Analysis Of Deep Sequencing Data Research Articles

Genome-Wide Analysis of the Universal Stress Protein Gene Family in Blueberry and Their Transcriptional Responses to UV-B Irradiation and Abscisic Acid

Universal stress proteins (USPs) play essential roles in plant development, hormonal regulation, and abiotic stress responses. However, the characteristics and functional divergence of USP family members have not been studied in blueberry (Vaccinium corymbosum). In this study, we identified 72 VcUSP genes from the Genome Database for Vaccinium. These VcUSPs could be divided into five groups based on their phylogenetic relationships. VcUSPs from groups Ⅰ, Ⅳ, and Ⅴ each possess one UspA domain; group Ⅰ proteins also contain an ATP-binding site that is not present in group Ⅳ and Ⅴ proteins. Groups Ⅱ and Ⅲ include more complex proteins possessing one to three UspA domains and UspE or UspF domains. Prediction of cis-regulatory elements in the upstream sequences of VcUSP genes indicated that their protein products are likely involved in phytohormone signaling pathways and abiotic stress responses. Analysis of RNA deep sequencing data showed that 21 and 7 VcUSP genes were differentially expressed in response to UV-B radiation and exogenous abscisic acid (ABA) treatments, respectively. VcUSP41 and VcUSP68 expressions responded to both treatments, and their encoded proteins may integrate the UV-B and ABA signaling pathways. Weighted gene co-expression network analysis revealed that VcUSP22, VcUSP26, VcUSP67, VcUSP68, and VcUSP41 were co-expressed with many transcription factor genes, most of which encode members of the MYB, WRKY, zinc finger, bHLH, and AP2 families, and may be involved in plant hormone signal transduction, circadian rhythms, the MAPK signaling pathway, and UV-B-induced flavonoid biosynthesis under UV-B and exogenous ABA treatments. Our study provides a useful reference for the further functional analysis of VcUSP genes and blueberry molecular breeding.

Genome-wide analysis of blueberry B-box family genes and identification of members activated by abiotic stress

BackgroundB-box (BBX) proteins play important roles in regulating plant growth, development, and abiotic stress responses. BBX family genes have been identified and functionally characterized in many plant species, but little is known about the BBX family in blueberry (Vaccinium corymbosum).ResultIn this study, we identified 23 VcBBX genes from the Genome Database for Vaccinium (GDV). These VcBBXs can be divided into five clades based on gene structures and conserved domains in their encoded proteins. The prediction of cis-acting elements in the upstream sequences of VcBBX genes and protein–protein interactions indicated that VcBBX proteins are likely involved in phytohormone signaling pathways and abiotic stress responses. Analysis of transcriptome deep sequencing (RNA-seq) data showed that VcBBX genes exhibited organ-specific expression pattern and 11 VcBBX genes respond to ultraviolet B (UV-B) radiation. The co-expression analysis revealed that the encoded 11 VcBBX proteins act as bridges integrating UV-B and phytohormone signaling pathways in blueberry under UV-B radiation. Reverse-transcription quantitative PCR (RT-qPCR) analysis showed that most VcBBX genes respond to drought, salt, and cold stress. Among VcBBX proteins, VcBBX24 is highly expressed in all the organs, not only responds to abiotic stress, but it also interacts with proteins in UV-B and phytohormone signaling pathways, as revealed by computational analysis and co-expression analysis, and might be an important regulator integrating abiotic stress and phytohormone signaling networks.ConclusionsTwenty-three VcBBX genes were identified in blueberry, in which, 11 VcBBX genes respond to UV-B radiation, and act as bridges integrating UV-B and phytohormone signaling pathways according to RNA-seq data. The expression patterns under abiotic stress suggested that the functional roles of most VcBBX genes respose to drought, salt, and cold stress. Our study provides a useful reference for functional analysis of VcBBX genes and for improving abiotic stress tolerance in blueberry.

