Analysis of high-throughput sequencing data.

BackgroundCultivated flax (Linum usitatissimum L.) is widely used for production of textile, food, chemical and pharmaceutical products. However, various stresses decrease flax production. Search for genes, which are involved in stress response, is necessary for breeding of adaptive cultivars. Imbalanced concentration of nutrient elements in soil decrease flax yields and also results in heritable changes in some flax lines. The appearance of Linum Insertion Sequence 1 (LIS-1) is the most studied modification. However, LIS-1 function is still unclear.ResultsHigh-throughput sequencing of transcriptome of flax plants grown under normal (N), phosphate deficient (P), and nutrient excess (NPK) conditions was carried out using Illumina platform. The assembly of transcriptome was performed, and a total of 34924, 33797, and 33698 unique transcripts for N, P, and NPK sequencing libraries were identified, respectively. We have not revealed any LIS-1 derived mRNA in our sequencing data. The analysis of high-throughput sequencing data allowed us to identify genes with potentially differential expression under imbalanced nutrition. For further investigation with qPCR, 15 genes were chosen and their expression levels were evaluated in the extended sampling of 31 flax plants. Significant expression alterations were revealed for genes encoding WRKY and JAZ protein families under P and NPK conditions. Moreover, the alterations of WRKY family genes differed depending on LIS-1 presence in flax plant genome. Besides, we revealed slight and LIS-1 independent mRNA level changes of KRP2 and ING1 genes, which are adjacent to LIS-1, under nutrition stress.ConclusionsDifferentially expressed genes were identified in flax plants, which were grown under phosphate deficiency and excess nutrition, on the basis of high-throughput sequencing and qPCR data. We showed that WRKY and JAS gene families participate in flax response to imbalanced nutrient content in soil. Besides, we have not identified any mRNA, which could be derived from LIS-1, in our transcriptome sequencing data. Expression of LIS-1 flanking genes, ING1 and KRP2, was suggested not to be nutrient stress-induced. Obtained results provide new insights into edaphic stress response in flax and the role of LIS-1 in these process.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-016-0927-9) contains supplementary material, which is available to authorized users.

BackgroundThe generation and analysis of high-throughput sequencing data are becoming a major component of many studies in molecular biology and medical research. Illumina's Genome Analyzer (GA) and HiSeq instruments are currently the most widely used sequencing devices. Here, we comprehensively evaluate properties of genomic HiSeq and GAIIx data derived from two plant genomes and one virus, with read lengths of 95 to 150 bases.ResultsWe provide quantifications and evidence for GC bias, error rates, error sequence context, effects of quality filtering, and the reliability of quality values. By combining different filtering criteria we reduced error rates 7-fold at the expense of discarding 12.5% of alignable bases. While overall error rates are low in HiSeq data we observed regions of accumulated wrong base calls. Only 3% of all error positions accounted for 24.7% of all substitution errors. Analyzing the forward and reverse strands separately revealed error rates of up to 18.7%. Insertions and deletions occurred at very low rates on average but increased to up to 2% in homopolymers. A positive correlation between read coverage and GC content was found depending on the GC content range.ConclusionsThe errors and biases we report have implications for the use and the interpretation of Illumina sequencing data. GAIIx and HiSeq data sets show slightly different error profiles. Quality filtering is essential to minimize downstream analysis artifacts. Supporting previous recommendations, the strand-specificity provides a criterion to distinguish sequencing errors from low abundance polymorphisms.

