Genome-wide analysis and expression profiling suggest diverse roles of GH3 genes during development and abiotic stress responses in legumes

Growth hormone auxin regulates various cellular processes by altering the expression of diverse genes in plants. Among various auxin-responsive genes, GH3 genes maintain endogenous auxin homeostasis by conjugating excess of auxin with amino acids. GH3 genes have been characterized in many plant species, but not in legumes. In the present work, we identified members of GH3 gene family and analyzed their chromosomal distribution, gene structure, gene duplication and phylogenetic analysis in different legumes, including chickpea, soybean, Medicago, and Lotus. A comprehensive expression analysis in different vegetative and reproductive tissues/stages revealed that many of GH3 genes were expressed in a tissue-specific manner. Notably, chickpea CaGH3-3, soybean GmGH3-8 and -25, and Lotus LjGH3-4, -5, -9 and -18 genes were up-regulated in root, indicating their putative role in root development. In addition, chickpea CaGH3-1 and -7, and Medicago MtGH3-7, -8, and -9 were found to be highly induced under drought and/or salt stresses, suggesting their role in abiotic stress responses. We also observed the examples of differential expression pattern of duplicated GH3 genes in soybean, indicating their functional diversification. Furthermore, analyses of three-dimensional structures, active site residues and ligand preferences provided molecular insights into function of GH3 genes in legumes. The analysis presented here would help in investigation of precise function of GH3 genes in legumes during development and stress conditions.

Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis

BACKGROUND

Experimental designs that take advantage of high-throughput sequencing to generate datasets include RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), sequencing of 16S rRNA gene fragments, metagenomic analysis and selective growth experiments. In each case the underlying data are similar and are composed of counts of sequencing reads mapped to a large number of features in each sample. Despite this underlying similarity, the data analysis methods used for these experimental designs are all different, and do not translate across experiments. Alternative methods have been developed in the physical and geological sciences that treat similar data as compositions. Compositional data analysis methods transform the data to relative abundances with the result that the analyses are more robust and reproducible.

RESULTS

Data from an in vitro selective growth experiment, an RNA-seq experiment and the Human Microbiome Project 16S rRNA gene abundance dataset were examined by ALDEx2, a compositional data analysis tool that uses Bayesian methods to infer technical and statistical error. The ALDEx2 approach is shown to be suitable for all three types of data: it correctly identifies both the direction and differential abundance of features in the differential growth experiment, it identifies a substantially similar set of differentially expressed genes in the RNA-seq dataset as the leading tools and it identifies as differential the taxa that distinguish the tongue dorsum and buccal mucosa in the Human Microbiome Project dataset. The design of ALDEx2 reduces the number of false positive identifications that result from datasets composed of many features in few samples.

CONCLUSION

Statistical analysis of high-throughput sequencing datasets composed of per feature counts showed that the ALDEx2 R package is a simple and robust tool, which can be applied to RNA-seq, 16S rRNA gene sequencing and differential growth datasets, and by extension to other techniques that use a similar approach.

Genome-wide transcriptional sequencing identifies novel mutations in metabolic genes in human hepatocellular carcinoma

We report on next-generation transcriptome sequencing results of three human hepatocellular carcinoma tumor/tumor-adjacent pairs. This analysis robustly examined ∼12,000 genes for both expression differences and molecular alterations. We observed 4,513 and 1,182 genes demonstrating 2-fold or greater increase or decrease in expression relative to their normal, respectively. Network analysis of expression data identified the Aurora B signaling, FOXM1 transcription factor network and Wnt signaling pathways pairs being altered in HCC. We validated as differential gene expression findings in a large data set containing of 434 liver normal/tumor sample pairs. In addition to known driver mutations in TP53 and CTNNB1, our mutation analysis identified non-synonymous mutations in genes implicated in metabolic diseases, i.e. diabetes and obesity: IRS1, HMGCS1, ATP8B1, PRMT6 and CLU, suggesting a common molecular etiology for HCC of alternative pathogenic origin.

Changes in transcript abundance for cuticular proteins and other genes three hours after a blood meal in Anopheles gambiae

Numerous studies have examined changes in transcript levels after Anopheles gambiae takes a blood meal. Marinotti et al. (2006) used microarrays and reported massive changes in transcript levels 3 h after feeding (BF3h) compared to non-blood fed (NBF). We were intrigued by the number of transcripts for structural cuticular proteins (CPs) that showed such major differences in levels and employed paired-end (50 bp) RNA-seq technology to compare whole body transcriptomes from 5-day-old females NBF and BF3h. We detected transcripts for the majority of CPs (164/243) but levels of only 12 were significantly altered by the blood meal. While relative transcript levels of NBF females were somewhat similar to the microarray data, there were major differences in BF3h animals, resulting in levels of many transcripts, both for CPs and other genes changing in the opposite direction. We compared our data also to other studies done with both microarrays and RNA-seq. Findings were consistent that a small number of CP genes have transcripts that persist even in 5-day-old adults. Some of these transcripts showed diurnal rhythms (Rund et al., 2013; Rinker et al., 2013). In situ hybridization revealed that transcripts for several of these CP genes were found exclusively or predominantly in the eye. Transcripts other than for CPs that changed in response to blood-feeding were predominantly expressed in midgut and Malpighian tubules. Even in these tissues, genes responsible for proteins with similar functions, such as immunity or digestion, responded differently, with transcript levels for some rising and others falling. These data demonstrate that genes coding for some CPs are dynamic in expression even in adults and that the response to a blood meal is rapid and precisely orchestrated.

Introduction to sequencing the brain transcriptome

High-throughput next-generation sequencing is now entering its second decade. However, it was not until 2008 that the first report of sequencing the brain transcriptome appeared (Mortazavi, Williams, Mccue, Schaeffer, & Wold, 2008). These authors compared short-read RNA-Seq data for mouse whole brain with microarray results for the same sample and noted both the advantages and disadvantages of the RNA-Seq approach. While RNA-Seq provided exon level resolution, the majority of the reads were provided by a small proportion of highly expressed genes and the data analysis was exceedingly complex. Over the past 6 years, there have been substantial improvements in both RNA-Seq technology and data analysis. This volume contains 11 chapters that detail various aspects of sequencing the brain transcriptome. Some of the chapters are very methods driven, while others focus on the use of RNA-Seq to study such diverse areas as development, schizophrenia, and drug abuse. This chapter briefly reviews the transition from microarrays to RNA-Seq as the preferred method for analyzing the brain transcriptome. Compared with microarrays, RNA-Seq has a greater dynamic range, detects both coding and noncoding RNAs, is superior for gene network construction, detects alternative spliced transcripts, and can be used to extract genotype information, e.g., nonsynonymous coding single nucleotide polymorphisms. RNA-Seq embraces the complexity of the brain transcriptome and provides a mechanism to understand the underlying regulatory code; the potential to inform the brain-behavior-disease relationships is substantial.

Separate enrichment analysis of pathways for up- and downregulated genes

Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

Comparative transcriptomics of early meiosis in Arabidopsis and maize

Though sexually reproductive plants share the same principle and most processes in meiosis, there are distinct features detectable. To address the similarities and differences of early meiosis transcriptomes from the dicot model system Arabidopsis and monocot model system maize, we performed comparative analyses of RNA-seq data of isolated meiocytes, anthers and seedlings from both species separately and via orthologous genes. Overall gene expression showed similarities, such as an increased number of reads mapping to unannotated features, and differences, such as the amount of differentially expressed genes. We detected major similarities and differences in functional annotations of genes up-regulated in meiocytes, which point to conserved features as well as unique features. Transcriptional regulation seems to be quite similar in Arabidopsis and maize, and we could reveal known and novel transcription factors and cis-regulatory elements acting in early meiosis. Taken together, meiosis between Arabidopsis and maize is conserved in many ways, but displays key distinctions that lie in the patterns of gene expression.

