Differential Type-I Interferon Response in Buffy Coat Transcriptome of Individuals Infected with SARS-CoV-2 Gamma and Delta Variants.

The innate immune system is the first line of defense against pathogens such as the acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The type I-interferon (IFN) response activation during the initial steps of infection is essential to prevent viral replication and tissue damage. SARS-CoV and SARS-CoV-2 can inhibit this activation, and individuals with a dysregulated IFN-I response are more likely to develop severe disease. Several mutations in different variants of SARS-CoV-2 have shown the potential to interfere with the immune system. Here, we evaluated the buffy coat transcriptome of individuals infected with Gamma or Delta variants of SARS-CoV-2. The Delta transcriptome presents more genes enriched in the innate immune response and Gamma in the adaptive immune response. Interactome and enriched promoter analysis showed that Delta could activate the INF-I response more effectively than Gamma. Two mutations in the N protein and one in the nsp6 protein found exclusively in Gamma have already been described as inhibitors of the interferon response pathway. This indicates that the Gamma variant evolved to evade the IFN-I response. Accordingly, in this work, we showed one of the mechanisms that variants of SARS-CoV-2 can use to avoid or interfere with the host Immune system.

Genomic characterization of a novel SARS-CoV-2 lineage from Rio de Janeiro, Brazil.

Almost simultaneously, several studies reported the emergence of novel SARS-CoV-2 lineages characterized by their phylogenetic and genetic distinction (1), (2), (3), (4).….

Buffy Coat Transcriptomic Analysis Reveals Alterations in Host Cell Protein Synthesis and Cell Cycle in Severe COVID-19 Patients.

Transcriptome studies have reported the dysregulation of cell cycle-related genes and the global inhibition of host mRNA translation in COVID-19 cases. However, the key genes and cellular mechanisms that are most affected by the severe outcome of this disease remain unclear. For this work, the RNA-seq approach was used to study the differential expression in buffy coat cells of two groups of people infected with SARS-CoV-2: (a) Mild, with mild symptoms; and (b) SARS (Severe Acute Respiratory Syndrome), who were admitted to the intensive care unit with the severe COVID-19 outcome. Transcriptomic analysis revealed 1009 up-regulated and 501 down-regulated genes in the SARS group, with 10% of both being composed of long non-coding RNA. Ribosome and cell cycle pathways were enriched among down-regulated genes. The most connected proteins among the differentially expressed genes involved transport dysregulation, proteasome degradation, interferon response, cytokinesis failure, and host translation inhibition. Furthermore, interactome analysis showed Fibrillarin to be one of the key genes affected by SARS-CoV-2. This protein interacts directly with the N protein and long non-coding RNAs affecting transcription, translation, and ribosomal processes. This work reveals a group of dysregulated processes, including translation and cell cycle, as key pathways altered in severe COVID-19 outcomes.

NIK1-mediated translation suppression functions as a plant antiviral immunity mechanism.

Plants and plant pathogens are subject to continuous co-evolutionary pressure for dominance, and the outcomes of these interactions can substantially impact agriculture and food security. In virus-plant interactions, one of the major mechanisms for plant antiviral immunity relies on RNA silencing, which is often suppressed by co-evolving virus suppressors, thus enhancing viral pathogenicity in susceptible hosts. In addition, plants use the nucleotide-binding and leucine-rich repeat (NB-LRR) domain-containing resistance proteins, which recognize viral effectors to activate effector-triggered immunity in a defence mechanism similar to that employed in non-viral infections. Unlike most eukaryotic organisms, plants are not known to activate mechanisms of host global translation suppression to fight viruses. Here we demonstrate in Arabidopsis that the constitutive activation of NIK1, a leucine-rich repeat receptor-like kinase (LRR-RLK) identified as a virulence target of the begomovirus nuclear shuttle protein (NSP), leads to global translation suppression and translocation of the downstream component RPL10 to the nucleus, where it interacts with a newly identified MYB-like protein, L10-INTERACTING MYB DOMAIN-CONTAINING PROTEIN (LIMYB), to downregulate translational machinery genes fully. LIMYB overexpression represses ribosomal protein genes at the transcriptional level, resulting in protein synthesis inhibition, decreased viral messenger RNA association with polysome fractions and enhanced tolerance to begomovirus. By contrast, the loss of LIMYB function releases the repression of translation-related genes and increases susceptibility to virus infection. Therefore, LIMYB links immune receptor LRR-RLK activation to global translation suppression as an antiviral immunity strategy in plants.

