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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Cereal Crops Research » Research » Publications at this Location » Publication #296565

Title: Genotype-by-sequencing of the plant-pathogenic fungi Pyrenophora teres and Sphaerulina musiva utilizing Ion Torrent sequence technology

item LEBOLDUS, JAROD - North Dakota State University
item KINZER, KASIA - North Dakota State University
item YA, ZHU - North Dakota State University
item YAN, CHANGHUI - North Dakota State University
item Friesen, Timothy
item BRUEGGEMAN, ROBERT - North Dakota State University
item RICHARDS, J - North Dakota State University

Submitted to: Molecular Plant Pathology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/15/2014
Publication Date: 7/6/2015
Publication URL:
Citation: Leboldus, J.M., Kinzer, K., Richards, J., Ya, Z., Yan, C., Friesen, T.L., Brueggeman, R. 2015. Genotype-by-sequencing of the plant-pathogenic fungi Pyrenophora teres and Sphaerulina musiva utilizing Ion Torrent sequence technology. Molecular Plant Pathology. 16(6):623-632.

Interpretive Summary: The mapping and identification of genes in fungal pathogens has long been a problem due to the lack of available resources and the high cost of developing resources for each pathogen. Here we present a tested method of deep coverage genotyping, called genotype by sequencing (GBS) that can saturate the whole genome of a pathogen with molecular markers at a reasonable cost without the necessity of previously developed resources. A map of the genome is then developed and can be used in characterizing the genetics of pathogen virulence. The level of saturation possible with this new GBS approach allows a much more efficient path to cloning genes involved in the destructive diseases of plants. Cloning of the genes and characterization of the interactions involving these genes yields a deeper understanding of these important host pathogen interactions, allowing both commercial and public breeders to more intelligently select for durable resistance.

Technical Abstract: The characterization of genes determining compatibility or incompatibility between plant pathogenic fungi and their hosts is important for the management of crop disease. The major focus of these interactions has typically been the identification and characterization of host genes, but it is equally important to characterize the genetics and diversity of the pathogen effectors to intelligently deploy durable resistance. Research to identify virulence factors or effectors requires the genetic characterization of pathogen populations, however this has been limited by availability of adequate resources including both genome knowledge and funding. To overcome these bottlenecks, a non-resource prohibitive method of deep coverage genotyping of pathogen populations is required. Here we describe the use of a two-enzyme genotype-by-sequencing (GBS) method adapted for Ion Torrent sequencing technology. Utilizing this method, 2,373 and 5,960 unique loci, ”sequence tags”, containing 9,992 and 17,193 SNPs were identified and characterized from natural populations of Septoria musiva and Pyrenophora teres f. maculata, respectively. S. musiva is a necrotrophic fungal pathogen that causes leaf spot and stem canker of poplar hybrids and P. teres f. maculata is a necrotrophic fungal pathogen that causes spot form net blotch of barley. Based on the estimated sizes of the S. musiva and P. teres f. maculata genomes, ~30 and 34 Mb, respectively, this GBS analysis placed a SNP marker on average approximately every 12.6 to 5.7 kb in the respective fungal genomes. This high-density of markers is adequate for association mapping in natural populations and positional cloning efforts in bi-parental fungal populations. Blast searches of the sequence tags generated from the S. musiva genome revealed that ~95% represent predicted genes, providing ~23% coverage of the total predicted genes present in the genome. This genotyping can be done at a relatively low cost per fungal isolate or progeny making it an option for researchers with limited resources and/or working on pathogens with no or limited genome information available.