scholarly journals Sequential Quantitative Trait Locus Mapping in Experimental Crosses

Author(s):  
Jaya M Satagopan ◽  
Saunak Sen ◽  
Gary A. Churchill

The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by systematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

2007 ◽  
Vol 1 (Suppl 1) ◽  
pp. S139 ◽  
Author(s):  
Tao Wang ◽  
Qing Lu ◽  
Monica Torres-Caban ◽  
Robert C Elston

2019 ◽  
Vol 144 (5) ◽  
pp. 352-362
Author(s):  
Vanessa E.T.M. Ashworth ◽  
Haofeng Chen ◽  
Carlos L. Calderón-Vázquez ◽  
Mary Lu Arpaia ◽  
David N. Kuhn ◽  
...  

The glossy, green-fleshed fruit of the avocado (Persea americana) has been the object of human selection for thousands of years. Recent interest in healthy nutrition has singled out the avocado as an excellent source of several phytonutrients. Yet as a sizeable, slow-maturing tree crop, it has been largely neglected by genetic studies, owing to a long breeding cycle and costly field trials. We use a small, replicated experimental population of 50 progeny, grown at two locations in two successive years, to explore the feasibility of developing a dense genetic linkage map and to implement quantitative trait locus (QTL) analysis for seven phenotypic traits. Additionally, we test the utility of candidate-gene single-nucleotide polymorphisms developed to genes from biosynthetic pathways of phytonutrients beneficial to human health. The resulting linkage map consisted of 1346 markers (1044.7 cM) distributed across 12 linkage groups. Numerous markers on Linkage Group 10 were associated with a QTL for flowering type. One marker on Linkage Group 1 tracked a QTL for β-sitosterol content of the fruit. A region on Linkage Group 3 tracked vitamin E (α-tocopherol) content of the fruit, and several markers were stable across both locations and study years. We argue that the pursuit of linkage mapping and QTL analysis is worthwhile, even when population size is small.


Author(s):  
Peng Qi ◽  
Thomas H. Pendergast ◽  
Alex Johnson ◽  
Bochra A. Bahri ◽  
Soyeon Choi ◽  
...  

Abstract Key message Mapping combined with expression and variant analyses in switchgrass, a crop with complex genetics, identified a cluster of candidate genes for leaf wax in a fast-evolving region of chromosome 7K. Abstract Switchgrass (Panicum virgatum L.) is a promising warm-season candidate energy crop. It occurs in two ecotypes, upland and lowland, which vary in a number of phenotypic traits, including leaf glaucousness. To initiate trait mapping, two F2 mapping populations were developed by crossing two different F1 sibs derived from a cross between the tetraploid lowland genotype AP13 and the tetraploid upland genotype VS16, and high-density linkage maps were generated. Quantitative trait locus (QTL) analyses of visually scored leaf glaucousness and of hydrophobicity of the abaxial leaf surface measured using a drop shape analyzer identified highly significant colocalizing QTL on chromosome 7K (Chr07K). Using a multipronged approach, we identified a cluster of genes including Pavir.7KG077009, which encodes a Type III polyketide synthase-like protein, and Pavir.7KG013754 and Pavir.7KG030500, two highly similar genes that encode putative acyl-acyl carrier protein (ACP) thioesterases, as strong candidates underlying the QTL. The lack of homoeologs for any of the three genes on Chr07N, the relatively low level of identity with other switchgrass KCS proteins and thioesterases, as well as the organization of the surrounding region suggest that Pavir.7KG077009 and Pavir.7KG013754/Pavir.7KG030500 were duplicated into a fast-evolving chromosome region, which led to their neofunctionalization. Furthermore, sequence analyses showed all three genes to be absent in the two upland compared to the two lowland accessions analyzed. This study provides an example of and practical guide for trait mapping and candidate gene identification in a complex genetic system by combining QTL mapping, transcriptomics and variant analysis.


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