Digital Gene Expression Profiling Data Research Articles

Transcriptional profiles define drug refractory disease in myeloma.

Identifying biomarkers associated with disease progression and drug resistance are important for personalized care. We investigated the expression of 121 curated genes, related to immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs) responsiveness. We analyzed 28 human multiple myeloma (MM) cell lines with known drug sensitivities and 130 primary MM patient samples collected at different disease stages, including newly diagnosed (ND), on therapy (OT), and relapsed and refractory (RR, collected within 12 months before the patients’ death) timepoints. Our findings led to the identification of a subset of genes linked to clinical drug resistance, poor survival, and disease progression following combination treatment containing IMIDs and/or PIs. Finally, we built a seven‐gene model (MM‐IMiD and PI sensitivity‐7 genes [IP‐7]) using digital gene expression profiling data that significantly separates ND patients from IMiD‐ and PI‐refractory RR patients. Using this model, we retrospectively analyzed RNA sequcencing (RNAseq) data from the Mulltiple Myeloma Research Foundation (MMRF) CoMMpass (n = 578) and Mayo Clinic MM patient registry (n = 487) to divide patients into probabilities of responder and nonresponder, which subsequently correlated with overall survival, disease stage, and number of prior treatments. Our findings suggest that this model may be useful in predicting acquired resistance to treatments containing IMiDs and/or PIs.

Identification of Drought-Resistant Genes in Shanlan Upland Rice

Shanlan upland rice is a kind of upland rice and is suitable for planting in the mountains and in hilly terrain. It is mainly found in China’s Hainan province. To discover the drought-resistant genes in Shanlan upland rice, two representative varieties—Baishanuo (BSN) and Dongfang Manpoxiang (MPX)—were selected for transcriptome sequencing, after which gene expression analysis was used to confirm their gene expression patterns. The results demonstrated that 2791 and 829 differentially expressed genes (DEGs) were identified for each variety, including 184 and 58 transcriptional factors, respectively. Expression analysis demonstrated that some genes with unknown functions, such as Os10g0505900, were highly expressed under drought stress treatment. The transcriptomic data and digital gene expression profiling data obtained in this study provide a basis for studying the drought-resistant mechanism in Shanlan upland rice.

Characterization and Comparative Expression Profiling of Browning Response in Medinilla formosana after Cutting.

Plant browning is a recalcitrant problem for in vitro culture and often leads to poor growth of explants and even failure of tissue culture. However, the molecular mechanisms underlying browning-induced physiological processes remain unclear. Medinilla is considered one of the most difficult genera for tissue culture owning to its severe browning. In the present study, intact aseptic plantlets of Medinilla formosana Hayata previously obtained by ovary culture, were used to explore the characteristics and molecular mechanism of the browning response. Successive morphological and anatomical observations after cutting showed that the browning of M. formosana was not lethal but adaptive. De novo transcriptome and digital gene expression (DGE) profiling using Illumina high-throughput sequencing were then used to explore molecular regulation after cutting. About 7.5 million tags of de novo transcriptome were obtained and 58,073 unigenes were assembled and annotated. A total of 6,431 differentially expressed genes (DEGs) at three stages after cutting were identified, and the expression patterns of these browning-related genes were clustered and analyzed. A number of putative DEGs involved in signal transduction and secondary metabolism were particularly studied and the potential roles of these cutting-responsive mRNAs in plant defense to diverse abiotic stresses are discussed. The DGE profiling data were also validated by quantitative RT-PCR analysis. The data obtained in this study provide an excellent resource for unraveling the molecular mechanisms of browning processes during in vitro tissue culture, and lay a foundation for future studies to inhibit and eliminate browning damage.

Digital gene expression profiling analysis of childhood acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is the most commonly diagnosed malignancy in children. It is a heterogeneous disease, and is determined by multiple gene alterations and chromosomal rearrangements. To improve current understanding of the underlying molecular mechanisms of ALL, the present study profiled genome‑wide digital gene expression (DGE) in a population of children with ALL in China. Using second‑generation sequencing technology, the profiling revealed that 2,825genes were upregulated and 1,952 were downregulated in the ALL group. Based on the DGE profiling data, the present study further investigated seven genes (WT1, RPS26, MSX1, CD70, HOXC4, HOXA5 and HOXC6) using reverse transcription‑quantitative polymerase chain reaction analysis. Gene Ontology analysis suggested that the differentially expressed genes were predominantly involved in immune cell differentiation, metabolic processes and programmed cell death. The results of the present study provided novel insights into the gene expression patterns in children with ALL.

