scholarly journals Repetitive DNA Restructuring Across Multiple Nicotiana Allopolyploidisation Events Shows a Lack of Strong Cytoplasmic Bias in Influencing Repeat Turnover

Genes ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 216
Author(s):  
Steven Dodsworth ◽  
Maïté S. Guignard ◽  
Oscar A. Pérez-Escobar ◽  
Monika Struebig ◽  
Mark W. Chase ◽  
...  

Allopolyploidy is acknowledged as an important force in plant evolution. Frequent allopolyploidy in Nicotiana across different timescales permits the evaluation of genome restructuring and repeat dynamics through time. Here we use a clustering approach on high-throughput sequence reads to identify the main classes of repetitive elements following three allotetraploid events, and how these are inherited from the closest extant relatives of the maternal and paternal subgenome donors. In all three cases, there was a lack of clear maternal, cytoplasmic bias in repeat evolution, i.e., lack of a predicted bias towards maternal subgenome-derived repeats, with roughly equal contributions from both parental subgenomes. Different overall repeat dynamics were found across timescales of <0.5 (N. rustica L.), 4 (N. repanda Willd.) and 6 (N. benthamiana Domin) Ma, with nearly additive, genome upsizing, and genome downsizing, respectively. Lower copy repeats were inherited in similar abundance to the parental subgenomes, whereas higher copy repeats contributed the most to genome size change in N. repanda and N. benthamiana. Genome downsizing post-polyploidisation may be a general long-term trend across angiosperms, but at more recent timescales there is species-specific variance as found in Nicotiana.

Author(s):  
Albert E. Beaton ◽  
James R. Chromy
Keyword(s):  

2021 ◽  
Vol 38 (10) ◽  
pp. 1791-1802
Author(s):  
Peiyan Chen ◽  
Hui Yu ◽  
Kevin K. W. Cheung ◽  
Jiajie Xin ◽  
Yi Lu

AbstractA dataset entitled “A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland” (PRITC dataset V1.0) is described in this paper, as are some basic statistical analyses. Estimating the severity of the impacts of tropical cyclones (TCs) that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study, including an index combining TC-induced precipitation and wind (IPWT) and further information, such as the corresponding category level (CAT_IPWT), an index of TC-induced wind (IWT), and an index of TC-induced precipitation (IPT). The current version of the dataset includes TCs that made landfall from 1949–2018; the dataset will be extended each year. Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased, as embodied by the annual mean IPWT values, and increases in TCinduced precipitation are the main contributor to this increase. TC Winnie (1997) and TC Bilis (2006) were the two TCs with the highest IPWT and IPT values, respectively. The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.


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