QTL分析发现与药物反应相关的基因。

Saunak Sen, Michael Ferdig
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引用次数: 18

摘要

已完成的恶性疟原虫基因组序列提出了一项重大挑战:我们如何利用这些丰富的数据来应对疟疾寄生虫不断向多重耐药性发展的趋势?迄今为止,对寄生虫耐药性的研究主要集中在定性的单基因耐药性测定上;然而,强大的基因组学工具的出现坚持这些问题需要重新措辞。现在有可能解决定量药物敏感性背后的真正遗传复杂性。数量性状位点(QTL)定位是通过将影响这些性状的遗传效应划分到特定的基因组区域来跟踪多基因性状的有效工具。两个寄生虫克隆之间的杂交捕获了等位基因组合,这些等位基因组合分离成对药物表现出不同敏感性的后代克隆。每个亲本所贡献的特定等位基因形式及其组合,实际上是它们独特进化历史的遗传标记。除了耐药基因本身外,耐药寄生虫还携带共同进化的基因组合,包括耐药的遗传背景。对耐药性的研究必然是针对特定的基因和机制,这些基因和机制受到对耐药性如何起作用的先验知识和假设的支持。QTL定位,通过在基因组序列、结构多态性和基因表达数据上叠加真实的生物学表型,可以为构建复杂表型的基因作用网络提供一种替代的、公正的观点。通过综合方法,研究可以超越寻找耐药性标记,而是表征寄生虫产生新抗性和交叉抗性的易感性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
QTL analysis for discovery of genes involved in drug responses.

The completed Plasmodium falciparum genome sequence poses a significant challenge: how do we bring this wealth of data to bear against the steady march of malaria parasites towards multiple-drug resistance? Studies of parasite drug resistance have until now focused on a qualitative, single-gene concept of resistance determination; however, the emergence of powerful genomics tools insists that these questions be rephrased. It is now possible to address the true genetic complexity underlying quantitative drug sensitivities. Quantitative trait loci (QTL) mapping is an effective tool for tracking multi-gene traits by partitioning genetic effects that influence these traits into specific genomic regions. A cross between two parasite clones captures allele combinations that have segregated into progeny clones that display varying sensitivity to drugs. The specific allele forms and their combinations contributed by each parent are, in effect, genetic signatures of their unique evolutionary histories. In addition to resistance genes, per se, a drug resistant parasite carries co-evolved gene combinations comprising a genetic background of drug resistance. Research into drug resistance necessarily has been directed at specific genes and mechanisms favored by a priori knowledge and assumptions about how resistance works. QTL mapping, by superimposing real biological phenotypes on genome sequence, structural polymorphisms, and gene expression data, can provide an alternative, unbiased view of the network of gene actions that build a complex phenotype. Through an integrated approach, studies can move beyond the search for markers of resistance to instead characterize the predisposition of parasites to develop new resistances and cross-resistances.

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