Interestingly, the cascade of events leading to the evolution of SLTS may result in increased molecular complexity, by enabling new molecular paths of gene expression.
2. The paths of gene loss are partially parallel and partially divergent as also noticed on many previous occasions, just for instance: Foster J. PLoS Biol.
If the paths of gene exchange are random, the number of exchanges between a pair of clades is expected to be proportional to the product of the numbers of gains on these clades.
Conserved syntenic regions would provide remarkable insight into the evolutionary paths of genes and genomes [21], [22], [34], [35].
Studies of the evolutionary paths of genes have shown that genome novelty is generated primarily by gene duplication and subsequent functional changes, and to a lesser extent, by de novo generation or the creation of mosaic genes [1], [2], [3].
Most studies of biological diversity in crops have focused on morphological characters and DNA markers, covering both ends of the path of gene expression from genome to phenotype.
To address this question, we consider the evolutionary path of genes in the earliest forms of life on Earth, where it is generally regarded that proteins evolved from a cellular machinery based entirely within RNA.
To the extent that these genes are really of bacterial origin, it may emphasize the unusual paths of SG gene evolution in the quest of hematophagous animals to obtain their 'perfect' potion that allows disarming of the complex host pathways of inflammation and hemostasis that would otherwise disrupt blood feeding.
After these adjustments, we consider each resulting component as a splicing graph that specifies the alternative splicing paths of one gene.
It is possible that the causal genes of a disease, which holds the symptom as particular phenotype, would be the related genes for symptom (marked in pink box), or the candidate genes for symptom would possibly locate on the shortest paths of these genes of the diseases, which have the related symptoms as general phenotypes (marked in red box).
The maximum run time of ∼850 s (<15 min) for realistic settings, (10 000 paths of ≥10 genes, entire KEGG yeast metabolic network), shows reasonable practical performance of our path ranking method.
