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  • 1
    Online Resource
    Online Resource
    Back to Acid Soil Fields: The Citrate Transporter SbMATE Is a Major Asset for Sustainable Grain Yield for Sorghum Cultivated on Acid Soils
    Oxford University Press (OUP) ; 2016
    In:  G3 Genes|Genomes|Genetics Vol. 6, No. 2 ( 2016-02-01), p. 475-484
    Details
    In: G3 Genes|Genomes|Genetics, Oxford University Press (OUP), Vol. 6, No. 2 ( 2016-02-01), p. 475-484
    Abstract: Aluminum (Al) toxicity damages plant roots and limits crop production on acid soils, which comprise up to 50% of the world’s arable lands. A major Al tolerance locus on chromosome 3, AltSB, controls aluminum tolerance in sorghum [Sorghum bicolor (L.) Moench] via SbMATE, an Al-activated plasma membrane transporter that mediates Al exclusion from sensitive regions in the root apex. As is the case with other known Al tolerance genes, SbMATE was cloned based on studies conducted under controlled environmental conditions, in nutrient solution. Therefore, its impact on grain yield on acid soils remains undetermined. To determine the real world impact of SbMATE, multi-trait quantitative trait loci (QTL) mapping in hydroponics, and, in the field, revealed a large-effect QTL colocalized with the Al tolerance locus AltSB, where SbMATE lies, conferring a 0.6 ton ha–1 grain yield increase on acid soils. A second QTL for Al tolerance in hydroponics, where the positive allele was also donated by the Al tolerant parent, SC283, was found on chromosome 9, indicating the presence of distinct Al tolerance genes in the sorghum genome, or genes acting in the SbMATE pathway leading to Al-activated citrate release. There was no yield penalty for AltSB, consistent with the highly localized Al regulated SbMATE expression in the root tip, and Al-dependent transport activity. A female effect of 0.5 ton ha–1 independently demonstrated the effectiveness of AltSB in hybrids. Al tolerance conferred by AltSB is thus an indispensable asset for sorghum production and food security on acid soils, many of which are located in developing countries.
    Type of Medium: Online Resource
    ISSN: 2160-1836
    URL: Article
    DOI: 10.1534/g3.115.025791
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2016
    detail.hit.zdb_id: 2629978-1
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  • 2
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    Online Resource
    Multi-trait association mapping for phosphorous efficiency reveals flexible root architectures in sorghum
    Springer Science and Business Media LLC ; 2024
    In:  BMC Plant Biology Vol. 24, No. 1 ( 2024-06-15)
    Details
    In: BMC Plant Biology, Springer Science and Business Media LLC, Vol. 24, No. 1 ( 2024-06-15)
    Abstract: On tropical regions, phosphorus (P) fixation onto aluminum and iron oxides in soil clays restricts P diffusion from the soil to the root surface, limiting crop yields. While increased root surface area favors P uptake under low-P availability, the relationship between the three-dimensional arrangement of the root system and P efficiency remains elusive. Here, we simultaneously assessed allelic effects of loci associated with a variety of root and P efficiency traits, in addition to grain yield under low-P availability, using multi-trait genome-wide association. We also set out to establish the relationship between root architectural traits assessed in hydroponics and in a low-P soil. Our goal was to better understand the influence of root morphology and architecture in sorghum performance under low-P availability. Result In general, the same alleles of associated SNPs increased root and P efficiency traits including grain yield in a low-P soil. We found that sorghum P efficiency relies on pleiotropic loci affecting root traits, which enhance grain yield under low-P availability. Root systems with enhanced surface area stemming from lateral root proliferation mostly up to 40 cm soil depth are important for sorghum adaptation to low-P soils, indicating that differences in root morphology leading to enhanced P uptake occur exactly in the soil layer where P is found at the highest concentration. Conclusion Integrated QTLs detected in different mapping populations now provide a comprehensive molecular genetic framework for P efficiency studies in sorghum. This indicated extensive conservation of P efficiency QTL across populations and emphasized the terminal portion of chromosome 3 as an important region for P efficiency in sorghum. Increases in root surface area via enhancement of lateral root development is a relevant trait for sorghum low-P soil adaptation, impacting the overall architecture of the sorghum root system. In turn, particularly concerning the critical trait for water and nutrient uptake, root surface area, root system development in deeper soil layers does not occur at the expense of shallow rooting, which may be a key reason leading to the distinctive sorghum adaptation to tropical soils with multiple abiotic stresses including low P availability and drought.