The myostatin gene of Mytilus chilensis evidences a high level of polymorphism and ubiquitous transcript expression

Myostatin (MSTN) is a protein of the Transforming Growth Factor-β (TGF-β) superfamily and plays a crucial role in muscular development for higher vertebrates. However, its biological function in marine invertebrates remains undiscovered. This study characterizes the full-length sequence of the Mytilus chilensis myostatin gene (Mc-MSTN). Furthermore, tissue transcription patterns and putative single nucleotide polymorphisms (SNPs) were also identified. The Mc-MSTN cDNA sequence showed 3528 base pairs (bp), consisting of 161 bp of 5' UTR, 2,110 bp of 3' UTR, and an open reading frame of 1,257 bp encoding for 418 amino acids and with an RXXR proteolytic site and nine cysteine-conserved residues. Gene transcription analysis revealed that the Mc-MSTN has ubiquitous expression among several tissues, with higher expression in the gonads and mantle than in the digestive gland, gills, and hemolymph. Furthermore, high levels of polymorphisms were detected (28 SNPs in 3'-UTR and 9 SNPs in the coding region). Two SNPs were non-synonymous and involved amino acid changes between Glu/Asp and Thr/Ile. Until now, the MSTN gene has been mainly related to muscle growth in marine bivalves. However, the present study suggests a putative biological function not entirely associated to muscle tissue and contributes molecular evidence to the current debate about the function of the MSTN gene in marine invertebrates.

Transcriptome dynamics and diversity in the early zebrafish embryo

Recent years advances in high-throughput sequencing have improved our understanding of how transcripts regulate early vertebrate development. Here, we review the transcriptome dynamics and diversity during early stages of zebrafish embryogenesis. Transcriptome dynamics is characterized by different patterns of mRNA degradation, activation of dormant transcripts and onset of transcription. Several studies have shown a striking diversity of both coding and non-coding transcripts. However, in the aftermath of this immense increase in data, functional studies of both protein-coding and non-coding transcripts are lagging behind. We anticipate that the forthcoming years will see studies relying on different high-throughput sequencing technologies and genomic tools developed for zebrafish embryos to further pin down yet un-annotated transcript-function relationships.

Tumor resistance to anti-VEGF therapy through up-regulation of VEGF-C expression

Increasing evidence has indicated that prolonged use of anti-VEGF (vascular endothelial growth factor) agents for cancer therapy promotes tumor resistance. To gain insight into the molecular mechanism underlying resistance to anti-VEGF therapy, we developed a mouse Lewis lung carcinoma (LLC) cell line that is resistant to treatment with a potent VEGF inhibitor, VEGF-Trap, through repeated in vivo selection. We compared the transcriptome profiles of resistant and non-resistant tumor cells using RNA-seq analysis. VEGF-C was significantly up-regulated in resistant tumor cells, as determined by quantitative real-time PCR and immunohistochemical analyses. Inhibition of VEGF-C in resistant cells suppressed endothelial cell migration in vitro and partially restored sensitivity to VEGF-Trap treatment in vivo. Our findings indicate that tumors may develop resistance to anti-VEGF therapy by activating the VEGF-C pathway.

Comprehensive transcriptome profiling of squamous cell carcinoma of horn in Bos indicus

Squamous cell carcinoma (SCC) of horn is frequently observed in Bos indicus affecting 1% of cattle population and accounting 83.34% of total tumours found. The transcriptome profile of horn cancer (HC) tissue and the matched normal (HN) tissue were analysed by RNA-seq using Roche 454 sequencing. A total of 1 504 900 reads comprising of 612 MB data were used to identify differentially expressed genes using CLC Genomic Workbench. These include up-regulation of KRT6A, KRT6B, KRT6C, KRT14, SFN, KRT84, PI3, COL17A1, ANLN, SERPINB5 and down-regulation of BOLA, SCGB1A1, CXCL17, KRT19, BPIFB1, NR4A1 and TFF3 in HC, which are involved in regulation of gene transcription, cell proliferation, apoptosis, cell survival and metabolic pathways. The qPCR analysis of several targets suggested concordance of gene expression profile with RNA-seq analysis. The present findings would provide basis for further screening of genes and identification of markers for early diagnosis and therapeutic intervention of HC.

Comparison of software packages for detecting differential expression in RNA-seq studies

RNA-sequencing (RNA-seq) has rapidly become a popular tool to characterize transcriptomes. A fundamental research problem in many RNA-seq studies is the identification of reliable molecular markers that show differential expression between distinct sample groups. Together with the growing popularity of RNA-seq, a number of data analysis methods and pipelines have already been developed for this task. Currently, however, there is no clear consensus about the best practices yet, which makes the choice of an appropriate method a daunting task especially for a basic user without a strong statistical or computational background. To assist the choice, we perform here a systematic comparison of eight widely used software packages and pipelines for detecting differential expression between sample groups in a practical research setting and provide general guidelines for choosing a robust pipeline. In general, our results demonstrate how the data analysis tool utilized can markedly affect the outcome of the data analysis, highlighting the importance of this choice.

Identification of immune-related SNPs in the transcriptome of Mytilus chilensis through high-throughput sequencing

Single nucleotide polymorphisms (SNPs) identified in coding regions represent a useful tool for understanding the immune response against pathogens and stressful environmental conditions. In this study, a SNPs database was generated from transcripts involved in the innate immune response of the mussel Mytilus chilensis. The SNPs were identified through hemocytes transcriptome sequencing from 18 individuals, and SNPs mining was performed in 225,336 contigs, yielding 20,306 polymorphisms associated to immune-related genes. Classification of identified SNPs was based on different pathways of the immune response for Mytilus sp. A total of 28 SNPs were identified in the Toll-like receptor pathway and included 5 non-synonymous polymorphisms; 19 SNPs were identified in the apoptosis pathway and included 3 non-synonymous polymorphisms; 35 SNPs were identified in the Ubiquitin-mediated proteolysis pathway and included 4 non-synonymous variants; and 54 SNPs involved in other molecular functions related to the immune response, such as molecular chaperones, antimicrobial peptides, and genes that interacts with marine toxins were also identified. The molecular markers identified in this work could be useful for novel studies, such as those related to associations between high-resolution molecular markers and functional response to pathogen agents.

A comprehensive analysis of the human placenta transcriptome

As the conduit for nutrients and growth signals, the placenta is critical to establishing an environment sufficient for fetal growth and development. To better understand the mechanisms regulating placental development and gene expression, we characterized the transcriptome of term placenta from 20 healthy women with uncomplicated pregnancies using RNA-seq. To identify genes that were highly expressed and unique to the placenta we compared placental RNA-seq data to data from 7 other tissues (adipose, breast, hear, kidney, liver, lung, and smooth muscle) and identified several genes novel to placental biology (QSOX1, DLG5, and SEMA7A). Semi-quantitative RT-PCR confirmed the RNA-seq results and immunohistochemistry indicated these proteins were highly expressed in the placental syncytium. Additionally, we mined our RNA-seq data to map the relative expression of key developmental gene families (Fox, Sox, Gata, Tead, and Wnt) within the placenta. We identified FOXO4, GATA3, and WNT7A to be amongst the highest expressed members of these families. Overall, these findings provide a new reference for understanding of placental transcriptome and can aid in the identification of novel pathways regulating placenta physiology that may be dysregulated in placental disease.

