Sharma Monica, Sandhir Rajat, Singh Anuradha, Kumar Pankaj, Mishra Ankita, Jachak Sanjay, Singh Sukhvinder P, Singh Jagdeep, Roy Joy
National Agri-Food Biotechnology InstituteMohali, India; Department of Biochemistry, Panjab UniversityChandigarh, India.
Department of Biochemistry, Panjab University Chandigarh, India.
Front Plant Sci. 2016 Dec 15;7:1870. doi: 10.3389/fpls.2016.01870. eCollection 2016.
Phenolic compounds (PCs) affect the bread quality and can also affect the other types of end-use food products such as chapatti (unleavened flat bread), now globally recognized wheat-based food product. The detailed analysis of PCs and their biosynthesis genes in diverse bread wheat () varieties differing for chapatti quality have not been studied. In this study, the identification and quantification of PCs using UPLC-QTOF-MS and/or MS/MS and functional genomics techniques such as microarrays and qRT-PCR of their biosynthesis genes have been studied in a good chapatti variety, "C 306" and a poor chapatti variety, "Sonalika." About 80% (69/87) of plant phenolic compounds were tentatively identified in these varieties. Nine PCs (hinokinin, coutaric acid, fertaric acid, p-coumaroylqunic acid, kaempferide, isorhamnetin, epigallocatechin gallate, methyl isoorientin-2'-O-rhamnoside, and cyanidin-3-rutinoside) were identified only in the good chapatti variety and four PCs (tricin, apigenindin, quercetin-3-O-glucuronide, and myricetin-3-glucoside) in the poor chapatti variety. Therefore, about 20% of the identified PCs are unique to each other and may be "variety or genotype" specific PCs. Fourteen PCs used for quantification showed high variation between the varieties. The microarray data of 44 phenolic compound biosynthesis genes and 17 of them on qRT-PCR showed variation in expression level during seed development and majority of them showed low expression in the good chapatti variety. The expression pattern in the good chapatti variety was largely in agreement with that of phenolic compounds. The level of variation of 12 genes was high between the good and poor chapatti quality varieties and has potential in development of markers. The information generated in this study can be extended onto a larger germplasm set for development of molecular markers using QTL and/or association mapping approaches for their application in wheat breeding.
酚类化合物（PCs）会影响面包品质，也会影响其他类型的最终食用食品，如恰巴提（一种未发酵的扁平面包），它是目前全球公认的以小麦为原料的食品。对于不同恰巴提品质的各种面包小麦（）品种中PCs及其生物合成基因的详细分析尚未开展。在本研究中，已在优质恰巴提品种“C 306”和劣质恰巴提品种“索纳利卡”中，利用超高效液相色谱-四极杆飞行时间质谱仪（UPLC-QTOF-MS）和/或串联质谱仪（MS/MS）对PCs进行了鉴定和定量，并采用了功能基因组学技术，如对其生物合成基因进行微阵列分析和实时定量聚合酶链反应（qRT-PCR）。在这些品种中初步鉴定出约80%（69/87）的植物酚类化合物。仅在优质恰巴提品种中鉴定出9种PCs（扁柏双黄酮、对香豆酰奎尼酸、阿魏酸、对香豆酰奎尼酸、山奈酚、异鼠李素、表没食子儿茶素没食子酸酯、甲基异荭草素-2'-O-鼠李糖苷和矢车菊素-3-芸香糖苷），在劣质恰巴提品种中鉴定出4种PCs（小麦黄素、芹菜苷元、槲皮素-3-O-葡萄糖醛酸苷和杨梅素-3-葡萄糖苷）。因此，约20%已鉴定的PCs在两个品种中是各自独有的，可能是“品种或基因型”特异性PCs。用于定量分析的14种PCs在不同品种间表现出高度差异。44个酚类化合物生物合成基因的微阵列数据以及其中17个基因的qRT-PCR数据显示，在种子发育过程中表达水平存在差异，且大多数基因在优质恰巴提品种中表达较低。优质恰巴提品种中的表达模式与酚类化合物的表达模式基本一致。12个基因在优质和劣质恰巴提品质品种间的差异水平较高，具有开发标记的潜力。本研究中产生的信息可扩展到更大的种质资源集，利用数量性状位点（QTL）和/或关联作图方法开发分子标记，以应用于小麦育种。
