Introduction {#s1}
============

MicroRNAs (miRNAs) are small non-coding RNAs that serve as post-transcriptional regulators of gene expression in plants and animals. They act by binding to complementary sites on target mRNAs to induce cleavage or repression of productive translation (reviewed in \[[@pbio-0030085-b01],[@pbio-0030085-b02],[@pbio-0030085-b03],[@pbio-0030085-b04]\]). The importance of miRNAs for development is highlighted by the fact that they comprise approximately 1% of genes in animals, and are often highly conserved across a wide range of species (e.g., \[[@pbio-0030085-b05],[@pbio-0030085-b06],[@pbio-0030085-b07]\]). Further, mutations in proteins required for miRNA function or biogenesis impair animal development \[[@pbio-0030085-b08],[@pbio-0030085-b09],[@pbio-0030085-b10],[@pbio-0030085-b11],[@pbio-0030085-b12],[@pbio-0030085-b13],[@pbio-0030085-b14],[@pbio-0030085-b15]\].

To date, functions have been assigned to only a few of the hundreds of animal miRNA genes. Mutant phenotypes in nematodes and flies led to the discovery that the *lin-4* and *let-7* miRNAs control developmental timing \[[@pbio-0030085-b16],[@pbio-0030085-b17]\], that *lsy-6* miRNA regulates left--right asymmetry in the nervous system \[[@pbio-0030085-b18]\], that *bantam* miRNA controls tissue growth \[[@pbio-0030085-b19]\], and that *bantam* and *miR-14* control apoptosis \[[@pbio-0030085-b19],[@pbio-0030085-b20]\]. Mouse *miR-181* is preferentially expressed in bone marrow and was shown to be involved in hematopoietic differentiation \[[@pbio-0030085-b21]\]. Recently, mouse *miR-375* was found to be a pancreatic-islet-specific miRNA that regulates insulin secretion \[[@pbio-0030085-b22]\].

Prediction of miRNA targets provides an alternative approach to assign biological functions. This has been very effective in plants, where miRNA and target mRNA are often nearly perfectly complementary \[[@pbio-0030085-b23],[@pbio-0030085-b24],[@pbio-0030085-b25]\]. In animals, functional duplexes can be more variable in structure: they contain only short complementary sequence stretches, interrupted by gaps and mismatches. To date, specific rules for functional miRNA--target pairing that capture all known functional targets have not been devised. This has created problems for search strategies, which apply different assumptions about how to best identify functional sites. As a result, the number of predicted targets varies considerably with only limited overlap in the top-ranking targets, indicating that these approaches might only capture subsets of real targets and/or may include a high number of background matches (\[[@pbio-0030085-b19],[@pbio-0030085-b26],[@pbio-0030085-b27],[@pbio-0030085-b28],[@pbio-0030085-b29],[@pbio-0030085-b30]\]; reviewed by \[[@pbio-0030085-b31]\]). Nonetheless, a number of predicted targets have proven to be functional when subjected to experimental tests \[[@pbio-0030085-b19],[@pbio-0030085-b26],[@pbio-0030085-b27],[@pbio-0030085-b29]\].

A better understanding of the pairing requirements between miRNA and target would clearly improve predictions of miRNA targets in animals. It is known that defined *cis*-regulatory elements in *Drosophila* 3′ UTRs are complementary to the 5′ ends of certain miRNAs \[[@pbio-0030085-b32]\]. The importance of the miRNA 5′ end has also emerged from the pairing characteristics and evolutionary conservation of known target sites \[[@pbio-0030085-b26]\], and from the observation of a non-random statistical signal specific to the 5′ end in genome-wide target predictions \[[@pbio-0030085-b27]\]. Tissue culture experiments have also underscored the importance of 5′ pairing and have provided some specific insights into the general structural requirements \[[@pbio-0030085-b29],[@pbio-0030085-b33],[@pbio-0030085-b34]\], though different studies have conflicted to some degree with each other, and with known target sites (reviewed in \[[@pbio-0030085-b31]\]). To date, no specific role has been ascribed to the 3′ end of miRNAs, despite the fact that miRNAs tend to be conserved over their full length.

Here, we systematically evaluate the minimal requirements for a functional miRNA--target duplex in vivo. These experiments have allowed us to identify two broad categories of miRNA target sites. Targets in the first category, "5′ dominant" sites, base-pair well to the 5′ end of the miRNA. Although there is a continuum of 3′ pairing quality within this class, it is useful to distinguish two subtypes: "canonical" sites, which pair well at both the 5′ and 3′ ends, and "seed" sites, which require little or no 3′ pairing support. Targets in the second category, "3′ compensatory" sites, have weak 5′ base-pairing and depend on strong compensatory pairing to the 3′ end of the miRNA. We present evidence that all of these site types are used to mediate regulation by miRNAs and show that the 3′ compensatory class of target sites is used to discriminate among individual members of miRNA families in vivo. A genome-wide statistical analysis allows us to estimate that an average miRNA has approximately 100 evolutionarily conserved target sites, indicating that miRNAs regulate a large fraction of protein-coding genes. Evaluation of 3′ pairing quality suggests that seed sites are the largest group. Sites of this type have been largely overlooked in previous target prediction methods.

Results {#s2}
=======

The Minimal miRNA Target Site {#s2a}
-----------------------------

To improve our understanding of the minimal requirements for a functional miRNA target site, we made use of a simple in vivo assay in the *Drosophila* wing imaginal disc. We expressed a miRNA in a stripe of cells in the central region of the disc and assessed its ability to repress the expression of a ubiquitously transcribed enhanced green fluorescent protein (EGFP) transgene containing a single target site in its 3′ UTR. The degree of repression was evaluated by comparing EGFP levels in miRNA-expressing and adjacent non-expressing cells. Expression of the miRNA strongly reduced EGFP expression from transgenes containing a single functional target site ([Figure 1](#pbio-0030085-g001){ref-type="fig"}A).

![Complementarity to the miRNA 5′ End Is Important for Target Site Function In Vivo\
(A) In vivo assay for target site regulation in the wing imaginal disc. The EGFP reporter is expressed in all cells (green). Cells expressing the miRNA under ptcGal4 control are shown in red. Functional target sites allow strong GFP repression by the miRNA (middle). Non-functional target sites do not (right). Yellow boxes indicate the disc region shown in (B) and later figures.\
(B) Regulation of individual target sites by *miR-7.* Numbers in the upper left of each image indicate the mismatched nucleotide in the target site. Positions important for regulation are shown in red, dispensable positions in green. Regulation by the miRNA is completely abolished in only a few cases.\
(C) Summary of the magnitude of reporter gene repression for the series in (B) and for a second set involving *miR-278* and a target site resembling the *miR-9* site in *Lyra* \[[@pbio-0030085-b26]\]. Positions important for regulation are shown in red, dispensable positions in green. Error bars are based on measurements of 3--5 individual discs.](pbio.0030085.g001){#pbio-0030085-g001}

In a first series of experiments we asked which part of the RNA duplex is most important for target regulation. A set of transgenic flies was prepared, each of which contained a different target site for *miR-7* in the 3′ UTR of the EGFP reporter construct. The starting site resembled the strongest *bantam* miRNA site in its biological target *hid* \[[@pbio-0030085-b19]\] and conferred strong regulation when present in a single copy in the 3′ UTR of the reporter gene ([Figure 1](#pbio-0030085-g001){ref-type="fig"}B). We tested the effects of introducing single nucleotide changes in the target site to produce mismatches at different positions in the duplex with the miRNA (note that the target site mismatches were the only variable in these experiments). The efficient repression mediated by the starting site was not affected by a mismatch at positions 1, 9, or 10, but any mismatch in positions 2 to 8 strongly reduced the magnitude of target regulation. Two simultaneous mismatches introduced into the 3′ region had only a small effect on target repression, increasing reporter activity from 10% to 30%. To exclude the possibility that these findings were specific for the tested miRNA sequence or duplex structure, we repeated the experiment with *miR-278* and a different duplex structure. The results were similar, except that pairing of position 8 was not important for regulation in this case ([Figure 1](#pbio-0030085-g001){ref-type="fig"}C). Moreover, some of the mismatches in positions 2--7 still allowed repression of EGFP expression up to 50%. Taken together, these observations support previous suggestions that extensive base-pairing to the 5′ end of the miRNA is important for target site function \[[@pbio-0030085-b26],[@pbio-0030085-b27],[@pbio-0030085-b29],[@pbio-0030085-b32],[@pbio-0030085-b34]\].

We next determined the minimal 5′ sequence complementarity necessary to confer target regulation. We refer to the core of 5′ sequence complementarity essential for target site recognition as the "seed" (Lewis et al. \[[@pbio-0030085-b27]\]). All possible 6mer, 5mer, and 4mer seeds complementary to the first eight nucleotides of the miRNA were tested in the context of a site that allowed strong base-pairing to the 3′ end of the miRNA ([Figure 2](#pbio-0030085-g002){ref-type="fig"}A). The seed was separated from a region of complete 3′ end pairing by a constant central bulge. 5mer and 6mer seeds beginning at positions 1 or 2 were functional. Surprisingly, as few as four base-pairs in positions 2--5 conferred efficient target regulation under these conditions, whereas bases 1--4 were completely ineffective. 4mer, 5mer, or 6mer seeds beginning at position 3 were less effective. These results suggest that a functional seed requires a continuous helix of at least 4 or 5 nucleotides and that there is some position dependence to the pairing, since sites that produce comparable pairing energies differ in their ability to function. For example, the first two duplexes in [Figure 2](#pbio-0030085-g002){ref-type="fig"}A (4mer, top row) have identical 5′ pairing energies (ΔG for the first 8 nt was −8.9 kcal/mol), but only one is functional. Similarly, the third 4mer duplex and fourth 5mer duplex (middle row) have the same energy (−8.7 kcal/mol), but only one is functional. We thus do not find a clear correlation between 5′ pairing energy and function, as reported in \[[@pbio-0030085-b34]\]. These experiments also indicate that extensive 3′ pairing of up to 17 nucleotides in the absence of the minimal 5′ element is not sufficient to confer regulation. Consequently, target searches based primarily on optimizing the extent of base-pairing or the total free energy of duplex formation will include many non-functional target sites \[[@pbio-0030085-b28],[@pbio-0030085-b30],[@pbio-0030085-b35]\], and ranking miRNA target sites according to overall complementarity or free energy of duplex formation might not reflect their biological activity \[[@pbio-0030085-b26],[@pbio-0030085-b27],[@pbio-0030085-b28],[@pbio-0030085-b30],[@pbio-0030085-b35]\].