AmpSeqR: an R package for amplicon deep sequencing data analysis

Amplicon sequencing (AmpSeq) is a methodology that targets specific genomic regions of interest for polymerase chain reaction (PCR) amplification so that they can be sequenced to a high depth of coverage. Amplicons are typically chosen to be highly polymorphic, usually with several highly informative, high frequency single nucleotide polymorphisms (SNPs) segregating in an amplicon of 100–200 base pair (bp). This allows high sensitivity detection and quantification of the frequency of each sequence within each sample making it suitable for applications such as low frequency somatic mosaicism detection or minor clone detection in mixed samples. AmpSeq is being increasingly applied to both biological and medical studies, in applications such as cancer, infectious diseases and brain mosaicism studies. Current bioinformatics pipelines for AmpSeq data processing lack downstream analysis, have difficulty distinguishing between true sequences and PCR sequencing errors and artifacts, and often require bioinformatic expertise. We present a new R package: AmpSeqR, designed for the processing of deep short-read amplicon sequencing data, with a focus on infectious diseases. The pipeline integrates several existing R packages combining them with newly developed functions to perform optimal filtering of reads to remove noise and improve the accuracy of the detected sequences data, permitting detection of very low frequency clones in mixed samples. The package provides useful functions including data pre-processing, amplicon sequence variants (ASVs) estimation, data post-processing, data visualization, and automatically generates a comprehensive Rmarkdown report that contains all essential results facilitating easy inclusion into reports and publications. AmpSeqR is publicly available at https://github.com/bahlolab/AmpSeqR.

Selective ribosome profiling as a tool to study interactions of translating ribosomes in mammalian cells.

The processing, membrane targeting and folding of newly synthesized polypeptides is closely linked to their synthesis at the ribosome. A network of enzymes, chaperones and targeting factors engages ribosome-nascent chain complexes (RNCs) to support these maturation processes. Exploring the modes of action of this machinery is critical for our understanding of functional protein biogenesis. Selective ribosome profiling (SeRP) is a powerful method for interrogating co-translational interactions of maturation factors with RNCs. It provides proteome-wide information on the factor's nascent chain interactome, the timing of factor binding and release during the progress of translation of individual nascent chain species, and the mechanisms and features controlling factor engagement. SeRP is based on the combination of two ribosome profiling (RP) experiments performed on the same cell population. In one experiment the ribosome-protected mRNA footprints of all translating ribosomes of the cell are sequenced (total translatome), while the other experiment detects only the ribosome footprints of the subpopulation of ribosomes engaged by the factor of interest (selected translatome). The codon-specific ratio of ribosome footprint densities from selected over total translatome reports on the factor enrichment at specific nascent chains. In this chapter, we provide a detailed SeRP protocol for mammalian cells. The protocol includes instructions on cell growth and cell harvest, stabilization of factor-RNC interactions, nuclease digest and purification of (factor-engaged) monosomes, as well as preparation of cDNA libraries from ribosome footprint fragments and deep sequencing data analysis. Purification protocols of factor-engaged monosomes and experimental results are exemplified for the human ribosomal tunnel exit-binding factor Ebp1 and chaperone Hsp90, but the protocols are readily adaptable to other co-translationally acting mammalian factors.

Therapeutic Potential of Adipose Stem Cell-Derived Conditioned Medium on Scar Contraction Model.

Scars are composed of stiff collagen fibers, which contract strongly owing to the action of myofibroblasts. To explore the substances that modulate scar contracture, the fibroblast-populated collagen lattice (FPCL) model has been used. However, the molecular signature of the patient-derived FPCL model has not been verified. Here, we examined whether the patient-derived keloid FPCL model reflects scar contraction, analyzing detailed gene expression changes using comprehensive RNA sequencing and histological morphology, and revealed that these models are consistent with the changes during human scar contracture. Moreover, we examined whether conditioned media derived from adipose stem cells (ASC-CM) suppress the scar contracture of the collagen disc. Detailed time-series measurements of changes in disc area showed that the addition of ASC-CM significantly inhibited the shrinkage of collagen discs. In addition, a deep sequencing data analysis revealed that ASC-CM suppressed inflammation-related gene expression in the early phase of contraction; in the later phase, this suppression was gradually replaced by extracellular matrix (ECM)-related gene expression. These lines of data suggested the effectiveness of ASC-CM in suppressing scar contractures. Therefore, the molecular analysis of the ASC-CM actions found in this study will contribute to solving medical problems regarding pathological scarring in wound prognosis.