Transcriptome analysis and gene expression profiling of abortive and developing ovules during fruit development in hazelnut.

BackgroundA high ratio of blank fruit in hazelnut (Corylus heterophylla Fisch) is a very common phenomenon that causes serious yield losses in northeast China. The development of blank fruit in the Corylus genus is known to be associated with embryo abortion. However, little is known about the molecular mechanisms responsible for embryo abortion during the nut development stage. Genomic information for C. heterophylla Fisch is not available; therefore, data related to transcriptome and gene expression profiling of developing and abortive ovules are needed.Methodology/Principal FindingsIn this study, de novo transcriptome sequencing and RNA-seq analysis were conducted using short-read sequencing technology (Illumina HiSeq 2000). The results of the transcriptome assembly analysis revealed genetic information that was associated with the fruit development stage. Two digital gene expression libraries were constructed, one for a full (normally developing) ovule and one for an empty (abortive) ovule. Transcriptome sequencing and assembly results revealed 55,353 unigenes, including 18,751 clusters and 36,602 singletons. These results were annotated using the public databases NR, NT, Swiss-Prot, KEGG, COG, and GO. Using digital gene expression profiling, gene expression differences in developing and abortive ovules were identified. A total of 1,637 and 715 unigenes were significantly upregulated and downregulated, respectively, in abortive ovules, compared with developing ovules. Quantitative real-time polymerase chain reaction analysis was used in order to verify the differential expression of some genes.Conclusions/SignificanceThe transcriptome and digital gene expression profiling data of normally developing and abortive ovules in hazelnut provide exhaustive information that will improve our understanding of the molecular mechanisms of abortive ovule formation in hazelnut.

Transcriptomic analysis of American ginseng seeds during the dormancy release process by RNA-Seq.

American ginseng (Panax quinquefolius L.) is an important herb that is cultivated in China, North American, and South Korea. It is propagated from seed, but the seed has deep dormancy characteristics described as morphophysiological dormancy. Two-stage temperature stratification, a warm (15–20°C) and cold (2°C) stratification period of 6 months, has been used successfully for seed dormancy release. However, little is known about the molecular mechanisms of seed dormancy release in the stratification process. In this study, seed development after pollination and seed development in the dormancy release process were investigated in American ginseng. The transcriptome during seed dormancy release was analyzed using RNA-Seq technology and 78,207 unigenes (mean length 531 bp) were generated. Based on similarity searches of public databases, 54,292 of the unigenes (69.4%) were functionally annotated. Further, three digital gene expression (DGE) libraries were sequenced and differences in gene expression at three stages during seed cold stratification were examined. The greatest number of differentially expressed genes occurred in the 90DCS versus 180DCS libraries, while the lowest number of differentially expressed genes occurred in the 135DCS verus 180DCS libraries. GO enrichment analysis revealed that 59, 29, and 39 GO terms were significantly enriched in the biological process, molecular function, and cell component GO categories, respectively. There were 25,190 genes with KEGG pathway annotation in the three DGE libraries and their enrichment pathways were compared. The gene expressions of 30 selected unigenes were validated using quantitative PCR. This study is the first to provide the transcriptome sequences for seed dormancy release in American ginseng, and demonstrates the successful use of DGE profiling data for analyzing transcriptomic variation during dormancy release. These data provide a basis for future researches of seed dormancy in morphophysiological dormancy seeds in non-model plants.

Transcriptome profiling of fruit development and maturation in Chinese white pear (Pyrus bretschneideri Rehd)

