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Genetics, Vol. 177, 2223-2232, December 2007, Copyright © 2007
doi:10.1534/genetics.107.079616
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,3
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* Department of Genetics, North Carolina State University, Raleigh, North Carolina 27695,
Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853 and
Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York 10003
5 Corresponding author: Department of Biology, 1009 Main Bldg., 100 Washington Square East, New York, NY 10003.
E-mail: mp132{at}nyu.edu
| ABSTRACT |
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150 kb) and indica (
75 kb). LD extends over a shorter distance in O. rufipogon (<<40 kb) than in any of the O. sativa groups assayed here. The differences in the extent of LD among these groups are consistent with differences in outcrossing and recombination rate estimates. As well as heterogeneity between groups, our results suggest variation in LD patterns among genomic regions. We demonstrate the feasibility of genomewide association mapping in cultivated Asian rice using a modest number of SNPs.
10,000 years ago from Oryza rufipogon Griff, with at least two centers of domestication—one in the lower Yangtze Valley of China that gave rise to the japonica variety group and the other possibly in South Asia that gave rise to the indica variety group (KHUSH 1997; CRAWFORD and CHEN 1998; GARRIS et al. 2005). The temperate japonica variety group, which is grown widely in Japan, Korea, and northeast China, is closely related to the tropical japonica subpopulation that is grown on hillsides throughout Southeast Asia (KHUSH 1997; GARRIS et al. 2005). Domestication in rice also resulted in a change in the breeding system; O. sativa is autogamous, outcrossing at a rate of
1–2%, while O. rufipogon outcrosses at a much higher rate (
7–56%) (OKA 1988; GAO et al. 2007).
The importance of rice as a major world crop has engendered interest in determining the levels and patterns of variation in its genome. Single nucleotide polymorphism (SNP) levels are generally low in the O. sativa and O. rufipogon genomes, with mean silent Watterson's
levels of 2.92 and 5.42/kb for rice and its wild ancestor, respectively (CAICEDO et al. 2007). SNP levels are highest in indica (
W = 2.21/kb) and lowest in temperate japonica (
W = 0.948/kb), with tropical japonica having intermediate polymorphism levels (
W = 1.70/kb). There appears to be an excess of high-frequency-derived SNPs in O. sativa but not in O. rufipogon, and modeling suggests that the patterns of polymorphism across the rice genome are best explained either by a bottleneck and strong selection on various domestication traits or by more complex demographic models that include bottlenecks, population subdivision, and migration (CAICEDO et al. 2007).
Although the levels and patterns of SNPs in rice have begun to be characterized, there is still little information on linkage disequilibrium (LD) in this crop species and its wild relative. There has been intense interest in characterizing LD levels and patterns in this species, both to infer evolutionary forces (RAKSHIT et al. 2007) and to exploit this information for gene discovery (GARRIS et al. 2003). Several forces—including mutation, drift, population bottlenecks, population substructure, population admixture, levels of inbreeding, and selection—contribute to the emergence and maintenance of LD. The extent of LD is also dependent on the effective recombination rate, since LD between two loci is degraded by crossover between genes. In a population of constant size, if recombination rates do not vary across the genome, a strong correlation is expected between interlocus distance and LD, and loci in close proximity will remain in disequilibrium for longer periods than those located farther apart (HARTL and CLARK 1997).
Patterns of linkage disequilibrium have been characterized in several crop species and their relatives. In maize (Zea mays ssp. mays), r2 decays within 0.3–2 kb, and this rapid decay may be due to this species being outcrossing (REMINGTON et al. 2001; TENAILLON et al. 2001). In the related species sorghum (Sorghum bicolor), r2 >0.1 is observed up to 15–20 kb (HAMBLIN et al. 2005). High levels of marker association (r2 > 0.1) across a 212-kb region are observed in cultivated, elite varieties of the selfing crop barley (Hordeum vulgare ssp. vulgare), while in landrace accessions, high LD levels persist to
90 kb (CALDWELL et al. 2006). LD in wild barley (H. vulgare ssp. spontaneum), a highly selfing species, decays intragenically, with a range of only a few kilobases (MORRELL et al. 2005). Linkage disequilibrium in soybean (Glycine max), which is also a selfer, can extend from 90 kb to > 500 kb in landrace material, although the level is dependent on the population sample (HYTEN et al. 2007).