Geminivirus data warehouse: a database enriched with machine learning approaches.

BACKGROUND: The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases. As a consequence, many important challenges have emerged, namely, how to classify, store, and analyze massive datasets as well as how to extract information or new knowledge. Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics. RESULTS: Here, we describe the development of a data warehouse enriched with ML approaches, designated geminivirus.org. We implemented search modules, bioinformatics tools, and ML methods to retrieve high precision information, demarcate species, and create classifiers for genera and open reading frames (ORFs) of geminivirus genomes. CONCLUSIONS: The use of data mining techniques such as ETL (Extract, Transform, Load) to feed our database, as well as algorithms based on machine learning for knowledge extraction, allowed us to obtain a database with quality data and suitable tools for bioinformatics analysis. The Geminivirus Data Warehouse (geminivirus.org) offers a simple and user-friendly environment for information retrieval and knowledge discovery related to geminiviruses.

NIK1, a host factor specialized in antiviral defense or a novel general regulator of plant immunity?

NIK1 is a receptor-like kinase involved in plant antiviral immunity. Although NIK1 is structurally similar to the plant immune factor BAK1, which is a key regulator in plant immunity to bacterial pathogens, the NIK1-mediated defenses do not resemble BAK1 signaling cascades. The underlying mechanism for NIK1 antiviral immunity has recently been uncovered. NIK1 activation mediates the translocation of RPL10 to the nucleus, where it interacts with LIMYB to fully down-regulate translational machinery genes, resulting in translation inhibition of host and viral mRNAs and enhanced tolerance to begomovirus. Therefore, the NIK1 antiviral immunity response culminates in global translation suppression, which represents a new paradigm for plant antiviral defenses. Interestingly, transcriptomic analyses in nik1 mutant suggest that NIK1 may suppress antibacterial immune responses, indicating a possible opposite effect of NIK1 in bacterial and viral infections.

The Stress-Induced Soybean NAC Transcription Factor GmNAC81 Plays a Positive Role in Developmentally Programmed Leaf Senescence.

The onset of leaf senescence is a highly regulated developmental change that is controlled by both genetics and the environment. Senescence is triggered by massive transcriptional reprogramming, but functional information about its underlying regulatory mechanisms is limited. In the current investigation, we performed a functional analysis of the soybean (Glycine max) osmotic stress- and endoplasmic reticulum (ER) stress-induced NAC transcription factor GmNAC81 during natural leaf senescence using overexpression studies and reverse genetics. GmNAC81-overexpressing lines displayed accelerated flowering and leaf senescence but otherwise developed normally. The precocious leaf senescence of GmNAC81-overexpressing lines was associated with greater Chl loss, faster photosynthetic decay and higher expression of hydrolytic enzyme-encoding GmNAC81 target genes, including the vacuolar processing enzyme (VPE), an executioner of vacuole-triggered programmed cell death (PCD). Conversely, virus-induced gene silencing-mediated silencing of GmNAC81 delayed leaf senescence and was associated with reductions in Chl loss, lipid peroxidation and the expression of GmNAC81 direct targets. Promoter-reporter studies revealed that the expression pattern of GmNAC81 was associated with senescence in soybean leaves. Our data indicate that GmNAC81 is a positive regulator of age-dependent senescence and may integrate osmotic stress- and ER stress-induced PCD responses with natural leaf senescence through the GmNAC81/VPE regulatory circuit.

Expression of myogenes in longissimus dorsi muscle during prenatal development in commercial and local Piau pigs.