Trascriptome analysis of the Pacific white shrimp Litopenaeus vannamei exposed to nitrite by RNA-seq

In the present study, transcriptome of nitrite-exposed Litopenaeus vannamei was performed using a newly developed high-throughput sequencing technology (Illumina RNA-seq). As many as 42,336 unigenes were generated with 561 bp of average length and 736 bp of unigene N50 after filtering and assembly. These unigenes from the de novo assembly were further annotated using BLAST and BLAST2GO softwares. A total of 23,532 unigenes were unambiguous alignments to the reference when BLAST against non-redundant protein sequence (Nr), non-redundant nucleotide (Nt), Swiss-Prot, Gene Ontology database (GO), Clusters of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases available at NCBI. Numerous candidate genes associated with immune response, detoxification, apoptosis pathway were identified. Ten candidate genes related to immune responses and apoptosis were selected for validating the results of assembly and annotation by real-time quantitative PCR. Results revealed that the expressions of all these ten genes were up-regulated after nitrite exposure. Combining to our previous study, we speculate that all these selected genes may be involved in the response to nitrite stress. The study shows a systematic overview of the transcriptome analysis in L. vannamei, and provides valuable gene information for studying molecular mechanisms under nitrite exposure.

Functional Immunomics of the Squash Bug, Anasa tristis (De Geer) (Heteroptera: Coreidae)

The Squash bug, Anasa tristis (De Geer), is a major piercing/sucking pest of cucurbits, causing extensive damage to plants and fruits, and transmitting phytopathogens. No genomic resources to facilitate field and laboratory studies of this pest were available; therefore the first de novo exome for this destructive pest was assembled. RNA was extracted from insects challenged with bacterial and fungal immunoelicitors, insects fed on different cucurbit species, and insects from all life stages from egg to adult. All treatments and replicates were separately barcoded for subsequent analyses, then pooled for sequencing in a single lane using the Illumina HiSeq2000 platform. Over 211 million 100-base tags generated in this manner were trimmed, filtered, and cleaned, then assembled into a de novo reference transcriptome using the Broad Institute Trinity assembly algorithm. The assembly was annotated using NCBIx NR, BLAST2GO, KEGG and other databases. Of the >130,000 total assemblies 37,327 were annotated identifying the sequences of candidate gene silencing targets from immune, endocrine, reproductive, cuticle, and other physiological systems. Expression profiling of the adult immune response was accomplished by aligning the 100-base tags from each biological replicate from each treatment and controls to the annotated reference assembly of the A. tristis transcriptome.

Gene expression profile analysis of Ligon lintless-1 (Li1) mutant reveals important genes and pathways in cotton leaf and fiber development

Ligon lintless-1 (Li1) is a monogenic dominant mutant of Gossypium hirsutum (upland cotton) with a phenotype of impaired vegetative growth and short lint fibers. Despite years of research involving genetic mapping and gene expression profile analysis of Li1 mutant ovule tissues, the gene remains uncloned and the underlying pathway of cotton fiber elongation is still unclear. In this study, we report the whole genome-level deep-sequencing analysis of leaf tissues of the Li1 mutant. Differentially expressed genes in leaf tissues of mutant versus wild-type (WT) plants are identified, and the underlying pathways and potential genes that control leaf and fiber development are inferred. The results show that transcription factors AS2, YABBY5, and KANDI-like are significantly differentially expressed in mutant tissues compared with WT ones. Interestingly, several fiber development-related genes are found in the downregulated gene list of the mutant leaf transcriptome. These genes include heat shock protein family, cytoskeleton arrangement, cell wall synthesis, energy, H2O2 metabolism-related genes, and WRKY transcription factors. This finding suggests that the genes are involved in leaf morphology determination and fiber elongation. The expression data are also compared with the previously published microarray data of Li1 ovule tissues. Comparative analysis of the ovule transcriptomes of Li1 and WT reveals that a number of pathways important for fiber elongation are enriched in the downregulated gene list at different fiber development stages (0, 6, 9, 12, 15, 18dpa). Differentially expressed genes identified in both leaf and fiber samples are aligned with cotton whole genome sequences and combined with the genetic fine mapping results to identify a list of candidate genes for Li1.

Early T helper cell programming of gene expression in human

Molecular mechanisms guiding naïve T helper cell differentiation into functionally specified effector cells are intensively studied. The rapidly growing knowledge is mainly achieved by using mouse cells or disease models. Comparatively exiguous data is gathered from human primary cells although they provide the "ultimate model" for immunology in man, have been exploited in many original studies paving the way for the field, and can be analyzed more easily than ever with the help of modern technology and methods. As usage of mouse models is unavoidable in translational research, parallel human and mouse studies should be performed to assure the relevancy of the hypothesis created during the basic research. In this review, we give an overview on the status of the studies conducted with human primary cells aiming at elucidating the mechanisms instructing the priming of T helper cell subtypes. The special emphasis is given to the recent high-throughput studies. In addition, by comparing the human and mouse studies we intend to point out the regulatory mechanisms and questions which are lacking examination with human primary cells.

Mapping genetic modifiers of survival in a mouse model of Dravet syndrome

Epilepsy is a common neurological disorder affecting approximately 1% of the population. Mutations in voltage-gated sodium channels are responsible for several monogenic epilepsy syndromes. More than 800 mutations in the voltage-gated sodium channel SCN1A have been reported in patients with generalized epilepsy with febrile seizures plus and Dravet syndrome. Heterozygous loss-of-function mutations in SCN1A result in Dravet syndrome, a severe infant-onset epileptic encephalopathy characterized by intractable seizures, developmental delays and increased mortality. A common feature of monogenic epilepsies is variable expressivity among individuals with the same mutation, suggesting that genetic modifiers may influence clinical severity. Mice with heterozygous deletion of Scn1a (Scn1a(+/-) ) model a number of Dravet syndrome features, including spontaneous seizures and premature lethality. Phenotype severity in Scn1a(+/-) mice is strongly dependent on strain background. On the 129S6/SvEvTac strain Scn1a(+/-) mice exhibit no overt phenotype, whereas on the (C57BL/6J × 129S6/SvEvTac)F1 strain Scn1a(+/-) mice exhibit spontaneous seizures and early lethality. To systematically identify loci that influence premature lethality in Scn1a(+/-) mice, we performed genome scans on reciprocal backcrosses. Quantitative trait locus mapping revealed modifier loci on mouse chromosomes 5, 7, 8 and 11. RNA-seq analysis of strain-dependent gene expression, regulation and coding sequence variation provided a list of potential functional candidate genes at each locus. Identification of modifier genes that influence survival in Scn1a(+/-) mice will improve our understanding of the pathophysiology of Dravet syndrome and may suggest novel therapeutic strategies for improved treatment of human patients.

Grouped False-Discovery Rate for Removing the Gene-Set-Level Bias of RNA-seq

In recent years, RNA-seq has become a very competitive alternative to microarrays. In RNA-seq experiments, the expected read count for a gene is proportional to its expression level multiplied by its transcript length. Even when two genes are expressed at the same level, differences in length will yield differing numbers of total reads. The characteristics of these RNA-seq experiments create a gene-level bias such that the proportion of significantly differentially expressed genes increases with the transcript length, whereas such bias is not present in microarray data. Gene-set analysis seeks to identify the gene sets that are enriched in the list of the identified significant genes. In the gene-set analysis of RNA-seq, the gene-level bias subsequently yields the gene-set-level bias that a gene set with genes of long length will be more likely to show up as enriched than will a gene set with genes of shorter length. Because gene expression is not related to its transcript length, any gene set containing long genes is not of biologically greater interest than gene sets with shorter genes. Accordingly the gene-set-level bias should be removed to accurately calculate the statistical significance of each gene-set enrichment in the RNA-seq.

We present a new gene set analysis method of RNA-seq, called FDRseq, which can accurately calculate the statistical significance of a gene-set enrichment score by the grouped false-discovery rate. Numerical examples indicated that FDRseq is appropriate for controlling the transcript length bias in the gene-set analysis of RNA-seq data. To implement FDRseq, we developed the R program, which can be downloaded at no cost from http://home.mju.ac.kr/home/index.action?siteId=tyang.

