Assessment of the sensitivity and specificity of oligonucleotide (50mer) microarrays

Scalable design of orthogonal DNA barcode libraries

Orthogonal DNA barcode library design is an essential task in bioengineering. Here we present seqwalk, an efficient method for designing barcode libraries that satisfy a sequence symmetry minimization (SSM) heuristic for orthogonality, with theoretical guarantees of maximal or near-maximal library size under certain design constraints. Seqwalk encodes SSM constraints in a de Bruijn graph representation of sequence space, enabling the application of recent advances in discrete mathematics1 to the problem of orthogonal sequence design. We demonstrate the scalability of seqwalk by designing a library of >106 SSM-satisfying barcode sequences in less than 20 s on a standard laptop.

CyanoStrainChip: A Novel DNA Microarray Tool for High-Throughput Detection of Environmental Cyanobacteria at the Strain Level

Detecting cyanobacteria in environments is an important concern due to their crucial roles in ecosystems, and they can form blooms with the potential to harm humans and nonhuman entities. However, the most widely used methods for high-throughput detection of environmental cyanobacteria, such as 16S rRNA sequencing, typically provide above-species-level resolution, thereby disregarding intraspecific variation. To address this, we developed a novel DNA microarray tool, termed the CyanoStrainChip, that enables strain-level comprehensive profiling of environmental cyanobacteria. The CyanoStrainChip was designed to target 1277 strains; nearly all major groups of cyanobacteria are included by implementing 43,666 genome-wide, strain-specific probes. It demonstrated strong specificity by in vitro mock community experiments. The high correlation (Pearson's R > 0.97) between probe fluorescence intensities and the corresponding DNA amounts (ranging from 1-100 ng) indicated excellent quantitative capability. Consistent cyanobacterial profiles of field samples were observed by both the CyanoStrainChip and next-generation sequencing methods. Furthermore, CyanoStrainChip analysis of surface water samples in Lake Chaohu uncovered a high intraspecific variation of abundance change within the genus Microcystis between different severity levels of cyanobacterial blooms, highlighting two toxic Microcystis strains that are of critical concern for Lake Chaohu harmful blooms suppression. Overall, these results suggest a potential for CyanoStrainChip as a valuable tool for cyanobacterial ecological research and harmful bloom monitoring to supplement existing techniques.

DNA Sensor for the Detection of Brucella spp. Based on Magnetic Nanoparticle Markers

Due to the limitations of conventional Brucella detection methods, including safety concerns, long incubation times, and limited specificity, the development of a rapid, selective, and accurate technique for the early detection of Brucella in livestock animals is crucial to prevent the spread of the associated disease. In the present study, we introduce a magnetic nanoparticle marker-based biosensor using frequency mixing magnetic detection for point-of-care testing and quantification of Brucella DNA. Superparamagnetic nanoparticles were used as magnetically measured markers to selectively detect the target DNA hybridized with its complementary capture probes immobilized on a porous polyethylene filter. Experimental conditions like density and length of the probes, hybridization time and temperature, and magnetic binding specificity, sensitivity, and detection limit were investigated and optimized. Our sensor demonstrated a relatively fast detection time of approximately 10 min, with a detection limit of 55 copies (0.09 fM) when tested using DNA amplified from Brucella genetic material. In addition, the detection specificity was examined using gDNA from Brucella and other zoonotic bacteria that may coexist in the same niche, confirming the method's selectivity for Brucella DNA. Our proposed biosensor has the potential to be used for the early detection of Brucella bacteria in the field and can contribute to disease control measures.

Content-based filter queries on DNA data storage systems

Recent developments in DNA data storage systems have revealed the great potential to store large amounts of data at a very high density with extremely long persistence and low cost. However, despite recent contributions to robust data encoding, current DNA storage systems offer limited support for random access on DNA storage devices due to restrictive biochemical constraints. Moreover, state-of-the-art approaches do not support content-based filter queries on DNA storage. This paper introduces the first encoding for DNA that enables content-based searches on structured data like relational database tables. We provide the details of the methods for coding and decoding millions of directly accessible data objects on DNA. We evaluate the derived codes on real data sets and verify their robustness.

Short-term response to iron resupply in an iron-limited open ocean diatom reveals rapid decay of iron-responsive transcripts

In large areas of the ocean, iron concentrations are insufficient to promote phytoplankton growth. Numerous studies have been conducted to characterize the effect of iron on algae and how algae cope with fluctuating iron concentrations. Fertilization experiments in low-iron areas resulted primarily in diatom-dominated algal blooms, leading to laboratory studies on diatoms comparing low- and high-iron conditions. Here, we focus on the short-term temporal response following iron addition to an iron-starved open ocean diatom, Thalassiosira oceanica. We employed the NanoString platform and analyzed a high-resolution time series on 54 transcripts encoding proteins involved in photosynthesis, N-linked glycosylation, iron transport, as well as transcription factors. Nine transcripts were iron-responsive, with an immediate response to the addition of iron. The fastest response observed was the decrease in transcript levels of proteins involved in iron uptake, followed by an increase in transcript levels of iron-containing enzymes and a simultaneous decrease in the transcript levels of their iron-free replacement enzymes. The transcription inhibitor actinomycin D was used to understand the underlying mechanisms of the decrease of the iron-responsive transcripts and to determine their half-lives. Here, Mn-superoxide dismutase (Mn-SOD), plastocyanin (PETE), ferredoxin (PETF) and cellular repressor of EA1-stimulated genes (CREGx2) revealed longer than average half-lives. Four iron-responsive transcripts showed statistically significant differences in their decay rates between the iron-recovery samples and the actD treatment. These differences suggest regulatory mechanisms influencing gene transcription and mRNA stability. Overall, our study contributes towards a detailed understanding of diatom cell biology in the context of iron fertilization response and provides important observations to assess oceanic diatom responses following sudden changes in iron concentrations.

Circular RNA as a Novel Biomarker for Diagnosis and Prognosis and Potential Therapeutic Targets in Multiple Myeloma

Circular RNAs (circRNAs) are a novel type of covalently closed RNAs involved in several physiological and pathological processes. They display tissue-specific expression and are constant, abundant, and highly conserved, making them perfect markers for diagnosis and prognosis. Several studies have proposed that circRNAs are also differentially produced in malignancies where they have oncogenic effects. Furthermore, circRNAs affecting microRNAs modify the expression profile of several transcription factors which play essential roles in tumors. CircRNAs within the hematopoietic compartment were identified as modulators of mechanisms able to enhance or suppress tumor progression in blood malignancies. Moreover, several circRNAs were suggested to confer resistance to the conventional drugs employed in hematopoietic cancers. In this review, we highlight the growing role and the controlling mechanisms by which circRNAs modify multiple myeloma genesis. We propose that circRNAs can be considered as potential diagnostic and prognostic markers, can induce chemoresistance, and might represent novel therapeutic targets for multiple myeloma.

