Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have rev...Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.展开更多
Sheep are one of the most economically important domesticated animals for human society. However, genetic improvements for the key traits associated with meat, growth, milk, wool, reproduction, horns and tails progres...Sheep are one of the most economically important domesticated animals for human society. However, genetic improvements for the key traits associated with meat, growth, milk, wool, reproduction, horns and tails progress slowly using conventional crossbreeding methods. With the development and utilization of highthroughput screening technologies over the last decade, a list of functional genes and genetic variants associated with these traits has been identified. This review covers recent genome-wide studies on sheep productive traits using high-throughput screening technologies, including those based on single-nucleotide polymorphisms and copy number variants at the whole-genome level(e.g.,genome-wide association studies), transcriptome and DNA methylation sequences. Additionally, comprehensive information on functional genes and genetic variants associated with economically important traits in sheep is provided.展开更多
基金supported by a grant from the Standardization and Integration of Resources Information for Seed-cluster in Hub-Spoke Material Bank Program,Rural Development Administration,Republic of Korea(PJ01587004).
文摘Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.
文摘全基因组重测序(whole-genome resequencing,WGRS)是一种基于参考基因组对同一物种不同个体进行测序并分析遗传差异的技术。通过WGRS可获得丰富的遗传变异信息,包括单核苷酸多态性(single nucleotide polymorphisms,SNPs)、结构变异(structural variations,SVs)、插入缺失(insertions and deletions,InDels)及拷贝数变异(copy number variations,CNVs)等。结合生物信息学技术,WGRS实现了对个体或群体基因组的全局比较与变异注释,为解析与畜禽重要性状相关的候选基因提供了可靠的数据基础。绵羊的大多数经济性状属于复杂的数量性状,受多个基因协同调控。基于WGRS数据的全基因组关联分析(genome-wide association studies,GWAS)和选择信号检测,已成为识别绵羊重要经济性状相关基因的有效手段。目前,WGRS主要依赖于第二代测序技术(next generation sequencing,NGS),未来的发展趋势则在于结合NGS和第三代测序技术(third generation sequencing,TGS)的优势,提升分析精度和效率。本文综述了近年来基于WGRS技术的绵羊经济性状研究进展,以期为进一步探索绵羊候选基因及分子标记提供重要见解与科学参考。
基金financially supported by the National Natural Science Foundation of China (31272413, 3161101336)the National Transgenic Breeding Project of China (2014ZX0800952B)+1 种基金the External Cooperation Program of Chinese Academy of Sciences (152111KYSB20150010)the Taishan Scholars Program of Shandong Province (201511085)
文摘Sheep are one of the most economically important domesticated animals for human society. However, genetic improvements for the key traits associated with meat, growth, milk, wool, reproduction, horns and tails progress slowly using conventional crossbreeding methods. With the development and utilization of highthroughput screening technologies over the last decade, a list of functional genes and genetic variants associated with these traits has been identified. This review covers recent genome-wide studies on sheep productive traits using high-throughput screening technologies, including those based on single-nucleotide polymorphisms and copy number variants at the whole-genome level(e.g.,genome-wide association studies), transcriptome and DNA methylation sequences. Additionally, comprehensive information on functional genes and genetic variants associated with economically important traits in sheep is provided.