![The Minimal miRNA Target Site\
(A) In vivo tests of the function of target sites with 6mer, 5mer, and 4mer seeds complementary to the first eight nucleotides of the miRNA. Sites were designed to have optimal support from 3′ pairing. The first 4mer seed site shows that extensive complementarity to the miRNA 3′ region is not sufficient for regulation in vivo.\
(B) Regulation of 8mer, 7mer, and 6mer seed sites lacking complementarity to the miRNA 3′ end. The test UTR contained one site (first column) or two identical sites (second column).](pbio.0030085.g002){#pbio-0030085-g002}

To determine the minimal lengths of 5′ seed matches that are sufficient to confer regulation alone, we tested single sites that pair with eight, seven, or six consecutive bases to the miRNA\'s 5′ end, but that do not pair to its 3′ end ([Figure 2](#pbio-0030085-g002){ref-type="fig"}B). Surprisingly, a single 8mer seed (miRNA positions 1--8) was sufficient to confer strong regulation by the miRNA. A single 7mer seed (positions 2--8) was also functional, although less effective. The magnitude of regulation for 8mer and 7mer seeds was strongly increased when two copies of the site were introduced in the UTR. In contrast, 6mer seeds showed no regulation, even when present in two copies. Comparable results were recently reported for two copies of an 8mer site with limited 3′ pairing capacity in a cell-based assay \[[@pbio-0030085-b34]\]. These results do not support a requirement for a central bulge, as suggested previously \[[@pbio-0030085-b29]\].

We took care in designing the miRNA 3′ ends to exclude any 3′ pairing to nearby sequence according to RNA secondary structure prediction. However, we cannot rule out the possibility that extensive looping of the UTR sequence might allow the 3′ end to pair to sequences further downstream in our reporter constructs. Note, however, that even if remote 3′ pairing was occurring and required for function of 8- and 7mer seeds, it is not sufficient for 5′ matches with less than seven complementary bases (all test sites are in the same sequence context; [Figure 2](#pbio-0030085-g002){ref-type="fig"}B). In addition, pairing at a random level will occur in any sequence if long enough loops are allowed. However, whether the ribonucleoprotein complexes involved in translational repression require 3′ pairing, and whether they are able to allow extensive looping to achieve this, remains an open question. Computationally, remote 3′ pairing cannot be distinguished from random matches if loops of any length are allowed. On this basis any site with a 7- or 8mer seed has to be taken seriously---especially when evolutionarily conserved.

From these experiments we conclude that (1) complementarity of seven or more bases to the 5′ end miRNA is sufficient to confer regulation, even if the target 3′ UTR contains only a single site; (2) sites with weaker 5′ complementarity require compensatory pairing to the 3′ end of the miRNA in order to confer regulation; and (3) extensive pairing to the 3′ end of the miRNA is not sufficient to confer regulation on its own without a minimal element of 5′ complementarity.

The Effect of G:U Base-Pairs and Bulges in the Seed {#s2b}
---------------------------------------------------

Several confirmed miRNA target genes contain predicted binding sites with seeds that are interrupted by G:U base-pairs or single nucleotide bulges \[[@pbio-0030085-b17],[@pbio-0030085-b19],[@pbio-0030085-b26],[@pbio-0030085-b36],[@pbio-0030085-b37],[@pbio-0030085-b38],[@pbio-0030085-b39]\]. In most cases these mRNAs contain multiple predicted target sites and the contributions of individual sites have not been tested. In vitro tests have shown that sites containing G:U base-pairs can function \[[@pbio-0030085-b29],[@pbio-0030085-b34]\], but that G:U base-pairs contribute less to target site function than would be expected from their contribution to the predicted base-pairing energy \[[@pbio-0030085-b34]\]. We tested the ability of single sites with seeds containing G:U base-pairs and bulges to function in vivo. One, two, or three G:U base-pairs were introduced into single target sites with 8mer, 7mer, or 6mer seeds ([Figure 3](#pbio-0030085-g003){ref-type="fig"}A). A single G:U base-pair caused a clear reduction in the efficiency of regulation by an 8mer seed site and by a 7mer seed site. The site with a 6mer seed lost its activity almost completely. Having more than one G:U base-pair compromised the activity of all the sites. As the target sites were designed to allow optimal 3′ pairing, we conclude that G:U base-pairs in the seed region are always detrimental.

![Effects of G:U Base-Pairs and Bulges\
(A) Regulation of sites with 8mer, 7mer, or 6mer seeds (rows) containing zero, one, two, or three G:U base-pairs in the seed region (columns).\
(B) Regulation of sites with bulges in the target sequence or in the miRNA.](pbio.0030085.g003){#pbio-0030085-g003}

Single nucleotide bulges in the seed are found in the *let-7* target *lin-41* and in the *lin-4* target *lin-14* \[[@pbio-0030085-b17],[@pbio-0030085-b36],[@pbio-0030085-b37]\]. Recent tissue culture experiments have led to the proposal that such bulges are tolerated if positioned symmetrically in the seed region \[[@pbio-0030085-b29]\]. We tested a series of sites with single nucleotide bulges in the target or the miRNA ([Figure 3](#pbio-0030085-g003){ref-type="fig"}B). Only some of these sites conferred good regulation of the reporter gene. Our results do not support the idea that such sites depend on a symmetrical arrangement of base-pairs flanking the bulge. We also note that the identity of the bulged nucleotide seems to matter. While it is clear that some target sites with one nucleotide bulge or a single mismatch can be functional if supported by extensive complementarity to the miRNA 3′ end, it is not possible to generalize about their potential function.

Functional Categories of Target Sites {#s2c}
-------------------------------------

While recognizing that there is a continuum of base-pairing quality between miRNAs and target sites, the experiments presented above suggest that sites that depend critically on pairing to the miRNA 5′ end (5′ dominant sites) can be distinguished from those that cannot function without strong pairing to the miRNA 3′ end (3′ compensatory sites). The 3′ compensatory group includes seed matches of four to six base-pairs and seeds of seven or eight bases that contain G:U base-pairs, single nucleotide bulges, or mismatches.

We consider it useful to distinguish two subgroups of 5′ dominant sites: those with good pairing to both 5′ and 3′ ends of the miRNA (canonical sites) and those with good 5′ pairing but with little or no 3′ pairing (seed sites). We consider seed sites to be those where there is no evidence for pairing of the miRNA 3′ end to nearby sequences that is better than would be expected at random. We cannot exclude the possibility that some sites that we identify as seed sites might be supported by additional long-range 3′ pairing. Computationally, this is always possible if long enough loops in the UTR sequence are allowed. Whether long loops are functional in vivo remains to be determined.

Canonical sites have strong seed matches supported by strong base-pairing to the 3′ end of the miRNA. Canonical sites can thus be seen as an extension of the seed type (with enhanced 3′ pairing in addition to a sufficient 5′ seed) or as an extension of the 3′compensatory type (with improved 5′ seed quality in addition to sufficient 3′ pairing). Individually, canonical sites are likely to be more effective than other site types because of their higher pairing energy, and may function in one copy. Due to their lower pairing energies, seed sites are expected to be more effective when present in more than one copy. [Figure 4](#pbio-0030085-g004){ref-type="fig"} presents examples of the different site types in biologically relevant miRNA targets and illustrates their evolutionary conservation in multiple drosophilid genomes.

![Three Classes of miRNA Target Sites\
Model of canonical (left), seed (middle) and 3′ compensatory (right) target sites. The upper diagram illustrates the mode of pairing between target site (upper line) and miRNA (lower line, color). Next down in each column are diagrams of the pattern of 3′ UTR conservation. The vertical black bars show stretches of at least six nucleotides that are conserved in several drosophilid genomes. Target sites for *miR-7, miR-4,* and *miR-10* are shown as colored horizontal bars beneath the UTR. Sites for other miRNAs are shown as black bars. Furthest down in each column the predicted structure of the duplex between the miRNA and its target site is shown; canonical base-pairs are marked with filled circles, G:U base-pairs with open circles. The sequence alignments show nucleotide conservation of these target sites in the different drosophilid species Nucleotides predicted to pair to the miRNA are shown in bold; nucleotides predicted to be unpaired are grey. Red asterisks indicate 100% sequence conservation; grey asterisks indicate conservation of base-pairing to the miRNA including G:U pairs. The additional sequence alignment for the *miR-10* target site in *Scr* in *Tribolium castanaeum, Anopheles gambiae,* and Bombyx mori strengthens this prediction. Note that the reduced quality of 3′ compensation in these species is compensated by the presence of a better quality 7mer seed. *A. ga, Anopheles gambiae; B. mo, B. mori; D. an, D. ananassae; D. me, D. melanogaster; D. ps, D. pseudoobscura; D. si, D. simulans; D. vi, D. virilis; D. ya, D. yakuba; T. ca, T. castanaeum.*](pbio.0030085.g004){#pbio-0030085-g004}

Most currently identified miRNA target sites are canonical. For example, the *hairy* 3′ UTR contains a single site for *miR-7,* with a 9mer seed and a stretch of 3′ complementarity. This site has been shown to be functional in vivo \[[@pbio-0030085-b26]\], and it is strikingly conserved in the seed match and in the extent of complementarity to the 3′ end of *miR-7* in all six orthologous 3′ UTRs.

Although seed sites have not been previously identified as functional miRNA target sites, there is some evidence that they exist in vivo. For example, the *Bearded (Brd)* 3′ UTR contains three sequence elements, known as Brd boxes, that are complementary to the 5′ region of *miR-4* and *miR-79* \[[@pbio-0030085-b32],[@pbio-0030085-b40]\]. Brd boxes have been shown to repress expression of a reporter gene in vivo, presumably via miRNAs, as expression of a *Brd* 3′ UTR reporter is elevated in *dicer-1* mutant cells, which are unable to produce any miRNAs \[[@pbio-0030085-b14]\]. All three Brd box target sites consist of 7mer seeds with little or no base-pairing to the 3′ end of either *miR-4* or *miR-79* (see below). The alignment of *Brd* 3′ UTRs shows that there is little conservation in the *miR-4* or *miR-79* target sites outside the seed sequence, nor is there conservation of pairing to either miRNA 3′ end. This suggests that the sequences that could pair to the 3′ end of the miRNAs are not important for regulation as they do not appear to be under selective pressure. This makes it unlikely that a yet unidentified Brd box miRNA could form a canonical site complex.

The 3′ UTR of the HOX gene *Sex combs reduced (Scr)* provides a good example of a 3′ compensatory site. *Scr* contains a single site for *miR-10* with a 5mer seed and a continuous 11-base-pair complementarity to the miRNA 3′ end \[[@pbio-0030085-b28]\]. The *miR-10* transcript is encoded within the same HOX cluster downstream of *Scr,* a situation that resembles the relationship between *miR-iab-5p* and *Ultrabithorax* in flies \[[@pbio-0030085-b26]\] and *miR-196*/*HoxB8* in mice \[[@pbio-0030085-b41]\]. The predicted pairing between *miR-10* and *Scr* is perfectly conserved in all six drosophilid genomes, with the only sequence differences occurring in the unpaired loop region. The site is also conserved in the 3′ UTR of the Scr genes in the mosquito, Anopheles gambiae, the flour beetle, Tribolium castaneum, and the silk moth,Bombyx mori. Conservation of such a high degree of 3′ complementarity over hundreds of millions of years of evolution suggests that this is likely to be a functional *miR-10* target site. Extensive 5′ and 3′ sequence conservation is also seen for other 3′ compensatory sites, e.g., the two *let-7* sites in *lin-41* or the *miR-2* sites in *grim* and *sickle* \[[@pbio-0030085-b17],[@pbio-0030085-b26],[@pbio-0030085-b36]\].