Spatial mapping of cancer tissues by OMICS technologies

Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding of cancers and help in the rapid detection of cancers with high accuracy and reliability. Significant advancements have been made in recent years in OMICS technologies, which possess the strong potential to be applied in the spatial mapping of biopsy tissue samples and their molecular profiling to a single-cell level. The clinical application of OMICS technologies in spatial profiling of cancer tissues is also advancing. The current review presents recent advancements and prospects of applying OMICS technologies to the spatial mapping of various analytes in cancer tissues. We benchmark the current state of the art in the field to advance existing OMICS technologies for high throughput spatial profiling. The factors taken into consideration include spatial resolution, types of biomolecules, number of different biomolecules that can be detected from the same assay, labeled versus label-free approaches, and approximate time required for each assay. Further advancements are still needed for the widespread application of OMICs technologies in performing fast and high throughput spatial mapping of cancer tissues as well as their effective use in research and clinical applications.

A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta

BACKGROUND

Human placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal DNAme in the uncomplicated term placenta (n = 343) using the Illumina 450K array.

RESULTS

At a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex and replicated in an independent cohort of samples (n = 293). Several of these differentially methylated CpG sites were part of larger correlated regions of sex differential DNAme. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Patterns of autosomal DNAme at these 162 CpGs were significantly associated with maternal age (in males) and newborn birthweight standard deviation (in females).

CONCLUSIONS

Our results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

Performance comparison of four types of target enrichment baits for exome DNA sequencing

BACKGROUND

Next-generation sequencing technology is developing rapidly and target capture sequencing has become an important technique. Several different platforms for library preparation and target capture with different bait types respectively are commercially available. Here we compare the performance of the four platforms with different bait types to find out their advantages and limitations. The purpose of this study is to help investigators and clinicians select the appropriate platform for their particular application and lay the foundation for the development of a better target capture platform for next-generation sequencing.

RESULTS

We formulate capture efficiency as a novel parameter that can be used to better evaluations of specificity and coverage depth among the different capture platforms. Target coverage, capture efficiency, GC bias, AT Dropout, sensitivity in single nucleotide polymorphisms, small insertions and deletions detection, and the feature of each platform were compared for low input samples. In general, all platforms perform well and small differences among them are revealed. In our results, RNA baits have stronger binding power than DNA baits, and with ultra deep sequencing, double stranded RNA baits perform better than single stranded RNA baits in all aspects. DNA baits got better performance in the region with high GC content and RNA baits got lower AT dropout suggesting that the binding power is different between DNA and RNA baits to genome regions with different characteristics.

CONCLUSIONS

The platforms with double stranded RNA baits have the most balanced capture performance. Our results show the key differences in performance among the four updated platforms with four different bait types. The better performance of double stranded RNA bait with ultra deep sequencing suggests that it may improve the sensitivity of ultra low frequent mutation detection. In addition, we further propose that the mixed baits of double stranded RNA and single stranded DNA may improve target capture performance.

Quantification of purified endogenous miRNAs with high sensitivity and specificity

MicroRNAs (miRNAs) are short (19-24 nt) non-coding RNAs that suppress the expression of protein coding genes at the post-transcriptional level. Differential expression profiles of miRNAs across a range of diseases have emerged as powerful biomarkers, making a reliable yet rapid profiling technique for miRNAs potentially essential in clinics. Here, we report an amplification-free multi-color single-molecule imaging technique that can profile purified endogenous miRNAs with high sensitivity, specificity, and reliability. Compared to previously reported techniques, our technique can discriminate single base mismatches and single-nucleotide 3'-tailing with low false positive rates regardless of their positions on miRNA. By preloading probes in Thermus thermophilus Argonaute (TtAgo), miRNAs detection speed is accelerated by more than 20 times. Finally, by utilizing the well-conserved linearity between single-molecule spot numbers and the target miRNA concentrations, the absolute average copy numbers of endogenous miRNA species in a single cell can be estimated. Thus our technique, Ago-FISH (Argonaute-based Fluorescence In Situ Hybridization), provides a reliable way to accurately profile various endogenous miRNAs on a single miRNA sensing chip.

Evaluation of Whole-Exome Enrichment Solutions: Lessons from the High-End of the Short-Read Sequencing Scale

Whole-exome sequencing has become a popular technique in research and clinical settings, assisting in disease diagnosis and increasing the understanding of disease pathogenesis. In this study, we aimed to compare common enrichment capture solutions available in the market. Peripheral blood-purified DNA samples were enriched with SureSelect^QXT V6 (Agilent) and various Illumina solutions: TruSeq DNA Nano, TruSeq DNA Exome, Nextera DNA Exome, and Illumina DNA Prep with Enrichment, and sequenced on a HiSeq 4000. We found that their percentage of duplicate reads was as much as 2 times higher than previously reported values for the previous HiSeq series. SureSelect^QXT and Illumina DNA Prep with Enrichment showed the best average on-target coverage, which improved when off-target regions were included. At high coverage levels and in shared bases, these two solutions and TruSeq DNA Exome provided three of the best performances. With respect to the number of small variants detected, SureSelect^QXT presented the lowest number of detected variants in target regions. When off-target regions were considered, its ability equalized to other solutions. Our results show SureSelect^QXT and Illumina DNA Prep with Enrichment to be the best enrichment capture solutions.

Ribo-Pop: simple, cost-effective, and widely applicable ribosomal RNA depletion

The measurement of RNA abundance derived from massively parallel sequencing experiments is an essential technique. Methods that reduce ribosomal RNA levels are usually required prior to sequencing library construction because ribosomal RNA typically comprises the vast majority of a total RNA sample. For some experiments, ribosomal RNA depletion is favored over poly(A) selection because it offers a more inclusive representation of the transcriptome. However, methods to deplete ribosomal RNA are generally proprietary, complex, inefficient, applicable to only specific species, or compatible with only a narrow range of RNA input levels. Here, we describe Ribo-Pop (ribosomal RNA depletion for popular use), a simple workflow and antisense oligo design strategy that we demonstrate works over a wide input range and can be easily adapted to any organism with a sequenced genome. We provide a computational pipeline for probe selection, a streamlined 20-min protocol, and ready-to-use oligo sequences for several organisms. We anticipate that our simple and generalizable "open source" design strategy would enable virtually any laboratory to pursue full transcriptome sequencing in their organism of interest with minimal time and resource investment.

