Reads Per Kilobase Per Million Research Articles

Shot-gun proteome and transcriptome mapping of the jujube floral organ and identification of a pollen-specific S-locus F-box gene.

The flower is a plant reproductive organ that forms part of the fruit produced as the flowering season ends. While the number and identity of proteins expressed in a jujube (Ziziphus jujuba Mill.) flower is currently unknown, integrative proteomic and transcriptomic analyses provide a systematic strategy of characterizing the floral biology of plants. We conducted a shotgun proteomic analysis on jujube flowers by using a filter-aided sample preparation tryptic digestion, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). In addition, transcriptomics analyses were performed on HiSeq2000 sequencers. In total, 7,853 proteins were identified accounting for nearly 30% of the ‘Junzao’ gene models (27,443). Genes identified in proteome generally showed higher RPKM (reads per kilobase per million mapped reads) values than undetected genes. Gene ontology categories showed that ribosomes and intracellular organelles were the most dominant classes and accounted for 17.0% and 14.0% of the proteome mass, respectively. The top-ranking proteins with iBAQ >1010 included non-specific lipid transfer proteins, histones, actin-related proteins, fructose-bisphosphate aldolase, Bet v I type allergens, etc. In addition, we identified one pollen-specificity S-locus F-box-like gene located on the same chromosome as the S-RNase gene. Both of these may activate the behaviour of gametophyte self-incompatibility in jujube. These results reflected the protein profile features of jujube flowers and contributes new information important to the jujube breeding system.

Union Exon Based Approach for RNA-Seq Gene Quantification: To Be or Not to Be?

In recent years, RNA-seq is emerging as a powerful technology in estimation of gene and/or transcript expression, and RPKM (Reads Per Kilobase per Million reads) is widely used to represent the relative abundance of mRNAs for a gene. In general, the methods for gene quantification can be largely divided into two categories: transcript-based approach and ‘union exon’-based approach. Transcript-based approach is intrinsically more difficult because different isoforms of the gene typically have a high proportion of genomic overlap. On the other hand, ‘union exon’-based approach method is much simpler and thus widely used in RNA-seq gene quantification. Biologically, a gene is expressed in one or more transcript isoforms. Therefore, transcript-based approach is logistically more meaningful than ‘union exon’-based approach. Despite the fact that gene quantification is a fundamental task in most RNA-seq studies, however, it remains unclear whether ‘union exon’-based approach for RNA-seq gene quantification is a good practice or not. In this paper, we carried out a side-by-side comparison of ‘union exon’-based approach and transcript-based method in RNA-seq gene quantification. It was found that the gene expression levels are significantly underestimated by ‘union exon’-based approach, and the average of RPKM from ‘union exons’-based method is less than 50% of the mean expression obtained from transcript-based approach. The difference between the two approaches is primarily affected by the number of transcripts in a gene. We performed differential analysis at both gene and transcript levels, respectively, and found more insights, such as isoform switches, are gained from isoform differential analysis. The accuracy of isoform quantification would improve if the read coverage pattern and exon-exon spanning reads are taken into account and incorporated into EM (Expectation Maximization) algorithm. Our investigation discourages the use of ‘union exons’-based approach in gene quantification despite its simplicity.

Transcriptome sequencing and characterization for Kappaphycus alvarezii

The transcriptome of Kappaphycus alvarezii was profiled using high-throughput Solexa paired-end sequencing technology. A total of 61 million sequencing reads was generated by filtering the low-quality reads, and 28 701 unigenes with a mean length of 901 bp were obtained based on de novo assembly. In similarity alignments against the NCBI non-redundant protein sequence (NR) database, Swissprot database, Cluster of Orthologous Groups (COG) database, Gene ontology (GO) database, and Kyoto Encyclopedia of Genes and Genomes (KEGG) database, 11 996 (41.79%) unigenes were identified with significant hits (E-value < 10−5) against existing genes. Functional annotation with the KEGG pathway database identified 8975 unigenes and mapped to 125 pathways. Through functional enrichment analysis of the genes with a higher expression value than the average RPKM (reads per kilobase per million reads), we found that some important pathways were highly expressed. The substantial number of transcript sequences of K. alvarezii provides a valuable resource for potential gene identification and comparative genomic studies.

