog in budding yeast can functionally substitute for eIF2. We performed ribosome profiling of a yeast deletion mutant lacking eIF2A and isogenic wild-type (WT) cells in the presence or absence of eIF2α phosphorylation induced by starvation for amino acids isoleucine and valine. Whereas starvation of WT confers changes in translational efficiencies (TEs) of hundreds of mRNAs, the eIF2AΔ mutation conferred no significant TE reductions for any mRNAs in non-starved cells, and it reduced the TEs of only a small number of transcripts in starved cells containing phosphorylated eIF2α. We found no evidence that eliminating eIF2A altered the translation of mRNAs containing putative internal ribosome entry site (IRES) elements, or harboring uORFs initiated by AUG or near-cognate start codons, in non-starved or starved cells. Thus, very few mRNAs (possibly only one) appear to employ eIF2A for Met-tRNAi recruitment in yeast cells, even when eIF2 function is attenuated by stress.

Yeast eIF2A has a minimal role in translation initiation and uORF-mediated translational control in vivo

Initiating translation of most eukaryotic mRNAs depends on recruitment of methionyl initiator tRNA (Met-tRNAi) in a ternary complex (TC) with GTP-bound eukaryotic initiation factor 2 (eIF2) to the small (40S) ribosomal subunit, forming a 43S preinitiation complex (PIC) that attaches to the mRNA and scans the 5'-untranslated region (5' UTR) for an AUG start codon. Previous studies have implicated mammalian eIF2A in GTP-independent binding of Met-tRNAi to the 40S subunit and its recruitment to specialized mRNAs that do not require scanning, and in initiation at non-AUG start codons, when eIF2 function is attenuated by phosphorylation of its α-subunit during stress. The role of eIF2A in translation in vivo is poorly understood however, and it was unknown whether the conserved ortholog in budding yeast can functionally substitute for eIF2. We performed ribosome profiling of a yeast deletion mutant lacking eIF2A and isogenic wild-type (WT) cells in the presence or absence of eIF2α phosphorylation induced by starvation for amino acids isoleucine and valine. Whereas starvation of WT confers changes in translational efficiencies (TEs) of hundreds of mRNAs, the eIF2AΔ mutation conferred no significant TE reductions for any mRNAs in non-starved cells, and it reduced the TEs of only a small number of transcripts in starved cells containing phosphorylated eIF2α. We found no evidence that eliminating eIF2A altered the translation of mRNAs containing putative IRES elements, or harboring uORFs initiated by AUG or near-cognate start codons, in non-starved or starved cells. Thus, very few mRNAs (possibly only one) appear to employ eIF2A for Met-tRNAi recruitment in yeast cells, even when eIF2 function is attenuated by stress.

miR-128-3p inhibits intramuscular adipocytes differentiation in chickens by downregulating FDPS

BACKGROUND

Intramuscular fat (IMF) content is the major indicator for evaluating chicken meat quality due to its positive correlation with tenderness, juiciness, and flavor. An increasing number of studies are focusing on the functions of microRNAs (miRNAs) in intramuscular adipocyte differentiation. However, little is known about the association of miR-128-3p with intramuscular adipocyte differentiation. Our previous RNA-seq results indicated that miR-128-3p was differentially expressed at different periods in chicken intramuscular adipocytes, revealing a possible association with intramuscular adipogenesis. The purpose of this research was to investigate the biological functions and regulatory mechanism of miR-128-3p in chicken intramuscular adipogenesis.

RESULTS

The results of a series of assays confirmed that miR-128-3p could promote the proliferation and inhibit the differentiation of intramuscular adipocytes. A total of 223 and 1,050 differentially expressed genes (DEGs) were identified in the mimic treatment group and inhibitor treatment group, respectively, compared with the control group. Functional enrichment analysis revealed that the DEGs were involved in lipid metabolism-related pathways, such as the MAPK and TGF-β signaling pathways. Furthermore, target gene prediction analysis showed that miR-128-3p can target many of the DEGs, such as FDPS, GGT5, TMEM37, and ASL2. The luciferase assay results showed that miR-128-3p targeted the 3' UTR of FDPS. The results of subsequent functional assays demonstrated that miR-128-3p acted as an inhibitor of intramuscular adipocyte differentiation by targeting FDPS.

CONCLUSION

miR-128-3p inhibits chicken intramuscular adipocyte differentiation by downregulating FDPS. Our findings provide a theoretical basis for the study of lipid metabolism and reveal a potential target for molecular breeding to improve meat quality.

Considerations for reproducible omics in aging research

Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.

Design, execution, and interpretation of plant RNA-seq analyses

Genomics has transformed our understanding of the genetic architecture of traits and the genetic variation present in plants. Here, we present a review of how RNA-seq can be performed to tackle research challenges addressed by plant sciences. We discuss the importance of experimental design in RNA-seq, including considerations for sampling and replication, to avoid pitfalls and wasted resources. Approaches for processing RNA-seq data include quality control and counting features, and we describe common approaches and variations. Though differential gene expression analysis is the most common analysis of RNA-seq data, we review multiple methods for assessing gene expression, including detecting allele-specific gene expression and building co-expression networks. With the production of more RNA-seq data, strategies for integrating these data into genetic mapping pipelines is of increased interest. Finally, special considerations for RNA-seq analysis and interpretation in plants are needed, due to the high genome complexity common across plants. By incorporating informed decisions throughout an RNA-seq experiment, we can increase the knowledge gained.