    Type of Medium: Online Resource
    ISSN: 1471-2229
    URL: Article
    DOI: 10.1186/s12870-024-05183-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2024
    detail.hit.zdb_id: 2059868-3
    SSG: 12
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  • 3
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    Online Resource
    Multi-parent multi-environment QTL analysis: an illustration with the EU-NAM Flint population
    Springer Science and Business Media LLC ; 2020
    In:  Theoretical and Applied Genetics Vol. 133, No. 9 ( 2020-09), p. 2627-2638
    Details
    In: Theoretical and Applied Genetics, Springer Science and Business Media LLC, Vol. 133, No. 9 ( 2020-09), p. 2627-2638
    Abstract: Multi-parent populations multi-environment QTL experiments data should be analysed jointly to estimate the QTL effect variation within the population and between environments. Abstract Commonly, QTL detection in multi-parent populations (MPPs) data measured in multiple environments (ME) is done by analyzing genotypic values ‘averaged’ across environments. This method ignores the environment-specific QTL (QTLxE) effects. Running separate single environment analyses is a possibility to measure QTLxE effects, but those analyses do not model the genetic covariance due to the use of the same genotype in different environments. In this paper, we propose methods to analyse MPP-ME QTL experiments using simultaneously the data from several environments and modelling the genotypic covariance. Using data from the EU-NAM Flint population, we show that these methods estimate the QTLxE effects and that they can improve the quality of the QTL detection. Those methods also have a larger inference power. For example, they can be extended to integrate environmental indices like temperature or precipitation to better understand the mechanisms behind the QTLxE effects. Therefore, our methodology allows the exploitation of the full MPP-ME data potential: to estimate QTL effect variation (a) within the MPP between sub-populations due to different genetic backgrounds and (b) between environments.
    Type of Medium: Online Resource
    ISSN: 0040-5752 , 1432-2242
    URL: Article
    DOI: 10.1007/s00122-020-03621-0
    RVK:
    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 1478966-8
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Table_2.DOCX
    Frontiers Media SA ; 2021
    In:  Frontiers in Plant Science Vol. 12 ( 2021-11-24)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 12 ( 2021-11-24)
    Abstract: Training set construction is an important prerequisite to Genomic Prediction (GP), and while this has been studied in diploids, polyploids have not received the same attention. Polyploidy is a common feature in many crop plants, like for example banana and blueberry, but also potato which is the third most important crop in the world in terms of food consumption, after rice and wheat. The aim of this study was to investigate the impact of different training set construction methods using a publicly available diversity panel of tetraploid potatoes. Four methods of training set construction were compared: simple random sampling, stratified random sampling, genetic distance sampling and sampling based on the coefficient of determination (CDmean). For stratified random sampling, population structure analyses were carried out in order to define sub-populations, but since sub-populations accounted for only 16.6% of genetic variation, there were negligible differences between stratified and simple random sampling. For genetic distance sampling, four genetic distance measures were compared and though they performed similarly, Euclidean distance was the most consistent. In the majority of cases the CDmean method was the best sampling method, and compared to simple random sampling gave improvements of 4–14% in cross-validation scenarios, and 2–8% in scenarios with an independent test set, while genetic distance sampling gave improvements of 5.5–10.5% and 0.4–4.5%. No interaction was found between sampling method and the statistical model for the traits analyzed.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2021.771075