There has been no large-scale assessment of LD in O. sativa, although the first study in rice found an LD decay of
100 kb around a disease resistance locus in the aus subpopulation (GARRIS et al. 2003) and a more recent study reported an LD decay of
50 kb in indica and of
5 kb in O. rufipogon (RAKSHIT et al. 2007). Here we determine the extent of LD in three major subpopulations of domesticated Asian rice (indica, tropical japonica, and temperate japonica) and its wild relative O. rufipogon. Using data from five
500-kb genomic regions in the rice genome, we are able to demonstrate differing extents of LD in these cultivated and wild groups and determine that a modest number of SNP markers can provide genomewide coverage for association studies.
| MATERIALS AND METHODS |
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Fragments sequenced:
Variation was assessed in six genomic regions of
500 kb from chromosomes 1 and 4 (Figure 1), which were the first two rice chromosomes to be completely sequenced (FENG et al. 2002; SASAKI et al. 2002). These regions are designated A–F (Table 1). In each genomic region, a focal gene in the middle of the region was completely sequenced (including
1.5 kb of upstream sequence and 1.0 kb of downstream sequence). Twelve
500- to 600-bp gene fragments on both sides of these focal genes and spaced
40 kb apart were sequenced to provide coverage across the 500-kb genomic region (Figure 2; supplemental Table S2 at http://www.genetics.org/supplemental/). Our analysis of genomewide background LD used 111 sequence-tagged site (STS) gene fragments randomly distributed throughout the genome as reported in a previous study (CAICEDO et al. 2007).
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Analysis of nucleotide variation:
The population mutation parameter
W (WATTERSON 1975) was calculated for silent sites within each gene or gene fragment. Each O. sativa accession and a Malaysian O. rufipogon accession (RA2747) were considered to contribute a single haplotype because heterozygotes are rare in O. sativa and both the O. sativa and the Malaysian O. rufipogon accessions had been selfed for several generations. The remaining O. rufipogon accessions contributed two haplotypes to the
W estimate.
LD analysis:
For the analysis of LD, only biallelic SNPs of at least 10% frequency and present in the data set at least three times for each group under analysis were considered, as rare alleles can have large variances in LD estimates. SNPs typed in <75% of the individuals in a group were excluded from analysis. Insertion/deletion polymorphisms were treated as missing data. We ran the LD analyses excluding the five elite cultivars and results were the same (data not shown).
We calculated the LD as the correlation coefficient r2 between each SNP pair (HARTL and CLARK 1997). Heterozygous SNPs were rare in O. sativa individuals (0.53% of SNP genotypes), but
6.7% of O. rufipogon SNP genotypes were heterozygotes. When only one SNP in a pair is heterozygous, it is possible to infer the haplotypes and calculate a r2 value. We excluded individuals from analysis if both SNPs in a pair were heterozygous so that only unambiguous haplotypes were used in the analysis. In the three O. sativa groups, very few SNP pairs contained doubly heterozygous individuals (2.59% in indica, 0.47% in tropical japonica, and 4.36% in temperate japonica) and were thus excluded. In the vast majority of these cases, only a single individual was heterozygous at both sites. In O. rufipogon, 24.5% of SNP pairs contained individuals with double heterozygotes, but the majority of these pairs (73.78%) had only a single doubly heterozygous individual to exclude. We also used the previously described STS data set (CAICEDO et al. 2007) to calculate the genomewide background LD, which is the level of disequilibrium between unlinked SNPs.
Due to the large amount of variance in the estimates of LD for any particular SNP pair, we combined SNP pairs into distance intervals to reduce the influence of outliers and to obtain a better visual description of the LD decay with distance. For the estimate of genomewide LD using the STS data set, the distance classes are <1 kb, 0.001–0.5 Mb, 0.5–2.0 Mb, and 2 Mb distance windows for SNP pairs >2 Mb in distance. For the study of the targeted genomic regions, a distance window of 40 kb was used. Due to our sampling scheme, the majority of SNP pairs in the genomic regions are close to the middle of the interval, so we plotted the median r2 for each distance window. We consider a particular intermarker distance interval to have LD elevated above the background level if it contains >10 SNP pairs and the interval median r2 exceeds the 75th percentile of the unlinked pairs. We chose the 75th percentile as a compromise between criteria that were too stringent and too relaxed. Clearly, the median of unlinked pairs is too low: by this criterion we would infer elevated LD for half of all intervals with LD at background levels. Given the great variance in LD values for any particular distance interval, there are bound to be pairs with low LD values, so requiring half of the pairs in a given interval to exceed the 95th percentile of unlinked pairs, for example, will only find evidence for LD that greatly exceeds genomewide background levels. We felt this was too stringent for our purposes.
