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Hybridization is a prominent process among natural plant populations that can result in phenotypic novelty, heterosis, and changes in gene expression. The effects of intraspecific hybridization on F1 hybrid gene expression were investigated using parents from divergent, natural populations of Cirsium arvense, an invasive Compositae weed.

Using an RNA-seq approach, the expression of 68,746 unigenes was quantified in parents and hybrids. The expression levels of 51% of transcripts differed between parents, a majority of which had <1.25x fold-changes. More unigenes had higher expression in the invasive parent (P1) than the non-invasive parent (P2). Of those that were divergently expressed between parents, 10% showed additive and 81% showed non-additive (transgressive or dominant) modes of gene action in the hybrids. A majority of the dominant cases had P2-like expression patterns in the hybrids. Comparisons of allele-specific expression also enabled a survey of cis- and trans-regulatory effects. Cis- and trans-regulatory divergence was found at 70% and 68% of 62,281 informative SNP sites, respectively. Of the 17% of sites exhibiting both cis- and trans- effects, a majority (70%) had antagonistic regulatory interactions (cis x trans); trans-divergence tended to drive higher expression of the P1 allele whereas cis-divergence tended to increase P2 transcript abundance. Trans-effects correlated more highly than cis- with parental expression divergence and accounted for a greater proportion of the regulatory divergence at sites with additive compared to non-additive inheritance patterns. This study explores the nature of, and types of mechanisms underlying, expression changes that occur in upon intraspecific hybridization in natural populations.

• Bell GD, Kane NC, Rieseberg LH, Adams KL. (2013) RNA-seq analysis of allele-specific expression, hybrid effects, and regulatory divergence in hybrids compared with their parents from natural populations. Genome Biol Evol [Epub ahead of print]. [abstract]

Many species have evolved into diverse strains with phenotypic and genotypic variations that facilitate adaptation to different ecological niches and, in the case of pathogens, to different hosts. Whereas comparison of genome sequences reveals differences and similarities among strains, the consequences of genomic variations can be tracked by studying the functional output from the genome. RNA sequencing has been revolutionizing transcriptome analyses of both pro- and eukaryotes. However, the bioinformatics-based analysis is still lagging behind, and transcriptome features are often manually annotated, which is laborious and time-consuming. This is even more compounded for the analyses of multiple strains.

Here, a team led by researchers at the University of Würzburg and the University of Tübingen, Germany compared the primary transcriptomes of four isolates of Campylobacter jejuni, the leading cause of bacterial gastroenteritis in humans, and provide genome-wide transcriptional start site (TSS) maps using a novel automated annotation method. Their comparative RNA–seq showed that most TSS are conserved in multiple strains, but they also observed SNP–dependent promoter usage. Furthermore, the researchers identified a novel minimal RNA–based CRISPR immune system as well as strain-specific small RNA repertoires. This automated, comparative TSS annotation will facilitate and improve transcriptome annotation for a wider range of organisms and provides insights into the contribution of transcriptome differences to phenotypic variation among closely related species.

• Dugar G, Herbig A, Förstner KU, Heidrich N, Reinhardt R, et al. (2013) High-Resolution Transcriptome Maps Reveal Strain-Specific Regulatory Features of Multiple Campylobacter jejuni Isolates. PLoS Genet 9(5), e1003495. [article]

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Exosomes, endosome-derived membrane microvesicles, contain specific RNA transcripts that are thought to be involved in cell-cell communication. These RNA transcripts have great potential as disease biomarkers. To characterize exosomal RNA profiles systemically, a team led by researchers at the Medical College of Wisconsin performed RNA sequencing analysis using three human plasma samples and evaluated the efficacies of small RNA library preparation protocols from three manufacturers. In all they evaluated 14 libraries (7 replicates).

