Sugarcane (Saccharum spp.) is one of the most economically significant crops because of its high sucrose content and it is a promising biomass feedstock for biofuel production. Sugarcane genome sequencing and analysis is a difficult task due to its heterozygosity and polyploidy. Long sequence read technologies, PacBio Single-Molecule Real-Time (SMRT) sequencing, the Illumina TruSeq, and the Oxford Nanopore sequencing could solve the problem of genome assembly. On the applications side, next generation sequencing (NGS) technologies played a major role in the discovery of single nucleotide polymorphism (SNP) and the development of low to high throughput genotyping platforms. The two mainstream high throughput genotyping platforms are the SNP microarray and genotyping by sequencing (GBS). This paper reviews the NGS in sugarcane genomics, genotyping methodologies, and the choice of these methods. Array-based SNP genotyping is robust, provides consistent SNPs, and relatively easier downstream data analysis. The GBS method identifies large scale SNPs across the germplasm. A combination of targeted GBS and array-based genotyping methods should be used to increase the accuracy of genomic selection and marker-assisted breeding.

甘蔗（甘蔗spp。）是最经济的农作物之一，因为其蔗糖含量高，并且它是用于生物燃料生产的有前途的生物质原料。甘蔗基因组测序和分析由于其杂合性和多倍性而成为一项艰巨的任务。长序列读取技术，PacBio单分子实时（SMRT）测序，Illumina TruSeq和牛津纳米孔测序可以解决基因组组装的问题。在应用方面，下一代测序（NGS）技术在单核苷酸多态性（SNP）的发现以及低至高通量基因分型平台的开发中发挥了重要作用。两个主流的高通量基因分型平台是SNP微阵列和测序基因分型（GBS）。本文概述了甘蔗基因组学，基因分型方法，以及这些方法的选择。基于阵列的SNP基因分型功能强大，可提供一致的SNP，并且下游数据分析相对容易。GBS方法可识别整个种质的大规模SNP。应结合使用靶向GBS和基于阵列的基因分型方法，以提高基因组选择和标记辅助育种的准确性。