ATF6 protects against protein misfolding during cardiac hypertrophy

Cardiomyocytes activate the unfolded protein response (UPR) transcription factor ATF6 during pressure overload-induced hypertrophic growth. The UPR is thought to increase ER protein folding capacity and maintain proteostasis. ATF6 deficiency during pressure overload leads to heart failure, suggesting that ATF6 protects against myocardial dysfunction by preventing protein misfolding. However, conclusive evidence that ATF6 prevents toxic protein misfolding during cardiac hypertrophy is still pending. Here, we found that activation of the UPR, including ATF6, is a common response to pathological cardiac hypertrophy in mice. ATF6 KO mice failed to induce sufficient levels of UPR target genes in response to chronic isoproterenol infusion or transverse aortic constriction (TAC), resulting in impaired cardiac growth. To investigate the effects of ATF6 on protein folding, the accumulation of poly-ubiquitinated proteins as well as soluble amyloid oligomers were directly quantified in hypertrophied hearts of WT and ATF6 KO mice. Whereas only low levels of protein misfolding was observed in WT hearts after TAC, ATF6 KO mice accumulated increased quantities of misfolded protein, which was associated with impaired myocardial function. Collectively, the data suggest that ATF6 plays a critical adaptive role during cardiac hypertrophy by protecting against protein misfolding.

State-of-the-Art Circular RNA Analytics Using the Circtools Software Suite

Circular RNAs (circRNAs) are types of RNA molecules that have been discovered relatively recently and have been found to be widely expressed in eukaryotic cells. Unlike canonical linear RNA molecules, circRNAs form a covalently closed continuous loop structure without a 5' or 3' end. They are generated by a process called back-splicing, in which a downstream splice donor site is joined to an upstream splice acceptor site. CircRNAs have been found to play important roles in various biological processes, including gene regulation, alternative splicing, and protein translation. They can act as sponges for microRNAs or RNA-binding proteins and can also encode peptides or proteins. Additionally, circRNAs have been implicated in several diseases, including cancer, neurological disorders, and cardiovascular diseases.This protocol provides all necessary steps to detect and analyze circRNAs in silico from RNA sequencing data using the circtools circRNA analytics software suite. The protocol starts from raw sequencing data with circRNA detection via back-splice events and includes statistical testing of circRNAs as well as primer design for follow-up wet lab experiments.

Ythdf2 regulates cardiac remodeling through its mRNA target transcripts

m6A mRNA methylation controls cardiomyocyte function and increased overall m6A levels are a stereotyping finding in heart failure independent of the underlying etiology. However, it is largely unknown how the information is read by m6A reader proteins in heart failure. Here we show that the m6A reader protein Ythdf2 controls cardiac function and identified a novel mechanism how reader proteins control gene expression and cardiac function. Deletion of Ythdf2 in cardiomyocytes in vivo leads to mild cardiac hypertrophy, reduced heart function, and increased fibrosis during pressure overload as well as during aging. Similarly, in vitro the knockdown of Ythdf2 results in cardiomyocyte growth and remodeling. Mechanistically, we identified the eucaryotic elongation factor 2 as post-transcriptionally regulated by Ythdf2 using cell type specific Ribo-seq data. Our study expands our understanding on the regulatory functions of m6A methylation in cardiomyocytes and how cardiac function is controlled by the m6A reader protein Ythdf2.

Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.

Transcriptional Effects of Candidate COVID-19 Treatments on Cardiac Myocytes

Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) has emerged as a major cause of morbidity and mortality worldwide, placing unprecedented pressure on healthcare. Cardiomyopathy is described in patients with severe COVID-19 and increasing evidence suggests that cardiovascular involvement portends a high mortality. To facilitate fast development of antiviral interventions, drugs initially developed to treat other diseases are currently being repurposed as COVID-19 treatments. While it has been shown that SARS-CoV-2 invades cells through the angiotensin-converting enzyme 2 receptor (ACE2), the effect of drugs currently repurposed to treat COVID-19 on the heart requires further investigation.