The miRNA 3′ End Determines Target Specificity within miRNA Families {#s2d}
--------------------------------------------------------------------

Several families of miRNAs have been identified whose members have common 5′ sequences but differ in their 3′ ends. In view of the evidence that 5′ ends of miRNA are functionally important \[[@pbio-0030085-b26],[@pbio-0030085-b27],[@pbio-0030085-b29],[@pbio-0030085-b42]\], and in some cases sufficient (present study), it can be expected that members of miRNA families may have redundant or partially redundant functions. According to our model, 5′ dominant canonical and seed sites should respond to all members of a given miRNA family, whereas 3′ compensatory sites should differ in their sensitivity to different miRNA family members depending on the degree of 3′ complementarity. We tested this using the wing disc assay with 3′ UTR reporter transgenes and overexpression constructs for various miRNA family members.

*miR-4* and *miR-79* share a common 5′ sequence that is complementary to a single 8mer seed site in the *bagpipe* 3′ UTR ([Figure 5](#pbio-0030085-g005){ref-type="fig"}A and [5](#pbio-0030085-g005){ref-type="fig"}B). The 3′ ends of the miRNAs differ. *miR-4* is predicted to have 3′ pairing at approximately 50% of the maximally possible level (−10.8 kcal/mol), whereas the level of 3′ pairing for *miR-79* is approximately 25% maximum (−6.1 kcal/mol), which is below the average level expected for random matches (see below). Both miRNAs repressed expression of the *bagpipe* 3′ UTR reporter, regardless of the 3′ complementarity ([Figure 5](#pbio-0030085-g005){ref-type="fig"}B). This indicates that both types of site are functional in vivo and suggests that *bagpipe* is a target for both miRNAs in this family.

![Target Specificity of miRNA Family Members\
(A) Diagrams of 3′ UTR conservation in six drosophilid genomes (horizontal black bars) and the location of predicted miRNA target sites. Above is the 3′ UTR of the myogenic transcription factor *bagpipe (bap)* showing the predicted target site for the Brd box miRNA family, *miR-4* and *miR-79* (black box below the UTR). Alignment of *miR-4* and *miR-79* illustrates that they share a similar seed sequence (except that *mir-4* has one extra 5′ base) but have little 3′ end similarity. Below are the conserved sequences in the3′ UTRs of the pro-apoptotic genes *grim* and *sickle.* Predicted target sites for the K Box miRNAs *miR-11, miR-2b,* and *miR-6* are shown below the UTR. Alignment of *miR-11, miR-2b,* and *miR-6* illustrates that they share the same family motif but have little similarity in their 3′ ends.\
(B) The *bagpipe (bap)* 3′ UTR reporter gene is regulated by *miR-4* and *miR-79.* Alignments of the two miRNAs to the predicted target site show good 8mer seed matches (left). Overexpression of *miR-4* or *miR-79* under ptcGal4 control downregulated the *bagpipe* 3′ UTR reporter (right).\
(C) Left: Alignment of K box miRNAs with the single predicted site in the *grim* 3′ UTR and regulation by overexpression of *miR-2* (top), but not by *miR-6* (middle) or *miR-11* (bottom). Right: Alignment of K box miRNAs with the two predicted sites in the *sickle* 3′ UTR. Regulation by overexpression of *miR-2* was strong (top), regulation by *miR-6* was weaker (middle), and *miR-11* had little effect (bottom).\
(D) Effect of clones of cells lacking *dicer-1* on expression of UTR reporters for predicted miRNA-regulated genes. Mutant cells were marked by the absence of β-Gal expression (red). EGFP expression is shown in green. Both channels are shown separately below in black and white. Mutant clones are indicated by yellow arrows. Expression of a uniformly transcribed reporter construct lacking miRNA target sites was unaffected in *dicer-1* mutant cells (first column). The UTR reporter for the *bantam* miRNA target *hid* was upregulated in the mutant cells (second column). The *bagpipe (bap)* UTR reporter was upregulated in *dicer-1* clones (third column). The *grim* (fourth column) and *sickle* (fifth column) UTR reporters were upregulated.](pbio.0030085.g005){#pbio-0030085-g005}

To test whether miRNA family members can also have non-overlapping targets, we used 3′ UTR reporters of the pro-apoptotic genes *grim* and *sickle,* two recently identified miRNA targets \[[@pbio-0030085-b26]\]. Both genes contain K boxes in their 3′ UTRs that are complementary to the 5′ ends of the *miR-2, miR-6,* and *miR-11* miRNA family \[[@pbio-0030085-b26],[@pbio-0030085-b32]\]. These miRNAs share residues 2--8 but differ considerably in their 3′ regions ([Figure 5](#pbio-0030085-g005){ref-type="fig"}A). The site in the *grim* 3′ UTR is predicted to form a 6mer seed match with all three miRNAs ([Figure 5](#pbio-0030085-g005){ref-type="fig"}C, left), but only *miR-2* shows the extensive 3′ complementarity that we predict would be needed for a 3′ compensatory site with a 6mer seed to function (−19.1 kcal/mol, 63% maximum 3′ pairing, versus −10.9 kcal/mol, 46% maximum, for *miR-11* and −8.7 kcal/mol, 37% maximum, for *miR-6*). Indeed, only *miR-2* was able to regulate the *grim* 3′ UTR reporter, whereas *miR-6* and *miR-11* were non-functional.

The *sickle* 3′ UTR contains two K boxes and provides an opportunity to test whether weak sites can function synergistically. The first site is similar to the *grim* 3′ UTR in that it contains a 6mer seed for all three miRNAs but extensive 3′ complementarity only to *miR-2*. The second site contains a 7mer seed for *miR-2* and *miR-6* but only a 6mer seed for *miR-11* ([Figure 5](#pbio-0030085-g005){ref-type="fig"}C, right). *miR-2* strongly downregulated the *sickle* reporter, *miR-6* had moderate activity (presumably via the 7mer seed site), and *miR-11* had nearly no activity, even though the miRNAs were overexpressed. The fact that a site is targeted by at least one miRNA argues that it is accessible (e.g., *miR-2* is able to regulate both UTR reporters), and that the absence of regulation for other family members is due to the duplex structure. These results are in line with what we would expect based on the predicted functionality of the individual sites, and indicate that our model of target site functionality can be extended to UTRs with multiple sites. Weak sites that do not function alone also do not function when they are combined.

To show that endogenous miRNA levels regulate all three 3′ UTR reporters, we compared EGFP expression in wild-type cells and *dicer-1* mutant cells, which are unable to produce miRNAs \[[@pbio-0030085-b14]\]. *dicer-1* clones did not affect a control reporter lacking miRNA binding sites, but showed elevated expression of a reporter containing the 3′ UTR of the previously identified *bantam* miRNA target *hid* ([Figure 5](#pbio-0030085-g005){ref-type="fig"}D). Similarly, all 3′ UTR reporters above were upregulated in *dicer-1* mutant cells, indicating that *bagpipe, sickle,* and *grim* are subject to repression by miRNAs expressed in the wing disc. Taken together, these experiments indicate that transcripts with 5′ dominant canonical and seed sites are likely to be regulated by all members of a miRNA family. However, transcripts with 3′ compensatory sites can discriminate between miRNA family members.

Genome-Wide Occurrence of Target Sites {#s2e}
--------------------------------------

Experimental tests such as those presented above and the observed evolutionary conservation suggest that all three types of target sites are likely to be used in vivo. To gain additional evidence we examined the occurrence of each site type in all Drosophila melanogaster 3′ UTRs. We made use of the D. pseudoobscura genome, the second assembled drosophilid genome, to determine the degree of site conservation for the three different site classes in an alignment of orthologous 3′ UTRs. From the 78 known *Drosophila* miRNAs, we selected a set of 49 miRNAs with non-redundant 5′ sequences. We first investigated whether sequences complementary to the miRNA 5′ ends were better conserved than would be expected for random sequences. For each miRNA, we constructed a cohort of ten randomly shuffled variants. To avoid a bias for the number of possible target matches, the shuffled variants were required to produce a number of sequence matches comparable (±15%) to the original miRNAs for D. melanogaster 3′ UTRs. 7mer and 8mer seeds complementary to real miRNA 5′ ends were significantly better conserved than those complementary to the shuffled variants. This is consistent with the findings of Lewis et al. \[[@pbio-0030085-b27]\] but was obtained without the need to use a rank and energy cutoff applied to the full-length miRNA target duplex, as was the case for vertebrate miRNAs. Conserved 8mer seeds for real miRNAs occur on average 2.8 times as often as seeds complementary to the shuffled miRNAs ([Figure 6](#pbio-0030085-g006){ref-type="fig"}A). For 7mer seeds this signal was 2:1, whereas 6mer, 5mer, and 4mer seeds did not show better conservation than expected for random sequences. To assess the validity of these signals and to control for the random shuffling of miRNAs, we repeated this procedure with "mutant" miRNAs in which two residues in the 5′ region were changed. There was no difference between the mutant test miRNAs and their shuffled variants ([Figure 6](#pbio-0030085-g006){ref-type="fig"}A). This indicates that a substantial fraction of the conserved 7mer and 8mer seeds complementary to real miRNAs identify biologically relevant target sites.

![Computational Analysis of Target Site Occurrence\
(A) Genome-wide occurrence of conserved 5′ seed matches. Histogram showing the ratio of 5′ seed matches for a set of 49 5′ non-redundant miRNAs and the average of their ten completely shuffled variants for different seed types (black bars). A ratio of one (red line) indicates no difference between the miRNA and its shuffled variants. The same ratio for mutated miRNAs and their shuffled variants shows no signal (white bars). The inset depicts shuffling of the entire miRNA sequence (wavy purple line).\
(B) Target site conservation between D. melanogaster and D. pseudoobscura. Histogram showing the average conservation of the 3′ UTR sequence (16 nt) upstream of a conserved 8mer seed match that would pair to the miRNA 3′ end. All sites were binned according to their conservation, and the percentage of sites in each bin is shown for sites identified by 49 5′ non-redundant miRNA sequences (grey) and their shuffled control sequences (black, error bars indicate one standard deviation).\
(C) 3′ pairing preferences for *miR-7* target sites. Histogram showing the distribution of 3′ pairing energies for *miR-7* (red bars) and the average of 50 3′ shuffled variants (black bars) for all sites identified genome-wide by 6mer 5′ seed matches for *miR-7.* The inset illustrates shuffling of the 3′ end of miRNA sequence only (wavy purple line). Because the miRNA 5′ end was not altered, the identical set of target sites was compared for pairing to the 3′ end of real and shuffled miRNAs.\
(D) 3′ pairing preferences for miRNA target sites. Histograms showing the ratio of the top 1% 3′ pairing energies for the set of 58 3′ non-redundant miRNAs and their shuffled variants. The y-axis shows the number of miRNAs for each ratio. Real miRNAs are shown in red; mutant miRNAs are shown in black. Left are shown combined 8- and 7mer seed sites. Right are shown combined 5- and 6mer seed sites. For combined 8- and 7mer seeds, 1% corresponds to approximately ten sites per miRNA; for combined 6- and 5mer, to approximately 25 sites. The difference between the real and mutated miRNAs improves if fewer sites per miRNA are considered.\
(E) Non-random signal of 3′ pairing. Plot of the ratio of the number of target sites for the set of 58 3′ non-redundant miRNAs and their shuffled miRNA 3′ ends (y-axis) with 3′ pairing energies that exceed a given pairing cutoff (x-axis). 100% is the pairing energy for a sequence perfectly complementary to the 3′ end. As the required level of 3′ pairing energy increases, fewer miRNAs and their sites remain to contribute to the signal. Plots for the real miRNAs extended to considerably higher 3′ pairing energies than the mutants, but as site number decreases we observe anomalous effects on the ratios, so the curves were cut off when the number of remaining miRNAs fell below five.](pbio.0030085.g006){#pbio-0030085-g006}

3′ compensatory and canonical sites depend on substantial pairing to the miRNA 3′ end. For these sites, we expect UTR sequences adjacent to miRNA 5′ seed matches to pair better to the miRNA 3′ end than to random sequences. However, unlike 5′ complementarity, 3′ base-pairing preference was not detected in previous studies looking at sequence complementarity and nucleotide conservation because UTR sequences complementary to the miRNA 3′ end were not better conserved than would be expected at random \[[@pbio-0030085-b27]\].

