本文關(guān)鍵詞：基于高通量成像技術(shù)的重離子束輻射誘變擬南芥表型組學(xué)篩選研究　出處：《中國科學(xué)院大學(xué)(中國科學(xué)院近代物理研究所)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 碳離子束輻射 擬南芥 突變篩選 高通量 表型組學(xué)

【摘要】：近年來,傳感器技術(shù)、機器人技術(shù)及各種成像設(shè)備的不斷發(fā)展,科研工作者經(jīng)過不斷探索和努力,開發(fā)出了各種自動化、高精度、高通量的表型組學(xué)分析平臺。這些平臺集高通量的成像系統(tǒng)、高精準(zhǔn)的傳感器系統(tǒng)、全自動化的機器人輔助及強大的數(shù)據(jù)分析處理軟件為一體,能夠?qū)χ仓赀M行高通量、無損傷、全自動化的表型采集和數(shù)據(jù)分析,可以對植株的根葉形態(tài)、生物量、產(chǎn)量及脅迫應(yīng)激反應(yīng)等眾多性狀進行檢測和分析。雖然這些平臺在一定程度上推動了表型組學(xué)的發(fā)展,但是還存在著一些尚待解決的問題。一方面,高通量的表型篩選平臺是否能夠有效的進行突變體篩選工作,尚未有相關(guān)報道對此進行有效的評價。另外,目前只有少數(shù)科研工作者正嘗試建立基于高通量成像系統(tǒng)的植物表型與基因型相對應(yīng)的評估體系。如何對“高通量”的表型組學(xué)分析平臺所獲得的“大數(shù)據(jù)”進行有效分析并獲得有用的“生物信息”已然成為解決這些難題的關(guān)鍵。基于這些問題,本研究設(shè)計了人機識別比較實驗,分別使用傳統(tǒng)肉眼觀測(人)和高通量表型觀測系統(tǒng)(機)兩種方式對擬南芥群體樣本進行突變體甄別。肉眼篩選方式采用傳統(tǒng)的方式進行,機器測量組使用實驗室高通量植物成像系統(tǒng)(Scanalyzer HTS)進行,所獲得的海量數(shù)據(jù)使用PCA(Principal component analysis)、散點矩陣聚類、生長曲線等統(tǒng)計學(xué)分析,對兩種方式進行突變體甄別的準(zhǔn)確率、假陽性率、假陰性率進行了比較。結(jié)合已有的突變體信息和人機實驗結(jié)果最終確定一套行之有效的突變體表型篩選體系。人機實驗研究,探索了一條表型組學(xué)大數(shù)據(jù)處理的分析路線:首先將HTS獲得的表型組學(xué)大數(shù)據(jù)進行降維處理,壓縮數(shù)據(jù)量;利用PCA分析及基于logistic函數(shù)的植物生長曲線分析,并結(jié)合散點矩陣聚類分析對植物表型突變體進行甄別。利用這套體系可以將80%以上的擬南芥表型突變體從眾多植株中識別出來。這一體系可以使用機器篩選剔除大部分非突變體植株,然后再用肉眼進行突變體篩選。這些結(jié)果為正在開展的重離子誘變育種、基于高通量表型組學(xué)大數(shù)據(jù)背景下的作物育種等工作奠定了實驗和理論基礎(chǔ)。人機比較實驗研究表明:(1)隨著聚類分析中置信區(qū)間水平的增加(從95%增至99.9%),機器識別突變體的準(zhǔn)確率逐漸降低,假陽性率逐漸降低,假陰性率逐漸增加。(2)95%置信區(qū)間以內(nèi),機器的準(zhǔn)確率均高于肉眼篩選,假陰性率均低于肉眼篩選。這說明在某種程度上機器可以替代人進行突變體甄別,與人眼識別相比不容易遺漏突變體。(3)機器的假陽性率值在不同置信區(qū)間均高于肉眼識別,說明與耗時耗力的肉眼篩選相比,使用機器可以在相對較短時間內(nèi)實現(xiàn)大批量的擬南芥突變體篩選過程,并且在一定范圍內(nèi)可以縮小突變體的范圍,提高突變體篩選效率。因此,可以先使用機器篩選剔除大部分非突變體植株,然后再使用肉眼篩選進行突變體篩選,這將大大提高篩選效率。(4)研究發(fā)現(xiàn),同一類型突變體種植在不同位置,肉眼將所有位置突變體識別出來的準(zhǔn)確率為16.7%,而機器為50%。然而肉眼有50%的概率只識別出兩個位置中的一個,而機器的識別概率卻為16.7%。這說明與具有一定主觀性的傳統(tǒng)肉眼篩選方式相比,機器篩選更為準(zhǔn)確,其甄別突變體的準(zhǔn)確率更高,能力更強。
[Abstract]:In recent years, the sensor technology, the development of robot technology and various imaging equipment, scientific research workers through continuous exploration and efforts, has developed a variety of automation, high precision, analysis platform phenotype of high throughput. Set high throughput imaging system to the platform, sensor system with high precision, full automation and robot assisted data the powerful analysis software as a whole, capable of high flux, no damage on plant phenotype, automatic acquisition and data analysis, can be on the plant leaf and root morphology, biomass, yield and stress responses and many other traits were detected and analyzed. Although the development of these platforms to a certain extent promoted Phenomics however, there are still some problems to be solved. On the one hand, whether the phenotype of high-throughput screening platform can effectively carry out mutant screening work, there is no relevant report They evaluated effectively. In addition, there are only a few researchers are trying to establish plant phenotype and genotype of high-throughput imaging system based on the corresponding evaluation system. How to "high throughput" Phenomics analysis platform for big data analysis effectively and obtain the useful biological information "has become the key to solve these problems. Based on these problems, this study designed a more experimental machine recognition, respectively using the traditional macroscopic observation (human) and high-throughput phenotypic observation system (machine) two ways for the screening of Arabidopsis mutant population sample. The naked eye screening methods using traditional methods of measuring machine using laboratory group a high-throughput plant (Scanalyzer HTS) imaging system, the massive data obtained using PCA (Principal component analysis), scatter matrix clustering, growth curve The statistical analysis, the accuracy of screening of mutants in two ways, the false positive rate and false negative rate. Compared with the experimental results and the human mutant information determined a set of effective screening of the mutant system. Research on machine experiment, explored a way of Phenomics data processing group HTS: first obtain science phenotypic data for dimensionality reduction, the amount of compressed data; PCA analysis and logistic function based on plant growth curve analysis by combining analysis on phenotypic screening mutant point matrix clustering scattered. Using this set of system can be more than 80% of the Arabidopsis mutant phenotype identified from many plants. This system can use the machine screen and remove most of the non mutant plants, then the naked eye mutant screening. These results are being carried out by the heavy Ion induced mutation breeding, science high-throughput phenotypic groups under the background of crop breeding based on the established experimental and theoretical basis. Comparative experiments show that machine (1) with the increase of the level of confidence interval in clustering analysis (from 95% to 99.9%), the accuracy of machine recognition of the mutant decreased gradually, the false positive rate gradually reduce the false negative rate increase gradually. (2) within the 95% confidence interval, the accuracy rate of the machine is higher than that of the naked eye screening, the false negative rate was lower than the naked eye screening. This means that the machine can replace people to a certain extent for mutant screening, compared with eye recognition is not easy to miss mutant. The false positive rate (3) the value at different confidence intervals were higher than that of the naked eye, and time-consuming eye screening compared to the use of machine can realize the mass screening of Arabidopsis mutants in a relatively short time, and in a Fixed range can narrow the mutant range, improve the efficiency of mutant screening. Therefore, you can first use the machine screen and remove most of the non mutant plants, and then use the naked eye mutant screening, which will greatly improve the efficiency of screening. (4) the study found that the same type of mutant grown in different locations, the naked eye will all position mutant identification the accuracy rate is 16.7%, while the machine for probability 50%. 50% only however visually identify a two position, and the identification probability machine was compared to the 16.7%. has certain subjectivity of traditional eye screening, screening machine is more accurate, the accuracy of screening mutants higher. The ability is stronger.

