A New Advanced Backcross Tomato Population Enables High Resolution Leaf QTL Mapping and Gene Identification.
A New Advanced Backcross Tomato Population Enables High Resolution Leaf QTL Mapping and Gene Identification.
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新的先进的番茄番茄种群可以实现高分辨率的叶子QTL映射和基因识别。
DOI：
10.1534/g3.116.030536
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发表时间：
2016-10-13
期刊：
影响因子：
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通讯作者：
Sinha NR
中科院分区：
文献类型：
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作者：
Fulop D;Ranjan A;Ofner I;Covington MF;Chitwood DH;West D;Ichihashi Y;Headland L;Zamir D;Maloof JN;Sinha NR
数量性状基因座（QTL）定位是剖析性状和物种差异遗传基础的有力技术。在已建立的番茄作图群体中，驯化番茄（Solanum lycopersicum）与其远缘可育近缘种之间通常遵循近等基因系（NIL）设计，如S。pennellii渐渗系（IL）群体，在其它驯化的遗传背景中每个系具有单个野生渐渗。在这里，我们报告了一个新的先进的番茄回交QTL定位资源，来自M82番茄品种和S。pennellii。这种所谓的回交自交系（BIL）群体由BC2和BC3系的混合物组成，驯化番茄作为轮回亲本。BIL人口是现有S的补充。pennellii IL种群，它与父母共享。使用BILs，我们映射叶的复杂性，小叶形状和开花时间的性状。我们证明了实用的BILs精细定位QTL，特别是QTL最初映射在IL，精细定位几个QTL到单个或几个候选基因。此外，我们确认了回交群体的价值与多个渐渗每线，如BILs，上位QTL定位。我们的工作进一步使我们自己的统计推断和可视化工具的发展，即异质隐马尔可夫模型的基因分型线，并通过使用国家的最先进的稀疏回归技术QTL定位。
Quantitative Trait Loci (QTL) mapping is a powerful technique for dissecting the genetic basis of traits and species differences. Established tomato mapping populations between domesticated tomato (Solanum lycopersicum) and its more distant interfertile relatives typically follow a near isogenic line (NIL) design, such as the S. pennellii Introgression Line (IL) population, with a single wild introgression per line in an otherwise domesticated genetic background. Here, we report on a new advanced backcross QTL mapping resource for tomato, derived from a cross between the M82 tomato cultivar and S. pennellii. This so-called Backcrossed Inbred Line (BIL) population is comprised of a mix of BC2 and BC3 lines, with domesticated tomato as the recurrent parent. The BIL population is complementary to the existing S. pennellii IL population, with which it shares parents. Using the BILs, we mapped traits for leaf complexity, leaflet shape, and flowering time. We demonstrate the utility of the BILs for fine-mapping QTL, particularly QTL initially mapped in the ILs, by fine-mapping several QTL to single or few candidate genes. Moreover, we confirm the value of a backcrossed population with multiple introgressions per line, such as the BILs, for epistatic QTL mapping. Our work was further enabled by the development of our own statistical inference and visualization tools, namely a heterogeneous hidden Markov model for genotyping the lines, and by using state-of-the-art sparse regression techniques for QTL mapping.