Mutually exclusive signaling signatures define the hepatic and pancreatic progenitor cell lineage divergence

A key question in stem cell biology is how distinct cell types arise from common multipotent progenitor cells. It is unknown how liver and pancreas cells diverge from a common endoderm progenitor population and adopt specific fates. Using RNA-seq, Spagnoli and colleagues define the gene expression programs of liver and pancreas progenitors and identify the noncanonical Wnt pathway as a potential developmental regulator of this fate decision. Furthermore, this study provides a framework for lineage-reprogramming strategies to convert adult hepatic cells into pancreatic cells.

Understanding how distinct cell types arise from multipotent progenitor cells is a major quest in stem cell biology. The liver and pancreas share many aspects of their early development and possibly originate from a common progenitor. However, how liver and pancreas cells diverge from a common endoderm progenitor population and adopt specific fates remains elusive. Using RNA sequencing (RNA-seq), we defined the molecular identity of liver and pancreas progenitors that were isolated from the mouse embryo at two time points, spanning the period when the lineage decision is made. The integration of temporal and spatial gene expression profiles unveiled mutually exclusive signaling signatures in hepatic and pancreatic progenitors. Importantly, we identified the noncanonical Wnt pathway as a potential developmental regulator of this fate decision and capable of inducing the pancreas program in endoderm and liver cells. Our study offers an unprecedented view of gene expression programs in liver and pancreas progenitors and forms the basis for formulating lineage-reprogramming strategies to convert adult hepatic cells into pancreatic cells.

Comparison of microarrays and RNA-seq for gene expression analyses of dose-response experiments

Relative to microarrays, RNA-seq has been reported to offer higher precision estimates of transcript abundance, a greater dynamic range, and detection of novel transcripts. However, previous comparisons of the 2 technologies have not covered dose-response experiments that are relevant to toxicology. Male F344 rats were exposed for 13 weeks to 5 doses of bromobenzene, and liver gene expression was measured using both microarrays and RNA-seq. Multiple normalization methods were evaluated for each technology, and gene expression changes were statistically analyzed using both analysis of variance and benchmark dose (BMD). Fold-change values were highly correlated between the 2 technologies, whereas the -log p values showed lower correlation. RNA-seq detected fewer statistically significant genes at lower doses, but more significant genes based on fold change except when a negative binomial transformation was applied. Overlap in genes significant by both p value and fold change was approximately 30%-40%. Random sampling of the RNA-seq data showed an equivalent number of differentially expressed genes compared with microarrays at ~5 million reads. Quantitative RT-PCR of differentially expressed genes uniquely identified by each technology showed a high degree of confirmation when both fold change and p value were considered. The mean dose-response expression of each gene was highly correlated between technologies, whereas estimates of sample variability and gene-based BMD values showed lower correlation. Differences in BMD estimates and statistical significance may be due, in part, to differences in the dynamic range of each technology and the degree to which normalization corrects genes at either end of the scale.

RNA-sequencing reveals previously unannotated protein- and microRNA-coding genes expressed in aleurone cells of rice seeds

The rice genome annotation has been greatly improved in recent years, largely due to the availability of full length cDNA sequences derived from many tissues. Among those yet to be studied is the aleurone layer, which produces hydrolases for mobilization of seed storage reserves during seed germination and post germination growth. Herein, we report transcriptomes of aleurone cells treated with the hormones abscisic acid, gibberellic acid, or both. Using a comprehensive approach, we identified hundreds of novel genes. To minimize the number of false positives, only transcripts that did not overlap with existing annotations, had a high level of expression, and showed a high level of uniqueness within the rice genome were considered to be novel genes. This approach led to the identification of 553 novel genes that encode proteins and/or microRNAs. The transcriptome data reported here will help to further improve the annotation of the rice genome.

Using machine learning and high-throughput RNA sequencing to classify the precursors of small non-coding RNAs

Recent advances in high-throughput sequencing allow researchers to examine the transcriptome in more detail than ever before. Using a method known as high-throughput small RNA-sequencing, we can now profile the expression of small regulatory RNAs such as microRNAs and small interfering RNAs (siRNAs) with a great deal of sensitivity. However, there are many other types of small RNAs (<50nt) present in the cell, including fragments derived from snoRNAs (small nucleolar RNAs), snRNAs (small nuclear RNAs), scRNAs (small cytoplasmic RNAs), tRNAs (transfer RNAs), and transposon-derived RNAs. Here, we present a user's guide for CoRAL (Classification of RNAs by Analysis of Length), a computational method for discriminating between different classes of RNA using high-throughput small RNA-sequencing data. Not only can CoRAL distinguish between RNA classes with high accuracy, but it also uses features that are relevant to small RNA biogenesis pathways. By doing so, CoRAL can give biologists a glimpse into the characteristics of different RNA processing pathways and how these might differ between tissue types, biological conditions, or even different species. CoRAL is available at http://wanglab.pcbi.upenn.edu/coral/.

Progression of 'OMICS' methodologies for understanding the pathogenicity of Corynebacterium pseudotuberculosis: the Brazilian experience

Since the first successful attempt at sequencing the Corynebacterium pseudotuberculosis genome, large amounts of genomic, transcriptomic and proteomic data have been generated. C. pseudotuberculosis is an interesting bacterium due to its great zoonotic potential and because it causes considerable economic losses worldwide. Furthermore, different strains of C. pseudotuberculosis are capable of causing various diseases in different hosts. Currently, we seek information about the phylogenetic relationships between different strains of C. pseudotuberculosis isolates from different hosts across the world and to employ these data to develop tools to diagnose and eradicate the diseases these strains cause. In this review, we present the latest findings on C. pseudotuberculosis that have been obtained with the most advanced techniques for sequencing and genomic organization. We also discuss the development of in silico tools for processing these data to prompt a better understanding of this pathogen.

Profiling the molecular mechanism of fullerene cytotoxicity on tumor cells by RNA-seq

The interest on functionalized fullerenes in the field of nanomedicine has seen a significant increase in the past decade. However, the different methods employed to increase C60 solubility profoundly influence the physicochemical properties and the toxicological effects of these compounds, thus complicating the evaluation of their toxicity and potential therapeutic use. Here we report a whole-transcriptome RNA-seq analysis assessing the effect of two fullerenes (1 and 2) on gene expression in the human MCF7 cell line. Although these two compounds had previously been characterized by in vitro studies as having a cytotoxic and null effect respectively, to date the mechanisms at the basis of this different behavior and, more in general, at the basis of the effect of most fullerene derivatives in living cells are still completely unknown. Our data evidence that: (a) fullerene 2 caused a significant, time-dependent alteration of gene expression, whereas 1 only had a negligible effect; (b) the biological processes mostly influenced over the 48h experimental time course were transcription, protein synthesis, cell cycle progression and cell adhesion; (c) the gene expression signature of 2-treated cells was strikingly similar to those induced by selective inhibitors of mTOR signaling, thus suggesting an effect on this pathway for fullerene 2. Our work represents the first approach toward the application of RNA-seq to the study of the molecular mechanisms underlying the interaction of fullerenes with cellular systems and provides an objective view of the feasibility and the safety of these nanomaterials for a medical application.

