Summary Plants are continuously exposed to diurnal fluctuations in light and temperature, and spontaneous changes in their physical or biotic environment. The circadian clock coordinates regulation of gene expression with a 24 h period, enabling the anticipation of these events. We used RNA sequencing to characterize the Brachypodium distachyon transcriptome under light and temperature cycles, as well as under constant conditions. Approximately 3% of the transcriptome was regulated by the circadian clock, a smaller proportion than reported in most other species. For most transcripts that were rhythmic under all conditions, including many known clock genes, the period of gene expression lengthened from 24 to 27 h in the absence of external cues. To functionally characterize the cyclic transcriptome in B. distachyon, we used Gene Ontology enrichment analysis, and found several terms significantly associated with peak expression at particular times of the day. Furthermore, we identified sequence motifs enriched in the promoters of similarly phased genes, some potentially associated with transcription factors. When considering the overlap in rhythmic gene expression and specific pathway behavior, thermocycles was the prevailing cue that controlled diurnal gene regulation. Taken together, our characterization of the rhythmic B. distachyon transcriptome represents a foundational resource with implications in other grass species.

The aim of the present study was to identify potential key genes associated with the progression and prognosis of colorectal cancer (CRC). Differentially expressed genes (DEGs) between CRC and normal samples were screened by integrated analysis of gene expression profile datasets, including the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted to identify the biological role of DEGs. In addition, a protein-protein interaction network and survival analysis were used to identify the key genes. The profiles of GSE9348, GSE22598 and GSE113513 were downloaded from the GEO database. A total of 405 common DEGs were identified, including 236 down- and 169 upregulated. GO analysis revealed that the downregulated DEGs were mainly enriched in ‘detoxification of copper ion’ [biological process, (BP)], ‘oxidoreductase activity, acting on CH-OH group of donors, NAD or NADP as acceptor’ [molecular function, (MF)] and ‘brush border’ [cellular component, (CC)]. Upregulated DEGs were mainly involved in ‘nuclear division’ (BP), ‘snoRNA binding’ (MF) and ‘nucleolar part’ (CC). KEGG pathway analysis revealed that DEGs were mainly involved in ‘mineral absorption’, ‘nitrogen metabolism’, ‘cell cycle’ and ‘caffeine metabolism’. A PPI network was constructed with 268 nodes and 1,027 edges. The top one module was selected, and it was revealed that module-related genes were mainly enriched in the GO terms ‘sister chromatid segregation’ (BP), ‘chemokine activity’ (MF), and ‘condensed chromosome (CC)’. The KEGG pathway was mainly enriched in ‘cell cycle’, ‘progesterone-mediated oocyte maturation’, ‘chemokine signaling pathway’, ‘IL-17 signaling pathway’, ‘legionellosis’, and ‘rheumatoid arthritis’. DNA topoisomerase II-α (TOP2A), mitotic arrest deficient 2 like 1 (MAD2L1), cyclin B1 (CCNB1), checkpoint kinase 1 (CHEK1), cell division cycle 6 (CDC6) and ubiquitin conjugating enzyme E2 C (UBE2C) were indicated as hub genes. Furthermore, survival analysis revealed that TOP2A, MAD2L1, CDC6 and CHEK1 may serve as prognostic biomarkers in CRC. The present study provided insights into the molecular mechanism of CRC that may be useful in further investigations.

The development of cutaneous squamous cell carcinoma (cSCC) is associated with activation of the epidermal growth factor receptor (EGFR). EGFR-targeting presents a promising strategy for improving therapeutic efficacy. However, recent studies have suggested that tumours overexpressing EGFR depend on autophagy for survival and exhibit resistance to EGFR-targeting drugs. Chloroquine diphosphate (CQ), an autophagy inhibitor that may enhance the cytocidal effect of gefitinib against cSCC, was used in the present study. Cytotoxicity assays were performed to determine the half-maximal inhibitory concentration values of gefitinib and CQ in A431 cells. Drug interaction was analysed using CompuSyn software, which also determined combination index and dose reduction index values. Apoptosis and autophagy of A431 cells were investigated via flow cytometry, western blotting analyses, acridine orange/ethidium bromide staining and monodansylcadaverine staining. Suppression of autophagy by CQ, which was demonstrated by an alteration in microtubule associated protein 1 light chain 3-B in CQ pre-treated A431 cells, significantly enhanced cell apoptosis, which suggested that gefitinib-induced autophagy is cytoprotective. Thus, CQ was demonstrated to exhibit a synergistic apoptotic effect when used in combination with gefitinib during cSCC therapy. Further in vivo investigations are required to confirm the results of the present study.

Motivation Tumor and adjacent normal RNA samples are commonly used to screen differentially expressed genes between normal and tumor samples or among tumor subtypes. Such paired-sample design could avoid numerous confounders in differential expression (DE) analysis, but the cellular contamination of tumor samples can be an important noise and confounding factor, which can both inflate false-positive rate and deflate true-positive rate. The existing DE tools that use next-generation RNA-seq data either do not account for cellular contamination or are computationally extensive with increasingly large sample size. Results A novel linear model was proposed to avoid the problem that could arise from tumor–normal correlation for paired samples. A statistically robust and computationally very fast DE analysis procedure, contamDE-lm, was developed based on the novel model to account for cellular contamination, boosting DE analysis power through the reduction in individual residual variances using gene-wise information. The desired advantages of contamDE-lm over some state-of-the-art methods (limma and DESeq2) were evaluated through the applications to simulated data, TCGA database and Gene Expression Omnibus (GEO) database. Availability and implementation The proposed method contamDE-lm was implemented in an updated R package contamDE (version 2.0), which is freely available at https://github.com/zhanghfd/contamDE. Supplementary information Supplementary data are available at Bioinformatics online.

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