High-throughput Sequencing Tools Research Articles

Function of Circular RNAs in Fish and Their Potential Application as Biomarkers.

Circular RNAs (circRNAs) are an emerging class of regulatory RNAs with a covalently closed-loop structure formed during pre-mRNA splicing. Recent advances in high-throughput RNA sequencing and circRNA-specific computational tools have driven the development of novel approaches to their identification and functional characterization. CircRNAs are stable, developmentally regulated, and show tissue- and cell-type-specific expression across different taxonomic groups. They play a crucial role in regulating various biological processes at post-transcriptional and translational levels. However, the involvement of circRNAs in fish immunity has only recently been recognized. There is also broad evidence in mammals that the timely expression of circRNAs in muscle plays an essential role in growth regulation but our understanding of their expression and function in teleosts is still very limited. Here, we discuss the available knowledge about circRNAs and their role in growth and immunity in vertebrates from a comparative perspective, with emphasis on cultured teleost fish. We expect that the interest in teleost circRNAs will increase substantially soon, and we propose that they may be used as biomarkers for selective breeding of farmed fish, thus contributing to the sustainability of the aquaculture sector.

Integrated Insight into the Molecular Mechanisms of Spontaneous Abortion during Early Pregnancy in Pigs.

Due to the high rate of spontaneous abortion (SAB) in porcine pregnancy, there is a major interest and concern on commercial pig farming worldwide. Whereas the perturbed immune response at the maternal–fetal interface is an important mechanism associated with the spontaneous embryo loss in the early stages of implantation in porcine, data on the specific regulatory mechanism of the SAB at the end stage of the implantation remains scant. Therefore, we used high-throughput sequencing and bioinformatics tools to analyze the healthy and arresting endometrium on day 28 of pregnancy. We identified 639 differentially expressed lncRNAs (DELs) and 2357 differentially expressed genes (DEGs) at the end stage of implantation, and qRT-PCR was used to verify the sequencing data. Gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and immunohistochemistry analysis demonstrated weaker immune response activities in the arresting endometrium compared to the healthy one. Using the lasso regression analysis, we screened the DELs and constructed an immunological competitive endogenous RNA (ceRNA) network related to SAB, including 4 lncRNAs, 11 miRNAs, and 13 genes. In addition, Blast analysis showed the applicability of the constructed ceRNA network in different species, and subsequently determined HOXA-AS2 in pigs. Our study, for the first time, demonstrated that the SAB events at the end stages of implantation is associated with the regulation of immunobiological processes, and a specific molecular regulatory network was obtained. These novel findings may provide new insight into the possibility of increasing the litter size of sows, making pig breeding better and thus improving the efficiency of animal husbandry production.

The chicken model organism for epigenomic research.

The chicken model organism has advanced the areas of developmental biology, virology, immunology, oncology, epigenetic regulation of gene expression, conservation biology, and genomics of domestication. Further, the chicken model organism has aided in our understanding of human disease. Through the recent advances in high-throughput sequencing and bioinformatic tools, researchers have successfully identified sequences in the chicken genome that have human orthologs, improving mammalian genome annotation. In this review, we highlight the importance of chicken as an animal model in basic and pre-clinical research. We will present the importance of chicken in poultry epigenetics and in genomic studies that trace back to their ancestor, the last link between human and chicken in the tree of life. There are still many genes of unknown function in the chicken genome yet to be characterized. By taking advantage of recent sequencing technologies, it is possible to gain further insight into the chicken epigenome.

Identifying the ‘unidentified’ fungi: a global-scale long-read third-generation sequencing approach

Molecular identification methods, in particular high-throughput sequencing tools, have greatly improved our knowledge about fungal diversity and biogeography, but many of the recovered taxa from natural environments cannot be identified to species or even higher taxonomic levels. This study addresses the phylogenetic placement of previously unrecognized fungal groups by using two complementary approaches: (i) third-generation amplicon sequencing analysis of DNA from global soil samples, screening out ITS reads of < 90% similarity to other available Sanger sequences, and (ii) analysis of common fungal taxa that were previously indicated to be enigmatic in terms of taxonomic placement based on the ITS sequences alone (so-called top50 sequences). For the global soil samples, we chose to amplify the full rRNA gene operon using four partly overlapping amplicons and multiple newly developed primers or primer combinations that cover nearly all fungi and a vast majority of non-fungal eukaryotes. We extracted the rRNA 18S (SSU) and 28S (LSU) genes and performed phylogenetic analyses against carefully selected reference material. Both SSU and LSU analyses placed most soil sequences and top50 sequences to known orders and classes, but tens of monophyletic groups and single sequences remained outside described taxa. Furthermore, the LSU analyses recovered a few small groups of sequences that may potentially represent novel phyla. We conclude that rRNA genes-based phylogenetic analyses are efficient tools for determining phylogenetic relationships of fungal taxa that cannot be placed to any order or class using ITS sequences alone. However, in many instances, longer rRNA gene sequences and availability of both SSU and LSU reads are needed to improve taxonomic resolution. By leveraging third-generation sequencing from global soil samples, we successfully provided phylogenetic placement for many previously unidentified sequences and broadened our view on the fungal tree of life, with 10–20% new order-level taxa. In addition, the PacBio sequence data greatly extends fungal class-level information in reference databases.