Methods

Human induced pluripotent stem cell-derived cardiac myocytes (hiPSC-CMs) were treated with five repurposed drugs (remdesivir, lopinavir/ritonavir, lopinavir/ritonavir/interferon beta (INF-β), hydroxychloroquine, and chloroquine) and compared with DMSO controls. Transcriptional profiling was performed to identify global changes in gene expression programs.

Results

RNA sequencing of hiPSC-CMs revealed significant changes in gene programs related to calcium handling and the endoplasmic reticulum stress response, most prominently for lopinavir/ritonavir and lopinavir/ritonavir/interferon-beta. The results of the differential gene expression analysis are available for interactive access at https://covid19drugs.jakobilab.org.

Conclusion

Transcriptional profiling in hiPSC-CMs treated with COVID-19 drugs identified unfavorable changes with lopinavir/ritonavir and lopinavir/ritonavir/INF-β in key cardiac gene programs that may negatively affect heart function.

Increased susceptibility of human endothelial cells to infections by SARS-CoV-2 variants

Coronavirus disease 2019 (COVID-19) spawned a global health crisis in late 2019 and is caused by the novel coronavirus SARS-CoV-2. SARS-CoV-2 infection can lead to elevated markers of endothelial dysfunction associated with higher risk of mortality. It is unclear whether endothelial dysfunction is caused by direct infection of endothelial cells or is mainly secondary to inflammation. Here, we investigate whether different types of endothelial cells are susceptible to SARS-CoV-2. Human endothelial cells from different vascular beds including umbilical vein endothelial cells, coronary artery endothelial cells (HCAEC), cardiac and lung microvascular endothelial cells, or pulmonary arterial cells were inoculated in vitro with SARS-CoV-2. Viral spike protein was only detected in HCAECs after SARS-CoV-2 infection but not in the other endothelial cells tested. Consistently, only HCAEC expressed the SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2), required for virus infection. Infection with the SARS-CoV-2 variants B.1.1.7, B.1.351, and P.2 resulted in significantly higher levels of viral spike protein. Despite this, no intracellular double-stranded viral RNA was detected and the supernatant did not contain infectious virus. Analysis of the cellular distribution of the spike protein revealed that it co-localized with endosomal calnexin. SARS-CoV-2 infection did induce the ER stress gene EDEM1, which is responsible for clearance of misfolded proteins from the ER. Whereas the wild type of SARS-CoV-2 did not induce cytotoxic or pro-inflammatory effects, the variant B.1.1.7 reduced the HCAEC cell number. Of the different tested endothelial cells, HCAECs showed highest viral uptake but did not promote virus replication. Effects on cell number were only observed after infection with the variant B.1.1.7, suggesting that endothelial protection may be particularly important in patients infected with this variant.

ADAR-deficiency perturbs the global splicing landscape in mouse tissues

Adenosine-to-inosine RNA editing and pre-mRNA splicing largely occur cotranscriptionally and influence each other. Here, we use mice deficient in either one of the two editing enzymes ADAR (ADAR1) or ADARB1 (ADAR2) to determine the transcriptome-wide impact of RNA editing on splicing across different tissues. We find that ADAR has a 100× higher impact on splicing than ADARB1, although both enzymes target a similar number of substrates with a large common overlap. Consistently, differentially spliced regions frequently harbor ADAR editing sites. Moreover, catalytically dead ADAR also impacts splicing, demonstrating that RNA binding of ADAR affects splicing. In contrast, ADARB1 editing sites are found enriched 5′ of differentially spliced regions. Several of these ADARB1-mediated editing events change splice consensus sequences, therefore strongly influencing splicing of some mRNAs. A significant overlap between differentially edited and differentially spliced sites suggests evolutionary selection toward splicing being regulated by editing in a tissue-specific manner.