On this basis, we decided to treat the 5′ and 3′ ends of the miRNA separately. For the 5′ end, seed matches were required to be fully conserved in an alignment of orthologous D. melanogaster and D. pseudoobscura 3′ UTRs (we expected one-half to two-thirds of these matches to be real miRNA sites). We first investigated the overall conservation of UTR sequences adjacent to the conserved seed matches and found that overall the sequences are not better conserved than a random control with shuffled miRNAs ([Figure 6](#pbio-0030085-g006){ref-type="fig"}B). For both real and random matches, the number of sites increases with the degree of 3′ conservation (up to the 80% level), reflecting the increased probability that sequences adjacent to conserved seed matches will also lie in blocks of conserved sequence ([Figure 6](#pbio-0030085-g006){ref-type="fig"}B). For real 7mers and 8mers we found a slightly higher percentage of sites between 30% and 80% identity than we did for the shuffled controls. In contrast, the ratio of sites with over 80% sequence identity was smaller for real 7- or 8mers than for random ones, meaning that in highly conserved 3′ UTR blocks (\>80% identity) the ratio of random matches exceeds that of real miRNA target sites. This caused us to question whether the degree of conservation for sequences adjacent to seed matches correlates with miRNA 3′ pairing as would be expected if the conservation were due to a biologically relevant miRNA target site. Indeed, we found that the best conserved sites adjacent to seed matches (i.e., those with zero, one, or two mismatches in the 3′ UTR alignment) and the least conserved sites (i.e., those with only three, two, or one matching nucleotides) are not distinguishable in that both pair only randomly to the corresponding miRNA 3′ end (approximately 35% maximal 3′ pairing energy, data not shown). The observation that miRNA target sites do not seem to be fully conserved over their entire length is consistent with the examples shown in [Figure 4](#pbio-0030085-g004){ref-type="fig"} in which only the degree of 3′ pairing but not the nucleotide identity is conserved *(miR-7/hairy),* or at least the unpaired bulge is apparently not under evolutionary pressure *(miR-10/Scr).* Although this result obviously depends on the evolutionary distance of the species under consideration (see \[[@pbio-0030085-b43]\] for a comparison of mammalian sites), it shows that conclusions about the contribution of miRNA 3′ pairing to target site function cannot be drawn solely from the degree of sequence conservation.

We therefore chose to evaluate the quality of 3′ pairing by the stability of the predicted RNA--RNA duplex. We assessed predicted pairing energy between the miRNA 3′ end and the adjacent UTR sequence for both *Drosophila* species and used the lower score. Use of the lower score measures conservation of the overall degree of pairing without requiring sequence identity. [Figure 6](#pbio-0030085-g006){ref-type="fig"}C shows the distribution of the 3′ pairing energies for all conserved 3′ compensatory *miR-7* sites identified by a 6mer seed match, compared to the distribution of 50 *miR-7* sequences shuffled only in the 3′ part, leaving the 5′ unchanged. This means that real and shuffled miRNAs identify the same 5′ seed matches in the 3′ UTRs, which allows us to compare the 3′ pairing characteristics of the adjacent sequences. We also required 3′ shuffled sequences to have similar pairing energies (±15%) to their complementary sequences and to 10,000 randomly selected sites to exclude generally altered pairing characteristics. The distributions for real and shuffled miRNAs were highly similar, with a mean of approximately 35% of maximal 3′ pairing energy and few sites above 55%. However, a small number of sites paired exceptionally well to *miR-7* at energies that were far above the shuffled averages and not reached by any of the 50 shuffled controls. This example illustrates that there is a significant difference between real and shuffled miRNAs for the sites with the highest 3′ complementarity, which are likely to be biologically relevant. Sites with weaker 3′ pairing might also be functional, but cannot be distinguished from random matches and can only be validated by experiments (see [Figure 5](#pbio-0030085-g005){ref-type="fig"}). To provide a global analysis of 3′ pairing comprising all miRNAs and to investigate how many miRNAs show significantly non-random 3′ pairing, we considered only the sites within the highest 1% of 3′ pairing energies.

The average of the highest 1% of 3′ pairing energies of each of 58 3′ non-redundant miRNAs was divided by that of its 50 3′ shuffled controls. This ratio is one if the averages are the same, and increases if the real miRNA has better 3′ pairing than the shuffled miRNAs. To test whether a signal was specific for real miRNAs, we repeated the same protocol with a mutant version of each miRNA. The altered 5′ sequence in the mutant miRNA selects different seed matches than the real miRNA and permits a comparison of sequences that have not been under selection for complementarity to miRNA 3′ ends with those that may have been. [Figure 6](#pbio-0030085-g006){ref-type="fig"}D shows the distribution of the energy ratios for canonical (left) and 3′ compensatory sites (right) for all 58 real and mutated 3′ non-redundant miRNAs. Most real miRNAs had ratios close to one, comparable to the mutants. But several had ratios well above those observed for mutant miRNAs, indicating significant conserved 3′ pairing.

A small fraction of sites show exceptionally good 3′ pairing. If we use 3′ pairing energy cutoffs to examine site quality for all miRNAs, we expect sites of this type to be distinguishable from random matches. The ratio of the number of sites above the cutoff for real versus 3′ shuffled miRNAs was plotted as a function of the 3′ pairing cutoff ([Figure 6](#pbio-0030085-g006){ref-type="fig"}E). For low cutoffs the ratio is one, as the number of sites corresponds to the number of seed matches (which is identical for real and 3′ shuffled miRNAs). For increasing cutoffs, the ratios increase once a certain threshold is reached, reflecting overrepresentation of sites that pair favorably to the real miRNA 3′ end but not the 3′ shuffled miRNAs. The maximal ratio obtained for mutated miRNAs never exceeded five, which we used as the threshold level to define where significant overrepresentation begins. For 8mer seed sites overrepresentation began at 55% maximal 3′ pairing; for 7mer seed sites, at 65%; for 6mer seed sites, at 68%; and for 5mer seed sites, at 78%. There was no statistical evidence for sites with 4mer seeds.

We also tested whether sequences forming 7mer or 8mer seeds containing G:U base-pairs, mismatches, or bulges were better conserved if complementary to real miRNAs. We did not find any statistical evidence for these seed types. Analysis of 3′ pairing also failed to show any non-random signal for these sites. This suggests that such sites are few in number genome-wide and are not readily distinguished from random matches. Nonetheless, our experiments do show that sites of this type can function in vivo. The *let-7* sites in *lin-41* provide a natural example.

Most Sites Lack Substantial 3′ Pairing {#s2f}
--------------------------------------

The experimental and computational results presented above provide information about 5′ and 3′ pairing that allows us to estimate the number of target sites of each type in *Drosophila.* The number of 3′ compensatory sites cannot be estimated on the basis of 5′ pairing, because seed matches of four, five, or six bases cannot be distinguished from random matches, reflecting that a large number of randomly conserved and non-functional matches predominate ([Figure 6](#pbio-0030085-g006){ref-type="fig"}A). Significant 3′ pairing can be distinguished from random matches for 6mer sites above 68% maximal 3′ pairing energy, and above 78% for 5mers ([Figure 6](#pbio-0030085-g006){ref-type="fig"}E). Using these pairing levels gives an estimate of one 3′ compensatory site on average per miRNA. The experiments in [Figure 5](#pbio-0030085-g005){ref-type="fig"} provide an opportunity to assess the contribution of 3′ pairing to the ability of sites with 6mer seeds to function. The 6mer K box site in the *grim* 3′ UTR was regulated by *miR-2* (63% maximal 3′ pairing energy), but not by *miR-11,* which has a predicted 3′ pairing energy of 46%. Similarly, the 6mer seed sites for *miR-11* in the *sickle* 3′ UTR had 3′ pairing energies of approximately 35% and were non-functional. We can use the 63% and 46% levels to provide upper and lower estimates of one and 20 3′ compensatory 6mer sites on average per miRNA. For 5mer sites, the examples in [Figure 1](#pbio-0030085-g001){ref-type="fig"} show that sites with 76% and 83% maximal 3′ pairing do not function. At the 80% threshold level, we expect less than one additional site on average per miRNA, suggesting that 3′ compensatory sites with 5mer seeds are rare. The predicted *miR-10* site in *Scr* (see [Figure 4](#pbio-0030085-g004){ref-type="fig"}) is one of the few sites with a 5mer seed that reaches this threshold (100% maximum 3′ pairing energy; −20 kcal/mol). It is likely that other sites in this group will also prove to be functionally important.

The overrepresentation of conserved 5′ seed matches (see [Figure 6](#pbio-0030085-g006){ref-type="fig"}A) suggests that approximately two-thirds of sites with 8mer seeds and approximately one-half of the sites with 7mer seeds are biologically relevant. This corresponds to an average of 28 8mers and 53 7mers, for a total of 81 sites per miRNA. We define canonical sites as those with meaningful contributions from both 5′ and 3′ pairing. Given that 7- and 8mer seed matches can function without significant 3′ pairing, it is difficult to assess at what level 3′ pairing contributes meaningfully to their function. The range of 3′ pairing energies that were minimally sufficient to support a weak seed match was between 46% and 63% of maximum pairing energy (see [Figure 5](#pbio-0030085-g005){ref-type="fig"}C). If we take the 46% level as the lower limit for meaningful 3′ pairing, over 95% of sites would be considered seed sites. This changes to 99% for pairing energies that can be statistically distinguished from noise (55% maximal; see [Figure 6](#pbio-0030085-g006){ref-type="fig"}E) and remains over 50% even for pairing energies at the average level achieved by random matches (30% maximal). It is clear from this analysis that the majority of miRNA target sites lack substantial pairing in the 3′ end in nearby sequences. Indeed the 3′ pairing level for the three seed sites for *miR-4* in *Brd* are all less than 25% (i.e., below the average for random matches) and *Brd* was thus not predicted as a *miR-4* target previously \[[@pbio-0030085-b26],[@pbio-0030085-b28],[@pbio-0030085-b35]\].