Integrative analysis of miRNAs-mRNAs reveals that miR-182 up-regulation contributes to proliferation and invasion of nasopharyngeal carcinoma by targeting PTEN.

Objective: Several miRNAs have been found to be abnormally expressed during nasopharyngeal carcinoma development. Nevertheless, the interaction between miRNAs and downstream genes remains unexploited. In this study, we aim to investigate miRNAs-mRNAs interaction and the mechanism of miR-182 in NPC.Results: Integrative analysis identified several hub-miRNAs that drive NPC pathogenesis. The expression of miR-182 was notably increased in 32 NPC tissues and cell lines (CNE1 and 5-8F). Up-regulation of miR-182 was strongly correlated with poor prognosis of NPC patients. Moreover, the proliferation and invasion of NPC cells were notably increased in miR-182 mimics condition and decreased in miR-182 inhibitor condition. Furthermore, PTEN was verified to be a target of miR-182 and overexpression of PTEN could abrogate the promotion effect of miR-182 mimics on NPC invasion.Conclusions: We identified several hub-miRNAs that may drive NPC pathogenesis. MiR-182 could promote proliferation and invasion of NPC cells via targeting PTEN, which provides a new insight into the clinical therapy of NPC.Materials and Methods: Genome-wide miRNAs of NPC tissues was analyzed using high-throughput sequencing and bioinformatics tools. QRT-PCR experiment was conducted to measure relative expression level. Dual-luciferase reporter assay was used to verify target relationship. The proliferation and invasion of transfected cells were measured by CCK-8 and transwell assay.

Ecological role of earthworm intestinal bacteria in terrestrial environments: A review

Increasing evidence demonstrated the critical role the earthworm gut played in sustaining earthworm's metabolism and transformation of nutrients and pollutants in the environment. Being rich in nutrients, the earthworm gut is favorable for the colonization of (facultative) anaerobic bacteria, which bridge the host earthworm gut with adjacent terrestrial environment. Therefore, the status quo of earthworm gut research was primarily reviewed in this work. It was found that most studies focused on the bacterial composition and diversity of the earthworm gut, and their potential application in nutrient element and pollutant transformation, such as nitrification, methanogens, heavy metal detoxification, etc. Yet limited information was available about the specific mechanism of intestinal bacteria in nutrient and pollutant transformation. Therefore, in this work we highlighted the current problems and concluded the future prospect of worm's intestinal bacteria research. On one hand, high throughput sequencing and bioinformatics tools are critical to break the bottleneck in the intestinal bacteria research via clarifying the molecular mechanism involved in the transformation processes described above. In addition, a global dataset concerning worm gut bacteria will be needed to provide comprehensive information about intestinal bacteria pool, and act as a communication platform to further encourage the progress of worm gut research.

High-Throughput Sequencing is a Crucial Tool to Investigate the Contribution of Human Endogenous Retroviruses (HERVs) to Human Biology and Development.

Human Endogenous retroviruses (HERVs) are remnants of ancient retroviral infections that represent a large fraction of our genome. Their transcriptional activity is finely regulated in early developmental stages and their expression is modulated in different cell types and tissues. Such activity has an impact on human physiology and pathology that is only partially understood up to date. Novel high-throughput sequencing tools have recently allowed for a great advancement in elucidating the various HERV expression patterns in different tissues as well as the mechanisms controlling their transcription, and overall, have helped in gaining better insights in an all-inclusive understanding of the impact of HERVs in biology of the host.

Comparative Transcriptomics Reveals Gene Families Associated with Predatory Behavior in Photuris femme fatale Fireflies.

