Recombination regulator PRDM9 influences the instability of its own coding sequence in humans

Abstract

PRDM9 plays a key role in specifying meiotic recombination hotspot locations in humans and mice via recognition of hotspot sequence motifs by a variable tandem-repeat zinc finger domain in the protein. We now explore germ-line instability of this domain in humans. We show that repeat turnover is driven by mitotic and meiotic mutation pathways, the latter frequently resulting in substantial remodeling of zinc fingers. Turnover dynamics predict frequent allele switches in populations with correspondingly fast changes of the recombination landscape, fully consistent with the known rapid evolution of hotspot locations. We found variation in meiotic instability between men that correlated with PRDM9 status. One particular "destabilizer" variant caused hyperinstability not only of itself but also of otherwise-stable alleles in heterozygotes. PRDM9 protein thus appears to regulate the instability of its own coding sequence. However, destabilizer variants are strongly self-limiting in populations and probably have little impact on the evolution of the recombination landscape.

Fig. 1.

De novo mutation at PRDM9. (A) Restriction sites used for size-enriching ZnF repeat array mutants, plus primers (blue arrows) for single molecule amplification of the array (boxes). Using HpaI and PvuII ensured that any residual partial digest products were much larger than array mutants. (B) Examples of mutants detected by small-pool PCR and Southern blot hybridization of sperm DNA fractions size-enriched from a man heterozygous for 13- and 14-repeat PRDM9 alleles. The expected size range of mutants in each fraction is shown by red bars, and the ladders L are corresponding amplicons from all known allele lengths (8–18 repeats) (4, 7). (C) Mutation dynamics in blood and sperm. Mutation spectra for simple (black) and complex (red) rearrangements are shown on the left, with progenitor allele length(s) shaded in green. PRDM9 genotypes and overall mutation frequencies per haploid genome are given in each panel, with the frequency for man 16 corrected for ∼32% of mutants not detectable because of the presence of progenitor alleles of different length. Representative examples of mutant structures are shown on the right, with different repeat types (defined in Fig. S2) color coded as indicated. Deletions are indicated by Δ, and reduplicated regions by black bars. Segments in recombinant mutants (blue) matching different alleles are underlined in blue or pink.

Fig. 2.

Distribution of rearrangements along the PRDM9 ZnF coding repeat array. (A) Distribution of rearrangement midpoints as a proportion of progenitor array length. Data were pooled over all sequenced mutants and binned into 0.05 intervals. Only the complex gains showed evidence for polarity, with 65% (193/298) of midpoints located 3′ to the center of the unstable region of the array (χ² test, P < 0.0001). (B) Unequal exchange activity per base pair in each interval of perfect sequence identity (IPSI) shared by misaligned PRDM9 alleles. Pairs of A or C repeat arrays are shown misaligned by one repeat, with sequence mismatches marked by vertical lines. All simple ±1 repeat mutants derived from A or C alleles (Fig. S4) were used to estimate the exchange activity in each IPSI relative to all other IPSIs, allowing data to be pooled from different men. Thus, if 10% of mutants mapped to an IPSI 50 bp long, then the relative activity of this IPSI per base pair, relative to all other IPSIs for a given allele misalignment, was 0.1/50 = 0.002. If exchanges are randomly distributed along an array irrespective of ISPI length, then all IPSIs should show the same activity. Gain and deletion activities are shown separately, with mutants identical to known alleles indicated above and below the histograms. Following IPSI binning, the best-fit relationship between IPSI length i and the relative frequency of exchange f was f = 6 × 10⁻⁵i^1.72 (Pearson's r = 0.989). This relationship was used to estimate the expected exchange activity in each IPSI (horizontal red lines). There was no significant correlation between IPSI location and the observed vs. expected exchange activity (Pearson's r = 0.175, P = 0.206), and thus no evidence that these simple exchanges are clustered toward one end of the repeat array.

Fig. 3.

Mutation frequency variation at PRDM9 in sperm. (A) Variation between men in the frequency of gains of two or more repeat units relative to the progenitor allele, with men ranked in ascending order of instability and with upper 95% confidence intervals indicated by bars. PRDM9 alleles in each man are shown on the left, with C and C-type (Ct) alleles (7) shaded in blue. The allelic origin of nonrecombinant mutants in heterozygotes is shown in black and red for the first and second allele, respectively. Gray, mutants not sequenced. (B) Structures of progenitor PRDM9 alleles in these men. In silico predicted DNA-binding motifs (19) are underneath, with matches to the PRDM9 A motif CCNCCNTNNCCNC 20 (20) highlighted in red and with the number of bases matching this motif indicated on the right. The repeat difference between alleles A and D and its match with allele C are indicated by lines. (C) Spectra of mutants, relative to the progenitor allele (green), derived from the A allele in A/A and A/D men, compared with the D allele in the A/D man. Undetectable mutant classes occluded by a progenitor allele are marked by crosses.

Fig. 4.

PRDM9 evolution and the effects of destabilizer variants. Sperm mutation parameters were used to simulate populations initially fixed for the common A variant, as described in Materials and Methods. One in 10 new mutants was assumed to encode a destabilizer, equivalent to the D variant, with a 15-fold higher level of instability in carriers compared with men lacking the destabilizer. Populations were allowed to evolve at constant size without selection for 3 Myr. (A) A typical evolutionary trajectory showing the frequencies of the most common PRDM9 alleles, with each allele colored differently. For clarity, only alleles attaining a population frequency >20% are shown. Periods dominated by a high-frequency (>50%) allele are marked by bars at the top, and contemporary A allele frequencies (4, 7) in Europeans (Eur) and Africans (Afr) are indicated by dotted lines. (B) Frequency of destabilizer (D-type) alleles. (C) Number of different alleles in the population. (D) Heterozygosity, with current European and African heterozygosities (4, 7) indicated.