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Testing Hypotheses on the Rate of Molecular Evolution in Relation to Gene Expression Using Micrornas

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Testing Hypotheses on the Rate of Molecular Evolution in Relation to Gene Expression Using Micrornas Testing hypotheses on the rate of molecular evolution in relation to gene expression using microRNAs Yang Shena, Yang Lva, Lei Huanga, Wensheng Liua, Ming Wena, Tian Tanga, Rui Zhangb, Eric Hungatec, Suhua Shia, and Chung-I Wua,b,c,1 aState Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen (Zhongshan) University, Guangzhou 510275, China; bLaboratory of Disease Genomics and Personalized Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 101300, China; and cDepartment of Ecology and Evolution, University of Chicago, Chicago, IL 60637 Edited by Masatoshi Nei, Pennsylvania State University, University Park, PA, and approved August 19, 2011 (received for review June 22, 2011) There exists an inverse relationship between the rate of molecular In this study, we aim to test the second class of explanations evolution and the level of gene expression. Among the many concerning processing accuracy (or efficiency). Such tests would explanations, the “toxic-error” hypothesis is a most general one, have to meet the following requirements. First, the portion of the which posits that processing errors may often be toxic to the cells. gene that functions solely in processing can be separately ana- However, toxic errors that constrain the evolution of highly lyzed from the portion that determines the mature product. This expressed genes are often difficult to measure. In this study, we processing unit also needs to be evolutionarily conserved. Sec- test the toxic-error hypothesis by using microRNA (miRNA) genes ond, processing errors can be directly observed and measured. because their processing errors can be directly measured by deep Because protein-coding genes often do not meet the two require- sequencing. A miRNA gene consists of a small mature product (≈22 ments, we propose to use microRNA (miRNA) genes to identify nt long) and a “backbone.” Our analysis shows that (i) like the the connection between expression level and evolutionary rate. mature miRNA, the backbone is highly conserved; (ii) the rate of The canonical structure of a miRNA gene is given in Fig. 1. sequence evolution in the backbone is negatively correlated with The transcript is eventually processed into a mature miRNA expression; and (iii) although conserved between distantly related (miR), which is ≈22 nt long (17–20). The imperfect complement species, the error rate in miRNA processing is also negatively cor- of miR is denoted miR* (21, 22), which may sometimes be related with the expression level. The observations suggest that, a functional product itself (Discussion). The sequence to the right as a miRNA gene becomes more highly (or more ubiquitously) of the miR:miR* stem is referred to as the loop end and, to the expressed, its sequence evolves toward a structure that minimizes left, the stem extension. Hence, the miRNA gene can generally processing errors. be divided into two parts, the mature miR and the backbone, consisting of miR*, the loop end, and the stem extension (Fig. 1). evolutionary rate | microRNA biogenesis | microRNA evolution The backbone, not being part of the mature product, main- tains a proper hairpin structure for miR biogenesis (18, 23). By host of factors, including expression level, tissue specificity, analogy, the stem extension of miRNAs is akin to the intron of Agene dispensability, number of interacting proteins, and lo- mRNA; both are removed before the rest is exported to the cal recombination rate, influence the rate of molecular evolution cytoplasm. The loop region may be compared with the UTR of – mRNA; both contribute to the processing but are not part of the (1 7). Among them, gene expression level and ubiquity (or speci- fi ficity) are of particular interest, because both are general characters nal product. Furthermore, miRNAs are highly abundant in cells and the mature products, including those that are incorrectly and easily measurable. Both have been reported to be negatively processed, can be observed by deep sequencing. These proper- correlated with the rate of molecular evolution (1, 2, 8, 9). ties make miRNAs suitable for investigating the relationship There are two classes of explanations for the negative corre- between evolutionary rate and gene expression. lations. The first class concerns the properties of the gene pro- duct (i.e., postprocessing functions). One conjecture is that the Results more highly or ubiquitously expressed genes might be function- Evolutionary Conservation of miRNA Genes. Taking advantage of ally more important and, hence, might evolve more slowly (7, 10, the available genomic sequences from the 12 species of Dro- 11). [However, protein-coding genes with essential functions, sophila (24, 25), we calculated the evolutionary divergence in which include many housekeeping genes, do not always evolve each part of the miRNA genes. Because the patterns are