Deep Characterization of Circular RNAs from Human Cardiovascular Cell Models and Cardiac Tissue

For decades, cardiovascular disease (CVD) has been the leading cause of death throughout most developed countries. Several studies relate RNA splicing, and more recently also circular RNAs (circRNAs), to CVD. CircRNAs originate from linear transcripts and have been shown to exhibit tissue-specific expression profiles. Here, we present an in-depth analysis of sequence, structure, modification, and cardiac circRNA interactions. We used human induced pluripotent stem cell-derived cardiac myocytes (hiPSC-CMs), human healthy and diseased (ischemic cardiomyopathy, dilated cardiomyopathy) cardiac tissue, and human umbilical vein endothelial cells (HUVECs) to profile circRNAs. We identified shared circRNAs across all samples, as well as model-specific circRNA signatures. Based on these circRNAs, we identified 63 positionally conserved and expressed circRNAs in human, pig, and mouse hearts. Furthermore, we found that the sequence of circRNAs can deviate from the sequence derived from the genome sequence, an important factor in assessing potential functions. Integration of additional data yielded evidence for m⁶A-methylation of circRNAs, potentially linked to translation, as well as, circRNAs overlapping with potential Argonaute 2 binding sites, indicating potential association with the RISC complex. Moreover, we describe, for the first time in cardiac model systems, a sub class of circRNAs containing the start codon of their primary transcript (AUG circRNAs) and observe an enrichment for m⁶A-methylation for AUG circRNAs.

circtools-a one-stop software solution for circular RNA research

MOTIVATION

Circular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, are not polyadenylated and have been shown to be highly specific for cell type and developmental stage. CircRNA detection starts from high-throughput sequencing data and is a multi-stage bioinformatics process yielding sets of potential circRNA candidates that require further analyses. While a number of tools for the prediction process already exist, publicly available analysis tools for further characterization are rare. Our work provides researchers with a harmonized workflow that covers different stages of in silico circRNA analyses, from prediction to first functional insights.

RESULTS

Here, we present circtools, a modular, Python-based framework for computational circRNA analyses. The software includes modules for circRNA detection, internal sequence reconstruction, quality checking, statistical testing, screening for enrichment of RBP binding sites, differential exon RNase R resistance and circRNA-specific primer design. circtools supports researchers with visualization options and data export into commonly used formats.

AVAILABILITY AND IMPLEMENTATION

circtools is available via https://github.com/dieterich-lab/circtools and http://circ.tools under GPLv3.0.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Proteomic analysis of the cardiac myocyte secretome reveals extracellular protective functions for the ER stress response

The effects of ER stress on protein secretion by cardiac myocytes are not well understood. In this study, the ER stressor thapsigargin (TG), which depletes ER calcium, induced death of cultured neonatal rat ventricular myocytes (NRVMs) in high media volume but fostered protection in low media volume. In contrast, another ER stressor, tunicamycin (TM), a protein glycosylation inhibitor, induced NRVM death in all media volumes, suggesting that protective proteins were secreted in response to TG but not TM. Proteomic analyses of TG- and TM-conditioned media showed that the secretion of most proteins was inhibited by TG and TM; however, secretion of several ER-resident proteins, including GRP78 was increased by TG but not TM. Simulated ischemia, which decreases ER/SR calcium also increased secretion of these proteins. Mechanistically, secreted GRP78 was shown to enhance survival of NRVMs by collaborating with a cell-surface protein, CRIPTO, to activate protective AKT signaling and to inhibit death-promoting SMAD2 signaling. Thus, proteins secreted during ER stress mediated by ER calcium depletion can enhance cardiac myocyte viability.

ATF6 Regulates Cardiac Hypertrophy by Transcriptional Induction of the mTORC1 Activator, Rheb

RATIONALE

Endoplasmic reticulum (ER) stress dysregulates ER proteostasis, which activates the transcription factor, ATF6 (activating transcription factor 6α), an inducer of genes that enhance protein folding and restore ER proteostasis. Because of increased protein synthesis, it is possible that protein folding and ER proteostasis are challenged during cardiac myocyte growth. However, it is not known whether ATF6 is activated, and if so, what its function is during hypertrophic growth of cardiac myocytes.

OBJECTIVE

To examine the activity and function of ATF6 during cardiac hypertrophy.