Methadone alters transcriptional programs associated with synapse formation in human cortical organoids

Opioid use disorder (OUD) among pregnant women has become an epidemic in the United States. Pharmacological interventions for maternal OUD most commonly involve methadone, a synthetic opioid analgesic that attenuates withdrawal symptoms and behaviors linked with drug addiction. However, evidence of methadone's ability to readily accumulate in neural tissue, and cause long-term neurocognitive sequelae, has led to concerns regarding its effect on prenatal brain development. We utilized human cortical organoid (hCO) technology to probe how this drug impacts the earliest mechanisms of cortico-genesis. Bulk mRNA sequencing of 2-month-old hCOs chronically treated with a clinically relevant dose of 1 μM methadone for 50 days revealed a robust transcriptional response to methadone associated with functional components of the synapse, the underlying extracellular matrix (ECM), and cilia. Co-expression network and predictive protein-protein interaction analyses demonstrated that these changes occurred in concert, centered around a regulatory axis of growth factors, developmental signaling pathways, and matricellular proteins (MCPs). TGFβ1 was identified as an upstream regulator of this network and appeared as part of a highly interconnected cluster of MCPs, of which thrombospondin 1 (TSP1) was most prominently downregulated and exhibited dose-dependent reductions in protein levels. These results demonstrate that methadone exposure during early cortical development alters transcriptional programs associated with synaptogenesis, and that these changes arise by functionally modulating extra-synaptic molecular mechanisms in the ECM and cilia. Our findings provide novel insight into the molecular underpinnings of methadone's putative effect on cognitive and behavioral development and a basis for improving interventions for maternal opioid addiction.

A field-wide assessment of differential expression profiling by high-throughput sequencing reveals widespread bias

We assess inferential quality in the field of differential expression profiling by high-throughput sequencing (HT-seq) based on analysis of datasets submitted from 2008 to 2020 to the NCBI GEO data repository. We take advantage of the parallel differential expression testing over thousands of genes, whereby each experiment leads to a large set of p-values, the distribution of which can indicate the validity of assumptions behind the test. From a well-behaved p-value set π0, the fraction of genes that are not differentially expressed can be estimated. We found that only 25% of experiments resulted in theoretically expected p-value histogram shapes, although there is a marked improvement over time. Uniform p-value histogram shapes, indicative of <100 actual effects, were extremely few. Furthermore, although many HT-seq workflows assume that most genes are not differentially expressed, 37% of experiments have π0-s of less than 0.5, as if most genes changed their expression level. Most HT-seq experiments have very small sample sizes and are expected to be underpowered. Nevertheless, the estimated π0-s do not have the expected association with N, suggesting widespread problems of experiments with controlling false discovery rate (FDR). Both the fractions of different p-value histogram types and the π0 values are strongly associated with the differential expression analysis program used by the original authors. While we could double the proportion of theoretically expected p-value distributions by removing low-count features from the analysis, this treatment did not remove the association with the analysis program. Taken together, our results indicate widespread bias in the differential expression profiling field and the unreliability of statistical methods used to analyze HT-seq data.

Decapping factor Dcp2 controls mRNA abundance and translation to adjust metabolism and filamentation to nutrient availability

Degradation of most yeast mRNAs involves decapping by Dcp1/Dcp2. DEAD-box protein Dhh1 has been implicated as an activator of decapping, in coupling codon non-optimality to enhanced degradation, and as a translational repressor, but its functions in cells are incompletely understood. RNA-Seq analyses coupled with CAGE sequencing of all capped mRNAs revealed increased abundance of hundreds of mRNAs in dcp2 Δ cells that appears to result directly from impaired decapping rather than elevated transcription, which was confirmed by ChIP-Seq analysis of RNA Polymerase II occupancies genome-wide. Interestingly, only a subset of mRNAs requires Dhh1 for targeting by Dcp2, and also generally requires the other decapping activators Pat1, Lsm2, Edc3 or Scd6; whereas most of the remaining transcripts utilize NMD factors for Dcp2-mediated turnover. Neither inefficient translation initiation nor stalled elongation appears to be a major driver of Dhh1-enhanced mRNA degradation. Surprisingly, ribosome profiling revealed that dcp2 Δ confers widespread changes in relative TEs that generally favor well-translated mRNAs. Because ribosome biogenesis is reduced while capped mRNA abundance is increased by dcp2 Δ, we propose that an increased ratio of mRNA to ribosomes increases competition among mRNAs for limiting ribosomes to favor efficiently translated mRNAs in dcp2 Δ cells. Interestingly, genes involved in respiration or utilization of alternative carbon or nitrogen sources are derepressed, and both mitochondrial function and cell filamentation (a strategy for nutrient foraging) are elevated by dcp2 Δ, suggesting that mRNA decapping sculpts gene expression post-transcriptionally to fine-tune metabolic pathways and morphological transitions according to nutrient availability.

Dynamic regulation of gonadal transposon control across the lifespan of the naturally short-lived African turquoise killifish

Although germline cells are considered to be functionally "immortal," both the germline and supporting somatic cells in the gonad within an organism experience aging. With increased age at parenthood, the age-related decline in reproductive success has become an important biological issue for an aging population. However, molecular mechanisms underlying reproductive aging across sexes in vertebrates remain poorly understood. To decipher molecular drivers of vertebrate gonadal aging across sexes, we perform longitudinal characterization of the gonadal transcriptome throughout the lifespan in the naturally short-lived African turquoise killifish (Nothobranchius furzeri). By combining mRNA-seq and small RNA-seq from 26 individuals, we characterize the aging gonads of young-adult, middle-aged, and old female and male fish. We analyze changes in transcriptional patterns of genes, transposable elements (TEs), and piRNAs. We find that testes seem to undergo only marginal changes during aging. In contrast, in middle-aged ovaries, the time point associated with peak female fertility in this strain, PIWI pathway components are transiently down-regulated, TE transcription is elevated, and piRNA levels generally decrease, suggesting that egg quality may already be declining at middle-age. Furthermore, we show that piRNA ping-pong biogenesis declines steadily with age in ovaries, whereas it is maintained in aging testes. To our knowledge, this data set represents the most comprehensive transcriptomic data set for vertebrate gonadal aging. This resource also highlights important pathways that are regulated during reproductive aging in either ovaries or testes, which could ultimately be leveraged to help restore aspects of youthful reproductive function.