Recombination analysis:
A composite-likelihood method (HUDSON 2001) as implemented in the LDhat software (MCVEAN et al. 2002) was used to estimate the population recombination parameter
= 4Ner for each target region. A likelihood permutation test was performed for each
estimate and the corresponding maximum-likelihood test for significant evidence of recombination. The minimum number of recombination events (HUDSON and KAPLAN 1985) was estimated across each target region using LDhat.
| RESULTS AND DISCUSSION |
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472 to
487 kb in length. In O. rufipogon, 1364 SNPs were identified, while 522 where found in the O. sativa variety group indica, 250 in tropical japonica, and 219 in temperate japonica.
Levels of nucleotide variation (
w) are given in Table 2. As expected, variation is greatest in O. rufipogon (average silent site
W = 0.0053) and lowest in temperate japonica (silent
w = 0.0010). The mean values of silent
W in indica and tropical japonica are 0.0023 and 0.0012, respectively. These are similar to the genomewide estimates of diversity reported in two previous studies (CAICEDO et al. 2007; RAKSHIT et al. 2007). The levels of nucleotide variation also differed widely among the six genomic regions; in indica, for example, silent variation ranged from a mean of
w = 0.0007–0.0046. In O. sativa, generally the A region had the lowest variation and the C region had the highest.
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0.04, while the 75th percentile for background LD (which we are using to define elevated LD) is
0.07–0.10 in all the studied genomes.
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LD decay in targeted genomic regions:
Data from the genomewide panel of 111 STS loci (CAICEDO et al. 2007) indicate that LD decays at <2 Mb for the O. sativa variety groups indica and tropical japonica and <500 kb for O. rufipogon. However, the STS data are fairly coarse grained, as the gene fragments are generally spaced apart at a megabase scale. We conducted a finer scale analysis of the extent of LD using five
500-kb regions (Figure 1), with gene fragment markers spaced
40 kb apart (Figure 2). One region (A) had very low variation in O. sativa (only two haplotypes in each variety group using SNPs that were frequent enough to be used for LD analysis) and thus was not considered in this analysis. Excluding SNPs in the A region, 423 in O. rufipogon, 262 in indica, 136 in tropical japonica, and 99 in temperate japonica had frequencies of at least 10%, were present in at least three copies, and were typed in at least 75% of the individuals in a group, making them suitable for assaying linkage disequilibrium.
The relationships of median r2 values with distance for each of these genomic regions are shown in supplemental Figure S1 at http://www.genetics.org/supplemental/. Variation in O. sativa is low (Table 2), and in many instances there are not a sufficient number of data points within each distance interval to draw strong conclusions for particular regions in particular groups. For example, the D region in temperate japonica and the B region in tropical japonica and temperate japonica each contained only a single biallelic SNP with a minor allele frequency >10%, so LD could not be assessed for these regions in these groups.
We combined the data from four genomic regions (regions B, D, E, and F) to estimate the average extent of LD within these different O. sativa variety groups and O. rufipogon (Figure 6). This does not weight each region equally, and regions with more data (for example, the F region) contribute more to the overall pattern. We did not include the data from genomic region C, since the pattern for this region appears atypical; LD in region C is only weakly correlated with intermarker distance and is exceptionally high in O. sativa: the median r2 values in the three O. sativa variety groups exceeds the 75th percentile for unlinked markers in all but one tropical japonica distance interval and four indica distance intervals. This region appears to have a large number of transposable elements. Although at the outset, attempts were made to exclude transposable elements, annotation updates of the rice genome during the course of this investigation meant that several flanking gene fragments in the C region were redone when annotation changed or sequencing demonstrated that more than one region was being amplified. New annotation since the conclusion of sequence indicates that three flanking gene fragments (5_01, 5_04, and 3_05) in the C region are putative transposable elements (see supplemental Table S2 at http://www.genetics.org/supplemental/). The atypical LD pattern (as well as high variation) in O. sativa may be explained by a high number of transposable elements in this region.
