Abstract

Polypoid species play significant roles in agriculture and food production. Many crop species are polyploid, such as potato, wheat, strawberry, and sugarcane. Genotyping has been a daunting task for genetic studies of polyploid crops, which lags far behind the diploid crop species. Single nucleotide polymorphism (SNP) array is considered to be one of, high-throughput, relatively cost-efficient and automated genotyping approaches. However, there are significant challenges for SNP identification in complex, polyploid genomes, which has seriously slowed SNP discovery and array development in polyploid species. Ploidy is a significant factor impacting SNP qualities and validation rates of SNP markers in SNP arrays, which has been proven to be a very important tool for genetic studies and molecular breeding. In this review, we (1) discussed the pros and cons of SNP array in general for high throughput genotyping, (2) presented the challenges of and solutions to SNP calling in polyploid species, (3) summarized the SNP selection criteria and considerations of SNP array design for polyploid species, (4) illustrated SNP array applications in several different polyploid crop species, then (5) discussed challenges, available software, and their accuracy comparisons for genotype calling based on SNP array data in polyploids, and finally (6) provided a series of SNP array design and genotype calling recommendations. This review presents a complete overview of SNP array development and applications in polypoid crops, which will benefit the research in molecular breeding and genetics of crops with complex genomes.

Highlights

  • Polyploid species contain more than two sets of chromosomes (Comai, 2005)

  • The current review focuses on following aspects in both autopolyploid and allopolyploid crops: (1) comparing Single nucleotide polymorphism (SNP) array technology with other methods, especially next generation sequencing (NGS)-based technologies for genotyping polyploids; (2) explaining SNP selection criteria for array design for polyploids; (3) summarizing currently available arrays and their applications in polyploid crops; (4) discussing available SNP array genotype calling software; and (5) providing suggestions and future perspectives of SNP array application in polyploid crops

  • Challenges exist for SNP discovery in polyploid species, progress has been made with the improved and increased number of available analysis tools (Clevenger et al, 2015; Song et al, 2016)

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Summary

INTRODUCTION

Polyploid species contain more than two sets of chromosomes (Comai, 2005). It is estimated that polyploid species account for up to 80% of living plants (Otto, 2007; Rieseberg and Willis, 2007). SNP Array for Polyploid Species hybridization and subsequent chromosome doubling, which produces allopolyploid species, such as bread wheat (Chen and Ni, 2006; Marcussen et al, 2014; Borrill et al, 2015). The combination of two or more sets of chromosomes from different species in allopolyploids through hybridization can lead to heterosis (Chen, 2013) This may be explained by the allelic interactions or epigenetic modifications of some key genes. SNP identification in polyploids (Kaur et al, 2012; Clevenger et al, 2015) and SNP array development mainly in diploid species (Rasheed et al, 2017) have been extensively reviewed. The current review focuses on following aspects in both autopolyploid and allopolyploid crops: (1) comparing SNP array technology with other methods, especially NGS-based technologies for genotyping polyploids; (2) explaining SNP selection criteria for array design for polyploids; (3) summarizing currently available arrays and their applications in polyploid crops; (4) discussing available SNP array genotype calling software; and (5) providing suggestions and future perspectives of SNP array application in polyploid crops

SNP IDENTIFICATION IN POLYPLOIDS
FEATURES OF SNP ARRAY TECHNOLOGY
SNP source
Genetic map generation
SNP ARRAY DEVELOPMENT AND APPLICATIONS IN POLYPLOID SPECIES
Octoploid and Dodecaploid
SNP ARRAY GENOTYPE CALLING AND DATA ANALYSIS PIPELINES
General Genotype Calling Based on Affymetrix Axiom and Illumina Infinium
More technical and computational details are available from
CONCLUSION AND SUGGESTIONS
Full Text
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