This study used qRT-PCR to examine variation in the expression of 13 myogenes during muscle development in four prenatal periods (21, 40, 70 and 90 days post-insemination) in commercial (the three-way Duroc, Landrace and Large-White cross) and local Piau pig breeds that differ in muscle mass. There was no variation in the expression of the CHD8, EID2B, HIF1AN, IKBKB, RSPO3, SOX7 and SUFU genes at the various prenatal ages or between breeds. The MAP2K1 and RBM24 genes showed similar expression between commercial and Piau pigs but greater expression (p < 0.05) in at least one prenatal period. Pair-wise comparisons of prenatal periods in each breed showed that only the CSRP3, LEF1, MRAS and MYOG genes had higher expression (p < 0.05) in at least one prenatal period in commercial and Piau pigs. Overall, these results identified the LEF1 gene as a primary candidate to account for differences in muscle mass between the pig breeds since activation of this gene may lead to greater myoblast fusion in the commercial breed compared to Piau pigs. Such fusion could explain the different muscularity between breeds in the postnatal periods.

Comprehensive analysis of the endoplasmic reticulum stress response in the soybean genome: conserved and plant-specific features.

BACKGROUND: Despite the relevance of the eukaryotic endoplasmic reticulum (ER)-stress response as an integrator of multiple stress signals into an adaptive response, knowledge about these ER-mediated cytoprotective pathways in soybean (Glycine max) is lacking. Here, we searched for genes involved in the highly conserved unfolded protein response (UPR) and ER stress-induced plant-specific cell death signaling pathways in the soybean genome. METHODS: Previously characterized Arabidopsis UPR genes were used as prototypes for the identification of the soybean orthologs and the in silico assembly of the UPR in soybean, using eggNOG v4.0 software. Functional studies were also conducted by analyzing the transcriptional activity of soybean UPR transducers. RESULTS: As a result of this search, we have provided a complete profile of soybean UPR genes with significant predicted protein similarities to A. thaliana UPR-associated proteins. Both arms of the plant UPR were further examined functionally, and evidence is presented that the soybean counterparts are true orthologs of previously characterized UPR transducers in Arabidopsis. The bZIP17/bZI28 orthologs (GmbZIP37 and GmbZIP38) and ZIP60 ortholog (GmbZIP68) from soybean have similar structural organizations as their Arabidopsis counterparts, were induced by ER stress and activated an ERSE- and UPRE-containing BiP promoter. Furthermore, the transcript of the putative substrate of GmIREs, GmbZIP68, harbors a canonical site for IRE1 endonuclease activity and was efficiently spliced under ER stress conditions. In a reverse approach, we also examined the Arabidopsis genome for components of a previously characterized ER stress-induced cell death signaling response in soybean. With the exception of GmERD15, which apparently does not possess an Arabidopsis ortholog, the Arabidopsis genome harbors conserved GmNRP, GmNAC81, GmNAC30 and GmVPE sequences that share significant structural and sequence similarities with their soybean counterparts. These results suggest that the NRP/GmNAC81 + GmNAC30/VPE regulatory circuit may transduce cell death signals in plant species other than soybean. CONCLUSIONS: Our in silico analyses, along with current and previous functional data, permitted generation of a comprehensive overview of the ER stress response in soybean as a framework for functional prediction of ER stress signaling components and their possible connections with multiple stress responses.

Sustained NIK-mediated antiviral signalling confers broad-spectrum tolerance to begomoviruses in cultivated plants.

Begomovirus-associated epidemics currently threaten tomato production worldwide due to the emergence of highly pathogenic virus species and the proliferation of a whitefly B biotype vector that is adapted to tomato. To generate an efficient defence against begomovirus, we modulated the activity of the immune defence receptor nuclear shuttle protein (NSP)-interacting kinase (NIK) in tomato plants; NIK is a virulence target of the begomovirus NSP during infection. Mutation of T474 within the kinase activation loop promoted the constitutive activation of NIK-mediated defences, resulting in the down-regulation of translation-related genes and the suppression of global translation. Consistent with these findings, transgenic lines harbouring an activating mutation (T474D) were tolerant to the tomato-infecting begomoviruses ToYSV and ToSRV. This phenotype was associated with reduced loading of coat protein viral mRNA in actively translating polysomes, lower infection efficiency and reduced accumulation of viral DNA in systemic leaves. Our results also add some relevant insights into the mechanism underlying the NIK-mediated defence. We observed that the mock-inoculated T474D-overexpressing lines showed a constitutively infected wild-type transcriptome, indicating that the activation of the NIK-mediated signalling pathway triggers a typical response to begomovirus infection. In addition, the gain-of-function mutant T474D could sustain an activated NIK-mediated antiviral response in the absence of the virus, further confirming that phosphorylation of Thr-474 is the crucial event that leads to the activation of the kinase.