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75 and 150 kb. As with the genomewide sampling, there is low variation in temperate japonica, but the overall pattern in this group shows that LD extends to a much greater distance than in the other groups. For all distance intervals with >10 SNP pairs (out to the 200-kb distance interval), median r2 remains elevated above the 90th percentile of unlinked temperate japonica SNP pairs. It is likely that LD extends much farther, probably even to >500 kb in this O. sativa variety group.
Recombination and the decay of LD:
The lower bound on the number of recombination events (RM) and composite-likelihood estimates of
are given in Table 3. Recombination rates are quite low in both domesticated and wild rice. Across regions of
500 kb, RM varies between 0 and 22 and
estimates are <30 (0.06 x 10–3/bp) in all but two cases. Estimates of
in other plants are higher: 7–8 x 10–3/bp in wild barley (MORRELL et al. 2006),
16–19 x 10–3/bp in maize (TENAILLON et al. 2002), and 0.2–0.8 x 10–3/bp in Arabidopsis thaliana (NORDBORG et al. 2005; KIM et al. 2007). Effective population size, outcrossing rate, domestication, and demographic history all play a role in shaping
. It is therefore difficult to explain the exact species differences that give rise to different population recombination estimates, but some patterns are apparent. Maize utilizes an outcrossing mating system, consistent with higher estimates of the population recombination parameter. Although wild barley self-fertilizes at a very high rate (probably
98%), which decreases apparent recombination, the high
could be attributed perhaps to a recent transition to selfing (MORRELL et al. 2006). The estimate of
in A. thaliana is higher than in rice, but less dramatically higher than the other plant species considered here. A. thaliana shows signs of a population expansion (INNAN et al. 1997), increasing the opportunities for crossing over, which may elevate the recombination estimates despite an inbreeding mating system. Low rates of outcrossing in cultivated and wild rice and bottlenecks associated with domestication in cultivated rice likely explain the very low effective recombination rates detected. Although recombination is very low, for most regions in O. rufipogon and indica, rates are significantly different from zero.
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estimates.
In all five regions, O. rufipogon appears to have more recombination than the O. sativa groups, consistent with greater outcrossing rates (OKA 1988; GAO et al. 2007) and a larger effective population size (CAICEDO et al. 2007). O. rufipogon RM values are higher than O. sativa RM estimates, often to a great extent (as in region E). O. rufipogon
estimates are higher than either tropical or temperate japonica (or as in the case in region D, none of the three are significantly different from zero) and vary from 0 to >100. When comparing O. rufipogon and indica
estimates, O. rufipogon rates are not consistently greater, but due to the low overall variation,
cannot be precisely estimated from these data, and these estimates are not likely to be significantly different from each other.
Recombination breaks down LD, so the higher recombination rates in O. rufipogon explain the lower LD levels in this species compared to cultivated rice and, within O. sativa, lower recombination rates in tropical and temperate japonica as compared to the indica variety explain the greater extent of LD in the two japonica groups. As well as variation in recombination rates among varieties, rate heterogeneity is present among regions, likely because of recombination hotspots, as have been observed in humans (MCVEAN et al. 2004).
The extent of linkage disequilibrium in rice:
Both linkage disequilibrium and the high densities of SNPs have combined to facilitate a new genomics strategy for identifying and mapping genes responsible for quantitative trait variation (TERWILLIGER and WEISS 1998; KRUGLYAK 1999; JORDE 2000; REMINGTON et al. 2001; KIM et al. 2007). This mapping strategy, referred to as LD or association mapping, has been applied to humans (MARTIN et al. 2000; PUCA et al. 2001) Drosophila (LONG et al. 1998, 2000; GEIGER-THORNSBERRY and MACKAY 2002), and several plant species (THORNSBERRY et al. 2001; PALAISA et al. 2003; OLSEN et al. 2004; WILSON et al. 2004). There has been considerable interest in using LD mapping or candidate gene association studies in identifying genes underlying variation in agronomically important phenotypes (GARRIS et al. 2003; ROSTOKS et al. 2006; YU and BUCKLER 2006). The ability to detect significant associations between molecular polymorphism(s) and particular phenotypes, as well as the resolving power of LD mapping techniques, depends on knowledge of the extent of linkage disequilibrium in species genomes and the rate of decay of LD with physical distance (LONG et al. 1998; TERWILLIGER and WEISS 1998; KRUGLYAK 1999; JORDE 2000; PRITCHARD et al. 2000; REMINGTON et al. 2001).