The role of long non-coding RNAs and downstream signaling pathways in leukemia progression

The study of long non-coding RNAs (lncRNA) is a newly established field and our knowledge about them is rapidly growing. These kinds of RNAs are unchanged parts of the genome throughout evolution, that modulate cell growth, differentiation, and apoptosis during diverse physiological and pathological processes including leukemia development. They have the capability to be useful biomarkers for the diagnosis, clinical typing, prognosis, as well as potential therapeutic targets. In this study, we summarized the role of lncRNAs in the expression and function of white blood cells and oncogenic transformation into four main types of leukemia.

A DNA Switch for Detecting Single Nucleotide Polymorphism within a Long DNA Sequence Under Denaturing Conditions

DNA detection is usually conducted under nondenaturing conditions to favor the formation of Watson-Crick base-paring interactions. However, although such a setting is excellent for distinguishing a single-nucleotide polymorphism (SNP) within short DNA sequences (15-25 nucleotides), it does not offer a good solution to SNP detection within much longer sequences. Here we report on a new detection method capable of detecting SNP in a DNA sequence containing 35-90 nucleotides. This is achieved through incorporating into the recognition DNA sequence a previously discovered DNA molecule that forms a stable G-quadruplex in the presence of 7 molar urea, a known condition for denaturing DNA structures. The systems are configured to produce both colorimetric and fluorescent signals upon target binding.

Multi-level patterning nucleic acid photolithography

The versatile and tunable self-assembly properties of nucleic acids and engineered nucleic acid constructs make them invaluable in constructing microscale and nanoscale devices, structures and circuits. Increasing the complexity, functionality and ease of assembly of such constructs, as well as interfacing them to the macroscopic world requires a multifaceted and programmable fabrication approach that combines efficient and spatially resolved nucleic acid synthesis with multiple post-synthetic chemical and enzymatic modifications. Here we demonstrate a multi-level photolithographic patterning approach that starts with large-scale in situ surface synthesis of natural, modified or chimeric nucleic acid molecular structures and is followed by chemical and enzymatic nucleic acid modifications and processing. The resulting high-complexity, micrometer-resolution nucleic acid surface patterns include linear and branched structures, multi-color fluorophore labeling and programmable targeted oligonucleotide immobilization and cleavage.

Cluster oligonucleotide signatures for rapid identification by sequencing

BACKGROUND

Oligonucleotide signatures (signatures) have been widely used for studying microbial diversity and function in wet-lab settings, but using them for accurate in silico identification of organisms from high-throughput sequencing (HTS) data is only a proof of concept. Existing signature design programs for sequence signatures (signatures matching exactly one sequence) or clade signatures (signatures matching every sequence in a phylogenetic clade) are not able to identify all possible polymorphic sites for sequences with high similarity and perform poorly when handling large genome sequencing datasets.

RESULTS

We introduce cluster signatures: subsequences that match perfectly and exclusively any group of sequences in a data set. Cluster signatures provide complete recall for primer/probe design and increased discrimination between sequences beyond that of clade signatures. Using cluster signatures for in silico identification of HTS targets achieves good precision/recall and running time performance. This method has been implemented into an open source tool, the Automated Oligonucleotide Design Pipeline (adop), included in supplementary material and available at: https://bitbucket.org/wenchen_aafc/aodp_v2.0_release .

CONCLUSIONS

Cluster signatures provide a rapid and universal analysis tool to identify all possible short diagnostic DNA markers and variants from any DNA sequencing dataset. They are particularly useful in discriminating genetic material from closely related organisms and in detecting deleterious mutations in highly or perfectly conserved genomic sites.

Methodological Approaches to Study Extracellular Vesicle miRNAs in Epstein⁻Barr Virus-Associated Cancers

Epstein Barr-virus (EBV) was the first virus identified to be associated with human cancer in 1964 and is found ubiquitously throughout the world's population. It is now established that EBV contributes to the development and progression of multiple human cancers of both lymphoid and epithelial cell origins. EBV encoded miRNAs play an important role in tumor proliferation, angiogenesis, immune escape, tissue invasion, and metastasis. Recently, EBV miRNAs have been found to be released from infected cancer cells in extracellular vesicles (EVs) and regulate gene expression in neighboring uninfected cells present in the tumor microenvironment and possibly at distal sites. As EVs are abundant in many biological fluids, the viral and cellular miRNAs present within EBV-modified EVs may serve as noninvasion markers for cancer diagnosis and prognosis. In this review, we discuss recent advances in EV isolation and miRNA detection, and provide a complete workflow for EV purification from plasma and deep-sequencing for biomarker discovery.

Long Non-Coding RNAs Guide the Fine-Tuning of Gene Regulation in B-Cell Development and Malignancy

With the introduction of next generation sequencing methods, such as RNA sequencing, it has become apparent that alterations in the non-coding regions of our genome are important in the development of cancer. Particularly interesting is the class of long non-coding RNAs (lncRNAs), including the recently described subclass of circular RNAs (circRNAs), which display tissue- and cell-type specific expression patterns and exert diverse regulatory functions in the cells. B-cells undergo complex and tightly regulated processes in order to develop from antigen naïve cells residing in the bone marrow to the highly diverse and competent effector cells circulating in peripheral blood. These processes include V(D)J recombination, rapid proliferation, somatic hypermutation and clonal selection, posing a risk of malignant transformation at each step. The aim of this review is to provide insight into how lncRNAs including circRNAs, participate in normal B-cell differentiation, and how deregulation of these molecules is involved in the development of B-cell malignancies. We describe the prognostic value and functional significance of specific deregulated lncRNAs in diseases such as acute lymphoblastic leukemia, chronic lymphocytic leukemia, mantle cell lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, Burkitt lymphoma and multiple myeloma, and we provide an overview of the current knowledge on the role of circRNAs in these diseases.

