Abstract
Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP) markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called ‘large p, small n’ problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers). While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat) and Norstar × Cappelle Desprez (bread wheat). The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF), we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez). Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase making map expansion unavoidable. Therefore, we suggest developers improve linkage mapping algorithms for efficient analysis of high-throughput data. This study outlines a practical strategy to estimate the IF due to the proportion of co-segregating markers and outlines a method to scale the length of the map accordingly.
Highlights
Genetic maps known as linkage maps are constructed for several purposes
The objective of our study is to investigate the effects of cosegregating markers on high-density genetic map length and marker order using empirical data from durum and bread wheat
The features of Mohawk × Cocorit and Norstar × Cappelle Desprez maps that were built in step 1 of phase I are presented in Table 1 and Table 2, respectively
Summary
Genetic maps known as linkage maps are constructed for several purposes (see Semagn et al, 2006 for a review). – Allow phylogenetic analyses between different species for evaluating similarity between genes (Ahn and Tanksley, 1993; Paterson et al, 2000). Genetic maps indicate the position and relative genetic distances between markers along chromosomes, which is analogous to signs or landmarks along a highway where the genes are “houses” (Paterson, 1996; Collard et al, 2005). Genetic maps are constructed using different types and sizes of mapping populations, laboratory techniques, marker systems, mapping strategies, statistical procedures and computer packages. These factors can affect the efficiency of the mapping process (Liu, 1998; Paterson et al, 2000). Map length and marker orders are impacted by various factors, including the type and size of the population (Ferreira et al, 2006), the type of markers (dominant or codominant), genotyping or scoring errors, distortion segregation (Hackett and Broadfoot, 2003; Oliveira et al, 2004) and the frequency of double recombinants
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