Again, we note the caveat that some of sites that we identify as seed could in principle be supported by 3′ pairing to more distant upstream sequences, but also that such sites would be difficult to distinguish from background computationally and that it is unclear whether large loops are functional. If there were statistical evidence for 3′ pairing that is lower than would be expected at random for some sites, this would be one line of argument for a discrete functional class that does not use 3′ pairing and would therefore suggest selection against 3′ pairing. Although the overall distribution of 3′ pairing energies for real miRNA 3′ ends adjacent to 8mer seed matches is very similar to the random control with 3′ shuffled sequences ([Figure 7](#pbio-0030085-g007){ref-type="fig"}; *R* ^2^ = 0.98), we observed a small but significant overrepresentation of real sites on both sides of the random distribution, which leads to a slightly wider distribution of real sites at the expense of the peak values around 30% pairing. Bearing in mind that one-third of 8mer seed matches are false positives (see [Figure 6](#pbio-0030085-g006){ref-type="fig"}A), we can account for the noise by subtracting one-third of the random distribution. We then see two peaks at around 20% and 35% maximum pairing energy, separated by a dip. Subtracting more (e.g., one-half or two-thirds) of the random distribution increases the separation of the two peaks, suggesting that the underlying distribution of 3′ pairing for real 8mer seed sites might indeed be bimodal. This effect is still present, though less pronounced, if 7mer seed matches are included. No such effect is seen for the combined 5- and 6mer seed matches. In addition, we see no difference between a random (noise) model that evaluates 3′ pairing of 3′ shuffled miRNAs to UTR sites identified by real miRNA seed matches and a random model that pairs the real (i.e., non-shuffled) miRNA 3′ end to randomly chosen UTR sequences, thus excluding bias due to shuffling. Overall, these results suggest that there might indeed be a bimodal distribution due to an enrichment of sites with both better and worse 3′ pairing than would be expected at random. We take this as evidence that seed sites are a biologically meaningful subgroup within the 5′ dominant site category.

![Distribution of 3′ Pairing Energies for 8mer Seed Matches\
Shown is the distribution (number of sites versus 3′ pairing) for 8mer seed matches identified genome-wide for 58 3′ non-redundant miRNAs (black) compared to a random control using 50 3′ shuffled miRNAs per real miRNA (grey). Note that the distribution for real miRNAs is broader at both the high and low end than the random control and has shoulders close to the peak. The red, blue, and green curves show the effect of subtracting background noise (random matches) from the real matches at three different levels, which reveals the real matches underlying these shoulders.](pbio.0030085.g007){#pbio-0030085-g007}

Overall, these estimates suggest that there are over 80 5′ dominant sites and 20 or fewer 3′ compensatory sites per miRNA in the *Drosophila* genome. As estimates of the number of miRNAs in *Drosophila* range from 96 to 124 \[[@pbio-0030085-b44]\], this translates to 8,000--12,000 miRNA target sites genome-wide, which is close to the number of protein-coding genes. Even allowing for the fact that some genes have multiple miRNA target sites, these findings suggest that a large fraction of genes are regulated by miRNAs.

Discussion {#s3}
==========

We have provided experimental and computational evidence for different types of miRNA target sites. One key finding is that sites with as little as seven base-pairs of complementarity to the miRNA 5′ end are sufficient to confer regulation in vivo and are used in biologically relevant targets. Genome-wide, 5′ dominant sites occur 2- to 3-fold more often in conserved 3′ UTR sequences than would be expected at random. The majority of these sites have been overlooked by previous miRNA target prediction methods because their limited capacity to base-pair to the miRNA 3′ end cannot be distinguished from random noise. Such sites rank low in search methods designed to optimize overall pairing energy \[[@pbio-0030085-b16],[@pbio-0030085-b17],[@pbio-0030085-b26],[@pbio-0030085-b27],[@pbio-0030085-b28],[@pbio-0030085-b30],[@pbio-0030085-b35]\]. Indeed, we find that few seed sites scored high enough to be considered seriously in these earlier predictions, even when 5′ complementarity was given an additional weighting (e.g., \[[@pbio-0030085-b28],[@pbio-0030085-b43]\]. We thus suspect that methods with pairing cutoffs would exclude many, if not all, such sites.

In a scenario in which protein-coding genes acquire miRNA target sites in the course of evolution \[[@pbio-0030085-b04]\], it is likely that seed sites with only seven or eight bases complementary to a miRNA would be the first functional sites to be acquired. Once present, a site would be retained if it conferred an advantage, and sites with extended complementarity could also be selected to confer stronger repression. In this scenario, the number of sites might grow over the course of evolution so that ancient miRNAs would tend to have more targets than those more recently evolved. Likewise, genes that should not be repressed by the miRNA milieu in a given cell type would tend to avoid seed matches to miRNA 5′ ends ("anti-targets" \[[@pbio-0030085-b04]\]).

Although a 7- to 8mer seed is sufficient for a site to function, additional 3′ pairing increases miRNA functionality. The activity of a single 7mer canonical site is expected to be greater than an equivalent seed site. Likewise, the magnitude of miRNA-induced repression is reduced by introducing 3′ mismatches into a canonical site. Genome-wide, there are many sites that appear to show selection for conserved 3′ pairing and, interestingly, many sites that appear to show selection against 3′ pairing. In vivo, canonical sites might function at lower miRNA concentrations and might repress translation more effectively, particularly when multiple sites are present in one UTR (e.g., \[[@pbio-0030085-b42]\]). Efficient repression is likely to be necessary for genes whose expression would be detrimental, as illustrated by the genetically identified miRNAs, which produce clear mutant phenotypes when their targets are not normally repressed ("switch targets" \[[@pbio-0030085-b04]\]). Prolonged expression of the *lin-14* and *lin-41* genes in Caenorhabditis elegans mutant for *lin-4* or *let-7* causes developmental defects, and their regulation involves multiple sites \[[@pbio-0030085-b17],[@pbio-0030085-b36],[@pbio-0030085-b37]\]. Similarly, multiple target sites allow robust regulation of the pro-apoptotic gene *hid* by *bantam* miRNA in *Drosophila* \[[@pbio-0030085-b19]\]. More subtle modulation of expression levels could be accomplished by weaker sites, such as those lacking 3′ pairing. Sites that cannot function efficiently alone are in fact a prerequisite for combinatorial regulation by multiple miRNAs. Seed sites might thus be useful for situations in which the combined input of several miRNAs is used to regulate target expression. Depending on the nature of the target sites, any single miRNA might not have a strong effect on its own, while being required in the context of others.

3′ Complementarity Distinguishes miRNA Family Members {#s3a}
-----------------------------------------------------

3′ compensatory sites have weak 5′ pairing and need substantial 3′ pairing to function. We find genome-wide statistical support for 3′ compensatory sites with 5mer and 6mer seeds and show that they are used in vivo. Furthermore, these sites can be differentially regulated by different miRNA family members depending on the quality of their 3′ pairing (e.g., regulation of the pro-apoptotic genes *grim* and *sickle* by *miR-2, miR-6,* and *miR-11*). Thus, members of a miRNA family may have common targets as well as distinct targets. They may be functionally redundant in regulation of some targets but not others, and so we can expect some overlapping phenotypes as well as differences in their mutant phenotypes.

Following this reasoning, it is likely that the *let-7* miRNA family members differentially regulate *lin-41* in C. elegans \[[@pbio-0030085-b17],[@pbio-0030085-b45]\]. The seed matches in *lin-41* to *let-7* and the related miRNAs *miR-48, miR-84,* and *miR-241* are weak, and only *let-7* has strong 3′ pairing. On this basis, it seems likely that *lin-41* is regulated only by *let-7*. In contrast, *hbl-1* has four sites with strong seed matches \[[@pbio-0030085-b38],[@pbio-0030085-b39]\], and we expect it to be regulated by all four *let-7* family members. As all four *let-7*-related miRNAs are expressed similarly during development \[[@pbio-0030085-b06]\], their role as regulators of *hbl-1* may be redundant. *let-7* must also have targets not shared by the other family members, as its function is essential. *lin-41* is likely to be one such target.

The idea that the 3′ end of miRNAs serves as a specificity factor provides an attractive explanation for the observation that many miRNAs are conserved over their full length across species separated by several hundreds of millions of years of evolution. 3′ compensatory sites may have evolved from canonical sites by mutations that reduce the quality of the seed match. This could confer an advantage by allowing a site to become differentially regulated by miRNA family members. In addition, sites could retain specificity and overall pairing energy, but with reduced activity, perhaps permitting discrimination between high and low levels of miRNA expression. This might also allow a target gene to acquire a dependence on inputs from multiple miRNAs. These scenarios illustrate a few ways in which more complex regulatory roles for miRNAs might arise during evolution.

A Large Fraction of the Genome Is Regulated by miRNAs {#s3b}
-----------------------------------------------------

Another intriguing outcome of this study is evidence for a surprisingly large number of miRNA target sites genome-wide. Even our conservative estimate is far above the numbers of sites in recent predictions, e.g., seven or fewer per miRNA \[[@pbio-0030085-b27],[@pbio-0030085-b28],[@pbio-0030085-b29]\]. Our estimate of the total number of targets approaches the number of protein-coding genes, suggesting that regulation of gene expression by miRNAs plays a greater role in biology than previously anticipated. Indeed, Bartel and Chen \[[@pbio-0030085-b46]\] have suggested in a recent review that the earlier estimates were likely to be low, and a recent study by John et al. \[[@pbio-0030085-b43]\], published while this manuscript was under review, predicts that approximately 10% of human genes are regulated by miRNAs. We agree with these authors\' suggestion that this is likely an underestimate, because their method identifies an average of only 7.1 target genes per miRNA, with few that we would classify as seed sites lacking substantial 3′ pairing. A large number of target sites per miRNA is also consistent with combinatorial gene regulation by miRNAs, analogous to that by transcription factors, leading to cell-type-specific gene expression \[[@pbio-0030085-b47]\]. Sites for multiple miRNAs allow for the possibility of cell-type-specific miRNA combinations to confer robust and specific gene regulation.

Our results provide an improved understanding of some of the important parameters that define how miRNAs bind to their target genes. We anticipate that these will be of use in understanding known miRNA--target relationships and in improving methods to predict miRNA targets. We have limited our evaluation to target sites in 3′ UTRs. miRNAs directed at other types of targets or with dramatically different functions (e.g., in regulation of chromatin structure) might well use different rules. Accordingly, there may prove to be more targets than we can currently estimate. Further, there may be additional features, such as overall UTR context, that either enhance or limit the accessibility of predicted sites and hence their ability to function. For example, the rules about target site structure cannot explain the apparent requirement for the linker sequence observed in the *let-7/lin-41* regulation \[[@pbio-0030085-b48]\]. Further efforts toward experimental target site validation and systematic examination of UTR features can be expected to provide new insight into the function of miRNA target sites.

Materials and Methods {#s4}
=====================

 {#s4a}

### Fly strains {#s4a1}

ptcGal4; EP miR278 was provided by Aurelio Teleman. The control, *hid, grim,* and *sickle* 3′ UTR reporter transgenes, and UAS-*miR-2b* are described in \[[@pbio-0030085-b19],[@pbio-0030085-b26]\]. For UAS constructs for miRNA overexpression, genomic fragments including *miR-4* (together with *miR-286* and *miR-5*) and *miR-11* were amplified by PCR and cloned into UAS-DSred as described for UAS-*miR-7* \[[@pbio-0030085-b26]\]. Details are available on request. UAS-*miR-79* (also contains *miR-9b* and *miR-9c*) and UAS-*miR-6* (*miR-6--1, miR-6--2,* and *miR-6--3*) were kindly provided by Eric Lai. *dcr-1* ^Q1147X^ is described in \[[@pbio-0030085-b14]\].

