转基因植物的环境生物安全：转基因逃逸及其潜在生态风险的研究和评价

转基因作物的商品化生产和大规模环境释放在带来巨大利益的同时,也引起了全球对其生物安全问题的广泛关注和争议,其中转基因通过花粉介导的基因漂移逃逸到非转基因作物及其野生近缘种,进而导致的潜在环境和生态风险就是备受争议的生物安全问题之一。转基因植物的环境生物安全涉及两方面关键问题：如何科学评价转基因植物商品化种植以后带来的环境和生态影响;如何利用环境生物安全的研究成果来制定科学有效的风险监测和管理措施。对转基因逃逸及其潜在生态风险的科学评价应包括三个重要环节：（1）检测转基因的逃逸的频率;（2）检测转基因逃逸后的表达和遗传规律;（3）确定逃逸后的转基因对野生近缘种群体适合度的影响及其进化潜力,本文将围绕对转基因逃逸及其潜在环境风险的科学评价,以转基因水稻为案例来对转基因逃逸带来生态影响的研究好评价的进展进行简要介绍,并对目前依据风险评价研究成果制定的各种管理策略进行了讨论。只有提高对转基因生物环境安全研究和评价的水平,并制定有效的风险监测和管理措施,才能为我国转基因技术的发展和转基因产品的商品化应用保驾护航。     

转基因林木潜在生态风险研究进展

近20年来,转基因技术在林木上的应用已使林木遗传育种研究取得了可喜的成绩,部分转基因林木已经进行了田间试验,还有一些获得了商品化许可。但与此同时,转基因林木的生态安全问题也逐渐引起了人们的关注,这些问题主要体现在外源基因的水平转移,垂直流动以及对昆虫、土壤生态系统、病毒等的潜在影响上。本文简要介绍了转基因林木田间试验、商品化生产情况及其潜在的生态风险,并对转基因林木的进一步发展进行了展望。     

转基因植物的生态风险评价

自从１９８３年第一株转基因植物诞生以来,至今各种类型的转基因植物进入大田试验的已不计其数,近１０种转基因作物的产物已经商品化。与此同时,转基因植物向环境释放后可能带来的生态风险问题也越来越受到人们的重视。关于转基因植物的生态风险或对环境的危害,科学家提出了不同的概念和测试方法。生态毒理学的经验以及８０年代发展起来的,为作环境决策用的生态风险评价的经验可以借鉴以作转基因植物生态风险的评价。本文介绍了转基因植物对农田生态系统和自然生态系统可能带来的危害以及从基因、基因组、个体、种群以至生态系统等各级水平上危害测试的方法。对风险的判断作了详细的论述,对风险的管理也作了概略的介绍,并对生态风险评价当前发展的水平进行了讨论。     

转基因鱼生态风险评价及其对策研究进展

遗传改良的转基因鱼具有许多优良经济性状, 但转基因鱼迄今尚未进行商业化养殖, 主要原因之一在于对转基因鱼逃逸或放流到自然水体中可能产生的生态风险的担忧. 本文以具有快速生长特性的转生长激素(GH)基因鱼为对象, 分析了转基因鱼潜在生态风险的实质, 简要综述了通过单因子表型与适合度分析、数学模型推演研究转基因鱼生态风险的现状, 阐述了利用人工模拟生态系统开展转基因鱼生态风险评价的新思路及最新研究成果, 同时评述了采用三倍体途径控制转基因鱼生态风险的策略及原理; 在此基础上, 提出生态风险评价与生态风险防范策略是转基因鱼育种研究体系中不可或缺的重要组成、必须与育种研究同步进行的观点, 以期为转基因鱼育种及生态风险评价和对策研究提供启示.     

