Hamilton's rule: A non-causal explanation?

The explanatory power of Hamilton's rule, the main explanatory principle of social evolution theory, is an ongoing subject of controversy. In this paper, we reinforce the case for the considerable value of the regression-based version of the rule in explaining the evolution of social traits. Although we agree that the rule can have an organizing role in social evolution research, we maintain that it does not explain in virtue of citing causes or providing an organizing framework. Instead, we argue it either provides an explanation by constraint or a non-causal counterfactual explanation.

How could models possibly provide how-possibly explanations?

One puzzle concerning highly idealized models is whether they explain. Some suggest they provide so-called 'how-possibly explanations'. However, this raises an important question about the nature of how-possibly explanations, namely what distinguishes them from 'normal', or how-actually, explanations? I provide an account of how-possibly explanations that clarifies their nature in the context of solving the puzzle of model-based explanation. I argue that the modal notions of actuality and possibility provide the relevant dividing lines between how-possibly and how-actually explanations. Whereas how-possibly explanations establish claims of possible explanations, how-actually explanations establish claims of actual ones. Models, in turn, simply provide evidence for these claims.

Understanding does not depend on (causal) explanation.

One can find in the literature two sets of views concerning the relationship between understanding and explanation: that one understands only if 1) one has knowledge of causes and 2) that knowledge is provided by an explanation. Taken together, these tenets characterize what I call the narrow knowledge account of understanding (narrow KAU). While the first tenet has recently come under severe attack, the second has been more resistant to change. I argue that we have good reasons to reject it on the basis of theoretical models that provide how-possibly explanations. These models, while they do not explain in the strict (narrow KAU) sense, afford understanding. In response, I propose an alternative epistemology of understanding, broad KAU, that takes cases of theoretical modelling into account.

Convergent origination of a Drosophila-like dosage compensation mechanism in a reptile lineage.

Sex chromosomes differentiated from different ancestral autosomes in various vertebrate lineages. Here, we trace the functional evolution of the XY Chromosomes of the green anole lizard (Anolis carolinensis), on the basis of extensive high-throughput genome, transcriptome and histone modification sequencing data and revisit dosage compensation evolution in representative mammals and birds with substantial new expression data. Our analyses show that Anolis sex chromosomes represent an ancient XY system that originated at least ≈160 million years ago in the ancestor of Iguania lizards, shortly after the separation from the snake lineage. The age of this system approximately coincides with the ages of the avian and two mammalian sex chromosomes systems. To compensate for the almost complete Y Chromosome degeneration, X-linked genes have become twofold up-regulated, restoring ancestral expression levels. The highly efficient dosage compensation mechanism of Anolis represents the only vertebrate case identified so far to fully support Ohno's original dosage compensation hypothesis. Further analyses reveal that X up-regulation occurs only in males and is mediated by a male-specific chromatin machinery that leads to global hyperacetylation of histone H4 at lysine 16 specifically on the X Chromosome. The green anole dosage compensation mechanism is highly reminiscent of that of the fruit fly, Drosophila melanogaster Altogether, our work unveils the convergent emergence of a Drosophila-like dosage compensation mechanism in an ancient reptilian sex chromosome system and highlights that the evolutionary pressures imposed by sex chromosome dosage reductions in different amniotes were resolved in fundamentally different ways.

The complete local genotype-phenotype landscape for the alternative splicing of a human exon.

The properties of genotype-phenotype landscapes are crucial for understanding evolution but are not characterized for most traits. Here, we present a >95% complete local landscape for a defined molecular function-the alternative splicing of a human exon (FAS/CD95 exon 6, involved in the control of apoptosis). The landscape provides important mechanistic insights, revealing that regulatory information is dispersed throughout nearly every nucleotide in an exon, that the exon is more robust to the effects of mutations than its immediate neighbours in genotype space, and that high mutation sensitivity (evolvability) will drive the rapid divergence of alternative splicing between species unless it is constrained by selection. Moreover, the extensive epistasis in the landscape predicts that exonic regulatory sequences may diverge between species even when exon inclusion levels are functionally important and conserved by selection.

Mechanisms and evolutionary patterns of mammalian and avian dosage compensation.

As a result of sex chromosome differentiation from ancestral autosomes, male mammalian cells only contain one X chromosome. It has long been hypothesized that X-linked gene expression levels have become doubled in males to restore the original transcriptional output, and that the resulting X overexpression in females then drove the evolution of X inactivation (XCI). However, this model has never been directly tested and patterns and mechanisms of dosage compensation across different mammals and birds generally remain little understood. Here we trace the evolution of dosage compensation using extensive transcriptome data from males and females representing all major mammalian lineages and birds. Our analyses suggest that the X has become globally upregulated in marsupials, whereas we do not detect a global upregulation of this chromosome in placental mammals. However, we find that a subset of autosomal genes interacting with X-linked genes have become downregulated in placentals upon the emergence of sex chromosomes. Thus, different driving forces may underlie the evolution of XCI and the highly efficient equilibration of X expression levels between the sexes observed for both of these lineages. In the egg-laying monotremes and birds, which have partially homologous sex chromosome systems, partial upregulation of the X (Z in birds) evolved but is largely restricted to the heterogametic sex, which provides an explanation for the partially sex-biased X (Z) expression and lack of global inactivation mechanisms in these lineages. Our findings suggest that dosage reductions imposed by sex chromosome differentiation events in amniotes were resolved in strikingly different ways.

The evolution of gene expression levels in mammalian organs.

Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

STRING 8--a global view on proteins and their functional interactions in 630 organisms.

Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures. Version 8.0 of STRING covers about 2.5 million proteins from 630 organisms, providing the most comprehensive view on protein-protein interactions currently available. STRING can be reached at http://string-db.org/.

eggNOG: automated construction and annotation of orthologous groups of genes.

The identification of orthologous genes forms the basis for most comparative genomics studies. Existing approaches either lack functional annotation of the identified orthologous groups, hampering the interpretation of subsequent results, or are manually annotated and thus lag behind the rapid sequencing of new genomes. Here we present the eggNOG database ('evolutionary genealogy of genes: Non-supervised Orthologous Groups'), which contains orthologous groups constructed from Smith-Waterman alignments through identification of reciprocal best matches and triangular linkage clustering. Applying this procedure to 312 bacterial, 26 archaeal and 35 eukaryotic genomes yielded 43 582 course-grained orthologous groups of which 9724 are extended versions of those from the original COG/KOG database. We also constructed more fine-grained groups for selected subsets of organisms, such as the 19 914 mammalian orthologous groups. We automatically annotated our non-supervised orthologous groups with functional descriptions, which were derived by identifying common denominators for the genes based on their individual textual descriptions, annotated functional categories, and predicted protein domains. The orthologous groups in eggNOG contain 1 241 751 genes and provide at least a broad functional description for 77% of them. Users can query the resource for individual genes via a web interface or download the complete set of orthologous groups at http://eggnog.embl.de.