A Modified Algorithm for the Improvement of Composite Interval Mapping

Li, Huihui; Ye, Guoyou; Wang, Jiankang

doi:10.1534/genetics.106.066811

Cited by 726 publications

(499 citation statements)

References 32 publications

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“…Dominance effects could not be tested in the backcross design of this experiment. Epistatic interactions between additive effects were analyzed in ICIM (Li et al 2007), which detects interactions between QTL with insignificant main effects.…”

Section: Qtl Analysismentioning

confidence: 99%

QTL involved in the partial restoration of male fertility of C-type cytoplasmic male sterility in maize

et al. 2011

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Partial restoration of male fertility limits the use of C-type cytoplasmic male sterility (C-CMS) for the production of hybrid seeds in maize. Nevertheless, the genetic basis of the trait is still unknown. Therefore, the aim to this study was to identify genomic regions that govern partial restoration by means of a QTL analysis carried out in an F 2 population (n = 180). This population was derived from the Corn Belt inbred lines B37C and K55. F 2 BC 1 progenies were phenotyped at three locations in Switzerland. Male fertility was rated according to the quality and number of anthers as well as the anthesis-silking interval. A weak effect of environment on the expression of partial restoration was reflected by high heritabilities of all fertility-related traits. Partial restoration was inherited like an oligogenic trait. Three major QTL regions were found consistently across environments in the chromosomal bins 2.09, 3.06 and 7.03. Therefore, a marker-assisted counter-selection of partial restoration is promising. Minor QTL regions were found on chromosomes 3, 4, 5, 6 and 8. A combination of partial restorer alleles at different QTL can lead to full restoration of fertility. The maternal parent was clearly involved in the partial restoration, because the restorer alleles at QTL in bins 2.09, 6.04 and 7.03 originated from B37. The three major QTL regions collocated with other restorer genes of maize, a phenomenon, which seems to be typical for restorer genes. Therefore, a study of the clusters of restorer genes in maize could lead to a better understanding of their evolution and function. In this respect, the long arm of chromosome 2 is particularly interesting, because it harbors restorer genes for the three major CMS systems (C, T and S) of maize.

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Section: Qtl Analysismentioning

confidence: 99%

QTL involved in the partial restoration of male fertility of C-type cytoplasmic male sterility in maize

et al. 2011

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“…We used the software ICIMapping (Li et al 2007) with a LOD score of 9 for grouping the markers, the Traveling Salesman algorithm for ordering, and a window size of 5 cM for rippling the linkage groups. Linkage groups having less than three markers or markers with no linkage where discarded from the analysis (altogether three out of 25).…”

Section: Genotypingmentioning

confidence: 99%

Mapping resistance to the bird cherry-oat aphid and the greenbug in wheat using sequence-based genotyping

et al. 2014

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“…In comparison with association mapping, QTL linkage mapping in animals and humans is normally based on pedigree data, but in plants it is more often based on biparental genetic populations. Statistical methods for QTL linkage mapping have been extensively studied (Lander and Botstein, 1989;Darvasi et al, 1993;Zeng, 1994;Whittaker et al, 1996;Piepho, 2000;Sen and Churchill, 2001;Xu, 2003;Bogdan and Doerge, 2005;Li et al, 2007;Wang, 2009), and composite interval mapping (CIM) proposed by Zeng (1994) represents one of the most commonly used methods.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Li et al (2007) found that CIM resulted in biased mapping results because of the simultaneous estimation of QTL and background effects in the implementation algorithm. Inclusive composite interval mapping (ICIM) was then proposed (Li et al, 2007;Wang, 2009) to deal with this problem while retaining other advantages related to CIM.…”

Section: Introductionmentioning

confidence: 99%

“…Inclusive composite interval mapping (ICIM) was then proposed (Li et al, 2007;Wang, 2009) to deal with this problem while retaining other advantages related to CIM. Major advantages of ICIM were summarized as follows: (1) ICIM controls the sampling variance better; (2) it makes the background marker selection process easier and simpler; (3) it gives clearly high logarithm of the odds (LOD) scores at chromosomal regions with QTL but rather low LOD scores (that is, close to 0) in which no QTLs are located, thereby increasing mapping power and decreasing the false discovery rate (FDR); (4) it is robust for mapping parameters; (5) it can be extended to map digenic epistatic QTLs regardless of whether the two interacting QTLs have significant additive effects or not; and (6) the expectation and maximization (EM) algorithm used in ICIM has a high convergence speed and is therefore less computing intensive (Li et al, 2007Zhang et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Statistical properties of QTL linkage mapping in biparental genetic populations

et al. 2010

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Quantitative trait gene or locus (QTL) mapping is routinely used in genetic analysis of complex traits. Especially in practical breeding programs, questions remain such as how large a population and what level of marker density are needed to detect QTLs that are useful to breeders, and how likely it is that the target QTL will be detected with the data set in hand. Some answers can be found in studies on conventional interval mapping (IM). However, it is not clear whether the conclusions obtained from IM are the same as those obtained using other methods. Inclusive composite interval mapping (ICIM) is a useful step forward that highlights the importance of model selection and interval testing in QTL linkage mapping. In this study, we investigate the statistical properties of ICIM compared with IM through simulation. Results indicate that IM is less responsive to marker density and population size (PS). The increase in marker density helps ICIM identify independent QTLs explaining 45% of phenotypic variance. When PS is 4200, ICIM achieves unbiased estimations of QTL position and effect. For smaller PS, there is a tendency for the QTL to be located toward the center of the chromosome, with its effect overestimated. The use of dense markers makes linked QTL isolated by empty marker intervals and thus improves mapping efficiency. However, only large-sized populations can take advantage of densely distributed markers. These findings are different from those previously found in IM, indicating great improvements with ICIM.

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A Modified Algorithm for the Improvement of Composite Interval Mapping

Cited by 726 publications

References 32 publications

QTL involved in the partial restoration of male fertility of C-type cytoplasmic male sterility in maize

QTL involved in the partial restoration of male fertility of C-type cytoplasmic male sterility in maize

Mapping resistance to the bird cherry-oat aphid and the greenbug in wheat using sequence-based genotyping

Statistical properties of QTL linkage mapping in biparental genetic populations

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