FibroChip, a Functional DNA Microarray to Monitor Cellulolytic and Hemicellulolytic Activities of Rumen Microbiota

Ruminants fulfill their energy needs for growth primarily through microbial breakdown of plant biomass in the rumen. Several biotic and abiotic factors influence the efficiency of fiber degradation, which can ultimately impact animal productivity and health. To provide more insight into mechanisms involved in the modulation of fibrolytic activity, a functional DNA microarray targeting genes encoding key enzymes involved in cellulose and hemicellulose degradation by rumen microbiota was designed. Eight carbohydrate-active enzyme (CAZyme) families (GH5, GH9, GH10, GH11, GH43, GH48, CE1, and CE6) were selected which represented 392 genes from bacteria, protozoa, and fungi. The DNA microarray, designated as FibroChip, was validated using targets of increasing complexity and demonstrated sensitivity and specificity. In addition, FibroChip was evaluated for its explorative and semi-quantitative potential. Differential expression of CAZyme genes was evidenced in the rumen bacterium Fibrobacter succinogenes S85 grown on wheat straw or cellobiose. FibroChip was used to identify the expressed CAZyme genes from the targeted families in the rumen of a cow fed a mixed diet based on grass silage. Among expressed genes, those encoding GH43, GH5, and GH10 families were the most represented. Most of the F. succinogenes genes detected by the FibroChip were also detected following RNA-seq analysis of RNA transcripts obtained from the rumen fluid sample. Use of the FibroChip also indicated that transcripts of fiber degrading enzymes derived from eukaryotes (protozoa and anaerobic fungi) represented a significant proportion of the total microbial mRNA pool. FibroChip represents a reliable and high-throughput tool that enables researchers to monitor active members of fiber degradation in the rumen.

Comparison of mitochondrial gene expression and polysome loading in different tobacco tissues

BACKGROUND

To investigate translational regulation of gene expression in plant mitochondria, a mitochondrial polysome isolation protocol was established for tobacco to investigate polysomal mRNA loading as a proxy for translational activity. Furthermore, we developed an oligonucleotide based microarray platform to determine the level of Nicotiana tabacum and Arabidopsis thaliana mitochondrial mRNA.

RESULTS

Microarray analysis of free and polysomal mRNAs was used to characterize differences in the levels of free transcripts and ribosome-bound mRNAs in various organs of tobacco plants. We have observed higher mitochondrial transcript levels in young leaves, flowers and floral buds as compared to fully expanded leaves and roots. A similar pattern of abundance was observed for ribosome-bound mitochondrial mRNAs in these tissues. However, the accumulation of the mitochondrial protein COX2 was found to be inversely related to that of its ribosome-bound mRNA.

CONCLUSIONS

Our results indicate that the association of mitochondrial mRNAs to ribosomes is largely determined by the total transcript level of a gene. However, at least for Cox2, we demonstrated that the level of ribosome-bound mRNA is not reflected by the amount of COX2 protein.

Targeted sequencing of both DNA strands barcoded and captured individually by RNA probes to identify genome-wide ultra-rare mutations

Next Generation Sequencing (NGS) has been widely implemented in biological research and has made a profound impact on patient care. One of the essential NGS applications is to identify disease-causing sequence variants, where high coverage and accuracy are needed. Here, we reported a novel NGS pipeline, termed a Sequencing System of Digitalized Barcode Encrypted Single-stranded Library from Extremely Low (quality and quantity) DNA Input with Probe-based DNA Enrichment by RNA probes targeting DNA duplex (DEEPER-Seq). This method combines an ultra-sensitive single-stranded library construction with barcoding error correction, termed DEEPER-Library; and a DNA capture approach using RNA probes targeting both DNA strands, termed DEEPER-Capture. DEEPER-Seq can create NGS libraries from as little as 20 pg DNA with PCR error correcting capabilities, and capture target sequences at an average ratio of 29.2% by targeting both DNA strands simultaneously with an over 98.6% coverage. Our method tags and sequences each of the two strands of a DNA duplex independently and only scores mutations that are found at the same position in both strands, which allows us to identify mutations with allelic fractions down to 0.03% in a whole exome sequencing (WES) study with a background error rate of one artificial error per 4.8 × 10⁹ nucleotides.

Novel metrics to measure coverage in whole exome sequencing datasets reveal local and global non-uniformity

Whole Exome Sequencing (WES) is a powerful clinical diagnostic tool for discovering the genetic basis of many diseases. A major shortcoming of WES is uneven coverage of sequence reads over the exome targets contributing to many low coverage regions, which hinders accurate variant calling. In this study, we devised two novel metrics, Cohort Coverage Sparseness (CCS) and Unevenness (UE) Scores for a detailed assessment of the distribution of coverage of sequence reads. Employing these metrics we revealed non-uniformity of coverage and low coverage regions in the WES data generated by three different platforms. This non-uniformity of coverage is both local (coverage of a given exon across different platforms) and global (coverage of all exons across the genome in the given platform). The low coverage regions encompassing functionally important genes were often associated with high GC content, repeat elements and segmental duplications. While a majority of the problems associated with WES are due to the limitations of the capture methods, further refinements in WES technologies have the potential to enhance its clinical applications.

Transcriptome analysis of mycobacteria in sputum samples of pulmonary tuberculosis patients

Pulmonary tuberculosis, the disease caused by Mycobacterium tuberculosis, still retains a top rank among the deadliest communicable diseases. Sputum expectorated during the disease continues to be a primary diagnostic specimen and also serves as a reservoir of bacteria. The expression pattern of mycobacteria in sputum will lead to an insight into bacterial adaptation at the most highly transmissible stage of infection and can also help in identifying newer diagnostic as well as drug targets. Thus, in the present study, a whole genome microarray of Mycobacterium tuberculosis was used to elucidate the transcriptional profile of mycobacteria in the sputum samples of smear positive pulmonary tuberculosis patients. Overall, the mycobacteria in sputum appeared to be in a low energy and low replicative state as compared to in vitro grown log phase M. tb with downregulation of genes involved in ATP synthesis, aerobic respiration and translational machinery. Simultaneously, downregulation was also seen in the genes involved in secretion machinery of mycobacteria along with the downregulation of genes involved in the synthesis of phthiocerol dimycocerosate and phenol glycolipids. In contrast, the majority of the genes which showed an upregulation in sputum mycobacteria were of unknown function. Further identification of these genes may provide new insights into the mycobacterial behavior during this phase of infection and may help in deciphering candidates for development of better diagnostic and drug candidates.

Differentiation of ncRNAs from small mRNAs in Escherichia coli O157:H7 EDL933 (EHEC) by combined RNAseq and RIBOseq - ryhB encodes the regulatory RNA RyhB and a peptide, RyhP

Background

While NGS allows rapid global detection of transcripts, it remains difficult to distinguish ncRNAs from short mRNAs. To detect potentially translated RNAs, we developed an improved protocol for bacterial ribosomal footprinting (RIBOseq). This allowed distinguishing ncRNA from mRNA in EHEC. A high ratio of ribosomal footprints per transcript (ribosomal coverage value, RCV) is expected to indicate a translated RNA, while a low RCV should point to a non-translated RNA.

