Application of High Resolution Melt analysis (HRM) for screening haplotype variation in a non-model plant genus: Cyclopia (Honeybush)

Abstract

Aim: This study has three broad aims: to (a) develop genus-specific primers for High Resolution Melt analysis (HRM) of members of Cyclopia Vent., (b) test the haplotype discrimination of HRM compared to Sanger sequencing, and (c) provide an example of using HRM to detect novel haplotype variation in wild C. subternata Vogel. populations.

Location: The Cape Floristic Region (CFR), located along the southern Cape of South Africa.

Methods: Polymorphic loci were detected through a screening process of sequencing 12 non-coding chloroplast DNA segments across 14 Cyclopia species. Twelve genus-specific primer combinations were designed around variable cpDNA loci, four of which failed to amplify under PCR; the eight remaining were applied to test the specificity, sensitivity and accuracy of HRM. The three top performing HRM Primer combinations were then applied to detect novel haplotypes in wild C. subternata populations, and phylogeographic patterns of C. subternata were explored.

Results: We present a framework for applying HRM to non-model systems. HRM accuracy varied across the PCR products screened using the genus-specific primers developed, ranging between 56 and 100%. The nucleotide variation failing to produce distinct melt curves is discussed. The top three performing regions, having 100% specificity (i.e. different haplotypes were never grouped into the same cluster, no false negatives), were able to detect novel haplotypes in wild C. subternata populations with high accuracy (96%). Sensitivity below 100% (i.e. a single haplotype being clustered into multiple unique groups during HRM curve analysis, false positives) was resolved through sequence confirmation of each cluster resulting in a final accuracy of 100%. Phylogeographic analyses revealed that wild C. subternata populations tend to exhibit phylogeographic structuring across mountain ranges (accounting for 73.8% of genetic variation base on an AMOVA), and genetic differentiation between populations increases with distance (p < 0.05 for IBD analyses).

Conclusions: After screening for regions with high HRM clustering specificity-akin to the screening process associated with most PCR based markers-the technology was found to be a high throughput tool for detecting genetic variation in non-model plants.

Keywords: Cape Floristic Region (CFR); Cyclopia; Genetics; Haplotype screening; High Resolution Melt analysis (HRM); Honeybush; Non-model organisims; Phylogeography.

Figure 1. Sample distribution map.

Study domain superimposed with the distribution of the CFRs fynbos biome, to which Cyclopia is endemic. Inset indicates the position of the study domain in relation to South Africa and the African continent. Distribution of samples included in non-coding cpDNA haplotype screening for HRM primer development are displayed (filled circles) in conjunction with the locations of the C. subternata populations included in the phylogeographic analysis (open circles). Closed circles are numbered based on species identity: 1 = C. galioides, 2 = C. genistoides, 3 = C. buxifolia, 4 = C. maculata, 5 = C. sessilifolia, 6 = C. burtonii, 7 = C. aurescens, 8 = C. bolusii, 9 = C. subternata, 10 = C. plicata, 11 = C. alpina, 12 = C. intermedia, 13 = C. longifolia, 14 = C. pubescens.

Figure 2. High Resolution Melt curve examples.

Melt curves and their difference curves for the PCR products amplified by three of the genus specific primers developed. Curves are ordered in decreasing HRM clustering accuracy and the bottom curves (E, F) were generated using the primer pair MLT T1-MLT T2 (TrnQ-5’rps16 intergenic spacer) that was excluded from HRM analysis due to poor amplification resulting in inconsistent melt curve production, the details of this primer pair, in addition to all primer pairs that were excluded from HRM haplotype discrimination analysis due to poor PCR amplification, are provided in Table S1. HRM curves (A, C, E), the normalized change in florescence associated with PCR product dissociation when heated. Melt domain identification and melt curve normalization was automated by the HRM software in this study, this process may be required to be performed manually on other platforms. A reference melt curve is selected and used as a baseline to plot melt curve differences across the melt domain, therefore difference curves (B, D, E) have different X axes. HRM clusters are automatically generated and colorised by the HRM software used. Melt curves were generated from the PCR products generated using the primer pairs, (A, B) MLT S1–MLT S2 (atpI-atpH intergenic spacer), (C, D) MLT C3–MLT C4 (trnG-trnG2G intergenic spacer), and (E,F) MLT T1–MLT T2 (trnQ-5’rps16 intergenic spacer).

Figure 3. Framework used to developed, test, and apply HRM to the genus Cyclopia, a group of non-model organisms.

This involves identifying polymorphic loci (A), designing taxon specific primers (B), testing PCR amplification success of the taxon specific primers (C), testing the HRM clustering accuracy of PCR products of known nucleotide sequence motif (D), and then screening novel nucleotide variation across loci that have proven to result in high HRM accuracy (E).

Figure 4. Summary of the (A) specificity, (B) sensitivity and (C) accuracy for the regions used to test haplotype discrimination by HRM.

Figure 5. Haplotype distribution and number of accessions for the eight C. subternata populations screened via HRM.

Black circles mark C. intermedia samples collected from the Swartberg mountains and included as out-group taxa. Inset is the genealogical relationship between haplotypes ascertained using the Statistical Parsimony algorithm. Haplotype frequency is indicated as a proportion of the circles representing each population, with total number of accessions provided in parenthesis. The color-coding in the map corresponds to the SP network. Population naming follows the description in Table 4. GAR, Garcia’s Pass located in the Langeberg; OUT, Outeniqua Pass and BP, Bergplaas MTO located in the western Outeniqua mountains; KNYS, Diepwalle Knysna and PLETT, Plettenberg Bay in the eastern Outeniqua mountains, and the BKB, Bloukrans Bridge; LK, Langkloof, and KP, Kareedouw Pass in the Tsitsikamma mountains.