Conservation of Nematocida microsporidia gene expression and host response in Caenorhabditis nematodes

Microsporidia are obligate intracellular parasites that are known to infect most types of animals. Many species of microsporidia can infect multiple related hosts, but it is not known if microsporidia express different genes depending upon which host species is infected or if the host response to infection is specific to each microsporidia species. To address these questions, we took advantage of two species of Nematocida microsporidia, N. parisii and N. ausubeli, that infect two species of Caenorhabditis nematodes, C. elegans and C. briggsae. We performed RNA-seq at several time points for each host infected with either microsporidia species. We observed that Nematocida transcription was largely independent of its host. We also observed that the host transcriptional response was similar when infected with either microsporidia species. Finally, we analyzed if the host response to microsporidia infection was conserved across host species. We observed that although many of the genes upregulated in response to infection are not direct orthologs, the same expanded gene families are upregulated in both Caenorhabditis hosts. Together our results describe the transcriptional interactions of Nematocida infection in Caenorhabditis hosts and demonstrate that these responses are evolutionarily conserved.

A toolkit for enhanced reproducibility of RNASeq analysis for synthetic biologists

Sequencing technologies, in particular RNASeq, have become critical tools in the design, build, test and learn cycle of synthetic biology. They provide a better understanding of synthetic designs, and they help identify ways to improve and select designs. While these data are beneficial to design, their collection and analysis is a complex, multistep process that has implications on both discovery and reproducibility of experiments. Additionally, tool parameters, experimental metadata, normalization of data and standardization of file formats present challenges that are computationally intensive. This calls for high-throughput pipelines expressly designed to handle the combinatorial and longitudinal nature of synthetic biology. In this paper, we present a pipeline to maximize the analytical reproducibility of RNASeq for synthetic biologists. We also explore the impact of reproducibility on the validation of machine learning models. We present the design of a pipeline that combines traditional RNASeq data processing tools with structured metadata tracking to allow for the exploration of the combinatorial design in a high-throughput and reproducible manner. We then demonstrate utility via two different experiments: a control comparison experiment and a machine learning model experiment. The first experiment compares datasets collected from identical biological controls across multiple days for two different organisms. It shows that a reproducible experimental protocol for one organism does not guarantee reproducibility in another. The second experiment quantifies the differences in experimental runs from multiple perspectives. It shows that the lack of reproducibility from these different perspectives can place an upper bound on the validation of machine learning models trained on RNASeq data.

Graphical Abstract

Barley (Hordeum Vulgare) Anther and Meiocyte RNA Sequencing: Mapping Sequencing Reads and Downstream Data Analyses

RNA sequencing (RNA-seq) data is by now the most common method to study differential gene expression. Here we present a pipeline from RNA-seq generation to analysis with examples based on our own barley anther and meiocyte transcriptome. The bioinformatics pipeline will give everyone, from a beginner to a more experienced user, the possibility to analyze their datasets and identify significantly differentially expressed genes. It also allows differential alternative splicing analysis which will become increasingly common due to the high regulatory impact on the gene expression. We describe use of the Galaxy interface for RNA-seq read quantification and the 3D RNA-seq app for the downstream data analysis.

Effects of rrm1 on NNV Resistance Revealed by RNA-seq and Gene Editing

Viral nervous necrosis (VNN) disease caused by the nervous necrosis virus (NNV) is a major disease, leading to a huge economic loss in aquaculture. Previous GWAS and QTL mapping have identified a major QTL for NNV resistance in linkage group 20 in Asian seabass. However, no causative gene for NNV resistance has been identified. In this study, RNA-seq from brains of Asian seabass fingerlings challenged with NNV at four time points (5, 10, 15 and 20 days post-challenge) identified 1228, 245, 189 and 134 DEGs, respectively. Eight DEGs, including rrm1, were located in the major QTL for NNV resistance. An association study in 445 survived and 608 dead fingerlings after NNV challenge revealed that the SNP in rrm1 were significantly associated with NNV resistance. Therefore, rrm1 was selected for functional analysis, as a candidate gene for NNV resistance. The expression of rrm1 was significantly increased in the gill, liver, spleen and muscle, and was suppressed in the brain, gut and skin after NNV challenge. The rrm1 protein was localized in the nuclear membrane. Over-expression of rrm1 significantly decreased viral RNA and titer in NNV-infected Asian seabass cells, whereas knock-down of rrm1 significantly increased viral RNA and titer in NNV-infected Asian seabass cells. The rrm1 knockout heterozygous zebrafish was more susceptible to NNV infection. Our study suggests that rrm1 is one of the causative genes for NNV resistance and the SNP in the gene may be applied for accelerating genetic improvement for NNV resistance.

Integrated miRNA and transcriptome profiling to explore the molecular determinism of convergent adaptation to corn in two lepidopteran pests of agriculture

Background

The degree to which adaptation to same environment is determined by similar molecular mechanisms, is a topic of broad interest in evolutionary biology, as an indicator of evolutionary predictability. We wished to address if adaptation to the same host plant in phytophagous insects involved related gene expression patterns. We compared sRNA-Seq and RNA-Seq data between two pairs of taxa of Ostrinia and Spodoptera frugiperda sharing maize as host-plant. For the latter, we had previously carried out a reciprocal transplant experiment by feeding of the larvae of the Corn strain (Sf-C) and the Rice strain (Sf-R) on corn versus rice and characterized the mRNA and miRNA responses.

Results

First, we predicted the genes encoding miRNA in Ostrinia nubilalis (On) and O. scapulalis (Os). Respectively 67 and 65 known miRNA genes, as well as 196 and 190 novel ones were predicted with Os genome using sncRNAs extracted from whole larvae feeding on corn or mugwort. In On, a read counts analysis showed that 37 (55.22%) known miRNAs and 19 (9.84%) novel miRNAs were differentially expressed (DE) on mugwort compared to corn (in Os, 25 known miRs (38.46%) and 8 novel ones (4.34%)). Between species on corn, 8 (12.5%) known miRNAs and 8 (6.83%) novel ones were DE while only one novel miRNA showed expression variation between species on mugwort. Gene target prediction led to the identification of 2953 unique target genes in On and 2719 in Os, among which 11.6% (344) were DE when comparing species on corn. 1.8% (54) of On miR targets showed expression variation upon a change of host-plant.