    DOI: 10.3389/fpls.2021.771075.s001
    DOI: 10.3389/fpls.2021.771075.s002
    DOI: 10.3389/fpls.2021.771075.s003
    DOI: 10.3389/fpls.2021.771075.s004
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 5
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    Online Resource
    Genomic Prediction of Grain Yield and Drought-Adaptation Capacity in Sorghum Is Enhanced by Multi-Trait Analysis
    Frontiers Media SA ; 2019
    In:  Frontiers in Plant Science Vol. 10 ( 2019-7-31)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 10 ( 2019-7-31)
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    DOI: 10.3389/fpls.2019.00997
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2019
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 6
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    Combining Crop Growth Modeling and Statistical Genetic Modeling to Evaluate Phenotyping Strategies
    Frontiers Media SA ; 2019
    In:  Frontiers in Plant Science Vol. 10 ( 2019-11-27)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 10 ( 2019-11-27)
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    DOI: 10.3389/fpls.2019.01491
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2019
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 7
    Online Resource
    Online Resource
    Common bean SNP alleles and candidate genes affecting photosynthesis under contrasting water regimes
    Oxford University Press (OUP) ; 2021
    In:  Horticulture Research Vol. 8, No. 1 ( 2021-12)
    Details
    In: Horticulture Research, Oxford University Press (OUP), Vol. 8, No. 1 ( 2021-12)
    Abstract: Water deficit is a major worldwide constraint to common bean ( Phaseolus vulgaris L.) production, being photosynthesis one of the most affected physiological processes. To gain insights into the genetic basis of the photosynthetic response of common bean under water-limited conditions, a collection of 158 Portuguese accessions was grown under both well-watered and water-deficit regimes. Leaf gas-exchange parameters were measured and photosynthetic pigments quantified. The same collection was genotyped using SNP arrays, and SNP-trait associations tested considering a linear mixed model accounting for the genetic relatedness among accessions. A total of 133 SNP-trait associations were identified for net CO 2 assimilation rate, transpiration rate, stomatal conductance, and chlorophylls a and b , carotenes, and xanthophyll contents. Ninety of these associations were detected under water-deficit and 43 under well-watered conditions, with only two associations common to both treatments. Identified candidate genes revealed that stomatal regulation, protein translocation across membranes, redox mechanisms, hormone, and osmotic stress signaling were the most relevant processes involved in common bean response to water-limited conditions. These candidates are now preferential targets for common bean water-deficit-tolerance breeding. Additionally, new sources of water-deficit tolerance of Andean, Mesoamerican, and admixed origin were detected as accessions valuable for breeding, and not yet explored.
    Type of Medium: Online Resource
    ISSN: 2662-6810 , 2052-7276
    URL: Article
    DOI: 10.1038/s41438-020-00434-6
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2781828-7
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  • 8
    Online Resource
    Online Resource
    Ascertainment bias from imputation methods evaluation in wheat
    Springer Science and Business Media LLC ; 2016
    In:  BMC Genomics Vol. 17, No. 1 ( 2016-12)
    Details
    In: BMC Genomics, Springer Science and Business Media LLC, Vol. 17, No. 1 ( 2016-12)
    Type of Medium: Online Resource
    ISSN: 1471-2164
    URL: Article
    DOI: 10.1186/s12864-016-3120-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2041499-7
    SSG: 12
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  • 9
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    Online Resource
    Genome-wide association mapping of frost tolerance in barley (Hordeum vulgare L.)
