- Research article
- Open Access
Characterization of meiotic crossovers and gene conversion by whole-genome sequencing in Saccharomyces cerevisiae
© Qi et al; licensee BioMed Central Ltd. 2009
- Received: 24 June 2009
- Accepted: 15 October 2009
- Published: 15 October 2009
Meiotic recombination alters frequency and distribution of genetic variation, impacting genetics and evolution. In the budding yeast, DNA double strand breaks (DSBs) and D loops form either crossovers (COs) or non-crossovers (NCOs), which occur at many sites in the genome. Differences at the nucleotide level associated with COs and NCOs enable us to detect these recombination events and their distributions.
We used high throughput sequencing to uncover over 46 thousand single nucleotide polymorphisms (SNPs) between two budding yeast strains and investigated meiotic recombinational events. We provided a detailed analysis of CO and NCO events, including number, size range, and distribution on chromosomes. We have detected 91 COs, very close to the average number from previous genetic studies, as well as 21 NCO events and mapped the positions of these events with high resolution. We have obtained DNA sequence-level evidence for a wide range of sizes of chromosomal regions involved in CO and NCO events. We show that a large fraction of the COs are accompanied by gene conversion (GC), indicating that meiotic recombination changes allelic frequencies, in addition to redistributing existing genetic variations.
This work is the first reported study of meiotic recombination using high throughput sequencing technologies. Our results show that high-throughput sequencing is a sensitive method to uncover at single-base resolution details of CO and NCO events, including some complex patterns, providing new clues about the mechanism of this fundamental process.
- Gene Conversion
- Meiotic Recombination
- Gene Conversion Event
- Holliday Junction
- Meiotic Product
Meiosis is essential for eukaryotic sexual reproduction and reduces the number of chromosomes in half to generate haploid cells [1–3]. To ensure the proper meiotic homolog segregation, the homologs must recognize and pair with each other in early prophase I [1–3]. It is thought that a key pairing mechanism is via DNA heteroduplex formation, which is intimately coupled with the initiation of meiotic recombination . One major type of outcome of meiotic recombination is crossover (CO), which involves the exchange of flanking markers, as well as possible gene conversion (GC) [4, 5]. Another result of recombination is GC without exchange of flanking markers (Non-CO, or NCO) [4, 5]. Meiosis is also the process that re-distributes the genetic variations in a eukaryotic population. The extent of meiotic recombination directly impacts the frequency of specific combinations of alleles. Because of the effect of meiotic recombination on the distribution of genetic diversity, meiosis is thought to have contributed to the extraordinary diversity and evolutionary success of eukaryotes [6–10].
Meiotic recombination has been studied extensively using model systems, including the budding and fission yeasts, Drosophila melanogaster, Caenorhabditis elegans, mammals, Arabidopsis thaliana, and maize [1–3]. In the budding yeast Saccharomyces cerevisiae, molecular and biochemical studies have identified key intermediates of meiotic recombination, starting with DNA double strand breaks (DSBs) and D-loops [4, 5]. A portion of the D-loops proceeds to form double Holliday junctions (DHJ), which are then resolved largely to COs. Some D-loops undertake another pathway to form COs, possibly via single Holliday junctions (SHJ), as seen in the fission yeast . A third option for the D-loops is the repair of DSBs without COs, resulting NCO/GC events if the two recombining DNAs are not identical.
Because recombination occurs at many sites in the genome, it is important to investigate recombination at the whole-genome level. Genome-wide genetic detection of crossovers has been done in many genetic systems, resulting in the construction of genetic maps, as well as producing other information. However, previous molecular studies usually relied on the use of naturally occurring (such as the one at the HIS4 locus) and artificially generated (such as ones induced by the HO endonuclease) recombination hotspots as substrates; therefore, the molecular details of crossovers are not available on a genome-wide level. In addition, NCO/GC has been investigated using a small number of markers or by inference at a population level. Recently, meiosis between two strains of the budding yeast has been analyzed using microarrays, providing valuable information on the frequency of CO and NCO events on a genome-wide scale .