【學(xué)位授予單位】：中國科學(xué)院大學(xué)(中國科學(xué)院近代物理研究所)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：Q947

【參考文獻】

相關(guān)期刊論文 前8條

1 王瑞;;數(shù)碼影像之前世今生[J];中國攝影;2015年01期

2 潘映紅;;論植物表型組和植物表型組學(xué)的概念與范疇[J];作物學(xué)報;2015年02期

3 袁陽陽;王青鋒;陳進明;;基于轉(zhuǎn)錄組測序信息的水生植物儠菜SSR標(biāo)記開發(fā)[J];植物科學(xué)學(xué)報;2013年05期

4 ;Life on Two Tracks[J];Genomics, Proteomics & Bioinformatics;2012年03期

5 ;Pigment analysis of a color-leaf mutant in Wandering Jew (Tradescantia fluminensis) irradiated by carbon ions[J];Nuclear Science and Techniques;2011年02期

6 周利斌;李文建;曲穎;李萍;;重離子束輻照育種研究進展及發(fā)展趨勢[J];原子核物理評論;2008年02期

7 衛(wèi)增泉,頡紅梅,梁劍平,袁世斌,馮巖,謝忠奎;重離子束在誘變育種和分子改造中的應(yīng)用[J];原子核物理評論;2003年01期

8 甘甫平,王潤生,馬藹乃,楊蘇明;利用PHI數(shù)據(jù)進行區(qū)域性植物生理信息探測與分析(英文)[J];Acta Botanica Sinica;2002年08期

，

本文編號：1385323