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Genetics, Vol. 170, 807-812, June 2005, Copyright © 2005
doi:10.1534/genetics.104.040055
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* Department of Biology and The Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, North Carolina 27599
Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, North Carolina 27599
Department of Mathematics and Department of Biology, Indiana University, Bloomington, Indiana 47405
Institute of Molecular Biology, University of Oregon, Eugene, Oregon 97403-1229
1 Corresponding author: Department of Biology and The Carolina Center for Genome Sciences, Campus Box 3280, Coker Hall 305, University of North Carolina, Chapel Hill, NC 27499.
E-mail: gcopenhaver{at}bio.unc.edu
| ABSTRACT |
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| MATERIALS AND METHODS |
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DNA preparation and marker analysis:
DNA was extracted from meiotically related progeny plants by grinding single cauline leaves (
0.51 cm) in 200 µl of 50 mM Tris·HCl (pH 8.0), 200 mM NaCl, 0.2 mM EDTA, 0.5% SDS, and 100 µg/ml Pronase E (Sigma, St. Louis). After incubation at 37° for 30 min samples were extracted with phenol and then chloroform. DNA was precipitated by the addition of 0.1 volume of sodium acetate and 2 volumes of 100% ethanol. After centrifugation, DNA pellets were washed twice in 70% ethanol, resuspended in 100 µl TE (10 mM Tris·HCl, pH 8.0, 1 mM EDTA), and stored at 4°. The PCR-based markers used in this analysis are described at the Arabidopsis Information Resource (http://www.arabidopsis.org/) and include for chromosome 2, RGA, nga1145, m246, mi310, T10J7-t7, THY1B, PLS2, PLS4, PLS8, nga1126, nga361, m323, nga168, BIO2, ML, GBF3, and SGCSNP1098 and for chromosome 4, Tel4N, JV30/31, CIW5, GA1, T5L23.3, nga8, nga1111, DET1, SGCSNP385, CIW6, COP9B, SC5, g4539, AG, CIW7, RPS2, nga1139, JM411, nga1107, DHS1, and SGCSNP53. PCR primers were purchased from Research Genetics (Huntsville, AL), Invitrogen Life Technologies (Carlsbad, CA), or MWG (Highpoint, NC). Markers were amplified by PCR using the following parameters: hotstart at 95°, 30 sec; denaturing at 94°, 15 sec (40 cycles); annealing optimized for each marker between 52° and 57° (10 cycles) followed by 54°61° (30 cycles); and extension at 72° (40 cycles) in an MJ Research (Cambridge, MA) DYAD. Markers were visualized with UV light following electrophoresis of PCR products using either 1% agarose gels or 14% native polyacrylamide gels and staining with ethidium bromide. If necessary, polymorphisms were detected by digesting PCR reactions with restriction enzymes prior to electrophoresis (KONIECZNY and AUSUBEL 1993).
Data analysis:
Marker scores for 143 tetrads were recorded and then verified by two individuals to avoid clerical errors. The tetrad data were analyzed using the methods described in the Appendix of HOUSWORTH and STAHL (2003). The details of the analysis differ from those given in COPENHAVER et al. (2002), but the results of the two methods for the two chromosomes studied in this article are statistically equivalent. The methods of HOUSWORTH and STAHL (2003) are appropriate here because the chromosomes in this article are so well marked that the position of a crossover on a chromosome is known within an error never exceeding 4 cM. The methods of HOUSWORTH and STAHL (2003) are also computationally faster and facilitate simulations required for assessing significance and providing confidence intervals for the data studied in this article.
| RESULTS |
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A summary of the observed crossover events for each chromosome is presented in Table 1. The average number of crossovers per chromosome tetrad (bivalent) was similar, with chromosome 2 experiencing 1.7 per meiosis and chromosome 4 experiencing 1.5. Importantly, these bivalents experienced multiple crossovers in sufficient meioses to enable an examination of interference parameters (Figure 1). On both chromosomes the majority of crossovers occurred on the longer arm of these short, acrocentric chromosomes. In only one case, on chromosome 2, did we observe a meiosis that apparently lacked a crossover. This could be due to the occurrence of two closely spaced 2-chromatid crossovers not separated by an intervening marker. However, the observed ratio of 2:3:4-chromatid double crossovers argues that our marker density is sufficient to detect nearly all double crossovers. Alternatively, the single meiosis apparently lacking a crossover on chromosome 2 could be explained by an undetected crossover on one or the other extreme terminus of the chromosomes. Such events have been observed in Arabidopsis using cytological analysis (SANCHEZ-MORAN et al. 2001, 2002). It is also possible that this bivalent did not experience a crossover: the model we used to simulate expected distributions of intercrossover distances in Arabidopsis predicts
1% nonexchange bivalents for chromosome 2.
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0.03 and 0.05, respectively, with 95% confidence intervals of (0.003, 0.059) and (0.023, 0.097), respectively. Thus, the distributions of crossovers on small, acrocentric, NOR-bearing chromosomes of Arabidopsis conform more closely to the simple counting model (FOSS et al. 1993) than do those on the remaining chromosomes, which are longer, metacentric, and lack NOR regions. | DISCUSSION |
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In Arabidopsis, homologous chromosome association appears to involve telomeres. FISH analysis of Arabidopsis chromosomes shows that telomeres associate with the NOR during premeiotic interphase. That association presumably assists in pairing and is later lost during leptotene and replaced with a loose bouquet formation in zygotene (ARMSTRONG et al. 2001). Whether loose zygotene telomere association is comparable to the strong "classical bouquet" seen in other organisms remains unclear. In asy1, an Arabidopsis mutant that abolishes synapsis, the premeiotic NOR-associated telomere clustering is maintained. However, because asy1 mutants fail to synapse the chromosome pairs eventually disjoin, yielding univalents, including the NOR-bearing chromosomes (ARMSTRONG et al. 2001). Thus, the NOR regions may be implicated in assisting chromosome organization during meiosis, but more analysis needs to be done to determine any specific role in pairing.
