Peanut variety identification is essential for protecting the intellectual property rights of researchers, ensuring quality management for producers, and safeguarding the interests of seed production stakeholders. In this research, we developed a molecular marker set for peanut variety identification using single nucleotide polymorphism (SNP) markers. We used genotyping data and selection procedures, including decision tree and optimal combination selection, to identify a minimal set of informative SNP sites. These SNPs were then converted into Kompetitive allele-specific PCR (KASP) markers. We selected a subset of 14 informative SNPs from a pool of 22 candidate markers, representing the minimum number of combinations required to distinguish cultivars. SNPs obtained from the microarrays were converted to KASP markers and then evaluated across 51 peanut varieties. The developed marker set, which consists of a minimal number of markers, is expected to be a rapid and cost-effective tool for peanut variety identification.
Peanut (
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Salinity stress is one of the important abiotic stresses in crops. In this study, ten different concentrations of NaCl solutions were tested to determine the optimal level of NaCl concentration for salinity tolerance test at the germination stage in peanut, and 0.6% NaC1 was suitable for the test. A total of 249 peanut accessions were tested with 0.6% NaC1 and radical root lengths of the accessions were measured. The results showed that there were significant genetic variations on the tolerance to salinity stress among the tested accessions. Through a Genome-Wide Association Study (GWAS) using the Axiom_Arachis array with 58K SNPs, three putative SNPs with significant relation to radicle root length were identified on chromosomes Aradu.A03, Araip.B01, and Araip.B05.
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The
objective
of this study was to develop high-throughput SNP or SNP-based markers by re-sequencing of two peanut cultivars, ‘K-Ol’ and ‘Pungan’. The whole genome re-sequencing for the two cultivars was performed to produce sequences of 35.3 × 109 bp with 350 × 106 reads and 32.0 × 109 bp with 318 × 106 reads, respectively. As compared with the peanut reference genome, the distribution of homozygous and heterozygous SNPs on each chromosome showed very similar patterns between ‘K-Ol’ and ‘Pungan’, and most of them were in intergenic-region regardless of the peanut cultivars and reference genome type. The SNPs identified between the two peanut cultivars were evenly distributed across chromosomes of peanut diploid A and B reference genomes. It indicated that these SNPs could be available to construct a genetic map using the segregating population derived from a cross between ‘K-Ol’ and ‘Pungan’. Total 61 CAPS marker were developed and tested for their availability. Of the CAPS markers, 60 CAPS markers produced normal PCR products and 18 out of them presented polymorphism among 6 peanut varieties. Results of the present study could provide useful genetic resources to facilitate marker-assisted selection for breeding programs as well as germplasm screening for peanut.
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Leafspot is one of the major diseases of peanut (
objective
of this study was to identify and map quantitative trait loci (QTLs) for resistance to leafspot disease. An F2:6 recombinant inbred line (RIL) population, derived from a released cultivar Tamrun OL07 and a highly tolerant breeding line Tx964117, were used as a mapping population. A total of 90 RILs were planted for disease phenotyping in Yoakum, Texas in 2010 and 2012. A genetic map spanning the 20 linkage groups was developed using 1,211 SNP markers based on double digest restriction-site associated DNA sequencing (ddRAD-seq). A total of six quantitative trait loci (QTLs) were identified, with LOD score values of 3.2–5.0 and phenotypic variance explained ranging from 11%–24%. Major QTLs identified in this study may be used as potential targets for peanut improvement to leafspot disease through molecular breeding.
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