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Utility of natural populations for microarray analyses: Isolation of genes necessary for functional genomic studies

机译:天然种群用于微阵列分析的功能:功能基因组研究必需的基因的分离

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How much variation is there in gene expression? How is this variation partitioned within and among populations? How much variation is biologically important? That is, how much of this variation affects longevity, reproductive fitness, or probability of survival? Microarray analyses can be used to accurately quantify the expression of most, if not all, genes expressed in a tissue and thus address the first question. The latter questions can be investigated by examining the patterns of variation within and among natural populations of Fundulus. These populations are large and affected by historical, demographic, and selective constraints, providing a framework for the partition of variation in gene expression within and among populations. Additionally, the well established, phylogenetic relationship among Fundulus species can be used to discern adaptive change. A phylogenetic perspective reveals changes that are produced by natural selection and therefore indicates whether this variation affects longevity, reproductive fitness, or probability of survival, i.e., whether the variation is biologically important. However, a Fundulus microarray requires DNAs encoding specific Fundulus genes. This paper provides information on the production, isolation, and characterization of 4440 Fundulus cDNAs used in microarrays. Our approach was to pick random colonies from a normalized cDNA library and then PCR amplify and sequence these genes in a 96-well format. Periodically, the isolated and sequenced cDNAs were subtracted from the normalized library. Normalization reduced the number of redundant genes from 33% to 11%, increasing the effectiveness of this screening process. From 4440 sequenced cDNAs, 49% (2173) had a match in GenBank using BlastX searches. Of these, 53% were nonredundant, yielding 1149 identified genes. These data suggest that cDNAs necessary for microarray analyses can be produced effectively from most organisms.
机译:基因表达有多少变化?这种差异如何在人群内部和人群之间划分?多少变异在生物学上很重要?也就是说,这种差异在多大程度上影响寿命,生殖健康或生存可能性?微阵列分析可用于准确定量组织中表达的大多数(如果不是全部)基因的表达,从而解决第一个问题。可以通过检查眼底自然种群内部和之间的变异模式来调查后一个问题。这些人群很大,并受历史,人口和选择性限制的影响,为人群内和人群之间基因表达变异的分配提供了框架。此外,眼底物种之间建立良好的系统发育关系可用于识别适应性变化。系统发生学的观点揭示了自然选择产生的变化,因此表明该变化是否影响寿命,生殖适应性或存活概率,即该变化是否具有生物学重要性。但是,眼底微阵列需要编码特定眼底基因的DNA。本文提供了有关用于微阵列的4440眼底cDNA的产生,分离和表征的信息。我们的方法是从标准化的cDNA文库中选择随机菌落,​​然后进行PCR扩增,并以96孔格式对这些基因进行测序。定期从标准化文库中减去分离和测序的cDNA。标准化将冗余基因的数量从33%减少到11%,从而提高了此筛选过程的有效性。使用BlastX搜索,从4440个测序的cDNA中,有49%(2173)在GenBank中具有匹配项。其中53%是非冗余的,产生了1149个已鉴定的基因。这些数据表明,可以从大多数生物体有效产生微阵列分析所需的cDNA。

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