Combining systems modeling with evolutionary algorithm makes it possible to identify optimal engineering options for future global climate change scenarios and simultaneously consider environmental constraints, such as with constant or even decreasing nitrogen fertilizer application in the field.
The Tamura 3-parameter model (T92) with evolutionary rates among sites modeled by using a discrete Gamma distribution (+G) with 5 rate categories had the highest fit (lowest BIC value) among the 24 different nucleotide substitution models tested by maximum likelihood.
As part of the Phenoscape Project (http://www.phenoscape.org), which aims to integrate model organism with evolutionary phenotype data using ontologies, we mounted a large-scale initiative to curate a significant data set of evolutionarily-varying phenotypes from the phylogenetic systematic literature.
The sequences were simulated from the Jukes-Cantor model, with variable evolutionary rates across sites drawn from the exponential distribution.
Maximum-likelihood unrooted phylogenetic trees were constructed using the MOLPHY program (Jones-Taylor-Thornton model with uniform evolutionary rate across sites), and the same program was used to compute the RELL bootstrap probabilities from 10,000 replications [ 81, 82].
On the other hand, analyses with the birth-death prior supported a model with five evolutionary regimes (i.e. four rate shifts, Additional file 6: Figure S5) located at (or near) the crown of the four most species-rich genera (according to BF values > 10, and BF = 29.3 over the null model).
Analyses with the Yule prior supported a model with three evolutionary regimes (i.e. two rate shifts, Additional file 5: Figure S4) located at the crown of the genera Cycas and Encephalartos (according to BF values > 10, and BF = 154.5 over the null model).
More importantly, with the advantages of genome sequencing technology, large batches of genome information of non-model organisms with evolutionary and/or ecological importance will be available which may provide new gene resources with potential impact during diverse evolutionary processes.
The majority of the missense variants were likely to be tolerated and were located in regions of low complexity (according to protein modeling) with weak evolutionary conservation (data not shown); they were thus not likely to be causative.
