Mahadevaiah Channappa, Appunu Chinnaswamy, Aitken Karen, Suresha Giriyapura Shivalingamurthy, Vignesh Palanisamy, Mahadeva Swamy Huskur Kumaraswamy, Valarmathi Ramanathan, Hemaprabha Govind, Alagarasan Ganesh, Ram Bakshi
Division of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore, India.
CSIRO (Commonwealth Scientific and Industrial Research Organization), St. Lucia, QLD, Australia.
Front Plant Sci. 2021 Sep 27;12:708233. doi: 10.3389/fpls.2021.708233. eCollection 2021.
Sugarcane is a C4 and agro-industry-based crop with a high potential for biomass production. It serves as raw material for the production of sugar, ethanol, and electricity. Modern sugarcane varieties are derived from the interspecific and intergeneric hybridization between , and other wild relatives. Sugarcane breeding programmes are broadly categorized into germplasm collection and characterization, pre-breeding and genetic base-broadening, and varietal development programmes. The varietal identification through the classic breeding programme requires a minimum of 12-14 years. The precise phenotyping in sugarcane is extremely tedious due to the high propensity of lodging and suckering owing to the influence of environmental factors and crop management practices. This kind of phenotyping requires data from both plant crop and ratoon experiments conducted over locations and seasons. In this review, we explored the feasibility of genomic selection schemes for various breeding programmes in sugarcane. The genetic diversity analysis using genome-wide markers helps in the formation of core set germplasm representing the total genomic diversity present in the gene bank. The genome-wide association studies and genomic prediction in the gene bank are helpful to identify the complete genomic resources for cane yield, commercial cane sugar, tolerances to biotic and abiotic stresses, and other agronomic traits. The implementation of genomic selection in pre-breeding, genetic base-broadening programmes assist in precise introgression of specific genes and recurrent selection schemes enhance the higher frequency of favorable alleles in the population with a considerable reduction in breeding cycles and population size. The integration of environmental covariates and genomic prediction in multi-environment trials assists in the prediction of varietal performance for different agro-climatic zones. This review also directed its focus on enhancing the genetic gain over time, cost, and resource allocation at various stages of breeding programmes.
甘蔗是一种基于农业产业的C4作物，具有很高的生物质生产潜力。它是生产糖、乙醇和电力的原材料。现代甘蔗品种源自 与其他野生近缘种之间的种间和属间杂交。甘蔗育种计划大致分为种质收集与鉴定、预育种与遗传基础拓宽以及品种培育计划。通过传统育种计划进行品种鉴定至少需要12至14年。由于环境因素和作物管理措施的影响，甘蔗极易倒伏和分蘖，因此精确的表型分析极其繁琐。这种表型分析需要来自不同地点和季节的宿根作物和新植作物试验的数据。在本综述中，我们探讨了甘蔗各种育种计划中基因组选择方案的可行性。使用全基因组标记进行遗传多样性分析有助于形成代表基因库中存在的全部基因组多样性的核心种质。基因库中的全基因组关联研究和基因组预测有助于识别甘蔗产量、商业蔗糖、对生物和非生物胁迫的耐受性以及其他农艺性状的完整基因组资源。在预育种、遗传基础拓宽计划中实施基因组选择有助于特定基因的精确导入，轮回选择方案可提高群体中有利等位基因的频率，同时显著缩短育种周期和缩小群体规模。在多环境试验中整合环境协变量和基因组预测有助于预测不同农业气候区的品种表现。本综述还着重关注在育种计划的各个阶段随着时间推移、成本和资源分配提高遗传增益。
