@article{23121,
  abstract     = {A widespread observation in molecular evolution is that X-linked genes evolve faster—and often adapt faster—than autosomal genes. Three main ideas have been put forward to explain “faster-X” adaptation. The first is that new beneficial mutations are typically partially recessive with respect to fitness, leading to more efficient selection in hemizygous males. The second is that sex differences in recombination, or sex differences in variance in reproductive success, enhance the effective population size on the X chromosome relative to autosomes. Both ideas have limitations: the first conflicts with theories of dominance, in which beneficial mutations are proposed to be partially dominant, while the second only applies to some taxa. Here we tested a third, newly-proposed theory, in which mutations with large “scaled phenotypic effects” (i.e., large effects relative to the distance to a phenotypic optimum) experience more positive selection on the X. Specifically, we used three proxies for scaled phenotypic effects—amino-acid dissimilarity, amino-acid conservation, and gene age—and estimated X and autosomal rates of adaptation of nonsynonymous mutations across effect-size classes. We did this in three lineages with a well-documented faster-X: Drosophila melanogaster, Mus musculus, and Homo sapiens. As expected, we found that large-effect mutations were more likely to be under purifying selection and less likely to be under positive selection than small-effect mutations. However, contrary to the new theory, faster-X adaptation was not enriched among large-effect mutations. Overall, our results highlight an unresolved gap between patterns of sex chromosome evolution and theories of dominance for fitness.},
  author       = {Ruzicka, Filip and Vicoso, Beatriz},
  issn         = {1759-6653},
  journal      = {Genome Biology and Evolution},
  keywords     = {evolutionary biology, population genetics, sex chromosomes, adaptation, genetic divergence, McDonald-Kreitman test, Fisher’s geometric model},
  publisher    = {Oxford University Press},
  title        = {{Is faster-X adaptation due to large-effect mutations? An empirical test of a new theory}},
  doi          = {10.1093/gbe/evag259},
  year         = {2026},
}

@article{11679,
  abstract     = {We are given a set T = {T 1 ,T 2 , . . .,T k } of rooted binary trees, each T i leaf-labeled by a subset L(Ti)⊂{1,2,...,n} . If T is a tree on {1,2, . . .,n }, we let T|L denote the minimal subtree of T induced by the nodes of L and all their ancestors. The consensus tree problem asks whether there exists a tree T * such that, for every i , T∗|L(Ti) is homeomorphic to T i .

We present algorithms which test if a given set of trees has a consensus tree and if so, construct one. The deterministic algorithm takes time min{O(N n 1/2 ), O(N+ n 2 log n )}, where N=∑i|Ti| , and uses linear space. The randomized algorithm takes time O(N log3 n) and uses linear space. The previous best for this problem was a 1981 O(Nn) algorithm by Aho et al. Our faster deterministic algorithm uses a new efficient algorithm for the following interesting dynamic graph problem: Given a graph G with n nodes and m edges and a sequence of b batches of one or more edge deletions, then, after each batch, either find a new component that has just been created or determine that there is no such component. For this problem, we have a simple algorithm with running time O(n 2 log n + b 0 min{n 2 , m log n }), where b 0 is the number of batches which do not result in a new component. For our particular application, b0≤1 . If all edges are deleted, then the best previously known deterministic algorithm requires time O(mn−−√) to solve this problem. We also present two applications of these consensus tree algorithms which solve other problems in computational evolutionary biology.},
  author       = {Henzinger, Monika H and King, V. and Warnow, T.},
  issn         = {1432-0541},
  journal      = {Algorithmica},
  keywords     = {Algorithms, Data structures, Evolutionary biology, Theory of databases},
  pages        = {1--13},
  publisher    = {Springer Nature},
  title        = {{Constructing a tree from homeomorphic subtrees, with applications to computational evolutionary biology}},
  doi          = {10.1007/pl00009268},
  volume       = {24},
  year         = {1999},
}