BackgroundPear (Pyrus spp) is an important fruit species worldwide; however, its genetics and genomic information is limited. Combining the Solexa/Illumina RNA-seq high-throughput sequencing approach (RNA-seq) with Digital Gene Expression (DGE) analysis would be a powerful tool for transcriptomic study. This paper reports the transcriptome profiling analysis of Chinese white pear (P. bretschneideri) using RNA-seq and DGE to better understand the molecular mechanisms in fruit development and maturation of Chinese white pear.ResultsDe novo transcriptome assembly and gene expression analysis of Chinese white pear were performed in an unprecedented depth (5.47 gigabase pairs) using high-throughput Illumina RNA-seq combined with a tag-based Digital Gene Expression (DGE) system. Approximately, 60.77 million reads were sequenced, trimmed, and assembled into 90,227 unigenes. These unigenes comprised 17,619 contigs and 72,608 singletons with an average length of 508 bp and had an N50 of 635 bp. Sequence similarity analyses against six public databases (Uniprot, NR, and COGs at NCBI, Pfam, InterPro, and KEGG) found that 61,636 unigenes can be annotated with gene descriptions, conserved protein domains, or gene ontology terms. By BLASTing all 61,636 unigenes in KEGG, a total of 31,215 unigenes were annotated into 121 known metabolic or signaling pathways in which a few primary, intermediate, and secondary metabolic pathways are directly related to pear fruit quality. DGE libraries were constructed for each of the five fruit developmental stages. Variations in gene expression among all developmental stages of pear fruit were significantly different in a large amount of unigenes.ConclusionExtensive transcriptome and DGE profiling data at five fruit developmental stages of Chinese white pear have been obtained from a deep sequencing, which provides comprehensive gene expression information at the transcriptional level. This could facilitate understanding of the molecular mechanisms in fruit development and maturation. Such a database can also be used as a public information platform for research on molecular biology and functional genomics in pear and other related species.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-14-823) contains supplementary material, which is available to authorized users.

Global transcriptome analysis of orange wheat blossom midge, Sitodiplosis mosellana (Gehin) (Diptera: Cecidomyiidae) to identify candidate transcripts regulating diapause.

BackgroundMany insects enter a developmental arrest (diapause) that allows them to survive harsh seasonal conditions. Despite the well-established ecological significance of diapause, the molecular basis of this crucial adaptation remains largely unresolved. Sitodiplosis mosellana (Gehin), the orange wheat blossom midge (OWBM), causes serious damage to wheat throughout the northern hemisphere, and sporadic outbreaks occur in the world. Traits related to diapause appear to be important factors contributing to their rapid spread and outbreak. To better understand the diapause mechanisms of OWBM, we sequenced the transcriptome and determined the gene expression profile of this species.Methodology/Principal FindingsIn this study, we performed de novo transcriptome analysis using short-read sequencing technology (Illumina) and gene expression analysis with a tag-based digital gene expression (DGE) system. The sequencing results generated 89,117 contigs, and 45,713 unigenes. These unigenes were annotated by Blastx alignment against the NCBI non-redundant (nr), Clusters of orthologous groups (COG), gene orthology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. 20,802 unigenes (45.5% of the total) matched with protein in the NCBI nr database. Two digital gene expression (DGE) libraries were constructed to determine differences in gene expression profiles during diapause and non-diapause developmental stages. Genes related to diapause were analyzed in detail and in addition, nine diapause-related genes were analyzed by real time PCR.Conclusions/SignificanceThe OWBM transcriptome greatly improves our genetic understanding and provides a platform for functional genomics research of this species. The DGE profiling data provides comprehensive information at the transcriptional level that facilitates our understanding of the molecular mechanisms of various physiological aspects including development and diapause stages in OWBM. From this study it is evident that various genes coding metabolic enzymes are crucial for diapause and metamorphosis.

Characterization of Pythium Transcriptome and Gene Expression Analysis at Different Stages of Fermentation

BackgroundThe Pythium splendens is a potentially useful organism for the synthesis of large amounts of eicosapentaenoic acid. Peak biomass and lipid accumulation do not occur at the same time and growth temperature has an effect on the fatty acid composition. Little is known about the pathway or the genes involved in growth, lipid synthesis or temperature resistance in P. splendens. Analysis of the transcriptome and expression profile data for P.splendensRBB-5 were used to extend genetic information for this strain and to contribute to a comprehensive understanding of the molecular mechanisms involved in specific biological processes.Methodology/Principal FindingsThis study used transcriptome assembly and gene expression analysis with short-read sequencing technology combined with a tag-based digital gene expression (DGE) system. Assembled sequences were annotated with gene descriptions, such as gene ontology (GO), clusters of orthologous group (COG) terms and KEGG orthology (KO) to generate 23,796 unigenes. In addition, we obtained a larger number of genes at different stages of fermentation (48, 100 and 148 h). The genes related to growth characteristics and lipid biosynthesis were analyzed in detail. Some genes associated with lipid and fatty acid biosynthesis were selected to confirm the digital gene expression (DGE) results by quantitative real-time PCR (qRT-PCR).Conclusion/SignificanceThe transcriptome improves our genetic understanding of P.splendensRBB-5 greatly and makes a large number of gene sequences available for further study. Notably, the transcriptome and DGE profiling data of P.splendensRBB-5 provide a comprehensive insight into gene expression profiles at different stages of fermentation and lay the foundation for the study of optimizing lipid content and growth speed at the molecular level.

