Department of Horticulture, University of Wisconsin, Madison, WI, USA.
Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Aguascalientes, Mexico.
Mol Genet Genomics. 2018 Dec;293(6):1379-1392. doi: 10.1007/s00438-018-1464-z. Epub 2018 Jul 2.
Because of its known phytochemical activity and benefits for human health, American cranberry (Vaccinium macrocarpon L.) production and commercialization around the world has gained importance in recent years. Flavonoid compounds as well as the balance of sugars and acids are key quality characteristics of fresh and processed cranberry products. In this study, we identified novel QTL that influence total anthocyanin content (TAcy), titratable acidity (TA), proanthocyanidin content (PAC), Brix, and mean fruit weight (MFW) in cranberry fruits. Using repeated measurements over the fruit ripening period, different QTLs were identified at specific time points that coincide with known chemical changes during fruit development and maturation. Some genetic regions appear to be regulating more than one trait. In addition, we demonstrate the utility of digital imaging as a reliable, inexpensive and high-throughput strategy for the quantification of anthocyanin content in cranberry fruits. Using this imaging approach, we identified a set of QTLs across three different breeding populations which collocated with anthocyanin QTL identified using wet-lab approaches. We demonstrate the use of a high-throughput, reliable and highly accessible imaging strategy for predicting anthocyanin content based on cranberry fruit color, which could have a large impact for both industry and cranberry research.
由于其已知的植物化学活性和对人类健康的益处，近年来，蔓越莓（Vaccinium macrocarpon L.）的生产和商业化在全球范围内变得越来越重要。黄酮类化合物以及糖和酸的平衡是新鲜和加工过的蔓越莓产品的关键质量特征。在这项研究中，我们确定了影响蔓越莓果实中总花青素含量（TAcy）、可滴定酸度（TA）、原花青素含量（PAC）、Brix 和平均果实重量（MFW）的新 QTL。使用果实成熟期间的重复测量，在特定时间点确定了不同的 QTL，这些时间点与果实发育和成熟过程中的已知化学变化相吻合。一些遗传区域似乎同时调节多个性状。此外，我们还证明了数字成像作为一种可靠、廉价且高通量的策略，可用于量化蔓越莓果实中的花青素含量。使用这种成像方法，我们在三个不同的育种群体中确定了一组与使用湿实验室方法鉴定的花青素 QTL 共定位的 QTL。我们展示了一种高通量、可靠且高度可访问的成像策略，用于根据蔓越莓果实颜色预测花青素含量，这对工业和蔓越莓研究都将产生重大影响。
