Genome Insights into Autopolyploid Evolution: A Case Study in Senecio doronicum (Asteraceae) from the Southern Alps

Abstract

Polyploidy is a widespread phenomenon across angiosperms, and one of the main drivers of diversification. Whilst it frequently involves hybridisation, autopolyploidy is also an important feature of plant evolution. Minority cytotypes are frequently overlooked due to their lower frequency in populations, but the development of techniques such as flow cytometry, which enable the rapid screening of cytotype diversity across large numbers of individuals, is now providing a more comprehensive understanding of cytotype diversity within species. Senecio doronicum is a relatively common daisy found throughout European mountain grasslands from subalpine to almost nival elevations. We have carried out a population-level cytotype screening of 500 individuals from Tête Grosse (Alpes-de-Haute-Provence, France), confirming the coexistence of tetraploid (28.2%) and octoploid cytotypes (71.2%), but also uncovering a small number of hexaploid individuals (0.6%). The analysis of repetitive elements from short-read genome-skimming data combined with nuclear (ITS) and whole plastid DNA sequences support an autopolyploid origin of the polyploid S. doronicum individuals and provide molecular evidence regarding the sole contribution of tetraploids in the formation of hexaploid individuals. The evolutionary impact and resilience of the new cytotype have yet to be determined, although the coexistence of different cytotypes may indicate nascent speciation.

Discovering the Repeatome of Five Species Belonging to the Asteraceae Family: A Computational Study

“…Regarding Gypsy lineages, Chromovirus elements were the most frequent in the genomes, and their abundance varied from 2.07% in chrysanthemum to 30.42% (i.e., more than 14-fold) in sunflower. The predominance of SIRE and Chromovirus elements has also been observed in other Asteraceae genera, including Hieracium [ 45 ], Senecio [ 46 ], and Stevia [ 51 ] These variations indicate that the high amplification rate was maintained in certain species even after speciation or that other rearrangements, such as duplications of chromosomal fragments, may have occurred, producing such large variations. These results suggest that after species separation, the repetitive components underwent different rates of amplification/loss but also that new LTR-RE sublineages originated (by mutations or by horizontal transfer) in the genomes.…”

“…Such variability can be due to the different genotypes analyzed, as reported in sunflower [ 24 ], or to the usage of diverse methods of repeat discovery and quantification. Clustering analyses, using unassembled reads obtained from low-coverage genome sequencing for estimating the genome proportion of the repeated sequences, is one of the most reliable methods as it has been demonstrated in other study systems [ 44 , 45 , 46 ].…”

LocoGSE, a sequence-based genome size estimator for plants

“…We downloaded 12 read sets from Senecio doronicum specimens with various degrees of ploidy ( Supplementary Table S6 ) and for which the 1C genome size was estimated by flux cytometry ( Fernández et al., 2022 ). We used LocoGSE to estimate 1Cx genome sizes, and we estimated the ploidy level of each sample with the following formula:…”

Compositae-ParaLoss-1272: Complementary sunflower specific probe-set reduces issues with paralogs in complex systems

“…However, the low paralog retention of the 1272 probe set can be very advantageous when dealing with groups known to be complicated by polyploidy since polyploidy is typically associated with higher paralog retention (Lynch and Conery, 2000;Wolfe, 2001;Veitia, 2005). More attention is being placed on polyploidy in nonmodel plant groups (e.g., Lim et al, 2008;Bellinger et al, 2022;Fernández et al, 2022), and the underlying issues associated with it are becoming more well known (see Rothfels, 2021). Being able to address these issues early in the phylogenomic pipeline can improve phylogenetic reconstructions and provide more confidence in data interpretations.…”