RNA‑seq技术在水生生物生态毒理学中的应用进展

水域是地球环境的重要组成部分,也是最易受污染的生态系统之一。水生态系统中不同营养级别的水生生物可通过摄食、接触等多种途径摄入水体中的污染物。因此,监测水域污染物对水生生物和生态系统的影响,解析污染物对不同水生生物的毒性机制,筛选敏感、有效的生物标志物对生态毒理学研究和环境风险评价具有重要意义。RNA测序（RNA sequencing,RNA?seq）技术因所需样品量少,且不需参考序列,可在整体水平上鉴定基因差异表达,成为水生生物生态毒理学研究的最佳方法之一。基于此,介绍了RNA?seq技术的基本流程与数据分析过程,对该技术在不同生态位的水生生物（如鱼类、两栖类、贝类、甲壳类等）生态毒理学中的应用展开综述,并对RNA?seq技术面临的不足、挑战及发展趋势进行探讨,以期为该技术在水生生物生态毒理学研究中的应用,尤其是水生态环境中污染物胁迫水生生物机制的阐明及污染水域生态环境恢复提供参考。     

Assessment of representational difference analysis (RDA) to construct informative cDNA microarrays for gene expression analysis of species with limited transcriptome information, using red and green tomatoes as a model

Microarray technology makes it feasible to analyse the expression of thousands of different gene elements in a single experiment. Most informative are 'whole genome' arrays, where all gene expression products of a single species or variety are represented. Such arrays are now available for a limited number of model species. However, for other, less well-documented species other routes are still necessary to obtain informative arrays. This includes the use of cDNA libraries. To enhance the amount of information that can be obtained from cDNA libraries, redundancy needs to be minimised, and the number of cDNAs relevant for the conditions of interest needs to be increased. Here, we used representational difference analysis (RDA), a mRNA subtraction procedure, as a tool to enhance the efficiency of cDNA libraries to be used to generate microarrays. Tomato was chosen as a model system for a less well-documented species. cDNA libraries for two distinct physiological conditions of tomato fruits, red and green, were made. The libraries were characterized by sequencing and hybridisation analysis. The RDA procedure was shown to be effective in selecting for genes of relevance for the physiological conditions under investigation, and against constitutively expressed genes. At the same time, redundancy was reduced, but complete normalisation was not obtained, and subsequent sequence analysis will be required to obtain non-redundant arrays. Further, known and putative ripening-related cDNAs were identified in hybridisation experiments on the basis of RNA populations as isolated from the green and red stage of ripening.     

DNA microarray technology in toxicogenomics of aquatic models: methods and applications

Toxicogenomics represents the merging of toxicology with genomics and bioinformatics to investigate biological functions of genome in response to environmental contaminants. Aquatic species have traditionally been used as models in toxicology to characterize the actions of environmental stresses. Recent completion of the DNA sequencing for several fish species has spurred the development of DNA microarrays allowing investigators access to toxicogenomic approaches. However, since microarray technology is thus far limited to only a few aquatic species and derivation of biological meaning from microarray data is highly dependent on statistical arguments, the full potential of microarray in aquatic species research has yet to be realized. Herein we review some of the issues related to construction, probe design, statistical and bioinformatical data analyses, and current applications of DNA microarrays. As a model a recently developed medaka (Oryzias latipes) oligonucleotide microarray was described to highlight some of the issues related to array technology and its application in aquatic species exposed to hypoxia. Although there are known non-biological variations present in microarray data, it remains unquestionable that array technology will have a great impact on aquatic toxicology. Microarray applications in aquatic toxicogenomics will range from the discovery of diagnostic biomarkers, to establishment of stress-specific signatures and molecular pathways hallmarking the adaptation to new environmental conditions.     

Microarray studies of gene expression in fish

The use of microarrays for the study of various aspects of fish physiology has seen a spectacular increase in recent years. From early studies with model species, such as zebrafish, to current studies with commercially important species, such as salmonids, catfish, carp, and flatfish, microarray technology has emerged as a key tool for understanding developmental processes as well as basic physiology. In addition, microarrays are being applied to the fields of ecotoxicology and nutrigenomics. A number of different platforms are now available, ranging from microarrays containing cDNA amplicons to oligomers of various sizes. High-density microarrays containing hundreds of thousands of distinct oligomers have been developed for zebrafish and catfish. As this exciting technology advances, so will our understanding of global gene expression in fish. Furthermore, lessons learned from this experimentally tractable group of organisms can also be applied to more advanced organisms such as humans.     

