Genetic Assessment of a Mini‐Core Subset Developed from the USDA Rice Genebank

Abstract

Development of core collections is an effective tool to extensively characterize large germplasm collections, and the use of a mini-core subsampling strategy further increases the effectiveness of genetic diversity analysis at detailed phenotype and molecular levels. We report the formation of a mini-core subset containing 217 entries derived from 1794 core entries representing the genetic diversity found in more than 18,000 accessions of the USDA-ARS rice (Oryza sativa L.) germplasm collection. The mini-core was developed with PowerCore software on the basis of 26 phenotypic traits and 70 molecular markers. The 217 entries in the mini-core had a similar distribution over 15 geographical regions, with 1794 entries in the original core collection. The resultant mini-core had 6.3% of mean difference (MD%), 16.5% of variance difference (VD%), 102.7% of variable rate (VR%), and 97.5% of coincidence rate (CR%) with the core collection, which brought about full coverage of 26 traits. All 962 alleles identifi ed by the 70 markers in the core collection were captured in the mini-core, which maximized allelic richness up to 100% and resulted in an average genetic diversity (Nei index) of 0.76, ranging from 0.37 to 0.97 among the markers. In conclusion, the mini-core presented in this study is a highly suitable and representative subset of the USDA rice core collection as well as the entire USDA-ARS rice germplasm holdings.

Population structure analysis and association mapping of blast resistance in indica rice (Oryza sativa L.) landraces

“…This is consistent with the 3.9 alleles per locus previously identified in 416 rice accessions, most of which were collected in China, with 100 SSR markers (Jin et al, 2010), and 5 alleles per locus, which were detected in 170 rice accessions from a putative mini-core collection of Chinese germplasms with 132 SSR and InDel markers (Wen et al, 2009). However, the value obtained in the present study was lower than the 7.7 alleles per locus detected in 247 rice accessions from a mini-core collection of Japanese rice landraces using 32 SSR markers, the 11.9 alleles per locus detected in 236 rice accessions from 23 countries with 60 SSR markers, and the 13.47 alleles per locus identified by 70 SSR markers in 217 rice accessions selected from the United States Department of Agriculture (USDA) Rice Genebank (Agrama et al, 2009). To reduce the impact of population structure on phenotypic variation, only indica landraces were selected in the present study, which may explain why the number of alleles per locus was lower than that found in other studies.…”

Development of a cassava core collection based on single nucleotide polymorphism markers

“…Therefore, regardless of the collection size, this study demonstrated a high allelic representation (100%) for all SNP markers relative to the entire cassava collection. Similar results for the maintenance of all alleles in a germplasm were also reported by Agrama et al (2009) for a mini rice core collection composed of 12% of an entire collection using 70 microsatellite markers.…”

“…Therefore, given the lowest intensity of sampling among all core collections (4.7%) and its genetic diversity between accessions, the PoHEU collection (established by PowerCore) may be the appropriate choice for the practical applications involving cassava genetic conservation. Other studies showed that the heuristic algorithm is capable of effectively reducing the number of accessions in germplasm collections while maintaining an almost complete proportion of the diversity in phenotypic and molecular characteristics (Kim et al, 2007;Agrama et al, 2009). The heuristic algorithm enabled the formation of a rice core collection containing only 1% of the entire germplasm in comparison with approximately 10% when proportional core collection and random core collection methods were applied (Chung et al, 2009).…”

Development of a Core Collection of Strawberry Cultivars Based on SSR and CAPS Marker Polymorphisms

“…Totally, 43 and 123 dominant alleles, which were generated by 25 CAPS and 45 SSR markers, respectively, were used to extract the core collection and further characterization analysis. Extraction of the strawberry core collection Many previous studies (Agrama et al, 2009;Belaj et al, 2012;Kaga et al, 2012;Oliveira et al, 2014) adopted PowerCore (Kim et al, 2007) as the software for construction of a core collection or core set because PowerCore has a function that can maintain 100% diversity of the base population. Therefore, PowerCore was used to extract the strawberry core collection from the 119 strawberry cultivars in this study.…”

“…They determined that the heuristic search approach of PowerCore was superior to a random search. Using PowerCore, core collections for ramie (Luan et al, 2014), rice (Agrama et al, 2009), soybean (Kaga et al, 2012), and cassava (Oliveira et al, 2014) have recently been developed. However, there are no reports regarding a strawberry core collection based on DNA marker polymorphisms.…”