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Gene and QTL detection in a three-way barley cross under selection by a mixed model with kinship information using SNPs.

ABSTRACT: Quantitative trait locus (QTL) detection is commonly performed by analysis of designed segregating populations derived from two inbred parental lines, where absence of selection, mutation and genetic drift is assumed. Even for designed populations, selection cannot always be avoided, with as consequence varying correlation between genotypes instead of uniform correlation. Akin to linkage disequilibrium mapping, ignoring this type of genetic relatedness will increase the rate of false-positives. In this paper, we advocate using mixed models including genetic relatedness, or 'kinship' information for QTL detection in populations where selection forces operated. We demonstrate our case with a three-way barley cross, designed to segregate for dwarfing, vernalization and spike morphology genes, in which selection occurred. The population of 161 inbred lines was screened with 1,536 single nucleotide polymorphisms (SNPs), and used for gene and QTL detection. The coefficient of coancestry matrix was estimated based on the SNPs and imposed to structure the distribution of random genotypic effects. The model incorporating kinship, coancestry, information was consistently superior to the one without kinship (according to the Akaike information criterion). We show, for three traits, that ignoring the coancestry information results in an unrealistically high number of marker-trait associations, without providing clear conclusions about QTL locations. We used a number of widely recognized dwarfing and vernalization genes known to segregate in the studied population as landmarks or references to assess the agreement of the mapping results with a priori candidate gene expectations. Additional QTLs to the major genes were detected for all traits as well.

SUBMITTER: Malosetti M

PROVIDER: S-EPMC3082036 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Drought is a major abiotic stress impeding the yield of cereal crops globally. Particularly in Mediterranean environments, water becomes a limiting factor during the reproductive developmental stage, causing yield losses. The wild progenitor of cultivated barley Hordeum vulgare ssp spontaneum (Hsp) is a potentially useful source of drought tolerance alleles. Wild barley introgression lines like the S42IL library may facilitate the introduction of favorable exotic alleles into breeding material. The complete set of 83 S42ILs was genotyped with the barley 9k iSelect platform in order to complete genetic information obtained in previous studies. The new map comprises 2,487 SNPs, spanning 989.8 cM and covering 94.5% of the Hsp genome. Extent and positions of introgressions were confirmed and new information for ten additional S42ILs was collected. A subset of 49 S42ILs was evaluated for drought response in four greenhouse experiments. Plants were grown under well-watered conditions until ten days post anthesis. Subsequently drought treatment was applied by reducing the available water. Several morphological and harvest parameters were evaluated. Under drought treatment, trait performance was reduced. However, there was no interaction effect between genotype and treatment, indicating that genotypes, which performed best under control treatment, also performed best under drought treatment. In total, 40 QTL for seven traits were detected in this study. For instance, favorable Hsp effects were found for thousand grain weight (TGW) and number of grains per ear under drought stress. In particular, line S42IL-121 is a promising candidate for breeding improved malting cultivars, displaying a TGW, which was increased by 17% under terminal drought stress due to the presence of an unknown wild barley QTL allele on chromosome 4H. The introgression line showed a similar advantage in previous field experiments and in greenhouse experiments under early drought stress. We, thus, recommend using S42IL-121 in barley breeding programs to enhance terminal drought tolerance.

Project description:BackgroundAngiosperms employ an astonishing variety of visual and olfactory floral signals that are generally thought to evolve under natural selection. Those morphological and chemical traits can form highly correlated sets of traits. It is not always clear which of these are used by pollinators as primary targets of selection and which would be indirectly selected by being linked to those primary targets. Quantitative genetics tools for predicting multiple traits response to selection have been developed since long and have advanced our understanding of evolution of genetically correlated traits in various biological systems. We use these tools to predict the evolutionary trajectories of floral traits and understand the selection pressures acting on them.ResultsWe used data from an artificial selection and a pollinator (bumblebee, hoverfly) evolution experiment with fast cycling Brassica rapa plants to predict evolutionary changes of 12 floral volatiles and 4 morphological floral traits in response to selection. Using the observed selection gradients and the genetic variance-covariance matrix (G-matrix) of the traits, we showed that the observed responses of most floral traits including volatiles were predicted in the right direction in both artificial- and bumblebee-selection experiment. Genetic covariance had a mix of constraining and facilitating effects on evolutionary responses. We further revealed that G-matrices also evolved in the selection processes.ConclusionsOverall, our integrative study shows that floral signals, especially volatiles, evolve under selection in a mostly predictable way, at least during short term evolution. Evolutionary constraints stemming from genetic covariance affected traits evolutionary trajectories and thus it is important to include genetic covariance for predicting the evolutionary changes of a comprehensive suite of traits. Other processes such as resource limitation and selfing also need to be considered for a better understanding of floral trait evolution.

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Gene and QTL detection in a three-way barley cross under selection by a mixed model with kinship information using SNPs.

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