U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer's disease

Deposition of insoluble protein aggregates is a hallmark of neurodegenerative diseases. The universal presence of β-amyloid and tau in Alzheimer's disease (AD) has facilitated advancement of the amyloid cascade and tau hypotheses that have dominated AD pathogenesis research and therapeutic development. However, the underlying etiology of the disease remains to be fully elucidated. Here we report a comprehensive study of the human brain-insoluble proteome in AD by mass spectrometry. We identify 4,216 proteins, among which 36 proteins accumulate in the disease, including U1-70K and other U1 small nuclear ribonucleoprotein (U1 snRNP) spliceosome components. Similar accumulations in mild cognitive impairment cases indicate that spliceosome changes occur in early stages of AD. Multiple U1 snRNP subunits form cytoplasmic tangle-like structures in AD but not in other examined neurodegenerative disorders, including Parkinson disease and frontotemporal lobar degeneration. Comparison of RNA from AD and control brains reveals dysregulated RNA processing with accumulation of unspliced RNA species in AD, including myc box-dependent-interacting protein 1, clusterin, and presenilin-1. U1-70K knockdown or antisense oligonucleotide inhibition of U1 snRNP increases the protein level of amyloid precursor protein. Thus, our results demonstrate unique U1 snRNP pathology and implicate abnormal RNA splicing in AD pathogenesis.

Late-life rapamycin treatment reverses age-related heart dysfunction

Rapamycin has been shown to extend lifespan in numerous model organisms including mice, with the most dramatic longevity effects reported in females. However, little is known about the functional ramifications of this longevity-enhancing paradigm in mammalian tissues. We treated 24-month-old female C57BL/6J mice with rapamycin for 3 months and determined health outcomes via a variety of noninvasive measures of cardiovascular, skeletal, and metabolic health for individual mice. We determined that while rapamycin has mild transient metabolic effects, there are significant benefits to late-life cardiovascular function with a reversal or attenuation of age-related changes in the heart. RNA-seq analysis of cardiac tissue after treatment indicated inflammatory, metabolic, and antihypertrophic expression changes in cardiac tissue as potential mechanisms mediating the functional improvement. Rapamycin treatment also resulted in beneficial behavioral, skeletal, and motor changes in these mice compared with those fed a control diet. From these findings, we propose that late-life rapamycin therapy not only extends the lifespan of mammals, but also confers functional benefits to a number of tissues and mechanistically implicates an improvement in contractile function and antihypertrophic signaling in the aged heart with a reduction in age-related inflammation.

Analysis of stress-responsive transcriptome in the intestine of Asian seabass (Lates calcarifer) using RNA-seq

Identification of differentially expressed genes (DEGs) and regulated pathways in response to stressors using a whole-genome approach is critical to understanding the mechanisms underlying stress responses. We challenged Asian seabass with lipopolysaccharide (LPS), Vibrio harveyi, high salinity and fasting, and sequenced six cDNA libraries of intestine samples using Roche 454 RNA-seq. Over 1 million reads (average size: 516 bp) were obtained. The de novo assembly obtained 83 911 unisequences with an average length of 747 bp. In total, 62.3% of the unisequences were annotated. We observed overall similar expression profiles among different challenges, while a number of DEGs and regulated pathways were identified under specific challenges. More than 1000 DEGs and over 200 regulated pathways for each stressor were identified. Thirty-seven genes were differentially expressed in response to all challenges. Our data suggest that there is a global coordination and fine-tuning of gene regulation during different challenges. In addition, we detected dramatic immune responses in intestines under different stressors. This study is the first step towards the comprehensive understanding of the mechanisms underlying stress responses and supplies significant transcriptome resources for studying biological questions in non-model fish species.

Taf7l cooperates with Trf2 to regulate spermiogenesis

TATA-binding protein (TBP)-associated factor 7l (Taf7l; a paralogue of Taf7) and TBP-related factor 2 (Trf2) are components of the core promoter complex required for gene/tissue-specific transcription of protein-coding genes by RNA polymerase II. Previous studies reported that Taf7l knockout (KO) mice exhibit structurally abnormal sperm, reduced sperm count, weakened motility, and compromised fertility. Here we find that continued backcrossing of Taf7l(-/Y) mice from N5 to N9 produced KO males that are essentially sterile. Genome-wide expression profiling by mRNA-sequencing analysis of wild-type (WT) and Taf7l(-/Y) (KO) testes revealed that Taf7l ablation impairs the expression of many postmeiotic spermatogenic-specific as well as metabolic genes. Importantly, histological analysis of testes revealed that Taf7l(-/Y) mice develop postmeiotic arrest at the first stage of spermiogenesis, phenotypically similar to Trf2(-/-) mice, but distinct from Taf4b(-/-) mice. Indeed, we find that Taf7l and Trf2 coregulate postmeiotic genes, but none of Taf4b-regulated germ stem cell genes in testes. Genome-wide ChIP-sequencing studies indicate that TAF7L binds to promoters of activated postmeiotic genes in testis. Moreover, biochemical studies show that TAF7L associates with TRF2 both in vitro and in testis, suggesting that TAF7L likely cooperates directly with TRF2 at promoters of a subset of postmeiotic genes to regulate spermiogenesis. Our findings thus provide a previously undescribed mechanism for cell-type-specific transcriptional control involving an interaction between a "nonprototypic" core promoter recognition factor (Trf2) and an orphan TAF subunit (Taf7l) in mammalian testis-specific gene transcription.

Altered epigenetic regulation of homeobox genes in human oral squamous cell carcinoma cells

To gain insight into oral squamous cell carcinogenesis, we performed deep sequencing (RNAseq) of non-tumorigenic human OKF6-TERT1R and tumorigenic SCC-9 cells. Numerous homeobox genes are differentially expressed between OKF6-TERT1R and SCC-9 cells. Data from Oncomine, a cancer microarray database, also show that homeobox (HOX) genes are dysregulated in oral SCC patients. The activity of Polycomb repressive complexes (PRC), which causes epigenetic modifications, and retinoic acid (RA) signaling can control HOX gene transcription. HOXB7, HOXC10, HOXC13, and HOXD8 transcripts are higher in SCC-9 than in OKF6-TERT1R cells; using ChIP (chromatin immunoprecipitation) we detected PRC2 protein SUZ12 and the epigenetic H3K27me3 mark on histone H3 at these genes in OKF6-TERT1R, but not in SCC-9 cells. In contrast, IRX1, IRX4, SIX2 and TSHZ3 transcripts are lower in SCC-9 than in OKF6-TERT1R cells. We detected SUZ12 and the H3K27me3 mark at these genes in SCC-9, but not in OKF6-TERT1R cells. SUZ12 depletion increased HOXB7, HOXC10, HOXC13, and HOXD8 transcript levels and decreased the proliferation of OKF6-TERT1R cells. Transcriptional responses to RA are attenuated in SCC-9 versus OKF6-TERT1R cells. SUZ12 and H3K27me3 levels were not altered by RA at these HOX genes in SCC-9 and OKF6-TERT1R cells. We conclude that altered activity of PRC2 is associated with dysregulation of homeobox gene expression in human SCC cells, and that this dysregulation potentially plays a role in the neoplastic transformation of oral keratinocytes.

Functional similarity and molecular divergence of a novel reproductive transcriptome in two male-pregnant Syngnathus pipefish species

Evolutionary studies have revealed that reproductive proteins in animals and plants often evolve more rapidly than the genome-wide average. The causes of this pattern, which may include relaxed purifying selection, sexual selection, sexual conflict, pathogen resistance, reinforcement, or gene duplication, remain elusive. Investigative expansions to additional taxa and reproductive tissues have the potential to shed new light on this unresolved problem. Here, we embark on such an expansion, in a comparison of the brood-pouch transcriptome between two male-pregnant species of the pipefish genus Syngnathus. Male brooding tissues in syngnathid fishes represent a novel, nonurogenital reproductive trait, heretofore mostly uncharacterized from a molecular perspective. We leveraged next-generation sequencing (Roche 454 pyrosequencing) to compare transcript abundance in the male brooding tissues of pregnant with nonpregnant samples from Gulf (S. scovelli) and dusky (S. floridae) pipefish. A core set of protein-coding genes, including multiple members of astacin metalloprotease and c-type lectin gene families, is consistent between species in both the direction and magnitude of expression bias. As predicted, coding DNA sequence analysis of these putative "male pregnancy proteins" suggests rapid evolution relative to nondifferentially expressed genes and reflects signatures of adaptation similar in magnitude to those reported from Drosophila male accessory gland proteins. Although the precise drivers of male pregnancy protein divergence remain unknown, we argue that the male pregnancy transcriptome in syngnathid fishes, a clade diverse with respect to brooding morphology and mating system, represents a unique and promising object of study for understanding the perplexing evolutionary nature of reproductive molecules.