BioWardrobe: an integrated platform for analysis of epigenomics and transcriptomics data.

High-throughput sequencing has revolutionized biology by enhancing our ability to perform genome-wide studies. However, due to lack of bioinformatics expertise, modern technologies are still beyond the capabilities of many laboratories. Herein, we present the BioWardrobe platform, which allows users to store, visualize and analyze epigenomics and transcriptomics data using a biologist-friendly web interface, without the need for programming expertise. Predefined pipelines allow users to download data, visualize results on a genome browser, calculate RPKMs (reads per kilobase per million) and identify peaks. Advanced capabilities include differential gene expression and binding analysis, and creation of average tag -density profiles and heatmaps. BioWardrobe can be found at http://biowardrobe.com.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0720-3) contains supplementary material, which is available to authorized users.

THE TREATMENT-RESISTANT MESENCHYMAL SIGNATURE IN GLIOBLASTOMA DERIVES FROM TUMOR CELLS INDEPENDENT OF STROMA

BACKGROUND: Glioma sphere-forming cells (GSCs) derived from surgical specimens are a fundamental resource to study glioblastoma (GBM) biology. Mesenchymal-expressing GSCs have been proposed as a source of treatment resistance and mesenchymal tumors correlate with poorer survival. Recently, we found that the anti-angiogensis drug bevacizumab appeared to provide no benefit to patients with mesenchymal tumors, in contradiction to expectations that a mesenchymal microenvironment may benefit from anti-angiogenesis therapy. We have developed a collection of GSCs that have undergone comprehensive genomic characterization, similar to that performed by the Cancer Genome Atlas (TCGA) for whole tumor specimens. We hypothesized that the genomic landscape of GSCs would recapitulate what was observed by TCGA. METHODS: 47 GSCs were obtained from primary culture of fresh tumor specimens obtained at surgery and cultured as 3-dimensional spheres in the absence of serum. All lines were subjected to RNAseq (75bp paired-end, 100X coverage), copy number analysis (Affymetrix Oncoscan 2.0), whole methylome (Illumina Infinium 450k bead array), and targeted resequencing of known cancer-associated genes. Whole exome sequencing was performed for 22 GSCs. Gene expression was determined by reads per kilobase per million (RPKM) using an RNA sequencing data analysis pipeline (PRADA) and somatic mutations identified by a commonly used detection method (MuTech). Consensus clustering based on none-negative matrix factorization (CNMF) was performed on expression data and correlation to TCGA clusters determined by single-sample gene set enrichment analysis (ssGSEA). RESULTS: While global copy number alterations such as gain of chromosome 7 at the EGFR locus or loss of chromosome 10 at the PTEN locus were shared between tumor and matched GSC, the rate of somatic events was significantly higher in GSCs compared to tumors (range 47-570, median 124 vs range 2-255, median 65). Optimization of CNMF identified a total of 5 gene-expression clusters. GSCs in only one of these clusters showed enrichment for a unique TCGA class, mesenchymal. GSCs in other clusters were divided among multiple TCGA classes. CONCLUSIONS: Mesenchymal glioblastomas are derived from mesenchymal GSCs, suggesting that the tumor component is the largest contributor to the aggressive biology of this subtype. GSCs from other tumor subtypes correlate to multiple TCGA classes, suggesting that tumor stroma may contribute to the expression phenotype in those cases. Therapeutics targeting the microenvironment, such as anti-angiogenesis drugs, may have a greater role in non-mesenchymal tumors where the stromal contribution is more prominent. SECONDARY CATEGORY: Neuropathology & Tumor Biomarkers.

Normalization of RNA-Sequencing Data from Samples with Varying mRNA Levels

Methods for normalization of RNA-sequencing gene expression data commonly assume equal total expression between compared samples. In contrast, scenarios of global gene expression shifts are many and increasing. Here we compare the performance of three normalization methods when polyA+ RNA content fluctuates significantly during zebrafish early developmental stages. As a benchmark we have used reverse transcription-quantitative PCR. The results show that reads per kilobase per million (RPKM) and trimmed mean of M-values (TMM) normalization systematically leads to biased gene expression estimates. Biological scaling normalization (BSN), designed to handle differences in total expression, showed improved accuracy compared to the two other methods in estimating transcript level dynamics. The results have implications for past and future studies using RNA-sequencing on samples with different levels of total or polyA+ RNA.