As an alternative way to analyze meiotic recombination at the DNA level on a whole-genome scale, we have used the recently developed Roche GS20/FLX  and Illumina  sequencing technologies. To obtain a large number of DNA polymorphisms as markers for recombination, we used two strains of S. cerevisiae that have sequenced genomes: S288C and RM11-1a [15, 16], which were estimated to have 0.5-1% sequence divergence distributed throughout the genome. Here we report our results from high-throughput sequencing of both the S288C and RM11-1a (hereafter referred to as RM11 for convenience) strains and four meiotic products. Over 46 thousand single nucleotide polymorphisms (SNPs) were revealed by comparison and further parsing of the two genomic sequences. Armed with these markers, we were able to detect COs, NCOs and other recombination events in meiotic products (spores) from a diploid generated by crossing S288C with RM11.
Resequencing of the S288C and RM11 strains identified errors in reported sequences
Number of reads, nucleotides and genome coverage of each meiotic product and reference genome sequencing
Sequencing of meiotic products by 454 provided a test for de novo assembly of new sequencing reads
To obtain a diploid with a large number of sequence polymorphisms, we crossed S288C with RM11; then we induced meiosis in the diploid using a standard protocol, and obtained a number of tetrads (asci) with meiotic spores (not shown). We cultured one set of four spores in a rich medium and isolated DNAs from these four cultures. These DNAs were sequenced using the 454 technology, resulting in approximately 300,000 to 416,000 reads, or 3.6× to 4.9× coverage, of each of the four meiotic products (Table 1).
Coverage of S288C by assembled contigs based on combined reads from different spores
2 spores (1+2)
2 spores (1+3)
2 spores (2+3)
3 spores (1+2+3)
Analysis of SNPs in the meiotic sequence data revealed 91 COs with and without GCs
Comparison of meiotic sequences uncovered 21 NCOs/GCs
In addition, by comparing sequences from all four meiotic products, we detected 21 putative GC events not associated with CO (Additional file 1 - Table S2). To verify its reliability, we analyzed the DNA sequences at all 21 putative GC sites using PCR and conventional Sanger DNA sequencing. The PCR and sequencing results were in complete agreement with the Roche GS20/FLX and Illumina results. The results indicated that the four meiotic chromatids had 7, 6, 4, and 4 detected GCs. Because the two yeast genomes are ~99% identical, the observed GC events were likely fewer than the actual recombination/pairing events. We estimated the possible number of undetected NCOs in a way similar to that in a recent study . Among 91 COs discovered in this analysis, 37 were detected using flanking SNP information, but did not show a detectable GC due to the lack of a SNP. If a similar fraction (37/91 = 0.407) of NCOs was not detected due to the lack of SNPs, the estimated total amount of NCOs would be 30 (= 21 × 1.407). Therefore, our genome sequencing results indicated that there were a significant number of NCO (GC) events, resulting in a change of allelic frequency.
The DNA of spore 4 was analyzed earlier than others and the 454 reads had shorter lengths, resulting in a reduced coverage of the SNPs. One effect of the reduced coverage was that a crossover involving spore 4 probably had more inaccurate border(s); nevertheless, all COs involving spore 4 were still detectable because flanking markers were still observed. Because NCOs were detected using the SNP information for each spore in the chromosomal context, reduced SNP coverage in spore 4 likely caused a decrease in NCO detection, providing another possible explanation for under-estimation of the NCO number.
Size range and map position of COs and NCOs
Nevertheless, at least 28 COs had minimal sizes of greater than 1.0 kb, with the largest minimum size being over 7 kb (Additional file 1 - Figure S6). Among the NCOs, the maximum sizes ranged from 1,109 bp to 7,575 bp, and the largest minimum size was over 6.5 kb (Additional file 1 - Figure S7). These results indicate that both CO and NCO can involve several kbs, suggesting that DNA repair and/or heteroduplex formation can be rather extensive. In budding yeast, most COs are thought to result from the double Holliday junctions (DHJs), and a small fraction of COs from single Holliday junctions (SHJs) . If all DHJ are initiated with the same size and then each Holliday junction "randomly" expands to a larger size, the length distribution of COs should follow a Normal distribution. However, we found that the observed sizes of COs (Figure 2A) were not consistent with a Normal distribution, supporting a mixture of COs resulted from both DHJs and SHJs, since COs from SHJs might have different ranges of lengths resulted from a different pathway . This distribution is also supported by the same analysis on the data of the recent study using microarrays (Figure 2B) .
