ARTICLE doi:10.1038/nature11532 A map of rice genome variation reveals the origin of cultivated rice Xuehui Huang1*, Nori Kurata2*, Xinghua Wei3*, Zi-Xuan Wang1,2*, Ahong Wang1, Qiang Zhao1, Yan Zhao1, Kunyan Liu1, Hengyun Lu1, Wenjun Li1, Yunli Guo1, Yiqi Lu1, Congcong Zhou1...
Moreover, a comprehensive map of rice genome variation will facilitate genetic mapping of complex traits in rice. We recently collected diverse rice cultivars for sequencing, and carried out genome-wide association studies (GWAS) for many agronomic traits in cultivated rice21,22. Here we sequenced ...
However,most mapping strategies based on different molecular markers are very time-consuming and then make gene cloning difficult.Here we present a useful method for rapidly cloning rice resistance genes based on the connection of map-based strategy and next-generation genomic sequencing.In this ...
This is the first integrated study to screen the MY2 RIL population (185 lines) derived from two US rice cultivars, “Cypress and LaGrue”, for grain quality traits such as GL, GW, and % chalk at booting stage (R2: reproductive stage) under HNT stress, map & characterize the QTLs regio...
and the hyperplane established by using these intercept points meets∑i=1Mfin=1. The set of structured reference points established by the system method will be uniformly distributed in the normalized hyperplane. In each generation of the algorithm process, the calculated poles will be used to comp...
The solution of λ was obtained by maximizing the above likelihood function using the newton iteration algorithm. The GBLUP method exploits the genomic relationships between training population and testing population to predict the genomic values for unknown individuals without estimating marker effects. ...
(biotic and abiotic) phenotyping for identification, classification, quantification, and prediction (ICQP) to make best use of digital image–based phenomics data (Singh et al.2018). Such technique based panicle segmentation algorithm has been found promising in rice to study different reproductive ...
CEL files generated in GeneChip Operating Software (GCOS) were further analyzed using avadis™. Data were normalized using GCRMA algorithm and log transformed. To get the expression values, averages of three biological replicates were used. The expression data for MADS-box genes was extracted by ...
The MSI-based RF algorithm inside the GEE performed paddy rice fields classification in a very short time. Thus, high-performance computing resources like GEE facilitate quick and rapid mapping of paddy rice planting areas at a large scale1,6. Future studies of paddy rice mapping under similar ...
The classifier and the weights learned in the feature extractor are trained by a back-propagation algorithm. A convolutional layer computes feature maps by applying convolution kernels to input data followed by an activation function as follows27: $${y}_{j}^{l}=f({z}_{j}^{l})$$ (1) ...