Two levels of interference in mouse meiotic recombination

Abstract

Meiosis consists of two divisions, meiosis I and II, by which a diploid cell produces four haploid daughters. Reduction in ploidy occurs at meiosis I, when homologous chromosomes (homologs) disjoin. This event is prepared during meiotic prophase, when homologs recognize each other and form stable pairs (bivalents) that can line up in the metaphase I spindle. In most eukaryotes, including mouse and yeast, both the recognition of homologs and the formation of stable bivalents depend on recombinational interactions between homologs (reviewed in ref. 1). For this process, the meiotic prophase cell actively induces DNA double-strand breaks (DSBs) and repairs them by homologous recombination, using preferably a nonsister chromatid of the homolog as template (2). In species such as yeast and mouse, most interhomolog recombinational interactions are not resolved as reciprocal exchanges [crossovers (COs)] and probably serve homolog recognition and alignment (3, 4). A small proportion, however, yields COs, which become cytologically visible as chiasmata and are essential for the stable connection of homologs. COs are not randomly distributed among and along bivalents; every bivalent forms at least one CO (obligate CO), and, if multiple COs occur, they are more evenly spaced along the bivalent than would be expected if they were randomly placed. This phenomenon was originally detected genetically by the finding that the frequency of double recombinants involving a pair of adjacent or nearby intervals was lower than the frequency expected from recombinant frequencies for each of those intervals (reviewed in refs. 5 and 6). Interference has also been analyzed cytologically, from spatial distributions of chiasmata (7, 8) or recombination complexes along chromosomes during meiotic prophase, when recombination is in progress (9). How interference is imposed is not known.

Concomitantly with meiotic recombination, the sister chromatids of each chromosome form a common axis, the axial element (AE), and the AEs of homologs align. Then, numerous transverse filaments connect the AEs of homologs, and a zipper-like structure, the synaptonemal complex (SC), is formed between the homologs (1). Protein complexes that mediate, and mark the sites of, recombination have been localized to AEs or SCs by both EM and immunocytology (reviewed in refs. 10 and 11). These studies (9, 12), together with molecular genetic analyses (13, 14), have elicited several specific questions regarding the imposition of interference: At which step in meiotic recombination is interference first detectable? Is the level of interference the same among recombination complexes representing early and late steps in meiotic recombination? Does the SC contribute to interference? We have analyzed these questions in the mouse by examining how protein complexes that are thought to mark intermediate and late events in meiotic recombination are distributed along SCs in two stages of meiotic prophase.

In mouse, many recombination-related proteins have been identified, and the meiotic time courses of immunofluorescent foci containing these proteins have been described (15, 16). The mouse transverse filament protein SYCP1 is also known (17, 18), and SYCP1-deficient mice have been constructed (19). We have analyzed the distributions of four types of foci along mouse SCs or AEs in wild-type and/or Sycp1 ^{strains: (}i) MLH1 foci, which occur during pachytene and specifically mark the sites of COs (9, 20); (ii and iii) MSH4 and replication protein A (RPA) foci, which appear earlier, during zygotene, and were analyzed here at late zygotene. In mouse, these foci outnumber the prospective COs. However, a subset of them likely matures into MLH1 foci and then into COs, because early MLH1 foci colocalize with MSH4 (16, 21) but then lose MSH4 at later stages; (iv) because Sycp1 ^{strains do not form MLH1 foci (}19), we analyzed γH2AX signals in Sycp1 ^{pachytene spermatocytes. In wild-type meiosis, γH2AX signals occur from leptotene until pachytene (}22). Based on their timing and other evidence (reviewed in refs. 13 and 23), MSH4 and RPA foci likely mark early intermediate stages of recombination involving strand exchange, whereas MLH1 foci likely mark the latest stages, e.g., conversion of double Holliday junctions to COs. γH2AX signals mark various DNA lesions, including DSBs (24); in Sycp1 ^{pachytene, they probably represent (perhaps diverse) unresolved recombination intermediates (}19).

