Illumina Deep Sequencing Technology Research Articles

MicroRNA signatures from multidrug‑resistant Mycobacterium tuberculosis.

Tuberculosis (TB) infections, caused by multi-drug-resistant Mycobacterium tuberculosis (MDR MTB), remain a significant public health concern worldwide. The regulatory mechanisms underlying the emergence of MDR MTB strains remain to be fully elucidated, and further investigation is required in order to develop better strategies for TB control. The present study investigated the expression profile of microRNA (miRNA) in MTB strains, and examined the differences between sensitive MTB and MDR MTB using next generation sequencing (NGS) with Illumina Deep Sequencing technology to better understand the mechanisms of resistance in MDR MTB, A total of 5, 785 and 195, and 6, 290 and 595 qualified Illumina reads were obtained from two MDR MTB strains, and 6, 673 and 665, and 7, 210 and 217 qualified Illumina reads were obtained from two sensitive MTB strains. The overall de novo assembly of miRNA sequence data generated 62 and 62, and 95 and 112 miRNAs between the 18 and 30 bp long from sensitive MTB strains and MDR MTB strains, respectively. Comparative miRNA analysis revealed that 142 miRNAs were differentially expressed in the MDR MTB strain, compared with the sensitive MTB strain, of which 48 were upregulated and 94 were downregulated. There were six similarly expressed miRNAs between the MDR and sensitive MTB strains, and 108 miRNAs were expressed only in the MDR MTB strain. The present study acquired miRNA data from sensitive MTB and MDR MTB strains using NGS techniques, and this identification miRNAs may serve as an invaluable resource for revealing the molecular basis of the regulation of expression associated with the mechanism of drug-resistance in MTB.

Identification of miRNAs during mouse postnatal ovarian development and superovulation.

BackgroundMicroRNAs are small noncoding RNAs that play critical roles in regulation of gene expression in wide array of tissues including the ovary through sequence complementarity at post-transcriptional level. Tight regulation of multitude of genes involved in ovarian development and folliculogenesis could be regulated at transcription level by these miRNAs. Therefore, tissue specific miRNAs identification is considered a key step towards understanding the role of miRNAs in biological processes.MethodsTo investigate the role of microRNAs during ovarian development and folliculogenesis we sequenced eight different libraries using Illumina deep sequencing technology. Different developmental stages were selected to explore miRNAs expression pattern at different stages of gonadal maturation with/without treatment of PMSG/hCG for superovulation.ResultsFrom massive sequencing reads, clean reads of 16–26 bp were selected for further analysis of differential expression analysis and novel microRNA annotation. Expression analysis of all miRNAs at different developmental stages showed that some miRNAs were present ubiquitously while others were differentially expressed at different stages. Among differentially expressed miRNAs we reported 61 miRNAs with a fold change of more than 2 at different developmental stages among all libraries. Among the up-regulated miRNAs, mmu-mir-1298 had the highest fold change with 4.025 while mmu-mir-150 was down-regulated more than 3 fold. Furthermore, we found 2659 target genes for 20 differentially expressed microRNAs using seven different target predictions programs (DIANA-mT, miRanda, miRDB, miRWalk, RNAhybrid, PICTAR5, TargetScan). Analysis of the predicted targets showed certain ovary specific genes targeted by single or multiple microRNAs. Furthermore, pathway annotation and Gene ontology showed involvement of these microRNAs in basic cellular process.ConclusionsThese results suggest the presence of different miRNAs at different stages of ovarian development and superovulation. Potential role of these microRNAs was elucidated using bioinformatics tools in regulation of different pathways, biological functions and cellular components underlying ovarian development and superovulation. These results provide a framework for extended analysis of miRNAs and their roles during ovarian development and superovulation. Furthermore, this study provides a base for characterization of individual miRNAs to discover their role in ovarian development and female fertility.Electronic supplementary materialThe online version of this article (doi:10.1186/s13048-015-0170-2) contains supplementary material, which is available to authorized users.