Using DNA microarrays to study gene expression in closely related species

MOTIVATION: Comparisons of gene expression levels within and between species have become a central tool in the study of the genetic basis for phenotypic variation, as well as in the study of the evolution of gene regulation. DNA microarrays are a key technology that enables these studies. Currently, however, microarrays are only available for a small number of species. Thus, in order to study gene expression levels in species for which microarrays are not available, researchers face three sets of choices: (i) use a microarray designed for another species, but only compare gene expression levels within species, (ii) construct a new microarray for every species whose gene expression profiles will be compared or (iii) build a multi-species microarray with probes from each species of interest. Here, we use data collected using a multi-primate cDNA array to evaluate the reliability of each approach. RESULTS: We find that, for inter-species comparisons, estimates of expression differences based on multi-species microarrays are more accurate than those based on multiple species-specific arrays. We also demonstrate that within-species expression differences can be estimated using a microarray for a closely related species, without discernible loss of information. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Mouse protein arrays from a TH1 cell cDNA library for antibody screening and serum profiling

The mouse is the premier genetic model organism for the study of disease and development. We describe the establishment of a mouse T helper cell type 1 (T(H)1) protein expression library that provides direct access to thousands of recombinant mouse proteins, in particular those associated with immune responses. The advantage of a system based on the combination of large cDNA expression libraries with microarray technology is the direct connection of the DNA sequence information from a particular clone to its recombinant, expressed protein. We have generated a mouse T(H)1 expression cDNA library and used protein arrays of this library to characterize the specificity and cross-reactivity of antibodies. Additionally, we have profiled the autoantibody repertoire in serum of a mouse model for systemic lupus erythematosus on these protein arrays and validated the putative autoantigens on highly sensitive protein microarrays.     

Applications of DNA and protein microarrays in comparative physiology

DNA microarrays have revolutionized gene expression studies and made large-scale parallel measurement of whole genome expression a feasible technique in model species where genomes are well characterized. Such studies are perfectly suited to unraveling the complex regulation and/or interaction of both genes and proteins likely involved in most physiological processes. Gene expression profiles are currently being used to identify genes underlying a range of physiological responses. Characterization of these genes will help to elucidate the pathways and processes regulating physiological processes. Expanding the use of DNA microarrays to non-model species that have been critical in elucidating certain physiological pathways will be valuable in determining the genes associated with these processes. Approaches that do not require complete genome information have recently been applied to "non-model" organisms. As whole genomes are sequenced for non-model organisms, the application of DNA microarrays to comparative physiology will expand even further. The recent development of protein microarrays will be critical in understanding the regulation of physiological processes not accounted for at the genomic level. Together, DNA and protein microarrays provide the most thorough and efficient method of understanding the molecular basis of physiological processes to date. In turn, classical physiological approaches will be vital in characterizing and verifying the function of the novel genes identified by microarray experiments. Ultimately, DNA and protein microarray expression profiles may be used to predict physiological responses.     

High-throughput protein arrays: prospects for molecular diagnostics

High-throughput protein arrays allow the miniaturized and parallel analysis of large numbers of diagnostic markers in complex samples. Using automated colony picking and gridding, cDNA or antibody libraries can be expressed and screened as clone arrays. Protein microarrays are constructed from recombinantly expressed, purified, and yet functional proteins, entailing a range of optimized expression systems. Antibody microarrays are becoming a robust format for expression profiling of whole genomes. Alternative systems, such as aptamer, PROfusion, nano- and microfluidic arrays are all at proof-of-concept stage. Differential protein profiles have been used as molecular diagnostics for cancer and autoimmune diseases and might ultimately be applied to screening of high-risk and general populations.     

Heterologous array analysis in Pinaceae: hybridization of Pinus taeda cDNA arrays with cDNA from needles and embryogenic cultures of P. Taeda, P. Sylvestris or Picea abies

Hybridization of labelled cDNA from various cell types with high-density arrays of expressed sequence tags is a powerful technique for investigating gene expression. Few conifer cDNA libraries have been sequenced. Because of the high level of sequence conservation between Pinus and Picea we have investigated the use of arrays from one genus for studies of gene expression in the other. The partial cDNAs from 384 identifiable genes expressed in differentiating xylem of Pinus taeda were printed on nylon membranes in randomized replicates. These were hybridized with labelled cDNA from needles or embryogenic cultures of Pinus taeda, P. sylvestris and Picea abies, and with labelled cDNA from leaves of Nicotiana tabacum. The Spearman correlation of gene expression for pairs of conifer species was high for needles (r(2) = 0.78 - 0.86), and somewhat lower for embryogenic cultures (r(2) = 0.68 - 0.83). The correlation of gene expression for tobacco leaves and needles of each of the three conifer species was lower but sufficiently high (r(2) = 0.52 - 0.63) to suggest that many partial gene sequences are conserved in angiosperms and gymnosperms. Heterologous probing was further used to identify tissue-specific gene expression over species boundaries. To evaluate the significance of differences in gene expression, conventional parametric tests were compared with permutation tests after four methods of normalization. Permutation tests after Z-normalization provide the highest degree of discrimination but may enhance the probability of type I errors. It is concluded that arrays of cDNA from loblolly pine are useful for studies of gene expression in other pines or spruces.     

