单细胞转录组数据批次效应评测的研究进展

单细胞转录组测序(Single cell RNA sequencing,ScRNA seq)是一种变革性的生物技术,以前所未有的高分辨率来解析组织复杂性,解决了普通转录组测序(Bulk RNA sequencing)无法回答的问题。但单细胞数据的高通量及复杂性给分析带来极大难度,批次效应(Batch effects,BEs)的处理便是主要挑战之一。批次效应是高通量生物数据分析中的技术性偏倚,其来源及处理具有高复杂性和研究依赖性。根据组织类型、测序技术及实验设计的不同,测序数据需采用不同的评估、分析、测量及处置流程来实现有效的批次效应处理。评测批次效应在单细胞数据分析中极易被忽略,但却有助于判断批次效应的来源、对数据变异的解释度、对数据分析结果的影响度及处理方法,是有效处理批次效应的基础。因此,本篇综述聚焦单细胞转录组数据的批次效应,分别论述批次效应的概念、与普通转录组批次效应的区别、评测方法及面临的挑战,并对未来发展做出展望。     

Identifying complete RNA structural ensembles including pseudoknots

The close relationship between RNA structure and function underlines the significance of accurately predicting RNA structures from sequence information. Structural topologies such as pseudoknots are of particular interest due to their ubiquity and direct involvement in RNA function, but identifying pseudoknots is a computationally challenging problem and existing heuristic approaches usually perform poorly for RNA sequences of even a few hundred bases. We survey the performance of pseudoknot prediction methods on a data set of full-length RNA sequences representing varied sequence lengths, and biological RNA classes such as RNase P RNA, Group I Intron, tmRNA and tRNA. Pseudoknot prediction methods are compared with minimum free energy and suboptimal secondary structure prediction methods in terms of correct base-pairs, stems and pseudoknots and we find that the ensemble of suboptimal structure predictions succeeds in identifying correct structural elements in RNA that are usually missed in MFE and pseudoknot predictions. We propose a strategy to identify a comprehensive set of non-redundant stems in the suboptimal structure space of a RNA molecule by applying heuristics that reduce the structural redundancy of the predicted suboptimal structures by merging slightly varying stems that are predicted to form in local sequence regions. This reduced-redundancy set of structural elements consistently outperforms more specialized approaches.in data sets. Thus, the suboptimal folding space can be used to represent the structural diversity of an RNA molecule more comprehensively than optimal structure prediction approaches alone.     

Improving the prediction of RNA secondary structure by detecting and assessing conserved stems

The prediction of RNA secondary structure can be facilitated by incorporating with comparative analysis of homologous sequences. However, most of existing comparative methods are vulnerable to alignment errors and thus are of low accuracy in practical application. Here we improve the prediction of RNA secondary structure by detecting and assessing conserved stems shared by all sequences in the alignment. Our method can be summarized by: 1) we detect possible stems in single RNA sequence using the so-called position matrix with which some possibly paired positions can be uncovered; 2) we detect conserved stems across multiple RNA sequences by multiplying the position matrices; 3) we assess the conserved stems using the Signal-to-Noise; 4) we compute the optimized secondary structure by incorporating the so-called reliable conserved stems with predictions by RNAalifold program. We tested our method on data sets of RNA alignments with known secondary structures. The accuracy, measured as sensitivity and specificity, of our method is greater than predictions by RNAalifold.     

Assessing the Quality of Hybridized RNA in Affymetrix GeneChips Using Linear Regression

The quality of data from microarray analysis is highly dependent on the quality of RNA. Because of the lability of RNA, steps involved in tissue sampling, RNA purification, and RNA storage are known to potentially lead to the degradation of RNAs; therefore, assessment of RNA quality and integrity is essential. Existing methods for estimating the quality of RNA hybridized to a GeneChip either suffer from subjectivity or are inefficient in performance. To overcome these drawbacks, we propose a linear regression method for assessing RNA quality for a hybridized Genechip. In particular, our approach used the probe intensities from the .cel files that the Affymetrix software associates with each microarray. The effectiveness and the improvements of the proposed method over the existing methods are illustrated by the application of the method to the previously published 19 human Affymetrix microarray data sets for which external verification of RNA quality is available.     

