The recent increase in genomic data is revealing an unexpected perspective of gene loss as a pervasive source of genetic variation that can cause adaptive phenotypic diversity. This novel perspective of gene loss is raising new fundamental questions. How relevant has gene loss been in the divergence of phyla? How do genes change from being essential to dispensable and finally to being lost? Is gene loss mostly neutral, or can it be an effective way of adaptation? These questions are addressed, and insights are discussed from genomic studies of gene loss in populations and their relevance in evolutionary biology and biomedicine.

Evolution by gene loss

DNA hydroxymethylation and its mediated DNA demethylation are critical for multiple cellular processes, for example, nuclear reprogramming, embryonic development, and many diseases. Here, we demonstrate that a vital nutrient ascorbic acid (AA), or vitamin C (Vc), can directly enhance the catalytic activity of Tet dioxygenases for the oxidation of 5-methylcytosine (5mC). As evidenced by changes in intrinsic fluorescence and catalytic activity of Tet2 protein caused by AA and its oxidation-resistant derivatives, we further show that AA can uniquely interact with the C-terminal catalytic domain of Tet enzymes, which probably promotes their folding and/or recycling of the cofactor Fe2+. Other strong reducing chemicals do not have a similar effect. These results suggest that AA also acts as a cofactor of Tet enzymes. In mouse embryonic stem cells, AA significantly increases the levels of all 5mC oxidation products, particularly 5-formylcytosine and 5-carboxylcytosine (by more than an order of magnitude), leadi...

Ascorbic acid enhances tet-mediated 5-methylcytosine oxidation and promotes DNA demethylation in mammals

The concepts of orthology and paralogy are fundamental to comparative genomics and are also frequently used for the functional annotation of uncharacterized genes. However, assumptions regarding function have recently been challenged, and the implications of assigning genes as orthologues or paralogues are far from straightforward.

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Functional and evolutionary implications of gene orthology

At different stages of any research project, molecular biologists need to choose - often somewhat arbitrarily, even after careful statistical data analysis - which genes or proteins to investigate further experimentally and which to leave out because of limited resources. Computational methods that integrate complex, heterogeneous data sets - such as expression data, sequence information, functional annotation and the biomedical literature - allow prioritizing genes for future study in a more informed way. Such methods can substantially increase the yield of downstream studies and are becoming invaluable to researchers.

Computational tools for prioritizing candidate genes: boosting disease gene discovery

To critically examine the relationship between species recognized by phylogenetic and reproductive compatibility criteria, we applied phylogenetic species recognition (PSR) to the fungus in which biological species recognition (BSR) has been most comprehensively applied, the well-studied genus Neurospora. Four independent anonymous nuclear loci were characterized and sequenced from 147 individuals that were representative of all described outbreeding species of Neurospora. We developed a consensus-tree approach that identified monophyletic genealogical groups that were concordantly supported by the majority of the loci, or were well supported by at least one locus but not contradicted by any other locus. We recognized a total of eight phylogenetic species, five of which corresponded with the five traditional biological species, and three of which were newly discovered. Not only were phylogenetic criteria superior to traditional reproductive compatibility criteria in revealing the full species diversity of Neurospora, but also significant phylogenetic subdivisions were detected within some species. Despite previous suggestions of hybridization between N. crassa and N. intermedia in nature, and the fact that several putative hybrid individuals were included in this study, no molecular evidence in support of recent interspecific gene flow or the existence of true hybrids was observed. The sequence data from the four loci were combined and used to clarify how the species discovered by PSR were related. Although species-level clades were strongly supported, the phylogenetic relationships among species remained difficult to resolve, perhaps due to conflicting signals resulting from differential lineage sorting.

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A multilocus genealogical approach to phylogenetic species recognition in the model eukaryote Neurospora.