M6A Modification Involves in Enriched Environment-Induced Neurogenesis and Cognition Enhancement.

Although previous studies have shown that an enriched environment (EE) promotes neurogenesis and alters DNA and histone modifications, it remains largely unknown whether an EE affects epitranscriptome in the context of neuronal development. Here, we showed that EE exposure enhanced the pool of adult neural stem/progenitor cells (aNSPCs) and promoted neuronal differentiation of aNSPCs. EE exposure also improved cognitive capabilities and altered the expression of genes relating to neuronal development, neurogenesis, and memory. N 6-Methyladenosine (m6A) immunoprecipitation combined with deep sequencing (MeRIP-seq) data analysis revealed that EE exposure increased the global level of m6A and led to differential m6A mRNA modification. Differential m6A modification-associated genes are involved in neuronal development, neurogenesis, and so on. Notably, EE exposure decreased the protein level of m6A eraser Fto, but did not affect the protein level of m6A writers METTL3 and METTL14. Taken together, our results suggest that enriched environment exposure induces differential m6A mRNA modification and adds a novel layer to the interaction between the environment and epigenetics in the context of postnatal neuronal development.

Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data

SummaryA key task of genomic surveillance of infectious viral diseases lies in the early detection of dangerous variants. Unexpected help to this end is provided by the analysis of deep sequencing data of viral samples, which are typically discarded after creating consensus sequences. Such analysis allows one to detect intra-host low-frequency mutations, which are a footprint of mutational processes underlying the origination of new variants. Their timely identification may improve public-health decision-making with respect to traditional approaches exploiting consensus sequences. We present the analysis of 220,788 high-quality deep sequencing SARS-CoV-2 samples, showing that many spike and nucleocapsid mutations of interest associated to the most circulating variants, including Beta, Delta, and Omicron, might have been intercepted several months in advance. Furthermore, we show that a refined genomic surveillance system leveraging deep sequencing data might allow one to pinpoint emerging mutation patterns, providing an automated data-driven support to virologists and epidemiologists.

Identification of Key microRNAs in Diabetes Mellitus Erectile Dysfunction Rats with Stem Cell Therapy by Bioinformatic Analysis of Deep Sequencing Data.

PurposeDiabetes mellitus erectile dysfunction (DMED) is a common resulting complication of diabetes. Studies have shown mesenchymal stem cell (MSC)-based therapy was beneficial in alleviating erectile function of DMED rats. While the pathogenesis of DMED and the mechanism MSCs actions are unclear.Materials and MethodsWe constructed a rat model of DMED with or without intracavernous injection of MSCs, and performed microRNA (miRNA) sequencing of corpora cavernosa tissues.ResultsWe identified three overlapping differentially expressed miRNAs (rno-miR-1298, rno-miR-122-5p, and rno-miR-6321) of the normal control group, DMED group, and DMED+MSCs group. We predicted 285 target genes of three miRNAs through RNAhybrid and miRanda database and constructed a miRNA-target gene network through Cytoscape. Next, we constructed protein-protein interaction networks through STRING database and identified the top 10 hub genes with highest connectivity scores. Five GO terms including cellular response to growth factor stimulus (GO:0071363), ossification (GO:0001503), response to steroid hormone (GO:0048545), angiogenesis (GO:0001525), positive regulation of apoptotic process (GO:0043065), and one Reactome pathway (Innate Immune System) were significantly enriched by 10 hub genes using the Metascape database. We selected the GSE2457 dataset to validate the expression of hub genes and found only the expression of B4galt1 was statistically different (p<0.001). B4galt1 was highly expressed in penile tissues of diabetic rats and would be negatively regulated by rno-miR-1298.ConclusionsThree key miRNAs were identified in DMED rats with stem cell therapy and the miR-1298/B4GalT1 axis might exert function in stem cell therapy for ED.

Recombinant SARS-CoV-2 genomes circulated at low levels over the first year of the pandemic.

Viral recombination can generate novel genotypes with unique phenotypic characteristics, including transmissibility and virulence. Although the capacity for recombination among betacoronaviruses is well documented, recombination between strains of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has not been characterized in detail. Here, we present a lightweight approach for detecting genomes that are potentially recombinant. This approach relies on identifying the mutations that primarily determine SARS-CoV-2 clade structure and then screening genomes for ones that contain multiple mutational markers from distinct clades. Among the over 537,000 genomes queried that were deposited on GISAID.org prior to 16 February 2021, we detected 1,175 potential recombinant sequences. Using a highly conservative criteria to exclude sequences that may have originated through de novo mutation, we find that at least 30 per cent (n = 358) are likely of recombinant origin. An analysis of deep-sequencing data for these putative recombinants, where available, indicated that the majority are high quality. Additional phylogenetic analysis and the observed co-circulation of predicted parent clades in the geographic regions of exposure further support the feasibility of recombination in this subset of potential recombinants. An analysis of these genomes did not reveal evidence for recombination hotspots in the SARS-CoV-2 genome. While most of the putative recombinant sequences we detected were genetic singletons, a small number of genetically identical or highly similar recombinant sequences were identified in the same geographic region, indicative of locally circulating lineages. Recombinant genomes were also found to have originated from parental lineages with substitutions of concern, including D614G, N501Y, E484K, and L452R. Adjusting for an unequal probability of detecting recombinants derived from different parent clades and for geographic variation in clade abundance, we estimate that at most 0.2–2.5 per cent of circulating viruses in the USA and UK are recombinant. Our identification of a small number of putative recombinants within the first year of SARS-CoV-2 circulation underscores the need to sustain efforts to monitor the emergence of new genotypes generated through recombination.

Integrated analysis of miRNAome and transcriptome reveals miRNA-mRNA network regulation in Vibrio alginolyticus infected thick shell mussel Mytilus coruscus

The thick shell mussel Mytilus coruscus has developed into a model species for studying the interaction between molluscs and environmental stimuli. Herein, integrated analysis of miRNAome and transcriptome was performed to reveal miRNA-mRNA network regulation in Vibrio alginolyticus infected M. coruscus. There have detected some histological abnormalities in digestive gland and gills of V. alginolyticus challenged mussels, ascertaining the effective irritation by the present bacterial strain. A total of 265 novel miRNAs were finally predicted, of which 26 were differentially expressed miRNAs (DEMs). Additionally, 667 differentially expressed genes (DEGs) were detected, which may be potentially associated with innate immune response to V. alginolyticus infection. A regulatory network linked to 22 important pathways and 16 DEMs and 34 OGs was constructed. Some traditional immune-related signaling pathways such as toll-like receptor signaling pathway (TLR) signaling pathway, transforming growth factor-beta (TGF-beta) signaling pathway, peroxisome, phagosome, lysosome, mammalian target of rapamyoin (mTOR) signaling pathway were linked to specific miRNAs and genes in this network. Further, interactional relationship between certain miRNAs and TLR pathway was dissected, which the results predicted that a number of TLRs and TLR-associated signaling genes including TLR1, TLR2, TLR4, TLR6, IRAK1, TRAF6, MAPK, and IL-17 were negatively regulated by novel_miR_11, novel_miR_145, novel_miR_196, novel_miR_5, novel_miR_163 and novel_miR_217 in the TLR pathway. Additionally, interactional relationship between novel_miR_145 and TLR2 was validated by laboratory experiment. The integrated analysis of mRNA and microRNA deep sequencing data exhibited a sophisticated miRNA-mRNA regulation network in M. coruscus in response to V. alginolyticus challenge, which shed a new light on the underlying mechanism of molluscan confronting bacterial infection.

ScBatch: batch-effect correction of RNA-seq data through sample distance matrix adjustment.

Batch effect is a frequent challenge in deep sequencing data analysis that can lead to misleading conclusions. Existing methods do not correct batch effects satisfactorily, especially with single-cell RNA sequencing (RNA-seq) data. We present scBatch, a numerical algorithm for batch-effect correction on bulk and single-cell RNA-seq data with emphasis on improving both clustering and gene differential expression analysis. scBatch is not restricted by assumptions on the mechanism of batch-effect generation. As shown in simulations and real data analyses, scBatch outperforms benchmark batch-effect correction methods. The R package is available at github.com/tengfei-emory/scBatch. The code to generate results and figures in this article is available at github.com/tengfei-emory/scBatch-paper-scripts. Supplementary data are available at Bioinformatics online.