broadly slowly (3, 12, 13).] It is also possible that highly expressed genes similar across all levels of phylogenetic depth (2–65 million may tend to have more interacting partners (14). The second years; Table S1), we focused on the divergence between D. virilis class of explanations invokes the accuracy or efficiency in making and D. melanogaster for simplicity. The divergence between these the gene product (i.e., processing or preprocessing functions). two species is near the limit whereby synonymous distance can For example, processing errors in protein synthesis are often still be calculated. assumed to result in toxic products (2, 15). Purifying selection In Drosophila, mature miRs are highly conserved. Most of the acts strongly on highly expressed genes because of a greater moderately to highly expressed miRNAs are completely con- quantity of erroneously synthesized products (2, 16). served in this genus. The extreme conservation of miRs, noted – The two classes of explanations are not mutually exclusive. many times before (26 28), may be explained by the large num- Explanations of the first class, based on the properties of the mature products, have been extensively explored with mixed Author contributions: Y.S., S.S., and C.-I.W. designed research; Y.S., Y.L., L.H., W.L., M.W., results (reviewed in refs. 12 and 15). A reason for the lack of T.T., R.Z., E.H., S.S., and C.-I.W. performed research; Y.S., Y.L., L.H., W.L., M.W., T.T., R.Z., a clear-cut conclusion may be the difficulties in separating the E.H., S.S., and C.-I.W. analyzed data; and Y.S. and C.-I.W. wrote the paper. two classes of explanations using protein-coding sequences. The authors declare no conflict of interest. Coding sequences determine the mature products but may often This article is a PNAS Direct Submission. be important in processing as well. Furthermore, errors in pro- 1To whom correspondence should be addressed. E-mail: [email protected]. cessing, such as protein misfolding, are usually computationally This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. inferred, rather than directly observed or measured (15). 1073/pnas.1110098108/-/DCSupplemental. 15942e15947 | PNAS | September 20, 2011 | vol. 108 | no. 38 www.pnas.org/cgi/doi/10.1073/pnas.1110098108 Downloaded by guest on September 25, 2021 Table 1 provides some details on sequence conservation. In simulations, we did not allow changes that disrupt the pairing configuration. In contrast, the unpaired sites change only half as often as simulations would allow (row 2). Fig. S1 presents four examples of conservation in the backbone. In the first two miRNA genes, there are 27 unpaired sites on the premiRNA Fig. 1. The canonical structure of the miRNA gene. Mature miRNA and its (including the loop region and bulge sites). During the 200 complement are denoted miR and miR*, respectively. Loop end is the in- million years of evolution in the four species, these unpaired sites terval between miR and miR*. Stem extension is a stem structure, averaged never experienced nucleotide substitutions. Although mis- to be ≈11 bp long, beyond the Drosha cut site. The four regions together inferences in the secondary structure might account for some of constitute a miRNA gene. Although a small region beyond stem extension is the patterns, the number of sites involved suggests that the con- often conserved as well, this region, having no obvious structure, is unsuit- servation of mispaired sites is not uncommon. For example, one able for evolutionary analysis. might have expected some “U/U” mismatches to occasionally change to “U/C” mismatches (transitions) without affecting the secondary structure, but that was not observed. Apparently, ber of targets (>50) each miR regulates. Likewise, proteins that unpaired sites are not all the same and identical secondary have many interacting partners also tend to evolve slowly (12). structures may not be functionally equivalent. Interestingly, the observed divergence in the backbone (Kb)of miRs is only 11% of synonymous substitution (Ks), and is even Divergence in miRNA Genes in Relation to Expression Level and Tissue lower than nonsynonymous substitution (13% of Ks). Because Specificity. The strong conservation of the backbone makes the the backbone is not part of the mature product (with the possible processing explanations plausible. In that case, a negative cor- exception of some miR*s; Discussion), its conservation cannot be relation between conservation and expression is expected. Using explained by the functions of miRs. We hence hypothesize that published data (refs. 30–32; see Table S2 for details) on genomic the structure of the precursor that governs miR processing may sequences and expression patterns in Drosophila, we analyzed be more relevant to the conservation. We carried out computer the correlation between the rate of evolution and the level of simulations in which the backbone is allowed to evolve while the expression (Fig. 3 A–C) and between the evolutionary rate and structure of the miRNA precursors is preserved. The observed the ubiquity of expression (Fig.
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