A Mapping Function for Man

Rao, D. C.; Morton, N.E.; Lindsten, J.; Hultén, Maj; Yee, Shirley J.

doi:10.1159/000152856

Cited by 84 publications

(51 citation statements)

References 7 publications

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“…For small chromosomes, the parameter estimates for the p arms tend to be higher than those for the q arms, but they have a great deal more variability, thus the two interval estimates overlap for all the chromosomes where estimates for both arms are available. However, we caution that this should not be viewed as contradictory to the results in Forabosco et al (1995), whose data suggested different levels of interference between the p arm and the q arm of chromosome 1 using Rao's map function (Rao et al 1977). There are several possible explanations for the discrepancy between the results from our analysis and theirs.…”

Section: contrasting

confidence: 92%

Genetic crossover interference in the human genome

Lin

Cheng

Wright

2001

Annals of Human Genetics

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Positive crossover interference refers to the phenomenon that the occurrence of a crossover reduces the probability of another crossover in its vicinity. There have been studies reporting the presence of positive interference in humans. Some studies have also found evidence suggesting within and between chromosomal interference heterogeneity on some of the chromosomes. However, there has been no systematic study of interference and interference heterogeneity in the whole human genome, using pedigree data without first inferring crossovers. In this paper, we studied the Chi-square interference model and other models extensively to compare the relative performance of each of these models for accounting for interference and measuring strength of interference. Our results showed that the Chi-square model consistently fitted the data well and provided easily interpretable estimates of interference strength. The Chi-square model was then used to study interference and interference heterogeneity within and between chromosomes. We found strong evidence of positive interference in the whole human genome. Our results also indicated that the level of interference was fairly constant in most parts of the genome, but there was some evidence suggesting that the levels of interference for two of the chromosomes were different from the rest. We also found evidence of within chromosomal interference heterogeneity for several of the chromosomes. Crossover interference refers to the phenomenon that crossovers in nearby intervals along a chromosome do not occur independently. When the occurrence of a crossover reduces the probability of another crossover in its vicinity, this type of crossover interference is termed positive interference. There have been studies suggesting the presence of positive interference in humans, and the evidence grows with the availability of densely mapped markers (see e.g. Kwiatkowski et

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Section: contrasting

confidence: 92%

Genetic crossover interference in the human genome

Lin

Cheng

Wright

2001

Annals of Human Genetics

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“…In the genetic map we estimated the interference parameter p in the Rao (1977) mapping function at 0.28 and typing error frequency E at 0.004 (Shields et al 1991) for the sequence order constrained map. The sex-averaged map length ( Fig.…”

Section: Resultsmentioning

confidence: 99%

A Sequence-Based Integrated Map of Chromosome 22

Tapper

Morton²,

Dunham³

et al. 2001

Genome Res.

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The near-completion of the sequence for chromosome 22q revolutionizes map integration. We describe a sequence-based integrated map containing 968 loci including 516 known or predicted gene sequences, 317 STSs not included in these sequences, and 135 nonexpressed multinucleotide polymorphisms. The published sequence spans 34.6 Mb, inclusive of gaps estimated to total 1.1 Mb, compared with a top-down estimate of 43 Mb. This discrepancy is discussed, but will not be resolved until more of the genome is analyzed. The radiation hybrid map has 5% error in order and 34% error in location exceeding 1 Mb. The utility of a composite location based on evidence other than sequence is limited to regions not yet sequenced. A genetic map conditional on sequence order was constructed from pairwise lods. Its length of 74.8 cM in males and 80.2 cM in females is slightly less than the previous estimate not constrained by sequence order. Five recombination hot spots are detected, with differences in location between the sexes. Male recombination correlates with repetitive

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“…Computer programs in common use for constructing linkage maps assume no chiasma interference for the computation of multilocus likelihoods and may then convert the resulting map to approximate conformity with the Kosambi function, which is not multipoint feasible. Studies of chiasma interference in humans have shown that it exists at greater levels than the Kosambi function provides and appears to vary among chromosomes (19)(20)(21). The estimate of t is significantly lower for smaller autosomes (Fig.…”

Section: Unexpected Variation In Estimates Of Effective Bottleneck Timementioning

confidence: 99%

A map of the human genome in linkage disequilibrium units

Tapper

Collins²,

Gibson³

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

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Two genetic maps with additive distances contribute information about recombination patterns, recombinogenic sequences, and discovery of genes affecting a particular phenotype. Recombination is measured in morgans (w) over a single generation in a linkage map but may cover thousands of generations in a linkage disequilibrium (LD) map measured in LD units (LDU). We used a subset of single nucleotide polymorphisms from the HapMap Project to create a genome-wide map in LDU. Recombination accounts for 96.8% of the LDU variance in chromosome arms and 92.4% in their deciles. However, deeper analysis shows that LDU͞w, an estimate of the effective bottleneck time (t), is significantly variable among chromosome arms because (i) the linkage map is approximated from the Haldane function, then adjusted toward the Kosambi function that is more accurate but still exaggerates w for all chromosomes, especially shorter ones; (ii) the nonpseudoautosomal region of the X chromosome is subject to hemizygous selection; and (iii) at resolution less than Ϸ40,000 markers per w, there are indeterminacies (holes) in the LD map reflecting intervals of very high recombination. Selection and stochastic variation in small regions must have effects, which remain to be investigated by comparisons among populations. These considerations suggest an optimal strategy to eliminate holes quickly, greatly enhance the resolution of sex-specific linkage maps, and maximize the gain in association mapping by using LD maps.effective bottleneck time ͉ HapMap ͉ recombination ͉ interference ͉ selection A linkage map with 14,759 polymorphic markers has recently been published, far exceeding the density and coverage of earlier maps (1). Although the human genome sequence facilitated construction of this genetic map by determining the physical order of its markers, 56% of its intervals have recombination rates of zero. This observation demonstrates the relatively low resolution of the linkage map, for which a costly solution would be the analysis of many more pedigrees and markers. Alternatively, sperm typing offers recombination data of the highest resolution currently available (2) but is feasible only for very small regions in male chromosomes and does not reflect historical recombination events. Using the HapMap data (3) to construct linkage disequilibrium (LD) maps measured in LD units (LDU) (4) and interpolating them into the sex-specific linkage map enhances the resolution of the linkage map as a by-product of our main objective, which is to construct genomewide LD maps with additive LDU distances. Such maps are applicable to association mapping (5, 6), population comparisons (7-9), and identification of genomic regions that are influenced by selection (10). LD mapping has begun the task of explaining and exploiting complexities (8) that do not affect application of the Malecot model (4) to create an LD map but determine how the map should be used to increase resolution of the linkage map. LD Map Construction. LD maps were constructed by the methods in th...

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A Mapping Function for Man

Cited by 84 publications

References 7 publications

Genetic crossover interference in the human genome

Genetic crossover interference in the human genome

A Sequence-Based Integrated Map of Chromosome 22

A map of the human genome in linkage disequilibrium units

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