Peanut SNP Discovery

DNA marker resources have been expanded for molecular breeding applications in groundnut (Arachis hypogaea L.). The objective to enhance the infrastructure for translational genomics and molecular breeding research in groundnut has been achieved by massively parallel sequencing of 17 tetraploid genotypes which, by comparison with the reference transcriptome of ‘Tifrunner’ (NCBI TSA project PRJNA49471), has provided a database for SNP discovery. Over 350 Mb of sequence from root, leaf, and pod tissues of 17 genotypes was assembled along with Sanger and Roche 454 sequences from the reference ‘Tifrunner’ transcriptome.
Download the fasta file (.zip): [download id=”1″].

8486 single nucleotide polymorphisms (SNPs) were identified when the data were subjected to moderately stringent filtering to account for a SNP in at least two sequences from a genotype, allele frequency among genotypes (min 0.01 minor), sequence errors at ends of reads (ignore 10 bp ends), and proximity to neighboring SNPs or indels (no other SNP or indel within 20 bp).
Download SNP data:  [download id=”2″]

An Illumina GoldenGate 1536-SNP array was designed from these 8486 candidate SNPs by prioritizing based on Illumina design score and distance from predicted intron-exon boundaries. The GoldenGate assay was used for genotyping of 80 tetraploid inbred lines, 3 amphidiploids, and several diploid accessions of Arachis. Loci could be detected for >95% of the SNP assays indicating successful design using this platform. However, SNPs between tetraploid genotypes were rare unless the tetraploid was synthetic. Nevertheless, the validated SNPs can be used to construct a smaller chip or transferred to an alternate platform for lower throughput assays. Sequence data from non-coding regions of the groundnut genome will be needed to increase the probability of finding nucleotide differences between cultivated genotypes in order to enhance the density of markers that can be used for breeding.

This project was funded by the Generation Challenge Program (Project No. G4008.06) and USDA-NIFA award no. 2006-35604-17242 (PI – Steven J. Knapp, co-PI – Peggy Ozias-Akins). Participants – John E. Bowers, Yufang Guo, Joann A. Conner, Jim Leebens-Mack, Michael McKain, Corley Holbrook, Rajeev Varshney)

 

 

 

Peggy Ozias-Akins | The University of Georgia