The shortage of noninterfering crossovers on the NOR-bearing chromosomes of Arabidopsis can be rationalized in the framework presented in COPENHAVER et al. (2002) and expanded in STAHL et al. (2004). By several criteria, Arabidopsis is a "group II" organism, whose chromosome synapsis depends on recombination functions (GRELON et al. 2001). We postulate that the crossovers resulting from these presynaptic events are interference free. Events initiated postsynaptically, on the other hand, give rise to crossovers that are subject to interference (among each other), presumably according to the counting rules of FOSS et al. (1993). Within this framework, the presence of NORs acting as pairing centers on the two short chromosomes reduces the need for the noninterfering crossovers. It is possible that the differentiation from noninterfering to interfering crossovers is controlled by the establishment of synapsis.
In Drosophila melanogaster and C. elegans, both of which are group I organisms lacking synapsis-promoting recombination events (STAHL et al. 2004), deletion of pairing centers, such as NORs, decreases crossing over and deters synapsis (HAWLEY 1980; VILLENEUVE 1994). Examination of pairing partner switches in autotetraploid lines suggests that Arabidopsis chromosomes also harbor multiple autonomous pairing sites (SANTOS et al. 2003). Low frequencies of chromosome 2 and 4 multivalent formation in autotetraploid lines may indicate the existence of a particularly strong pairing site, perhaps the NOR, that dominates the pairing choice for the length of these chromosomes (SANTOS et al. 2003). It is interesting to note that in these studies chromosome 2 exhibits the lowest multivalent frequencies (and therefore the most persistent bivalent pairing), and in our experiments chromosome 2 exhibits the fewest noninterfering crossovers. These observations suggest that the presence of NOR domains (putative pairing centers) influences the relative frequencies of two distinct classes of crossovers in Arabidopsis. We find this hypothesis particularly interesting since it implies that interference is regulated at a chromosomal level in a manner that reflects chromosome architecture.
Distribution of interference-sensitive and insensitive crossovers:
The mathematical model that we used to simulate the distribution of intercrossover distances on the chromosomes of Arabidopsis has two variables: p, which is the portion of interference-insensitive crossovers out of the total crossover population, and m, which is the obligate number of "failures" between any two interfering crossovers. As an aside, it should be noted that many other intriguing models of interference have been proposed (e.g., KING and MORTIMER 1990; FUJITANI et al. 2002; BORNER et al. 2004). The interference parameters for chromosomes 1, 3, and 5 in our previous study varied from 10 to 17, and all estimates in that range were statistically indistinguishable due to the lack of statistical power of the analysis. The level of interference for chromosomes 2 and 4 estimated in this study is
m = 9 (±2). Thus, interference-sensitive crossovers may be subject to the same intensity of interference (m) on all the Arabidopsis chromosomes. This is striking given the large difference in the frequencies (p) of the interference-insensitive crossovers. We propose that this reflects a fundamental difference in the way that interference-insensitive and -sensitive crossovers are apportioned on chromosomes, while the strength of interference (m) is consistent for all crossovers subject to interference, regardless of chromosome.
HIGGINS et al. (2004) recently provided genetic support for the two-pathway model of recombination in Arabidopsis by examining mutants in the MSH4 gene. In Saccharomyces cerevisiae msh4 mutants have reduced crossover frequency and the residual crossovers are free of interference (NOVAK et al. 2001) Chiasmata in Atmsh4 mutants are reduced by
85% and the remaining chiasmata are distributed randomly among cells and chromosomes, suggesting that they are free of interference. However, the initial analysis of Atmsh4 lacked the resolution to measure interference on individual chromosomes. Nonetheless, it is intriguing to note that the observed 85% reduction in chiasmata is consistent with the modeling prediction that
80% of all crossovers on chromosomes 1, 3, and 5 are insensitive to interference (COPENHAVER et al. 2002). It should be noted that HIGGINS et al. (2004) did not report any differences in the level of noninterfering crossovers among the five Arabidopsis chromosomes.
This study examines interference on chromosomes 2 and 4 of Arabidopsis. In addition to harboring large NOR domains these chromosomes are also shorter than the other three Arabidopsis chromosomes. In yeast, short chromosomes have been shown to have a higher crossover density and exhibit weaker interference when compared to longer chromosomes (KABACK et al. 1999). Consistent with these observations, DE LOS SANTOS et al. (2003) report that interference-insensitive crossovers occur more frequently on smaller chromosomes in yeast. Taken together these findings suggest that one would expect that chromosomes 2 and 4 should have a relatively higher fraction of interference-insensitive crossoversprecisely the opposite of what we observe. This discrepancy highlights the need for analysis that disentangles the effects of chromosome stature and chromosome architecture (NOR presence) on crossover interference.
The counting model of FOSS et al. (1993) proposes that m represents noncrossover gene conversion events. We have calculated the predicted number of gene conversions expected on chromosomes 2 and 4, using the assumptions and formulas described in COPENHAVER et al. (2002) for similar calculations on chromosomes 1, 3, and 5. These calculations predict 0.74 and 0.83 gene conversions for chromosomes 2 and 4, respectively, in the 143 tetrads assayed. This is consistent with our observed data described here, which did not detect any gene conversions.
| ACKNOWLEDGEMENTS |
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