METHODS AND RESULTS

We found that ER stress and ATF6 were activated and ATF6 target genes were induced in mice subjected to an acute model of transverse aortic constriction, or to free-wheel exercise, both of which promote adaptive cardiac myocyte hypertrophy with preserved cardiac function. Cardiac myocyte-specific deletion of Atf6 (ATF6 cKO [conditional knockout]) blunted transverse aortic constriction and exercise-induced cardiac myocyte hypertrophy and impaired cardiac function, demonstrating a role for ATF6 in compensatory myocyte growth. Transcript profiling and chromatin immunoprecipitation identified RHEB (Ras homologue enriched in brain) as an ATF6 target gene in the heart. RHEB is an activator of mTORC1 (mammalian/mechanistic target of rapamycin complex 1), a major inducer of protein synthesis and subsequent cell growth. Both transverse aortic constriction and exercise upregulated RHEB, activated mTORC1, and induced cardiac hypertrophy in wild type mouse hearts but not in ATF6 cKO hearts. Mechanistically, knockdown of ATF6 in neonatal rat ventricular myocytes blocked phenylephrine- and IGF1 (insulin-like growth factor 1)-mediated RHEB induction, mTORC1 activation, and myocyte growth, all of which were restored by ectopic RHEB expression. Moreover, adeno-associated virus 9- RHEB restored cardiac growth to ATF6 cKO mice subjected to transverse aortic constriction. Finally, ATF6 induced RHEB in response to growth factors, but not in response to other activators of ATF6 that do not induce growth, indicating that ATF6 target gene induction is stress specific.

CONCLUSIONS

Compensatory cardiac hypertrophy activates ER stress and ATF6, which induces RHEB and activates mTORC1. Thus, ATF6 is a previously unrecognized link between growth stimuli and mTORC1-mediated cardiac growth.

Monitoring Cell-Type-Specific Gene Expression Using Ribosome Profiling In Vivo During Cardiac Hemodynamic Stress

Supplemental Digital Content is available in the text.

Rationale:

Gene expression profiles have been mainly determined by analysis of transcript abundance. However, these analyses cannot capture posttranscriptional gene expression control at the level of translation, which is a key step in the regulation of gene expression, as evidenced by the fact that transcript levels often poorly correlate with protein levels. Furthermore, genome-wide transcript profiling of distinct cell types is challenging due to the fact that lysates from tissues always represent a mixture of cells.

Objectives:

This study aimed to develop a new experimental method that overcomes both limitations and to apply this method to perform a genome-wide analysis of gene expression on the translational level in response to pressure overload.

Methods and Results:

By combining ribosome profiling (Ribo-seq) with a ribosome-tagging approach (Ribo-tag), it was possible to determine the translated transcriptome in specific cell types from the heart. After pressure overload, we monitored the cardiac myocyte translatome by purifying tagged cardiac myocyte ribosomes from cardiac lysates and subjecting the ribosome-protected mRNA fragments to deep sequencing. We identified subsets of mRNAs that are regulated at the translational level and found that translational control determines early changes in gene expression in response to cardiac stress in cardiac myocytes. Translationally controlled transcripts are associated with specific biological processes related to translation, protein quality control, and metabolism. Mechanistically, Ribo-seq allowed for the identification of upstream open reading frames in transcripts, which we predict to be important regulators of translation.

Conclusions:

This method has the potential to (1) provide a new tool for studying cell-specific gene expression at the level of translation in tissues, (2) reveal new therapeutic targets to prevent cellular remodeling, and (3) trigger follow-up studies that address both, the molecular mechanisms involved in the posttranscriptional control of gene expression in cardiac cells, and the protective functions of proteins expressed in response to cellular stress.

