High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational methods that can tackle the analysis and management of data. The data normalization is one of the most crucial steps of data processing and this process must be carefully considered as it has a profound effect on the results of the analysis. In this work, we focus on a comprehensive comparison of five normalization methods related to sequencing depth, widely used for transcriptome sequencing (RNA-seq) data, and their impact on the results of gene expression analysis. Based on this study, we suggest a universal workflow that can be applied for the selection of the optimal normalization procedure for any particular data set. The described workflow includes calculation of the bias and variance values for the control genes, sensitivity and specificity of the methods, and classification errors as well as generation of the diagnostic plots. Combining the above information facilitates the selection of the most appropriate normalization method for the studied data sets and determines which methods can be used interchangeably.

Summary: Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) are responsible for significant cassava yield losses in eastern sub‐Saharan Africa. To study the possible mechanisms of plant resistance to CBSVs, we inoculated CBSV‐susceptible and CBSV‐resistant cassava varieties with a mixed infection of CBSVs using top‐cleft grafting. Transcriptome profiling of the two cassava varieties was performed at the earliest time point of full infection (28 days after grafting) in the susceptible scions. The expression of genes encoding proteins in RNA silencing, salicylic acid pathways and callose deposition was altered in the susceptible cassava variety, but transcriptional changes were limited in the resistant variety. In total, the expression of 585 genes was altered in the resistant variety and 1292 in the susceptible variety. Transcriptional changes led to the activation of β‐1,3‐glucanase enzymatic activity and a reduction in callose deposition in the susceptible cassava variety. Time course analysis also showed that CBSV replication in susceptible cassava induced a strong up‐regulation of RDR1 , a gene previously reported to be a susceptibility factor in other potyvirus–host pathosystems. The differences in the transcriptional responses to CBSV infection indicated that susceptibility involves the restriction of callose deposition at plasmodesmata. Aniline blue staining of callose deposits also indicated that the resistant variety displays a moderate, but significant, increase in callose deposition at the plasmodesmata. Transcriptome data suggested that resistance does not involve typical antiviral defence responses (i.e. RNA silencing and salicylic acid). A meta‐analysis of the current RNA‐sequencing (RNA‐seq) dataset and selected potyvirus–host and virus–cassava RNA‐seq datasets revealed that the conservation of the host response across pathosystems is restricted to genes involved in developmental processes.

Cereal leaf beetle (CLB, Oulema melanopus, Coleoptera, Chrysomelidae) is a serious agricultural pest that causes considerable damages to agricultural production. The aim of this study was to characterize the bacterial communities associated with larvae and imagoes of CLB collected from various cereal host species and locations. The bacterial profile was characterized by 16S rRNA gene sequencing at the V3-V4 hypervariable region. Using taxonomy-based analysis, the bacterial community of CLB containing 16 phyla, 26 classes, 49 orders, 78 families, 94 genera, and 63 species of bacteria was identified. The abundance of Wolbachia, Rickettsia, and Lactococcus genus was significantly higher in CLB imagoes than in larvae. Statistical analysis confirmed that the bacterial community of the larvae is more diverse in comparison to imagoes and that insects collected from spring barley and wheat are characterized by a much higher biodiversity level of bacterial genera and species than insects collected from other cereals. Obtained results indicated that the developmental stage, the host plant, and the insect’s sampling location affected the CLB’s microbiome. Additionally, the CLB core microbiome was determined. It consists of 2 genera (Wolbachia and Rickettsia) shared by at least 90% tested CLB insects, regardless of the variables analysed.