A selection of papers prepared by participants of 7th Young Scientists School SBB’15 is presented in three Supplementary Issues to the journals of BMC series, namely, BMC Genomics, BMC Genetics and BMC Microbiology. SBB’15 took place June 22nd-25th in Novosibirsk, Russia (http://conf.nsc.ru/sbb2015). The series of Young Scientists Schools in Systems Biology and Bioinformatics (SBB) started several years ago, in 2008, as educational workshop associated with the large international conference series on bioinformatics known as BGRS\SB (Bioinformatics of Genome Regulation and Structure\Systems Biology) (http://conf.bionet.nsc.ru/bgrssb2016). After its inauguration year of 1998, BGRS/SBB held biannually at the Institute of Cytology and Genetics SB RAS in Novosibirsk. In a recent decade, it became a prime meeting venue for biologists, computer scientists, physicists, mathematicians and biochemists working in an interdisciplinary field of systems biology and computer genomics. Being the largest system biology meeting series in Russia, BGRS\SB-14 attracted participants from 27 countries. In the past BioMedCentral had published series of special issues based on best materials presented at the conference in BMC Genomics (http://www.biomedcentral.com/bmcgenomics/supplements/15/S12), BMC Evolutionary Biology (http://www.biomedcentral.com/bmcevolbiol/supplements/15/S1), BMC Genetics (http://www.biomedcentral.com/bmcgenet/supplements/16/S1) and BMC Systems biology (http://www.biomedcentral.com/bmcsystbiol/supplements/9/S2). In addition, the protein structure related studies presented by BGRS/SBB participants were collated as special issues in Journal of Bioinformatics and Computational Biology (http://www.worldscientific.com/toc/jbcb/4113/01; http://www.worldscientific.com/toc/jbcb/11/01). [1] In addition, the SBB School series has its own history to be proud of. The first generation of its participants already matured enough to substantially advance in the field. A majority of the participants graduated with PhDs, and now are contributing to the school as the lecturers and to a number of world universities as professors. For some students, the conference became instrumental in obtaining their post-doc or first independent position in academic world. In many cases, the informal atmosphere of the school helped to spark a collaboration that later led to publications in leading journals or the dramatic changes in their science career. The Program Committee of the conference and SBB Schools series includes data analysis, bioinformatics and computational biology professionals from different countries. For the last decade, the SBB conference was co-chaired by Academician Prof. Nikolay A. Kolchanov of the Institute of Cytology and Genetics SB RAS, Russia and Prof. Dr. Ralf Hofestadt of Bielefeld University, Germany. System biology and bioinformatics are rapidly developing and wide fields of science knowledge. For Young Scientists Schools, every year is different as it comprises the topics for the trainings that are the hottest at the time of the event. In 2015, the SBB School concentrated on the modern genomics and an analysis of high-throughput sequencing data. The materials presented in the current special issue provide examples of seamless integration of experimental studies performed in the lab and the computer-assisted inquiries into in the complex patterns of the organization and the functioning of biologic systems at the molecular, cell, tissue, organ, and body levels. The scientific topics discussed in 2015 were presented at the following sections: Next generation sequencing (NGS) and data analysis Evolutionary bioinformatics Systems biology and gene network modeling In SBB’15 Supplements to BMC journals Genomics, we collected the best studies presented at the conference. Due to the general breadth of the field of Systems Biology and Bioinformatic, the manuscripts were accepted into three separate tracks, thus forming three Supplementary Issues, BMC Genomics, BMC Genetics and BMC Microbiology. Below we will describe contents of these issues.

Analysis of high-throughput small RNA deep sequencing data, in combination with black pepper transcriptome sequences revealed microRNA-mediated gene regulation in black pepper ( Piper nigrum L.). Black pepper is an important spice crop and its berries are used worldwide as a natural food additive that contributes unique flavour to foods. In the present study to characterize microRNAs from black pepper, we generated a small RNA library from black pepper leaf and sequenced it by Illumina high-throughput sequencing technology. MicroRNAs belonging to a total of 303 conserved miRNA families were identified from the sRNAome data. Subsequent analysis from recently sequenced black pepper transcriptome confirmed precursor sequences of 50 conserved miRNAs and four potential novel miRNA candidates. Stem-loop qRT-PCR experiments demonstrated differential expression of eight conserved miRNAs in black pepper. Computational analysis of targets of the miRNAs showed 223 potential black pepper unigene targets that encode diverse transcription factors and enzymes involved in plant development, disease resistance, metabolic and signalling pathways. RLM-RACE experiments further mapped miRNA-mediated cleavage at five of the mRNA targets. In addition, miRNA isoforms corresponding to 18 miRNA families were also identified from black pepper. This study presents the first large-scale identification of microRNAs from black pepper and provides the foundation for the future studies of miRNA-mediated gene regulation of stress responses and diverse metabolic processes in black pepper.