    Springer Science and Business Media LLC ; 2013
    In:  BMC Genomics Vol. 14, No. 1 ( 2013-12)
    Details
    In: BMC Genomics, Springer Science and Business Media LLC, Vol. 14, No. 1 ( 2013-12)
    Abstract: Frost tolerance is a key trait with economic and agronomic importance in barley because it is a major component of winter hardiness, and therefore limits the geographical distribution of the crop and the effective transfer of quality traits between spring and winter crop types. Three main frost tolerance QTL ( Fr-H1 , Fr-H2 and Fr-H3 ) have been identified from bi-parental genetic mapping but it can be argued that those mapping populations only capture a portion of the genetic diversity of the species. A genetically broad dataset consisting of 184 genotypes, representative of the barley gene pool cultivated in the Mediterranean basin over an extended time period, was genotyped with 1536 SNP markers. Frost tolerance phenotype scores were collected from two trial sites, Foradada (Spain) and Fiorenzuola (Italy) and combined with the genotypic data in genome wide association analyses (GWAS) using Eigenstrat and kinship approaches to account for population structure. Results GWAS analyses identified twelve and seven positive SNP associations at Foradada and Fiorenzuola, respectively, using Eigenstrat and six and four, respectively, using kinship. Linkage disequilibrium analyses of the significant SNP associations showed they are genetically independent. In the kinship analysis, two of the significant SNP associations were tightly linked to the Fr-H2 and HvBmy loci on chromosomes 5H and 4HL, respectively. The other significant kinship associations were located in genomic regions that have not previously been associated with cold stress. Conclusions Haplotype analysis revealed that most of the significant SNP loci are fixed in the winter or facultative types, while they are freely segregating within the un-adapted spring barley genepool. Although there is a major interest in detecting new variation to improve frost tolerance of available winter and facultative types, from a GWAS perspective, working within the un-adapted spring germplasm pool is an attractive alternative strategy which would minimize statistical issues, simplify the interpretation of the data and identify phenology independent genetic determinants of frost tolerance.
    Type of Medium: Online Resource
    ISSN: 1471-2164
    URL: Article
    DOI: 10.1186/1471-2164-14-424
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2013
    detail.hit.zdb_id: 2041499-7
    SSG: 12
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  • 10
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    Online Resource
    Improvement of Predictive Ability by Uniform Coverage of the Target Genetic Space
    Oxford University Press (OUP) ; 2016
    In:  G3 Genes|Genomes|Genetics Vol. 6, No. 11 ( 2016-11-01), p. 3733-3747
    Details
    In: G3 Genes|Genomes|Genetics, Oxford University Press (OUP), Vol. 6, No. 11 ( 2016-11-01), p. 3733-3747
    Abstract: Genome-enabled prediction provides breeders with the means to increase the number of genotypes that can be evaluated for selection. One of the major challenges in genome-enabled prediction is how to construct a training set of genotypes from a calibration set that represents the target population of genotypes, where the calibration set is composed of a training and validation set. A random sampling protocol of genotypes from the calibration set will lead to low quality coverage of the total genetic space by the training set when the calibration set contains population structure. As a consequence, predictive ability will be affected negatively, because some parts of the genotypic diversity in the target population will be under-represented in the training set, whereas other parts will be over-represented. Therefore, we propose a training set construction method that uniformly samples the genetic space spanned by the target population of genotypes, thereby increasing predictive ability. To evaluate our method, we constructed training sets alongside with the identification of corresponding genomic prediction models for four genotype panels that differed in the amount of population structure they contained (maize Flint, maize Dent, wheat, and rice). Training sets were constructed using uniform sampling, stratified-uniform sampling, stratified sampling and random sampling. We compared these methods with a method that maximizes the generalized coefficient of determination (CD). Several training set sizes were considered. We investigated four genomic prediction models: multi-locus QTL models, GBLUP models, combinations of QTL and GBLUPs, and Reproducing Kernel Hilbert Space (RKHS) models. For the maize and wheat panels, construction of the training set under uniform sampling led to a larger predictive ability than under stratified and random sampling. The results of our methods were similar to those of the CD method. For the rice panel, all training set construction methods led to similar predictive ability, a reflection of the very strong population structure in this panel.
    Type of Medium: Online Resource
    ISSN: 2160-1836
    URL: Article
    DOI: 10.1534/g3.116.035410
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2016
    detail.hit.zdb_id: 2629978-1
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