Evaluating statistical analysis models for RNA sequencing experiments

Validating statistical analysis methods for RNA sequencing (RNA-seq) experiments is a complex task. Researchers often find themselves having to decide between competing models or assessing the reliability of results obtained with a designated analysis program. Computer simulation has been the most frequently used procedure to verify the adequacy of a model. However, datasets generated by simulations depend on the parameterization and the assumptions of the selected model. Moreover, such datasets may constitute a partial representation of reality as the complexity or RNA-seq data is hard to mimic. We present the use of plasmode datasets to complement the evaluation of statistical models for RNA-seq data. A plasmode is a dataset obtained from experimental data but for which come truth is known. Using a set of simulated scenarios of technical and biological replicates, and public available datasets, we illustrate how to design algorithms to construct plasmodes under different experimental conditions. We contrast results from two types of methods for RNA-seq: (1) models based on negative binomial distribution (edgeR and DESeq), and (2) Gaussian models applied after transformation of data (MAANOVA). Results emphasize the fact that deciding what method to use may be experiment-specific due to the unknown distributions of expression levels. Plasmodes may contribute to choose which method to apply by using a similar pre-existing dataset. The promising results obtained from this approach, emphasize the need of promoting and improving systematic data sharing across the research community to facilitate plasmode building. Although we illustrate the use of plasmode for comparing differential expression analysis models, the flexibility of plasmode construction allows comparing upstream analysis, as normalization procedures or alignment pipelines, as well.

Functional genomics of adaptation to hypoxic cold-stress in high-altitude deer mice: transcriptomic plasticity and thermogenic performance

In species that are distributed across steep environmental gradients, adaptive variation in physiological performance may be attributable to transcriptional plasticity in underlying regulatory networks. Here we report the results of common-garden experiments that were designed to elucidate the role of regulatory plasticity in evolutionary adaptation to hypoxic cold-stress in deer mice (Peromyscus maniculatus). We integrated genomic transcriptional profiles with measures of metabolic enzyme activities and whole-animal thermogenic performance under hypoxia in highland (4350 m) and lowland (430 m) mice from three experimental groups: (1) wild-caught mice that were sampled at their native elevations; (2) wild-caught/lab-reared mice that were deacclimated to low-elevation conditions in a common-garden lab environment; and (3) the F(1) progeny of deacclimated mice that were maintained under the same low-elevation common-garden conditions. In each experimental group, highland mice exhibited greater thermogenic capacities than lowland mice, and this enhanced performance was associated with upregulation of transcriptional modules that influence several hierarchical steps in the O(2) cascade, including tissue O(2) diffusion (angiogenesis) and tissue O(2) utilization (metabolic fuel use and cellular oxidative capacity). Most of these performance-related transcriptomic changes occurred over physiological and developmental timescales, suggesting that regulatory plasticity makes important contributions to fitness-related physiological performance in highland deer mice.

De novo assembly of the pennycress (Thlaspi arvense) transcriptome provides tools for the development of a winter cover crop and biodiesel feedstock

Field pennycress (Thlaspi arvense L.) has potential as an oilseed crop that may be grown during fall (autumn) and winter months in the Midwestern United States and harvested in the early spring as a biodiesel feedstock. There has been little agronomic improvement in pennycress through traditional breeding. Recent advances in genomic technologies allow for the development of genomic tools to enable rapid improvements to be made through genomic assisted breeding. Here we report an annotated transcriptome assembly for pennycress. RNA was isolated from representative plant tissues, and 203 million unique Illumina RNA-seq reads were produced and used in the transcriptome assembly. The draft transcriptome assembly consists of 33 873 contigs with a mean length of 1242 bp. A global comparison of homology between the pennycress and Arabidopsis transcriptomes, along with four other Brassicaceae species, revealed a high level of global sequence conservation within the family. The final assembly was functionally annotated, allowing for the identification of putative genes controlling important agronomic traits such as flowering and glucosinolate metabolism. Identification of these genes leads to testable hypotheses concerning their conserved function and to rational strategies to improve agronomic properties in pennycress. Future work to characterize isoform variation between diverse pennycress lines and develop a draft genome sequence for pennycress will further direct trait improvement.

Predicting long non-coding RNAs using RNA sequencing

The advent of next-generation sequencing, and in particular RNA-sequencing (RNA-seq), technologies has expanded our knowledge of the transcriptional capacity of human and other animal, genomes. In particular, recent RNA-seq studies have revealed that transcription is widespread across the mammalian genome, resulting in a large increase in the number of putative transcripts from both within, and intervening between, known protein-coding genes. Long transcripts that appear to lack protein-coding potential (long non-coding RNAs, lncRNAs) have been the focus of much recent research, in part owing to observations of their cell-type and developmental time-point restricted expression patterns. A variety of sequencing protocols are currently available for identifying lncRNAs including RNA polymerase II occupancy, chromatin state maps and - the focus of this review - deep RNA sequencing. In addition, there are numerous analytical methods available for mapping reads and assembling transcript models that predict the presence and structure of lncRNAs from RNA-seq data. Here we review current methods for identifying lncRNAs using large-scale sequencing data from RNA-seq experiments and highlight analytical considerations that are required when undertaking such projects.

SNP development from RNA-seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA-seq is one such technique for the discovery of SNPs and development of markers for large-scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black-faced blenny), a small rocky-shore fish from the Mediterranean Sea. RNA-seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time-consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.

Understanding of auxin regulation during somatic embryogenesis in cotton by RNA-seq and sRNA-seq

Somatic embryogenesis (SE), by which somatic cells of higher plants can dedifferentiate and reorganize into new plants, is a notable illustration of cell totipotency. However, the precise molecular mechanisms regulating SE remain unclear. To characterize the molecular events of this unique process, transcriptome analysis, small RNA, and degradome sequencing were conducted in cotton, a typical plant species in SE. The results indicated that transcripts associated with auxin biosynthesis, conjugation, transport, and signal transduction were regulated during the whole developmental process. The complex auxin pathways with differentially regulated genes revealed that the auxin-related transcripts belonged to indoleacetic acid-induced protein (Aux/IAA), auxin response factor (ARF), small auxin-up RNA (SAUR), and other auxin-related proteins, which allow an intricate system of auxin utilization to achieve multiple purposes in SE. Additionally, we identified some small RNAs with their targets related to the auxin signaling pathway during cotton SE, and demonstrated that some sRNA regulate cotton SE by participating in auxin signaling pathways.

Emiliania huxleyi increases calcification but not expression of calcification-related genes in long-term exposure to elevated temperature and pCO2

Increased atmospheric pCO2 is expected to render future oceans warmer and more acidic than they are at present. Calcifying organisms such as coccolithophores that fix and export carbon into the deep sea provide feedbacks to increasing atmospheric pCO2. Acclimation experiments suggest negative effects of warming and acidification on coccolithophore calcification, but the ability of these organisms to adapt to future environmental conditions is not well understood. Here, we tested the combined effect of pCO2 and temperature on the coccolithophore Emiliania huxleyi over more than 700 generations. Cells increased inorganic carbon content and calcification rate under warm and acidified conditions compared with ambient conditions, whereas organic carbon content and primary production did not show any change. In contrast to findings from short-term experiments, our results suggest that long-term acclimation or adaptation could change, or even reverse, negative calcification responses in E. huxleyi and its feedback to the global carbon cycle. Genome-wide profiles of gene expression using RNA-seq revealed that genes thought to be essential for calcification are not those that are most strongly differentially expressed under long-term exposure to future ocean conditions. Rather, differentially expressed genes observed here represent new targets to study responses to ocean acidification and warming.