For the detection of genetic interference, the coefficient of coincidence (CC) is often used. However, CC is problematic as a measure for the level of interference because it is not based on the precise positions of genetic exchanges but instead is based on the frequencies of recombinants for genetic markers that delimit two adjacent or nearby chromosomal intervals. Besides the strength of interference between exchanges in adjacent/nearby intervals, the size of the analyzed intervals thus codetermines the value of CC (see, which are published as supporting information on the PNAS web site; for the mouse, cf. 25). This effect precludes a CC-based comparison of the strength of interference among two types of foci with widely different densities. Additionally, in microscopic studies, the (cytological) interference among foci will be overestimated if the size of the intervals to which foci are assigned is close to the resolution limit of the light microscope (see Supporting Text, which is published as supporting information on the PNAS web site). Assignment of foci to intervals will also result in loss of information. In short, if the positions of genetic exchanges/chiasmata/foci are precisely known, models dealing with the exact positions of events are preferable for estimating the strength of interference.

Several point process models have been considered for estimating the strength of interference (ref. 26 and references therein), and the gamma distribution has repeatedly emerged as most useful (26–29). The gamma distribution is commonly used for the analysis of distances between events along a linear axis (see Supporting Text); it describes the frequency distribution of interfocus distances that one would get if (imaginary or real) focus precursors were randomly placed along the SC, but only every nth precursor would yield a focus. Fig. 1A shows gamma distributions for various values of n (or ν, see below). The gamma distribution thus stands for a family of distributions, because each n value yields a distribution with another shape. One can determine for which n value the observed frequency distribution of interfocus distances fits best to a gamma distribution. If the best fit is obtained for n = 1, then there is no interference among foci. Fig. 1A furthermore shows that the distribution is narrower for higher n values: for a given average interfocus distance, the variance of interfocus distances decreases with increasing n. In other words, the higher the n value, the more evenly the foci are spaced and the stronger interference is. n is therefore called the interference parameter of the gamma model. Note that n is not a measure for the average interfocus distance. If one assumes that the biological mechanism of interference conforms to the gamma model (i.e., there is a mechanism that counts focus precursors; e.g., refs. 27 and 28), then n can only be a positive integer. Because it is not our purpose in this study to assume or test a specific biological interference mechanism but to instead use the gamma model as a device to estimate the strength of interference, we do not assume that n is an integer, and we will further denote the interference parameter of the gamma model as ν, which represents positive but not necessarily integer values, as distinct from n, which represents integer values only (see also Supporting Text).

Fig. 1.

Analysis of foci along bivalents. (A) Shape of gamma distributions for different ν values. The average interfocus distance equals 10 for all distributions shown. As ν increases, the very short and very long distances become sparser, and the distributions become narrower and more symmetrical. (B–D) Examples of histograms of observed interfocus distances in spermatocytes (black bars), the best fit of the observed distances to the gamma distribution (red curves), the ν value for which the best fit was obtained ($\widehat{\nu }$), and the distributions expected if there were no interference (i.e., ν = 1; blue curves). The observed interfocus distances were binned for representation only; the best fits to the gamma distribution are based on the exact, unbinned distances. show histograms of all data sets. (E–G) Distribution of foci along bivalents. Shown are the cumulative frequencies of foci as a function of the distance to the centromeric end of the SC (wild type) or AE (Sycp1^{). The distances are expressed as percentage of the length of the SC/AE on which the focus was located. The numbers of foci on which the curves are based are shown in the upper left corners, and the chromosome numbers are shown in the lower right corners of the graphs. A uniform distribution of foci would yield a straight line from the lower left to the upper right corner of the graph. M, male; F, female; Wt, wild type; −/−,} Sycp1^.

The primary finding of this study is that cytological interference occurs among RPA or MSH4 foci in late zygotene, whereas interference among MLH1 foci in midpachytene was much stronger. Mouse SYCP1 was not required for cytological interference among RPA or MSH4 foci. However, our data do not allow us to decide whether SYCP1 is required for the high level of interference among MLH1 foci in wild type.

Acknowledgments

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