Contrasting genetic regulation of plant development in wild barley grown in two European environments revealed by nested association mapping

Herzig, Paul; Maurer, Andreas; Draba, Vera; Sharma, Rajiv; Draicchio, Fulvia; Bull, Hazel; Milne, Linda; Thomas, William; Flavell, Andrew J.; Pillen, Klaus

doi:10.1093/jxb/ery002

Cited by 35 publications

(69 citation statements)

References 89 publications

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“…Flowering under long days is promoted by the photoperiod responsive Ppd-H1 Supplementary Table S8a). This finding is in accordance with several other studies conducted in barley 20,23,25 . At these locations, the wild allele of Ppd-H1 accelerated plant development in HEB-YIELD (SHO, HEA and maturity (MAT)) with a maximum effect of -9.0 days in Halle.…”

Section: Ppd-h1supporting

confidence: 94%

“…In order to explore the interplay between flowering time regulation and yield formation, we investigated the effects of four major flowering time genes, Ppd-H1, Sdw1, Vrn-H1 and Table S8a). The relevance of these candidate genes has been reported in various studies 34,36 , including the wild barley NAM population HEB-25 18,20,22,25 . The wild barley lines of HEB-YIELD were selected to compare the effects of wild and cultivated alleles at these four flowering time loci ( Supplementary Table S1).…”

Section: Flowering Time Genes Exhibit Pleiotropic Effects On Yield Fomentioning

confidence: 95%

“…Wild barley accessions, in particular H. v. ssp. spontaneum, the progenitor of cultivated barley have been used to improve disease resistance 24,82 and abiotic stress tolerance 22,69,83,84 , as well as plant developmental traits 18,20,25 and quality traits 82,85,86 . The successful use of wild relatives to increase grain yield of barley has not been reported frequently, some exceptions are available 69,87,88 .…”

Section: The Best Wild Barley Heb-yield Lines Match the Yield Performmentioning

confidence: 99%

“…The usefulness of wild germplasm for future breeding has often been emphasized [14][15][16] , mostly as a source to improve biotic resistance and abiotic stress tolerance rather than to directly increase grain yield 17 . Recent studies in wild barley indicate the existence of vast phenological variation for important agronomic traits [18][19][20][21][22][23][24][25] .…”

Section: Introductionmentioning

confidence: 99%

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Barley yield formation under abiotic stress depends on the interplay between flowering time genes and environmental cues

Wiegmann

Maurer

Pham

et al. 2018

Preprint

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Since the dawn of agriculture, crop yield has always been impaired through abiotic stresses. In a field trial across five locations worldwide, we tested three abiotic stresses, nitrogen deficiency, drought and salinity, using HEB-YIELD, a selected subset of the wild barley nested association mapping population HEB-25. We show that barley flowering time genes Ppd-H1, Sdw1, Vrn-H1 and Vrn-H3 exert pleiotropic effects on plant development and grain yield. Under field conditions, these effects are strongly influenced by environmental cues like day length and temperature. For example, in Al-Karak, Jordan, the day length-sensitive wild barley allele of Ppd-H1 was associated with an increase of grain yield by up to 30% compared to the insensitive elite barley allele. The observed yield increase is accompanied by pleiotropic effects of Ppd-H1 resulting in shorter life cycle, extended grain filling period and increased grain size. Our study indicates that the adequate timing of plant development is crucial to maximize yield formation under harsh environmental conditions. We provide evidence that wild barley germplasm, introgressed into elite barley cultivars, can be utilized to improve grain yield. The presented knowledge may be transferred to related crop species like wheat and rice securing the rising global food demand for cereals.

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Section: Ppd-h1supporting

confidence: 94%

Section: Flowering Time Genes Exhibit Pleiotropic Effects On Yield Fomentioning

confidence: 95%

Section: The Best Wild Barley Heb-yield Lines Match the Yield Performmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Barley yield formation under abiotic stress depends on the interplay between flowering time genes and environmental cues

Wiegmann

Maurer

Pham

et al. 2018

Preprint

Self Cite

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“…We analysed two polygenic traits in the barley NAM population: days to heading (DTH) and yield (YLD), which were respectively taken from Herzig et al (2018) and Sharma et al (2018). Since only raw data on DTH and YLD were provided, we calculated the least squares means of DTH and YLD for 1,420 lines based on the fixed effects of location, nitrogen treatment and year.…”

Section: Methodsmentioning

confidence: 99%

Origin Specific Genomic Selection: a simple process to optimize the favourable contribution of parents to progeny

Yang

Sharma

Hearne

et al. 2019

Preprint

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17Modern crop breeding is in constant demand for new genetic diversity as part of the arms 18 race with genetic gain. The elite gene pool has limited genetic variation and breeders are 19 trying to introduce novelty from unadapted germplasm, landraces and wild relatives. For 20 polygenic traits, currently available approaches to introgression are not ideal, as there is a 21 demonstrable bias against exotic alleles during selection. Here, we propose a partitioned 22

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Multi-parent multi-environment QTL analysis: an illustration with the EU-NAM Flint population

2020

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Key message 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. Electronic supplementary material The online version of this article (10.1007/s00122-020-03621-0) contains supplementary material, which is available to authorized users.

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Contrasting genetic regulation of plant development in wild barley grown in two European environments revealed by nested association mapping

Abstract: Plant development in a barley nested association mapping population is controlled by interacting genotypic (wild donor alleles) and environmental (geographical location) effects.

Cited by 35 publications

References 89 publications

Barley yield formation under abiotic stress depends on the interplay between flowering time genes and environmental cues

Barley yield formation under abiotic stress depends on the interplay between flowering time genes and environmental cues

Origin Specific Genomic Selection: a simple process to optimize the favourable contribution of parents to progeny

Multi-parent multi-environment QTL analysis: an illustration with the EU-NAM Flint population

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