Implications of miRNA expression pattern in bovine oocytes and follicular fluids for developmental competence

Developmental competence determines the oocyte capacity to support initial embryo growth, but the molecular mechanisms underlying this phenomenon are still ill-defined. Changes in microRNA (miRNA) expression pattern have been described during follicular growth in several species. Therefore, aim of this study was to investigate whether miRNA expression pattern in cow oocyte and follicular fluid (FF) is associated with the acquisition of developmental competence. Samples were collected from ovaries with more than, or fewer than, 10 mid-antral follicles (H- and L-ovaries) because previous studies demonstrated that this parameter is a reliable predictor of oocyte competence. After miRNA deep sequencing and bioinformatic data analysis, we identified 58 miRNAs in FF and 6 in the oocyte that were differentially expressed between H- and L-ovaries. Overall, our results indicate that miRNA levels both in FF and in the ooplasm must remain within specific thresholds and that changes in either direction compromising oocyte competence. Some of the miRNAs found in FF (miR-769, miR-1343, miR-450a, miR-204, miR-1271 and miR-451) where already known to regulate follicle growth and their expression pattern indicate that they are also involved in the acquisition of developmental competence. Some miRNAs were differentially expressed in both compartments but with opposite patterns, suggesting that miRNAs do not flow freely between FF and oocyte. Gene Ontology analysis showed that the predicted gene targets of most differentially expressed miRNAs are part of a few signalling pathways. Regulation of maternal mRNA storage and mitochondrial activity seem to be the processes more functionally relevant in determining oocyte quality. In conclusion, our data identified a few miRNAs in the follicular fluid and in the ooplasm that modulate the oocyte developmental competence. This provides new insights that could help with the management of cattle reproductive efficiency.

ChimerDB 4.0: an updated and expanded database of fusion genes.

Fusion genes represent an important class of biomarkers and therapeutic targets in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data (ChimerSeq) and text mining of publications (ChimerPub) with extensive manual annotations (ChimerKB). In this update, we present all three modules substantially enhanced by incorporating the recent flood of deep sequencing data and related publications. ChimerSeq now covers all 10 565 patients in the TCGA project, with compilation of computational results from two reliable programs of STAR-Fusion and FusionScan with several public resources. In sum, ChimerSeq includes 65 945 fusion candidates, 21 106 of which were predicted by multiple programs (ChimerSeq-Plus). ChimerPub has been upgraded by applying a deep learning method for text mining followed by extensive manual curation, which yielded 1257 fusion genes including 777 cases with experimental supports (ChimerPub-Plus). ChimerKB includes 1597 fusion genes with publication support, experimental evidences and breakpoint information. Importantly, we implemented several new features to aid estimation of functional significance, including the fusion structure viewer with domain information, gene expression plot of fusion positive versus negative patients and a STRING network viewer. The user interface also was greatly enhanced by applying responsive web design. ChimerDB 4.0 is available at http://www.kobic.re.kr/chimerdb/.

T-705 induces lethal mutagenesis in Ebola and Marburg populations in macaques

Nucleoside analogues (NA) disrupt RNA viral RNA-dependent RNA polymerase (RdRP) function and fidelity for multiple viral families. The mechanism of action (MOA) of T-705 has been attributed alternatively or concurrently to chain termination and lethal mutagenesis depending on the viral species during in vitro studies. In this study, we evaluated the effect of T-705 on the viral population in non-human primates (NHPs) after challenge with Ebola virus (EBOV) or Marburg virus (MARV) to identify the predominant in vivo MOA. We used common virological assays in conjunction with deep sequencing to characterize T-705 effects. T-705 exhibited antiviral activity that was associated with a reduction in specific infectivity and an accumulation of low frequency nucleotide variants in plasma samples collected day 7 post infection. Stranded analysis of deep sequencing data to identify chain termination demonstrated no change in the transcriptional gradient in negative stranded viral reads and minimal changes in positive stranded viral reads in T-705 treated animals, questioning as a MOA in vivo. These findings indicate that lethal mutagenesis is a MOA of T-705 that may serve as an indication of therapeutic activity of NAs for evaluation in clinical settings. This study expands our understanding of MOAs of these compounds for the Filovirus family and provides further evidence that lethal mutagenesis could be a preponderant MOA for this class of therapeutic compounds.