From the 14 size-selected sequencing libraries, the researchers obtained a total of 101.8 million raw single-end reads, an average of about 7.27 million reads per library. Sequence analysis showed that there was a diverse collection of the exosomal RNA species among which microRNAs (miRNAs) were the most abundant, making up over 42.32% of all raw reads and 76.20% of all mappable reads. At the current read depth, 593 miRNAs were detectable. The five most common miRNAs (miR-99a-5p, miR-128, miR-124-3p, miR-22-3p, and miR-99b-5p) collectively accounted for 48.99% of all mappable miRNA sequences. MiRNA target gene enrichment analysis suggested that the highly abundant miRNAs may play an important role in biological functions such as protein phosphorylation, RNA splicing, chromosomal abnormality, and angiogenesis. From the unknown RNA sequences, they predicted 185 potential miRNA candidates. Furthermore, they detected significant fractions of other RNA species including ribosomal RNA (9.16% of all mappable counts), long non-coding RNA (3.36%), piwi-interacting RNA (1.31%), transfer RNA (1.24%), small nuclear RNA (0.18%), and small nucleolar RNA (0.01%); fragments of coding sequence (1.36%), 5’ untranslated region (0.21%), and 3’ untranslated region (0.54%) were also present. In addition to the RNA composition of the libraries, they found that the three tested commercial kits generated a sufficient number of DNA fragments for sequencing but each had significant bias toward capturing specific RNAs. Read more

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The granulosa cells in the mammalian ovarian follicle respond to gonadotropin signalling and are involved in the processes of folliculogenesis and oocyte maturation. Studies on gene expression and regulation in human granulosa cells are of interest due to their potential for estimating the oocyte viability and IVF success. However, the post-transcriptional gene expression studies on microRNA (miRNA) level in the human ovary have been scarce.

The current study determined the miRNA profile by deep sequencing of the two intrafollicular somatic cell types: mural and cumulus granulosa cells (MGC and CGC, respectively) isolated from women undergoing controlled ovarian stimulation and in vitro fertilization. Altogether 936 annotated and nine novel miRNAs were identified. Ninety of the annotated miRNAs were differentially expressed between MGC and CGC. Bioinformatic prediction revealed that TGFβ, ErbB signalling and heparan sulphate biosynthesis were targeted by miRNAs in both granulosa cell populations, while extracellular matrix remodelling, Wnt and neurotrophin signalling pathways were enriched among miRNA targets in MGC. Two of the novel miRNAs found were of intronic origin: one from the aromatase and the other from the FSH receptor gene. The latter miRNA was predicted to target the activin signalling pathway.

In addition to revealing the genome-wide miRNA signature in human granulosa cells, these results suggest that post-transcriptional regulation of gene expression by miRNAs could play an important role in the modification of gonadotropin signalling. miRNA expression studies could therefore lead to new prognostic markers in assisted reproductive technologies.

• Velthut-Meikas A, Simm J, Tuuri T, Tapanainen JS, Metsis M, Salumets A. (2013) Research Resource: Small RNA-seq of human granulosa cells reveals miRNAs in FSHR and aromatase genes. Mol Endocrinol [Epub ahead of print]. [abstract]

New sequencing technologies allow unprecedented views into changes occurring in virus-infected cells, including comprehensive and largely unbiased measurements of different types of RNA. In this study, researchers from the University of Washington used RNA-Seq to profile dynamic changes in cellular microRNAs occurring in HIV-infected cells. The sensitivity afforded by sequencing allowed them to detect changes in microRNA expression early in infection, before the onset of viral replication. A phased pattern of expression was evident among these microRNAs, and many that were initially suppressed were later overexpressed at the height of infection, providing unique signatures of infection. By integrating additional mRNA data with the microRNA data, they identified a role for microRNAs in transcriptional regulation during infection and specifically a network of microRNAs involved in the expression of a known HIV cofactor. Finally, as a distinct benefit of sequencing, they identified candidate nonannotated microRNAs, including one whose downregulation may allow HIV-1 replication to proceed fully.

