Identification of chilling stress-responsive tomato microRNAs and their target genes by high-throughput sequencing and degradome analysis

Background

MicroRNAs (miRNAs) are a class of noncoding small RNAs (sRNAs) that are 20–24 nucleotides (nt) in length. Extensive studies have indicated that miRNAs play versatile roles in plants, functioning in processes such as growth, development and stress responses. Chilling is a common abiotic stress that seriously affects plants growth and development. Recently, chilling-responsive miRNAs have been detected in several plant species. However, little is known about the miRNAs in the model plant tomato. ‘LA1777’ (Solanum habrochaites) has been shown to survive chilling stress due to its various characteristics.

Results

Here, two small RNA libraries and two degradome libraries were produced from chilling-treated (CT) and non-chilling-treated (NT) leaves of S. habrochaites seedlings. Following high-throughput sequencing and filtering, 161 conserved and 236 novel miRNAs were identified in the two libraries. Of these miRNAs, 192 increased in the response to chilling stress while 205 decreased. Furthermore, the target genes of the miRNAs were predicted using a degradome sequencing approach. It was found that 62 target genes were cleaved by 42 conserved miRNAs, while nine target genes were cleaved by nine novel miRNAs. Additionally, nine miRNAs and six target genes were validated by quantitative real-time PCR (qRT-PCR). Target gene functional analysis showed that most target genes played positive roles in the chilling response, primarily by regulating the expression of anti-stress proteins, antioxidant enzyme and genes involved in cell wall formation.

Conclusions

Tomato is an important model plant for basic biological research. In this study, numerous conserved and novel miRNAs involved in the chilling response were identified using high-throughput sequencing, and the target genes were analyzed by degradome sequencing. The work helps identify chilling-responsive miRNAs in tomato and increases the number of identified miRNAs involved in chilling stress. Furthermore, the work provides a foundation for further study of the regulation of miRNAs in the plant response to chilling stress.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1130) contains supplementary material, which is available to authorized users.     

Identification of miRNAs and their targets from Brassica napus by high-throughput sequencing and degradome analysis

ABSTRACT: BACKGROUND: MicroRNAs (miRNAs) are endogenous regulators of a broad range of physiological processes and act by either degrading mRNA or blocking its translation. Oilseed rape (Brassica napus) is one of the most important crops in China, Europe and other Asian countries with publicly available expressed sequence tags (ESTs) and genomic survey sequence (GSS) databases, but little is known about its miRNAs and their targets. To date, only 46 miRNAs have been identified in B. napus. RESULTS: Forty-one conserved and 62 brassica-specific candidate B. napus miRNAs, including 20 miRNA* sequences, were identified using Solexa sequencing technology. Furthermore, 33 non-redundant mRNA targets of conserved brassica miRNAs and 19 new non-redundant mRNA targets of novel brassica-specific miRNAs were identified by genome-scale sequencing of mRNA degradome. CONCLUSIONS: This study describes large scale cloning and characterization of B. napus miRNAs and their potential targets, providing the foundation for further characterization of miRNA function in the regulation of diverse physiological processes in B. napus.     

Promises and pitfalls of using high‐throughput sequencing for diet analysis

The application of high‐throughput sequencing‐based approaches to DNA extracted from environmental samples such as gut contents and faeces has become a popular tool for studying dietary habits of animals. Due to the high resolution and prey detection capacity they provide, both metabarcoding and shotgun sequencing are increasingly used to address ecological questions grounded in dietary relationships. Despite their great promise in this context, recent research has unveiled how a wealth of biological (related to the study system) and technical (related to the methodology) factors can distort the signal of taxonomic composition and diversity. Here, we review these studies in the light of high‐throughput sequencing‐based assessment of trophic interactions. We address how the study design can account for distortion factors, and how acknowledging limitations and biases inherent to sequencing‐based diet analyses are essential for obtaining reliable results, thus drawing appropriate conclusions. Furthermore, we suggest strategies to minimize the effect of distortion factors, measures to increase reproducibility, replicability and comparability of studies, and options to scale up DNA sequencing‐based diet analyses. In doing so, we aim to aid end‐users in designing reliable diet studies by informing them about the complexity and limitations of DNA sequencing‐based diet analyses, and encourage researchers to create and improve tools that will eventually drive this field to its maturity.     

Digital fragment analysis of short tandem repeats by high‐throughput amplicon sequencing

High‐throughput sequencing has been proposed as a method to genotype microsatellites and overcome the four main technical drawbacks of capillary electrophoresis: amplification artifacts, imprecise sizing, length homoplasy, and limited multiplex capability. The objective of this project was to test a high‐throughput amplicon sequencing approach to fragment analysis of short tandem repeats and characterize its advantages and disadvantages against traditional capillary electrophoresis. We amplified and sequenced 12 muskrat microsatellite loci from 180 muskrat specimens and analyzed the sequencing data for precision of allele calling, propensity for amplification or sequencing artifacts, and for evidence of length homoplasy. Of the 294 total alleles, we detected by sequencing, only 164 alleles would have been detected by capillary electrophoresis as the remaining 130 alleles (44%) would have been hidden by length homoplasy. The ability to detect a greater number of unique alleles resulted in the ability to resolve greater population genetic structure. The primary advantages of fragment analysis by sequencing are the ability to precisely size fragments, resolve length homoplasy, multiplex many individuals and many loci into a single high‐throughput run, and compare data across projects and across laboratories (present and future) with minimal technical calibration. A significant disadvantage of fragment analysis by sequencing is that the method is only practical and cost‐effective when performed on batches of several hundred samples with multiple loci. Future work is needed to optimize throughput while minimizing costs and to update existing microsatellite allele calling and analysis programs to accommodate sequence‐aware microsatellite data.     