Transcriptome analysis and SNP identification in SCC of horn in (Bos indicus) Indian cattle

Single Nucleotide Polymorphisms (SNPs) have become the marker of choice for genome wide association studies. In order to provide the best genome coverage for the analysis of disease, production and performance traits, a large number of relatively evenly distributed SNPs are needed. The main objective of present work was to identify large numbers of gene-associated SNPs using high-throughput sequencing in squamous cell carcinoma of horn. RNA-seq analysis was conducted on 2 tissues viz. Horn Cancer (HC) and Horn Normal (HN) in Kankrej breed of cattle. A total of 909,362 reads with average read length of 405 bp for HC and 583,491 reads with average read length of 411 bp for HN were obtained. We found 9532 and 7065 SNPs as well as 1771 and 1172 Indels in HC and HN, respectively, from which, 7889 SNPs and 1736 Indels were uniquely present in HC, 5886 SNPs and 1146 Indels were uniquely present in HN and reported first time in Bos indicus, whereas the rest are already reported in Bos taurus dbSNP database. The gene-associated SNPs and Indels were high in upregulated genes of HC as compared to HN. Analysis of differentially expressed genes was identified, these genes are involved in regulation of cell proliferation, apoptosis, gene transcription, cell survival and metabolism through various metabolic pathways. The result of transcriptome expression profiling was validated using Real Time quantitative PCR in nine randomly selected genes. We identified numbers aberrant signaling pathways responsible for carcinogenesis in HC which are also commonly altered in squamous cell carcinoma (SCC) of lung in human being. We conclude that a large number of altered genes and dysfunction of multiple pathways are involved in the development of Horn Cancer. The present findings contribute to theoretical information for further screening of genes and identification of markers for early diagnosis of HC as well as SNPs identified in this report provide a much needed resource for genetic studies in B. indicus and shall contribute to the development of a high density SNP array. Validation and testing of these SNPs using SNP arrays will form the material basis for gene associated SNPs in HC.

Profiling microRNA expression in bovine alveolar macrophages using RNA-seq

MicroRNAs (miRNAs) are important regulators of gene expression and are known to play a key role in regulating both adaptive and innate immunity. Bovine alveolar macrophages (BAMs) help maintain lung homeostasis and constitute the front line of host defense against several infectious respiratory diseases, such as bovine tuberculosis. Little is known, however, about the role miRNAs play in these cells. In this study, we used a high-throughput sequencing approach, RNA-seq, to determine the expression levels of known and novel miRNAs in unchallenged BAMs isolated from lung lavages of eight different healthy Holstein-Friesian male calves. Approximately 80 million sequence reads were generated from eight BAM miRNA Illumina sequencing libraries, and 80 miRNAs were identified as being expressed in BAMs at a threshold of at least 100 reads per million (RPM). The expression levels of miRNAs varied over a large dynamic range, with a few miRNAs expressed at very high levels (up to 800,000RPM), and the majority lowly expressed. Notably, many of the most highly expressed miRNAs in BAMs have known roles in regulating immunity in other species (e.g. bta-let-7i, bta-miR-21, bta-miR-27, bta-miR-99b, bta-miR-146, bta-miR-147, bta-miR-155 and bta-miR-223). The most highly expressed miRNA in BAMs was miR-21, which has been shown to regulate the expression of antimicrobial peptides in Mycobacterium leprae-infected human monocytes. Furthermore, the predicted target genes of BAM-expressed miRNAs were found to be statistically enriched for roles in innate immunity. In addition to profiling the expression of known miRNAs, the RNA-seq data was also analysed to identify potentially novel bovine miRNAs. One putatively novel bovine miRNA was identified. To the best of our knowledge, this is the first RNA-seq study to profile miRNA expression in BAMs and provides an important reference dataset for investigating the regulatory roles miRNAs play in this important immune cell type.

Shaping development through mechanical strain: the transcriptional basis of diet-induced phenotypic plasticity in a cichlid fish

Adaptive phenotypic plasticity, the ability of an organism to change its phenotype to match local environments, is increasingly recognized for its contribution to evolution. However, few empirical studies have explored the molecular basis of plastic traits. The East African cichlid fish Astatoreochromis alluaudi displays adaptive phenotypic plasticity in its pharyngeal jaw apparatus, a structure that is widely seen as an evolutionary key innovation that has contributed to the remarkable diversity of cichlid fishes. It has previously been shown that in response to different diets, the pharyngeal jaws change their size, shape and dentition: hard diets induce an adaptive robust molariform tooth phenotype with short jaws and strong internal bone structures, while soft diets induce a gracile papilliform tooth phenotype with elongated jaws and slender internal bone structures. To gain insight into the molecular underpinnings of these adaptations and enable future investigations of the role that phenotypic plasticity plays during the formation of adaptive radiations, the transcriptomes of the two divergent jaw phenotypes were examined. Our study identified a total of 187 genes whose expression differs in response to hard and soft diets, including immediate early genes, extracellular matrix genes and inflammatory factors. Transcriptome results are interpreted in light of expression of candidate genes-markers for tooth size and shape, bone cells and mechanically sensitive pathways. This study opens up new avenues of research at new levels of biological organization into the roles of phenotypic plasticity during speciation and radiation of cichlid fishes.

Developing nuclear DNA phylogenetic markers in the angiosperm genus Leucadendron (Proteaceae): a next-generation sequencing transcriptomic approach

Despite the recent advances in generating molecular data, reconstructing species-level phylogenies for non-models groups remains a challenge. The use of a number of independent genes is required to resolve phylogenetic relationships, especially for groups displaying low polymorphism. In such cases, low-copy nuclear exons and non-coding regions, such as 3' untranslated regions (3'-UTRs) or introns, constitute a potentially interesting source of nuclear DNA variation. Here, we present a methodology meant to identify new nuclear orthologous markers using both public-nucleotide databases and transcriptomic data generated for the group of interest by using next generation sequencing technology. To identify PCR primers for a non-model group, the genus Leucadendron (Proteaceae), we adopted a framework aimed at minimizing the probability of paralogy and maximizing polymorphism. We anchored when possible the right-hand primer into the 3'-UTR and the left-hand primer into the coding region. Seven new nuclear markers emerged from this search strategy, three of those included 3'-UTRs. We further compared the phylogenetic potential between our new markers and the ribosomal internal transcribed spacer region (ITS). The sequenced 3'-UTRs yielded higher polymorphism rates than the ITS region did. We did not find strong incongruences with the phylogenetic signal contained in the ITS region and the seven new designed markers but they strongly improved the phylogeny of the genus Leucadendron. Overall, this methodology is efficient in isolating orthologous loci and is valid for any non-model group given the availability of transcriptomic data.