### Clonal analysis {#s4a2}

Clones mutant for *dcr-1* ^Q1147X^ were induced in HS-Flp;dcr-1 FRT82/armadillo-lacZ FRT82 larvae by heat shock for 1 h at 38 °C at 50--60 h of development. Wandering third-instar larvae were dissected and labeled with rabbit anti-GFP (Torrey Pines Biolabs, Houston, Texas, United States; 1:400) and anti-β-Gal (rat polyclonal, 1:500).

### Reporter constructs {#s4a3}

The *bagpipe* 3′ UTR was PCR amplified from genomic DNA (using the following primers \[enzyme sites in lower case\]: AAtctaga AGGTTGGGAGTGACCATGTCTC and AActcgag TATTTAGCTCTCGGGTAGATACG) and cloned downstream of the tubulin promoter and EGFP (Clontech, Palo Alto, California, United States) in Casper4 as in \[[@pbio-0030085-b26]\].

### Single target site constructs {#s4a4}

Oligonucleotides containing the target site sequences shown in the figures were annealed and cloned downstream of tub\>EGFP and upstream of SV40polyA (XbaI/XhoI). Clones were verified by DNA sequencing. Details are available on request.

### EGFP intensity measurements {#s4a5}

NIH image 1.63 was used to quantify intensity levels in miRNA-expressing and non-expressing cells from confocal images. Depending on the variation, between three and five individual discs were analyzed.

### 3′ UTR alignments {#s4a6}

For each D. melanogaster gene, we identified the D. pseudoobscura ortholog using TBlastn as described in \[[@pbio-0030085-b26]\]. We then aligned the D. melanogaster 3′ UTR obtained from the Berkeley Drosophila Genome Project to the D. pseudoobscura 3′ adjacent sequence (Human Genome Sequencing Center at Baylor College of Medicine) using AVID \[[@pbio-0030085-b49]\]. For individual examples, we manually mapped the D. melanogaster coding region to genomic sequence traces (National Center for Biotechnology Information trace archive) of *D. ananassae, D. virilis, D. simulans,* and D. yakuba by TBlastn and extended the sequences by Blastn-walking. These 3′ UTR sequences were then aligned to the D. melanogaster and D. pseudoobscura 3′ UTRs using AVID.

### miRNA-sequences {#s4a7}

Drosophila miRNA sequences were from \[[@pbio-0030085-b44],[@pbio-0030085-b50],[@pbio-0030085-b51]\] downloaded from Rfam (<>). The 5′ non-redundant set (49 miRNAs) comprised *bantam, let-7, miR-1, miR-10, miR-11, miR-100, miR-124, miR-125, miR-12, miR-133, miR-13a, miR-14, miR-184, miR-210, miR-219, miR-263b, miR-275, miR-276b, miR-277, miR-278, miR-279, miR-281, miR-283, miR-285, miR-287, miR-288, miR-303, miR-304, miR-305, miR-307, miR-309, miR-310, miR-314, miR-315, miR-316, miR-317, miR-31a, miR-33, miR-34, miR-3, miR-4, miR-5, miR-79, miR-7, miR-87, miR-8, miR-92a, miR-9a,* and *miR-iab-4--5p.* Additional miRNAs in the 3′ non-redundant set were *miR-2b, miR-286, miR-306, miR-308, miR-311, miR-312, miR-313, miR-318,* and *miR-6.*

### miRNA shuffles and mutants {#s4a8}

For the completely shuffled miRNAs, we shuffled the miRNA sequence over the entire length and required all possible 8mer and 7mer seeds within the first nine bases to have an equal frequency (±15%) to the D. melanogaster 3′ UTRs (i.e., same single genome count). For the 3′ shuffled miRNAs, we shuffled the 3′ end starting at base 10 and required the shuffles to have equal (±15%) pairing energy to a perfect complement and to 10,000 randomly chosen sites. For each miRNA we created all possible 2-nt mutants (exchanging A to T or C, C to A or G, G to C or T, and T to A or G) within the seed (nucleotides 3--6) and chose the one with the closest alignment frequencies to the real miRNA in D. melanogaster 3′ UTRs and in the conserved sequences in D. melanogaster and D. pseudoobscura 3′ UTRs.

### Seed matching and site evaluation {#s4a9}

For each miRNA and seed type we found the 5′ match in the D. melanogaster 3′ UTRs and required it to be 100% conserved in an alignment to the D. pseudoobscura ortholog allowing for positional alignment errors of ±2 nt. When searching 7mer to 4mer seeds we masked all longer seeds to avoid identifying the same site more than once. For each matching site we extracted the 3′ adjacent sequence for both genomes, aligned it to the miRNA 3′ end starting at nucleotide 10 using RNAhybrid \[[@pbio-0030085-b35]\], and took the worse energy.

Supporting Information {#s5}
======================

Accession Numbers {#s5a}
-----------------

The miRNA sequences discussed in this paper can be found in the miRNA Registry (<>). NCBI RefSeq (<>) accession numbers: *bagpipe* (NM_169958), *Brd* (NM_057541), *grim* (NM_079413), *hairy* (NM_079253), *hid* (NM_079412), *lin-14* (NM_077516), *lin-41* (NM_060087), and *Scr* (NM_206443). GenBank (<>) accession numbers: *sickle* (AF460844) and *D. simulans hairy* (AY055843).

We thank Ann-Mari Voie for cheerfully producing the large number of transgenic strains used in this work. We are grateful to Marc Rehmsmeier for providing us with the RNAhybrid program prior to publication, to Eric Lai for providing unpublished fly strains, to Aurelio Teleman for comments on the manuscript, and to Lars Juhl Jensen for helpful discussions on the statistics.

**Competing interests.** The authors have declared that no competing interests exist.

**Author contributions.** JB, AS, and SMC conceived and designed the experiments. JB and AS performed the experiments and analyzed the data. JB, AS, RBR, and SMC wrote the paper.

Citation: Brennecke J, Stark A, Russell RB, Cohen SM (2005) Principles of microRNA--target recognition. PLoS Biol 3(3): e85.

*Brd*

:   *Bearded*

EGFP

:   enhanced green fluorescent protein

miRNA

:   microRNA

*Scr*

:   *Sex combs reduced*

```{=html}
<!-- -->
```

Academic Editor: James C. Carrington

:   Oregon State University


Compare the gene number of fruitfly (13,000) to human (20,000), and it\'s pretty clear that complexity emerges not just from gene number but from how those genes are regulated. In recent years, it\'s become increasingly clear that one class of molecules, called microRNAs (miRNAs), exert significant regulatory control over gene expression in most plant and animal species. A mere 22 nucleotides long, miRNAs control a cell\'s protein composition by preventing the translation of protein-coding messenger RNAs (mRNAs). When a miRNA pairs with an mRNA, through complementary base pairing between the molecules, the mRNA is either destroyed or is not translated.

Hundreds of miRNAs have been found in animals, but functions for just a few have been identified, mostly through genetic studies. Many more functions could be assigned if miRNA targets could be predicted. This approach has worked in plants, because miRNAs and their targets pair through the near perfect complementarity of their base pairs. But the molecules follow different rules in animals---duplexes contain just short stretches of complementary sequence interrupted by gaps and mismatches---which makes predicting miRNA targets a challenge.

In a new study, Stephen Cohen and his colleagues at the European Molecular Biological Laboratory in Germany establish basic ground rules for miRNA--mRNA pairing using a combination of genetics and computational analyses, and identify different classes of miRNA targets with distinct functional properties. Although the miRNA is only 22 nucleotides long, its 5′ and 3′ ends seem to have distinct roles in binding. Cohen and colleagues show that miRNA functional targets can be divided into two broad categories: those that depend primarily on pairing to the miRNA\'s 5′ end (called 5′ dominant sites), with varying degrees of 3′ pairing, and those that also need the miRNA\'s 3′ end (called 3′ compensatory sites). Surprisingly, miRNAs can regulate their targets simply by strong pairing with so-called seed sites that consist of just seven or eight bases complementary to the miRNA 5′ end. Target sites with weaker 5′ complementarity need supplemental pairing with the miRNA\'s 3′ end to function. The finding that so little sequence complementarity is needed means that there are many more target sites than had been previously recognized.

The miRNA 3′ end, while not essential, is expected to confer some function, since it tends to be conserved in animals---miRNA 3′ ends provide an additional measure of regulatory control by permitting the function of target sites that have only limited complementarity to the miRNA 5′ end. The authors speculate that seed sites might be the first functional sites acquired by protein-coding genes that require repression, and that additional sites might be acquired to promote stronger repression.

Based on their experimental results, Cohen and colleagues searched the Drosophila genome for biologically relevant targets, and estimate that the fly has about 100 sites for every miRNA in its genome. Since the fruitfly has anywhere from 96 to 124 miRNAs, that means it has 8,000 to 12,000 target sites (in the 11,000 genes sampled). This indicates that miRNAs regulate a large fraction of protein-coding genes. Of the known animal miRNAs, many regulate critical developmental processes. This new approach to predicting targets should help reveal just how much regulatory control actually flows from these tiny bits of RNA.


For Proust, a taste of cookie was enough to trigger vivid recollections of his childhood, the first of a long string of reveries that he fashioned into his famous memoir *Remembrance of Things Past*. For many animals, too, tastes and smells are evocative and play a crucial role in finding food, allowing them to build on past successes and to learn how to find their next meal.

To locate blooming flowers, for example, honeybees rely heavily on scent. They can associate a whiff of an aldehyde, say, with a nectar-filled orchid. Then later they\'ll seek out the same or similar scents. To succeed in the wild, they must be able to distinguish relevant scents at varying concentrations, and within complex milieus of other scents. But to find food in varied conditions and adapt to new situations, they also have to generalize from past experience.

Through both physiological and behavioral studies, scientists have investigated the response to smell in a wide range of organisms and have suggested that two key properties of scent-inducing chemicals are the functional class, such as alcohol or aldehyde, and the carbon-chain length. Bees trained to associate a particular chemical with a reward, for example, can then generalize to some extent to other chemicals with the same functional groups or similar carbon-chain lengths. In these situations, bees are surprisingly consistent in both in their behavior (extending their proboscis to an odor previously associated with food) and in their brains (brain activity in smell-processing centers). Each set of data, behavioral and neural, can be thought of as a "code" underlying the bee\'s response: present a scent, and a bee\'s brain and body will tend to react in a certain way.[](#pbio-0030122-g001){ref-type="fig"}

![Linking smellperception and neural activity in the bee (Image: Axel Brockmann)](pbio.0030122.g001){#pbio-0030122-g001}

A new study of smell perception in honeybees (Apis mellifera) published in *PLoS Biology* gives a more comprehensive picture of how bees react to a suite of scents and also shows a remarkable correspondence between the codes for the insects\' behavior and brain activity. The researchers, led by Martin Giurfa, first trained bees to associate a specific chemical, such as the alcohol 1-nonanol, with a sucrose reward. Then the researchers tested the bees\' response to a set of other chemicals, varying in carbon-chain length from six to nine, and with four different functional groups: aldehydes, ketones, and primary and secondary alcohols.

By watching how often the bees generalized---that is, how often they responded positively to a particular scent when they\'d been trained on another---the researchers could assign perceptual "distances" between pairs of chemicals. Drawing together all these distances, they created a preliminary map of the bees\' "perceptual space," similar to how surveyors measure distances between landmarks to map a landscape. From this comparison they found, for example, that the bees generalized more by functional group than by carbon-chain length.

