PeerJGenomicsPeer-reviewed journal article
Genomic comparison of non-photosynthetic plants from the family Balanophoraceae with their photosynthetic relatives.
Mikhail I. SchelkunoviD, MAXIM S. NURALIEViD, Maria D. LogachevaiD
Abstract
The plant family Balanophoraceae consists entirely of species that have lost the ability to photosynthesize. Instead, they obtain nutrients by parasitizing other plants. Recent studies have shown that plastid genomes of Balanophoraceae have a number of interesting features, one of the most prominent of those being a tremendous AT content close to 90%. Also, the nucleotide substitution rate in the plastid genomes of Balanophoraceae is greater by an order of magnitude compared to photosynthetic relatives, without signs of relaxed selection. All these features have no definite explanations. Given these unusual features, we supposed that it would be interesting to gain insight into the characteristics of nuclear genomes of Balanophoraceae. To do this, in the present study we analysed transcriptomes of two species from Balanophoraceae, namely Rhopalocnemis phalloides and Balanophora fungosa, and compared them with transcriptomes of their close photosynthetic relatives Daenikera sp., Dendropemon caribaeus, Malania oleifera. The analysis showed that the AT content of nuclear genes of Balanophoraceae does not markedly differ from that of photosynthetic relatives. The nucleotide substitution rate in genes of Balanophoraceae is for an unknown reason several times larger than in genes of photosynthetic Santalales, though the negative selection in Balanophoraceae is likely stronger. We observed an extensive loss of photosynthesis-related genes in Balanophoraceae. Also, for Balanophoraceae we did not see transcripts of several genes whose products participate in plastid genome repair. This implies their loss or very low expression, which may explain the increased nucleotide substitution rate and AT content of the plastid genomes.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 16
- FWCI
- 1.71
- Field percentile
- top 16%
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