摘 要
單核苷酸多態(tài)性（Single Nucleotide Polymorphism, SNP）是由單堿基顛換、轉(zhuǎn)換、插入或缺失引起的DNA序列變異。與限制性片段長度多態(tài)性（Restriction Fragment Length Polymorphism，RFLP）和簡單重復(fù)序列（Simple Sequence Repeat，SSR）等常用分子標(biāo)記相比，SNP具有分布密度高、遺傳穩(wěn)定、與表型性狀相關(guān)性強(qiáng)、檢測簡便、易于實(shí)現(xiàn)自動(dòng)化分析等諸多優(yōu)點(diǎn)，被稱為第三代分子標(biāo)記。針對(duì)SSR分子標(biāo)記密度不足， 現(xiàn)有的SNP分子標(biāo)記開發(fā)一般只基于兩種基因型的序列差異，用以檢測其他基因型的材料時(shí)多態(tài)性不高，不能滿足目前玉米基因精細(xì)定位需要的現(xiàn)狀，本研究從公共數(shù)據(jù)庫下載來自不同遺傳背景的玉米表達(dá)序列標(biāo)簽（Expressed Sequence Tag，EST），運(yùn)用各種生物信息學(xué)軟件和自主編寫的程序，開發(fā)基于EST序列的SNP分子標(biāo)記，并通過高分辨率熔解（High Resolution Melt，HRM）技術(shù)驗(yàn)證部分標(biāo)記的多態(tài)性。
以生物信息學(xué)理論為基礎(chǔ)，利用Blast、Cross_Match、Phrap、ePrimer3、e-PCR和自主開發(fā)的Perl腳本程序，基于Windows XP和Linux操作系統(tǒng)構(gòu)建數(shù)據(jù)分析系統(tǒng)，并使用Perl語言結(jié)合Bioperl模塊編寫的腳本程序讓整個(gè)分析過程自動(dòng)化，使EST數(shù)據(jù)得到快速、有效的分析。該數(shù)據(jù)分析系統(tǒng)完成了EST序列聚類，載體序列、低質(zhì)量序列和重復(fù)序列的去除，EST序列拼接，SNP位點(diǎn)的發(fā)掘，PCR引物的設(shè)計(jì)和篩選，SNP分子標(biāo)記定位以及多態(tài)性信息含量（Polymorphism Information Content，PIC）計(jì)算。
通過對(duì)2018530條玉米EST序列的聚類與拼接發(fā)掘出遍布全基因組的80363個(gè)SNP位點(diǎn)。在SNP位點(diǎn)兩側(cè)的保守序列上設(shè)計(jì)PCR引物，開發(fā)出12388個(gè)SNP分子標(biāo)記，包含34721個(gè)SNP位點(diǎn)，12762個(gè)位點(diǎn)的多態(tài)性信息含量（PIC）大于0.4，具有高度多態(tài)性。其中，6008個(gè)標(biāo)記只含單一的SNP位點(diǎn)。根據(jù)SNP標(biāo)記所在“B73”自交系基因組BAC序列在染色體上的位置，12117個(gè)標(biāo)記可定位于玉米的10條染色體上，以第1染色體上的標(biāo)記最多。并基于Microsoft Windows XP操作系統(tǒng)，利用Adobe Dreamweaver等軟件在四川農(nóng)業(yè)大學(xué)玉米研究所網(wǎng)站上建立標(biāo)記公共數(shù)據(jù)庫的靜態(tài)平臺(tái)（http://www.sicau.edu.cn/web/yms/snp/snp.html），所有SNP分子標(biāo)記及相關(guān)信息可登錄該網(wǎng)頁查閱。
從所開發(fā)的SNP分子標(biāo)記中隨機(jī)挑選9對(duì)標(biāo)記引物，以46個(gè)玉米自交系的為材料，根據(jù)差異核苷酸高分辨率熔解曲線形狀的不同，利用HRM技術(shù)對(duì)加有飽和熒光染料的實(shí)時(shí)定量PCR擴(kuò)增產(chǎn)物進(jìn)行基因分型來驗(yàn)證SNP的多態(tài)性。熒光值差異曲線顯示：在有熒光信號(hào)的自交系中，9對(duì)引物的PCR產(chǎn)物都被HRM分型，表現(xiàn)出多態(tài)性，P5和P6出現(xiàn)兩種基因型，其余引物都顯示出3種基因型，SNP檢測率為100%。熔解峰顯示：對(duì)于有信號(hào)的自交系，9對(duì)引物的PCR產(chǎn)物熔解峰都為單一峰，無非特異性擴(kuò)增及引物二聚體產(chǎn)生，且峰值相近，說明這些引物的特異性高較好。由于在SNP標(biāo)記開發(fā)過程中，引物是基于模式自交系“B73”的BAC文庫設(shè)計(jì)及篩選的，擴(kuò)增信號(hào)的有無可能跟B73與其他自交系在引物結(jié)合區(qū)域的核苷酸差異有關(guān)。每對(duì)引物都有少數(shù)自交系目的條帶沒有被擴(kuò)增出來，HRM熔解無熒光信號(hào)，其中，P4只有“丹340”無信號(hào)，P1最多，有14個(gè)自交系沒有信號(hào)。
綜上所述，本研究開發(fā)SNP分子標(biāo)記共計(jì)12388個(gè)，其中6008個(gè)標(biāo)記只含單一的SNP位點(diǎn)，這些標(biāo)記具有較高的多態(tài)性，在基因精細(xì)定位、關(guān)聯(lián)分析及分子標(biāo)記輔助育種上具有一定的應(yīng)用價(jià)值。
關(guān)鍵詞：玉米；表達(dá)序列標(biāo)簽；單核苷酸多態(tài)性分子標(biāo)記；高分辨率熔解曲線








Abstract
A single-nucleotide polymorphism (SNP) is a DNA sequence variation caused by nucleotides substitution, deletion or insertion. Compared with the commonly used molecular makers such as restriction fragment length polymorphism (RFLP) and simple sequence repeat (SSR), SNP is recognized as the third generation of molecular makers for its high density coverage, stable heredity, high correlation with phenotype, easy detection and automatical analysis, and so on. Due to the inadequate density of SSR markers, and the inadequate polymorphism of SNP markers developed based on sequence difference between only two genotypes, these two kinds of DNA molecular markers do not meet the current demand of fine mapping for maize genes. In this study, expressed sequence tags (EST) of maize (Zea mays) with different genetic background were downloaded from public databases, and used for the development of SNP molecular markers, with the help of different bioinformatical softwares and self-developed Perl scripts. High resolution melt (HRM) was used to eva luate the predicted SNP makers.
Based on Windows XP and Linux operating systems, software such as Blast, cross_match, Phrap, ePrimer3, e-PCR and self-developed Perl scripts were used to construct an analysis system by bioinformatics approach. Moreover, using Bioperl modules, the scripts written with Perl language make automatization of the whole analysis process come true. The data of EST could be analyzed promptly and effectively. The analysis system includes Clustering EST sequences, clipping vectors, detecting low quality and repeated sequences, aligning EST sequences, mining SNP sites, designing and filtrating PCR primers, mapping SNP molecular marker on chromosome and calculating polymorphism information content (PIC).
On the basis of the Cluster and alignment among 2018530 pieces of EST sequences, 80363 SNP loci were found out throughout the genome. According to the flanking conserved sequences beyond these SNP loci, 12388 pairs of PCR primers were designed to amplify sequences involving 34721 SNP loci, and provided to be used as SNP molecular markers, among which 6008 contain only one S..