Dijkhuizen Rens, van Eijnatten Abraham L, Mehrem Sarah L, van den Bergh Esther, van Lieshout Jelmer, Spaninks Kiki, Kaandorp Steven, Offringa Remko, Proveniers Marcel, van den Ackerveken Guido, Snoek Basten L
Theoretical Biology and Bioinformatics, Department of Biology, Science Faculty, Institute of Biodynamics and Biocomplexity, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands.
Translational Plant Biology, Department of Biology, Science Faculty, Institute of Environmental Biology, Utrecht University, Padualaan 8, Utrecht, 3584CH, The Netherlands.
Plant J. 2025 Aug;123(3):e70405. doi: 10.1111/tpj.70405.
In recent years, accurate and low-cost variant calling has enabled the genotyping of large diversity panels for genome-wide association studies. As a result, phenotyping rather than genotyping is now the rate-limiting step, especially in field experiments. This has created a strong need for high-throughput, accurate, and low-cost in-field phenotyping. Here, we present a genome-wide association study (GWAS) study on 194 field-grown accessions of lettuce (Lactuca sativa). These accessions were non-destructively phenotyped at two time points 15 days apart using a drone equipped with an RGB and multispectral (MSP) camera. Our high-throughput phenotyping approach integrates an RGB- and MSP camera to measure the color and height of lettuce in this large-scale field experiment. We used the mean and other summary statistics, such as median, quantiles, skewness, kurtosis, minimum, and maximum to quantify different aspects of color and height variation in lettuce from the drone images. Using these summary statistics as traits for GWAS, we confirm several previously described genetic associations, now under field conditions, and identify additional novel associations for color and height traits in lettuce.
近年来，准确且低成本的变异检测使得在全基因组关联研究中对大量多样化群体进行基因分型成为可能。因此，现在表型分析而非基因分型成为了限速步骤，尤其是在田间试验中。这就产生了对高通量、准确且低成本的田间表型分析的强烈需求。在此，我们展示了一项针对194份田间种植的生菜（Lactuca sativa）种质的全基因组关联研究（GWAS）。这些种质在相隔15天的两个时间点使用配备了RGB和多光谱（MSP）相机的无人机进行了非破坏性表型分析。我们的高通量表型分析方法在这个大规模田间试验中整合了RGB和MSP相机来测量生菜的颜色和高度。我们使用均值以及其他汇总统计量，如中位数、分位数、偏度、峰度、最小值和最大值，来量化无人机图像中生菜颜色和高度变化的不同方面。将这些汇总统计量用作GWAS的性状，我们证实了一些先前描述的遗传关联（现在是在田间条件下），并鉴定出了生菜颜色和高度性状的其他新关联。
