Self-transcribing active regulatory region sequencing (STARR-seq) is widely used to identify enhancers at the whole-genome level. However, whether STARR-seq works as efficiently in plants as in animal systems remains unclear. Here, we determined that the traditional STARR-seq method can be directly applied to rice (Oryza sativa) protoplasts to identify enhancers, though with limited efficiency. Intriguingly, we identified not only enhancers but also constitutive promoters with this technique. To increase the performance of STARR-seq in plants, we optimized two procedures. We coupled fluorescence activating cell sorting (FACS) with STARR-seq to alleviate the effect of background noise, and we minimized PCR cycles and retained duplicates during prediction, which significantly increased the positive rate for activating regulatory elements (AREs). Using this method, we determined that AREs are associated with AT-rich regions and are enriched for a motif that the AP2/ERF family can recognize. Based on GC content preferences, AREs are clustered into two groups corresponding to promoters and enhancers. Either AT- or GC-rich regions within AREs could boost transcription. Additionally, disruption of AREs resulted in abnormal expression of both proximal and distal genes, which suggests that STARR-seq-revealed elements function as enhancers in vivo. In summary, our work provides a promising method to identify AREs in plants.

中文翻译：

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结合 STARR-seq 和 FACS 对水稻中激活调控元件的全基因组预测

自转录活性调控区测序 (STARR-seq) 广泛用于鉴定全基因组水平的增强子。然而，STARR-seq 在植物系统中是否像在动物系统中一样有效仍不清楚。在这里，我们确定传统的 STARR-seq 方法可以直接应用于水稻（Oryza sativa) 原生质体来识别增强子，但效率有限。有趣的是，我们不仅用这种技术鉴定了增强子，还鉴定了组成型启动子。为了提高 STARR-seq 在植物中的性能，我们优化了两个程序。我们将荧光激活细胞分选 (FACS) 与 STARR-seq 相结合以减轻背景噪声的影响，并且我们最大限度地减少了 PCR 循环并在预测过程中保留了重复项，这显着提高了激活调节元件 (ARE) 的阳性率。使用这种方法，我们确定 AREs 与富含 AT 的区域相关，并且丰富了 AP2/ERF 家族可以识别的基序。根据 GC 内容偏好，ARE 被分为两组，分别对应启动子和增强子。ARE 中富含 AT 或 GC 的区域都可以促进转录。体内。总之，我们的工作提供了一种很有前途的方法来识别植物中的 ARE。