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BMC Plant Biology (1)
PLoS Genetics (1)
PLoS ONE (1)
Scarcelli, Nora (3)
Vigouroux, Yves (2)
Baco, Mohamed N (1)
Barnaud, Adeline (1)
Couderc, Marie (1)
Durrant, Caroline (1)
Egah, Janvier (1)
Ehrenreich, Ian M. (1)
Eiserhardt, Wolf (1)
Kover, Paula X. (1)
Mott, Richard (1)
Pintaud, Jean-Christophe (1)
Purugganan, Michael D. (1)
Seveno, Marie (1)
Trakalo, Joseph (1)
Treier, Urs A. (1)
Valdar, William (1)
d'Anfray, Amélie (1)
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Clonal diversity and estimation of relative clone age: application to agrobiodiversity of yam (Dioscorea rotundata)
Baco, Mohamed N
BMC Plant Biology
Clonal propagation is a particular reproductive system found in both the plant and animal kingdoms, from human parasites to clonally propagated crops. Clonal diversity provides information about plant and animal evolutionary history, i.e. how clones spread, or the age of a particular clone. In plants, this could provide valuable information about agrobiodiversity dynamics and more broadly about the evolutionary history of a particular crop. We studied the evolutionary history of yam, Dioscorea rotundata. In Africa, Yam is cultivated by tuber clonal propagation.
We used 12 microsatellite markers to identify intra-clonal diversity in yam varieties. We then used this diversity to assess the relative ages of clones. Using simulations, we assessed how Approximate Bayesian Computation could use clonal diversity to estimate the age of a clone depending on the size of the sample, the number of independent samples and the number of markers. We then applied this approach to our particular dataset and showed that the relative ages of varieties could be estimated, and that each variety could be ranked by age.
We give a first estimation of clone age in an approximate Bayesian framework. However the precise estimation of clone age depends on the precision of the mutation rate. We provide useful information on agrobiodiversity dynamics and suggest recurrent creation of varietal diversity in a clonally propagated crop.
Approximate Bayesian Computation; Clone; Diversity; Mutation; Yam
A Set of 100 Chloroplast DNA Primer Pairs to Study Population Genetics and Phylogeny in Monocotyledons
Treier, Urs A.
Chloroplast DNA sequences are of great interest for population genetics and phylogenetic studies. However, only a small set of markers are commonly used. Most of them have been designed for amplification in a large range of Angiosperms and are located in the Large Single Copy (LSC). Here we developed a new set of 100 primer pairs optimized for amplification in Monocotyledons. Primer pairs amplify coding (exon) and non-coding regions (intron and intergenic spacer). They span the different chloroplast regions: 72 are located in the LSC, 13 in the Small Single Copy (SSC) and 15 in the Inverted Repeat region (IR). Amplification and sequencing were tested in 13 species of Monocotyledons: Dioscorea abyssinica, D. praehensilis, D. rotundata, D. dumetorum, D. bulbifera, Trichopus sempervirens (Dioscoreaceae), Phoenix canariensis, P. dactylifera, Astrocaryum scopatum, A. murumuru, Ceroxylon echinulatum (Arecaceae), Digitaria excilis and Pennisetum glaucum (Poaceae). The diversity found in Dioscorea, Digitaria and Pennisetum mainly corresponded to Single Nucleotide Polymorphism (SNP) while the diversity found in Arecaceae also comprises Variable Number Tandem Repeat (VNTR). We observed that the most variable loci (rps15-ycf1, rpl32-ccsA, ndhF-rpl32, ndhG-ndhI and ccsA) are located in the SSC. Through the analysis of the genetic structure of a wild-cultivated species complex in Dioscorea, we demonstrated that this new set of primers is of great interest for population genetics and we anticipate that it will also be useful for phylogeny and bar-coding studies.
A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana
Kover, Paula X.
Ehrenreich, Ian M.
Purugganan, Michael D.
Identifying natural allelic variation that underlies quantitative trait variation remains a fundamental problem in genetics. Most studies have employed either simple synthetic populations with restricted allelic variation or performed association mapping on a sample of naturally occurring haplotypes. Both of these approaches have some limitations, therefore alternative resources for the genetic dissection of complex traits continue to be sought. Here we describe one such alternative, the Multiparent Advanced Generation Inter-Cross (MAGIC). This approach is expected to improve the precision with which QTL can be mapped, improving the outlook for QTL cloning. Here, we present the first panel of MAGIC lines developed: a set of 527 recombinant inbred lines (RILs) descended from a heterogeneous stock of 19 intermated accessions of the plant Arabidopsis thaliana. These lines and the 19 founders were genotyped with 1,260 single nucleotide polymorphisms and phenotyped for development-related traits. Analytical methods were developed to fine-map quantitative trait loci (QTL) in the MAGIC lines by reconstructing the genome of each line as a mosaic of the founders. We show by simulation that QTL explaining 10% of the phenotypic variance will be detected in most situations with an average mapping error of about 300 kb, and that if the number of lines were doubled the mapping error would be under 200 kb. We also show how the power to detect a QTL and the mapping accuracy vary, depending on QTL location. We demonstrate the utility of this new mapping population by mapping several known QTL with high precision and by finding novel QTL for germination data and bolting time. Our results provide strong support for similar ongoing efforts to produce MAGIC lines in other organisms.
Most traits of economic and evolutionary interest vary quantitatively and have multiple genes affecting their expression. Dissecting the genetic basis of such traits is crucial for the improvement of crops and management of diseases. Here, we develop a new resource to identify genes underlying such quantitative traits in Arabidopsis thaliana, a genetic model organism in plants. We show that using a large population of inbred lines derived from intercrossing 19 parents, we can localize the genes underlying quantitative traits better than with existing methods. Using these lines, we were able to replicate the identification of previously known genes that affect developmental traits in A. thaliana and identify some new ones. This paper also presents all the necessary biological and computational material necessary for the scientific community to use these lines in their own research. Our results suggest that the use of lines derived from a multiparent advanced generation inter-cross (MAGIC lines) should be very useful in other organisms.
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