The peach volatilome modularity is reflected at the genetic and environmental response levels in a QTL mapping population

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.

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Identification and QTL mapping of resistance to Turnip yellows virus (TuYV) in oilseed rape, Brassica napus

Theoretical and Applied Genetics ◽

10.1007/s00122-019-03469-z ◽

2019 ◽

Vol 133 (2) ◽

pp. 383-393 ◽

Cited By ~ 3

Author(s):

Dieter Hackenberg ◽

Elvis Asare-Bediako ◽

Adam Baker ◽

Peter Walley ◽

Carol Jenner ◽

...

Keyword(s):

Brassica Napus ◽

Qtl Mapping ◽

Oilseed Rape ◽

Genetic Resource ◽

Mapping Population ◽

Resistant Parent ◽

Potato Aphid ◽

Turnip Yellows Virus ◽

Peach Potato Aphid ◽

Major Qtl

Abstract Key message Partially dominant resistance to Turnip yellows virus associated with one major QTL was identified in the natural allotetraploid oilseed rape cultivar Yudal. Abstract Turnip yellows virus (TuYV) is transmitted by the peach-potato aphid (Myzus persicae) and causes severe yield losses in commercial oilseed rape crops (Brassica napus). There is currently only one genetic resource for resistance to TuYV available in brassica, which was identified in the re-synthesised B. napus line ‘R54’. In our study, 27 mostly homozygous B. napus accessions, either doubled-haploid (DH) or inbred lines, representing a diverse subset of the B. napus genepool, were screened for TuYV resistance/susceptibility. Partial resistance to TuYV was identified in the Korean spring oilseed rape, B. napus variety Yudal, whilst the dwarf French winter oilseed rape line Darmor-bzh was susceptible. QTL mapping using the established Darmor-bzh × Yudal DH mapping population (DYDH) revealed one major QTL explaining 36% and 18% of the phenotypic variation in two independent experiments. A DYDH line was crossed to Yudal, and reciprocal backcross (BC1) populations from the F1 with either the susceptible or resistant parent revealed the dominant inheritance of the TuYV resistance. The QTL on ChrA04 was verified in the segregating BC1 population. A second minor QTL on ChrC05 was identified in one of the two DYDH experiments, and it was not observed in the BC1 population. The TuYV resistance QTL in ‘R54’ is within the QTL interval on Chr A04 of Yudal; however, the markers co-segregating with the ‘R54’ resistance are not conserved in Yudal, suggesting an independent origin of the TuYV resistances. This is the first report of the QTL mapping of TuYV resistance in natural B. napus.

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Effect of small mapping population sizes on reliability of quantitative trait locus (QTL) mapping

AFRICAN JOURNAL OF BIOTECHNOLOGY ◽

10.5897/ajb11.2032 ◽

2012 ◽

Vol 4 (47) ◽

Cited By ~ 3

Author(s):

C. Raghavan

Keyword(s):

Quantitative Trait Locus ◽

Qtl Mapping ◽

Quantitative Trait ◽

Mapping Population ◽

Population Sizes ◽

Trait Locus

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QTL mapping for micronutrients concentration and yield component traits in a hexaploid wheat mapping population

Journal of Cereal Science ◽

10.1016/j.jcs.2019.05.008 ◽

2019 ◽

Vol 88 ◽

pp. 57-64 ◽

Cited By ~ 16

Author(s):

Jia Liu ◽

Bihua Wu ◽

Ravi P. Singh ◽

Govindan Velu

Keyword(s):

Qtl Mapping ◽

Hexaploid Wheat ◽

Mapping Population ◽

Yield Component ◽

Component Traits ◽

Yield Component Traits

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Linkage analysis and QTL mapping in a tetraploid russet mapping population of potato

BMC Genetics ◽

10.1186/s12863-018-0672-1 ◽

2018 ◽

Vol 19 (1) ◽

Cited By ~ 7

Author(s):

Alicia N. Massa ◽

Norma C. Manrique-Carpintero ◽

Joseph Coombs ◽

Kathleen G. Haynes ◽

Paul C. Bethke ◽

...

Keyword(s):

Linkage Analysis ◽

Qtl Mapping ◽

Mapping Population

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Genetic analysis of the transition from wild to domesticated cotton (G. hirsutum L.)