Cryptorchidism is the most common form of disorder of sex development in male dogs, but its hereditary predisposition is poorly elucidated. The gonadal transcriptome of nine unilaterally cryptorchid dogs and seven control dogs was analyzed using RNA-seq. Comparison between the scrotal and inguinal gonads of unilateral cryptorchid dogs revealed 8,028 differentially expressed genes (DEGs) (3,377 up-regulated and 4,651 down-regulated). A similar number of DEGs (7,619) was found by comparing the undescended testicles with the descended testicles of the control dogs. The methylation status of the selected DEGs was also analyzed, with three out of nine studied DEGs showing altered patterns. Bioinformatic analysis of the cDNA sequences revealed 20,366 SNP variants, six of which showed significant differences in allelic counts between cryptorchid and control dogs. Validation studies in larger cohorts of cryptorchid ( n = 122) and control ( n = 173) dogs showed that the TT genotype (rs850666472, p.Ala1230Val) and the AA genotype in 3′UTR (16:23716202G>A) in KATA6 , responsible for acetylation of lysine 9 in histone H3, are associated with cryptorchidism ( P = 0.0383). Both the transcript level of KAT6A and H3K9 acetylation were lower in undescended testes, and additionally, the acetylation depended on the genotypes in exon 17 and the 3′UTR. Our study showed that the massive alteration of the transcriptome in undescended testicles is not caused by germinal DNA variants in DEG regulatory sequences but is partly associated with an aberrant DNA methylation and H3K9 acetylation patterns. Moreover, variants of KAT6A can be considered markers associated with the risk of this disorder.

Resistance to anti-cancer drugs is the main challenge in oncology. In pre-clinical studies, established cancer cell lines are primary tools in deciphering molecular mechanisms of this phenomenon. In this study, we proposed a new, transcriptome-focused approach, utilizing a model of isogenic cancer cell lines with gradually changing resistance. We analyzed trends in gene expression in the aim to find out a scaffold of resistance development process. The ovarian cancer cell line A2780 was treated with stepwise increased concentrations of paclitaxel (PTX) to generate a series of drug resistant sublines. To monitor transcriptome changes we submitted them to mRNA-sequencing, followed by the identification of differentially expressed genes (DEGs), principal component analysis (PCA), and hierarchical clustering. Functional interactions of proteins, encoded by DEGs, were analyzed by building protein-protein interaction (PPI) networks. We obtained human ovarian cancer cell lines with gradually developed resistance to PTX and collateral sensitivity to cisplatin (CDDP) (inverse resistance). In their transcriptomes, we identified two groups of DEGs: (1) With fluctuations in expression in the course of resistance acquiring; and (2) with a consistently changed expression at each stage of resistance development, constituting a scaffold of the process. In the scaffold PPI network, the cell cycle regulator—polo-like kinase 2 (PLK2); proteins belonging to the tumor necrosis factor (TNF) ligand and receptor family, as well as to the ephrin receptor family were found, and moreover, proteins linked to osteo- and chondrogenesis and the nervous system development. Our cellular model of drug resistance allowed for keeping track of trends in gene expression and studying this phenomenon as a process of evolution, reflected by global transcriptome remodeling. This approach enabled us to explore novel candidate genes and surmise that abrogation of the osteomimic phenotype in ovarian cancer cells might occur during the development of inverse resistance between PTX and CDDP.

Nrf2 (nuclear factor erythroid 2 (NF-E2)-related factor 2) transcription factor is recognized for its pro-survival and cell protective role upon exposure to oxidative, chemical, or metabolic stresses. Nrf2 controls a number of cellular processes such as proliferation, differentiation, apoptosis, autophagy, lipid synthesis, and metabolism and glucose metabolism and is a target of activation in chronic diseases like diabetes, neurodegenerative, and inflammatory diseases. The dark side of Nrf2 is revealed when its regulation is imbalanced (e.g., via oncogene activation or mutations) and under such conditions constitutively active Nrf2 promotes cancerogenesis, metastasis, and radio- and chemoresistance. When there is no stress, Nrf2 is instantly degraded via Keap1-Cullin 3 (Cul3) pathway but despite this, cells exhibit a basal activation of Nrf2 target genes. It is yet not clear how Nrf2 maintains the expression of its targets under homeostatic conditions. Here, we found a stable 105 kDa Nrf2 form that is resistant to Keap1-Cul3-mediated degradation and translocates to the nucleus of lung cancer cells. RNA-Seq analysis indicate that it might originate from the exon 2 or exon 3-truncated transcripts. This stable 105 kDa Nrf2 form might help explain the constitutive activity of Nrf2 under normal cellular conditions.