Previously, Giovanni Galizia\'s group, which works closely with Giurfa\'s group, had recorded bees\' brain responses to the same pairs of scents, assigning distances within centers of activity for each scent. Giurfa\'s team compared these two sets of data and found that the perceptual and neural distances correlated well, which suggests there\'s a species-specific code that ties together the insects\' brain and behavior.

The brain recordings covered only a quarter of the bees\' main smell-processing center, the antennal lobe. Future studies with new methods of microscopy that visualize more of the brain and which focus on the olfactory message sent by the antennal lobe to higher-order brain centers should only improve our ability to investigate the correlations between brain and behavior, the authors say. Such studies would go even further toward cracking the codes underlying animals\' perception and memory.


Introduction {#s1}
============

Sex differences in recombination were discovered in the first linkage studies on *Drosophila* \[[@pbio-0030063-b01],[@pbio-0030063-b02]\] and *Bombyx* (Tanaka \[1914\] in \[[@pbio-0030063-b03]\]) almost one century ago. However, this observation remains today largely unexplained despite several attempts. Based on very limited observations (see [Table 1](#pbio-0030063-t001){ref-type="table"}), especially of *Bombyx,* in which the female is heterogametic, Haldane \[[@pbio-0030063-b03]\] suggested, as far as "these facts are anything more than a coincidence," that the lower autosomal recombination rate in the heterogametic sex may reflect a pleiotropic consequence of selection against recombination between the sex chromosomes. Later, Huxley \[[@pbio-0030063-b04]\] showed that *Gammarus* males also recombined less than females. He gave the same evolutionary explanation, although he restricted it to cases of a marked sex difference.

::: {#pbio-0030063-t001 .table-wrap}
::: {.caption}
###### Data on Which the Haldane-Huxley Rule is Based
:::

![](pbio.0030063.t001)

Listed are the data available to Haldane \[[@pbio-0030063-b04]\] when he proposed the Haldane-Huxley rule

^a^  *r~m~* represents recombination in males

^b^  *r~f~* represents recombination in females

^c^ Plus and minus symbols indicate the direction of heterochiasmy, and zero indicates achiasmy
:::

This conjecture has now been confirmed for achiasmate species (i.e., species in which only one sex recombines) and is referred to as Haldane-Huxley rule: Nei \[[@pbio-0030063-b05]\] showed theoretically that tight linkage should evolve on Y or W chromosomes, and Bell \[[@pbio-0030063-b06]\] compiled a large dataset showing that achiasmy evolved 29--34 times independently, each time with no recombination in the heterogametic sex.

However, for heterochiasmate species, three problems with the Haldane-Huxley pleiotropy explanation were discovered \[[@pbio-0030063-b07],[@pbio-0030063-b08]\]. The first problem arose when substantial variation in male-female differences in recombination rate was found between pairs of autosomes within mice \[[@pbio-0030063-b08]\] and *Tribolium* \[[@pbio-0030063-b09],[@pbio-0030063-b10]\], and between genotypes for the same pair of autosomes \[[@pbio-0030063-b11]\]. The second problem was the discovery that hermaphrodite species (the platyhelminth *Dendrocoelum* \[[@pbio-0030063-b12]\] and the plant *Allium* \[[@pbio-0030063-b13]\]) may present strong heterochiasmy between male and female meiosis despite having no sex chromosomes or even sex-determining loci. The third problem was the discovery of species in which the heterogametic sex recombines more than the homogametic one (e.g., in some *Triturus* species) \[[@pbio-0030063-b14]\]. Because of these contradictory observations, variation in heterochiasmy has remained difficult to explain because of the absence of an alternative theory as well as the lack of a clear pattern in the data.

In 1969, Nei \[[@pbio-0030063-b05]\] worked out the first "modifier" model to study the evolution of sex differences in recombination, and concluded for autosomes that "the evolutionary mechanism of these sex differences is not known at present." Surveying an updated dataset, Bell \[[@pbio-0030063-b06]\] concluded that "female gametes experience more crossing over among hermaphroditic plants (and perhaps animals), but this is not invariably the case among gonochoric animals (...) certainly (this) has never received any explanation." The idea that heterochiasmy may be explained by a sex rather than by a sex chromosome effect, which was ignored by Haldane because of *Bombyx,* was reconsidered. This led Trivers \[[@pbio-0030063-b15]\] to suggest that, because only males with very good gene combinations reproduce (relative to females, for whom reproduction success is often less variable), they should recombine less to keep intact these combinations. He accounted for exceptions by variation in the regime of sexual selection. The idea was criticized by Burt et al. \[[@pbio-0030063-b16]\], who also questioned the correlations---with an updated dataset---between heterochiasmy and either sex or heterogamety. These authors tried to correlate the level of heterochiasmy with the amount of "opportunity for sex-specific selection," but failed to find an effect. They were tempted to advocate neutrality, but were puzzled by the positive correlation between male and female recombination rate and by evidence showing compensation (e.g., female mice tend to recombine more on the X, as if they were compensating for no recombination in males; similarly, no species is known with achiasmy in both sexes \[[@pbio-0030063-b16]\]). In 1994, Korol et al. \[[@pbio-0030063-b17]\] insisted on a possible role for gametic selection but did not give evidence in favour of this claim. Recently, Lenormand \[[@pbio-0030063-b18]\], using Nei\'s modifier approach, showed that it is very difficult to explain heterochiasmy by sex-specific diploid selection. Rather, a sex difference in selection during haploid phase, or a sex difference in diploid selection on imprinted genes, is a more likely explanation. He predicted that, as far as haploid selection is concerned, the sex experiencing the more intense haploid selection should recombine less. Indeed, when allelic effects interact to determine fitness (i.e., when there is "epistasis," either negative or positive), recombining decreases mean fitness in the population of the next generation \[[@pbio-0030063-b19]\]. This effect occurs because recombination breaks up combinations of genes that have previously been built up by selection. For a given average recombination rate between sexes and for a given average epistasis between male and female haploids, it is always advantageous for the haploid population (male or female) with the greatest absolute value in epistasis to be produced with the lowest amount of recombination. In this way, the "recombination load" that the haploid population is exposed to is minimized.

In this paper, we would like to come up with a more quantitative evaluation of the possible role of haploid selection in shaping heterochiasmy. For that purpose, we first updated the dataset of Burt et al. \[[@pbio-0030063-b16]\] on heterochiasmy, focusing on genetic maps that have become available over the last 15 years. We then determined how fast heterochiasmy evolves, in order to measure the amount of phylogenetic inertia on this trait. Finally, we determined whether variables such as gender, heterogamety, or the opportunity for selection in the haploid phase, could explain variation in heterochiasmy. If there is selection with substantial epistasis on some genes during the haploid phase, we expect the sex with the greater opportunity for haploid selection to show less recombination. Alternatively, if selection during the haploid phase is weak or without substantial epistasis, we do not expect it to produce a directional bias in the amount of recombination displayed by either sex.

Results/Discussion {#s2}
==================

Sex Chromosomes {#s2a}
---------------

Heterochiasmy is a fast-evolving trait, and phylogenetic inertia does not satisfactorily explain its distribution. In contrast to achiasmy, we found that heterochiasmy is not influenced by the nature of the sex chromosomes. This is interesting, because it suggests that achiasmy and heterochiasmy are influenced by qualitatively different evolutionary forces, although they seem to differ only quantitatively. It would be useful to determine whether achiasmy evolved to reduce the average recombination rate or to change the relative amount of recombination between the sexes. The two situations may be discriminated by determining whether the homogametic sex in achiasmate species tends to recombine more than in closely related chiasmate species. Evidence for such compensation would indicate that achiasmy did not evolve to reduce the average recombination rate. In the absence of such compensation, however, achiasmy may simply reflect selection for tight linkage. In such a situation, we propose that Haldane-Huxley rule may be caused by the converse argument to the one previously considered: The presence of achiasmy only in the heterogametic sex may reflect selection to maintain nonzero recombination rate on X or Z chromosomes in the homogametic sex. In species in which the average autosomal recombination rate is selected against (i.e., towards a lower equilibrium value), loss-of-function (recombination) mutations with an effect restricted to one sex may spread only if they affect the heterogametic sex, because mutations suppressing recombination in the homogametic sex completely suppress recombination on the X or Z chromosome. The same argument applies to XO species and may explain why achiasmy is associated only with the heterogametic sex. In addition, this hypothesis does not require the existence of genes suppressing recombination between the sex chromosomes with autosomal pleiotropic effects. Under this hypothesis, there is no reason to find an effect of the presence of heteromorphic sex chromosome on the amount of heterochiasmy, as originally envisioned by Haldane and Huxley. Overall, this hypothesis would explain why heterochiasmy and achiasmy differ qualitatively and why we do not observe any effect of sex chromosomes on heterochiasmy.

Heterochiasmy in Animals {#s2b}
------------------------

In animals, male-female dimorphism in haploid selection may also contribute to heterochiasmy. In general, there is no female haploid phase in animals, because meiosis is completed only at fertilisation. As far as at least some genes are expressed and under selection during the male haploid phase, this would tend to bias towards tighter linkage in males. Sets of genes responsible for male-specific meiotic drive systems would be good candidates and are often found in tight linkage. Measuring the opportunity for haploid selection in animals may be possible within some groups. Imprinting may, however, act as a confounding effect in many groups of animals while trying to measure the opportunity for "haploid" selection. Within-species comparisons of imprinted regions or of regions with sex-specific recombination using high-resolution maps \[[@pbio-0030063-b20]\] may be more fruitful to discriminate among potential causes of heterochiasmy in animals. In particular, there is evidence in humans that the reduction in crossing-over associated with imprinting is in the direction that theory predicts, even if this pattern is consistent with other explanations \[[@pbio-0030063-b21]\]. Finally, understanding exceptions within groups (e.g., male marsupials, contrarily to most mammals, recombine more than females of the species \[[@pbio-0030063-b22]\]) may also shed light on the different hypotheses.

Heterochiasmy in Plants {#s2c}
-----------------------

We found that plant heterochiasmy is correlated with the opportunity for male and female haploid selection. Female meiosis tends to exhibit lower recombination rates relative to male meiosis when selection is intense among female gametophytes (e.g., in Pinaceae) or mild among male gametophytes (e.g., in highly selfing species). This pattern is expected if heterochiasmy is determined by the relative magnitude of haploid selection in male and female individuals. Finding a pattern consistent with this general population genetic prediction is, of course, not firm evidence that male-female dimorphism in haploid selection is the evolutionary force generating heterochiasmy. Other correlates of selfing rates might have to be closely examined \[[@pbio-0030063-b23]\]. However, we consider this explanation the most parsimonious so far. Our finding provides, therefore, the first empirical evidence for a theory explaining male-female differences in the amount of recombination and contributes to our understanding of contradictory observations that have puzzled geneticists for almost a century. It also indicates that the amount of recombination may be shaped by indirect selection, and, therefore, corroborates theories based on selection and variation for the evolution of sexual reproduction.