The maximum possible lengths of CO regions in this study covered a wide range. If interference insensitive COs in the budding yeast also involve a SHJ, it is possible that shorter COs might be generated by the interference insensitive pathway. To test this idea, we analyzed the genomic distribution of the COs that were shorter than 1.5 kb, and found them to be consistent with a Poisson distribution (Figure 4B); on the other hand, the COs that were longer than 1.5 kb did not have a Poisson distribution, consistent with the possibility that they were generated by the interference-sensitive pathway (Figure 4C). Analyses with different cutoffs other than 1.5 kb were also preformed (data now shown), but the statistical fit of the distribution of shorter COs to a Poisson model was not as good as that of the 1.5 kb cutoff; in addition, the proportion of shorter COs from the 1.5 kb cutoff was consistent with previous observations [18, 20–23].
Sequence data revealed complex CO and post-meiotic segregation events
A major difference between this study and the microarray studies published recently  is that we determined the actual sequences of the meiotic products, rather than inferring about the SNP genotypes on the basis of differential hybridization signals. Our approach can detect both SNPs and any other sequence information. It was reported that spontaneous mutation rates at specific loci could be 6-20 fold higher in meiosis than mitosis [28, 29]. However, there has been no study of mutations during meiosis at a genome-wide scale. To search for spontaneous mutations, we examined the sequences throughout the genome for base substitution mutations and did not identify any sequences that differed from both parental sequences. Therefore, the mutation rate was below our detection limit of ~8 × 10-8 per base per cell division. A recent genome-wide analysis of mitotic yeast cells provided an estimated rate of mitotic substitution of 3.3 × 10-10 per base per cell division , suggesting that a 6-20 fold increase would not be detected by our analysis. Tandem repetitive sequences are known to have high mutation rates to form different copy numbers in cell division. Repeats with a higher copy number usually have higher mutation rates and lower appearance frequency (number of loci) . However, the possibility of appearance of such kind of mutation is still too low to be observed in one generation of meiosis, as confirmed by our analysis of all 16 chromosomes in the 4 spores.
In summary, our studies have reliably verified over 46 thousand SNPs that were identified by comparison between the public S288C and RM11 genomic sequences and have uncovered errors in the S288C and RM11 sequences, respectively, thereby removing 1907 previously reported SNPs and defining 358 new SNPs. These new sequence results are useful resources for further genomic and genetic studies using the budding yeast. We have uncovered detailed molecular information about meiotic recombination on a whole genome level using high-throughput sequencing. The numbers of CO and NCO events we detected were in very good agreement with previous studies; furthermore, we described complex patterns of COs that involved three chromatids, shedding new light on the process of meiotic recombination. Our studies provide a window into the nature of meiotic recombination at the DNA level throughout the genome and established a whole-genome foundation for further molecular genetic studies of this fundamental process.
Growth of yeast cells
The Saccharomyces cerevisiae strains S288C and RM11 were grown overnight at 30° on an agar plate with the YPD rich medium, and mixed on an YPD plate to allow mating to form diploid cells. Newly formed zygotes were identified under a light microscope and transferred to a clean area of the YPD plate using a micromanipulator, and grown to a colony at 30°. The diploid strain was then grown on an YPD plate as a patch, and freshly grown cells were transferred to a sporulation plate. After one week, tetrads with four spores were detected under a light microscope, were partially digested in an aqueous solution of zymolyase. The partially digested tetrads were dissected to separate the spores under a light microscope using a micromanipulator, and the spores were allowed to grow for two days on an YPD plate into colonies. Cells from the colonies were used to inoculate liquid YPD cultures. Also, S288C and RM11 were similarly grown in YPD cultures to late exponential phase. The yeast cells were then harvested from the cultures and used for the isolation of genomic DNAs.