Identifying the basis of phenotypic variation is a key objective of genetics. This work has been mostly limited to model systems with a plethora of genetic manipulation and functional characterization tools. With the development of high-throughput sequencing and new computational tools, it is possible to identify candidate genes related to phenotypic variation in non-model organisms. Fireflies are excellent for studying phenotypic variation because of their diverse and well-characterized behaviors. Most adult fireflies emit a single mating flash pattern and do not eat. In contrast, adult females of many species in the genus Photuris employ multiple flash patterns and prey upon mate-seeking males of other firefly species. To investigate the genetic basis for this variation, we used comparative transcriptomics to identify positively selected genes between a predatory firefly, Photuris sp., and a non-predatory relative, Photuris frontalis, controlling for genes generally under selection in fireflies by comparing to a Photinus firefly. Nine gene families were identified under positive selection in the predatory versus non-predatory Photuris comparison, including genes involved in digestion, detoxification, vision, reproduction, and neural processes. These results generate intriguing hypotheses about the genetic basis for insect behavior and highlight the utility of comparative transcriptomic tools to investigate complex behaviors in non-model systems.

Influence of electron acceptor availability and microbial community structure on sedimentary methane oxidation in a boreal estuary

Methane is produced microbially in vast quantities in sediments throughout the world’s oceans. However, anaerobic oxidation of methane (AOM) provides a near-quantitative sink for the produced methane and is primarily responsible for preventing methane emissions from the oceans to the atmosphere. AOM is a complex microbial process that involves several different microbial groups and metabolic pathways. The role of different electron acceptors in AOM has been studied for decades, yet large uncertainties remain, especially in terms of understanding the processes in natural settings. This study reports whole-core incubation methane oxidation rates along an estuarine gradient ranging from near fresh water to brackish conditions, and investigates the potential role of different electron acceptors in AOM. Microbial community structure involved in different methane processes is also studied in the same estuarine system using high throughput sequencing tools. Methane oxidation in the sediments was active in three distinct depth layers throughout the studied transect, with total oxidation rates increasing seawards. We find extensive evidence of non-sulphate AOM throughout the transect. The highest absolute AOM rates were observed below the sulphate-methane transition zone (SMTZ), strongly implicating the role of alternative electron acceptors (most likely iron and manganese oxides). However, oxidation rates were ultimately limited by methane availability. ANME-2a/b were the most abundant microbial phyla associated with AOM throughout the study sites, followed by ANME-2d in much lower abundances. Similarly to oxidation rates, highest abundances of microbial groups commonly associated with AOM were found well below the SMTZ, further reinforcing the importance of non-sulphate AOM in this system.

Dynamic change of bacterial community during dairy manure composting process revealed by high-throughput sequencing and advanced bioinformatics tools

The aim of this work was to study the dynamic change in structure and potential function of bacterial community during dairy manure composting process using high-throughput sequencing and advanced bioinformatics tools. Alpha diversity of microbial community significantly decreased during the thermophilic phase and then recovered gradually. Beta diversity analysis showed unique community structures in different composting phases. Keystone microbes such as genus Corynebacterium, Bacillus, Luteimonas and Nonomuraea were identified for different composting phases. Six functional modules were identified for bacterial community during the composting process using co-occurrence analysis. These modules were significantly associated with temperature, pH, degradation of organic matter and maturation of compost. Predicted metagenomics analysis showed that the relative abundance of amino acid, lipid, energy and xenobiotics metabolism increased during the composting process. These results provide valuable insights into the microbiota during dairy manure composting and how the structures and metabolic functions changed in response to composting phases.

The biogenesis, biology and characterization of circular RNAs.

Circular RNAs (circRNAs) are covalently closed, endogenous biomolecules in eukaryotes with tissue-specific and cell-specific expression patterns, whose biogenesis is regulated by specific cis-acting elements and trans-acting factors. Some circRNAs are abundant and evolutionarily conserved, and many circRNAs exert important biological functions by acting as microRNA or protein inhibitors ('sponges'), by regulating protein function or by being translated themselves. Furthermore, circRNAs have been implicated in diseases such as diabetes mellitus, neurological disorders, cardiovascular diseases and cancer. Although the circular nature of these transcripts makes their detection, quantification and functional characterization challenging, recent advances in high-throughput RNA sequencing and circRNA-specific computational tools have driven the development of state-of-the-art approaches for their identification, and novel approaches to functional characterization are emerging.

Analyzing Secondary Structure Patterns in DNA Aptamers Identified via CompELS.