The endoplasmic reticulum binding protein BiP displays dual function in modulating cell death events.

The binding protein (BiP) has been demonstrated to participate in innate immunity and attenuate endoplasmic reticulum- and osmotic stress-induced cell death. Here, we employed transgenic plants with manipulated levels of BiP to assess whether BiP also controlled developmental and hypersensitive programmed cell death (PCD). Under normal conditions, the BiP-induced transcriptome revealed a robust down-regulation of developmental PCD genes and an up-regulation of the genes involved in hypersensitive PCD triggered by nonhost-pathogen interactions. Accordingly, the BiP-overexpressing line displayed delayed leaf senescence under normal conditions and accelerated hypersensitive response triggered by Pseudomonas syringae pv tomato in soybean (Glycine max) and tobacco (Nicotiana tabacum), as monitored by measuring hallmarks of PCD in plants. The BiP-mediated delay of leaf senescence correlated with the attenuation of N-rich protein (NRP)-mediated cell death signaling and the inhibition of the senescence-associated activation of the unfolded protein response (UPR). By contrast, under biological activation of salicylic acid (SA) signaling and hypersensitive PCD, BiP overexpression further induced NRP-mediated cell death signaling and antagonistically inhibited the UPR. Thus, the SA-mediated induction of NRP cell death signaling occurs via a pathway distinct from UPR. Our data indicate that during the hypersensitive PCD, BiP positively regulates the NRP cell death signaling through a yet undefined mechanism that is activated by SA signaling and related to ER functioning. By contrast, BiP's negative regulation of leaf senescence may be linked to its capacity to attenuate the UPR activation and NRP cell death signaling. Therefore, BiP can function either as a negative or positive modulator of PCD events.

Predicting novel mosquito-associated viruses from metatranscriptomic dark matter.

The exponential growth of metatranscriptomic studies dedicated to arboviral surveillance in mosquitoes has yielded an unprecedented volume of unclassified sequences referred to as the virome dark matter. Mosquito-associated viruses are classified based on their host range into Mosquito-specific viruses (MSV) or Arboviruses. While MSV replication is restricted to mosquito cells, Arboviruses infect both mosquito vectors and vertebrate hosts. We developed the MosViR pipeline designed to identify complex genomic discriminatory patterns for predicting novel MSV or Arboviruses from viral contigs as short as 500 bp. The pipeline combines the predicted probability score from multiple predictive models, ensuring a robust classification with Area Under ROC (AUC) values exceeding 0.99 for test datasets. To assess the practical utility of MosViR in actual cases, we conducted a comprehensive analysis of 24 published mosquito metatranscriptomic datasets. By mining this metatranscriptomic dark matter, we identified 605 novel mosquito-associated viruses, with eight putative novel Arboviruses exhibiting high probability scores. Our findings highlight the limitations of current homology-based identification methods and emphasize the potentially transformative impact of the MosViR pipeline in advancing the classification of mosquito-associated viruses. MosViR offers a powerful and highly accurate tool for arboviral surveillance and for elucidating the complexities of the mosquito RNA virome.

Exploring the versatility of sesquiterpene biosynthesis in guava plants: a comparative genome-wide analysis of two cultivars.