Genomic sequence data sets
The public whole genome sequences of the S288C and RM11 strains were downloaded from NCBI (National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov/) and Broad Institute http://www.broad.mit.edu/ respectively. The four haploid meiotic products from the same meiosis were sequenced by using Roche GS20/FLX pyrosequencing technology to detect COs, NCOs and other recombination events. The S288C and RM11-1a genomic DNAs were sent to Fasteris http://www.fasteris.com for re-sequencing by using Illumina sequencing technology to verify SNPs between these two parental references. The public S288C and RM11-1a genomic sequences were used for BLAST analysis to map the newly obtained sequences from the high throughput shotgun sequencing technologies.
Reads Mapping and SNPs Detection and Correction
We applied a series of steps to map the high-throughput reads to the S288C and RM11-1a public sequences and to detect SNPs.
First, SNPs between S288C and RM11-1a were initially identified by the global alignment tool MUMMER . Ambiguous differences in repetitive and low complexity regions were ignored (the option "--mum" was used for anchoring matches uniquely on both references genomes). Total 62,324 SNPs were detected for all 16 pairs of chromosomes.
However, some SNPs were false positive and could be attributable to the sequencing error on either S288C or RM11. Each sequencing error on reference genomes could raise an artifact of gene conversion. In order to identify and then exclude these pseudo-SNPs from our analysis, S288C and RM11 were re-sequenced by using Illumina sequencing technology. 803 and 1104 nucleotides on the public S288C and RM11 were corrected by mapping of their re-sequenced reads. 46,487 of 62,324 SNPs were verified for further analysis. A confirmed SNP in this analysis must have at least 2 Illumina reads from each of S288C and RM11. Those SNPs without coverage by Illumina reads on either S288C or RM11, due to uneven sequencing coverage or matches to repeats, were removed in the analysis. These filtered out SNPs need to be verified by additional sequencing coverage.
Third, the reads from the four meiotic products were mapped to the pubic S288C and RM11 sequences by BLASTN  to provide primary information of location and identity for further alignment. A global identity cutoff of 80% was applied to all read matches, from which reads with high identity to reference genomes were kept. Then nucleotide sequences of the references near each SNP and the reads of meiotic products nearby were selected for detailed multiple alignment by CLUSTALW .
Last, whole genome mapping and visualization were applied to all 4 meiotic products near the SNPs. We developed a whole genome visualization tool, named inGAP to display all homology exchange among meiotic products. The manuscript has been submitted (Ji Qi, Fangqing Zhao, Anne Buboltz and Stephan C. Schuster) and the software is available online at http://sites.google.com/site/nextgengenomics/ingap
We have also written an additional set of scripts to perform the bioinformatic analyses in this study. More information will be provided if requested.
We thank three anonymous reviewers of a previous version of this manuscript for their helpful comments. This sequencing-by-synthesis study was made possible through generous funding from the Department of Biology and the Huck Institutes of the Life Sciences, the Pennsylvania State University. A.J.W. and H.M. were partially supported by funds from Rijk Zwaan, the Netherlands. H.M. was partially supported by funds from Fudan University. J.Q. and S.C.S. were supported in part by the Gordon and Betty Moore Foundation. This project was also supported in part by a grant from the Pennsylvania Department of Health using Tobacco Settlement Funds appropriated by the US legislature. The Pennsylvania Department of Health specifically disclaims responsibility for any analyses, interpretations or conclusions.