Discovery and characterization of novel Aspergillus fumigatus mycoviruses.

In the last few years, increasing numbers of viruses infecting fungi have been identified. In this study, we used an in silico approach for the analysis of deep RNA sequencing data in order to discover and characterize putative genomic ssRNA or dsRNA mycovirus sequences in Aspergillus fumigatus. RNA sequencing reads of A. fumigatus strains were mapped against the A. fumigatus Af293 reference genome. Unmapped reads were collected for de novo assembly. Contigs were analyzed by Blastx comparison with a mycovirus protein database. Assembled viral genomes were used as template for remapping of RNA sequencing reads. In total, deep RNA sequencing results from 11 A. fumigatus strains were analyzed for the presence of mycoviral genomic RNAs. In 9 out of 11 strains, putative mycoviral RNA genomes were identified. Three strains were infected with two different mycovirus species. Two strains were infected with Aspergillus fumigatus polymycovirus type-1 (AfuPmV-1). Four strains contained fully recovered genomic RNA of unknown narna-like viruses designated as Aspergillus fumigatus narnavirus-1 and Aspergillus fumigatus narnavirus-2 (AfuNV-1 and AfuNV-2). Both viruses showed 38% amino acid sequence identity to Beihai narna-like virus-21. Three strains contained partially recovered genomic RNA of an unknown narna-like virus. Two strains contained fully recovered genomic RNAs of an unknown partitivirus designated as Aspergillus fumigatus partitivirus-2 (AfuPV-2) which showed 50% amino acid sequence identity to Alternaria alternata partitivirus-1. Finally, one strain contained fully recovered genomic RNA of an unknown mitovirus designated as Aspergillus fumigatus mitovirus-1 (AfuMV-1) which showed 34% amino acid sequence identity to Sclerotina sclerotiorum mitovirus. In silico analysis of deep RNA sequencing results showed that a majority of the A. fumigatus strains used here were infected with mycoviruses. Four novel A. fumigatus RNA mycoviruses could be identified: two different Aspergillus fumigatus narna-like viruses, one Aspergillus fumigatus partitivirus, and one Aspergillus fumigatus mitovirus.

Discovery of new type I toxin-antitoxin systems adjacent to CRISPR arrays in Clostridium difficile.

Clostridium difficile, a major human enteropathogen, must cope with foreign DNA invaders and multiple stress factors inside the host. We have recently provided an experimental evidence of defensive function of the C. difficile CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) system important for its survival within phage-rich gut communities. Here, we describe the identification of type I toxin–antitoxin (TA) systems with the first functional antisense RNAs in this pathogen. Through the analysis of deep-sequencing data, we demonstrate the general co-localization with CRISPR arrays for the majority of sequenced C. difficile strains. We provide a detailed characterization of the overlapping convergent transcripts for three selected TA pairs. The toxic nature of small membrane proteins is demonstrated by the growth arrest induced by their overexpression. The co-expression of antisense RNA acting as an antitoxin prevented this growth defect. Co-regulation of CRISPR-Cas and type I TA genes by the general stress response Sigma B and biofilm-related factors further suggests a possible link between these systems with a role in recurrent C. difficile infections. Our results provide the first description of genomic links between CRISPR and type I TA systems within defense islands in line with recently emerged concept of functional coupling of immunity and cell dormancy systems in prokaryotes.

