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These data are built through a phylogenetic reconstruction of yeasts, and thus allow to estimate duplication dates [ 4].
While it would certainly be desirable to directly estimate duplication rates in this manner, this approach comes with substantial added complexity.
Among other things, reconciliation methods can be used to estimate duplication or transfer rates and to predict sequence orthology (=sequences related by speciation) [ 26, 27].
Note that since only retained duplications are observable, it is hard to estimate duplication and retention rates independently; hence our use of the "duplication/retention rate" terminology.
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We estimated duplication frequencies by aligning all predicted lamprey protein-coding genes from the MAKER5 data set to the human (GRCh37, GCA_000001405.1) and chicken (Gallus_gallus-2.1, GCA_000002315.1) whole-genome assemblies.
We then applied the equation Td = K ¯ s /2* ř to find the estimated duplication time range.
However, this estimated duplication age could be invalid because the regions were likely selected during rice domestication (see below).
To conclude: phylogenetic relationships between CTLD paralogues and estimated duplication time distribution indicate that there was a burst in duplication activity in the Fugu genome 300 400 Myr ago.
However, for some genomic segments, concerted evolution homogenizes homologous sequences through unequal crossing-over and gene conversion, changing the estimated duplication age and gene divergence [ 9, 13- 15].
The high sequence similarity over the coding and non-coding regions of the two sequences indicated that TaEXPB11cs3 is a very recent duplication of TaEXPB11cs2 with an estimated duplication age of 1.59 MYA.
Our results were essentially unchanged when we chose an even looser criterion, such as E = 1 e − 5. We developed an analytical pipeline to estimate the duplication times (ages) of mouse duplicate genes on a large scale, using the split-time between the mouse and zebrafish (430 million years ago, mya) as a calibration.
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