Computational approaches for circular RNA analysis

Circular RNAs (circRNAs) are a recent addition to the expanding universe of RNA species and originate through back-splicing events from linear primary transcripts. CircRNAs show specific expression profiles with regards to cell type and developmental stage. Importantly, only few circRNAs have been functionally characterized to date. The detection of circRNAs from RNA sequencing data is a complex computational workflow that, depending on tissue and condition typically yields candidate sets of hundreds or thousands of circRNA candidates. Here, we provide an overview on different computational analysis tools and pipelines that became available throughout the last years. We outline technical and experimental requirements that are common to all approaches and point out potential pitfalls during the computational analysis. Although computational prediction of circRNAs has become quite mature in recent years, we provide a set of valuable validation strategies, in silico as well as in vitro-based approaches. In addition to circRNA detection via back-splicing junction, we present available analysis pipelines for delineating the primary sequence and for predicting possible functions of circRNAs. Finally, we outline the most important web resources for circRNA research. This article is categorized under: RNA Methods > RNA Analyses in vitro and In Silico RNA Evolution and Genomics > Computational Analyses of RNA.

Early Response of Sulfolobus acidocaldarius to Nutrient Limitation

In natural environments microorganisms encounter extreme changes in temperature, pH, osmolarities and nutrient availability. The stress response of many bacterial species has been described in detail, however, knowledge in Archaea is limited. Here, we describe the cellular response triggered by nutrient limitation in the thermoacidophilic crenarchaeon Sulfolobus acidocaldarius. We measured changes in gene transcription and protein abundance upon nutrient depletion up to 4 h after initiation of nutrient depletion. Transcript levels of 1118 of 2223 protein coding genes and abundance of approximately 500 proteins with functions in almost all cellular processes were affected by nutrient depletion. Our study reveals a significant rerouting of the metabolism with respect to degradation of internal as well as extracellular-bound organic carbon and degradation of proteins. Moreover, changes in membrane lipid composition were observed in order to access alternative sources of energy and to maintain pH homeostasis. At transcript level, the cellular response to nutrient depletion in S. acidocaldarius seems to be controlled by the general transcription factors TFB2 and TFEβ. In addition, ribosome biogenesis is reduced, while an increased protein degradation is accompanied with a loss of protein quality control. This study provides first insights into the early cellular response of Sulfolobus to organic carbon and organic nitrogen depletion.

Deep Computational Circular RNA Analytics from RNA-seq Data

Circular RNAs (circRNAs) have been first described as "scrambled exons" in the 1990s. CircRNAs originate from back splicing or exon skipping of linear RNA templates and have continuously gained attention in recent years due to the availability of high-throughput whole-transcriptome sequencing methods. Numerous manuscripts describe thousands of circRNAs throughout uni- and multicellular eukaryote species and demonstrated that they are conserved, stable, and abundant in specific tissues or conditions. This manuscript provides a walk-through of our bioinformatics toolbox, which covers all aspects of in silico circRNA analysis, starting from raw sequencing data and back-splicing junction discovery to circRNA quantitation and reconstruction of internal the circRNA structure.

Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations

Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures.

Integrin-linked kinase regulates the niche of quiescent epidermal stem cells

Stem cells reside in specialized niches that are critical for their function. Quiescent hair follicle stem cells (HFSCs) are confined within the bulge niche, but how the molecular composition of the niche regulates stem cell behaviour is poorly understood. Here we show that integrin-linked kinase (ILK) is a key regulator of the bulge extracellular matrix microenvironment, thereby governing the activation and maintenance of HFSCs. ILK mediates deposition of inverse laminin (LN)-332 and LN-511 gradients within the basement membrane (BM) wrapping the hair follicles. The precise BM composition tunes activities of Wnt and transforming growth factor-β pathways and subsequently regulates HFSC activation. Notably, reconstituting an optimal LN microenvironment restores the altered signalling in ILK-deficient cells. Aberrant stem cell activation in ILK-deficient epidermis leads to increased replicative stress, predisposing the tissue to carcinogenesis. Overall, our findings uncover a critical role for the BM niche in regulating stem cell activation and thereby skin homeostasis.

Radial spacing distributions from planar point sets

This paper explores the radial projection method for locally finite planar point sets and provides numerical examples for different types of order. The main question is whether the method is suitable to analyse order in a quantitative way. The findings indicate that the answer is affirmative. In this context, local visibility conditions are also studied for certain types of aperiodic point sets.