Development of amplicon deep sequencing markers and data analysis pipeline for genotyping multi-clonal malaria infections

BackgroundAmplicon deep sequencing permits sensitive detection of minority clones and improves discriminatory power for genotyping multi-clone Plasmodium falciparum infections. New amplicon sequencing and data analysis protocols are needed for genotyping in epidemiological studies and drug efficacy trials of P. falciparum.MethodsTargeted sequencing of molecular marker csp and novel marker cpmp was conducted in duplicate on mixtures of parasite culture strains and 37 field samples. A protocol allowing to multiplex up to 384 samples in a single sequencing run was applied. Software “HaplotypR” was developed for data analysis.ResultsCpmp was highly diverse (He = 0.96) in contrast to csp (He = 0.57). Minority clones were robustly detected if their frequency was >1%. False haplotype calls owing to sequencing errors were observed below that threshold.ConclusionsTo reliably detect haplotypes at very low frequencies, experiments are best performed in duplicate and should aim for coverage of >10′000 reads/amplicon. When compared to length polymorphic marker msp2, highly multiplexed amplicon sequencing displayed greater sensitivity in detecting minority clones.

Deep Sequencing Reveals a MicroRNA Expression Signature in Triple-Negative Breast Cancer.

Deep sequencing is an advanced technology in genomic biology to detect the precise order of nucleotides in a strand of DNA/RNA molecule. The analysis of deep sequencing data also requires sophisticated knowledge in both computational software and bioinformatics. In this chapter, the procedures of deep sequencing analysis of microRNA (miRNA) transcriptome in triple-negative breast cancer and adjacent normal tissue are described in detail. As miRNAs are critical regulators of gene expression and many of them were previously reported to be associated with the malignant progression of human cancer, the analytical method that accurately identifies deregulated miRNAs in a specific type of cancer is thus important for the understanding of its tumor behavior. We obtained raw sequence reads of miRNA expression from 24 triple-negative breast cancers and 14 adjacent normal tissues using deep sequencing technology in this work. Expression data of miRNA reads were normalized with the quantile-quantile scaling method and were analyzed statistically. A miRNA expression signature composed of 25 differentially expressed miRNAs showed to be an effective classifier between triple-negative breast cancers and adjacent normal tissues in a hierarchical clustering analysis.

Cellular and molecular characterization of gametogenic progression in ex vivo cultured prepuberal mouse testes

BackgroundRecently, an effective testis culture method using a gas-liquid interphase, capable of differentiate male germ cells from neonatal spermatogonia to spermatozoa has been developed. Nevertheless, this methodology needs deep analyses that allow future experimental approaches in basic, pathologic and/or reprotoxicologic studies. Because of this, we characterized at cellular and molecular levels the entire in vitro spermatogenic progression, in order to understand and evaluate the characteristics that define the spermatogenic process in ex vivo cultured testes compared to the in vivo development.MethodsTesticular explants of CD1 mice aged 6 and 10 days post-partum were respectively cultured during 55 and 89 days. Cytological and molecular approaches were performed, analyzing germ cell proportion at different time culture points, meiotic markers immunodetecting synaptonemal complex protein SYCP3 by immunocytochemistry and the relative expression of different marker genes along the differentiation process by Reverse Transcription - quantitative Polymerase Chain Reaction. In addition, microRNA and piwi-interactingRNA profiles were also evaluated by Next Generation Sequencing and bioinformatic approaches.ResultsThe method promoted and maintained the spermatogenic process during 89 days. At a cytological level we detected spermatogenic development delays of cultured explants compared to the natural in vivo process. The expression of different spermatogenic stages gene markers correlated with the proportion of different cell types detected in the cytological preparations.ConclusionsIn vitro progression analysis of the different spermatogenic cell types, from both 6.5 dpp and 10.5 dpp testes explants, has revealed a relative delay in relation to in vivo process. The expression of the genes studied as biomarkers correlates with the cytologically and functional detected progression and differential expression identified in vivo. After a first analysis of deep sequencing data it has been observed that as long as cultures progress, the proportion of microRNAs declined respect to piwi-interactingRNAs levels that increased, showing a similar propensity than which happens in in vivo spermatogenesis. Our study allows to improve and potentially to control the ex vivo spermatogenesis development, opening new perspectives in the reproductive biology fields including male fertility.

NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

BackgroundBiomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them.ResultsHere we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs).ConclusionsThe typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed.