A "forward genomics" approach links genotype to phenotype using independent phenotypic losses among related species

Abstract

Genotype-phenotype mapping is hampered by countless genomic changes between species. We introduce a computational "forward genomics" strategy that-given only an independently lost phenotype and whole genomes-matches genomic and phenotypic loss patterns to associate specific genomic regions with this phenotype. We conducted genome-wide screens for two metabolic phenotypes. First, our approach correctly matches the inactivated Gulo gene exactly with the species that lost the ability to synthesize vitamin C. Second, we attribute naturally low biliary phospholipid levels in guinea pigs and horses to the inactivated phospholipid transporter Abcb4. Human ABCB4 mutations also result in low phospholipid levels but lead to severe liver disease, suggesting compensatory mechanisms in guinea pig and horse. Our simulation studies, counts of independent changes in existing phenotype surveys, and the forthcoming availability of many new genomes all suggest that forward genomics can be applied to many phenotypes, including those relevant for human evolution and disease.

Figure 1. Evolutionary model and assumptions behind our forward genomics approach

(A) An ancestral trait is passed to descendant species, along with the genomic regions required for this trait, which evolve under purifying selection. (B) One lineage loses the ancestral trait due to an inactivating mutation in a trait-required region. (C) Following trait loss, all trait-specific (non-pleiotropic) regions switch to evolve neutrally and begin to accumulate random mutations in the first trait-loss lineage. Meanwhile, two additional independent lineages lose this trait, due to independent mutations occurring either in the same or in other trait-required regions. (D) All trait-specific regions continue to erode independently in the three different trait-loss lineages, while their counterparts in the trait-preserving species are conserved due to purifying selection. This characteristic evolutionary signature can be detected using forward genomics, revealing functional components of this (monogenic or polygenic) trait.

Figure 2. A forward genomics screen to match an ancestral presence/absence trait pinpoints Gulo inactivation in vitamin C non-synthesizing species

(A) For every gene (dot) in the mouse genome (x-axis) we measured how well it matches the given phenotree by counting the number of species (y-axis) whose divergence level violates the expectation of divergence or conservation based on the vitamin C phenotree shown in panel C. Gulo, with 0 violations, is the only gene that perfectly matches. (B) Elevated ratio of non-synonymous to synonymous (Ka/Ks) substitutions show that remaining megabat and guinea pig exons evolve under relaxed pressure to preserve the Gulo protein sequence. (C) Non-synthesizing species show elevated sequence divergence in the Gulo coding sequence, with a divergence margin (grey) that perfectly separates them from synthesizing species. Note that the microbat and megabat lineage have independently lost this trait since intermediate bat species (without a sequenced genome) were biochemically shown to synthesize vitamin C (Cui et al., 2011a). (D) Graphical sequence alignment of the Gulo coding region. Rows match species in panel C. Large deletions (red blocks) occurred only in non-synthesizing species. See also Figures S1 and S2.

Figure 3. Forward genomics implicates independent inactivation of the human disease gene ABCB4 in two species with low levels of biliary phospholipids

(A) The level of biliary phospholipids is a continuous trait that varies over 200 fold between mammals. 796 genes show more divergence in guinea pig than ten other measured species, but only 8 genes show elevated divergence in both guinea pig and horse, the two species with the lowest biliary phospholipid levels. (B) We plot (y-axis) the number of violations of each gene (dot) in the mouse genome (x-axis), against the biliary phospholipid level phenotree in panel E. The eight genes with 0 violations are labeled. (C) Of the eight genes, only Abcb4 (bold) has a bile-related function. (D) Increased Abcb4 non-synonymous to synonymous (Ka/Ks) substitution ratios for guinea pig and horse. (E,F) Divergence from the reconstructed common ancestor (E) and a graphical sequence alignment representation (F) of the Abcb4 coding sequence reveals elevated divergence and deletions (red blocks) in trait-loss species only. See also Figure S3 and Table S1.

Figure 4. Broad applicability of our forward genomics approach

(A) We show the branches in the phylogeny that evolve neutrally for the trait-associated gene in the trait-loss simulation (red: vitamin C synthesis; green: biliary phospholipids). For biliary phospholipids, we simulated a loss that happened either 0.05 or 0.1 substitutions per site ago. (B) Simulations suggest that the evolutionary signature of independent loss of vitamin C synthesis can highlight exons of the trait-associated gene in nine of ten iterations (iteration 5 gave no hit). We observed no false positives. (C) Simulations of the biliary phospholipid trait show that in at least seven of ten iterations the single top-ranked hit is an exon of the trait-associated gene (shown as *) and that the trait-associated gene has often the most hits (shown as #) while false positives are scattered across the genome. The chart (right) shows that true positives (green) usually rank highly. (D) In three very different vertebrate phenotype scoring studies, an average of 42% of phenotypes have changes in two or more independent lineages, the conditions required for forward genomics analysis. See also Figure S4.