We found molecular changes matching convergent phenotype, i.e., a set of nine miRNAs that are regulated either according to the host-plant both in On and Sf-C or between them on the same plant, corn. Among DE miR target genes between taxa, 13.7% shared exactly the same annotation between the two pairs of taxa and had function related to insect host-plant interaction.

Conclusion

There is some similarity in underlying genetic mechanisms of convergent evolution of two distant Lepidopteran species having adopted corn in their host range, highlighting possible adaptation genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07905-7.

Effect of high variation in transcript expression on identifying differentially expressed genes in RNA-seq analysis

Great efforts have been made on the algorithms that deal with RNA-seq data to enhance the accuracy and efficiency of differential expression (DE) analysis. However, no consensus has been reached on the proper threshold values of fold change and adjusted p-value for filtering differentially expressed genes (DEGs). It is generally believed that the more stringent the filtering threshold, the more reliable the result of a DE analysis. Nevertheless, by analyzing the impact of both adjusted p-value and fold change thresholds on DE analyses, with RNA-seq data obtained for three different cancer types from the Cancer Genome Atlas (TCGA) database, we found that, for a given sample size, the reproducibility of DE results became poorer when more stringent thresholds were applied. No matter which threshold level was applied, the overlap rates of DEGs were generally lower for small sample sizes than for large sample sizes. The raw read count analysis demonstrated that the transcript expression of the same gene in different samples, whether in tumor groups or in normal groups, showed high variations, which resulted in a drastic fluctuation in fold change values and adjustedp-values when different sets of samples were used. Overall, more stringent thresholds did not yield more reliable DEGs due to high variations in transcript expression; the reliability of DEGs obtained with small sample sizes was more susceptible to these variations. Therefore, less stringent thresholds are recommended for screening DEGs. Moreover, large sample sizes should be considered in RNA-seq experimental designs to reduce the interfering effect of variations in transcript expression on DEG identification.

Ethylene signaling modulates tomato pollen tube growth through modifications of cell wall remodeling and calcium gradient

Ethylene modulates plant developmental processes including flower development. Previous studies have suggested ethylene participates in pollen tube (PT) elongation, and both ethylene production and perception seem critical at the time of fertilization. The full gene set regulated by ethylene during PT growth is unknown. To study this, we used various EThylene Receptor (ETR) tomato (Solanum lycopersicum) mutants: etr3-ko, a loss-of-function (LOF) mutant; and NR (NEVER RIPE), a gain-of-function (GOF) mutant. The etr3-ko PTs grew faster than wild-type (WT) PTs. Oppositely, NR PT elongation was slower than in WT, and PTs displayed larger diameters. ETR mutations result in feedback control of ethylene production. Furthermore, ethylene treatment of germinating pollen grains increased PT length in etr-ko mutants and WT, but not in NR. Treatment with the ethylene perception inhibitor 1-methylcyclopropene decreased PT length in etr-ko mutants and WT, but had no effect on NR. This confirmed that ethylene regulates PT growth. The comparison of PT transcriptomes in LOF and GOF mutants, etr3-ko and NR, both harboring mutations of the ETR3 gene, revealed that ethylene perception has major impacts on cell wall- and calcium-related genes as confirmed by microscopic observations showing a modified distribution of the methylesterified homogalacturonan pectic motif and of calcium load. Our results establish links between PT growth, ethylene, calcium, and cell wall metabolism, and also constitute a transcriptomic resource.

RNA Sequencing of CD4+ T Cells in Relapsing-Remitting Multiple Sclerosis Patients at Relapse: Deciphering the Involvement of Novel genes and Pathways

CD4⁺ T cells are known as a noteworthy potential modulator of inflammation in multiple sclerosis (MS). In the current study, we investigated the transcriptome profile of CD4⁺ T cells in patients with relapsing-remitting MS (RRMS) at the relapse phase. We performed RNA sequencing of CD4⁺ T cells isolated from four relapsing-remitting MS (RRMS) patients at the relapse phase and four age- and sex-matched healthy controls. The edgeR statistical method was employed to determine differentially expressed genes (DEGs). Gene set enrichment analysis was subsequently performed. Applying a physical interaction network, genes with higher degrees were selected as hub genes. A total of 1278 and 1034 genes were defined at significantly higher or lower levels, respectively, in CD4⁺ T cells of RRMS patients at the relapse phase as compared with healthy controls. The top up- and downregulated genes were JAML and KDM3A. The detected DEGs were remarkable on chromosomes 1 and 2, respectively. The DEGs were mainly enriched in the pathways "regulation of transcription, DNA-templated," "regulation of B cell receptor signaling pathway," "protein phosphorylation," "epidermal growth factor receptor signaling pathway," and "positive regulation of neurogenesis." Moreover, 16 KEGG pathways mostly associated with the immune system and viral infections were enriched. In the constructed physical interaction networks, UBA52 and TP53 were shown to be the most highly ranked hub genes among upregulated and downregulated genes, respectively. By applying global transcriptome profiling of CD4⁺ T cells, we deciphered the involvement of several novel genes and pathways in MS pathogenesis. The present results must be confirmed by in vivo and in vitro studies.

A Transcriptomic Pipeline Adapted for Genomic Sequence Discovery of Germline-Restricted Sequence in Zebra Finch, Taeniopygia guttata

Songbirds have an unusual genomic element which is only found in their germline cells, known as the germline-restricted chromosome (GRC). Because germ cells contain both GRC and non-GRC (or A-chromosome) sequences, confidently identifying the GRC-derived elements from genome assemblies has proven difficult. Here, we introduce a new application of a transcriptomic method for GRC sequence identification. By adapting the Stringtie/Ballgown pipeline to use somatic and germline DNA reads, we find that the ratio of fragments per kilobase per million mapped reads can be used to confidently assign contigs to the GRC. Using this comparative coverage analysis, we successfully identify 733 contigs as high confidence GRC sequences (720 newly identified in this study) and 51 contigs which were validated using quantitative polymerase chain reaction. We also identified two new GRC genes, one hypothetical protein and one gene encoding an RNase H-like domain, and placed 16 previously identified but unplaced genes onto their host contigs. With the current focus on sequencing GRCs from different songbirds, our work adds to the genomic toolkit to identify GRC elements, and we provide a detailed protocol and GitHub repository at https://github.com/brachtlab/Comparative_Coverage_Analysis (last accessed May 12, 2021).