Materials and Methods {#s3}
=====================

 {#s3a}

### An extended dataset {#s3a1}

We measured heterochiasmy as the log of the male/-to-female ratio (*ρ*) of autosomal recombination rate measured either with chiasma number or map length. We log-transformed the ratio to avoid bias due to measurement error in the denominator. Chiasma-count data for different species were compiled by Burt et al. \[[@pbio-0030063-b16]\], and we used their dataset, adding a few recent studies. We compiled genetic map data and linkage studies in animals and plants for which both a male and a female map were available. Only homologous fragments (i.e., between shared markers) in male and female maps were considered (especially in low-resolution maps). Heterochiasmy data were available for 107 species, with 46 sets of data based on genomic maps ([Table 2](#pbio-0030063-t201){ref-type="table"}).

::: {#pbio-0030063-t201 .table-wrap}
::: {.caption}
###### Dataset Pooled by Species with Levels of Phylogenetic Grouping Used in the Analysis
:::

![](pbio.0030063.t201)

Note that references given in Burt et al. \[[@pbio-0030063-b17]\] were not repeated here

^a^ K, kingdom. Numeric indicators in this column are: 1, Animalia; 2, Plantae

^b^ P, phylum. Numeric indicators in this column are: 1, Arthropoda; 2, Chordata; 3, Embryophyta; 4, Platyhelminthes

^c^ C, class. Numeric indicators in this column are: 1, Actinopterygii; 2, Amphibia; 3, Magnoliopsidae (subclass asterids); 4, Aves; 5, Coniferopsida; 6, Insecta; 7, Liliopsida; 8, Mammalia; 9, Magnoliopsidae (subclass rosids); 10, Trematoda; 11, Turbellaria

^d^ Data refers to linkage map (LM) or chiasma count (CC)

^e^ Male and female indicate the value for the chiasma count or map length for each sex

^f^ Ratio refers to male/female recombination rate

^g^  *V~sc~* refers to the presence or absence of sex chromosome (see [Materials and Methods](#s3){ref-type="sec"}, "Sex chromosome effect")

^h^ Data were obtained from maps DBNordic2 and NIAIJapan (<>) \[[@pbio-0030063-b54],[@pbio-0030063-b55]\]

ND, no data
:::

::: {#pbio-0030063-t202 .table-wrap}
::: {.caption}
###### Continued
:::

![](pbio.0030063.t202)
:::

### Phylogenetic inertia {#s3a2}

Heterochiasmy may evolve so slowly that there is important phylogenetic inertia. Alternatively, it may be so fast-evolving that the amount of heterochiasmy takes on nearly independent values among related species. In the same way, heterochiasmy may be so variable between genotypes within a species that it may be difficult to measure and irrelevant to analyse species specific effects. In order to get a picture of phylogenetic inertia on heterochiasmy, we estimated the phylogenetic autocorrelation of *ρ* using Moran\'s *I* spatial autocorrelation statistic \[[@pbio-0030063-b24]\]. When standardized, values of Moran\'s *I* vary from −1 to 1. Positive values indicate that heterochiasmy is more similar than random within a taxonomic level, whereas negative values indicate that it is more different. Because a few species had multiple estimates of heterochiasmy, we also estimated the within-species correlation. The resulting correlogram is shown in [Figure 1](#pbio-0030063-g001){ref-type="fig"}. We found that heterochiasmy is a fast-evolving trait: Genotypes tend to be correlated within a species (I/I~max~ = 0.38, *p* = 7.9%), but this correlation is lower among species within genera (I/I~max~ = 0.18, P-value = 13%), and very low when comparing genera within families (I/I~max~ = 0.039, *p* = 63%). This pattern is very different from the one observed for highly autocorrelated traits using the same method (for instance, mammalian body size \[[@pbio-0030063-b25]\]). This analysis indicates that there is very little phylogenetic inertia overall on heterochiasmy, but that the species level is appropriate for our dataset. However, this low level of inertia may nevertheless inflate type-I error while testing the effect of independent variables on heterochiasmy. In order to avoid this problem, we tested the association between different variables and heterochiasmy using a generalized estimating equations linear model correcting for the full phylogeny (see below) \[[@pbio-0030063-b26]\].

![Phylogenetic Correlogram of Heterochiasmy and Selfing Rate\
The y-axis represents Moran\'s *I* rescaled to enable comparisons between each taxonomic level for heterochiasmy (*ρ*, solid line) and selfing rate (*V~m~*, dashed line). The x-axis represents the taxonomic level: /S is the correlation within species, S/G is the correlation of species within genera, etc. F, family; O, order; C, class; P, phylum; K, kingdom. Filled points indicate significance at *p* = 0.05.](pbio.0030063.g001){#pbio-0030063-g001}

### Sex chromosome effect {#s3a3}

For each species, we reported the presence of sex chromosomes. We defined the variable *V~sc~* with the following values: −1 for XY/XX species, −1/2 for XO/XX or XY/XX without pseudoautosomal regions (marsupials), 0 for species without sex-chromosomes, and +1 for ZZ/ZW species. We distinguished the −1 and −1/2 cases to reflect the fact that, in the latter, recombination does not occur between sex chromosomes, so we expect a lower current selection pressure to suppress recombination. Under the Haldane-Huxley hypothesis, the presence of sex chromosomes is supposed to favour reduced recombination rate in the heterogametic sex. We therefore expect a positive effect of the variable *V~sc~* on *ρ*. We did not find such an effect in animals or plants (the linear effect of *V~sc~* on *ρ* is not significantly different from zero \[*p* = 0.75 in animals and *p* = 0.52 in plants\], assuming species were independent), and this result is unchanged if the −1 and −1/2 cases are not distinguished. Given this negative result, there was no need to do a phylogenetic correction.

### Gametic selection {#s3a4}

In animals from our dataset, there is no female haploid phase because the completion of meiosis occurs only at fertilisation (sperm triggers the end of meiosis). In male gametes, very few genes are expressed, and sperm phenotype is determined mostly either by the diploid genotype of the paternal tissue or by its mitochondrial genome. Imprinted genes, which can also affect the evolution of heterochiasmy \[[@pbio-0030063-b18],[@pbio-0030063-b21]\], may be as numerous as haploid-expressed genes and act as a confounding factor while evaluating the "opportunity" for male or female gametic selection. As a consequence, we did not attempt to evaluate the opportunity for haploid selection in animals. Rather, we focused on plants, in which there is both a male (pollen) and female (ovule) haploid phase and during which many genes are expressed (e.g., as many as 60% of genes may be expressed in the male gametophyte \[[@pbio-0030063-b27],[@pbio-0030063-b28]\]).

In order to evaluate the effect of the "opportunity for selection" for male haploid phase on *ρ,* we used selfing rate as an indirect variable estimating the degree of pollen competition. We assume that with high selfing rates, there is less genetic variation among competing pollen grains and, therefore, less scope for haploid selection. We defined *V~m~* (the degree of male gamete competition in plants) using three values depending on the amount of selfing: 0 for dioecious, self-incompatible or largely outcrossing (less than 5% selfing reported) species; 1 for species exhibiting low selfing rates (less than 30% reported); and 2 for other species. We used these three broad categories to reflect the fact that selfing rate is often variable within species and that it is often measured indirectly and with low precision. We therefore expect a positive effect of the variable *V~m~* on *ρ* if the opportunity for male gametic selection favours smaller *ρ* values, as predicted by the modifier model \[[@pbio-0030063-b18]\]. We tested this effect using the 57 species for which we were able to estimate *V~m~* ([Table 3](#pbio-0030063-t003){ref-type="table"}). We used a linear model in R \[[@pbio-0030063-b29]\] assuming that all species are either independent or phylogenetically related. In the latter case, we used a generalized estimating equations linear model \[[@pbio-0030063-b26]\] with a plant phylogenetic tree to the family level using data from Davies et al. \[[@pbio-0030063-b30]\], and several calibration points, including the *Picea*/*Pinus* divergence approximately 140 million years ago \[[@pbio-0030063-b31]\], that are not included in the Davies et al. dataset. We found an effect in the right direction with or without correcting for the phylogeny (linear effect of *ρ* on *V~m~*, *p* \< 0.0002 in both cases, [Figure 2](#pbio-0030063-g002){ref-type="fig"}). The fact that selfing plants exhibit higher recombination rates than their outcrossing relatives has been mentioned previously in the literature \[[@pbio-0030063-b32],[@pbio-0030063-b33]\]. However, in most cases, recombination was measured only in male meiosis. It would be valuable to reexamine this trend in the light of our results that recombination in male meiosis is typically greater than in female meiosis among selfers.

![Logarithm of Male-Female Ratio in Recombination Rate in Plants\
Mean and 95% confidence interval of *ρ* is shown for different groups of plants, assuming normality and independent data points The number of species in each group is indicated next to the mean.](pbio.0030063.g002){#pbio-0030063-g002}

::: {#pbio-0030063-t003 .table-wrap}
::: {.caption}
###### Plant Species Used to Test the Effect of Male and Female Opportunity for Selection
:::

![](pbio.0030063.t003)

^a^ Ratio refers to male-to-female recombination rate

LM, linkage map; CC, chiasma count; *n,* haploid number of chromosomes; *V~m~*, measure of male opportunity for haploid selection; *V~f~*, measure of female opportunity for haploid selection
:::

In order to evaluate the effect of the "opportunity for selection" during the female haploid phase on *ρ* in plants, we contrasted angiosperms with gymnosperms. In angiosperms, ovules do not compete much with each other on a mother plant, because resource accumulation starts after fertilisation (i.e., during fruit development in the diploid phase). In *Pinus* (three species in our dataset; see [Table 2](#pbio-0030063-t201){ref-type="table"}), male meiosis, female meiosis, and pollination occur in the year prior to fertilisation, but the pollen tube stops growing until the next spring, while the female gametophytes continue to accumulate resources and compete with each other over the course of the year. The same situation occurs in *Picea,* although the period between female meiosis and fertilisation is only 2--3 mo \[[@pbio-0030063-b34]\]. Perhaps more importantly, the endosperm (which is the organ managing resources for the zygote) is haploid in Pinaceae, in contrast to the double fertilisation that occurs in angiosperms to produce at least a diploid (typically triploid) endosperm \[[@pbio-0030063-b35],[@pbio-0030063-b36]\]. We therefore expect that *ρ* should be greater in Pinaceae, compared to angiosperms. We assigned *V~f~* (the degree of female gamete competition in plants) the values 1 for gymnosperms and −1 for angiosperms. We expected a positive effect of the variable *V~f~* on *ρ* according to the modifier model. An effect in the right direction was indeed detected (linear effect of *V~f~* on *ρ, p* = 0.011 and *p* = 0.0001, with and without correcting for the phylogeny as above, respectively; see [Figure 2](#pbio-0030063-g002){ref-type="fig"}).

We thank G. Besnard, J. Britton-Davidian, J.-B. Ferdy, S. Glémin, L. D. Hurst, P. Jarne, O. Judson, M. Kirkpatrick, S. P. Otto, J.-M. Prosperi, and C. Vosa for helpful comments, information, and stimulating discussions. This study was supported by the Centre National de la Recherche Scientifique and French Ministry of Research.

**Competing interests.** The authors have declared that no competing interests exist.

**Author contributions.** TL and JD conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, and wrote the paper.

Citation: Lenormand T, Dutheil J (2005) Recombination difference between sexes: A role for haploid selection. PLoS Biol 3(3): e63.