Identifying orthologous molecular markers that potentially resolve relationships at and below species level has been a major challenge in molecular phylogenetics over the past decade. Non-coding regions of nuclear low- or single-copy markers are a vast and promising source of data providing information for shallow-scale phylogenetics. Taking advantage of public transcriptome data from the One Thousand Plant Project (1KP), we developed a genome-scale mining strategy for recovering potentially orthologous single-copy markers to address low-scale phylogenetics. Our marker design targeted the amplification of intron-rich nuclear single-copy regions from genomic DNA. As a case study we used Hydrangea section Cornidia, one of the most recently diverged lineages within Hydrangeaceae (Cornales), for comparing the performance of three of these nuclear markers to other “fast” evolving plastid markers.
Our data mining and filtering process retrieved 73 putative nuclear single-copy genes which are potentially useful for resolving phylogenetic relationships at a range of divergence depths within Cornales. The three assessed nuclear markers showed considerably more phylogenetic signal for shallow evolutionary depths than conventional plastid markers. Phylogenetic signal in plastid markers increased less markedly towards deeper evolutionary divergences. Potential phylogenetic noise introduced by nuclear markers was lower than their respective phylogenetic signal across all evolutionary depths. In contrast, plastid markers showed higher probabilities for introducing phylogenetic noise than signal at the deepest evolutionary divergences within the tribe Hydrangeeae (Hydrangeaceae).
While nuclear single-copy markers are highly informative for shallow evolutionary depths without introducing phylogenetic noise, plastid markers might be more appropriate for resolving deeper-level divergences such as the backbone relationships of the Hydrangeaceae family and deeper, at which non-coding parts of nuclear markers could potentially introduce noise due to elevated rates of evolution. The herein developed and demonstrated transcriptome based mining strategy has a great potential for the design of novel and highly informative nuclear markers for a range of plant groups and evolutionary scales.