• Chang ST, Thomas MJ, Sova P, Green RR, Palermo RE, Katze MG. (2013) Next-generation sequencing of small RNAs from HIV-infected cells identifies phased microrna expression patterns and candidate novel microRNAs differentially expressed upon infection. MBio 4(1), e00549-12. [article]

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Alternative mRNA splicing (AS) is a major mechanism for increasing regulatory complexity. A key concept in AS is the distinction between alternatively and constitutively spliced exons (ASEs and CSEs, respectively). ASEs and CSEs have been reported to be differentially regulated, and to have distinct biological properties. However, the recent flood of RNA-sequencing data has obscured the boundary between ASEs and CSEs. Researchers are beginning to question whether ‘authentic CSEs’ do exist, and whether the ASE/CSE distinction is biologically invalid.

Here, Feng-Chi Chen with the National Health Research Institutes of Taiwan examines the influences of increasing transcriptome data on the human ASE/CSE classification and our past understanding of the properties of these two types of exons. Interestingly, although the percentage of human ASEs has increased dramatically in recent years, the overall distinction between ASEs and CSEs remains valid. For example, CSEs are longer, evolve more slowly, and less frequently correspond to intrinsically disordered protein regions than ASEs. In addition, only a relatively small number of human genes have their transcripts composed entirely of ASEs despite the large amount of high-throughput transcriptome information. Therefore, the ‘backbone’ concept of AS, in which CSEs constitute the invariant part and ASEs the flexible part of the transcript, appears to be generally true despite the increasing percentage of ASEs in the human exome.

 

• Chen FC. (2013) Are all of the human exons alternatively spliced? Brief Bioinform [Epub ahead of print]. [abstract]

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Transcriptome analysis is a valuable tool for identification and characterization of genes and pathways underlying plant growth and development. A team led by scientists at University of Wisconsin previously published a microarray-based maize gene atlas from the analysis of 60 unique spatially and temporally separated tissues from 11 maize organs. To enhance the coverage and resolution of the maize gene atlas, they have analyzed 18 selected tissues representing five organs using RNA sequencing (RNA-Seq). For a direct comparison of the two methodologies, the same RNA samples originally used for our microarray-based atlas were evaluated using RNA-Seq. Both technologies produced similar transcriptome profiles as evident from high Pearson’s correlation statistics ranging from 0.70 to 0.83, and from nearly identical clustering of the tissues.

RNA-Seq provided enhanced coverage of the transcriptome, with 82.1% of the filtered maize genes detected as expressed in at least one tissue by RNA-Seq compared to only 56.5% detected by microarrays. Further, from the set of 465 maize genes that have been historically well characterized by mutant analysis, 427 show significant expression in at least one tissue by RNA-Seq compared to 390 by microarray analysis. RNA-Seq provided higher resolution for identifying tissue-specific expression as well as for distinguishing the expression profiles of closely related paralogs as compared to microarray-derived profiles. Co-expression analysis derived from the microarray and RNA-Seq data revealed that broadly similar networks result from both platforms, and that co-expression estimates are stable even when constructed from mixed data including both RNA-Seq and microarray expression data. The RNA-Seq information provides a useful complement to the microarray-based maize gene atlas and helps to further understand the dynamics of transcription during maize development.

• Sekhon RS, Briskine R, Hirsch CN, Myers CL, Springer NM, et al. (2013) Maize Gene Atlas Developed by RNA Sequencing and Comparative Evaluation of Transcriptomes Based on RNA Sequencing and Microarrays. PLoS ONE 8(4), e61005. [article]

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Researchers at the National Institute of Environmental Health Sciences hypothesized RNA-Seq would reveal more differentially expressed genes (DEG) than microarray analysis, including low copy and novel transcripts related to the carcinogenic activity of 1 ppm aflatoxin B1 (AFB1) compared to feed controls (CTRL). Paired-end reads were mapped to the rat genome (Rn4) with TopHat and further analyzed by DESeq and Cufflinks-Cuffdiff pipelines to identify differentially expressed transcripts, new exons and unannotated transcripts.

PCA and cluster analysis of DEGs showed clear separation between AFB1 and CTRL treatments and concordance among group replicates. qPCR of eight high and medium DEGs and three low DEGs showed good comparability among RNA-Seq and microarray transcripts. DESeq analysis identified 1,026 differentially expressed transcripts at greater than two-fold change (p<0.005) compared to 626 transcripts by microarray due to base pair resolution of transcripts by RNA-Seq, probe placement within transcripts or an absence of probes to detect novel transcripts, splice variants and exons. Pathway analysis among DEGs revealed signaling of Ahr, Nrf2, GSH, xenobiotic, cell cycle, extracellular matrix, and cell differentiation networks consistent with pathways leading to AFB1 carcinogenesis, including almost 200 upregulated transcripts controlled by E2f1-related pathways related to kinetochore structure, mitotic spindle assembly and tissue remodeling.

The researchers report 49 novel, differentially-expressed transcripts including confirmation by PCR-cloning of two unique, unannotated, hepatic AFB1-responsive transcripts (HAfT’s) on chromosomes 1.q55 and 15.q11, overexpressed by 10 to 25-fold. Several potentially novel exons were found and exon refinements were made including AFB1 exon-specific induction of homologous family members, Ugt1a6 and Ugt1a7c. They find the rat transcriptome contains many previously unidentified, AFB1-responsive exons and transcripts supporting RNA-Seq’s capabilities to provide new insights into AFB1-mediated gene expression leading to hepatocellular carcinoma.

• Merrick BA, Phadke DP, Auerbach SS, Mav D, Stiegelmeyer SM, et al. (2013) RNA-Seq Profiling Reveals Novel Hepatic Gene Expression Pattern in Aflatoxin B1 Treated Rats. PLoS ONE 8(4),  e61768. [article]

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The methanogenic archaeon Methanopyrus kandleri grows near the upper temperature limit for life. Genome analyses revealed strategies to adapt to these harsh conditions and elucidated a unique transfer RNA (tRNA) C-to-U editing mechanism at base 8 for 30 different tRNA species.

Here, RNA-Seq deep sequencing methodology was combined with computational analyses to characterize the small RNome of this hyperthermophilic organism and to obtain insights into the RNA metabolism at extreme temperatures. A large number of 132 small RNAs were identified that guide RNA modifications, which are expected to stabilize structured RNA molecules. The C/D box guide RNAs were shown to exist as circular RNA molecules. In addition, clustered regularly interspaced short palindromic repeats RNA processing and potential regulatory RNAs were identified. Finally, the identification of tRNA precursors before and after the unique C8-to-U8 editing activity enabled the determination of the order of tRNA processing events with termini truncation preceding intron removal. This order of tRNA maturation follows the compartmentalized tRNA processing order found in Eukaryotes and suggests its conservation during evolution.

• Su AAH, Tripp V, Randau L. (2013) RNA-Seq analyses reveal the order of tRNA processing events and the maturation of C/D box and CRISPR RNAs in the hyperthermophile Methanopyrus kandleri NAR [Epub ahead of print]. [article]

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The mosquito gut accommodates dynamic microbial communities across different stages of the insect’s life cycle. Characterization of the genetic capacity and functionality of the gut community will provide insight into the effects of gut microbiota on mosquito life traits.

Metagenomic RNA-Seq has become an important tool to analyze transcriptomes from various microbes present in a microbial community. Messenger RNA usually comprises only 1-3% of total RNA, while rRNA constitutes approximately 90%. It is challenging to enrich messenger RNA from a metagenomic microbial RNA sample because most prokaryotic mRNA species lack stable poly(A) tails. This prevents oligo d(T) mediated mRNA isolation.

Here, researchers from New Mexico State University describe a protocol that employs sample derived rRNA capture probes to remove rRNA from a metagenomic total RNA sample. To begin, both mosquito and microbial small and large subunit rRNA fragments are amplified from a metagenomic community DNA sample. Then, the community specific biotinylated antisense ribosomal RNA probes are synthesized in vitro using T7 RNA polymerase. The biotinylated rRNA probes are hybridized to the total RNA. The hybrids are captured by streptavidin-coated beads and removed from the total RNA. This subtraction-based protocol efficiently removes both mosquito and microbial rRNA from the total RNA sample. The mRNA enriched sample is further processed for RNA amplification and RNA-Seq.

