Studies in diploid parental species of polyploid plants are important to understand their contributions to the formation of plant and species evolution. Coffea eugenioides is a diploid species that is considered to be an ancestor of allopolyploid Coffea arabica together with Coffea canephora. Despite its importance in the evolutionary history of the main economic species of coffee, no study has focused on C. eugenioides molecular genetics. RNA-seq creates the possibility to generate reference transcriptomes and identify coding genes and potential candidates related to important agronomic traits. Therefore, the main objectives were to obtain a global overview of transcriptionally active genes in this species using next-generation sequencing and to analyze specific genes that were highly expressed in leaves and fruits with potential exploratory characteristics for breeding and understanding the evolutionary biology of coffee. A de novo assembly generated 36,935 contigs that were annotated using eight databases. We observed a total of ~5000 differentially expressed genes between leaves and fruits. Several genes exclusively expressed in fruits did not exhibit similarities with sequences in any database. We selected ten differentially expressed unigenes in leaves and fruits to evaluate transcriptional profiles using qPCR. Our study provides the first gene catalog for C. eugenioides and enhances the knowledge concerning the mechanisms involved in the C. arabica homeologous. Furthermore, this work will open new avenues for studies into specific genes and pathways in this species, especially related to fruit, and our data have potential value in assisted breeding applications.

Melatonin is a pleiotropic anti-cancer molecule that controls cancer growth by multiple mechanisms. RNA-Seq can potentially evaluate therapeutic response and its use in xenograft tumor models can differentiate the changes that occur specifically in tumor cells or in the tumor microenvironment (TME). Melatonin actions were evaluated in a xenograft model of triple-negative breast cancer. Balb/c nude mice bearing MDA-MB-231 tumors were treated with melatonin or vehicle. RNA-Seq was performed on the Illumina HiSeq. 2500 and data were mapped against human and mouse genomes separately to differentiate species-specific expression. Differentially expressed (DE) genes were identified and Weighted Gene Co-expression Network Analysis (WGCNA) was used to detect clusters of highly co-expressed genes. Melatonin treatment reduced tumor growth (p < 0.01). 57 DE genes were identified in murine cells, which represented the TME, and were mainly involved in immune response. The WGCNA detected co-expressed genes in tumor cells and TME, which were related to the immune system among other biological processes. The upregulation of two genes (Tnfaip8l2 and Il1f6) by melatonin was validated in the TME, these genes play important roles in the immune system. Taken together, the transcriptomic data suggests that melatonin anti-tumor actions occur through modulation of TME in this xenograft tumor model.

Piry virus (PIRYV) is a rhabdovirus (genus Vesiculovirus) and is described as a possible human pathogen, originally isolated from a Philander opossum trapped in Para State, Northern Brazil. This study describes the complete full coding sequence and the genetic characterization of PIRYV. The genome sequence reveals that PIRYV has a typical vesiculovirus-like organization, encoding the five genes typical of the genus. Phylogenetic analysis confirmed that PIRYV is most closely related to Perinet virus and clustered in the same clade as Chandipura and Isfahan vesiculoviruses.

Melatonin is a hormone produced by the pineal gland and has been shown different antitumor effects, as immunomodulatory, antioxidant, pro-apoptotic, anti-proliferative, antimetastatic and antiangiogenic, however, the pathways by which melatonin exerts its action need to be identified. Thus, the aims of this study were to perform the transcriptome analysis to evaluate the pathways of melatonin action in triple-negative breast cancer. Triple-negative breast cancer cells (MDA-MB-231) were injected into the mammary gland of the athymic nude mice (n=10), which were treated with melatonin (40 mg/kg) or vehicle during 21 days. RNA-Seq libraries were created using Truseq RNA-Seq Library Prep Kit v2. The experiment was paired-end with 100nt read length, performed on the Illumina HiSeq2500 sequencer, producing about 30 million reads per library. To differentiate human and mouse expression, the alignment was performed to filter out mouse-like reads before mapping to the human reference and vice versa, and data were mapped against human (GRCh37/hg19) and mouse (NCBI37/mm9) genomes separately, using the TopHat software. The HTSeq was employed for analyses of read counts and DESeq2 was used to identify genes differentially expressed between melatonin treated and control tumors. Differentially expressed genes (DEGs) were identified based on a false discovery rate (FDR) q-value threshold of less than 0.05. Also, we applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Results showed that animals treated with melatonin had smaller tumors volume than controls (p&lt;0.05). RNA-Seq data showed that 57.24% of reads mapped uniquely to human, 29.66% reads in mouse and 11% reads mapping to both human and mouse genomes. In human tumor cells, there was no DEGs between melatonin treated and control group (adjP&gt;0.05). In mouse cells, which represent the tumor microenvironment, there were 34 DEGs between animals treated with melatonin and controls (adjP&lt;0.05). In tumors cells, we detected 714 differentially co-expressed genes (IKdiffI&gt;0.6), which were functionally enriched for GO terms like lipid metabolic process, response to drug, oxidoreductase activity and PPAR signaling (adjP&lt;0.1). Also, we identified 3 gene modules strongly associated with melatonin treatment, which were related with metabolic pathways (adjP&lt;0.1). In mouse cells, were detected 1345 differentially co-expressed genes, which were enriched for signaling pathways like Wnt receptor, Hedgehog and TGF-beta (adjP&lt;0.1). There were 3 gene modules strongly associated with melatonin treatment, which are enriched for regulation of translation and cell cycle, immune system process and T cell differentiation, regulation of action cytoskeleton and ErbB signaling pathway (adjP&lt;0.1). Also, potential regulator genes for melatonin treatment were detected by generating clusters of co-expressed genes and individual analysis confirms these results. Transcriptomic network analysis coupled with other results showed that melatonin treatment controls the tumor growth, acting especially by metabolic pathways in tumor cells and modulating the tumor microenvironment. Citation Format: Jardim-Perassi BV, Sonehara NM, de Paula-Junior R, Chammas R, Coutinho LL, Reis Júnior O, Alexandre PA, Fukumasu H, Zuccari DAPC. Melatonin treatment: A transcriptomic networks in a xenograft model of breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-05-28.