Transcriptome analysis of the plateau fish (Triplophysa dalaica): Implications for adaptation to hypoxia in fishes

Triplophysa dalaica, endemic species of Qinghai-Tibetan Plateau, is informative for understanding the genetic basis of adaptation to hypoxic conditions of high altitude habitats. Here, a comprehensive gene repertoire for this plateau fish was generated using the Illumina deep paired-end high-throughput sequencing technology. De novo assembly yielded 145, 256 unigenes with an average length of 1632bp. Blast searches against GenBank non-redundant database annotated 74,594 (51.4%) unigenes encoding for 30,047 gene descriptions in T. dalaica. Functional annotation and classification of assembled sequences were performed using Gene Ontology (GO), clusters of euKaryotic Orthologous Groups (KOG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. After comparison with other fish transcriptomes, including silver carp (Hypophthalmichthys molitrix) and mud loach (Misgurnus anguillicaudatus), 2621 high-quality orthologous gene alignments were constructed among these species. 61 (2.3%) of the genes were identified as having undergone positive selection in the T. dalaica lineage. Within the positively selected genes, 13 genes were involved in hypoxia response, of which 11 were listed in HypoxiaDB. Furthermore, duplicated hif-α (hif-1αA/B and hif-2αA/B), EGLN1 and PPARA candidate genes involved in adaptation to hypoxia were identified in T. dalaica transcriptome. Branch-site model in PAML validated that hif-1αB and hif-2αA genes have undergone positive selection in T.dalaica. Finally, 37,501 simple sequence repeats (SSRs) and 19,497 high-quality single nucleotide polymorphisms (SNPs) were identified in T. dalaica. The identified SSR and SNP markers will facilitate the genetic structure, population geography and ecological studies of Triplophysa fishes.

Genome-wide miRNA-profiling of aflatoxin B1-induced hepatic injury using deep sequencing

Aflatoxin B1 is a potent carcinogen which can induce** hepatocellular carcinoma (HCC) in mammals. Though microRNAs are known to play important roles in tumorigenesis, the functional complexity of microRNAs in AFB1-induced hepatocellular tumorigenesis has not yet been elucidated. Here, we applied Illumina deep sequencing technology for high-throughput profiling of microRNA in rat liver tissue before and after treatment with aflatoxin B1. Analysis of mature miRNAs from different arms of pre-miRNAs allowed us to identify the predominant form of miRNA. We studied the differential expression profile of miRNAs in two libraries, identifying several cancer-related microRNAs which exhibit abnormal expression. KEGG analysis indicated that predicted target genes of differentially expressed miRNAs are involved in cancer-related pathways. Bioinformatic analysis predicted 16 potential novel miRNAs. Our work provides new insights at the miRNA level into AFB1-induced hepatic injury which may lead to HCC.

Deciphering the role of micrornas in early stages of haematopoiesis

Early steps of development are crucial to the emergence and expansion of haematopoieitic stem cells (HSC) as these cells are responsible for the formation of all blood cells throughout life. This research project focuses on the identification of miRNAs that can act as modulators of HSC emergence and expansion during embryonic life. MiRNAs are small non-coding RNAs that modulate the expression of many transcripts simultaneously and their biological role can be cell-type specific. First, we generated a miRNA expression profile of tissues that are involved in HSC emergence and expansion (E11 AGM/Aorta-Gonad-Mesonephros, E11 Yolk Sac, E12 Placenta, E14 Fetal Liver), using Illumina deep sequencing technology.

Genome-Wide Identification of miRNAs Responsive to Drought in Peach (Prunus persica) by High-Throughput Deep Sequencing