We examined the levels of LD in cultivated rice in part to determine the level of resolution of LD mapping and candidate gene association studies in this important crop species. We found that the extent of linkage disequilibrium differs in significant ways between domesticated Asian rice and its wild ancestor O. rufipogon. Both in genomewide LD and in targeted genomic regions, there is substantially less LD in O. rufipogon compared to the O. sativa variety groups. The fact that O. rufipogon outcrosses at a higher rate than O. sativa, which we see for the most part reflected in higher recombination rates, and that both population bottlenecks and selection are associated with the domestication of the latter (CAICEDO et al. 2007) probably accounts for the difference in disequilibrium between the two species. In particular, the transition to selfing in O. sativa leads to a decrease in the effective recombination rate, while bottlenecks and selection will reduce the number of haplotypes in domesticated rice, all of which would inflate LD in the species. A similar pattern of greater LD in domesticated crops compared to their wild ancestors has been observed in several other crop species (e.g., barley) (REMINGTON et al. 2001; TENAILLON et al. 2001; CALDWELL et al. 2006; HYTEN et al. 2007), indicating that the process of domestication is a key force in the rise of LD in crop species.
Among the three variety groups, there is more LD in temperate japonica rice than in indica or tropical japonica. Temperate japonica is closely related to tropical japonica (KHUSH 1997; GARRIS et al. 2005), and the bottleneck associated with adaptation to the temperate environment resulted in a smaller effective population size compared to the other two rice groups (S. WILLIAMSON, unpublished results). Interestingly, the extent of LD in indica is less than that of tropical japonica, which may also arise from differences in the severity of the population bottleneck or the intensity of selection accompanying the domestication of these two groups. Modeling studies based on the nucleotide polymorphism site-frequency spectrum, for example, suggest a less severe bottleneck and less intense selection in indica compared to tropical japonica (S. WILLIAMSON and A. L. CAICEDO, unpublished results), which would also account for the greater extent of LD in the latter group.
Most studies to date in humans (HUTTLEY et al. 1999; GABRIEL et al. 2002) and maize (REMINGTON et al. 2001; TENAILLON et al. 2001) have documented variation in levels and patterns of LD across the genome, and our work in rice supports these observations in other species. Differences in recombination may account for this pattern, and for the most part we find that higher recombination rates are associated with regions and groups with lower linkage disequilibrium. The low number of targeted genomic regions that we used makes it difficult to draw strong inferences, but from our sample there appears to be a correlation between estimated recombination rate and extent of LD.
There appears to be a correspondence between levels of selfing and extent of LD in crop species. LD in maize, which is outcrossing, decays within 2 kb (REMINGTON et al. 2001; TENAILLON et al. 2001), while LD in sorghum, which has an outcrossing rate of 10–20%, can extend to 20 kb (HAMBLIN et al. 2005). Barley and soybean, which are both selfers, can have high LD levels that extend to several hundred kilobases (CALDWELL et al. 2006; HYTEN et al. 2007), a pattern similar to that for O. sativa. However, wild barley, which is also a selfer, has LD decay scales of only a few kilobases (MORRELL et al. 2005; CALDWELL et al. 2006), suggesting that the process of domestication may amplify the effects of self-fertilization, resulting in increasing LD levels across larger genomic regions in crop species.
These results provide insights into the possible resolution of LD mapping in domesticated rice. In maize, the short extent of LD allows association studies to localize SNPs that are significantly correlated to trait phenotypes to specific candidate genes, including those in flowering time (THORNSBERRY et al. 2001), starch content (WILSON et al. 2004), and kernel coloration (PALAISA et al. 2003). Rice has a greater extent of LD and thus candidate gene association studies may not be as successful. If we take 75 kb as the average resolution scale in indica and 150 kb in tropical japonica, this corresponds to genomic regions encompassing
9 to 17 genes, respectively. We should note, however, that these represent mean estimates of genomewide LD, and different genomic regions and groups do have different LD decay patterns (supplemental Figure S1 at http://www.genetics.org/supplemental/). The resolving power of LD mapping in rice thus will differ across genomic regions and population samples.
