An ultra-high-density map as a community resource for discerning the genetic basis of quantitative traits in maize.
An ultra-high-density map as a community resource for discerning the genetic basis of quantitative traits in maize.
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超高密度图谱作为社区资源，用于识别玉米数量性状的遗传基础
DOI：
10.1186/s12864-015-2242-5
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发表时间：
2015-12-21
期刊：
影响因子：
4.4
通讯作者：
Pan G
中科院分区：
文献类型：
--
作者：
Liu H;Niu Y;Gonzalez-Portilla PJ;Zhou H;Wang L;Zuo T;Qin C;Tai S;Jansen C;Shen Y;Lin H;Lee M;Ware D;Zhang Z;Lübberstedt T;Pan G
为了保障不断增长的人类人口的食物供应，了解和开发数量性状的遗传基础是重要的。下一代测序技术在不同遗传资源的遗传图谱和基因组分析中发挥着优势和有效的作用。因此，我们将重测序技术和二元图策略相结合，构建了具有数千个二元组标记的超高密度二元图，以精确定位一个数量性状基因座。在本研究中，我们构建了一个包含1,151,856个优质SNPs的连锁图谱，该连锁图谱在B73 × Mo17(IBM)Syn10群体中得到了验证。该资源是对现有玉米遗传图谱的极好补充，可在在线数据库(iPLANT，http://data.maizecode.org/maize/qtl/syn10/).)中找到此外，在这个群体中，结合IBM Syn4 RIL群体，我们在两个群体中检测到135个控制开花时间和株高性状的QTL。18个已知功能基因和25个控制开花时间和株高性状的候选基因被精细定位在2.21-4.96亿Mb的区间内。对图谱扩展和分离扭曲进行了分析，并观察到在作图群体发展过程中不小心选择早花时间的证据。此外，还构建了包含1,151,856个优质SNPs、2,916个传统标记和6,618个bin标记的最新整合图谱。这些数据被存放在iPlants发现环境(DE)中，该环境为玉米遗传研究社区提供了基本的遗传数据来源。我们的发现为玉米遗传研究界提供了基本的基本遗传数据。更新的IBM Syn10群体和可靠的、经过验证的位于Mo17和B73之间的高质量SNP集将有助于未来的分子育种努力。本文的在线版本(doi：10.1186/s12864-0152242-5)包含补充材料，授权用户可以使用。
To safeguard the food supply for the growing human population, it is important to understand and exploit the genetic basis of quantitative traits. Next-generation sequencing technology performs advantageously and effectively in genetic mapping and genome analysis of diverse genetic resources. Hence, we combined re-sequencing technology and a bin map strategy to construct an ultra-high-density bin map with thousands of bin markers to precisely map a quantitative trait locus. In this study, we generated a linkage map containing 1,151,856 high quality SNPs between Mo17 and B73, which were verified in the maize intermated B73 × Mo17 (IBM) Syn10 population. This resource is an excellent complement to existing maize genetic maps available in an online database (iPlant, http://data.maizecode.org/maize/qtl/syn10/). Moreover, in this population combined with the IBM Syn4 RIL population, we detected 135 QTLs for flowering time and plant height traits across the two populations. Eighteen known functional genes and twenty-five candidate genes for flowering time and plant height trait were fine-mapped into a 2.21–4.96 Mb interval. Map expansion and segregation distortion were also analyzed, and evidence for inadvertent selection of early flowering time in the process of mapping population development was observed. Furthermore, an updated integrated map with 1,151,856 high-quality SNPs, 2,916 traditional markers and 6,618 bin markers was constructed. The data were deposited into the iPlant Discovery Environment (DE), which provides a fundamental resource of genetic data for the maize genetic research community. Our findings provide basic essential genetic data for the maize genetic research community. An updated IBM Syn10 population and a reliable, verified high-quality SNP set between Mo17 and B73 will aid in future molecular breeding efforts. The online version of this article (doi:10.1186/s12864-015-2242-5) contains supplementary material, which is available to authorized users.