Prevention,diagnosis and treatment of high‐throughput sequencing data pathologies

High‐throughput sequencing (HTS) technologies generate millions of sequence reads from DNA/RNA molecules rapidly and cost‐effectively, enabling single investigator laboratories to address a variety of ‘omics’ questions in nonmodel organisms, fundamentally changing the way genomic approaches are used to advance biological research. One major challenge posed by HTS is the complexity and difficulty of data quality control (QC). While QC issues associated with sample isolation, library preparation and sequencing are well known and protocols for their handling are widely available, the QC of the actual sequence reads generated by HTS is often overlooked. HTS‐generated sequence reads can contain various errors, biases and artefacts whose identification and amelioration can greatly impact subsequent data analysis. However, a systematic survey on QC procedures for HTS data is still lacking. In this review, we begin by presenting standard ‘health check‐up’ QC procedures recommended for HTS data sets and establishing what ‘healthy’ HTS data look like. We next proceed by classifying errors, biases and artefacts present in HTS data into three major types of ‘pathologies’, discussing their causes and symptoms and illustrating with examples their diagnosis and impact on downstream analyses. We conclude this review by offering examples of successful ‘treatment’ protocols and recommendations on standard practices and treatment options. Notwithstanding the speed with which HTS technologies – and consequently their pathologies – change, we argue that careful QC of HTS data is an important – yet often neglected – aspect of their application in molecular ecology, and lay the groundwork for developing a HTS data QC ‘best practices’ guide.     

PipeCraft: Flexible open‐source toolkit for bioinformatics analysis of custom high‐throughput amplicon sequencing data

High‐throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user‐friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable.     

jackalope: A swift,versatile phylogenomic and high‐throughput sequencing simulator

High‐throughput sequencing (HTS) is central to the study of population genomics and has an increasingly important role in constructing phylogenies. Choices in research design for sequencing projects can include a wide range of factors, such as sequencing platform, depth of coverage and bioinformatic tools. Simulating HTS data better informs these decisions, as users can validate software by comparing output to the known simulation parameters. However, current standalone HTS simulators cannot generate variant haplotypes under even somewhat complex evolutionary scenarios, such as recombination or demographic change. This greatly reduces their usefulness for fields such as population genomics and phylogenomics. Here I present the R package jackalope that simply and efficiently simulates (i) sets of variant haplotypes from a reference genome and (ii) reads from both Illumina and Pacific Biosciences platforms. Haplotypes can be simulated using phylogenies, gene trees, coalescent‐simulation output, population‐genomic summary statistics, and Variant Call Format (VCF) files. jackalope can simulate single, paired‐end or mate‐pair Illumina reads, as well as reads from Pacific Biosciences. These simulations include sequencing errors, mapping qualities, multiplexing and optical/PCR duplicates. It can read reference genomes from fasta files and can simulate new ones, and all outputs can be written to standard file formats. jackalope is available for Mac, Windows and Linux systems.     

Small‐scale and automatable high‐throughput compositional analysis of biomass

Conventional wet chemistry methods to determine biomass composition are labor‐ and time‐intensive and require larger amounts of biomass (300 mg) than is often available. To overcome these limitations and to support a high‐throughput pretreatment and hydrolysis (HTPH) screening system, this article reports on the development of a downscaled biomass compositional analysis that is based on conventional wet chemistry techniques but is scaled down by a factor of 100 to use significantly less material. The procedure is performed in readily available high‐performance liquid chromatography vials and can be automated to reduce operator input and increase throughput. Comparison of the compositional analyses of three biomasses determined by the downscaled approach to those obtained by conventional methods showed that the downscaled method measured statistically identical carbohydrate compositions as standard procedures and also can provide reasonable estimates of lignin and ash contents. These results demonstrate the validity of the downscaled procedure for measuring biomass composition to enable the calculation of sugar yields and determination of trends in sugar release behavior in HTPH screening studies. Biotechnol. Bioeng. 2011;108: 306–312. © 2010 Wiley Periodicals, Inc.     

Applying high‐throughput sequencing to identify and evaluate foetal chromosomal deletion and duplication

The present study aimed to estimate the clinical performance of non‐invasive prenatal testing (NIPT) based on high‐throughput sequencing method for the detection of foetal chromosomal deletions and duplications. A total of 6348 pregnant women receiving NIPT using high‐throughput sequencing method were included in our study. They all conceived naturally, without twins, triplets or multiple births. Individuals showing abnormalities in NIPT received invasive ultrasound‐guided amniocentesis for chromosomal karyotype and microarray analysis at 18‐24 weeks of pregnancy. Detection results of foetal chromosomal deletions and duplications were compared between high‐throughput sequencing method and chromosomal karyotype and microarray analysis. Thirty‐eight individuals were identified to show 51 chromosomal deletions/duplications via high‐throughput sequencing method. In subsequent chromosomal karyotype and microarray analysis, 34 subchromosomal deletions/duplications were identified in 26 pregnant women. The observed deletions and duplications ranged from 1.05 to 17.98 Mb. Detection accuracy for these deletions and duplications was 66.7%. Twenty‐one deletions and duplications were found to be correlated with the known abnormalities. NIPT based on high‐throughput sequencing technique is able to identify foetal chromosomal deletions and duplications, but its sensitivity and specificity were not explored. Further progress should be made to reduce false‐positive results.