Moderate body lipid accumulation in mice attenuated benzene-induced hematotoxicity via acceleration of benzene metabolism and clearance

645 Array comparative genomic hybridization (aCGH) differentiates the major intrinsic subgroups of breast carcinomas

Downy mildew is a severe disease that leads to significant losses in grape yields worldwide. It is caused by the oomycete Plasmopara viticola. The study of the distribution of this agent and the search for endophytic organisms that inhibit the growth of P. viticola are essential objectives to facilitate the transition to sustainable and high-yield agriculture, while respecting the environment. In this study, high-throughput sequencing of the ITS (ITS1f/ITS2 region) and 16S (V4 region) amplicons was employed to analyze 80 samples of leaves and stems from different grapevine species and cultivars grown in the Russian Far East (Vitis amurensis Rupr., Vitis coignetiae Pulliat, and several grapevine cultivars). The analysis revealed the presence of P. viticola in 53.75% of the grape samples. The pathogen P. viticola was not detected in V. amurensis samples collected near Vladivostok and Russky Island. Among the P. viticola-affected samples, only two (out of the eighty analyzed grape samples) from the Makarevich vineyard in Primorsky Krai exhibited disease symptoms, while the majority appeared visually healthy. We also found six distinct P. viticola ASVs in our metagenomic data. Based on phylogenetic analysis, we hypothesize that the P. viticola population in the Russian Far East may have originated from the invasive P. viticola clade aestivalis, which has spread around the world from North America. To identify putative microbial antagonists of P. viticola, a differential analysis of high-throughput sequencing data was conducted using the DESeq2 method to compare healthy and P. viticola-affected samples. The in silico analysis revealed an increased representation of certain taxa in healthy samples compared to P. viticola-affected ones: fungi—Kabatina sp., Aureobasidium sp., and Vishniacozyma sp.; bacteria—Hymenobacter spp., Sphingomonas spp., Massilia spp., Methylobacterium-Methylorubrum spp., and Chryseobacterium spp. This in-silico-obtained information on the potential microbial antagonists of P. viticola serves as a theoretical basis for the development of biocontrol agents for grapevine downy mildew.

The perception and signal transduction of the plant hormone abscisic acid (ABA) are crucial for strawberry fruit ripening, but the underlying mechanism of how ABA regulates ripening-related genes has not been well understood. By employing high-throughput sequencing technology, we comprehensively analyzed transcriptomic and miRNA expression profiles simultaneously in ABA- and nordihydroguaiaretic acid (NDGA, an ABA biosynthesis blocker)-treated strawberry fruits with temporal resolution. The results revealed that ABA regulated many genes in different pathways, including hormone signal transduction and the biosynthesis of secondary metabolites. Transcription factor genes belonging to WRKY and heat shock factor (HSF) families might play key roles in regulating the expression of ABA inducible genes, whereas the KNOTTED1-like homeobox protein and Squamosa Promoter-Binding-like protein 18 might be responsible for ABA-downregulated genes. Additionally, 20 known and six novel differentially expressed miRNAs might be important regulators that assist ABA in regulating target genes that are involved in versatile physiological processes, such as hormone balance regulation, pigments formation and cell wall degradation. Furthermore, degradome analysis showed that one novel miRNA, Fa_novel6, could degrade its target gene HERCULES1, which likely contributed to fruit size determination during strawberry ripening. These results expanded our understanding of how ABA drives the strawberry fruit ripening process as well as the role of miRNAs in this process.

High-throughput sequencing (HTS) offers a modern, fast, and explorative solution to unveil the full potential of display techniques, like antibody phage display, in molecular biology. However, a significant challenge lies in the processing and analysis of such data. Furthermore, there is a notable absence of open-access user-friendly software tools that can be utilized by scientists lacking programming expertise. Here, we present ExpoSeq as an easy-to-use tool to explore, process, and visualize HTS data from antibody discovery campaigns like an expert while only requiring a beginner's knowledge. The pipeline is distributed via GitHub and PyPI, and it can either be installed as a package with pip or the user can choose to clone the repository.

In the past 5 years, RNA-Seq has become a powerful tool in transcriptome analysis even though computational methods dedicated to the analysis of high-throughput sequencing data are yet to be standardized. It is, however, now commonly accepted that the choice of a normalization procedure is an important step in such a process, for example in differential gene expression analysis. The present article highlights the similarities between three normalization methods: TMM from edgeR R package, RLE from DESeq2 R package, and MRN. Both TMM and DESeq2 are widely used for differential gene expression analysis. This paper introduces properties that show when these three methods will give exactly the same results. These properties are proven mathematically and illustrated by performing in silico calculations on a given RNA-Seq data set.

In the past decade, the microRNAs (miRNAs) have emerged to be important regulators of gene expression across various species. Several studies have confirmed different types of post-transcriptional modifications at terminal ends of miRNAs. The reports indicate that miRNA modifications are conserved and functionally significant as it may affect miRNA stability and ability to bind mRNA targets, hence affecting target gene repression. Next Generation Sequencing (NGS) of the small RNA (sRNA) provides an efficient and reliable method to explore miRNA modifications. The need for dedicated software, especially for users with little knowledge of computers, to determine and analyze miRNA modifications in sRNA NGS data, motivated us to develop miRMOD. miRMOD is a user-friendly, Microsoft Windows and Graphical User Interface (GUI) based tool for identification and analysis of 5′ and 3′ miRNA modifications (non-templated nucleotide additions and trimming) in sRNA NGS data. In addition to identification of miRNA modifications, the tool also predicts and compares the targets of query and modified miRNAs. In order to compare binding affinities for the same target, miRMOD utilizes minimum free energies of the miRNA:target and modified-miRNA:target interactions. Comparisons of the binding energies may guide experimental exploration of miRNA post-transcriptional modifications. The tool is available as a stand-alone package to overcome large data transfer problems commonly faced in web-based high-throughput (HT) sequencing data analysis tools. miRMOD package is freely available at http://bioinfo.icgeb.res.in/miRMOD.

BackgroundAt the Division of Neonatology, Department of Paediatrics, Medical University Graz, a unique regimen of necrotizing enterocolitis (NEC) prophylaxis in preterm infants showing a < 1500 g birth weight (i.e. very low birth weight, VLBW) is used. The regimen includes oral antibiotic and antifungal therapy and probiotic preparations as well as a standardised feeding regimen. The incidence of NEC in preterm infants treated by this regimen has been shown to be lower, reflecting 0.7% when treatment was initiated on the first day of life, compared to international incidence rates (5.1%). However, the impact of the prophylaxis regimen on the intestinal microbiome is yet unknown.MethodsWe here report the protocol of an observational multicentre STROBE compliant pilot study in VLBW preterm infants. Research will compare three groups as defined by different NEC prophylaxis regimens. Each centre will provide 20 infants. Stool samples will be collected every 2 days throughout the first 2 weeks of life. Samples will be stored at − 80 °C until 16S-rRNA sequencing. 16S-rRNA genes will be amplified using suitable primers (specific for bacteria, fungi and archaea) and prepared for MiSeq Sequencing. Analyses will be performed using public analysis-pipelines, such as Mothur and Qiime, thus allowing an analysis of high-throughput community sequencing data. Abundance and composition changes in intestinal microbiota will be compared between the groups throughout the first 2 weeks of life.DiscussionDifferent surroundings at the three participating study centres, including contacts to care takers and parents, as well as feeding or medication all might influence intestinal microbiota composition and abundance. In the planned sequel study, this should be kept in mind and a more standardised process ought to be established. However, the results obtained from the presented pilot study will display the burden of bias and help to establish a more strict protocol for the future.Trial registrationTrial has been registered with the German Registry for Clinical Trials (registry ID DRKS00009290).

Detection of KMT2A Partial Tandem Duplication in Myeloid Samples By Pacbio® Long Read Sequencing

Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIPseq) is a powerful technique for the genome-wide location of protein DNA-binding sites. The ChIP experiment consists in treating living cells with a cross-linking agent to bind proteins to their DNA substrates. After fragmentation of DNA, specific fractions associated with a particular protein of interest are purified by immunoaffinity. They are next sequenced and identified on the reference genome using dedicated bioinformatics programs. Several technical aspects are important to obtain high-quality ChIPseq results. This includes the quality of antibodies, the sequencing protocols, the use of accurate controls and the careful choice of bioinformatics tools. We present here a general protocol to perform ChIPseq analyses in yeast species. This protocol has been optimized to identify target genes of specific transcription factors but can be used for any other DNA binding proteins.

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture