Author
YOU, QIAN - University Of Florida | |
YANG, XIPING - University Of Florida | |
SONG, JIAN - University Of Florida | |
Islam, Md | |
Comstock, Jack | |
XU, LIPING - Fujian Agricultural & Forestry University | |
Sood, Sushma |
Submitted to: International Conference on Sugar and Integrated Industries
Publication Type: Abstract Only Publication Acceptance Date: 2/9/2018 Publication Date: 3/6/2018 Citation: You, Q., Yang, X., Song, J., Islam, M.S., Comstock, J.C., Xu, L., Sood, S.G. 2018. Discovery of 100K SNP array and its utilization in sugarcane. International Conference on Sugar and Integrated Industries. ABSTRACT ONLY. Interpretive Summary: N/A Technical Abstract: Next generation sequencing (NGS) enable us to identify thousands of single nucleotide polymorphisms (SNPs) marker for genotyping and fingerprinting. However, the process requires very precise bioinformatics analysis and filtering process. High throughput SNP array with predefined genomic location could overcome the problem. A 100K SNP array has been developed for facilitating high throughput and easy genotyping service for the sugarcane researchers. We selected the SNPs mainly based on two classes. The first class included 68,682 single dose (SD) SNPs based on genotyping of 37 sugarcane hybrids selected from the world collection of sugarcane and related grasses (WCSRG) through target enrichment sequencing. The second class was comprised of 31,415 SD SNPs from a small panel of 12 accessions selected from WCSRG, which had proven to be low dosage SNPs (less than 3 copies) in 37 hybrids. In total, 100,097 SNPs (121,806 probe sets) have been implemented on the array with one SNP per 6, 404 bases based on sorghum genome. To evaluate the 100K sugarcane SNP array, a bi-parental population having 314 F1 individuals and a diversity panel of 13 sugarcane accessions were genotyped with the newly developed array using Affymetrix Axiom platform. According to the SNP genotyping calling methods of Axiom Best Practices Genotyping Work-flow, SNPs were sorted into six quality classes based on the clustering performance. As a result, a total of 62,761 polymorphic SNPs were detected with a polymorphic rate of 62.7%, of which 19,325 SNPs from three quality classes with clear two or three clusters (poly high resolution no minor homozygote, and call rate below threshold ) can be utilized for further analysis. This large amount of SNP markers allowed us to construct a high density genetic map for sugarcane, which will be a critical tool for further gene mapping. This SNP array will leverage high throughput genotyping and molecular breeding in sugarcane with minimal effort. |