转基因技术的伦理问题及解决方案

转基因技术已广泛应用于农业、医药、食品、环境保护、能源等各个领域,但也面临着对健康的潜在风险,对生态的破坏及转基因技术带来的责任问题。本文提出了部分解决方案,如成立伦理委员会,发挥政府的理性作用,加强宣传与教育。     

转基因植物根系分泌物对土壤微生态的影响

随着转基因植物商品化进程的加快,对其进行生态风险性评价日益引起学者的重视。诸如转基因逃逸到其它亲缘物种中、产生超级杂草和病毒、昆虫产生耐受性及生物多样性遭受破坏等问题已在部分转基因作物中显现。本文综述了转基因植物中根系分泌物对土壤微生态的影响。     

转基因植物中外源基因及其表达产物转移的途径

随着转基因植物商品化应用的增多,全面了解转基因植物潜在的生态风险性尤为重要。国内外对“转基因植物中外源基因向野生亲缘物种漂移的可能性”、“昆虫对抗虫转基因植物的耐受性”以及“转基因植物对生物多样性的潜在影响”等问题已进行了广泛研究。对转基因植物中外源基因及其表达产物的几种可能转移途径作了概述。着重介绍了“经花粉散布或与野生亲缘物种杂交等途径引起的外源基因转移”以及“转基因植物对土壤生态系统的影响”等方面的研究情况。此外,还对“鉴定外源基因及其表达产物存在的方法”进行了简要探讨。     

转基因植物与近缘种之间基因流的研究进展

随着转基因植物的大面积种植,转基因植物的生态风险受到广泛关注,其中主要的风险是转基因植物与近缘物种之间的基因流及其影响。本文综述了目前商业化种植的转基因作物油菜、棉花、玉米和大豆,以及未商业化种植的水稻、小麦的基因流研究进展;分析了不同转基因作物与其近缘种之间发生基因流的频率和最远发生距离;介绍了降低基因流发生的方法。基因流频率受物种亲缘关系、花期重叠时间、风速风向等因素的影响,最远发生距离受气候条件、传粉媒介、地理条件等因素的影响。转基因作物与其近缘种之间的基因流频率与距花粉源的距离呈负相关关系(y=-0.59x-0.46,R²=0.25,P<0.01),亲缘关系近的基因流频率高。为了降低转基因植物与其近缘物种之间的基因流风险,建议采取“分区管理”的策略,并加强基因流发生之后的生态风险评价研究。     

转基因作物和利弊分析

１９９５年后转基因作物的商品化种植迅猛发展。优良的农艺性状和巨大的经济效益,日益显示出转基因作物是解决２１世纪不断膨胀人口对食物需求的主要途径之一。转基因作物的潜在生态风险及对人体健康影响的急讼随和物的商品化也日趋耨税。为保护转基因作物知识产权发展起来的“终止子技术”引垆经三世界国家的强烈反对。《生物多样化约》缔约国对生物安全有关问题半急激烈,迟迟达不成协议。围绕转基因作物的斗急已悄仅是科学技术之     

转转基因植物对根际土壤生态系统的影响

随着全世界转基因植物种植的普及,转基因植物对生态环境的影响也受到人们的广泛关注。本文针对转基因植物对土壤生态系统带来的潜在风险做了较全面的探讨,概述了转基因植物在土壤中的残留、外源基因的水平转移及其表达产物对土壤生物、土壤理化性质的影响,为今后更安全利用转基因植物提供借鉴。     

Gustatory evoked cortical activity in humans studied by simultaneous EEG and MEG recording

Evoked potentials are widely used in clinical medicine for objective evaluation of sensory disturbances. However, gustatory evoked potentials (GEPs) have not been extensively studied due to lack of agreement among investigators regarding the waveforms. In this study GEPs and gustatory magnetic fields (GEMfs) were simultaneously recorded from five subjects in response to 0.3 M NaCl in an attempt to establish GEP recording as an objective gustatometer. Each subject received a total of 240 stimulus presentations over six sessions. Three GEP components (P1, N1 and P2) were observed and correlated with their corresponding equivalent current dipoles (ECD1, ECD2 and ECD3, respectively). ECD1 was localized to area G in all subjects, P1 being the indicator of intact gustatory projection to area G. No significant GEP activity was detected during the time preceding P1, which suggests that there was no activity in cortical gyri other than that detected by magnetoencephalography. ECD2 and ECD3 were localized to various cortical structures, including the inferior insula and the superior temporal sulcus, indicating that N1 and P2 reflect higher order gustatory functions. The present results indicate that measurement of GEPs may be useful for objective evaluation of gustatory disturbance.     