Prediction of RNA secondary structure based on helical regions distribution

MOTIVATION: RNAs play an important role in many biological processes and knowing their structure is important in understanding their function. Due to difficulties in the experimental determination of RNA secondary structure, the methods of theoretical prediction for known sequences are often used. Although many different algorithms for such predictions have been developed, this problem has not yet been solved. It is thus necessary to develop new methods for predicting RNA secondary structure. The most-used at present is Zuker's algorithm which can be used to determine the minimum free energy secondary structure. However many RNA secondary structures verified by experiments are not consistent with the minimum free energy secondary structures. In order to solve this problem, a method used to search a group of secondary structures whose free energy is close to the global minimum free energy was developed by Zuker in 1989. When considering a group of secondary structures, if there is no experimental data, we cannot tell which one is better than the others. This case also occurs in combinatorial and heuristic methods. These two kinds of methods have several weaknesses. Here we show how the central limit theorem can be used to solve these problems. RESULTS: An algorithm for predicting RNA secondary structure based on helical regions distribution is presented, which can be used to find the most probable secondary structure for a given RNA sequence. It consists of three steps. First, list all possible helical regions. Second, according to central limit theorem, estimate the occurrence probability of every helical region based on the Monte Carlo simulation. Third, add the helical region with the biggest probability to the current structure and eliminate the helical regions incompatible with the current structure. The above processes can be repeated until no more helical regions can be added. Take the current structure as the final RNA secondary structure. In order to demonstrate the confidence of the program, a test on three RNA sequences: tRNAPhe, Pre-tRNATyr, and Tetrahymena ribosomal RNA intervening sequence, is performed. AVAILABILITY: The program is written in Turbo Pascal 7.0. The source code is available upon request. CONTACT: Wujj@nic.bmi.ac.cn or Liwj@mail.bmi.ac.cn      

Incorporating global features of RNA motifs in predictions for an ensemble of secondary structures for encapsidated MS2 bacteriophage RNA

The secondary structure of encapsidated MS2 genomic RNA poses an interesting RNA folding challenge. Cryoelectron microscopy has demonstrated that encapsidated MS2 RNA is well-ordered. Models of MS2 assembly suggest that the RNA hairpin-protein interactions and the appropriate placement of hairpins in the MS2 RNA secondary structure can guide the formation of the correct icosahedral particle. The RNA hairpin motif that is recognized by the MS2 capsid protein dimers, however, is energetically unfavorable, and thus free energy predictions are biased against this motif. Computer programs called Crumple, Sliding Windows, and Assembly provide useful tools for prediction of viral RNA secondary structures when the traditional assumptions of RNA structure prediction by free energy minimization may not apply. These methods allow incorporation of global features of the RNA fold and motifs that are difficult to include directly in minimum free energy predictions. For example, with MS2 RNA the experimental data from SELEX experiments, crystallography, and theoretical calculations of the path for the series of hairpins can be incorporated in the RNA structure prediction, and thus the influence of free energy considerations can be modulated. This approach thoroughly explores conformational space and generates an ensemble of secondary structures. The predictions from this new approach can test hypotheses and models of viral assembly and guide construction of complete three-dimensional models of virus particles.     

Assessing quality of hybridized RNA in Affymetrix GeneChip experiments using mixed-effects models

The technology for hybridizing archived tissue specimens and the use of laser-capture microdissection for selecting cell populations for RNA extraction have increased over the past few years. Both these methods contribute to RNA degradation. Therefore, quality assessments of RNA hybridized to microarrays are becoming increasingly more important. Existing methods for estimating the quality of RNA hybridized to a GeneChip, from resulting microarray data, suffer from subjectivity and lack of estimates of variability. In this article, a method for assessing RNA quality for a hybridized array which overcomes these drawbacks is proposed. The effectiveness of the proposed method is demonstrated by the application of the method to two microarray data sets for which external verification of RNA quality is known.     

RNA integrity and the effect on the real-time qRT-PCR performance

The assessment of RNA integrity is a critical first step in obtaining meaningful gene expression data. Working with low-quality RNA may strongly compromise the experimental results of downstream applications which are often labour-intensive, time-consuming, and highly expensive. Using intact RNA is a key element for the successful application of modern molecular biological methods, like qRT-PCR or micro-array analysis. To verify RNA quality nowadays commercially available automated capillary-electrophoresis systems are available which are on the way to become the standard in RNA quality assessment. Profiles generated yield information on RNA concentration, allow a visual inspection of RNA integrity, and generate approximated ratios between the mass of ribosomal sub-units. In this review, the importance of RNA quality for the qRT-PCR was analyzed by determining the RNA quality of different bovine tissues and cell culture. Independent analysis systems are described and compared (OD measurement, NanoDrop, Bioanalyzer 2100 and Experion). Advantage and disadvantages of RNA quantity and quality assessment are shown in performed applications of various tissues and cell cultures. Further the comparison and correlation between the total RNA integrity on PCR performance as well as on PCR efficiency is described. On the basis of the derived results we can argue that qRT-PCR performance is affected by the RNA integrity and PCR efficiency in general is not affected by the RNA integrity. We can recommend a RIN higher than five as good total RNA quality and higher than eight as perfect total RNA for downstream application.     

