Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat

Atkinson, Jonathan A.; Wingen, Luzie U.; Griffiths, Marcus; Pound, Michael P.; Gaju, Oorbessy; Foulkes, J.; Gouis, Jacques Le; Griffiths, Simon; Bennett, Malcolm J.; King, Julie; Wells, Darren M.

doi:10.1093/jxb/erv006

Cited by 190 publications

(222 citation statements)

References 28 publications

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“…Hydroponic systems were reported to be handy tools for root phenotyping (Atkinson et al, 2015;Ayalew et al, 2015). The present study employed hydroponic culture to get easy access to intact roots.…”

Section: Discussionmentioning

confidence: 99%

“…Sarker et al (2005) have reported in lentil that long root and shoot lengths at seedling stage were highly correlated with high grain yield. Initial root parameters and above-ground biomass were also reported to be positively correlated in wheat (Atkinson et al, 2015). Among the seedling traits that enable plants withstand drought are early establishment and ground cover, deep root system and leaf waxiness (Blum, 2005).…”

Section: Introductionmentioning

confidence: 96%

“…Therefore, breeding for drought resistance has to integrate all methodologies that help in genotype evaluation and selection at all stages of the crop instead of one final stage (Qu et al, 2008). Seedling or early vigour, and deep root system are believed to contribute for better drought resistance (Al-Karaki, 1998;Atkinson et al, 2015;Chloupek et al, 2010;Comas et al, 2013;Lilley and Kirkegaard, 2011). Some genes that contribute to seedling drought resistance may also contribute to later stage resistance (Comas et al, 2013;Hoffmann et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Performance of Ethiopian bread wheat (Tritium aestivum L.) genotypes under contrasting water regimes: potential sources of variability for drought resistance breeding

Ayalew¹,

Dessalegn²,

Liu³

et al. 2016

Aust J Crop Sci

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Drought is a common abiotic stress in Ethiopian agriculture. Crop yield is at risk due to drought that happens at various developmental stages of the crop. This experiment evaluated 248 Ethiopian bread wheat genotypes under water stress and non-stress growing conditions. Augmented complete block design with three blocks and eight replicated entries was used. Analysis of variance showed significant diversity among the genotypes in reaction to water stress. The average root and shoot lengths were reduced by 33.4% and 28.8%, respectively, due to water stress. The average fresh biomass per plant was 192 mg for non-stressed and 116 mg for stressed treatments, suffering a 40.5% reduction due to stress. Accessions 8314, 204463, 204454 and 204521 showed the longest roots while accessions 222381, 222405, 222439 and 204586 showed the shortest roots under stress conditions. Drought tolerance indices were calculated based on root length. Geometric mean performance (GMP) index was found helpful in identifying the relatively stable genotypes across the two water regimes. High GMP indices were observed for genotypes 8314, 204521, 231614, and KSN81 which were long rooting genotypes under both stress and non-stress conditions. ANOVA based on region of collection showed that genotypes from Southern Nations Nationalities and Peoples Region had the longest roots. Elevation of origin did not show any significant difference for any of the traits measured. This study demonstrated the presence of large variations for water stress response in the Ethiopian bread wheat germplasm. The identified stress resistant genotypes can be used as potential breeding stocks to develop drought resistant cultivars.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Performance of Ethiopian bread wheat (Tritium aestivum L.) genotypes under contrasting water regimes: potential sources of variability for drought resistance breeding

Ayalew¹,

Dessalegn²,

Liu³

et al. 2016

Aust J Crop Sci

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“…However, the process of automatically acquiring images of plants and their subsequent analysis is complex, and requires an understanding of the software processes at work, and their limitations (Pridmore et al 2012). The combination of rapid image capture and high throughput, objective analysis, though, has been shown to lead to new genetic insight (Atkinson et al 2015). These potential rewards then, and the necessity for specialist knowledge to apply and develop the underlying systems, provide the motivation for the timely application and development of image analysis to plant biology.…”

Section: Introductionmentioning

confidence: 99%

From image processing to computer vision: plant imaging grows up

Dee

French

2015

Functional Plant Biol.

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Abstract. Image analysis is a field of research which, combined with novel methods of capturing images, can help to bridge the genotype-phenotype gap, where our understanding of the genotype has until now been leaps and bounds ahead of our ability to work with the phenotype. Methods of automating image capture in plant science research have increased in usage recently, as has the need to provide objective and highly accurate measures on large image datasets, thereby bringing the phenotype back to the centre of interest. In this special issue of Functional Plant Biology, we present some recent advances in the field of image analysis, and look at examples of different kinds of image processing and computer vision, which is occurring with increasing frequency in the plant sciences.

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“…Most root phenotyping platforms focus on measurements at high throughput of selected root traits on a large number of plants, with the objective of detecting quantitative trait loci usable in breeding (Kuijken et al, 2015). For example, Atkinson et al (2015) reported a phenotyping platform where root systems grow in 2D on a filter paper for a few days. Platforms where root systems grow in 3D also have been developed (IyerPascuzzi et al, 2010) and used for quantitative trait locus detection (Topp et al, 2013).…”

mentioning

confidence: 99%

A New Phenotyping Pipeline Reveals Three Types of Lateral Roots and a Random Branching Pattern in Two Cereals

et al. 2018

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Recent progress in root phenotyping has focused mainly on increasing throughput for genetic studies, while identifying root developmental patterns has been comparatively underexplored. We introduce a new phenotyping pipeline for producing high-quality spatiotemporal root system development data and identifying developmental patterns within these data. The SmartRoot image-analysis system and temporal and spatial statistical models were applied to two cereals, pearl millet (Pennisetum glaucum) and maize (Zea mays). Semi-Markov switching linear models were used to cluster lateral roots based on their growth rate profiles. These models revealed three types of lateral roots with similar characteristics in both species. The first type corresponds to fast and accelerating roots, the second to rapidly arrested roots, and the third to an intermediate type where roots cease elongation after a few days. These types of lateral roots were retrieved in different proportions in a maize mutant affected in auxin signaling, while the first most vigorous type was absent in maize plants exposed to severe shading. Moreover, the classification of growth rate profiles was mirrored by a ranking of anatomical traits in pearl millet. Potential dependencies in the succession of lateral root types along the primary root were then analyzed using variable-order Markov chains. The lateral root type was not influenced by the shootward neighbor root type or by the distance from this root. This random branching pattern of primary roots was remarkably conserved, despite the high variability of root systems in both species. Our phenotyping pipeline opens the door to exploring the genetic variability of lateral root developmental patterns. Breakthrough Technologieswww.plantphysiol.org on April 29, 2019 -Published by Downloaded from

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Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat

Abstract: HighlightA phenotyping pipeline was used to quantify seedling root architectural traits in a wheat double haploid mapping population. QTL analyses revealed a potential major effect gene regulating seedling root vigour/growth.

Cited by 190 publications

References 28 publications

Performance of Ethiopian bread wheat (Tritium aestivum L.) genotypes under contrasting water regimes: potential sources of variability for drought resistance breeding

Performance of Ethiopian bread wheat (Tritium aestivum L.) genotypes under contrasting water regimes: potential sources of variability for drought resistance breeding

From image processing to computer vision: plant imaging grows up

A New Phenotyping Pipeline Reveals Three Types of Lateral Roots and a Random Branching Pattern in Two Cereals

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