Nevertheless, our study suggests that a modest number of SNPs across the genome may be sufficient for undertaking genomewide LD mapping studies in rice. On the basis of the LD decay range in the O. sativa variety groups, LD mapping would be possible in indica and tropical japonica; in temperate japonica, there is too little polymorphism and the extent of LD is too large for this mapping approach to be readily feasible. It appears that placement of SNP markers every 75 kb for indica for a total of
5200 markers stands a reasonable chance of genomewide coverage in this variety group. For tropical japonica, markers can be placed
150 kb apart, and a total of 2600 markers can result in good coverage. Other approaches, such as the use of tag SNPs (CARLSON 2004) will require larger numbers of markers to achieve genomewide coverage, but more extensive resequencing is necessary to determine the tag-SNP densities required. It does appear, however, that rice association studies can be achieved with reasonable SNP marker densities and, given genotyping technologies, at relatively low cost.
| ACKNOWLEDGEMENTS |
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| FOOTNOTES |
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1 Present address: Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003. ![]()
2 Present address: Department of Biology, University of Massachusetts, Amherst, MA 01001. ![]()
3 Present address: Department of Biology, Pennsylvania State University, University Park, PA 16802. ![]()
4 Present address: Department of Biology, Washington University, St. Louis, MO 63130-4899. ![]()
| LITERATURE CITED |
|---|
|
|
|---|
CAICEDO, A., S. WILLIAMSON, R. D. HERNANDEZ, A. BOYKO, A. FLEDEL-ALON et al., 2007 Genome-wide patterns of nucleotide polymorphism in domesticated rice. PLoS Genet. 3: e163.[CrossRef]
CALDWELL, K. S., J. RUSSELL, P. LANGRIDGE and W. POWELL, 2006 Extreme population-dependent linkage disequilibrium detected in an inbreeding plant species, Hordeum vulgare. Genetics 172: 557–567.
CARLSON, C. S., M. A. EBERLE, M. J. RIEDER, Q. YI, L. KRUGLYAK et al., 2004 Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am. J. Hum. Genet. 74: 106–120.[CrossRef][Medline]
CRAWFORD, G. W., and S. CHEN, 1998 The origins of rice agriculture: recent progress in East Asia. Antiquity 72: 858–866.
FENG, Q., Y. ZHANG, P. HAO, S. WANG, G. FU et al., 2002 Sequence and analysis of rice chromosome 4. Nature 420: 316–320.[CrossRef][Medline]
GABRIEL, S. B., S. F. SCHAFFNER, H. NGUYEN, J. M. MOORE, J. ROY et al., 2002 The structure of haplotype blocks in the human genome. Science 296: 2225–2229.
GAO, H., S. WILLIAMSON and C. D. BUSTAMANTE, 2007 A Markov chain Monte Carlo approach for joint inference of population structure and inbreeding rates from multilocus genotype data. Genetics 176: 1635–1651.
GARRIS, A. J., S. R. MCCOUCH and S. KRESOVICH, 2003 Population structure and its effect on haplotype diversity and linkage disequilibrium surrounding the xa5 locus of rice (Oryza sativa L.). Genetics 165: 759–769.
GARRIS, A. J., T. H. TAI, J. COBURN, S. KRESOVICH and S. MCCOUCH, 2005 Genetic structure and diversity in Oryza sativa L. Genetics 169: 1631–1638.
GEIGER-THORNSBERRY, G. L., and T. F. MACKAY, 2002 Association of single-nucleotide polymorphisms at the Delta locus with genotype by environment interaction for sensory bristle number in Drosophila melanogaster. Genet. Res. 79: 211–218.[CrossRef][Medline]
HAMBLIN, M. T., M. G. SALAS FERNANDEZ, A. M. CASA, S. E. MITCHELL, A. H. PATERSON et al., 2005 Equilibrium processes cannot explain high levels of short- and medium-range linkage disequilibrium in the domesticated grass Sorghum bicolor. Genetics 171: 1247–1256.
