农业作物改良的分子进展以满足当前的种植需求

Q3 Agricultural and Biological Sciences Hellenic Plant Protection Journal Pub Date : 2019-07-01 DOI:10.2478/HPPJ-2019-0006
T. Margaritopoulou, D. Milioni
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引用次数: 0

摘要

向日葵、玉米和土豆是世界上主要的农作物。为了改善各种性状,这些作物已经在很大程度上进行了基因工程改造。尽管简单性状的分子标记,如肥力、除草剂耐受性或特定病原体抗性已经成功地应用于标记辅助育种计划多年,但农学上重要的复杂数量性状,如产量、生物和非生物抗逆性和种子质量含量,具有挑战性,需要全基因组方法。这些作物的遗传资源在世界范围内保存,是研究复杂性状的宝贵资源。如今,技术的进步和基因组序列的可用性使全基因组水平的新方法成为可能。分子育种,包括转基因方法和标记辅助育种,促进了高密度图谱中大量标记的产生,并使向日葵、玉米和马铃薯的全基因组关联研究和基因组选择成为可能。与杂交性能相关的标记辅助选择表明,基因组选择是解决复杂数量性状和促进未来这些作物育种计划的成功方法。
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Molecular advances on agricultural crop improvement to meet current cultivating demands
Sunflower, maize and potato are among the world’s principal crops. In order to improve various traits, these crops have been genetically engineered to a great extent. Even though molecular markers for simple traits such as, fertility, herbicide tolerance or specific pathogen resistance have been successfully used in marker-assisted breeding programs for years, agronomical important complex quantitative traits like yield, biotic and abiotic stress resistance and seed quality content are challenging and require whole genome approaches. Collections of genetic resources for these crops are conserved worldwide and represent valuable resources to study complex traits. Nowadays technological advances and the availability of genome sequence have made novel approaches on the whole genome level possible. Molecular breeding, including both transgenic approach and marker-assisted breeding have facilitated the production of large amounts of markers for high density maps and allowed genome-wide association studies and genomic selection in sunflower, maize and potato. Marker-assisted selection related to hybrid performance has shown that genomic selection is a successful approach to address complex quantitative traits and to facilitate speeding up breeding programs in these crops in the future.
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来源期刊
Hellenic Plant Protection Journal
Hellenic Plant Protection Journal Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
1.50
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0.00%
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0
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