- Roeder GS: Meiotic chromosomes: it takes two to tango. Genes Dev. 1997, 11 (20): 2600-2621. 10.1101/gad.11.20.2600.View ArticlePubMedGoogle Scholar
- Zickler D, Kleckner N: The leptotene-zygotene transition of meiosis. Annu Rev Genet. 1998, 32: 619-697. 10.1146/annurev.genet.32.1.619.View ArticlePubMedGoogle Scholar
- Ma H: The Arabidopsis book. A molecular portrait of Arabidopsis meiosis. Edited by: Somerville CR, Meyerowitz EM, Dangl J, Stitt M. 2006, Rockville, MD: American Society of Plant BiologistsGoogle Scholar
- Lichten M: Meiotic recombination: breaking the genome to save it. Curr Biol. 2001, 11 (7): R253-256. 10.1016/S0960-9822(01)00131-2.View ArticlePubMedGoogle Scholar
- Keeney S: Mechanism and control of meiotic recombination initiation. Curr Top Dev Biol. 2001, 52: 1-53. full_text.View ArticlePubMedGoogle Scholar
- Ezov TK, Boger-Nadjar E, Frenkel Z, Katsperovski I, Kemeny S, Nevo E, Korol A, Kashi Y: Molecular-genetic biodiversity in a natural population of the yeast Saccharomyces cerevisiae from "Evolution Canyon": microsatellite polymorphism, ploidy and controversial sexual status. Genetics. 2006, 174 (3): 1455-1468. 10.1534/genetics.106.062745.PubMed CentralView ArticlePubMedGoogle Scholar
- Grimsby JL, Tsirelson D, Gammon MA, Kesseli R: Genetic diversity and clonal vs. sexual reproduction in Fallopia spp. (Polygonaceae). American Journal of Botany. 2007, 94: 957-964. 10.3732/ajb.94.6.957.View ArticlePubMedGoogle Scholar
- Barton NH, Charlesworth B: Why sex and recombination?. Science. 1998, 281 (5385): 1986-1990. 10.1126/science.281.5385.1986.View ArticlePubMedGoogle Scholar
- Burt A: Perspective: sex, recombination, and the efficacy of selection--was Weismann right?. Evolution. 2000, 54 (2): 337-351.PubMedGoogle Scholar
- Weismann A: The Evolution Theory. 1904, London: Thoemmes PressGoogle Scholar
- Cromie GA, Hyppa RW, Taylor AF, Zakharyevich K, Hunter N, Smith GR: Single Holliday junctions are intermediates of meiotic recombination. Cell. 2006, 127 (6): 1167-1178. 10.1016/j.cell.2006.09.050.PubMed CentralView ArticlePubMedGoogle Scholar
- Mancera E, Bourgon R, Brozzi A, Huber W, Steinmetz LM: High-resolution mapping of meiotic crossovers and non-crossovers in yeast. Nature. 2008, 454 (7203): 479-485. 10.1038/nature07135.PubMed CentralView ArticlePubMedGoogle Scholar
- Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, et al: Genome sequencing in microfabricated high-density picolitre reactors. Nature. 2005, 437 (7057): 376-380.PubMed CentralPubMedGoogle Scholar
- Bentley DR: Whole-genome re-sequencing. Curr Opin Genet Dev. 2006, 16 (6): 545-552. 10.1016/j.gde.2006.10.009.View ArticlePubMedGoogle Scholar
- Ruderfer DM, Pratt SC, Seidel HS, Kruglyak L: Population genomic analysis of outcrossing and recombination in yeast. Nat Genet. 2006, 38 (9): 1077-1081. 10.1038/ng1859.View ArticlePubMedGoogle Scholar
- Schacherer J, Shapiro JA, Ruderfer DM, Kruglyak L: Comprehensive polymorphism survey elucidates population structure of Saccharomyces cerevisiae. Nature. 2009, 458 (7236): 342-345. 10.1038/nature07670.PubMed CentralView ArticlePubMedGoogle Scholar
- Szostak JW, Orr-Weaver TL, Rothstein RJ, Stahl FW: The double-strand-break repair model for recombination. Cell. 1983, 33 (1): 25-35. 10.1016/0092-8674(83)90331-8.View ArticlePubMedGoogle Scholar
- Hollingsworth NM, Brill SJ: The Mus81 solution to resolution: generating meiotic crossovers without Holliday junctions. Genes Dev. 2004, 18 (2): 117-125. 10.1101/gad.1165904.PubMed CentralView ArticlePubMedGoogle Scholar