In contrast to sophisticated high-throughput sequencing tools for genomic DNA, analytical tools for comparing secondary structure features between multiple single-stranded DNA sequences are less developed. For single-stranded nucleic acid ligands called aptamers, secondary structure is widely thought to play a pivotal role in driving recognition-based binding activity between an aptamer sequence and its specific target. Here, we employ a competition-based aptamer screening platform called CompELS to identify DNA aptamers for a colloidal target. We then analyze predicted secondary structures of the aptamers and a large population of random sequences to identify sequence features and patterns. Our secondary structure analysis identifies patterns ranging from position-dependent score matrixes of individual structural elements to position-independent consensus domains resulting from global alignment.

Taxonomic and Functional Characterization of the Microbial Community During Spontaneous in vitro Fermentation of Riesling Must.

Although there is an extensive tradition of research into the microbes that underlie the winemaking process, much remains to be learnt. We combined the high-throughput sequencing (HTS) tools of metabarcoding and metagenomics, to characterize how microbial communities of Riesling musts sampled at four different vineyards, and their subsequent spontaneously fermented derivatives, vary. We specifically explored community variation relating to three points: (i) how microbial communities vary by vineyard; (ii) how community biodiversity changes during alcoholic fermentation; and (iii) how microbial community varies between musts that successfully complete alcoholic fermentation and those that become ‘stuck’ in the process. Our metabarcoding data showed a general influence of microbial composition at the vineyard level. Two of the vineyards (4 and 5) had strikingly a change in the differential abundance of Metschnikowia. We therefore additionally performed shotgun metagenomic sequencing on a subset of the samples to provide preliminary insights into the potential relevance of this observation, and used the data to both investigate functional potential and reconstruct draft genomes (bins). At these two vineyards, we also observed an increase in non-Saccharomycetaceae fungal functions, and a decrease in bacterial functions during the early fermentation stage. The binning results yielded 11 coherent bins, with both vineyards sharing the yeast bins Hanseniaspora and Saccharomyces. Read recruitment and functional analysis of this data revealed that during fermentation, a high abundance of Metschnikowia might serve as a biocontrol agent against bacteria, via a putative iron depletion pathway, and this in turn could help Saccharomyces dominate the fermentation. During alcoholic fermentation, we observed a general decrease in biodiversity in both the metabarcoding and metagenomic data. Unexpected Micrococcus behavior was observed in vineyard 4 according to metagenomic analyses based on reference-based read mapping. Analysis of open reading frames using these data showed an increase of functions assigned to class Actinobacteria in the end of fermentation. Therefore, we hypothesize that bacteria might sit-and-wait until Saccharomyces activity slows down. Complementary approaches to annotation instead of relying a single database provide more coherent information true species. Lastly, our metabarcoding data enabled us to identify a relationship between stuck fermentations and Starmerella abundance. Given that robust chemical analysis indicated that although the stuck samples contained residual glucose, all fructose had been consumed, we hypothesize that this was because fructophilic Starmerella, rather than Saccharomyces, dominated these fermentations. Overall, our results showcase the different ways in which metagenomic analyses can improve our understanding of the wine alcoholic fermentation process.

Decoding the Structural Keywords in Protein Structure Universe

Although the protein sequence-structure gap continues to enlarge due to the development of high-throughput sequencing tools, the protein structure universe tends to be complete without proteins with novel structural folds deposited in the protein data bank (PDB) recently. In this work, we identify a protein structural dictionary (Frag-K) composed of a set of backbone fragments ranging from 4 to 20 residues as the structural “keywords” that can effectively distinguish between major protein folds. We firstly apply randomized spectral clustering and random forest algorithms to construct representative and sensitive protein fragment libraries from a large scale of high-quality, non-homologous protein structures available in PDB. We analyze the impacts of clustering cut-offs on the performance of the fragment libraries. Then, the Frag-K fragments are employed as structural features to classify protein structures in major protein folds defined by SCOP (Structural Classification of Proteins). Our results show that a structural dictionary with ~400 4- to 20-residue Frag-K fragments is capable of classifying major SCOP folds with high accuracy.

Rapid isolation and characterization of microsatellites in the critically endangered mountain bongo (Tragelaphus eurycerus isaaci)

High-throughput sequencing tools promise to revolutionize many aspects of genetic research, e.g. by allowing the identification of functional adaptive genetic variation. However, the expense and expertise required to apply these tools to basic conservation questions is a challenge for applications outside academia, resulting in a so-called 'conservation genomics gap' (Shafer et al. 2015). The conservation genetics paradigm is that, basic information about inbreeding and gene flow are often critical to inform conservation management of small populations (Ouborg et al. 2010). This information is often needed quickly and ideally should be accessible to workers without special expertise in genomics (DeSalle and Amato 2004). While the inferential power of highthroughput sequencing to interrogate the genome is profound, the cost for population analysis is higher (though decreasing) than for traditional neutral markers. Thus, the use of neutral markers is still relevant in conservation applications. However, this assumes that neutral markers have been discovered and characterized for a given species of conservation concern, which is often untrue for nonmodel organisms. Here, we use a fast, cost-efficient, high-throughput sequencing method (Illumina MiSeq) to rapidly identify and characterize microsatellites in the mountain bongo (Tragelaphus eurycerus isaaci), which has a clear and timely conservation imperative but lacks any described neutral markers.

