類別資料探索分析用於番茄晚疫病中的基因作用

Abstract

近期在遺傳科學領域，特別是定序技術方面的進步，大大提升了我們對基因或數量性狀基因座(QTL)與表型特徵之間關係的了解，這對植物育種研究有重要助益。次世代定序(NGS)技術使得更有效識別與作物病害抵抗等特性相關的基因和基因座成為可能。這對於對抗由Phytophthora infestans引起的晚疫病至關重要，該病害在全球範圍內對番茄和馬鈴薯造成顯著影響。 本研究脫離了傳統的線性模型，採用常用於類別型分析的卡方檢定(Chi-square test)對遺傳和表型數據進行分析，用以捕捉基因型與性狀表現之關係。此外，我們應用了源於信息理論的互條件熵(MCE)方法來幫助辨識與番茄晚疫病抗性相關的基因間交互作用。MCE方法強調基於計數的分析方式，特別著重於識別可能影響晚疫病抗性的遺傳因子組合。 我們利用美國國家生物技術資訊中心(NCBI)的局部相似性基本查詢工具(BLAST)將我們數據集中的序列與已知蛋白進行匹配，以驗證我們識別的遺傳標記是否與疾病抗性蛋白相關。本研究發現數個潛在的病害抗性相關基因，包括四個含多白胺酸重複(LRR)的蛋白質基因。值得注意的是，LRR是植物抗性蛋白中常見的結構。希望藉由持續的研究，並使用多樣的遺傳數據集，能評估這方法的有效性並驗證此研究的發現。

Recent advances in genetic science, especially sequencing technology, have greatly advanced our understanding of the relationship between genes or quantitative trait loci (QTL) and phenotypic traits, aiding plant breeding research. Next-generation sequencing (NGS) has enabled more efficient identification of genes and mapping of loci associated with traits like disease resistance in crops. This is crucial for combating Late blight, caused by Phytophthora infestans, which significantly affects tomatoes and potatoes worldwide. This research diverged from traditional linear approaches, using categorical analysis like the Chi-square test for genetic and phenotypic data to reveal complex genotype-phenotype connections. We also applied Mutual Conditional Entropy (MCE), an information theory-based method, to identify the potential gene interactions related to tomato late blight resistance, focusing on interactive genetic factors that may affect this resistance. Utilizing Basic Local Alignment Search Tool (BLAST) provided by the National Center for Biotechnology Information (NCBI), we matched the sequences in our dataset with known proteins to verify if our identified markers are linked to disease resistance proteins. Our study highlighted the discovery of several significant resistance genes, including four Leucine-rich repeat (LRR) protein genes. LRR is a common structure in plant resistance proteins. Ongoing research, employing diverse genetic datasets, is vital to thoroughly evaluate the efficacy of this approach and validate our findings.