Reprogramming of translation in yeast cells impaired for ribosome recycling favors short, efficiently translated mRNAs

In eukaryotes, 43S preinitiation complex (PIC) formation is a rate-determining step of translation. Ribosome recycling following translation termination produces free 40S subunits for re-assembly of 43S PICs. Yeast mutants lacking orthologs of mammalian eIF2D (Tma64), and either MCT-1 (Tma20) or DENR (Tma22), are broadly impaired for 40S recycling; however, it was unknown whether this defect alters the translational efficiencies (TEs) of particular mRNAs. Here, we conducted ribosome profiling of a yeast tma64∆/tma20∆ double mutant and observed a marked reprogramming of translation, wherein the TEs of the most efficiently translated ('strong') mRNAs increase, while those of 'weak' mRNAs generally decline. Remarkably, similar reprogramming was seen on reducing 43S PIC assembly by inducing phosphorylation of eIF2α or by decreasing total 40S subunit levels by depleting Rps26. Our findings suggest that strong mRNAs outcompete weak mRNAs in response to 43S PIC limitation achieved in various ways, in accordance with previous mathematical modeling.

High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

BACKGROUND

RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible.

RESULTS

Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis.

CONCLUSIONS

High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat

Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future.

Comparative analysis and antimicrobial action of some essential oils from plants

In this research, essential oils (EOs) were extracted through steaming from aerial parts of three plants: basil (Ocinum basilicum L.), peppermint (Mentha piperita L.) and oregano (Origanum vulgare L.) form Sibiu County, Romania. The GC-MS analysis indicated that eugenol and apiol were the major compounds in the basil EO. Timol, ɣ-terpinene, and p-cymene were the major compounds in the volatile oil extracted from oregano and menthol and methone the main components in the peppermint EO. In the first 48 h of analysis, basil EO inhibition action was the highest against Salmonella anatum (48%), followed by Aspergillus niger (26%), Bacillus cereus (21%) and Saccharomyces cerevisiae (15%); this action was maintained for 120 h for all samples. In the first 48 h, the peppermint EO showed the highest inhibition rate (50%) on B. cereus, followed by A. niger (45%), S. cerevisiae (20%) and no action against Salmonella; this action varied after 72h and 120 h by slightly increasing in case of B. cereus, strongly decreasing in case of A. niger and remaining constant in case of S. cerevisiae. Oregano EO showed a very small antimicrobial action, only on S. anatum (12%) and this action was maintained for 120 h.

In search of preventive strategies: novel high-CBD Cannabis sativa extracts modulate ACE2 expression in COVID-19 gateway tissues

With the current COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for new therapies and prevention strategies that can help curtail disease spread and reduce mortality. The inhibition of viral entry and thus spread is a plausible therapeutic avenue. SARS-CoV-2 uses receptor-mediated entry into a human host via the angiotensin-converting enzyme 2 (ACE2), which is expressed in lung tissue as well as the oral and nasal mucosa, kidney, testes and gastrointestinal tract. The modulation of ACE2 levels in these gateway tissues may be an effective strategy for decreasing disease susceptibility. Cannabis sativa, especially those high in the anti-inflammatory cannabinoid cannabidiol (CBD), has been found to alter gene expression and inflammation and harbour anti-cancer and anti-inflammatory properties. However, its effects on ACE2 expression remain unknown. Working under a Health Canada research license, we developed over 800 new C. sativa cultivars and hypothesized that high-CBD C. sativa extracts may be used to down-regulate ACE2 expression in target COVID-19 tissues. Using artificial 3D human models of oral, airway and intestinal tissues, we identified 13 high-CBD C. sativa extracts that decrease ACE2 protein levels. Some C. sativa extracts down-regulate serine protease TMPRSS2, another critical protein required for SARS-CoV-2 entry into host cells. While our most effective extracts require further large-scale validation, our study is important for future analyses of the effects of medical cannabis on COVID-19. The extracts of our most successful novel high-CBD C. sativa lines, pending further investigation, may become a useful and safe addition to the prevention/treatment of COVID-19 as an adjunct therapy.

dearseq: a variance component score test for RNA-seq differential analysis that effectively controls the false discovery rate

RNA-seq studies are growing in size and popularity. We provide evidence that the most commonly used methods for differential expression analysis (DEA) may yield too many false positive results in some situations. We present dearseq, a new method for DEA that controls the false discovery rate (FDR) without making any assumption about the true distribution of RNA-seq data. We show that dearseq controls the FDR while maintaining strong statistical power compared to the most popular methods. We demonstrate this behavior with mathematical proofs, simulations and a real data set from a study of tuberculosis, where our method produces fewer apparent false positives.

Effect of ladostigil treatment of aging rats on gene expression in four brain areas associated with regulation of memory

Episodic and spatial memory decline in aging and are controlled by the hippocampus, perirhinal, frontal and parietal cortices and the connections between them. Ladostigil, a drug with antioxidant and anti-inflammatory activity, was shown to prevent the loss of episodic and spatial memory in aging rats. To better understand the molecular effects of aging and ladostigil on these brain regions we characterized the changes in gene expression using RNA-sequencing technology in rats aged 6 and 22 months. We found that the changes induced by aging and chronic ladostigil treatment were brain region specific. In the hippocampus, frontal and perirhinal cortex, ladostigil decreased the overexpression of genes regulating calcium homeostasis, ion channels and those adversely affecting synaptic function. In the parietal cortex, ladostigil increased the expression of several genes that provide neurotrophic support, while reducing that of pro-apoptotic genes and those encoding pro-inflammatory cytokines and their receptors. Ladostigil also decreased the expression of axonal growth inhibitors and those impairing mitochondrial function. Together, these actions could explain the protection by ladostigil against age-related memory decline.