An a posteriori strategy for enhancing gene discovery in anonymous cDNA microarray experiments

MOTIVATION: Because of the high cost of sequencing, the bulk of gene discovery is performed using anonymous cDNA microarrays. Though the clones on such arrays are easier and cheaper to construct and utilize than unigene and oligonucleotide arrays, they are there in proportion to their corresponding gene expression activity in the tissue being examined. The associated redundancy will be there in any pool of possibly interesting differentially expressed clones identified in a microarray experiment for subsequent sequencing and investigation. An a posteriori sampling strategy is proposed to enhance gene discovery by reducing the impact of the redundancy in the identified pool. RESULTS: The proposed strategy exploits the fact that individual genes that are highly expressed in a tissue are more likely to be present as a number of spots in an anonymous library and, as a direct consequence, are also likely to give higher fluorescence intensity responses when present in a probe in a cDNA microarray experiment. Consequently, spots that respond with low intensities will have a lower redundancy and so should be sequenced in preference to those with the highest intensities. The proposed method, which formalizes how the fluorescence intensity of a spot should be assessed, is validated using actual microarray data, where the sequences of all the clones in the identified pool had been previously determined. For such validations, the concept of a repeat plot is introduced. It is also utilized to visualize and examine different measures for the characterization of fluorescence intensity. In addition, as confirmatory evidence, sequencing from the lowest to the highest intensities in a pool, with all the sequences known, is compared graphically with their random sequencing. The results establish that, in general, the opportunity for gene discovery is enhanced by avoiding the pooling of different biological libraries (because their construction will have involved different hybridization episodes) and concentrating on the clones with lower fluorescence intensities.     

Quantitative assessment of filter-based cDNA microarrays: gene expression profiles of human T-lymphoma cell lines

MOTIVATION: While the use of cDNA microarrays for functional genomic analysis has become commonplace, relatively little attention has been placed on false positives, i.e. the likelihood that a change in measured radioactive or fluorescence intensity may reflect a change in gene expression when, in fact, there is none. Since cDNA arrays are being increasingly used to rapidly distinguish biomarkers for disease detection and subsequent assay development (Wellman et al., Blood, 96, 398-404, 2000), the impact of false positives can be significant. For the use of this technology, it is necessary to develop quantitative criteria for reduction of false positives with radioactively-labeled cDNA arrays. RESULTS: We used a single source of RNA (HuT78 T lymphoma cells) to eliminate sample variation and quantitatively examined intensity ratios using radioactively labeled cDNA microarrays. Variation in intensity ratios was reduced by processing microarrays in side-by-side (parallel mode) rather than by using the same microarray for two hybridizations (sequential mode). Based on statistical independence, calculation of the expected number of false positives as a function of threshold showed that a detection limit of [log(2)R] >0.65 with agreement from three replicates could be used to identify up- or down-modulated genes. Using this quantitative criteria, gene expression differences between two related T lymphoma cell lines, HuT78 and H9, were identified. The relevance of these findings to the known functional differences between these cell types is discussed.     

An ecological perspective in aquatic ecotoxicology: Approaches and challenges

This paper aims to highlight the considerable potential of a better integration of ecological theory in aquatic ecotoxicology. It outlines how community ecology, studies on trophic interaction and disturbance ecology could provide an enhanced theoretical basis for aquatic ecotoxicology and increase ecological relevance in environmental risk assessment of chemicals. Based on the literature and own research, approaches from aquatic ecotoxicology are presented, which are based on ecological considerations and address a higher level of biological complexity for risk assessment strategies of chemicals. The concepts of species-sensitivity distribution (SSD), pollution-induced community tolerance (PICT), the use of model ecosystems and the sediment quality triad (SQT) in ecological risk assesment as well as inputs from ecotoxicology into landscape ecology are illustrated. These examples aim to evidence aquatic ecotoxicology as a rewarding field of ecological research.     

Comparison of gene expression measurements from cDNA and 60-mer oligonucleotide microarrays

As the data generated by microarray technology continue to amass, it is necessary to compare and combine gene expression data from different platforms. To evaluate the performance of cDNA and long oligonucleotide (60-mer) arrays, we generated gene expression profiles for two cancer cell lines and compared the data between the two platforms. All 6182 unique genes represented on both platforms were included in the analysis. A limited correlation (r = 0.4708) was obtained and the difference in measurement of low-expression genes was considered to contribute to the limited correlation. Further restriction of the data set to differentially expressed genes detected in cDNA microarrays (1205 genes) and oligonucleotide arrays (1325 genes) showed modest correlations of 0.7076 and 0.6441 between the two platforms. Quantitative real-time PCR measurements of a set of 10 genes showed better correlation with oligonucleotide arrays. Our results demonstrate that there is substantial variation in the data generated from cDNA and 60-mer oligonucleotide arrays. Although general agreement was observed in measurements of differentially expressed genes, we suggest that data from different platforms could not be directly amassed.