NSF Postdoctoral Fellowship in Biology FY 2020: Genetic Determinants of Hybrid Decay in Backcross Populations of Teosinte with Maize

这项行动资助了2018财年的NSF国家植物基因组计划生物学博士后研究奖学金。该研究金支持研究员在东道实验室的研究和培训计划，研究员还提出了扩大生物学参与的计划。向Manisha Munasinghe提供的研究和培训计划的标题是“大刍草与玉米回交群体中杂种衰退的遗传决定因素”。该研究金的主办机构是明尼苏达大学，赞助科学家是Yaniv Brandvain博士和Nathan Springer博士。植物育种者试图利用作物物种野生亲缘物种中存在的有用的遗传变异。物种之间的遗传不相容性可能不利于这一目标，这使得理解它们如何在种群中出现和持续具有高度相关性。玉米与其野生亲缘种墨西哥大刍草之间的独特不亲和性被认为是由杂交种中重复DNA的不受控制的增殖引发的。该项目的目的不仅是确定这种不相容性背后的特定遗传变异，而且还利用这些知识来扩展进化理论，以更好地了解这些变异是如何在人群中建立起来的。研究员的培训目标包括植物生物学，计算生物学，统计遗传学和分析建模。更广泛的影响包括为本科生开发遗传学和统计学两个教学模块，并通过参加Carpentries（www.carpentries.org）计算培训讲习班提供指导和培训。 长期以来，人们一直对了解生殖隔离的基因组基础感兴趣，因为它既可以告知物种形成如何发生，也可以告知谱系内发生的进化力量。自私的重复DNA（如转座因子）的解偶联，以及表观遗传学上沉默其增殖的分子机制是杂交不亲和性的潜在原因，但相对较少受到关注。该项目探讨了作物玉米与其野生亲缘墨西哥大刍草之间杂交不亲和的一个不寻常案例，认为这是由重复DNA与阻止其增殖的变异体解偶联引起的。没有异常表型的F1杂种，持续的不亲和性，尽管经常回交到玉米，杂交后代的表观遗传变化区分这种情况下，从其他。该项目将描述这种上位不亲和性的基因组基础，估计其在自然界中的频率，并模拟其对全基因组渗入模式的影响。长读，全基因组测序将允许精细规模的特点，在重复DNA的变化之间的亲本物种和杂交种。将收集更多的大刍草样本进行群体水平的分析，以确定选择下的区域，其中可能包括重复的DNA阻遏系统。最后，解偶联的重复DNA从其阻遏系统的后果将被建模，以表征其对群体分歧的影响。所有的计算机管道和代码都将公开共享，以便其他研究人员可以根据他们的需要调整这些工具。原始数据/代码将通过公共存储库发布，如GitHub或NCBI。处理后的数据集将通过CyVerse Data Commons、Dryad或DRUM（www.lib.umn.edu/datamanagement/drum）发布。所有经过处理的数据和任何可能对更广泛的社区感兴趣的文件都将通过CyVerse或GitHub公开提供，并与MaizeGDB共享。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2018. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to Manisha Munasinghe is "Genetic Determinants of Hybrid Decay in Backcross Populations of Teosinte with Maize". The host institution for the fellowship is the University of Minnesota and the sponsoring scientists are Drs. Yaniv Brandvain and Nathan Springer. Plant breeders seek to take advantage of useful genetic variants present in wild relatives of crop species. Genetic incompatibilities between species can work against this goal, which makes understanding how they emerge and persist in populations highly relevant. A unique incompatibility between the crop species maize and its wild relative the Mexican teosinte is thought to be triggered by the uncontrolled proliferation of repetitive DNA in hybrids. This project is designed to not only identify the specific genetic variants underlying this incompatibility but also to use this knowledge to expand evolutionary theory to better understand how these variants become established in populations. Training objectives for the Fellow include plant biology, computational biology, statistical genetics, and analytical modeling. Broader impacts include the development of two teaching modules in genetics and statistics for undergraduate students and providing mentoring and training through participation in the Carpentries (www.carpentries.org) computational training workshops. There is a longstanding interest in understanding the genomic basis of reproductive isolation as it can both inform how speciation occurs and the evolutionary forces occurring within lineages. The uncoupling of selfish repetitive DNA, such as transposable elements, and the molecular machinery that epigenetically silences their proliferation is a potential cause of hybrid incompatibility that has received comparatively little attention. This project explores an unusual case of hybrid incompatibility between the crop species maize and its wild relative Mexican teosinte thought to be caused by the uncoupling of repetitive DNA from the variants that halt their proliferation. No abnormal phenotype in the F1 hybrids, the persistence of the incompatibility despite recurrent backcrossing to maize, and epigenetic changes in hybrids distinguish this case from others. This project will characterize the genomic basis of this epistatic incompatibility, estimate its frequency in nature, and model its impacts on genome-wide patterns of introgression. Long-read, whole-genome sequencing will allow the fine-scale characterization of changes in repetitive DNA between the parental species and hybrids. Additional teosinte samples will be collected to perform population-level analyses to identify regions under selection, which will likely include repetitive DNA repressor systems. Finally, the consequence of uncoupling repetitive DNA from its repressor system will be modelled to characterize its effect on population divergence. All computer pipelines and codes will be shared publicly so other researchers may adapt these tools to their needs. Raw data/code will be released through public repositories, such as GitHub or NCBI. Processed datasets will be released through CyVerse Data Commons, Dryad, or DRUM (www.lib.umn.edu/datamanagement/drum). All processed data and any files that may be of interest to the broader community will be made publicly available through CyVerse or GitHub and will also be shared with MaizeGDB.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.