SlGID1a Is a Putative Candidate Gene for qtph1.1, a Major-Effect Quantitative Trait Locus Controlling Tomato Plant Height

Plant height is an important agronomic trait in crops. Several genes underlying tomato (Solanum lycopersicum) plant height mutants have been cloned. However, few quantitative trait genes for plant height have been identified in tomato. In this study, seven quantitative trait loci (QTLs) controlling plant height were identified in tomato. Of which, qtph1.1 (QTL for tomato plant height 1.1), qtph3.1 and qtph12.1 were major QTLs and explained 15, 16, and 12% of phenotypic variation (R²), respectively. The qtph1.1 was further mapped to an 18.9-kb interval on chromosome 1. Based on the annotated tomato genome (version SL2.50, annotation ITAG2.40), Solyc01g098390 encoding GA receptor SlGID1a was the putative candidate gene. The SlGID1a gene underlying the qtph1.1 locus contained a single nucleotide polymorphism (SNP) that resulted in an amino acid alteration in protein sequence. The near-isogenic line containing the qtph1.1 locus (NIL-qtph1.1) exhibited shorter internode length and cell length than the wild type (NIL-WT). The dwarf phenotype of NIL-qtph1.1 could not be rescued by exogenous GA₃ treatment. Transcriptome analysis and real-time quantitative reverse transcription PCR (qPCR) showed that several genes related to biosynthesis and signaling of GA and auxin were differentially expressed in stems between NIL-qtph1.1 and NIL-WT. These findings might pave the road for understanding the molecular regulation mechanism of tomato plant height.

The transcription factor scleraxis differentially regulates gene expression in tenocytes isolated at different developmental stages

The transcription factor scleraxis (SCX) is expressed throughout tendon development and plays a key role in directing tendon wound healing. However, little is known regarding its role in fetal or young postnatal tendons, stages in development that are known for their enhanced regenerative capabilities. Here we used RNA-sequencing to compare the transcriptome of adult and fetal tenocytes following SCX knockdown. SCX knockdown had a larger effect on gene expression in fetal tenocytes, affecting 477 genes in comparison to the 183 genes affected in adult tenocytes, indicating that scleraxis-dependent processes may differ in these two developmental stages. Gene ontology, network and pathway analysis revealed an overrepresentation of extracellular matrix (ECM) remodelling processes within both comparisons. These included several matrix metalloproteinases, proteoglycans and collagens, some of which were also investigated in SCX knockdown tenocytes from young postnatal foals. Using chromatin immunoprecipitation, we also identified novel genes that SCX differentially interacts with in adult and fetal tenocytes. These results indicate a role for SCX in modulating ECM synthesis and breakdown and provide a useful dataset for further study into SCX gene regulation.

Reference genome and transcriptome informed by the sex chromosome complement of the sample increase ability to detect sex differences in gene expression from RNA-Seq data

BACKGROUND

Human X and Y chromosomes share an evolutionary origin and, as a consequence, sequence similarity. We investigated whether the sequence homology between the X and Y chromosomes affects the alignment of RNA-Seq reads and estimates of differential expression. We tested the effects of using reference genomes and reference transcriptomes informed by the sex chromosome complement of the sample's genome on the measurements of RNA-Seq abundance and sex differences in expression.

RESULTS

The default genome includes the entire human reference genome (GRCh38), including the entire sequence of the X and Y chromosomes. We created two sex chromosome complement informed reference genomes. One sex chromosome complement informed reference genome was used for samples that lacked a Y chromosome; for this reference genome version, we hard-masked the entire Y chromosome. For the other sex chromosome complement informed reference genome, to be used for samples with a Y chromosome, we hard-masked only the pseudoautosomal regions of the Y chromosome, because these regions are duplicated identically in the reference genome on the X chromosome. We analyzed the transcript abundance in the whole blood, brain cortex, breast, liver, and thyroid tissues from 20 genetic female (46, XX) and 20 genetic male (46, XY) samples. Each sample was aligned twice: once to the default reference genome and then independently aligned to a reference genome informed by the sex chromosome complement of the sample, repeated using two different read aligners, HISAT and STAR. We then quantified sex differences in gene expression using featureCounts to get the raw count estimates followed by Limma/Voom for normalization and differential expression. We additionally created sex chromosome complement informed transcriptome references for use in pseudo-alignment using Salmon. Transcript abundance was quantified twice for each sample: once to the default target transcripts and then independently to target transcripts informed by the sex chromosome complement of the sample.

CONCLUSIONS

We show that regardless of the choice of the read aligner, using an alignment protocol informed by the sex chromosome complement of the sample results in higher expression estimates on the pseudoautosomal regions of the X chromosome in both genetic male and genetic female samples, as well as an increased number of unique genes being called as differentially expressed between the sexes. We additionally show that using a pseudo-alignment approach informed on the sex chromosome complement of the sample eliminates Y-linked expression in female XX samples.

Slower development of lower canopy beans produces better coffee

The production of high-quality coffee is being challenged by changing climates in coffee-growing regions. The coffee beans from the upper and lower canopy at different development stages of the same plants were analyzed to investigate the impact of the microenvironment on gene expression and coffee quality. Compared with coffee beans from the upper canopy, lower canopy beans displayed more intense aroma with higher caffeine, trigonelline, and sucrose contents, associated with greater gene expression in the representative metabolic pathways. Global gene expression indicated a longer ripening in the lower canopy, resulting from higher expression of genes relating to growth inhibition and suppression of chlorophyll degradation during early bean ripening. Selection of genotypes or environments that enhance expression of the genes slowing bean development may produce higher quality coffee beans, allowing coffee production in a broader range of available future environments.

eIF1 discriminates against suboptimal initiation sites to prevent excessive uORF translation genome-wide

