How accurate are the marker orders in crop linkage maps generated from large marker datasets?

2009 ◽  
Vol 60 (4) ◽  
pp. 362 ◽  
Author(s):  
Bertrand Collard ◽  
Emma Mace ◽  
Mark McPhail ◽  
Peter Wenzl ◽  
Mehmet Cakir ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Mapping Population ◽  
Mammalian Genome ◽  
Marker Order ◽  
Linkage Maps ◽  
Analysis Software ◽  
Map Construction ◽  
The Stability ◽  
Weighted Rank ◽  
Accuracy And Stability

Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930–932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30–40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping.

scholarly journals Using probabilistic genotypes in linkage analysis of polyploids

2021 ◽  
Author(s):  
Yanlin Liao ◽  
Roeland E. Voorrips ◽  
Peter M. Bourke ◽  
Giorgio Tumino ◽  
Paul Arens ◽  
...  
Keyword(s):  
Linkage Map ◽  
Linkage Mapping ◽  
Mapping Population ◽  
Snp Array ◽  
Linkage Maps ◽  
Sequencing Data ◽  
Genotype Calling ◽  
Map Construction ◽  
Allele Dosage ◽  
Discrete Values

Abstract Key message In polyploids, linkage mapping is carried out using genotyping with discrete dosage scores. Here, we use probabilistic genotypes and we validate it for the construction of polyploid linkage maps. Abstract Marker genotypes are generally called as discrete values: homozygous versus heterozygous in the case of diploids, or an integer allele dosage in the case of polyploids. Software for linkage map construction and/or QTL analysis usually relies on such discrete genotypes. However, it may not always be possible, or desirable, to assign definite values to genotype observations in the presence of uncertainty in the genotype calling. Here, we present an approach that uses probabilistic marker dosages for linkage map construction in polyploids. We compare our method to an approach based on discrete dosages, using simulated SNP array and sequence reads data with varying levels of data quality. We validate our approach using experimental data from a potato (Solanum tuberosum L.) SNP array applied to an F1 mapping population. In comparison to the approach based on discrete dosages, we mapped an additional 562 markers. All but three of these were mapped to the expected chromosome and marker position. For the remaining three markers, no physical position was known. The use of dosage probabilities is of particular relevance for map construction in polyploids using sequencing data, as these often result in a higher level of uncertainty regarding allele dosage.

scholarly journals Genomic Resource Development for Hydrangea (Hydrangea macrophylla (Thunb.) Ser.)—A Transcriptome Assembly and a High-Density Genetic Linkage Map

Horticulturae ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 25
Author(s):  
Xingbo Wu ◽  
Amanda M. Hulse-Kemp ◽  
Phillip A. Wadl ◽  
Zach Smith ◽  
Keithanne Mockaitis ◽  
...  
Keyword(s):  
Genetic Resources ◽  
Linkage Map ◽  
Genetic Linkage ◽  
Genetic Linkage Map ◽  
Mapping Population ◽  
High Density ◽  
Linkage Maps ◽  
Map Construction ◽  
Hydrangea Macrophylla ◽  
Genetic Linkage Maps

Hydrangea (Hydrangea macrophylla) is an important ornamental crop that has been cultivated for more than 300 years. Despite the economic importance, genetic studies for hydrangea have been limited by the lack of genetic resources. Genetic linkage maps and subsequent trait mapping are essential tools to identify and make markers available for marker-assisted breeding. A transcriptomic study was performed on two important cultivars, Veitchii and Endless Summer, to discover simple sequence repeat (SSR) markers and an F1 population based on the cross ‘Veitchii’ × ‘Endless Summer’ was established for genetic linkage map construction. Genotyping by sequencing (GBS) was performed on the mapping population along with SSR genotyping. From an analysis of 42,682 putative transcripts, 8780 SSRs were identified and 1535 were validated in the mapping parents. A total of 267 polymorphic SSRs were selected for linkage map construction. The GBS yielded 3923 high quality single nucleotide polymorphisms (SNPs) in the mapping population, resulting in a total of 4190 markers that were used to generate maps for each parent and a consensus map. The consensus linkage map contained 1767 positioned markers (146 SSRs and 1621 SNPs), spanned 1383.4 centiMorgans (cM), and was comprised of 18 linkage groups, with an average mapping interval of 0.8 cM. The transcriptome information and large-scale marker development in this study greatly expanded the genetic resources that are available for hydrangea. The high-density genetic linkage maps presented here will serve as an important foundation for quantitative trait loci mapping, map-based gene cloning, and marker-assisted selection of H. macrophylla.

scholarly journals Linkage Analysis and QTL Mapping Using SNP Dosage Data in a Tetraploid Potato Mapping Population

PLoS ONE ◽  
2013 ◽  
Vol 8 (5) ◽  
pp. e63939 ◽  
Author(s):  
Christine A. Hackett ◽  
Karen McLean ◽  
Glenn J. Bryan
Keyword(s):  
Linkage Analysis ◽  
Qtl Mapping ◽  
Mapping Population ◽  
Tetraploid Potato

scholarly journals Advanced Strategies in Bulked Segregant Analysis and its Applications

2021 ◽  
Author(s):  
Harshavardan J. Hilli
Keyword(s):  
Genetic Markers ◽  
Mapping Population ◽  
Bulked Segregant Analysis ◽  
High Density ◽  
Mutant Phenotype ◽  
Linkage Maps ◽  
Quick Method ◽  
Reduced Time

Bulked segregant analysis (BSA) is a technique used to identify genetic markers associated with a mutant phenotype and is a quick method for identifying markers in particular genome regions. The paper focussed on Advanced methods which escape the requirement of genotyping all the individuals of the mapping population and generation of high-density linkage maps for mapping of the gene for the trait of interest. With the emergence of re-sequencing techniques, quick mapping of genes has become possible with reduced time and cost by using advanced methodologies like MutMap, MutMap+, MutMap-Gap, QTL-Seq, RNAseq BSA, NGS BSA and QTG seq. The procedure for various advanced BSA strategies has been described.

scholarly journals Investigation and Validation of Detection of Storage Stability of Difenoconazole Residue in Mango

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Fangfang Zhao ◽  
Jingkun Liu ◽  
Bingjun Han ◽  
Jinhui Luo
Keyword(s):  
Food Safety ◽  
Pesticide Residue ◽  
Storage Stability ◽  
Sample Solution ◽  
Sample Storage ◽  
Fruit Samples ◽  
Different Temperatures ◽  
The Stability ◽  
Food Safety And Quality ◽  
Accuracy And Stability

To investigate the stability of the pesticide residue in storage samples is a part of detection, which is also an improvement to the accuracy of analytical results. In this work, the UPLC-MS/MS method with perfect accuracy and stability was established for determining residues of difenoconazole in mango. The stability of the residue under different temperatures (4°C and −20°C) and media (fruit samples and pretreated sample solution) was investigated. At 0.1 mg/kg, the residue degraded in 6 months by 12% when at −20°C, while in a week by only 12.2% at 4°C. However, when pretreated and preserved in the solution, the residue remained more than 90% for 6–8 weeks. The results indicated that the main causes of degradation are biochemical factors, and the factors are affected by temperature. The findings also provided appropriate conditions for sample storage. This investigation promotes the accuracy in detection and hence guarantees food safety and quality.

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