Peach (Prunus persica L.) is one of the most important worldwide fresh fruits. Since fruit growth largely depends on adequate water supply, drought stress is considered as the most important abiotic stress limiting fleshy fruit production and quality in peach. Plant responses to drought stress are regulated both at transcriptional and post-transcriptional level. As post-transcriptional gene regulators, miRNAs (miRNAs) are small (19–25 nucleotides in length), endogenous, non-coding RNAs. Recent studies indicate that miRNAs are involved in plant responses to drought. Therefore, Illumina deep sequencing technology was used for genome-wide identification of miRNAs and their expression profile in response to drought in peach. In this study, four sRNA libraries were constructed from leaf control (LC), leaf stress (LS), root control (RC) and root stress (RS) samples. We identified a total of 531, 471, 535 and 487 known mature miRNAs in LC, LS, RC and RS libraries, respectively. The expression level of 262 (104 up-regulated, 158 down-regulated) of the 453 miRNAs changed significantly in leaf tissue, whereas 368 (221 up-regulated, 147 down-regulated) of the 465 miRNAs had expression levels that changed significantly in root tissue upon drought stress. Additionally, a total of 197, 221, 238 and 265 novel miRNA precursor candidates were identified from LC, LS, RC and RS libraries, respectively. Target transcripts (137 for LC, 133 for LS, 148 for RC and 153 for RS) generated significant Gene Ontology (GO) terms related to DNA binding and catalytic activites. Genome-wide miRNA expression analysis of peach by deep sequencing approach helped to expand our understanding of miRNA function in response to drought stress in peach and Rosaceae. A set of differentially expressed miRNAs could pave the way for developing new strategies to alleviate the adverse effects of drought stress on plant growth and development.

Comparative analysis of strand-specific RNA sequencing approaches

Background Standard RNA sequencing approaches generally require double-stranded cDNA synthesis, which erases RNA strand information. Synthesis of a randomly primed double-stranded cDNA followed by addition of adaptors for next-generation sequencing leads to the loss of information about which strand was present in the original mRNA template. The polarity of the transcript is important for correct annotation of novel genes, identification of antisense transcripts with potential regulatory roles, and for correct determination of gene expression levels in the presence of antisense transcripts. Different strand-specific RNA-seq approaches have been developed to preserve information about strand polarity with different level of performances. Material and methods Using Illumina Deep Sequencing Technology, this work investigates the performance of two different directional RNA-Seq (strand-specific RNA-seq) strategies. One is based on direct ligation of adaptors to the RNA ends and the other is based on the labeling and excision of the second strand cDNA. The RNA-seq workflows present in this work have been improved over current more laborious RNA-seq methods. Their low RNA input and streamlined workflows make them compatible with high throughput and automation. We also analyze the effect of different RNA fragmentation methods (divalent cations plus heat versus enzymatic fragmentation). Results We will provide a comparative full data analysis of different strand-specific RNA methods (library performance, complexity, continuity of gene coverage, strand specificity, rRNA background). Conclusions Our results show improved methods for high-quality strand-specific RNA-seq library construction amenable to large-scale library construction and automation.

High throughput sequencing reveals novel and abiotic stress-regulated microRNAs in the inflorescences of rice

BackgroundMicroRNAs (miRNAs) are small RNA molecules that play important regulatory roles in plant development and stress responses. Identification of stress-regulated miRNAs is crucial for understanding how plants respond to environmental stimuli. Abiotic stresses are one of the major factors that limit crop growth and yield. Whereas abiotic stress-regulated miRNAs have been identified in vegetative tissues in several plants, they are not well studied in reproductive tissues such as inflorescences.ResultsWe used Illumina deep sequencing technology to sequence four small RNA libraries that were constructed from the inflorescences of rice plants that were grown under control condition and drought, cold, or salt stress. We identified 227 miRNAs that belong to 127 families, including 70 miRNAs that are not present in the miRBase. We validated 62 miRNAs (including 10 novel miRNAs) using published small RNA expression data in DCL1, DCL3, and RDR2 RNAi lines and confirmed 210 targets from 86 miRNAs using published degradome data. By comparing the expression levels of miRNAs, we identified 18, 15, and 10 miRNAs that were regulated by drought, cold and salt stress conditions, respectively. In addition, we identified 80 candidate miRNAs that originated from transposable elements or repeats, especially miniature inverted-repeat elements (MITEs).ConclusionWe discovered novel miRNAs and stress-regulated miRNAs that may play critical roles in stress response in rice inflorescences. Transposable elements or repeats, especially MITEs, are rich sources for miRNA origination.