• Kukutla P, Steritz M, Xu J. (2013) Depletion of Ribosomal RNA for Mosquito Gut Metagenomic RNA-seq. J Vis Exp (74). [abstract]

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Bdellovibrio bacteriovorus is an obligate predator of bacteria ubiquitously found in the environment. Its life cycle is composed of two essential phases: a free-living, non-replicative, fast swimming attack phase (AP) wherein the predator searches for prey; and a non-motile, actively dividing growth phase (GP) in which it consumes the prey. The molecular regulatory mechanisms governing the switch between AP and GP are largely unknown.

Researchers at the Weizmann Institute of Science, Israel used RNA-Seq to generate a single-base-resolution map of the Bdellovibrio transcriptome in AP and GP, revealing a specific “AP” transcriptional program, which is largely mutually exclusive of the GP program. Based on the expression map, most genes in the Bdellovibrio genome are classified as “AP only” or “GP only”. They experimentally generated a genome-wide map of 140 AP promoters, controlling the majority of AP-specific genes. This revealed a common sigma-like DNA binding site highly similar to the E. coli flagellar genes regulator sigma28 (FliA). Further analyses suggest that FliA has evolved to become a global AP regulator in Bdellovibrio. These results also reveal a non-coding RNA that is massively expressed in AP. This ncRNA contains a c-di-GMP riboswitch. The researchers suggest it functions as an intracellular reservoir for c-di-GMP, playing a role in the rapid switch from AP to GP.

• Karunker I, Rotem O, Dori-Bachash M, Jurkevitch E, Sorek R. (2013) A Global Transcriptional Switch between the Attack and Growth Forms of Bdellovibrio bacteriovorus. PLoS One 8(4), e61850. [article]

Breast cancer transcriptome acquires a myriad of regulation changes, and splicing is critical for the cell to “tailor-make” specific functional transcripts. Researchers at The George Washington University systematically revealed splicing signatures of the three most common types of breast tumors using RNA sequencing: TNBC, non-TNBC and HER2-positive breast cancer.

1. Discovered subtype specific differentially spliced genes and splice isoforms not previously recognized in human transcriptome.
2. Demonstrated that exon skip and intron retention are predominant splice events in breast cancer.
3. Found that differential expression of primary transcripts and promoter switching are significantly deregulated in breast cancer compared to normal breast.
4. Validated the presence of novel hybrid isoforms of critical molecules like CDK4, LARP1, ADD3, and PHLPP2.

This study provides the first comprehensive portrait of transcriptional and splicing signatures specific to breast cancer sub-types, as well as previously unknown transcripts that prompt the need for complete annotation of tissue and disease specific transcriptome.

• Eswaran J, Horvath A, Godbole S, Reddy SD, Mudvari P, Ohshiro K, Cyanam D, Nair S, Fuqua SA, Polyak K, Florea LD, Kumar R. (2013) RNA sequencing of cancer reveals novel splicing alterations. Sci Rep 3, 1689. [article]

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RNA transcripts are generally classified into polyA-plus and polyA-minus subgroups due to the presence or absence of a polyA tail at the 3′ end. Even though a number of physiologically and pathologically important polyA-minus RNAs have been recently identified, a systematic analysis of the expression and function of these transcripts in adipogenesis is still elusive. To study the potential function of the polyA-minus RNAs in adipogenesis, a dynamic expressional profiling was performed in the induced differentiation of 3T3-L1 cells. In addition to identifying thousands of novel intergenic transcripts, differentiation-synchronized expression was characterized for many of them. Among these, several large intergenic transcripts were found to be upregulated by more than 19-fold during differentiation. Further study demonstrated a fat tissue-specific expression pattern for these regions and identified an adipogenesis-associated long non-coding RNA. Collectively, these lines of evidence contribute to the characterization of a super-long intergenic transcript functioning in adipogenesis.