Quack: A quality assurance tool for high throughput sequence data

The quality of data generated by high-throughput DNA sequencing tools must be rapidly assessed in order to determine how useful the data may be in making biological discoveries; higher quality data leads to more confident results and conclusions. Due to the ever-increasing size of data sets and the importance of rapid quality assessment, tools that analyze sequencing data should quickly produce easily interpretable graphics. Quack addresses these issues by generating information-dense visualizations from FASTQ files at a speed far surpassing other publicly available quality assurance tools in a manner independent of sequencing technology.

Circular RNAs Act as miRNA Sponges.

Majority of RNAs expressed in animal cells lack protein-coding ability. Unlike other cellular RNAs, circular (circ)RNAs include a large family of noncoding (nc)RNAs that lack the 5' or 3' ends. The improvements in high-throughput RNA sequencing and novel bioinformatics tools have led to the identification of thousands of circRNAs in various organisms. CircRNAs can regulate gene expression by influencing the transcription, the mRNA turnover, and translation by sponging RNA-binding proteins and microRNAs. Given the broad impact of circRNA on miRNA activity, there is huge interest in understanding the impact of miRNA sponging by circRNA on gene regulation. In this review, we summarize our current knowledge of the miRNA-circRNA interaction and mechanisms that influence gene expression.

Bioinformatic prediction and analysis of glucolipid metabolic regulation by miR-34a in Megalobrama amblycephala

The objective of this study was to analyze the target genes and regulatory function of miR-34a in Megalobrama amblycephala using second-generation high-throughput sequencing and bioinformatic tools. Functional enrichment analysis was performed by gene ontology. MiR-34a and target gene expression levels were measured in M. amblycephala fed normal and high-carbohydrate diets. The results revealed that miR-34a was highly conserved in several species, and miR-34a of M. amblycephala has a close evolutionary relationship to that of zebrafish and common carp. miRanda, TargetScan, RNAhybrid predicted 5,185, 6,282 and 2,168 target genes, respectively, and 645 target genes were in common. According to annotation information, the target genes were enriched in phosphate metabolism, glycerophospholipid metabolism, Golgi vesicle transport, cell division, and other biological processes (P < 0.05). Pathway enrichment analysis revealed that these target genes were mainly enriched in alpha-linolenic acid and linoleic acid metabolism, ether lipid metabolism, VEGF signaling pathway, Fc epsilon RI signaling pathway, GnRH signaling pathway, and MAPK signaling pathway (P < 0.05). The regulatory role of miR-34a was more significant in the liver than in the brain of M. amblycephala. MiR-34a regulates glucose lipid homeostasis induced by high glucose diets by upregulating hepatic PI3K/Akt, FOXO, and TOR signaling pathways.

A multivariate distance-based analytic framework for microbial interdependence association test in longitudinal study.

Human microbiome is the collection of microbes living in and on the various parts of our body. The microbes living on our body in nature do not live alone. They act as integrated microbial community with massive competing and cooperating and contribute to our human health in a very important way. Most current analyses focus on examining microbial differences at a single time point, which do not adequately capture the dynamic nature of the microbiome data. With the advent of high-throughput sequencing and analytical tools, we are able to probe the interdependent relationship among microbial species through longitudinal study. Here, we propose a multivariate distance-based test to evaluate the association between key phenotypic variables and microbial interdependence utilizing the repeatedly measured microbiome data. Extensive simulations were performed to evaluate the validity and efficiency of the proposed method. We also demonstrate the utility of the proposed test using a well-designed longitudinal murine experiment and a longitudinal human study. The proposed methodology has been implemented in the freely distributed open-source R package and Python code.

Advances in single-cell RNA sequencing and its applications in cancer research.

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years’ development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects:1. Methodologies of single-cell RNA-seq2. Single-cell isolation techniques3. Single-cell RNA-seq in solid tumor research4. Single-cell RNA-seq in circulating tumor cell research5. Perspectives