Deep sequencing analysis of phage libraries using Illumina platform

This paper presents an analysis of phage-displayed libraries of peptides using Illumina. We describe steps for the preparation of short DNA fragments for deep sequencing and MatLab software for the analysis of the results. Screening of peptide libraries displayed on the surface of bacteriophage (phage display) can be used to discover peptides that bind to any target. The key step in this discovery is the analysis of peptide sequences present in the library. This analysis is usually performed by Sanger sequencing, which is labor intensive and limited to examination of a few hundred phage clones. On the other hand, Illumina deep-sequencing technology can characterize over 107 reads in a single run. We applied Illumina sequencing to analyze phage libraries. Using PCR, we isolated the variable regions from M13KE phage vectors from a phage display library. The PCR primers contained (i) sequences flanking the variable region, (ii) barcodes, and (iii) variable 5′-terminal region. We used this approach to examine how diversity of peptides in phage display libraries changes as a result of amplification of libraries in bacteria. Using HiSeq single-end Illumina sequencing of these fragments, we acquired over 2×107 reads, 57 base pairs (bp) in length. Each read contained information about the barcode (6bp), one complimentary region (12bp) and a variable region (36bp). We applied this sequencing to a model library of 106 unique clones and observed that amplification enriches ∼150 clones, which dominate ∼20% of the library. Deep sequencing, for the first time, characterized the collapse of diversity in phage libraries. The results suggest that screens based on repeated amplification and small-scale sequencing identify a few binding clones and miss thousands of useful clones. The deep sequencing approach described here could identify under-represented clones in phage screens. It could also be instrumental in developing new screening strategies, which can preserve diversity of phage clones and identify ligands previously lost in phage display screens.

Gene expression profiling of Sinapis alba leaves under drought stress and rewatering growth conditions with Illumina deep sequencing

Sinapis alba has many desirable agronomic traits including tolerance to drought. In this investigation, we performed the genome-wide transcriptional profiling of S. alba leaves under drought stress and rewatering growth conditions in an attempt to identify candidate genes involved in drought tolerance, using the Illumina deep sequencing technology. The comparative analysis revealed numerous changes in gene expression level attributable to the drought stress, which resulted in the down-regulation of 309 genes and the up-regulation of 248 genes. Gene ontology analysis revealed that the differentially expressed genes were mainly involved in cell division and catalytic and metabolic processes. Our results provide useful information for further analyses of the drought stress tolerance in Sinapis, and will facilitate molecular breeding for Brassica crop plants.

Use of Illumina Deep Sequencing Technology To Differentiate Hepatitis C Virus Variants

Hepatitis C virus (HCV) is a positive-strand enveloped RNA virus that shows diverse viral populations even in one individual. Though Sanger sequencing has been used to determine viral sequences, deep sequencing technologies are much faster and can perform large-scale sequencing. We demonstrate the successful use of Illumina deep sequencing technology and subsequent analyses to determine the genetic variants and amino acid substitutions in both treatment-naïve (patient 1) and treatment-experienced (patient 7) isolates from HCV-infected patients. As a result, almost the full nucleotide sequence of HCV was detectable for patients 1 and 7. The reads were mapped to the HCV reference sequence. The coverage was 99.8% and the average depth was 69.5× for patient 7, with values of 99.4% (coverage) and 51.1× (average depth) for patient 1. In patient 7, amino acid (aa) 70 in the core region showed arginine, with methionine at aa 91, by Sanger sequencing. Major variants showed the same amino acid sequence, but minor variants were detectable in 18% (6/34 sequences) of sequences, with replacement of methionine by leucine at aa 91. In NS3, 8 amino acid positions showed mixed variants (T72T/I, K213K/R, G237G/S, P264P/S/A, S297S/A, A358A/T, S457S/C, and I615I/M) in patient 7. In patient 1, 3 amino acid positions showed mixed variants (L14L/F/V, S61S/A, and I586T/I). In conclusion, deep sequencing technologies are powerful tools for obtaining more profound insight into the dynamics of variants in the HCV quasispecies in human serum.

Caenorhabditis elegans mutant allele identification by whole-genome sequencing

Identification of the molecular lesion in Caenorhabditis elegans mutants isolated through forward genetic screens usually involves time-consuming genetic mapping. We used Illumina deep sequencing technology to sequence a complete, mutant C. elegans genome and thus pinpointed a single-nucleotide mutation in the genome that affects a neuronal cell fate decision. This constitutes a proof-of-principle for using whole-genome sequencing to analyze C. elegans mutants.