Transcriptomic Analysis of Genes Modulated by Cyclo(L-Phenylalanine-L-Proline) in Vibrio vulnificus

Diketopiperazine is produced by various organisms, including bacteria, fungi, and animals, and has been suggested as a novel signal molecule involved in the modulation of genes with various biological functions. Vibrio vulnificus, which causes septicemia in humans, produces cyclo(L-phenylalanine-L-proline) (cFP). To understand the biological roles of cFP, the effect of the compound on the expression of the total mRNA in V. vulnificus was assessed by nextgeneration sequencing. Based on the transcriptomic analysis, we classified the cFP-regulated genes into functional categories and clustered them according to the expression patterns resulted from treatment with cFP. From a total of 4,673 genes, excepting the genes encoding tRNA in V. vulnificus, 356 genes were up-regulated and 602 genes were down-regulated with an RPKM (reads per kilobase per million) value above 3. The genes most highly induced by cFP comprised those associated with the transport and metabolism of inorganic molecules, particularly iron. The genes negatively regulated by cFP included those associated with energy production and conversion, as well as carbohydrate metabolism. Noticeably, numerous genes related with biofilm formation were modulated by cFP. We demonstrated that cFP interferes significantly with the biofilm formation of V. vulnificus.

Abstract 1509: Transcriptome analysis reveals significant effects of EGFR signaling on the secretome of mesenchymal stem cells.

Abstract Mesenchymal stem cell (MSCs) are recruited by developing tumors, where MSCs release factors that enhance tumor cell proliferation and migration. Since different carcinomas synthesize epidermal growth factor (EGF)-like peptides and MSCs express the EGF receptor (EGFR), we hypothesize that EGFR signaling might mediate the interaction between MSCs and tumor cells. In order to comprehensively assess the mechanisms and factors that are regulated by EGFR signaling in MSCs and are involved in the interaction between MSCs and tumor cells, we analysed the transcriptome of MSCs cultured in absence or in presence of transforming growth factor α (TGFα), one of the main ligands of the EGFR, by using massively parallel sequencing. Libraries were prepared from poly-A RNA from not-stimulated (MSC-CTRL) or TGFα-stimulated (MSC-TGFα) MSCs. Sequencing was performed on the SOLiD 5500xl platform using the paired-end protocol (75bp + 35bp). The experiments were repeated in quadruplicate, and the average number of reads obtained in the 4 replicates resulted of about 37 million for MSC-CTRL, and 47 million for MSC-TGFα. The quality analysis of raw data showed that 75% of reads at the 75th position had quality values above 14. The mapping of the sequence reads to human hg19 reference genome evidenced a coverage ranging between 79.5% and 81.7% for MSC-CTRL, and between 76.3% and 79.0% for MSC-TGFα. The number of observed counts was normalized for the length of the element and the number of mapped reads, namely RPKM (Reads Per Kilobase per Million of mapped reads). The RPKM values obtained in the 4 replicates were compared by ANOVA test and the very high p-value (of about 1) demonstrated that the replicates were not statistically different. The differential gene expression in MSC-CTRL and MSC-TGFα was represented as fold induction (FI). When selecting genes for which the average count value of the 4 replicates was equal or higher than 1, 8946 genes resulted to have FI&amp;gt;1 and 10305 genes FI&amp;lt;1 according to RPKM values. Next, we focused the attention on 274 genes coding for secreted proteins, including interleukins, chemokines, angiogenesis factors, growth factors of the EGF, IGF and FGF families and their receptors. Using as cutoff a count value equal or higher than 1, 47 genes were considered not expressed, 126 genes resulted to have FI&amp;gt;1.0, 91 genes FI&amp;lt;1.0 and 10 genes FI=1.0. Among the secreted proteins investigated, a number of angiogenic factors were significantly modulated in MSCs by TGFα treatment. Analysis of secreted proteins, performed with XMAP based assays, confirmed that activation of EGFR signaling induces in MSCs the secretion of several pro-angiogenic factors, including VEGF, IL6, IL8, HGF and G-CSF. These findings strongly suggest that the EGFR-mediated interaction between MSCs and tumor cells induces in MSCs the secretion of factors that play an important role in tumor progression. Citation Format: Antonella De Luca, Cristin Roma, Francesca Fenizia, Francesca Bergantino, Marianna Gallo, Daniela Frezzetti, Susan Costantini, Nicola Normanno. Transcriptome analysis reveals significant effects of EGFR signaling on the secretome of mesenchymal stem cells. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1509. doi:10.1158/1538-7445.AM2013-1509

Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts

Chimeric RNAs comprise exons from two or more different genes and have the potential to encode novel proteins that alter cellular phenotypes. To date, numerous putative chimeric transcripts have been identified among the ESTs isolated from several organisms and using high throughput RNA sequencing. The few corresponding protein products that have been characterized mostly result from chromosomal translocations and are associated with cancer. Here, we systematically establish that some of the putative chimeric transcripts are genuinely expressed in human cells. Using high throughput RNA sequencing, mass spectrometry experimental data, and functional annotation, we studied 7424 putative human chimeric RNAs. We confirmed the expression of 175 chimeric RNAs in 16 human tissues, with an abundance varying from 0.06 to 17 RPKM (Reads Per Kilobase per Million mapped reads). We show that these chimeric RNAs are significantly more tissue-specific than non-chimeric transcripts. Moreover, we present evidence that chimeras tend to incorporate highly expressed genes. Despite the low expression level of most chimeric RNAs, we show that 12 novel chimeras are translated into proteins detectable in multiple shotgun mass spectrometry experiments. Furthermore, we confirm the expression of three novel chimeric proteins using targeted mass spectrometry. Finally, based on our functional annotation of exon organization and preserved domains, we discuss the potential features of chimeric proteins with illustrative examples and suggest that chimeras significantly exploit signal peptides and transmembrane domains, which can alter the cellular localization of cognate proteins. Taken together, these findings establish that some chimeric RNAs are translated into potentially functional proteins in humans.

Characterization of Transcriptional Differences Between Columnar and Standard Apple Trees Using RNA-Seq

The columnar apple tree is a valuable resource for genetic improvement of cultivated apples due to its special architecture. To identify genes involved in the columnar architecture, expression profiles of newly developing shoots of standard and columnar trees from a segregating population of “Fuji” × “Telamon” have been analyzed using the new generation of high-throughput RNA-Seq technology. Following Blast analysis against Nr, SwissProt, KEGG, and COG databases, a total of 69,558 unigene annotations have been identified. Among them, more than 80.68% and 79.87% clean reads of Apple-Co and Apple-St samples, respectively, have been mapped to reference apple genome. Interestingly, 57% of genes were covered with more than 50% clean reads. Moreover, 1,252 and 1,443 unigenes from Apple-Co and Apple-St tissues, respectively, had alternative splicing sites. Among these, 614 and 666 were alternative 3′ splice sites and the most abundant, followed by alternative 5′ splice sites, while exon skipping sites were the least frequent. In addition, 13,142 and 13,334 novel transcript units were identified form Apple-Co and Apple-St samples, respectively. Moreover, analysis of RPKM (reads per kilobase per million reads) values found that expression of 5,237 unigenes differed by more than twofold. Among these, 1,359 were enriched in 232 metabolic pathways based on KEGG database annotation, and 2,233 were enriched in biological regulation, cellular process, etc. pathways based on GO functional annotation, and 287 unigenes were related with apple architecture. Among the 287 unigenes, 31 unigenes mapped to chromosome 10 of apple genome, and 25 unigenes were GRAS transcription factor, which were suggested to play an important role in architecture formation of columnar apple trees. Taking together, this study provided a theoretical basis for further enriching gene resources of important agronomic traits of fruit trees and for understanding the formation mechanism of columnar apple trees.