Results

Based on their low RCV, 150 novel non-translated EHEC transcripts were identified as putative ncRNAs, representing both antisense and intergenic transcripts, 74 of which had expressed homologs in E. coli MG1655. Bioinformatics analysis predicted statistically significant target regulons for 15 of the intergenic transcripts; experimental analysis revealed 4-fold or higher differential expression of 46 novel ncRNA in different growth media. Out of 329 annotated EHEC ncRNAs, 52 showed an RCV similar to protein-coding genes, of those, 16 had RIBOseq patterns matching annotated genes in other enterobacteriaceae, and 11 seem to possess a Shine-Dalgarno sequence, suggesting that such ncRNAs may encode small proteins instead of being solely non-coding. To support that the RIBOseq signals are reflecting translation, we tested the ribosomal-footprint covered ORF of ryhB and found a phenotype for the encoded peptide in iron-limiting condition.

Conclusion

Determination of the RCV is a useful approach for a rapid first-step differentiation between bacterial ncRNAs and small mRNAs. Further, many known ncRNAs may encode proteins as well.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3586-9) contains supplementary material, which is available to authorized users.

Evolution of High-Sensitivity Microarray Technology

Microarray technology is a multiplex analytical technique for the detection of many different analytes in a mixture of biomolecules. The detection limits for each of the analytes for which the array is designed depend on a multiplicity of reaction parameters, the array itself, and profoundly on the label and detection technology employed. Significant improvements in assay sensitivity have been achieved by optimizing all steps that affect the generation of signal and noise. Nanoparticle technology brings a new dimension to this technology by providing not only higher sensitivity but also improved specificity for hybridization-based microarray assay systems.

Challenges for MicroRNA Microarray Data Analysis

Microarray is a high throughput discovery tool that has been broadly used for genomic research. Probe-target hybridization is the central concept of this technology to determine the relative abundance of nucleic acid sequences through fluorescence-based detection. In microarray experiments, variations of expression measurements can be attributed to many different sources that influence the stability and reproducibility of microarray platforms. Normalization is an essential step to reduce non-biological errors and to convert raw image data from multiple arrays (channels) to quality data for further analysis. In general, for the traditional microarray analysis, most established normalization methods are based on two assumptions: (1) the total number of target genes is large enough (>10,000); and (2) the expression level of the majority of genes is kept constant. However, microRNA (miRNA) arrays are usually spotted in low density, due to the fact that the total number of miRNAs is less than 2,000 and the majority of miRNAs are weakly or not expressed. As a result, normalization methods based on the above two assumptions are not applicable to miRNA profiling studies. In this review, we discuss a few representative microarray platforms on the market for miRNA profiling and compare the traditional methods with a few novel strategies specific for miRNA microarrays.

Low Input Whole-Exome Sequencing to Determine the Representation of the Tumor Exome in Circulating DNA of Non-Small Cell Lung Cancer Patients

Circulating cell-free DNA (cfDNA) released from cancerous tissues has been found to harbor tumor-associated alterations and to represent the molecular composition of the tumor. Recent advances in technologies, especially in next-generation sequencing, enable the analysis of low amounts of cfDNA from body fluids. We analyzed the exomes of tumor tissue and matched serum samples to investigate the molecular representation of the tumor exome in cfDNA. To this end, we implemented a workflow for sequencing of cfDNA from low serum volumes (200 μl) and performed whole-exome sequencing (WES) of serum and matched tumor tissue samples from six non-small cell lung cancer (NSCLC) patients and two control sera. Exomes, including untranslated regions (UTRs) of cfDNA were sequenced with an average coverage of 68.5x. Enrichment efficiency, target coverage, and sequencing depth of cfDNA reads were comparable to those from matched tissues. Discovered variants were compared between serum and tissue as well as to the COSMIC database of known mutations. Although not all tissue variants could be confirmed in the matched serum, up to 57% of the tumor variants were reflected in matched cfDNA with mutations in PIK3CA, ALK, and PTEN as well as variants at COSMIC annotated sites in all six patients analyzed. Moreover, cfDNA revealed a mutation in MTOR, which was not detected in the matched tissue, potentially from an untested region of the heterogeneous primary tumor or from a distant metastatic clone. WES of cfDNA may provide additional complementary molecular information about clinically relevant mutations and the clonal heterogeneity of the tumors.

Assessing the reproducibility of exome copy number variations predictions

Background

Reproducibility is receiving increased attention across many domains of science and genomics is no exception. Efforts to identify copy number variations (CNVs) from exome sequence (ES) data have been increasing. Many algorithms have been published to discover CNVs from exomes and a major challenge is the reproducibility in other datasets. Here we test exome CNV calling reproducibility under three conditions: data generated by different sequencing centers; varying sample sizes; and varying capture methodology.

Methods

Four CNV tools were tested: eXome Hidden Markov Model (XHMM), Copy Number Inference From Exome Reads (CoNIFER), EXCAVATOR, and Copy Number Analysis for Targeted Resequencing (CONTRA). To examine the reproducibility, we ran the callers on four datasets, varying sample sizes of N = 10, 30, 75, 100, 300, and data with different capture methodology. We examined the false negative (FN) calls and false positive (FP) calls for potential limitations of the CNV callers. The positive predictive value (PPV) was measured by checking the CNV call concordance against single nucleotide polymorphism array.

Results

Using independently generated datasets, we examined the PPV for each dataset and observed wide range of PPVs. The PPV values were highly data dependent (p <0.001). For the sample sizes and capture method analyses, we tested the callers in triplicates. Both analyses resulted in wide ranges of PPVs, even for the same test. Interestingly, negative correlations between the PPV and the sample sizes were observed for CoNIFER (ρ = –0.80). Further examination of FN calls showed that 44 % of these were missed by all callers and were attributed to the CNV size (46 % spanned ≤3 exons). Overlap of the FP calls showed that FPs were unique to each caller, indicative of algorithm dependency.

Conclusions

Our results demonstrate that further improvements in CNV callers are necessary to improve reproducibility and to include wider spectrum of CNVs (including the small CNVs). These CNV callers should be evaluated on multiple independent, heterogeneously generated datasets of varying size to increase robustness and utility. These approaches to the evaluation of exome CNV are essential to support wide utility and applicability of CNV discovery in exome studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0336-6) contains supplementary material, which is available to authorized users.