10.1101/616763 ◽

2019 ◽

Cited By ~ 1

Author(s):

Corrinne E. Grover ◽

Mi-Jeong Yoo ◽

Meng Lin ◽

Matthew D. Murphy ◽

David B. Harker ◽

...

Keyword(s):

Genetic Analysis ◽

Candidate Genes ◽

Mapping Population ◽

Multiple Traits ◽

Intraspecific Divergence ◽

Phenotypic Changes ◽

Evolutionary Forces ◽

Environmentally Responsive ◽

Elite Cultivar ◽

Qtl Mapping Population

AbstractThe evolution and domestication of cotton is of great interest from both economic and evolutionary standpoints. Although many genetic and genomic resources have been generated for cotton, the genetic underpinnings of the transition from wild to domesticated cotton remain poorly known. Here we generated an intraspecific QTL mapping population specifically targeting domesticated cotton phenotypes. We used 466 F2 individuals derived from an intraspecific cross between the wild Gossypium hirsutum var. yucatanense (TX2094) and the elite cultivar G. hirsutum cv. Acala Maxxa, in two environments, to identify 120 QTL associated with phenotypic changes under domestication. While the number of QTL recovered in each subpopulation was similar, only 22 QTL were considered coincident (i.e., shared) between the two locations, eight of which shared peak markers. Although approximately half of QTL were located in the A-subgenome, many key fiber QTL were detected in the D-subgenome, which was derived from a species with unspinnable fiber. We found that many QTL are environment-specific, with few shared between the two environments, indicating that QTL associated with G. hirsutum domestication are genomically clustered but environmentally labile. Possible candidate genes were recovered and are discussed in the context of the phenotype. We conclude that the evolutionary forces that shape intraspecific divergence and domestication in cotton are complex, and that phenotypic transformations likely involved multiple interacting and environmentally responsive factors.SummaryAn F2 population between wild and domesticated cotton was used to identify QTL associated with selection under domestication. Multiple traits characterizing domesticated cotton were evaluated, and candidate genes underlying QTL are described for all traits. QTL are unevenly distributed between subgenomes of the domesticated polyploid, with many fiber QTL located on the genome derived from the D parent, which does not have spinnable fiber, but a majority of QTL overall located on the A subgenome. QTL are many (120) and environmentally labile. These data, together with candidate gene analyses, suggest recruitment of many environmentally responsive factors during cotton domestication.

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The full-sib intercross line (FSIL): a QTL mapping design for outcrossing species

Genetics Research ◽

10.1017/s0016672398003486 ◽

1999 ◽

Vol 73 (1) ◽

pp. 61-73 ◽

Cited By ~ 8

Author(s):

J. Z. SONG ◽

M. SOLLER ◽

A. GENIZI

Keyword(s):

Qtl Mapping ◽

Positional Cloning ◽

Statistical Power ◽

Mapping Population ◽

Dna Pooling ◽

Mapping Accuracy ◽

Total Size ◽

Outcrossing Species ◽

Line Cross ◽

Selective Dna Pooling

A full-sib intercross line (FSIL) is constructed in an outcrossing species by mating two parents and intercrossing their progeny to form a large intercross line. For given statistical power, a FSIL design requires only slightly more individuals than an F2 design derived from inbred line cross, but 6- to 10-fold fewer than a half-sib or full-sib design. Due to population-wide linkage disequilibrium, a FSIL is amenable to analysis by selective DNA pooling. In addition, a FSIL is maintained by continued intercrossing so that DNA samples and phenotypic information are accumulated across generations. Continued intercrossing also leads to map expansion and thus to increased mapping accuracy in the later generations. A FSIL can thus provide a bridge to positional cloning of quantitative trait loci (QTL) and marker-assisted selection in outcrossers; and is particularly effective in exploiting the QTL mapping potential of crosses between selection lines or phenotypically differentiated populations that differ in frequency, but are not at fixation, for alternative QTL alleles. In the course of the power analyses, it is shown that for F2 and FSIL designs, power is a function of Nd2 alone, where N is the total size of the mapping population and d is the standardized gene effect; while for half-sib and full-sib populations, power is a function of Nd2 and of the number of families included in the mapping population. This provides a convenient means of estimating power for a wide variety of mapping designs.

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