Variability among the Most Rapidly Evolving Plastid Genomic Regions is Lineage-Specific: Implications of Pairwise Genome Comparisons in Pyrus (Rosaceae) and Other Angiosperms for Marker Choice

Abstract

Plastid genomes exhibit different levels of variability in their sequences, depending on the respective kinds of genomic regions. Genes are usually more conserved while noncoding introns and spacers evolve at a faster pace. While a set of about thirty maximum variable noncoding genomic regions has been suggested to provide universally promising phylogenetic markers throughout angiosperms, applications often require several regions to be sequenced for many individuals. Our project aims to illuminate evolutionary relationships and species-limits in the genus Pyrus (Rosaceae)—a typical case with very low genetic distances between taxa. In this study, we have sequenced the plastid genome of Pyrus spinosa and aligned it to the already available P. pyrifolia sequence. The overall p-distance of the two Pyrus genomes was 0.00145. The intergenic spacers between ndhC–trnV, trnR–atpA, ndhF–rpl32, psbM–trnD, and trnQ–rps16 were the most variable regions, also comprising the highest total numbers of substitutions, indels and inversions (potentially informative characters). Our comparative analysis of further plastid genome pairs with similar low p-distances from Oenothera (representing another rosid), Olea (asterids) and Cymbidium (monocots) showed in each case a different ranking of genomic regions in terms of variability and potentially informative characters. Only two intergenic spacers (ndhF–rpl32 and trnK–rps16) were consistently found among the 30 top-ranked regions. We have mapped the occurrence of substitutions and microstructural mutations in the four genome pairs. High AT content in specific sequence elements seems to foster frequent mutations. We conclude that the variability among the fastest evolving plastid genomic regions is lineage-specific and thus cannot be precisely predicted across angiosperms. The often lineage-specific occurrence of stem-loop elements in the sequences of introns and spacers also governs lineage-specific mutations. Sequencing whole plastid genomes to find markers for evolutionary analyses is therefore particularly useful when overall genetic distances are low.

Dynamics of chloroplast genomes in green plants

“…Furthermore, atpE, clpP, rps2, rps3, rps7, rps8, rps11, rpl2, rpl12, rpl20, and cemA genes were evolutionary constraint in Poaceae, especially rps7 and rpl2 genes are almost identical in Poaceae, while psaA, psbC, psbD, petB, and rbcL genes are fast evolved in Poaceae, suggested that chloroplast genomes has been suggested to be lineage specific in some regions, which is consistent with previous studies [44][45][46].…”

Lineage‐specific evolutionary rate in plants: Contributions of a screening for Cereus (Cactaceae)

“…2). These results agree with the high heterogeneity in molecular evolutionary rates in plants (Korotkova et al, 2014; Shaw et al, 2014); however, they also suggest that lineage-specific variation in cpDNA seems to be more accentuated than in nuclear DNA. Furthermore, these data indicate that rate heterogeneity in cpDNA evolution appears to increase in early stages of population differentiation (Duchene and Bromham, 2013; Bromham et al, 2015).…”

“…Inversions are difficult to analyze because they are not well recognized in the alignment, especially in small sample sizes (Borsch and Quandt, 2009). Recent studies have discovered that this mutation is usually common in noncoding regions (Borsch and Quandt, 2009), even at population level or in lineage-specific analyses (Quandt et al, 2003; Borsch and Quandt, 2009; Korotkova et al, 2014). Inversions are usually associated with inverted repeat sequences, yielding a hairpin secondary structure such as predicted in our sampling ().…”

“…Despite some advantages (i.e., uniparental inheritance, genome stability, and rare recombination; Clegg et al, 1994; Ravi et al, 2007; Pleines et al, 2008; Borsch and Quandt, 2009), there are also limitations in using cpDNA at the shallowest taxonomic level (i.e., low genetic variability and evolutionary rate heterogeneity between lineages; Korotkova et al, 2014; Shaw et al, 2014). Nuclear regions are usually combined with cpDNA data, considering that these regions usually have a higher evolutionary rate in these organisms (Wolfe et al, 1987).…”

“…As screening for variable markers has become the first mandatory step to perform phylogeographic studies in targeted species due to the high evolutionary rate heterogeneity between plant lineages (Shaw et al, 2014; Korotkova et al, 2014), our aim was to evaluate whether regions that are likely variable among closely allied species (i.e., those described by Shaw et al, 2007, 2014) could similarly be predicted as variable in intraspecific studies. We focused on three biological hierarchical levels to screen for potentially informative markers for Cereus : distinct clades in the phylogeny, different species of the same clade, and allopatric populations of the same species.…”