The Carotenoid Cleavage Dioxygenase Gene CCD7-B, at Large, Is Associated with Tillering in Common Wheat

Abstract

Wheat, an important cereal crop, is responsible for the livelihoods of many people, and a component of national food security. Tillering, which determines plant architecture and spike number, is a critical agronomic trait of wheat. The carotenoid cleavage dioxygenase 7 (CCD7) has an important effect on the growth of tillers or lateral branches and lateral roots of plants. In order to study the relationship between CCD7 and tillering in wheat, CCD7-B was isolated from 10 Chinese wheat varieties with different tiller numbers. Subsequently, bioinformatics, allelic variation analysis, and field experiments were performed. Wheat CCD7-B belongs to the retinal pigment epithelial membrane receptor (RPE65) superfamily; it displays the greatest homology with monocot CCD7 proteins. Phylogenetic analysis of wheat CCD7-B proteins indicated division into dicotyledonous and monocotyledonous clades. Allelic variation analysis of CCD7-B via SrgAI enzyme digestion (a marker of cleaved amplified polymorphic sequences) suggested that 262 Chinese wheat micro-core collections and 121 Chinese wheat major cultivars from the Yellow and Huai River Valley winter wheat region can be divided into two groups: CCD7-B1 (C/T/T) and CCD7-B2 (G/C/A). CCD7-B1 showed better allelic variation than did CCD7-B2 for increasing the number of effective tillers of wheat varieties in China. This study provides reference data for the application of CCD7-B alleles to wheat breeding and supports further research regarding the mechanism of tillering in common wheat.

Variational iteration method along with intelligent computing system for the radiated flow of electrically conductive viscous fluid through porous medium

“…Fluidic models [ [25] , [26] , [27] , [28] , [29] , [30] ], Dioxygenase Gene [ 31 ], smoking model [ 32 ], cantilever piezoelectric-mechanical [ 33 ], plant virus [ 34 ], Stuxnet virus [ 35 ] and COVID-19 model [ 36 ] are some recent work of ANNs. The numerical and artificial neural network simulation of unsteady hydromagnetic Williamson fluid flow in a radiative surface was investigated by Shafiq, A., et al [ 37 ].…”