Psidium guajava L., a fruit crop belonging to the Myrtaceae family, is highly valued for its nutritional and medicinal properties. The family exhibits a diverse chemical profile of essential oils and serves as a valuable resource due to its ecological interactions, adaptability, and dispersal capacity. The Myrtaceae family has been extensively studied for its terpenoids. Genetic studies have focused on foliar terpene yield in species from the Eucalypteae and Melaleucaceae tribes. To understand the evolutionary trends in guava breeding, this study predicted terpene synthase genes (TPS) from different cultivars. Through this analysis, 43 full-length TPS genes were identified, and approximately 77% of them exhibited relative expression in at least one of the five investigated plant tissues (root, leaf, bud, flower, and fruit) of two guava cultivars. We identified intra-species variation in the terpene profile and single nucleotide polymorphisms (SNPs) in twelve TPS genes, resulting in the clustering of 62 genotypes according to their essential oil chemotypes. The high concentration of sesquiterpenes is supported by the higher number of TPS-a genes and their expression. The expansion for TPS sub-families in P. guajava occurred after the expansion of other rosids species. Providing insight into the origin of structural diversification and expansion in each clade of the TPS gene family within Myrtaceae. This study can provide insights into the diversity of genes for specialized metabolites such as terpenes, and their regulation, which can lead to a diverse chemotype of essential oil in different tissues and genotypes. This suggests a mode of enzymatic evolution that could lead to high sesquiterpene production, act as a chemical defense and contribute to the adaptive capacity of this species to different habitats.

Effects of trimer repeats on Psidium guajava L. gene expression and prospection of functional microsatellite markers.

Most research on trinucleotide repeats (TRs) focuses on human diseases, with few on the impact of TR expansions on plant gene expression. This work investigates TRs' effect on global gene expression in Psidium guajava L., a plant species with widespread distribution and significant relevance in the food, pharmacology, and economics sectors. We analyzed TR-containing coding sequences in 1,107 transcripts from 2,256 genes across root, shoot, young leaf, old leaf, and flower bud tissues of the Brazilian guava cultivars Cortibel RM and Paluma. Structural analysis revealed TR sequences with small repeat numbers (5-9) starting with cytosine or guanine or containing these bases. Functional annotation indicated TR-containing genes' involvement in cellular structures and processes (especially cell membranes and signal recognition), stress response, and resistance. Gene expression analysis showed significant variation, with a subset of highly expressed genes in both cultivars. Differential expression highlighted numerous down-regulated genes in Cortibel RM tissues, but not in Paluma, suggesting interplay between tissues and cultivars. Among 72 differentially expressed genes with TRs, 24 form miRNAs, 13 encode transcription factors, and 11 are associated with transposable elements. In addition, a set of 20 SSR-annotated, transcribed, and differentially expressed genes with TRs was selected as phenotypic markers for Psidium guajava and, potentially for closely related species as well.

Immune response stability to the SARS-CoV-2 mRNA vaccine booster is influenced by differential splicing of HLA genes.

Many molecular mechanisms that lead to the host antibody response to COVID-19 vaccines remain largely unknown. In this study, we used serum antibody detection combined with whole blood RNA-based transcriptome analysis to investigate variability in vaccine response in healthy recipients of a booster (third) dose schedule of the mRNA BNT162b2 vaccine against COVID-19. The cohort was divided into two groups: (1) low-stable individuals, with antibody concentration anti-SARS-CoV IgG S1 below 0.4 percentile at 180 days after boosting vaccination; and (2) high-stable individuals, with antibody values greater than 0.6 percentile of the range in the same period (median 9525 [185-80,000] AU/mL). Differential gene expression, expressed single nucleotide variants and insertions/deletions, differential splicing events, and allelic imbalance were explored to broaden our understanding of the immune response sustenance. Our analysis revealed a differential expression of genes with immunological functions in individuals with low antibody titers, compared to those with higher antibody titers, underscoring the fundamental importance of the innate immune response for boosting immunity. Our findings also provide new insights into the determinants of the immune response variability to the SARS-CoV-2 mRNA vaccine booster, highlighting the significance of differential splicing regulatory mechanisms, mainly concerning HLA alleles, in delineating vaccine immunogenicity.

Soybean chlorotic spot virus, a novel begomovirus infecting soybean in Brazil.