The translation preinitiation complex (PIC) scans the mRNA for an AUG codon in a favorable context. Previous findings suggest that the factor eIF1 discriminates against non-AUG start codons by impeding full accommodation of Met-tRNA_i in the P site of the 40S ribosomal subunit, necessitating eIF1 dissociation for start codon selection. Consistent with this, yeast eIF1 substitutions that weaken its binding to the PIC increase initiation at UUG codons on a mutant his4 mRNA and particular synthetic mRNA reporters; and also at the AUG start codon of the mRNA for eIF1 itself owing to its poor Kozak context. It was not known however whether such eIF1 mutants increase initiation at suboptimal start codons genome-wide. By ribosome profiling, we show that the eIF1-L96P variant confers increased translation of numerous upstream open reading frames (uORFs) initiating with either near-cognate codons (NCCs) or AUGs in poor context. The increased uORF translation is frequently associated with the reduced translation of the downstream main coding sequences (CDS). Initiation is also elevated at certain NCCs initiating amino-terminal extensions, including those that direct mitochondrial localization of the GRS1 and ALA1 products, and at a small set of main CDS AUG codons with especially poor context, including that of eIF1 itself. Thus, eIF1 acts throughout the yeast translatome to discriminate against NCC start codons and AUGs in poor context; and impairing this function enhances the repressive effects of uORFs on CDS translation and alters the ratios of protein isoforms translated from near-cognate versus AUG start codons.

Minority Gene Expression Profiling: Probing the Genetic Signatures of Pathogenesis Using Ribosome Profiling

Minority Gene Expression Profiling (MGEP) refers to a scenario where the expression profiles of specific genes of interest are concentrated in a small cellular pool that is embedded within a larger, non-expressive pool. An example of this is the analysis of disease-related genes within sub-populations of blood or biopsied tissues. These systems are characterized by low signal-to-noise ratios that make it difficult, if not impossible, to uncover the desired signatures of pathogenesis in the absence of lengthy, and often problematic, technical manipulations. We have adapted ribosome profiling (RP) workflows from the Illumina to the Ion Proton platform and used them to analyze signatures of pathogenesis in an MGEP model system consisting of human cells eliciting <3% productive dengue infection. We find that RP is powerful enough to identify relevant responses of differentially expressed genes, even in the presence of significant noise. We discuss how to deal with sources of unwanted variation, and propose ways to further improve this powerful approach to the study of pathogenic signatures within MGEP systems.

Differential Expression Analysis of RNA-seq Reads: Overview, Taxonomy, and Tools

Analysis of RNA-sequence (RNA-seq) data is widely used in transcriptomic studies and it has many applications. We review RNA-seq data analysis from RNA-seq reads to the results of differential expression analysis. In addition, we perform a descriptive comparison of tools used in each step of RNA-seq data analysis along with a discussion of important characteristics of these tools. A taxonomy of tools is also provided. A discussion of issues in quality control and visualization of RNA-seq data is also included along with useful tools. Finally, we provide some guidelines for the RNA-seq data analyst, along with research issues and challenges which should be addressed.

An endophyte from salt-adapted Pokkali rice confers salt-tolerance to a salt-sensitive rice variety and targets a unique pattern of genes in its new host

Endophytes, both of bacterial and fungal origin, are ubiquitously present in all plants. While their origin and evolution are enigmatic, there is burgeoning literature on their role in promoting growth and stress responses in their hosts. We demonstrate that a salt-tolerant endophyte isolated from salt-adapted Pokkali rice, a Fusarium sp., colonizes the salt-sensitive rice variety IR-64, promotes its growth under salt stress and confers salinity stress tolerance to its host. Physiological parameters, such as assimilation rate and chlorophyll stability index were higher in the colonized plants. Comparative transcriptome analysis revealed 1348 up-regulated and 1078 down-regulated genes in plants colonized by the endophyte. Analysis of the regulated genes by MapMan and interaction network programs showed that they are involved in both abiotic and biotic stress tolerance, and code for proteins involved in signal perception (leucine-rich repeat proteins, receptor-like kinases) and transduction (Ca2+ and calmodulin-binding proteins), transcription factors, secondary metabolism and oxidative stress scavenging. For nine genes, the data were validated by qPCR analysis in both roots and shoots. Taken together, these results show that salt-adapted Pokkali rice varieties are powerful sources for the identification of novel endophytes, which can be used to confer salinity tolerance to agriculturally important, but salt-sensitive rice varieties.

A Dynamic Transcriptional Analysis Reveals IL-6 Axis as a Prominent Mediator of Surgical Acute Response in Non-ischemic Mouse Heart

Background

Ischemic heart diseases are a major cause of death worldwide. Different animal models, including cardiac surgery, have been developed over time. Unfortunately, the surgery models have been reported to trigger an important inflammatory response that might be an effect modifier, where involved molecular processes have not been fully elucidated yet.

Objective

We sought to perform a thorough characterization of the sham effect in the myocardium and identify the interfering inflammatory reaction in order to avoid misinterpretation of the data via systems biology approaches.

Methods and Results

We combined a comprehensive analytical pipeline of mRNAseq dataset and systems biology analysis to characterize the acute phase response of mouse myocardium at 0 min, 45 min, and 24 h after surgery to better characterize the molecular processes inadvertently induced in sham animals. Our analysis showed that the surgical intervention induced 1209 differentially expressed transcripts (DETs). The clustering of positively co-regulated transcript modules at 45 min fingerprinted the activation of signalization pathways, while positively co-regulated genes at 24 h identified the recruitment of neutrophils and the differentiation of macrophages. In addition, we combined the prediction of transcription factors (TF) regulating DETs with protein-protein interaction networks built from these TFs to predict the molecular network which have induced the DETs. By mean of this retro-analysis of processes upstream gene transcription, we revealed a major role of the Il-6 pathway and further confirmed a significant increase in circulating IL-6 at 45 min after surgery.

Conclusion

This study suggests that a strong induction of the IL-6 axis occurs in sham animals over the first 24 h and leads to the induction of inflammation and tissues’ homeostasis processes.