Discovery of transcription start sites in the Chinese hamster genome by next-generation RNA sequencing

Chinese hamster ovary (CHO) cell lines are one of the major production tools for monoclonal antibodies, recombinant proteins, and therapeutics. Although many efforts have significantly improved the availability of sequence information for CHO cells in the last years, forthcoming draft genomes still lack the information depth known from the mouse or human genomes. Many genes annotated for CHO cells and the Chinese hamster reference genome still are in silico predictions, only insufficiently verified by biological experiments. The correct annotation of transcription start sites (TSSs) is of special interest for CHO cells, as these directly define the location of the eukaryotic core promoter. Our study aims to elucidate these largely unexplored regions, trying to shed light on promoter landscapes in the Chinese hamster genome. Based on a 5' enriched dual library RNA sequencing approach 6547 TSSs were identified, of which over 90% were assigned to known genes. These TSSs were used to perform extensive promoter studies using a novel, modular bioinformatics pipeline, incorporating analyses of important regulatory elements of the eukaryotic core promoter on per-gene level and on genomic scale.

Large-scale compression of genomic sequence databases with the Burrows-Wheeler transform

MOTIVATION

The Burrows-Wheeler transform (BWT) is the foundation of many algorithms for compression and indexing of text data, but the cost of computing the BWT of very large string collections has prevented these techniques from being widely applied to the large sets of sequences often encountered as the outcome of DNA sequencing experiments. In previous work, we presented a novel algorithm that allows the BWT of human genome scale data to be computed on very moderate hardware, thus enabling us to investigate the BWT as a tool for the compression of such datasets.

RESULTS

We first used simulated reads to explore the relationship between the level of compression and the error rate, the length of the reads and the level of sampling of the underlying genome and compare choices of second-stage compression algorithm. We demonstrate that compression may be greatly improved by a particular reordering of the sequences in the collection and give a novel 'implicit sorting' strategy that enables these benefits to be realized without the overhead of sorting the reads. With these techniques, a 45× coverage of real human genome sequence data compresses losslessly to under 0.5 bits per base, allowing the 135.3 Gb of sequence to fit into only 8.2 GB of space (trimming a small proportion of low-quality bases from the reads improves the compression still further). This is >4 times smaller than the size achieved by a standard BWT-based compressor (bzip2) on the untrimmed reads, but an important further advantage of our approach is that it facilitates the building of compressed full text indexes such as the FM-index on large-scale DNA sequence collections.

AVAILABILITY

Code to construct the BWT and SAP-array on large genomic datasets is part of the BEETL library, available as a github repository at https://github.com/BEETL/BEETL.

Computational identification of microRNA gene loci and precursor microRNA sequences in CHO cell lines

MicroRNAs (miRNAs) have recently entered Chinese hamster ovary (CHO) cell culture technology, due to their severe impact on the regulation of cellular phenotypes. Applications of miRNAs that are envisioned range from biomarkers of favorable phenotypes to cell engineering targets. These applications, however, require a profound knowledge of miRNA sequences and their genomic organization, which exceeds the currently available information of ~400 conserved mature CHO miRNA sequences. Based on these recently published sequences and two independent CHO-K1 genome assemblies, this publication describes the computational identification of CHO miRNA genomic loci. Using BLAST alignment, 415 previously reported CHO miRNAs were mapped to the reference genomes, and subsequently assigned to a distinct genomic miRNA locus. Sequences of the respective precursor-miRNAs were extracted from both reference genomes, folded in silico to verify correct structures and cross-compared. In the end, 212 genomic loci and pre-miRNA sequences representing 319 expressed mature miRNAs (approximately 50% of miRNAs represented matching pairs of 5' and 3' miRNAs) were submitted to the miRBase miRNA repository. As a proof-of-principle for the usability of the published genomic loci, four likely polycistronic miRNA cluster were chosen for PCR amplification using CHO-K1 and DHFR (-) genomic DNA. Overall, these data on the genomic context of miRNA expression in CHO will simplify the development of tools employing stable overexpression or deletion of miRNAs, allow the identification of miRNA promoters and improve detection methods such as microarrays.