Getting the right cells to the array: Gene expression microarray analysis of cell mixtures and sorted cells.

BACKGROUND: Most biological samples are cell mixtures. Some basic questions are still unanswered about analyzing these heterogeneous samples using gene expression microarray technology (MAT). How meaningful is a cell mixture's overall gene expression profile (GEP)? Is it necessary to purify the cells of interest before microarray analysis, and how much purity is needed? How much does the purification itself distort the GEP, and how well can the GEP of a small cell subset be recovered? METHODS: Model cell mixtures with different cell ratios were analyzed by both spotted and Affymetrix MAT. GEP distortion during cell purification and GEPs of purified cells were studied. CD34+ cord blood cells were purified and analyzed by MAT. RESULTS: GEPs for mixed cell populations were found to mirror the cell ratios in the mixture. Over 75% pure samples were indistinguishable from pure cells by their overall GEP. Cell purification preserved the GEP. The GEPs of small cell subsets could be accurately recovered by cell sorting both from model cell mixtures and from cord blood. CONCLUSIONS: Purification of small cell subsets from a mixture prior to MAT is necessary for meaningful results. Even completely hidden GEPs of small cell subpopulations can be recovered by cell sorting.     

Quantifying difference in gene expression profile between bovine blastocysts derived by in vitro fertilization and somatic cell nuclear transfer

Epigenetic reprogramming intensely occurs in somatic-cell nuclear transfer (SCNT) embryos, which highlights the importance of proper expressions of reprogramming-related genes in SCNT embryos. We here assessed gene expression profiles (GEPs) difference between bovine blastocyst groups derived by in-vitro fertilization (IVF) or SCNT; in SCNT, cumulus cells and ear skin fibroblasts were used for cSCNT and fSCNT blastocysts, respectively. We obtained GEPs of 15 reprogramming-related genes in single blastocysts using multiplex PCR and found a broad range of variations in their GEPs. Weighted root-mean-square deviation (wRMSD) analysis, which calculates the deviation of SCNT blastocysts' GEPs from IVF blastocysts' mean GEP, found a significant difference between IVF and fSCNT and between cSCNT and fSCNT blastocysts (p < 0.001) but not between IVF and cSCNT. Since the fibroblasts' GEP was more distant from the IVF blastocysts' than the cumulus cells', it might partly explain the less similarity of fSCNT blastocysts' GEPs to the IVF's mean GEP. Our wRMSD method succeeds in expressing in figures how different two comparable embryo groups of different derivations are in GEP, which would be useful to select a better embryo derivation protocol among the candidates prior to field applications.     

Classification of Genes and Putative Biomarker Identification Using Distribution Metrics on Expression Profiles

Background

Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers.

Methodology/Principal Findings

In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness) were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic), and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as ‘brain group’ and ‘non-brain group’; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes.

Conclusions/Significance

The methodology employed here may be used to facilitate disease-specific biomarker discovery.     

Molecular analysis of early rice stamen development using organ-specific gene expression profiling

Elucidating the regulatory mechanisms of plant organ formation is an important component of plant developmental biology and will be useful for crop improvement applications. Plant organ formation, or organogenesis, occurs when a group of primordial cells differentiates into an organ, through a well-orchestrated series of events, with a given shape, structure and function. Research over the past two decades has elucidated the molecular mechanisms of organ identity and dorsalventral axis determinations. However, little is known about the molecular mechanisms underlying the successive processes. To develop an effective approach for studying organ formation at the molecular level, we generated organ-specific gene expression profiles (GEPs) reflecting early development in rice stamen. In this study, we demonstrated that the GEPs are highly correlated with early stamen development, suggesting that this analysis is useful for dissecting stamen development regulation. Based on the molecular and morphological correlation, we found that over 26 genes, that were preferentially up-regulated during early stamen development, may participate in stamen development regulation. In addition, we found that differentially expressed genes during early stamen development are clustered into two clades, suggesting that stamen development may comprise of two distinct phases of pattern formation and cellular differentiation. Moreover, the organ-specific quantitative changes in gene expression levels may play a critical role for regulating plant organ formation. Electronic Supplementary Material Supplementary material is available for this article at Xiao-Chun Lu, Hua-Qin Gong contributed equally to this work.     