HARTL, D. L., and A. G. CLARK, 1997 Principles of Population Genetics. Sinauer Associates, Sunderland, MA.
HUDSON, R. R., 2001 Two-locus sampling distributions and their application. Genetics 159: 1805–1817.
HUDSON, R. R., and N. L. KAPLAN, 1985 Statistical properties of the number of recombination events in the history of a sample of DNA sequences. Genetics 111: 147–164.
HUTTLEY, G. A., M. W. SMITH, M. CARRINGTON and S. J. O'BRIEN, 1999 A scan for linkage disequilibrium across the human genome. Genetics 152: 1711–1722.
HYTEN, D. L., I.-Y. CHOI, Q. SONG, R. C. SHOEMAKER, R. L. NELSON et al., 2007 Highly variable patterns of linkage disequilibrium in multiple soybean populations. Genetics 175: 1937–1944.
INNAN, H., R. TERAUCHI and N. T. MIYASHITA, 1997 Microsatellite polymorphism in natural populations of the wild plant Arabidopsis thaliana. Genetics 146: 1441–1452.[Abstract]
INTERNATIONAL RICE GENOME SEQUENCING PROJECT, 2005 The map-based sequence of the rice genome. Nature 436: 793–800.[CrossRef][Medline]
JORDE, L. B., 2000 Linkage disequilibrium and the search for complex disease genes. Genome Res. 10: 1435–1444.
KHUSH, G. S., 1997 Origin, dispersal, cultivation and variation of rice. Plant Mol. Biol. 35: 25–34.[CrossRef][Medline]
KIM, S., V. PLAGNOL, T. T. HU, C. TOOMAJIAN, R. M. CLARK et al., 2007 Recombination and linkage disequilibrium in Arabidopsis thaliana. Nat. Genet. 39: 1151–1155.[CrossRef][Medline]
KRUGLYAK, L., 1999 Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nat. Genet. 22: 139–144.[CrossRef][Medline]
LONG, A. D., R. F. LYMAN, C. H. LANGLEY and T. F. MACKAY, 1998 Two sites in the Delta gene region contribute to naturally occurring variation in bristle number in Drosophila melanogaster. Genetics 149: 999–1017.
LONG, A. D., R. F. LYMAN, A. H. MORGAN, C. H. LANGLEY and T. F. MACKAY, 2000 Both naturally occurring insertions of transposable elements and intermediate frequency polymorphisms at the achaete-scute complex are associated with variation in bristle number in Drosophila melanogaster. Genetics 154: 1255–1269.
MARTIN, E. R., J. R. GILBERT, E. H. LAI, J. RILEY, A. R. ROGALA et al., 2000 Analysis of association at single nucleotide polymorphisms in the APOE region. Genomics 63: 7–12.[CrossRef][Medline]
MCVEAN, G., P. AWADALLA and P. FEARNHEAD, 2002 A coalescent-based method for detecting and estimating recombination from gene sequences. Genetics 160: 1231–1241.
MCVEAN, G. A., S. R. MYERS, S. HUNT, P. DELOUKAS, D. R. BENTLEY et al., 2004 The fine-scale structure of recombination rate variation in the human genome. Science 304: 581–584.
MORRELL, P. L., D. M. TOLENO, K. E. LUNDY and M. T. CLEGG, 2005 Low levels of linkage disequilibrium in wild barley (Hordeum vulgare ssp. spontaneum) despite high rates of self-fertilization. Proc. Natl. Acad. Sci. USA 102: 2442–2447.
MORRELL, P. L., D. M. TOLENO, K. E. LUNDY and M. T. CLEGG, 2006 Estimating the contribution of mutation, recombination and gene conversion in the generation of haplotypic diversity. Genetics 173: 1705–1723.
NORDBORG, M., T. T. HU, Y. ISHINO, J. JHAVERI, C. TOOMAJIAN et al., 2005 The pattern of polymorphism in Arabidopsis thaliana. PLoS Biol. 3: e196.[CrossRef][Medline]
OKA, H. I., 1988 Origin of Cultivated Rice. Elsevier, Amsterdam.
OLSEN, K. M., S. S. HALLDORSDOTTIR, J. R. STINCHCOMBE, C. WEINIG, J. SCHMITT et al., 2004 Linkage disequilibrium mapping of Arabidopsis CRY2 flowering time alleles. Genetics 167: 1361–1369.
