Few breeders have previously applied the sequence data to plant breeding in China. However, Dr. Yu Wang, an expert in data analysis, recently proposed a new data analysis method based on the combination of whole-genome sequence data and genomic prediction to optimize the famous molecular-assisted breeding, thus, filling a crucial gap in the field of plant breeding in China. This method has been applied in the Lettuce Genetic Variation Detection and Breeding Project (referred to as Lettuce Project) at the Genetic Resource Center of Wageningen University in the Netherlands. It has promoted the exploration of plant genetic variation detection in China.

In this project, 445 lettuce germplasm resources from 47 countries around the world were re-sequenced, including all cultivated types of lettuce and major wild relative species, fully revealing the complete domestication process of cultivated lettuce, and exploring the germplasm structure, the architecture of important agronomic traits and the identification of disease-resistance genes of lettuce. Dr. Yu Wang proposed to examine the reliability of genome prediction based on imputed whole-genome sequence genotypes, making full use of genetic variation to improve the recognition of molecular markers, and to identify candidate genes that affect essential agronomic traits of lettuce, thus improving the prediction accuracy of the performance of traits of interest during the selection process, and finally optimizing the popular molecular breeding methods. This method can achieve more accurate predictions for the performance of grain yield, stress resistance, and other important economic traits of major grain crops, thus helping breeders to breed superior crop varieties. At the same time, it can significantly speed up the selection cycle and, therefore, enhance the selection gains per unit of time and cost.

Population analysis of cultivated lettuce (shown in green in the picture) and wild related species

Part scientific results of this project have been published in the peer-reviewed scientific journal Nature Genetics. Based on this lettuce project, one of the world’s largest collections of lettuce germplasms has been built (https://db.cngb.org/lettuce/). This database collects lettuce genomic resources and germplasm information. It can be used as a lettuce research and breeding platform, available to lettuce researchers worldwide.

Dr. Yu Wang, an expert in data analysis in China, has made an irreplaceable role in numerous applications based on her deep understanding and rich experience in the application of data analysis in the field of crop genetics and breeding, biostatistics, and the active safety of commercial vehicles.

Besides the achievement in biostatistics and crop genetics and breeding, Dr. Yu Wang’s data analysis potential is also emerging in the fields of intelligent transportation and the active safety of commercial vehicles. According to the data of the China Federation of Logistics & Purchasing, 82.4% of truck drivers work 8 hours or longer per day, which poses a risk of fatigue driving and a significant hidden danger to the driving safety of commercial vehicles. As the ‘ex-chief data officer’ of Qianhai Chemi Yuntu Technology Co., Ltd., she proposed to construct the driver rating system, the fatigue driving model, and the driver portrait system, which created a new situation for analyzing drivers’ driving behavior in the field of active safety of commercial vehicles.

Since the driver rating system was integrated into the active safety intelligent surveillance platform in 2019, the drivers’ unsafe behaviors have dropped significantly, and 138 drivers’ hazardous driving behaviors have been monitored and corrected; By the end of 2019, the fatigue driving model was successfully applied to the platform, leading to a year-on-year decline of 52.21% in the total number of accidents per million vehicle kilometers and a drop of 50% in the rear-end accidents caused by fatigue. Taking urban public transport as an example, by the end of 2019, according to the insurance company, the claim ratio of accidents has dropped significantly over the previous year, with a total drop of over 30%, especially 70.2%, 47.2% and 41.1% in first three quarters, respectively.

Data has become a vital production resource with the advent of new technology eras such as big data, cloud computing, artificial intelligence, and 5G. ChatGPT, an artificial intelligence chat robot program developed by OpenAI in the United States, has become a hit since its debut in November 2022. Data analysis promotes the development of artificial intelligence robots. Also, it has been profitably applied in many applications, and data analysis will play a crucial role in different areas.

About Yu Wang (Female)

Dr. Yu Wang is now holding a Doctor degree in biostatistics from the University of Hohenheim in Germany, and a Master’s degree in plant genetics and breeding from the Chinese Academy of Agricultural Sciences and Shenyang Agricultural University, China. She specializes in data analysis that applies to the field of biostatistics, crop genetics and breeding, and the active safety of commercial vehicles. During her Master and PH.D., she has published four scholarly articles in professional publications with a total citation of 187, including Molecular Breeding, BMC Genomics, the Journal of Experimental Botany, and Theoretical and Applied Genetics, which have relatively high ranks in the field of Agronomy and Crop Science, Biotechnology, and Plant Science.

 

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