Gene Cascade Finder: A tool for identification of gene cascades and its application in Caenorhabditis elegans

Obtaining a comprehensive understanding of the gene regulatory networks, or gene cascades, involved in cell fate determination and cell lineage segregation in Caenorhabditis elegans is a long-standing challenge. Although RNA-sequencing (RNA-Seq) is a promising technique to resolve these questions, the bioinformatics tools to identify associated gene cascades from RNA-Seq data remain inadequate. To overcome these limitations, we developed Gene Cascade Finder (GCF) as a novel tool for building gene cascades by comparison of mutant and wild-type RNA-Seq data along with integrated information of protein-protein interactions, expression timing, and domains. Application of GCF to RNA-Seq data confirmed that SPN-4 and MEX-3 regulate the canonical Wnt pathway during embryonic development. Moreover, lin-35, hsp-3, and gpa-12 were found to be involved in MEX-1-dependent neurogenesis, and MEX-3 was found to control the gene cascade promoting neurogenesis through lin-35 and apl-1. Thus, GCF could be a useful tool for building gene cascades from RNA-Seq data.

Accurate Classification of Differential Expression Patterns in a Bayesian Framework With Robust Normalization for Multi-Group RNA-Seq Count Data

Empirical Bayes is a choice framework for differential expression (DE) analysis for multi-group RNA-seq count data. Its characteristic ability to compute posterior probabilities for predefined expression patterns allows users to assign the pattern with the highest value to the gene under consideration. However, current Bayesian methods such as baySeq and EBSeq can be improved, especially with respect to normalization. Two R packages (baySeq and EBSeq) with their default normalization settings and with other normalization methods (MRN and TCC) were compared using three-group simulation data and real count data. Our findings were as follows: (1) the Bayesian methods coupled with TCC normalization performed comparably or better than those with the default normalization settings under various simulation scenarios, (2) default DE pipelines provided in TCC that implements a generalized linear model framework was still superior to the Bayesian methods with TCC normalization when overall degree of DE was evaluated, and (3) baySeq with TCC was robust against different choices of possible expression patterns. In practice, we recommend using the default DE pipeline provided in TCC for obtaining overall gene ranking and then using the baySeq with TCC normalization for assigning the most plausible expression patterns to individual genes.

Stability of methods for differential expression analysis of RNA-seq data

Background

As RNA-seq becomes the assay of choice for measuring gene expression levels, differential expression analysis has received extensive attentions of researchers. To date, for the evaluation of DE methods, most attention has been paid on validity. Yet another important aspect of DE methods, stability, is overlooked and has not been studied to the best of our knowledge.

Results

In this study, we empirically show the need of assessing stability of DE methods and propose a stability metric, called Area Under the Correlation curve (AUCOR), that generates the perturbed datasets by a mixture distribution and combines the information of similarities between sets of selected features from these perturbed datasets and the original dataset.

Conclusion

Empirical results support that AUCOR can effectively rank the DE methods in terms of stability for given RNA-seq datasets. In addition, we explore how biological or technical factors from experiments and data analysis affect the stability of DE methods. AUCOR is implemented in the open-source R package AUCOR, with source code freely available at https://github.com/linbingqing/stableDE.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5390-6) contains supplementary material, which is available to authorized users.

Characterization and expression profiling of microRNAs in response to plant feeding in two host-plant strains of the lepidopteran pest Spodoptera frugiperda

Background

A change in the environment may impair development or survival of living organisms leading them to adapt to the change. The resulting adaptation trait may reverse, or become fixed in the population leading to evolution of species. Deciphering the molecular basis of adaptive traits can thus give evolutionary clues. In phytophagous insects, a change in host-plant range can lead to emergence of new species. Among them, Spodoptera frugiperda is a major agricultural lepidopteran pest consisting of two host-plant strains having diverged 3 MA, based on mitochondrial markers. In this paper, we address the role of microRNAs, important gene expression regulators, in response to host-plant change and in adaptive evolution.

Results

Using small RNA sequencing, we characterized miRNA repertoires of the corn (C) and rice (R) strains of S. frugiperda, expressed during larval development on two different host-plants, corn and rice, in the frame of reciprocal transplant experiments. We provide evidence for 76 and 68 known miRNAs in C and R strains and 139 and 171 novel miRNAs. Based on read counts analysis, 34 of the microRNAs were differentially expressed in the C strain larvae fed on rice as compared to the C strain larvae fed on corn. Twenty one were differentially expressed on rice compared to corn in R strain. Nine were differentially expressed in the R strain compared to C strain when reared on corn. A similar ratio of microRNAs was differentially expressed between strains on rice. We could validate experimentally by QPCR, variation in expression of the most differentially expressed candidates. We used bioinformatics methods to determine the target mRNAs of known microRNAs. Comparison with the mRNA expression profile during similar reciprocal transplant experiment revealed potential mRNA targets of these host-plant regulated miRNAs.

Conclusions

In the current study, we performed the first systematic analysis of miRNAs in Lepidopteran pests feeding on host-plants. We identified a set of the differentially expressed miRNAs that respond to the plant diet, or differ constitutively between the two host plant strains. Among the latter, the ones that are also deregulated in response to host-plant are molecular candidates underlying a complex adaptive trait.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5119-6) contains supplementary material, which is available to authorized users.

Functional Genomics

Functional genomics encompasses diverse disciplines in molecular biology and bioinformatics to comprehend the blueprint, regulation, and expression of genetic elements that define the physiology of an organism. The deluge of sequencing data in the postgenomics era has demanded the involvement of computer scientists and mathematicians to create algorithms, analytical software, and databases for the storage, curation, and analysis of biological big data. In this chapter, we discuss on the concept of functional genomics in the context of systems biology and provide examples of its application in human genetic disease studies, molecular crop improvement, and metagenomics for antibiotic discovery. An overview of transcriptomics workflow and experimental considerations is also introduced. Lastly, we present an in-house case study of transcriptomics analysis of an aromatic herbal plant to understand the effect of elicitation on the biosynthesis of volatile organic compounds.