Prediction of future gene expression profile by analyzing its past variation pattern

A number of initial Hematopoietic Stem Cells (HSC) are considered in a container that are able to divide into HSCs or differentiate into various types of descendant cells. In this paper, a method is designed to predict an approximate gene expression profile (GEP) for future descendant cells resulted from HSC division/differentiation. First, the GEP prediction problem is modeled into a multivariate time series prediction problem. A novel method called EHSCP (Extended Hematopoietic Stem Cell Prediction) is introduced which is an artificial neural machine to solve the problem. EHSCP accepts the initial sequence of measured GEPs as input and predicts GEPs of future descendant cells. This prediction can be performed for multiple stages of cell division/differentiation. EHSCP considers the GEP sequence as time series and computes correlation between input time series. Two novel artificial neural units called PLSTM (Parametric Long Short Term Memory) and MILSTM (Multi-Input LSTM) are designed. PLSTM makes EHSCP able to consider this correlation in output prediction. Since there exist thousands of time series in GEP prediction, a hierarchical encoder is proposed that computes this correlation using 101 MILSTMs. EHSCP is trained using 155 datasets and is evaluated on 39 test datasets. These evaluations show that EHSCP surpasses existing methods in terms of prediction accuracy and number of correctly-predicted division/differentiation stages. In these evaluations, number of correctly-predicted stages in EHSCP was 128 when as many as 8 initial stages were given.     

Cooperative function of rho GDS and rho GDI to regulate rho p21 activation in smooth muscle.

The GDP/GTP exchange reaction of rho p21, a member of ras p21-related small GTP-binding protein superfamily, is regulated by two stimulatory GDP/GTP exchange proteins (GEPs), named smg GDS and rho GDS, and by one inhibitory GEP, named rho GDI. In bovine aortic smooth muscle, rho GDS and rho GDI were major GEPs for rho p21, and the rho GDI activity on the GDP/GTP exchange reaction of rho p21 was stronger than the rho GDS activity in their simultaneous presence. Moreover, in the crude cytosol, the GDP-bound form of rho p21 was complexed with rho GDI but not with rho GDS. These results, together with our recent finding that rho p21 is involved in the vasoconstrictor-induced Ca2+ sensitization of smooth muscle contraction, suggest that there is some mechanism to release the inhibitory action of rho GDI and to make rho p21 sensitive to the stimulatory action of rho GDS, eventually leading to the rho p21 activation, in the signaling pathways of the vasoconstrictor receptors in smooth muscle.     

Rom1p and Rom2p are GDP/GTP exchange proteins (GEPs) for the Rho1p small GTP binding protein in Saccharomyces cerevisiae.

The RHO1 gene encodes a homolog of the mammalian RhoA small GTP binding protein in the yeast Saccharomyces cerevisiae. Rho1p is localized at the growth site and is required for bud formation. Multicopy suppressors of a temperature-sensitive, dominant negative mutant allele of RHO1, RHO1(G22S, D125N), were isolated and named ROM (RHO1 multicopy suppressor). Rom1p and Rom2p were found to contain a DH (Dbl homologous) domain and a PH (pleckstrin homologous) domain, both of which are conserved among the GDP/GTP exchange proteins (GEPs) for the Rho family small GTP binding proteins. Disruption of ROM2 resulted in a temperature-sensitive growth phenotype, whereas disruption of both ROM1 and ROM2 resulted in lethality. The phenotypes of deltarom1deltarom2 cells were similar to those of deltarho1 cells, including growth arrest with a small bud and cell lysis. Moreover, the temperature-sensitive growth phenotype of deltarom2 was suppressed by overexpression of RHO1 or RHO2, but not of CDC42. The glutathione-S-transferase (GST) fusion protein containing the DH domain of Rom2p showed the lipid-modified Rholp-specific GDP/GTP exchange activity which was sensitive to Rho GDP dissociation inhibitor. These results indicate that Rom1p and Rom2p are GEPs that activate Rho1p in S.cerevisiae.