Unraveling the Chinese hamster ovary cell line transcriptome by next-generation sequencing

The pyrosequencing technology from 454 Life Sciences and a novel assembly approach for cDNA sequences with the Newbler Assembler were used to achieve a major step forward to unravel the transcriptome of Chinese hamster ovary (CHO) cells. Normalized cDNA libraries originating from several cell lines and diverse culture conditions were sequenced and the resulting 1.84 million reads were assembled into 32,801 contiguous sequences, 29,184 isotigs, and 24,576 isogroups. A taxonomic classification of the isotigs showed that more than 70% of the assembled data is most similar to the transcriptome of Mus musculus, with most of the remaining isotigs being homologous to DNA sequences from Rattus norvegicus. Mapping of the CHO cell line contigs to the mouse transcriptome demonstrated that 9124 mouse transcripts, representing 6701 genes, are covered by more than 95% of their sequence length. Metabolic pathways of the central carbohydrate metabolism and biosynthesis routes of sugars used for protein N-glycosylation were reconstructed from the transcriptome data. All relevant genes representing major steps in the N-glycosylation pathway of CHO cells were detected. The present manuscript represents a data set of assembled and annotated genes for CHO cells that can now be used for a detailed analysis of the molecular functioning of CHO cell lines.

Next-generation sequencing of the Chinese hamster ovary microRNA transcriptome: Identification, annotation and profiling of microRNAs as targets for cellular engineering

Chinese hamster ovary (CHO) cells are the predominant cell factory for the production of recombinant therapeutic proteins. Nevertheless, the lack in publicly available sequence information is severely limiting advances in CHO cell biology, including the exploration of microRNAs (miRNA) as tools for CHO cell characterization and engineering. In an effort to identify and annotate both conserved and novel CHO miRNAs in the absence of a Chinese hamster genome, we deep-sequenced small RNA fractions of 6 biotechnologically relevant cell lines and mapped the resulting reads to an artificial reference sequence consisting of all known miRNA hairpins. Read alignment patterns and read count ratios of 5' and 3' mature miRNAs were obtained and used for an independent classification into miR/miR* and 5p/3p miRNA pairs and discrimination of miRNAs from other non-coding RNAs, resulting in the annotation of 387 mature CHO miRNAs. The quantitative content of next-generation sequencing data was analyzed and confirmed using qPCR, to find that miRNAs are markers of cell status. Finally, cDNA sequencing of 26 validated targets of miR-17-92 suggests conserved functions for miRNAs in CHO cells, which together with the now publicly available sequence information sets the stage for developing novel RNAi tools for CHO cell engineering.

TRUNCATULIX--a data warehouse for the legume community

BACKGROUND

Databases for either sequence, annotation, or microarray experiments data are extremely beneficial to the research community, as they centrally gather information from experiments performed by different scientists. However, data from different sources develop their full capacities only when combined. The idea of a data warehouse directly adresses this problem and solves it by integrating all required data into one single database - hence there are already many data warehouses available to genetics. For the model legume Medicago truncatula, there is currently no such single data warehouse that integrates all freely available gene sequences, the corresponding gene expression data, and annotation information. Thus, we created the data warehouse TRUNCATULIX, an integrative database of Medicago truncatula sequence and expression data.

RESULTS

The TRUNCATULIX data warehouse integrates five public databases for gene sequences, and gene annotations, as well as a database for microarray expression data covering raw data, normalized datasets, and complete expression profiling experiments. It can be accessed via an AJAX-based web interface using a standard web browser. For the first time, users can now quickly search for specific genes and gene expression data in a huge database based on high-quality annotations. The results can be exported as Excel, HTML, or as csv files for further usage.

CONCLUSION

The integration of sequence, annotation, and gene expression data from several Medicago truncatula databases in TRUNCATULIX provides the legume community with access to data and data mining capability not previously available. TRUNCATULIX is freely available at http://www.cebitec.uni-bielefeld.de/truncatulix/.