- Buhler C, Borde V, Lichten M: Mapping meiotic single-strand DNA reveals a new landscape of DNA double-strand breaks in Saccharomyces cerevisiae. PLoS Biol. 2007, 5 (12): e324-10.1371/journal.pbio.0050324.PubMed CentralView ArticlePubMedGoogle Scholar
- Hollingsworth NM, Ponte L, Halsey C: MSH5, a novel MutS homolog, facilitates meiotic reciprocal recombination between homologs in Saccharomyces cerevisiae but not mismatch repair. Genes Dev. 1995, 9 (14): 1728-1739. 10.1101/gad.9.14.1728.View ArticlePubMedGoogle Scholar
- Copenhaver GP, Housworth EA, Stahl FW: Crossover interference in Arabidopsis. Genetics. 2002, 160 (4): 1631-1639.PubMed CentralPubMedGoogle Scholar
- Housworth EA, Stahl FW: Crossover interference in humans. Am J Hum Genet. 2003, 73 (1): 188-197. 10.1086/376610.PubMed CentralView ArticlePubMedGoogle Scholar
- Nakagawa T, Ogawa H: The Saccharomyces cerevisiae MER3 gene, encoding a novel helicase-like protein, is required for crossover control in meiosis. EMBO J. 1999, 18 (20): 5714-5723. 10.1093/emboj/18.20.5714.PubMed CentralView ArticlePubMedGoogle Scholar
- Bugreev DV, Mazina OM, Mazin AV: Rad54 protein promotes branch migration of Holliday junctions. Nature. 2006, 442 (7102): 590-593. 10.1038/nature04889.View ArticlePubMedGoogle Scholar
- Greig D, Travisano M, Louis EJ, Borts RH: A role for the mismatch repair system during incipient speciation in Saccharomyces. J Evol Biol. 2003, 16 (3): 429-437. 10.1046/j.1420-9101.2003.00546.x.View ArticlePubMedGoogle Scholar
- Oh SD, Lao JP, Hwang PY, Taylor AF, Smith GR, Hunter N: BLM ortholog, Sgs1, prevents aberrant crossing-over by suppressing formation of multichromatid joint molecules. Cell. 2007, 130 (2): 259-272. 10.1016/j.cell.2007.05.035.PubMed CentralView ArticlePubMedGoogle Scholar
- Oh SD, Lao JP, Taylor AF, Smith GR, Hunter N: RecQ helicase, Sgs1, and XPF family endonuclease, Mus81-Mms4, resolve aberrant joint molecules during meiotic recombination. Mol Cell. 2008, 31 (3): 324-336. 10.1016/j.molcel.2008.07.006.PubMed CentralView ArticlePubMedGoogle Scholar
- Magni GE, Von Borstel RC: Different rates of spontaneous mutation during mitosis and meiosis in Yeast. Genetics. 1962, 47 (8): 1097-1108.PubMed CentralPubMedGoogle Scholar
- Magni GE: The origin of spontaneous mutations during meiosis. Proc Natl Acad Sci USA. 1963, 50: 975-980. 10.1073/pnas.50.5.975.PubMed CentralView ArticlePubMedGoogle Scholar
- Lynch M, Sung W, Morris K, Coffey N, Landry CR, Dopman EB, Dickinson WJ, Okamoto K, Kulkarni S, Hartl DL, et al: A genome-wide view of the spectrum of spontaneous mutations in yeast. Proc Natl Acad Sci USA. 2008, 105 (27): 9272-9277. 10.1073/pnas.0803466105.PubMed CentralView ArticlePubMedGoogle Scholar
- Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, Salzberg SL: Versatile and open software for comparing large genomes. Genome Biol. 2004, 5 (2): R12-10.1186/gb-2004-5-2-r12.PubMed CentralView ArticlePubMedGoogle Scholar
- Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic local alignment search tool. J Mol Biol. 1990, 215 (3): 403-410.View ArticlePubMedGoogle Scholar
- Thompson JD, Higgins DG, Gibson TJ: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994, 22 (22): 4673-4680. 10.1093/nar/22.22.4673.PubMed CentralView ArticlePubMedGoogle Scholar
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