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Evo–devo: Plastic flies

(SNPs) are the bread and butter of many studies of sequence variation, and so understanding how they vary is useful to studies of genome evolution and disease susceptibility. Most human SNPs are biallelic — that is, two allelic variants are segregating in the population — but a paper now shows that there are twice as many triallelic SNPs as expected, and puts forward a mutational mechanism by which they might arise. Hodgkinson and Eyre-Walker looked at the allelic diversity of SNPs in ~900 nuclear genes. When both exons and CpG dinucleotides were excluded (to avoid biases caused, respectively, by natural selection and a higher mutation rate), the number of triallelic sites in the data set was 113 — twice the number that would be expected if mutations were randomly distributed. There are several possible explanations for this excess, which the authors proceeded to test. Natural selection on the region of the SNPs is an obvious candidate. Another is that the nature of the nucleotides surrounding a triallelic SNP increases the local mutation rate. But neither of these explanations holds up — biallelic SNPs are not clustered, as one would expect if selection was preventing them from segregating, and the probability of seeing a triallelic SNP was independent of the local sequence context. If the mutational properties of particular regions are not to blame, then perhaps the explanation lies in the ability of a site, once mutated, to generate a second mutation. This could occur through the resolution of a mismatched heteroduplex during recombination (for example, a G–C base pair that mutates to an A–C mismatch, and then to an A–G). This is also not the case, however, as there is no correlation between the recombination rate of a gene and the presence of a triallelic SNP. Although other, untested explanations could account for the observed levels of diversity, the most plausible is a mutational mechanism that leads to the simultaneous creation of two new base pairs at the same site. The mechanism is not known, but simultaneous generation of two mutations might also explain an observed excess of adjacent biallelic SNPs. This model will be tested in the not-too-distant future by the 1000 Genomes Project; the explanation will be borne out if a haplotype analysis of the non-recombining portion of the Y chromosome reveals that two of the alleles at triallelic sites emerged coincidentally. Tanita Casci

Population genetics: SNPs that come in threes.

ago that many animal embryos converge on a similar form during development, only to diverge afterwards. This temporal ‘waist’ in the so-called hourglass model of embryonic development is known as the ‘phylotypic stage’, and it is thought — controversially, given that it is based on subjective morphological comparisons — to represent an evolutionary conserved period. Now, two transcriptomics studies give this theory strong molecular support by showing that genes active during this period are more ancient and more highly conserved in their expression. Kalinka, Varga and colleagues directly tested the hourglass model by comparing genome-wide expression profiles across embryonic development in six species of Drosophila. By generating a DNA microarray time-course for over 3,000 orthologous genes, they show that variation in temporal gene expression across species is minimal at the phylotypic stage and is greater before and after that point. Modelling suggests that this pattern is best explained by selective constraint, which seems to be strongest at the phylotypic stage. The genes whose expression follows the hourglass pattern are also most likely to be involved in core developmental processes. In a related study, Domazet-Lošo and Tautz combined transcriptomics and evolutionary developmental genomics to connect morphological novelties to the evolutionary age of genes that are expressed at different developmental stages. They used a previously described approach known as ‘phylostratigraphy’ to divide the genome into gene classes, each of which encompasses genes that have evolved at a distinct evolutionary stage (for example, a set of genes might be common to all cells, to all animals or to all chordates). By overlaying this gene classification on the developmental transcriptome of zebrafish (Danio rerio), they showed that genes that are expressed at the phylotypic stage belong to the oldest and most conserved set; by contrast, genes expressed earlier or later are more likely to belong to more newly evolved gene sets. A similar pattern was also seen in published data from Drosophila melanogaster, Anopheles gambiae and Caenorhabditis elegans. The phylotypic stage is the step at which the principal animal body-plan is laid down — the conserved expression profile described by these studies would have been established early in the evolution of multicellular life, and the steps both before and after it would have diverged to forge the morphological diversity we see across animal species. However, the mechanism that preserves the expression profile seen in the hourglass waist remains to be definitively established: is the mid-embryonic stage actively constrained by selection or is it under less pressure to evolve than early and late stages? These studies open up opportunities to address such mechanistic questions experimentally. Tanita Casci

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Development: Hourglass theory gets molecular approval

To identify key genes involved in wound healing, Masinde et al. crossed two mouse strains together that have markedly different wound-healing rates. They then carried out genome-wide scans in F 2 mice at different time points after ear punching and found ten wound-healing quantitative trait loci (QTL), eight of which are new. Some QTL are involved at all stages of wound healing, and epistatic interactions between loci also occur.

Tanita Casci

Papers

Evo–devo: Plastic flies

Population genetics: SNPs that come in threes.

Development: Hourglass theory gets molecular approval

Filling the gap in gene prediction

Network fundamentals, via hub genes