Effects of genotyping errors, missing values and segregation distortion in molecular marker data on the construction of linkage maps

Abstract

A simulation study was performed to investigate the effects of missing values, typing errors and distorted segregation ratios in molecular marker data on the construction of genetic linkage maps, and to compare the performance of three locus-ordering criteria (weighted least squares, maximum likelihood and minimum sum of adjacent recombination fractions criteria) in the presence of such effects. The study was based upon three linkage groups of 10 loci at 2, 6, and 10 cM spacings simulated from a doubled-haploid population of size 150. Criteria performance were assessed using the number of replicates with correctly estimated orders, the mean rank correlation between the estimated and the true order and the mean total map length. Bootstrap samples from replicates in the maximum likelihood analysis produced a measure of confidence in the estimated locus order. The effects of missing values and/or typing errors in the data are to reduce the proportion of correctly ordered maps, and this problem worsens as the distances between loci decreases. The maximum likelihood criterion is most successful at ordering loci correctly, but gives estimated map lengths, which are substantially inflated when typing errors are present. The presence of missing values in the data produces shorter map lengths for more widely spaced markers, especially under the weighted least-squares criterion. Overall, the presence of segregation distortion has little effect on this population.

Evaluation of algorithms used to order markers on genetic maps

“…This is in accordance with previous studies based on double haploid populations. Hackett and Broadfoot (2003) (n ¼ 150) noticed that likelihood performed better, and Wu et al (2003) (n ¼ 100, 150, and 200) were the algorithm SER proved to be an excellent alternative. Wu et al (2003) have discussed that the estimates of the recombination fractions obtained between dominant markers in repulsion in an F 2 population are biased, thus suggests the use of co-dominant markers to overcome the problem.…”

“…Wu et al (2003) have evaluated the efficiency of the criteria SARF, PARF, SALOD and LHMC, along with the algorithm SER in situations with m ¼ 5. Hackett and Broadfoot (2003) have compared the efficiency of the criteria weighted least squares, SARF and LHMC in maps with 10 loci. In general, it is noticeable that none of the aforementioned works have considered the ordering problem in highly saturated maps, which is currently a very common situation due to the great availability of molecular markers.…”

New genetic maps for globe artichoke and wild cardoon and their alignment with an SSR-based consensus map

“…Such minor differences may be due to mapping imprecisions (Lombard and Delourme 2001), to differences in recombination frequencies of marker pairs in different populations (Studer et al 2010) or might be attributed to different population sizes (Spiller et al 2011). Other potential sources of variation are genotyping errors, an excess of missing values and the mapping of distorted markers (Hackett and Broadfoot 2003). Given the probabilistic nature of genetic maps, the re-ordering of tightly linked markers will generally produce a version of the map only marginally less probable than the most probable one, so this practice is quite frequently followed to improve alignment quality (Cervera et al 2001;Jeuken et al 2001;Lespinasse et al 2000;Lombard and Delourme 2001;Sebastian et al 2000).…”

Extensive linkage disequilibrium in a wild bird population

“…In practice, however, mapping data is compromised in all of these respects. However, as simulated and concluded in previous research [53], the effect of missing genotypes depends greatly on the sample size: the smaller the sample, the more severe the effects are likely to be. In comparison to published simulations, in LG1…”