Expressed miRNAs target feather related mRNAs involved in cell signaling, cell adhesion and structure during chicken epidermal development

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression at the post-transcriptional level. Previous studies have shown that miRNA regulation contributes to a diverse set of processes including cellular differentiation and morphogenesis which leads to the creation of different cell types in multicellular organisms and is thus key to animal development. Feathers are one of the most distinctive features of extant birds and are important for multiple functions including flight, thermal regulation, and sexual selection. However, the role of miRNAs in feather development has been woefully understudied despite the identification of cell signaling pathways, cell adhesion molecules and structural genes involved in feather development. In this study, we performed a microarray experiment comparing the expression of miRNAs and mRNAs among three embryonic stages of development and two tissues (scutate scale and feather) of the chicken. We combined this expression data with miRNA target prediction tools and a curated list of feather related genes to produce a set of 19 miRNA-mRNA duplexes. These targeted mRNAs have been previously identified as important cell signaling and cell adhesion genes as well as structural genes involved in feather and scale morphogenesis. Interestingly, the miRNA target site of the cell signaling pathway gene, Aldehyde Dehydrogenase 1 Family, Member A3 (ALDH1A3), is unique to birds indicating a novel role in Aves. The identified miRNA target site of the cell adhesion gene, Tenascin C (TNC), is only found in specific chicken TNC splice variants that are differentially expressed in developing scutate scale and feather tissue indicating an important role of miRNA regulation in epidermal differentiation. Additionally, we found that β-keratins, a major structural component of avian and reptilian epidermal appendages, are targeted by multiple miRNA genes. In conclusion, our work provides quantitative expression data on miRNAs and mRNAs during feather and scale development and has produced a highly diverse, but manageable list of miRNA-mRNA duplexes for future validation experiments.

Thermodynamically optimal whole-genome tiling microarray design and validation

Background

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations.

Findings

Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome.

Conclusions

This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-016-2113-4) contains supplementary material, which is available to authorized users.

Development and validation of a custom microarray for global transcriptome profiling of the fungus Aspergillus nidulans

Transcriptome profiling is a powerful tool for identifying gene networks from whole genome expression analysis in many living species. Here is described the first extensively characterized platform using Agilent microarray technology for transcriptome analysis in the filamentous fungus Aspergillus (Emericella) nidulans. We developed and validated a reliable gene expression microarray in 8 × 15 K format, with predictive and experimental data establishing its specificity and sensitivity. Either one or two 60-mer oligonucleotide probes were selected for each of 10,550 nuclear as well as 20 mitochondrial coding sequences. More than 99 % of probes were predicted to hybridize with 100 % identity to their aimed specific A. nidulans target only. Probe sensitivity was supported by a highly narrow distribution of melting temperatures together with thermodynamic features, which strongly favored probe-target perfect match hybridization, in comparison with predicted secondary structures. Array quality was evaluated through transcriptome comparison of two A. nidulans strains, differing by the presence or not of Escherichia coli LacZ transgene. High signal-to-noise ratios were measured, and signal reproducibility was established at intra-probe and inter-probe levels. Reproducibility of microarray performances was assessed by high correlation between two-color dye signals and between technical replicates. Results were confirmed by RT-qPCR analysis on five genes. Though it covers 100 % of the A. nidulans targeted coding sequences, this low density array allows limited experimental costs and simplified data analysis process, making it suitable for studying gene expression in this model organism through large numbers of experimental conditions, in basic, biomedical or industrial microbiology research fields.

Probe Design Strategies for Oligonucleotide Microarrays

Oligonucleotide microarrays have been widely used for gene detection and/or quantification of gene expression in various samples ranging from a single organism to a complex microbial assemblage. The success of a microarray experiment, however, strongly relies on the quality of designed probes. Consequently, probe design is of critical importance and therefore multiple parameters should be considered for each probe in order to ensure high specificity, sensitivity, and uniformity as well as potentially quantitative power. Moreover, to assess the complete gene repertoire of complex biological samples such as those studied in the field of microbial ecology, exploratory probe design strategies must be also implemented to target not-yet-described sequences. To design such probes, two algorithms, KASpOD and HiSpOD, have been developed and they are available via two user-friendly web services. Here, we describe the use of this software necessary for the design of highly effective probes especially in the context of microbial oligonucleotide microarrays by taking into account all the crucial parameters.

Comprehensive genetic exploration of skeletal dysplasia using targeted exome sequencing

PURPOSE

The purpose of this study was to evaluate the clinical utility of targeted exome sequencing (TES) as a molecular diagnostic tool for patients with skeletal dysplasia.

METHODS

A total of 185 patients either diagnosed with or suspected to have skeletal dysplasia were recruited over a period of 3 years. TES was performed for 255 genes associated with the pathogenesis of skeletal dysplasia, and candidate variants were selected using a bioinformatics analysis. All candidate variants were confirmed by Sanger sequencing, correlation with the phenotype, and a cosegregation study in the family.

RESULTS

TES detected "confirmed" or "highly likely" pathogenic sequence variants in 74% (71 of 96) of cases in the assured clinical diagnosis category and 20.3% (13 of 64 cases) of cases in the uncertain clinical diagnosis category. TES successfully detected pathogenic variants in all 25 cases of previously known genotypes. The data also suggested a copy-number variation that led to a molecular diagnosis.

CONCLUSION

This study demonstrates the feasibility of TES for the molecular diagnosis of skeletal dysplasia. However, further confirmation is needed for a final molecular diagnosis, including Sanger sequencing of candidate variants with suspected, poorly captured exons.Genet Med 18 6, 563-569.

Investigation of Human Cancers for Retrovirus by Low-Stringency Target Enrichment and High-Throughput Sequencing

Although nearly one fifth of all human cancers have an infectious aetiology, the causes for the majority of cancers remain unexplained. Despite the enormous data output from high-throughput shotgun sequencing, viral DNA in a clinical sample typically constitutes a proportion of host DNA that is too small to be detected. Sequence variation among virus genomes complicates application of sequence-specific, and highly sensitive, PCR methods. Therefore, we aimed to develop and characterize a method that permits sensitive detection of sequences despite considerable variation. We demonstrate that our low-stringency in-solution hybridization method enables detection of <100 viral copies. Furthermore, distantly related proviral sequences may be enriched by orders of magnitude, enabling discovery of hitherto unknown viral sequences by high-throughput sequencing. The sensitivity was sufficient to detect retroviral sequences in clinical samples. We used this method to conduct an investigation for novel retrovirus in samples from three cancer types. In accordance with recent studies our investigation revealed no retroviral infections in human B-cell lymphoma cells, cutaneous T-cell lymphoma or colorectal cancer biopsies. Nonetheless, our generally applicable method makes sensitive detection possible and permits sequencing of distantly related sequences from complex material.