• Yi F, Yang F, Liu X, Chen H, Ji T, Jiang L, Wang X, Yang Z, Zhang LH, Ding X, Liang Z, Du Q. (2013) RNA-seq identified a super-long intergenic transcript functioning in adipogenesis. RNA Biol [Epub ahead of print]. [article]

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• SEQanswers – RNA Sequencing

  • standard of clean data May 21, 2013
    Hi all I recently got my prokaryotes RNA-seq data report back. the standard filter steps of the raw data set by our local sequencing center is as... […]
    Pengfei Liu
  • Problem with cummeRbund diffData() May 20, 2013
    Hi all, I'm running Tophat/cufflinks/cuffdiff for differential gene expression and analysis with cummeRbund (v 2.0.0). I'm having an issue with... […]
    Enrique Zudaire
  • How to increase rowsize in heatmap? May 16, 2013
    Hi, I am a complete newbie to all things cummeRbund and am currently fighting with generating readable heatmaps. When I use ... […]
    Mags
  • novoalign mapping May 15, 2013
    Hi, I want to use novoalign to map reads - allowing up to 15 mismatches for 100 bp paired-end reads I am new to novoalign(went through the... […]
    abh
  • Design of expt across multiple lanes May 15, 2013
    Hi, I am performing an RNA-seq experiment to look at differential expression. The design is as follows: 2 populations x 3 biological... […]
    jbono
  • RNA kinds expected in RNA-seq results May 15, 2013
    Hi, We use RNA isolation and library preparation protocols which capture polyadenylated RNA. My question is what kinds of RNA can we expect to... […]
    Kocur

• Biostar – RNA-Seq

  • How do TopHat options -g , --supress-hits, and Bowtie options interplay?
    Hi, I am currently using TopHat2 to map RNA-seq runs. I think there have been some changes pertaining the -g option. Does anyone know how it works now? I used to think that setting -g would look for n alignments for a given read, report them [if top-scoring] and discard those reads that had more than g [top scoring] alignments. Now, the description sounds mo […]
  • What happened to -k in TopHat for multiple-mapping reads?
    Selecting -g n in tophat does not discard reads mapping more than n, but instead only reports n alignments for those out all all their TOP scoring alignments. I think there used to be an option -k that would allow one to discard reads that topped x alignments -- whatever happened to that? I only see -g in the tophat 2 manual, no reporting options like before […]
  • Does tophat use the library-type information for mapping, or just for the XS flag?
    When I specify library-type to TopHat, i.e., first-strand, second-strand, unstranded, TopHat appends a value + or - to the XS:A tag, which is useful for subsequent analyses, such as annotation. However, does this information influence the "mappability" of reads, or is this unaffected? My guess is that the information will be considered for mapping […]
  • Purpose of Y-shaped adapters in Illumina Sequencing?
    Hi all, Y adapters different sequences to be annealed to the 5' and 3' ends of each molecule in a library. The arms of the Y are unique, and the middle part, connected to the DNA fragment, is complementary. What are the advantages of this? My take of this over having fully-complementary adapters (ADAPTER1 - - - - - ADAPTER1) is that: -Upon primer a […]
  • Cell Type composition in a tissue based on gene marker expression
    I am not sure if the following would even make sense.... Tissues are composed of composite cell types, and often there are studies such as microarray/NGS where we perform a collective sampling of cells from these tissues. Information about the composition (say percentage of cell type) is not taken into consideration. In some case (such as brain/cancer), ther […]
  • Which SNP caller / method to use after aligning RNA-seq with TopHat
    Which SNP caller / method can / should I use after aligning RNA-seq data with TopHat? For genomic data I use GATK, but supposedly it is not just as easy as running GATK on the TopHat RNA-seq data. The team from Broad has no information / documentation on how to use GATK for RNA-seq data. I don't have any variants yet from DNA re-sequencing. […]