Transcriptome analysis of Cymbidium sinense and its application to the identification of genes associated with floral development

BackgroundCymbidium sinense belongs to the Orchidaceae, which is one of the most abundant angiosperm families. C. sinense, a high-grade traditional potted flower, is most prevalent in China and some Southeast Asian countries. The control of flowering time is a major bottleneck in the industrialized development of C. sinense. Little is known about the mechanisms responsible for floral development in this orchid. Moreover, genome references for entire transcriptome sequences do not currently exist for C. sinense. Thus, transcriptome and expression profiling data for this species are needed as an important resource to identify genes and to better understand the biological mechanisms of floral development in C. sinense.ResultsIn this study, de novo transcriptome assembly and gene expression analysis using Illumina sequencing technology were performed. Transcriptome analysis assembles gene-related information related to vegetative and reproductive growth of C. sinense. Illumina sequencing generated 54,248,006 high quality reads that were assembled into 83,580 unigenes with an average sequence length of 612 base pairs, including 13,315 clusters and 70,265 singletons. A total of 41,687 (49.88%) unique sequences were annotated, 23,092 of which were assigned to specific metabolic pathways by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene Ontology (GO) analysis of the annotated unigenes revealed that the majority of sequenced genes were associated with metabolic and cellular processes, cell and cell parts, catalytic activity and binding. Furthermore, 120 flowering-associated unigenes, 73 MADS-box unigenes and 28 CONSTANS-LIKE (COL) unigenes were identified from our collection. In addition, three digital gene expression (DGE) libraries were constructed for the vegetative phase (VP), floral differentiation phase (FDP) and reproductive phase (RP). The specific expression of many genes in the three development phases was also identified. 32 genes among three sub-libraries with high differential expression were selected as candidates connected with flower development.ConclusionRNA-seq and DGE profiling data provided comprehensive gene expression information at the transcriptional level that could facilitate our understanding of the molecular mechanisms of floral development at three development phases of C. sinense. This data could be used as an important resource for investigating the genetics of the flowering pathway and various biological mechanisms in this orchid.

Transcriptome Profiling of the Goose (Anser cygnoides) Ovaries Identify Laying and Broodiness Phenotypes

BackgroundThe geese have strong broodiness and poor egg performance. These characteristics are the key issues that hinder the goose industry development. Yet little is known about the mechanisms responsible for follicle development due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to produce a comprehensive and integrated genomic resource and to better understand the biological mechanisms of goose follicle development.Methodology/Principal FindingsIn this study, we performed de novo transcriptome assembly and gene expression analysis using short-read sequencing technology (Illumina). We obtained 67,315,996 short reads of 100 bp, which were assembled into 130,514 unique sequences by Trinity strategy (mean size = 753bp). Based on BLAST results with known proteins, these analyses identified 52,642 sequences with a cut-off E-value above 10−5. Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. In addition, we investigated the transcription changes during the goose laying/broodiness period using a tag-based digital gene expression (DGE) system. We obtained a sequencing depth of over 4.2 million tags per sample and identified a large number of genes associated with follicle development and reproductive biology including cholesterol side-chain cleavage enzyme gene and dopamine beta-hydroxylas gene. We confirm the altered expression levels of the two genes using quantitative real-time PCR (qRT-PCR).Conclusions/SignificanceThe obtained goose transcriptome and DGE profiling data provide comprehensive gene expression information at the transcriptional level that could promote better understanding of the molecular mechanisms underlying follicle development and productivity.

Transcriptomic Immune Response of Tenebrio molitor Pupae to Parasitization by Scleroderma guani