ApiAP2 Factors as Candidate Regulators of Stochastic Commitment to Merozoite Production in Theileria annulata

Background

Differentiation of one life-cycle stage to the next is critical for survival and transmission of apicomplexan parasites. A number of studies have shown that stage differentiation is a stochastic process and is associated with a point that commits the cell to a change over in the pattern of gene expression. Studies on differentiation to merozoite production (merogony) in T. annulata postulated that commitment involves a concentration threshold of DNA binding proteins and an auto-regulatory loop.

Principal Findings

In this study ApiAP2 DNA binding proteins that show changes in expression level during merogony of T. annulata have been identified. DNA motifs bound by orthologous domains in Plasmodium were found to be enriched in upstream regions of stage-regulated T. annulata genes and validated as targets for the T. annulata AP2 domains by electrophoretic mobility shift assay (EMSA). Two findings were of particular note: the gene in T. annulata encoding the orthologue of the ApiAP2 domain in the AP2-G factor that commits Plasmodium to gametocyte production, has an expression profile indicating involvement in transmission of T. annulata to the tick vector; genes encoding related domains that bind, or are predicted to bind, sequence motifs of the type 5'-(A)CACAC(A) are implicated in differential regulation of gene expression, with one gene (TA11145) likely to be preferentially up-regulated via auto-regulation as the cell progresses to merogony.

Conclusions

We postulate that the Theileria factor possessing the AP2 domain orthologous to that of Plasmodium AP2-G may regulate gametocytogenesis in a similar manner to AP2-G. In addition, paralogous ApiAP2 factors that recognise 5'-(A)CACAC(A) type motifs could operate in a competitive manner to promote reversible progression towards the point that commits the cell to undergo merogony. Factors possessing AP2 domains that bind (or are predicted to bind) this motif are present in the vector-borne genera Theileria, Babesia and Plasmodium, and other Apicomplexa; leading to the proposal that the mechanisms that control stage differentiation will show a degree of conservation.

The ability of vector-borne Apicomplexan parasites (Babesia, Plasmodium and Theileria) to change from one life-cycle stage to the next is critical for establishment of infection and transmission to new hosts. Stage differentiation steps of both Plasmodium and Theileria are known to involve stochastic transition through an intermediate form to a point that commits the cell to generate the next stage in the life-cycle. In this study we have identified genes encoding ApiAP2 DNA binding proteins in Theileria annulata that are differentially expressed during differentiation from the macroschizont stage, through merozoite production (merogony) to the piroplasm stage. The results provide evidence that the ApiAp2 factor in Theileria that possesses the orthologue of the Plasmodium AP2-G domain may also operate to regulate gametocytogenesis, and that progression to merogony is promoted by the ability of a merozoite DNA binding protein to preferentially up-regulate its own production. In addition, identification of multiple ApiAP2 DNA binding domains that bind related motifs within and across vector-borne Apicomplexan genera lead to the proposal that the mechanisms that promote the transition from asexual to sexual replication will show a degree of conservation.

Development of a DNA-based microarray for the detection of zoonotic pathogens in rodent species

The demand for diagnostic tools that allow simultaneous screening of samples for multiple pathogens is increasing because they overcome the limitations of other methods, which can only screen for a single or a few pathogens at a time. Microarrays offer the advantages of being capable to test a large number of samples simultaneously, screening for multiple pathogen types per sample and having comparable sensitivity to existing methods such as PCR. Array design is often considered the most important process in any microarray experiment and can be the deciding factor in the success of a study. There are currently no microarrays for simultaneous detection of rodent-borne pathogens. The aim of this report is to explicate the design, development and evaluation of a microarray platform for use as a screening tool that combines ease of use and rapid identification of a number of rodent-borne pathogens of zoonotic importance. Nucleic acid was amplified by multiplex biotinylation PCR prior to hybridisation onto microarrays. The array sensitivity was comparable to standard PCR, though less sensitive than real-time PCR. The array presented here is a prototype microarray identification system for zoonotic pathogens that can infect rodent species.

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We have developed a microarray to detect zoonotic pathogens in rodent species.

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The design stage of a microarray experiment is crucial for a successful experiment.

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We examined the difference between amplification methods prior to hybridisation.

DNA hybridization on silicon nanowire platform prepared by glancing angle deposition and metal assisted chemical etching process

Porous nanowire surface provides high capacity for oligonucleotide hybridization.

Detection of genetically modified crops using multiplex asymmetric polymerase chain reaction and asymmetric hyperbranched rolling circle amplification coupled with reverse dot blot

To meet the ever-increasing demand for detection of genetically modified crops (GMCs), low-cost, high-throughput and high-accuracy detection assays are needed. The new multiplex asymmetric polymerase chain reaction and asymmetric hyper-branched rolling circle amplification coupled with reverse dot blot (RDB) systems were developed to detect GMCs. Thirteen oligonucleotide probes were designed to identify endogenous targets (Lec1, Hmg and Sad1), event-specific targets (RRS-5C, RRS-3C, Bt176-3C and MON810-3C), screening targets (35S promoter and NOS terminator), and control targets (18S and PLX). Optimised conditions were as follows: tailed hybridization probes (1-2 pmol/l) were immobilized on a membrane by baking for 2h, and a 10:1 ratio of forward to reverse primers was used. The detection limits were 0.1 μg/l of 2% RRS and 0.5 ng/l of DNA from genetically modified (GM) soybean. These results indicate that the RDB assay could be used to detect multiplex target genes of GMCs rapidly and inexpensively.

