Abstract：
Gene discovery reveals new biology, expands the utility of marker-assisted selection, and enables targeted mutagenesis. Still, such discoveries can take over a decade. We present a general strategy, \"Agile Genetics,\" that uses nested, structured populations to overcome common limits on gene resolution. Extensive simulation work on realistic genetic architectures shows that, at population sizes of >5000 samples, single gene-resolution can be achieved using bulk segregant pools. At this scale, read depth and technical replication become major drivers of resolution. Emerging enrichment methods to address coverage are on the horizon; we describe one possibility - iterative depth sequencing (ID-seq). In addition, graph-based pangenomics in experimental populations will continue to maximize accuracy and improve interpretation. Based on this merger of agronomic scale with molecular and bioinformatic innovation, we predict a new age of rapid gene discovery.
摘要：
基因发现揭示了新的生物学，扩展了标记辅助选择的效用，并实现靶向诱变。尽管如此，这样的发现可能需要十多年的时间。我们提出了一个总体战略，“敏捷遗传学，\"使用嵌套，结构化种群，以克服基因分辨率的常见限制。对现实遗传架构的大量模拟工作表明，在>5000个样本的人口规模下，单基因分辨率可以实现使用批量分离池。在这个尺度上,阅读深度和技术复制成为分辨率的主要驱动因素。解决覆盖问题的新兴富集方法即将出现；我们描述了一种可能性-迭代深度测序（ID-seq）。此外,在实验人群中基于图形的pangenomics将继续最大限度地提高准确性和改善解释。基于这种农艺尺度与分子和生物信息学创新的合并，我们预言了一个快速发现基因的新时代.