A novel soybean-infecting begomovirus from Brazil was identified in Jaíba, in the state of Minas Gerais, and molecularly characterized. By using rolling-circle amplification-based cloning of viral DNAs, three DNA-A variants and a cognate DNA-B were isolated from infected samples. The DNA variants share more than 98 % sequence identity but have less than 89 % identity to other reported begomovirus, the limit for demarcation of new species. In a phylogenetic analysis, both DNA-A and DNA-B clustered with other Brazilian begomoviruses. Infectious cloned DNA-A and DNA-B components induced distinct symptoms in Solanaceae and Fabaceae species by biolistic inoculation. In soybean, the virus induced mild symptoms, i.e., chlorotic spots on the leaves, from which the name soybean chlorotic spot virus (SoCSV) was proposed. The most severe symptoms were displayed by common beans, which exhibited leaf distortion, blistering, interveinal chlorosis, mosaic and golden mosaic. The possibility that SoCSV may become a threat to bean production in Brazil is discussed.

Genomic growth curves of an outbred pig population.

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

(m, n)-mer-a simple statistical feature for sequence classification.

Summary: The (m, n)-mer is a simple alternative classification feature based on conditional probability distributions. In this application note, we compared k-mer and (m, n)-mer frequency features in 11 distinct datasets used for binary, multiclass and clustering classifications. Our findings show that the (m, n)-mer frequency features are related to the highest performance metrics and often statistically outperformed the k-mers. Here, the (m, n)-mer frequencies improved performance for classifying smaller sequence lengths (as short as 300 bp) and yielded higher metrics when using short values of k (ranging from 2 to 4). Therefore, we present the (m, n)-mers frequencies to the scientific community as a feature that seems to be quite effective in identifying complex discriminatory patterns and classifying polyphyletic sequence groups. Availability and implementation: The (m, n)-mer algorithm is released as an R package within the CRAN project (https://cran.r-project.org/web/packages/mnmer) and is also available at https://github.com/labinfo-lncc/mnmer. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Inference of differentially expressed genes using generalized linear mixed models in a pairwise fashion.

Background: Technological advances involving RNA-Seq and Bioinformatics allow quantifying the transcriptional levels of genes in cells, tissues, and cell lines, permitting the identification of Differentially Expressed Genes (DEGs). DESeq2 and edgeR are well-established computational tools used for this purpose and they are based upon generalized linear models (GLMs) that consider only fixed effects in modeling. However, the inclusion of random effects reduces the risk of missing potential DEGs that may be essential in the context of the biological phenomenon under investigation. The generalized linear mixed models (GLMM) can be used to include both effects. Methods: We present DEGRE (Differentially Expressed Genes with Random Effects), a user-friendly tool capable of inferring DEGs where fixed and random effects on individuals are considered in the experimental design of RNA-Seq research. DEGRE preprocesses the raw matrices before fitting GLMMs on the genes and the derived regression coefficients are analyzed using the Wald statistical test. DEGRE offers the Benjamini-Hochberg or Bonferroni techniques for P-value adjustment. Results: The datasets used for DEGRE assessment were simulated with known identification of DEGs. These have fixed effects, and the random effects were estimated and inserted to measure the impact of experimental designs with high biological variability. For DEGs' inference, preprocessing effectively prepares the data and retains overdispersed genes. The biological coefficient of variation is inferred from the counting matrices to assess variability before and after the preprocessing. The DEGRE is computationally validated through its performance by the simulation of counting matrices, which have biological variability related to fixed and random effects. DEGRE also provides improved assessment measures for detecting DEGs in cases with higher biological variability. We show that the preprocessing established here effectively removes technical variation from those matrices. This tool also detects new potential candidate DEGs in the transcriptome data of patients with bipolar disorder, presenting a promising tool to detect more relevant genes. Conclusions: DEGRE provides data preprocessing and applies GLMMs for DEGs' inference. The preprocessing allows efficient remotion of genes that could impact the inference. Also, the computational and biological validation of DEGRE has shown to be promising in identifying possible DEGs in experiments derived from complex experimental designs. This tool may help handle random effects on individuals in the inference of DEGs and presents a potential for discovering new interesting DEGs for further biological investigation.