Carlo Artieri writes about his new paper: Evolution at two levels of gene expression in yeast which is in press in Genome Research.
Understanding the molecular basis of regulatory variation within and between species has become a major focus of modern genetics. For instance, the majority of identified human disease-risk alleles lie in non-coding regions of the genome, suggesting that they affect gene regulation (Epstein 2009). Furthermore, it has been argued that regulatory changes have played a dominant role in explaining uniquely human attributes (King and Wilson 1975). However, our knowledge of gene regulatory evolution is based almost entirely on studies of mRNA levels, despite both the greater functional importance of protein abundance, and evidence that post-transcriptional regulation is pervasive. The availability of high-throughput methods for measuring mRNA abundance, coupled to the lack of comparable methods at the protein level have contributed to this focus; however, a new method known as ribosome profiling, or ‘riboprofiling’ (Ingolia et al. 2009), has enabled us to study the evolution of translation in much greater detail than was possible before. This method involves the construction of two RNA-seq libraries: one measuring mRNA abundance (the ‘mRNA’ fraction), and the second capturing the portion of the transcriptome that is actively being translated by ribosomes (the ‘Ribo’ fraction). On average, the abundance of genes within the Ribo fraction should be proportional to that of the mRNA fraction. Genes with increased translational efficiency are identified when Ribo fraction abundance is higher than that of the mRNA fraction, whereas reduced translational efficiency is inferred when the opposite is observed.
Riboprofiling of yeast hybrids
We performed riboprofiling on hybrids of two closely related species of budding yeast, Saccharomyces cerevisiae and S. paradoxus, (~5 million years diverged). In hybrids, the parental alleles at a locus share the same trans cellular environment; therefore in the absence of cis-regulatory divergence in transcription, both alleles should be expressed at equal levels. Conversely, cis-regulatory divergence will produce unequal expression of alleles (termed allele-specific expression, or ‘ASE’). Cis-regulatory divergence at the translational level is detected when ASE in the mRNA fraction does not equal that measured in the Ribo fraction, indicating independent divergence across levels. We also performed riboprofiling on the two parental strains, as differences in the expression of orthologs between parental species that cannot be explained by the allelic differences in the hybrids can be attributed to trans divergence. Therefore, by measuring differences in the magnitudes of ASE between the two riboprofiling fractions in the hybrids and the parents, we identified independent cis and trans regulatory changes in both mRNA abundance and translational efficiency.
We found that both cis and trans regulatory divergence in translational efficiency is widespread, and of comparable magnitude to divergence at the mRNA level – indicating that we miss much regulatory evolution by focusing on mRNA in isolation. Moreover, we observed an overwhelming bias towards divergence in opposing parental directions, indicating that while many orthologs had higher mRNA abundance in one parent, they often showed increased translational efficiency in the other parent. This suggests that stabilizing selection acts to maintain more similar protein levels between species than would be expected by comparing mRNA abundances alone.
Translational divergence not associated with TATA boxes
Interestingly, while we confirmed the results of previous studies indicating that both cis and trans regulatory divergence at the mRNA level are associated with the presence of TATA boxes and nucleosome free regions in promoters, no such relationship was found for translational divergence, indicating that these regulatory systems have different underlying architectures.
Evidence for polygenic selection at two levels
We also searched for evidence of polygenic selection in and between both regulatory levels by applying a recently developed modification of Orr’s sign test (Orr 1998; Fraser et al. 2010; Bullard et al. 2010). Under neutral divergence, no pattern is expected with regards to the parental direction of up or down-regulating alleles among orthologs within a functional group (e.g., a pathway or multi-gene complex). However, a significant bias towards one parental lineage is evidence of lineage-specific selection. This analysis uncovered evidence of polygenic selection at both regulatory levels in a number of functional groups. In particular, genes involved in tolerance to heavy metals were enriched for reinforcing divergence in mRNA abundance and translation favoring S. cerevisiae. Increased tolerance to these metals has been observed in S. cerevisiae (Warringer et al. 2011), suggesting that domesticated yeasts have experienced a history of polygenic adaptation across regulatory levels allowing them to grow on metals such as copper.
Finally, using data from the Ribo fraction, we also uncovered multiple instances of conserved stop-codon readthrough, a mechanism via which the ribosome ‘ignores’ the canonical stop codon and produces a C-terminally extended peptide. Only two cases of C-terminal extensions have previously been observed in yeast, though in one such case, PDE2, extension of the canonical protein plays a functional role in regulating cAMP levels (Namy et al. 2002). Our data suggests that this mechanism may occur in dozens of genes, highlighting yet another post-transcriptional mechanism leading to increased proteomic diversity.
By applying a novel approach to a long-standing question, our analysis has revealed that post-transcriptional regulation is abundant, and likely as important as transcriptional regulation. We argue that partitioning the search for the locus of selection into the binary categories of ‘coding’ vs. ‘regulatory’ overlooks the many opportunities for selection to act at multiple regulatory levels along the path from genotype to phenotype.
Bullard JH, Mostovoy Y, Dudoit S, Brem RB. 2010. Polygenic and directional regulatory evolution across pathways in Saccharomyces. Proc Natl Acad Sci USA 107: 5058-5063.
Epstein DJ. 2009. Cis-regulatory mutations in human disease. Brief Funct Genomic Proteomic 8: 310–316.
Fraser HB, Moses AM, Schadt EE. 2010. Evidence for widespread adaptive evolution of gene expression in budding yeast. Proc Natl Acad Sci USA 107: 2977-2982.
Ingolia NT, Ghaemmaghami S, Newman JR, Weissman JS. 2009. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324:218-223.
King MC, Wilson AC. 1975. Evolution at two levels in humans and chimpanzees. Science 188: 107-116.
Namy O, Duchateau-Nguyen G, Rousset JP. 2002. Translational readthrough of the PDE2 stop codon modulates cAMP levels in Saccharomyces cerevisiae. Mol Microbiol 43: 641-652.
Orr HA. 1998. Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data. Genetics 149: 2099-2104.
Warringer J, Zörgö E, Cubillos FA, Zia A, Gjuvsland A, Simpson JT, Forsmark A, Durbin R, Omholt SW, Louis EJ, Liti G, Moses A, Blomberg A. 2011. Trait variation in yeast is defined by population history. PLoS Genet 7 :e1002111.