High resolution melting curve (HRM) is a recent advance for the detection of SNPs. The technique measures temperature induced strand separation of short PCR amplicons, and is able to detect variation as small as one base difference between samples. It has been applied to the analysis and scan of mutations in the genes causing human diseases. In plant species, the use of this approach is limited. We applied HRM analysis to almond SNP discovery and genotyping based on the predicted SNP information derived from the almond and peach EST database. Putative SNPs were screened from almond and peach EST contigs by HRM analysis against 25 almond cultivars. All 4 classes of SNPs, INDELs and microsatellites were discriminated, and the HRM profiles of 17 amplicons were established. The PCR amplicons containing single, double and multiple SNPs produced distinctive HRM profiles. Additionally, different genotypes of INDEL and microsatellite variations were also characterised by HRM analysis. By sequencing the PCR products, 100 SNPs were validated/revealed in the HRM amplicons and their flanking regions. The results showed that the average frequency of SNPs was 1:114 bp in the genic regions, and transition to transversion ratio was 1.16:1. Rare allele frequencies of the SNPs varied from 0.02 to 0.5, and the polymorphic information contents of the SNPs were from 0.04 to 0.53 at an average of 0.31. HRM has been demonstrated to be a fast, low cost, and efficient approach for SNP discovery and genotyping, in particular, for species without much genomic information such as almond.

Summary We sequenced the genome of the highly heterozygous almond Prunus dulcis cv. Texas combining short‐ and long‐read sequencing. We obtained a genome assembly totaling 227.6 Mb of the estimated almond genome size of 238 Mb, of which 91% is anchored to eight pseudomolecules corresponding to its haploid chromosome complement, and annotated 27 969 protein‐coding genes and 6747 non‐coding transcripts. By phylogenomic comparison with the genomes of 16 additional close and distant species we estimated that almond and peach (Prunus persica) diverged around 5.88 million years ago. These two genomes are highly syntenic and show a high degree of sequence conservation (20 nucleotide substitutions per kb). However, they also exhibit a high number of presence/absence variants, many attributable to the movement of transposable elements (TEs). Transposable elements have generated an important number of presence/absence variants between almond and peach, and we show that the recent history of TE movement seems markedly different between them. Transposable elements may also be at the origin of important phenotypic differences between both species, and in particular for the sweet kernel phenotype, a key agronomic and domestication character for almond. Here we show that in sweet almond cultivars, highly methylated TE insertions surround a gene involved in the biosynthesis of amygdalin, whose reduced expression has been correlated with the sweet almond phenotype. Altogether, our results suggest a key role of TEs in the recent history and diversification of almond and its close relative peach.

Identification of the incompatibility genotypes of almond cultivars is important in breeding programmes for designing crosses and for selecting progeny. This paper describes a novel molecular technique for the identification of S‐alleles in almond based on the use of PCR primers designed from the sequences of the introns without the need for restriction enzyme digestion. Nine specific pairs of primers have been designed for the S1, S2, S5, S7, S8, S9, S10 (putative), S23 and Sf alleles, and these confirmed the S‐allele specificities for 22 of the 23 accessions for which published information is available. This technique provides a precise method for identifying S‐alleles from the genomic DNAs of almond cultivars, and will be useful for confirming the segregation of alleles in breeding progeny.

DNA-based molecular markers have been extensively utilized for a variety of studies in both plant and animal systems. One of the major uses of these markers is the construction of genome-wide molecular maps and the genetic analysis of simple and complex traits. However, these studies are generally based on linkage analysis in mapping populations, thus placing serious limitations in using molecular markers for genetic analysis in a variety of plant populations. Therefore, alternative approach has been suggested, linkage disequilibrium-based association analysis which detects and locates quantitative trait loci (QTL) by the strength of the correlation between a trait and a marker. Although association analysis has already been used for studies on genetics of complex traits in humans, its use in plants has newly started. In the present review, we describe what is known about variation in linkage disequilibrium (LD) and summarize published results on association studies in crop plant species. We give a list of different factors affecting LD, and discuss the current issues of LD research in plants. Later, we also describe the various uses of LD in crop plants research and summarize the present status of LD researches in different plant genomes. Finally, future key issues about the application of these studies on the localization of genes in these crop plants have been also discussed.