BackgroundHost and parasitoid interaction is one of the most fascinating relationships of insects, which is currently receiving an increasing interest. Understanding the mechanisms evolved by the parasitoids to evade or suppress the host immune system is important for dissecting this interaction, while it was still poorly known. In order to gain insight into the immune response of Tenebrio molitor to parasitization by Scleroderma guani, the transcriptome of T. molitor pupae was sequenced with focus on immune-related gene, and the non-parasitized and parasitized T. molitor pupae were analyzed by digital gene expression (DGE) analysis with special emphasis on parasitoid-induced immune-related genes using Illumina sequencing.Methodology/Principal FindingsIn a single run, 264,698 raw reads were obtained. De novo assembly generated 71,514 unigenes with mean length of 424 bp. Of those unigenes, 37,373 (52.26%) showed similarity to the known proteins in the NCBI nr database. Via analysis of the transcriptome data in depth, 430 unigenes related to immunity were identified. DGE analysis revealed that parasitization by S. guani had considerable impacts on the transcriptome profile of T. molitor pupae, as indicated by the significant up- or down-regulation of 3,431 parasitism-responsive transcripts. The expression of a total of 74 unigenes involved in immune response of T. molitor was significantly altered after parasitization.Conclusions/Significanceobtained T. molitor transcriptome, in addition to establishing a fundamental resource for further research on functional genomics, has allowed the discovery of a large group of immune genes that might provide a meaningful framework to better understand the immune response in this species and other beetles. The DGE profiling data provides comprehensive T. molitor immune gene expression information at the transcriptional level following parasitization, and sheds valuable light on the molecular understanding of the host-parasitoid interaction.

Transcriptomic analysis of ‘Suli’ pear (Pyrus pyrifolia white pear group) buds during the dormancy by RNA-Seq

BackgroundBud dormancy is a critical developmental process that allows perennial plants to survive unfavorable environmental conditions. Pear is one of the most important deciduous fruit trees in the world, but the mechanisms regulating bud dormancy in this species are unknown. Because genomic information for pear is currently unavailable, transcriptome and digital gene expression data for this species would be valuable resources to better understand the molecular and biological mechanisms regulating its bud dormancy.ResultsWe performed de novo transcriptome assembly and digital gene expression (DGE) profiling analyses of ‘Suli’ pear (Pyrus pyrifolia white pear group) using the Illumina RNA-seq system. RNA-Seq generated approximately 100 M high-quality reads that were assembled into 69,393 unigenes (mean length = 853 bp), including 14,531 clusters and 34,194 singletons. A total of 51,448 (74.1%) unigenes were annotated using public protein databases with a cut-off E-value above 10-5. We mainly compared gene expression levels at four time-points during bud dormancy. Between Nov. 15 and Dec. 15, Dec. 15 and Jan. 15, and Jan. 15 and Feb. 15, 1,978, 1,024, and 3,468 genes were differentially expressed, respectively. Hierarchical clustering analysis arranged 190 significantly differentially-expressed genes into seven groups. Seven genes were randomly selected to confirm their expression levels using quantitative real-time PCR.ConclusionsThe new transcriptomes offer comprehensive sequence and DGE profiling data for a dynamic view of transcriptomic variation during bud dormancy in pear. These data provided a basis for future studies of metabolism during bud dormancy in non-model but economically-important perennial species.

Transcriptome Analysis of the Brown Planthopper Nilaparvata lugens

BackgroundThe brown planthopper (BPH) Nilaparvata lugens (Stål) is one of the most serious insect pests of rice in Asia. However, little is known about the mechanisms responsible for the development, wing dimorphism and sex difference in this species. Genomic information for BPH is currently unavailable, and, therefore, transcriptome and expression profiling data for this species are needed as an important resource to better understand the biological mechanisms of BPH.Methodology/Principal FindingsIn this study, we performed de novo transcriptome assembly and gene expression analysis using short-read sequencing technology (Illumina) combined with a tag-based digital gene expression (DGE) system. The transcriptome analysis assembles the gene information for different developmental stages, sexes and wing forms of BPH. In addition, we constructed six DGE libraries: eggs, second instar nymphs, fifth instar nymphs, brachypterous female adults, macropterous female adults and macropterous male adults. Illumina sequencing revealed 85,526 unigenes, including 13,102 clusters and 72,424 singletons. Transcriptome sequences larger than 350 bp were subjected to Gene Orthology (GO) and KEGG Orthology (KO) annotations. To analyze the DGE profiling, we mainly compared the gene expression variations between eggs and second instar nymphs; second and fifth instar nymphs; fifth instar nymphs and three types of adults; brachypterous and macropterous female adults as well as macropterous female and male adults. Thousands of genes showed significantly different expression levels based on the various comparisons. And we randomly selected some genes to confirm their altered expression levels by quantitative real-time PCR (qRT-PCR).Conclusions/SignificanceThe obtained BPH transcriptome and DGE profiling data provide comprehensive gene expression information at the transcriptional level that could facilitate our understanding of the molecular mechanisms from various physiological aspects including development, wing dimorphism and sex difference in BPH.