Copy number variation in the horse genome

We constructed a 400K WG tiling oligoarray for the horse and applied it for the discovery of copy number variations (CNVs) in 38 normal horses of 16 diverse breeds, and the Przewalski horse. Probes on the array represented 18,763 autosomal and X-linked genes, and intergenic, sub-telomeric and chrY sequences. We identified 258 CNV regions (CNVRs) across all autosomes, chrX and chrUn, but not in chrY. CNVs comprised 1.3% of the horse genome with chr12 being most enriched. American Miniature horses had the highest and American Quarter Horses the lowest number of CNVs in relation to Thoroughbred reference. The Przewalski horse was similar to native ponies and draft breeds. The majority of CNVRs involved genes, while 20% were located in intergenic regions. Similar to previous studies in horses and other mammals, molecular functions of CNV-associated genes were predominantly in sensory perception, immunity and reproduction. The findings were integrated with previous studies to generate a composite genome-wide dataset of 1476 CNVRs. Of these, 301 CNVRs were shared between studies, while 1174 were novel and require further validation. Integrated data revealed that to date, 41 out of over 400 breeds of the domestic horse have been analyzed for CNVs, of which 11 new breeds were added in this study. Finally, the composite CNV dataset was applied in a pilot study for the discovery of CNVs in 6 horses with XY disorders of sexual development. A homozygous deletion involving AKR1C gene cluster in chr29 in two affected horses was considered possibly causative because of the known role of AKR1C genes in testicular androgen synthesis and sexual development. While the findings improve and integrate the knowledge of CNVs in horses, they also show that for effective discovery of variants of biomedical importance, more breeds and individuals need to be analyzed using comparable methodological approaches.

Genomes of individuals in a species vary in many ways, one of which is DNA copy number variation (CNV). This includes deletions, duplications, and complex rearrangements typically larger than 50 base-pairs. CNVs are part of normal genetic variation contributing to phenotypic diversity but can also be pathogenic and associated with diseases and disorders. In order to distinguish between the two, detailed knowledge about CNVs in the species of interest is needed. Here we studied the genomes of 38 normal horses of 16 diverse breeds, and identified 258 CNV regions. We integrated our findings with previously published horse CNVs and generated a composite dataset of ∼1400 CNVRs. Despite this large number, our analysis shows that CNV research in horses needs further improvement because the current data are based on 10% of horse breeds and that most CNVRs are study-specific and require validation. Finally, we analyzed CNVs in horses with disorders of sexual development and found in two male pseudo-hermaphrodites a large deletion disrupting a group of genes involved in sex hormone metabolism and sexual differentiation. The findings underline the possible role of CNVs in complex disorders such as development and reproduction.

Species and gene divergence in Littorina snails detected by array comparative genomic hybridization

Background

Array comparative genomic hybridization (aCGH) is commonly used to screen different types of genetic variation in humans and model species. Here, we performed aCGH using an oligonucleotide gene-expression array for a non-model species, the intertidal snail Littorina saxatilis. First, we tested what types of genetic variation can be detected by this method using direct re-sequencing and comparison to the Littorina genome draft. Secondly, we performed a genome-wide comparison of four closely related Littorina species: L. fabalis, L. compressa, L. arcana and L. saxatilis and of populations of L. saxatilis found in Spain, Britain and Sweden. Finally, we tested whether we could identify genetic variation underlying “Crab” and “Wave” ecotypes of L. saxatilis.

Results

We could reliably detect copy number variations, deletions and high sequence divergence (i.e. above 3%), but not single nucleotide polymorphisms. The overall hybridization pattern and number of significantly diverged genes were in close agreement with earlier phylogenetic reconstructions based on single genes. The trichotomy of L. arcana, L. compressa and L. saxatilis could not be resolved and we argue that these divergence events have occurred recently and very close in time. We found evidence for high levels of segmental duplication in the Littorina genome (10% of the transcripts represented on the array and up to 23% of the analyzed genomic fragments); duplicated genes and regions were mostly the same in all analyzed species. Finally, this method discriminated geographically distant populations of L. saxatilis, but we did not detect any significant genome divergence associated with ecotypes of L. saxatilis.

Conclusions

The present study provides new information on the sensitivity and the potential use of oligonucleotide arrays for genotyping of non-model organisms. Applying this method to Littorina species yields insights into genome evolution following the recent species radiation and supports earlier single-gene based phylogenies. Genetic differentiation of L. saxatilis ecotypes was not detected in this study, despite pronounced innate phenotypic differences. The reason may be that these differences are due to single-nucleotide polymorphisms.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-687) contains supplementary material, which is available to authorized users.

Microarray-based RNA profiling of breast cancer: batch effect removal improves cross-platform consistency

Microarray is a powerful technique used extensively for gene expression analysis. Different technologies are available, but lack of standardization makes it challenging to compare and integrate data. Furthermore, batch-related biases within datasets are common but often not tackled. We have analyzed the same 234 breast cancers on two different microarray platforms. One dataset contained known batch-effects associated with the fabrication procedure used. The aim was to assess the significance of correcting for systematic batch-effects when integrating data from different platforms. We here demonstrate the importance of detecting batch-effects and how tools, such as ComBat, can be used to successfully overcome such systematic variations in order to unmask essential biological signals. Batch adjustment was found to be particularly valuable in the detection of more delicate differences in gene expression. Furthermore, our results show that prober adjustment is essential for integration of gene expression data obtained from multiple sources. We show that high-variance genes are highly reproducibly expressed across platforms making them particularly well suited as biomarkers and for building gene signatures, exemplified by prediction of estrogen-receptor status and molecular subtypes. In conclusion, the study emphasizes the importance of utilizing proper batch adjustment methods when integrating data across different batches and platforms.

Characterizing a collective and dynamic component of chromatin immunoprecipitation enrichment profiles in yeast

BACKGROUND

Recent chromatin immunoprecipitation (ChIP) experiments in fly, mouse, and human have revealed the existence of high-occupancy target (HOT) regions or "hotspots" that show enrichment across many assayed DNA-binding proteins. Similar co-enrichment observed in yeast so far has been treated as artifactual, and has not been fully characterized.

RESULTS

Here we reanalyze ChIP data from both array-based and sequencing-based experiments to show that in the yeast S. cerevisiae, the collective enrichment phenomenon is strongly associated with proximity to noncoding RNA genes and with nucleosome depletion. DNA sequence motifs that confer binding affinity for the proteins are largely absent from these hotspots, suggesting that protein-protein interactions play a prominent role. The hotspots are condition-specific, suggesting that they reflect a chromatin state or protein state, and are not a static feature of underlying sequence. Additionally, only a subset of all assayed factors is associated with these loci, suggesting that the co-enrichment cannot be simply explained by a chromatin state that is universally more prone to immunoprecipitation.

CONCLUSIONS

Together our results suggest that the co-enrichment patterns observed in yeast represent transcription factor co-occupancy. More generally, they make clear that great caution must be used when interpreting ChIP enrichment profiles for individual factors in isolation, as they will include factor-specific as well as collective contributions.