Simulation of the structure and dynamics of nonhelical RNA motifs

Computer simulation methods are increasingly being used to study possible conformations and dynamics of structural motifs in RNA. Recent results of molecular dynamics simulations and continum solvent studies of RNA structures and RNA-ligand complexes show promising agreement with experimental data. Combined with the ongoing progress in the experimental characterization of RNA structure and thermodynamics, these computational approaches can help to better understand the mechanism of RNA structure formation and the binding of ligands.     

RNA-binding properties of the matrix protein (p19gag) of avian sarcoma and leukemia viruses

We have reinvestigated the ability of the matrix protein (MA) (p19gag) of avian sarcoma and leukemia viruses to interact with RNA. Previous reports claimed on the one hand that MA can bind tightly and with a high degree of specificity to avian sarcoma and leukemia virus RNA in vitro and on the other that it cannot bind to RNA at all. We found that MA purified by any of several methods does bind to RNA, as measured by its ability to cause retention of radioactive RNA on nitrocellulose membranes in a filtration assay. However, this interaction is weak and lacks specificity. The interaction of MA with RNA was barely detectable by classical sedimentation analysis, and from this observation we estimate that the intrinsic MA-RNA association constant is ca. 10(3) M-1, at least 3 orders of magnitude smaller than the constant describing the interaction of the viral nucleocapsid protein (NC) (p12gag) with RNA, ca. 10(6) M-1. Separately purified phosphorylated and nonphosphorylated MA species bound RNA equally. We also found that MA can bind to DNA with an affinity similar to that for RNA. The large quantitative discrepancy between our results and earlier published reports can be traced in part to methods of data analysis.     

Turnover of polyadenylated messenger RNA in fission yeast. Evidence for the control of protein synthesis at the translational level.

Polyadenylated RNA was isolated from fission yeast (Schizosaccharomyces pombe) total RNA using oligo(dT)-cellulose, and was studied as a model for messenger RNA. The half-life of poly adenylated RNA was measured by two independent methods. (a) The rate of labelling of polyadenylated RNA during incubation of cells with [5-3H]uridine was measured. A half-life of 40-45 min was found by comparing the experimental data with theoretical curves calculated for labelling of RNAs with various half-lives. The influence of precursor-pool specific activity on RNA labelling kinetics is considered. (b) Cells were labelled with [5-3H]uridine then further RNA synthesis was inhibited by addition of 8-hydroxyquinoline. The rate of loos of radioactivity from polyadenylated RNA indicated a half-life of 50 min. The half-life found by these two methods is about one-third of the cell doubling time, and is much longer than previous estimates by indirect methods of yeast messenger RNA half-life. Both experimental methods provided evidence for the existence of tas a half-life of 40-50 min; a much smaller population is probably turning over more rapidly. After inhibition of RNA synthesis by 8-hydroxyquinoline, the rate of total protein synthesis declined much more rapidly than the polyadenylated RNA content of the cells. However, 60 min after inhibition of RNA synthesis there was a small rise in the rate of portein synthesis. These data are interpreted as evidence for mechanisms controlling protein synthesis which operate at the level of messenger RNA translation.     

Measuring the dynamic surface accessibility of RNA with the small paramagnetic molecule TEMPOL

The surface accessibility of macromolecules plays a key role in modulating molecular recognition events. RNA is a complex and dynamic molecule involved in many aspects of gene expression. However, there are few experimental methods available to measure the accessible surface of RNA. Here, we investigate the accessible surface of RNA using NMR and the small paramagnetic molecule TEMPOL. We investigated two RNAs with known structures, one that is extremely stable and one that is dynamic. For helical regions, the TEMPOL probing data correlate well with the predicted RNA surface, and the method is able to distinguish subtle variations in atom depths, such as the relative accessibility of pyrimidine versus purine aromatic carbon atoms. Dynamic motions are also detected by TEMPOL probing, and the method accurately reports a previously characterized pH-dependent conformational transition involving formation of a protonated C–A pair and base flipping. Some loop regions are observed to exhibit anomalously high accessibility, reflective of motions that are not evident within the ensemble of NMR structures. We conclude that TEMPOL probing can provide valuable insights into the surface accessibility and dynamics of RNA, and can also be used as an independent means of validating RNA structure and dynamics in solution.