Improving QTL Mapping Resolution Based on Genotypic Sampling—a Case Using a RIL Population

Yan, Jianbing; Tang, Jihua; Meng, Yijiang; Ma, Xiqing; Teng, Wen-Tao; Chander, Subhash; Lin, Li; Li, Jiansheng

doi:10.1016/s0379-4172(06)60091-7

Cited by 8 publications

(4 citation statements)

References 8 publications

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“…Once the associated regions are identified, further mapping or map-based cloning can be pursued to identify markers more closely linked to genes. The major disadvantage of mapping genes from a smaller number of individuals is that the associations detected using a smaller sized population sometimes is not representative (Yan et al 2006). Thus, QTL cannot be confirmed using a larger number of individuals.…”

Section: Discussionmentioning

confidence: 99%

Selection of a core set of RILs from Forrest × Williams 82 to develop a framework map in soybean

Vuong

Leroy

et al. 2011

Theor Appl Genet

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Soybean BAC-based physical maps provide a useful platform for gene and QTL map-based cloning, EST mapping, marker development, genome sequencing, and comparative genomic research. Soybean physical maps for “Forrest” and “Williams 82” representing the southern and northern US soybean germplasm base, respectively, have been constructed with different fingerprinting methods. These physical maps are complementary for coverage of gaps on the 20 soybean linkage groups. More than 5,000 genetic markers have been anchored onto the Williams 82 physical map, but only a limited number of markers have been anchored to the Forrest physical map. A mapping population of Forrest × Williams 82 made up of 1,025 F8 recombinant inbred lines (RILs) was used to construct a reference genetic map. A framework map with almost 1,000 genetic markers was constructed using a core set of these RILs. The core set of the population was evaluated with the theoretical population using equality, symmetry and representativeness tests. A high-resolution genetic map will allow integration and utilization of the physical maps to target QTL regions of interest, and to place a larger number of markers into a map in a more efficient way using a core set of RILs.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-010-1522-3) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Selection of a core set of RILs from Forrest × Williams 82 to develop a framework map in soybean

Vuong

Leroy

et al. 2011

Theor Appl Genet

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“…Egg-to-adult survival was successfully scored for four replicates in 49 lines (30 lines RIL-D48 and 19 lines RIL-SH2). Although the number of contrasting RIL can limit our statistical power (i.e., allowing only the detection of large-effect QTL), this issue was partially improved because two reciprocal sets of RIL were used (i.e., from the two reciprocal backcrosses, as mentioned above), and because RIL were constructed from selected populations (Yan et al, 2006).…”

Section: Egg-to-adult Survivalmentioning

confidence: 99%

Genetic variation for egg‐to‐adult survival in Drosophila melanogaster in a set of recombinant inbred lines reared under heat stress in a natural thermal environment

Borda

Sambucetti

Gómez

et al. 2018

Entomologia Exp Applicata

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Quantitative trait loci (QTL) for thermotolerance were previously identified for adult flies in several mapping populations of Drosophila melanogaster Meigen (Diptera: Drosophilidae) in the laboratory. However, laboratory assays may not necessarily reflect the performance under heat stress in the field. For instance, do the heat‐resistance QTL regions in the field match the QTL for thermotolerance in laboratory studies? To address this and related questions we used a set of recombinant inbred lines (RIL), which were originally used to identify QTL in the laboratory. We tested egg‐to‐adult survival (EAS) QTL in a field experiment under naturally varying heat‐stress temperatures in fly cultures reared on a rotting fruit (banana) in summer. EAS under heat stress was found to be 3–6× lower (depending on RIL) in the field than in the corresponding control at benign temperature (25 °C). Five QTL for EAS were significant in the field experiment under heat stress, four of them co‐located with plasticity QTL, and none of the QTL was significant at control temperature. All significant QTL overlapped (co‐localized) with thermotolerance QTL previously identified in the laboratory. A previously found QTL in the middle of chromosome 2 explained near 30% of the phenotypic variance in EAS under heat stress in previous studies in the laboratory, but this QTL explained only 8% of the EAS variation in our field assay. The largest effect on EAS was found for an X‐linked QTL (cytological range 7B3‐10C3) in the heat‐stress field experiment, explaining a high percentage (14–45%) of the phenotypic variation in EAS. The ecological relevance of QTL implicated in this study is discussed.

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“…Such selective phenotyping approaches sample the population in a way that minimizes segregation distortion while maximizing global recombination rate, thereby increasing both power and precision on a per line basis (de Koning et al, 2007). Indeed, the power of eQTL detection can be increased if a subset of the population is chosen for its genetic dissimilarity without a commensurate decrease in mapping power (Yan et al, 2006). Another appealing approach is to select two different subsets of the population for two different treatments (Li et al, 2008).…”

Section: Challenges To Designing Executing and Analyzing An Eqtl Exmentioning

confidence: 99%

Prospects for advancing defense to cereal rusts through genetical genomics

Ballini¹,

Lauter²,

Wise³

2013

Front. Plant Sci.

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Rusts are one of the most severe threats to cereal crops because new pathogen races emerge regularly, resulting in infestations that lead to large yield losses. In 1999, a new race of stem rust, Puccinia graminis f. sp. tritici (Pgt TTKSK or Ug99), was discovered in Uganda. Most of the wheat and barley cultivars grown currently worldwide are susceptible to this new race. Pgt TTKSK has already spread northward into Iran and will likely spread eastward throughout the Indian subcontinent in the near future. This scenario is not unique to stem rust; new races of leaf rust (Puccinia triticina) and stripe rust (Puccinia striiformis) have also emerged recently. One strategy for countering the persistent adaptability of these pathogens is to stack complete- and partial-resistance genes, which requires significant breeding efforts in order to reduce deleterious effects of linkage drag. These varied resistance combinations are typically more difficult for the pathogen to defeat, since they would be predicted to apply lower selection pressure. Genetical genomics or expression Quantitative Trait Locus (eQTL) analysis enables the identification of regulatory loci that control the expression of many to hundreds of genes. Integrated deployment of these technologies coupled with efficient phenotyping offers significant potential to elucidate the regulatory nodes in genetic networks that orchestrate host defense responses. The focus of this review will be to present advances in genetical genomic experimental designs and analysis, particularly as they apply to the prospects for discovering partial disease resistance alleles in cereals.

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Improving QTL Mapping Resolution Based on Genotypic Sampling—a Case Using a RIL Population

Cited by 8 publications

References 8 publications

Selection of a core set of RILs from Forrest × Williams 82 to develop a framework map in soybean

Selection of a core set of RILs from Forrest × Williams 82 to develop a framework map in soybean

Genetic variation for egg‐to‐adult survival in Drosophila melanogaster in a set of recombinant inbred lines reared under heat stress in a natural thermal environment

Prospects for advancing defense to cereal rusts through genetical genomics

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