The role of desaturases in the biosynthesis of marking pheromones in bumblebee males

Bumblebee males (Hymenoptera) produce species-specific labial gland secretions called marking pheromones (MPs). MPs generally consist of terpenoids and fatty-acid-derived aliphatic compounds with various chain lengths predominantly containing one or no double bonds. The unsaturated fatty-acid-derived MP components were hypothesized to be produced by fatty acid desaturases (FADs) that exhibit diverse substrate specificities. To address this hypothesis, we isolated and functionally characterized FADs from three bumblebee species: Bombus lucorum, Bombus terrestris, and Bombus lapidarius. By employing RNA sequencing of the male labial glands and fat bodies of B. lucorum and B. terrestris, we identified five paralogous FAD-like sequences but only two FAD lineages were abundant and differentially expressed in the labial glands. We found that abundant FAD lineages were also expressed in the labial gland and fat body of Bombus lapidarius. Functional characterization of FADs in a yeast expression system confirmed that Δ4-FADs exhibited a unique Δ4-desaturase activity exclusively on 14-carbon fatty acyls and Δ9-FADs displayed Δ9-desaturase activity on 14- to 18-carbon fatty acyls. These results indicate that Δ9-FADs are involved in the biosynthesis of major unsaturated components of MPs in B. lucorum and B. lapidarius despite the diverse MP composition of these bumblebee species. The contribution of lipases, acyltransferases, esterases, and fatty acid reductases to production of the species-specific MP composition is also discussed in light of the transcriptomic data obtained in this study.

A global view of transcriptome dynamics during flower development in chickpea by deep sequencing

Measurement of gene expression can provide important clues about gene function and molecular basis of developmental processes. Here, we have analysed the chickpea transcriptome in vegetative and flower tissues by exploiting the potential of high-throughput sequencing to measure gene expression. We mapped more than 295 million reads to quantify the transcript abundance during flower development. We detected the expression of more than 90% genes in at least one tissue analysed. We found quite a large number of genes were differentially expressed during flower development as compared to vegetative tissues. Further, we identified several genes expressed in a stage-specific manner. Various transcription factor families and metabolic pathways involved in flower development were elucidated. The members of MADS-box family were most represented among the transcription factor genes up-regulated during various stages of flower development. The abundant expression of several well-known genes implicated in flower development in chickpea flower development stages confirmed our results. In addition, we detected the expression specificities of lineage-specific genes during flower development. The expression data presented in this study is the most comprehensive dataset available for chickpea as of now and will serve as resource for unraveling the functions of many specific genes involved in flower development in chickpea and other legumes.

Enzyme engineering through evolution: thermostable recombinant group II intron reverse transcriptases provide new tools for RNA research and biotechnology

Current investigation of RNA transcriptomes relies heavily on the use of retroviral reverse transcriptases. It is well known that these enzymes have many limitations because of their intrinsic properties. This commentary highlights the recent biochemical characterization of a new family of reverse transcriptases, those encoded by group II intron retrohoming elements. The novel properties of these enzymes endow them with the potential to revolutionize how we approach RNA analyses.

TRP53 activates a global autophagy program to promote tumor suppression

The mechanisms by which the TP53/TRP53 transcription factor acts as a tumor suppressor remain incompletely understood. To gain new insights into TP53/TRP53 biology, we used ChIP-seq and RNA-seq technologies to define global TRP53 transcriptional networks in primary cells subjected to DNA damage. Intriguingly, we identified a TRP53-regulated autophagy program, which can be coordinately regulated by the TRP53 family members TRP63 and TRP73 in certain settings. While autophagy is not involved in TRP53-dependent cell cycle arrest, it contributes to both TRP53-driven apoptosis in response to DNA damage and TRP53-mediated transformation suppression. Collectively, our genome-wide analyses reveal a profound role for TRP53 in regulating autophagy, through an extensive transcriptional network, and have demonstrated an important role for this program in promoting TRP53-mediated apoptosis and tumor suppression.

Pairwise comparisons of ten porcine tissues identify differential transcriptional regulation at the gene, isoform, promoter and transcription start site level

The transcriptome is the absolute set of transcripts in a tissue or cell at the time of sampling. In this study RNA-Seq is employed to enable the differential analysis of the transcriptome profile for ten porcine tissues in order to evaluate differences between the tissues at the gene and isoform expression level, together with an analysis of variation in transcription start sites, promoter usage, and splicing. Totally, 223 million RNA fragments were sequenced leading to the identification of 59,930 transcribed gene locations and 290,936 transcript variants using Cufflinks with similarity to approximately 13,899 annotated human genes. Pairwise analysis of tissues for differential expression at the gene level showed that the smallest differences were between tissues originating from the porcine brain. Interestingly, the relative level of differential expression at the isoform level did generally not vary between tissue contrasts. Furthermore, analysis of differential promoter usage between tissues, revealed a proportionally higher variation between cerebellum (CBE) versus frontal cortex and cerebellum versus hypothalamus (HYP) than in the remaining comparisons. In addition, the comparison of differential transcription start sites showed that the number of these sites is generally increased in comparisons including hypothalamus in contrast to other pairwise assessments. A comprehensive analysis of one of the tissue contrasts, i.e. cerebellum versus heart for differential variation at the gene, isoform, and transcription start site (TSS), and promoter level showed that several of the genes differed at all four levels. Interestingly, these genes were mainly annotated to the "electron transport chain" and neuronal differentiation, emphasizing that "tissue important" genes are regulated at several levels. Furthermore, our analysis shows that the "across tissue approach" has a promising potential when screening for possible explanations for variations, such as those observed at the gene expression levels.

An optimal test with maximum average power while controlling FDR with application to RNA-seq data

The recent RNA-seq technology is an attractive method to study gene expression. One of the most important goals in RNA-seq data analysis is to detect genes differentially expressed across treatments. Although several statistical methods have been published, there are no theoretical justifications for whether these methods are optimal or how to search for the optimal test. Furthermore, most proposed tests are designed for testing whether the mean expression levels are exactly the same or not across treatments, whereas sometimes, biologists are interested in detecting genes with expression changes larger than a certain threshold. Another issue with current methods is that the false discovery rate (FDR) control is not well studied. In this manuscript, we propose a test to address all the above issues. Under model assumptions, we derive an optimal test that achieves the maximum of average power among those that control FDR at the same level. We also provide an approximated version, the approximated most average powerful (AMAP) test, for practical implementation. The proposed method allows for testing null hypotheses that are much more general than the ones most previous studies have considered, and it leads to a natural way of controlling the FDR. Through simulation studies, we show that our test has a higher power than other methods, including the widely-used edgeR, DESeq, and baySeq methods, as well as better FDR control than two other FDR control procedures commonly used in practice. For demonstration, we also apply the proposed method to a real RNA-seq dataset obtained from maize.

Prostate cancer invasion and metastasis: insights from mining genomic data

Prostate cancer (PCa) is the second most commonly diagnosed malignancy in men in the Western world and the second leading cause of cancer-related deaths among men worldwide. Although most cancers have the potential to metastasize under appropriate conditions, PCa favors the skeleton as a primary site of metastasis, suggesting that the bone microenvironment is conducive to its growth. PCa metastasis proceeds through a complex series of molecular events that include angiogenesis at the site of the original tumor, local migration within the primary site, intravasation into the blood stream, survival within the circulation, extravasation of the tumor cells to the target organ and colonization of those cells within the new site. In turn, each one of these steps involves a complicated chain of events that utilize multiple protein-protein interactions, protein signaling cascades and transcriptional changes. Despite the urgent need to improve current biomarkers for diagnosis, prognosis and drug resistance, advances have been slow. Global gene expression methods such as gene microarrays and RNA sequencing enable the study of thousands of genes simultaneously and allow scientists to examine molecular pathways of cancer pathogenesis. In this review, we summarize the current literature that explored high-throughput transcriptome analysis toward the advancement of biomarker discovery for PCa. Novel biomarkers are strongly needed to enable more accurate detection of PCa, improve prediction of tumor aggressiveness and facilitate the discovery of new therapeutic targets for tailored medicine. Promising molecular markers identified from gene expression profiling studies include HPN, CLU1, WT1, WNT5A, AURKA and SPARC.