OLSEN, K. M., A. L. CAICEDO, N. POLATO, A. MCCLUNG, S. MCCOUCH et al., 2006 Selection under domestication: evidence for a sweep in the rice Waxy genomic region. Genetics 173: 975–983.
PALAISA, K., M. MORGANTE, M. WILLIAMS and A. RAFALSKI, 2003 Contrasting effects of selection on sequence diversity and linkage disequilibrium at two phytoene synthase loci. Plant Cell 15: 1795–1806.
PRITCHARD, J. K., M. STEPHENS and P. DONNELLY, 2000 Inference of population structure using multilocus genotype data. Genetics 155: 945–959.
PUCA, A. A., M. J. DALY, S. J. BREWSTER, T. C. MATISE, J. BARRETT et al., 2001 A genome-wide scan for linkage to human exceptional longevity identifies a locus on chromosome 4. Proc. Natl. Acad. Sci. USA 98: 10505–10508.
RAKSHIT, S., A. RAKSHIT, H. MATSUMURA, Y. TAKAHASHI, Y. HASEGAWA et al., 2007 Large-scale DNA polymorphism study of Oryza sativa and O. rufipogon reveals the origin and divergence of Asian rice. Theor. Appl. Genet. 114: 731–743.[CrossRef][Medline]
REMINGTON, D. L., J. M. THORNSBERRY, Y. MATSUOKA, L. M. WILSON, S. R. WHITT et al., 2001 Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc. Natl. Acad. Sci. USA 98: 11479–11484.
ROSTOKS, N., L. RAMSAY, K. MACKENZIE, L. CARDLE, P. R. BHAT et al., 2006 Recent history of artificial outcrossing facilitates whole-genome association mapping in elite inbred crop varieties. Proc. Natl. Acad. Sci. USA 103: 18656–18661.
ROZEN, S., and H. J. SKALETSKY, 2000 Primer3 on the WWW for general users and for biologist programmers, pp. 365–386 in Bioinformatics Methods and Protocols: Methods in Molecular Biology, edited by S. MISENER and S. KRAWETZ. Humana Press, Totowa, NJ.
SASAKI, T., T. MATSUMOTO, K. YAMAMOTO, K. SAKATA, T. BABA et al., 2002 The genome sequence and structure of rice chromosome 1. Nature 420: 312–316.[CrossRef][Medline]
TENAILLON, M. I., M. C. SAWKINS, A. D. LONG, R. L. GAUT, J. F. DOEBLEY et al., 2001 Patterns of DNA sequence polymorphism along chromosome 1 of maize (Zea mays ssp. mays L.). Proc. Natl. Acad. Sci. USA 98: 9161–9166.
TENAILLON, M. I., M. C. SAWKINS, L. K. ANDERSON, S. M. STACK, J. DOEBLEY et al., 2002 Patterns of diversity and recombination along chromosome 1 of maize (Zea mays ssp. mays L.). Genetics 162: 1401–1413.
TERWILLIGER, J. D., and K. M. WEISS, 1998 Linkage disequilibrium mapping of complex disease: Fantasy or reality? Curr. Opin. Biotechnol. 9: 578–594.[CrossRef][Medline]
THORNSBERRY, J. M., M. M. GOODMAN, J. DOEBLEY, S. KRESOVICH, D. NIELSEN et al., 2001 Dwarf8 polymorphisms associate with variation in flowering time. Nat. Genet. 28: 286–289.[CrossRef][Medline]
WATTERSON, G. A., 1975 On the number of segregating sites in genetical models without recombination. Theor. Popul. Biol. 7: 256–276.[CrossRef][Medline]
WILSON, L. M., S. R. WHITT, A. M. IBANEZ, T. R. ROCHEFORD, M. M. GOODMAN et al., 2004 Dissection of maize kernel composition and starch production by candidate gene association. Plant Cell 16: 2719–2733.
YU, J., and E. S. BUCKLER, 2006 Genetic association mapping and genome organization of maize. Curr. Opin. Biotechnol. 17: 155–160.[Medline]
YU, J., S. HU, J. WANG, G. K. WONG, S. LI et al., 2002 A draft sequence of the rice genome (Oryza sativa L. ssp. indica). Science 296: 79–92.
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