Precision Phenotyping Reveals Novel Loci for Quantitative Resistance to Septoria Tritici Blotch

Yates, Steven; Mikaberidze, Alexey; Krattinger, Simon G.; Abrouk, Michaël; Hund, Andreas; Yu, Kang; Studer, Bruno; Fouché, Simone; Meile, Lukas; Pereira, Daniel; Karisto, Petteri; McDonald, Bruce A.

doi:10.34133/2019/3285904

Cited by 41 publications

(51 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…S4). This is consistent with prior work using the same population (Kollers et al, 2013;Yates et al, 2019). On average across all chromosomes, LD decayed below an r 2 of 0.2 at a distance of MB.…”

Section: Linkage Disequilibrium and Population Structuresupporting

confidence: 90%

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

Kronenberg

Yates

Boer

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

9In wheat, the timing and dynamics of stem elongation are tightly linked to temperature. It is 10 yet unclear if and how these processes are genetically controlled. We aimed to identify 11 quantitative trait loci (QTL) controlling temperature-response during stem elongation and to 12 evaluate their relationship to phenology and height. Canopy height of the GABI wheat panel 13was measured between 2015 and 2017 in bi-weekly intervals in the field phenotyping platform 14(FIP) using a LIDAR. Temperature-response was modelled using a linear regression between 15 stem elongation and the mean interval temperature. 16The temperature-response was highly heritable (H 2 = 0.81) and positively related to a later 17 start and end of stem elongation as well as an increased final height (FH). Genome-wide 18 association mapping revealed three temperature-responsive and four temperature-19 irresponsive QTL. Furthermore, putative candidate genes for temperature-response QTL were 20 frequently related to the flowering pathway in A. thaliana while temperature-irresponsive 21QTLs corresponded with growth and reduced height genes. These loci, together with the loci 22for start and end of stem elongation accounted for 49% of the variability in height. 23This demonstrates how high throughput field phenotyping in combination with environmental 24 covariates can contribute to a smarter selection of climate-resilient crops. 25 26

show abstract

Section: Linkage Disequilibrium and Population Structuresupporting

confidence: 90%

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

Kronenberg

Yates

Boer

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition, we detected 15 QTL whose positions overlapped with previously published QTL conferring resistance to STB (detailed in Figure 3 and Table S5). Of these, four QTL (QStb.teagasc-2D.1, QStb.teagasc-4B.1, QStb.teagasc-6D.2, and QStb.teagasc-7B.1) were co-located with published adult plant STB resistance QTL identified under German field conditions [76], while nine QTL co-located with QTL from a single previously published study of field STB resistance in Switzerland [74]. Notably, QStb.teagasc-7B.1 co-located with STB resistance QTL identified in both [74,76].…”

Section: Qtl Analysis and Comparison With Previously Reported Stb Qtlmentioning

confidence: 85%

“…Of these, four QTL (QStb.teagasc-2D.1, QStb.teagasc-4B.1, QStb.teagasc-6D.2, and QStb.teagasc-7B.1) were co-located with published adult plant STB resistance QTL identified under German field conditions [76], while nine QTL co-located with QTL from a single previously published study of field STB resistance in Switzerland [74]. Notably, QStb.teagasc-7B.1 co-located with STB resistance QTL identified in both [74,76]. As these QTL appear to have been identified in more than one country, this suggests they may provide sources of durable resistance against different pathogen populations and prevailing conditions.…”

Section: Qtl Analysis and Comparison With Previously Reported Stb Qtlmentioning

confidence: 85%

“…The QTL identified were compared with previously reported Stb genes and QTL by projecting onto the physical map in The Triticeae Toolbox (T3) database to identify the co-located genes/QTL and determine the novelty of others. For our QTL co-location study, only QTL mapping and genome-wide association scan (GWAS) studies of STB using high-throughput marker platforms were considered [60,[74][75][76][77][78][79][80][81][82][83]…”

Section: Alignment Of Qtl Identified In This Study With Previously Rementioning

confidence: 99%

“…As Stb.teagasc-7B.1 was the most significant locus identified in the MAGIC population, having been identified in seven of our 13 datasets, we consider this QTL in more detail here. QStb.teagasc-7B.1 co-located with eight previously reported STB QTL (IWA814 [77], IWA3513 [77], AX-95223861 [76], QTL_7B_1, and QTL_7B_2 [81], QStb.B22-7B.b [79], wsnp_JD_c646_966400 [80] and Interval_ID-17 [74]) and three Stb genes (Stb8 [85], Stb13 and Stb14 [86]). We found resistance alleles at QStb.teagasc-7B.1 to be conferred by the founders Alchemy, while alleles from the remaining five parents were associated with susceptibility ( Figure S4).…”

Section: Qtl Analysis and Comparison With Previously Reported Stb Qtlmentioning

confidence: 99%

See 2 more Smart Citations

Genetic Analysis Using a Multi-Parent Wheat Population Identifies Novel Sources of Septoria Tritici Blotch Resistance

Riaz

Kock-Appelgren

Hehir

et al. 2020

Genes

View full text Add to dashboard Cite

Zymoseptoria tritici is the causative fungal pathogen of septoria tritici blotch (STB) disease of wheat (Triticum aestivum L.) that continuously threatens wheat crops in Ireland and throughout Europe. Under favorable conditions, STB can cause up to 50% yield losses if left untreated. STB is commonly controlled with fungicides; however, a combination of Z. tritici populations developing fungicide resistance and increased restrictions on fungicide use in the EU has led to farmers relying on fewer active substances. Consequently, this serves to drive the emergence of Z. tritici resistance against the remaining chemistries. In response, the use of resistant wheat varieties provides a more sustainable disease management strategy. However, the number of varieties offering an adequate level of resistance against STB is limited. Therefore, new sources of resistance or improved stacking of existing resistance loci are needed to develop varieties with superior agronomic performance. Here, we identified quantitative trait loci (QTL) for STB resistance in the eight-founder “NIAB Elite MAGIC” winter wheat population. The population was screened for STB response in the field under natural infection for three seasons from 2016 to 2018. Twenty-five QTL associated with STB resistance were identified in total. QTL either co-located with previously reported QTL or represent new loci underpinning STB resistance. The genomic regions identified and the linked genetic markers serve as useful resources for STB resistance breeding, supporting rapid selection of favorable alleles for the breeding of new wheat cultivars with improved STB resistance.

show abstract

Genome‐wide association analysis of freezing tolerance in soft red winter wheat

et al. 2022

View full text Add to dashboard Cite

Freezing tolerance is likely to be an important adaptation for both natural populations and crop cultivars like winter wheat (Triticum aestivum L.). In the United States, winter wheat represents 80% of the total wheat production. Understanding the genetic basis of freezing tolerance in wheat furthers our knowledge of abiotic stress tolerance in plants and may inform breeding programs aimed at adjusting the level of freezing tolerance for a given region. We examined freezing tolerance in a 267-line panel of elite soft red winter wheat that has previously been used for genome-wide association study (GWAS) on agronomically important traits. We were specifically interested in determining the extent of genetic variation for freezing tolerance within the panel, what the genetic basis of that variation is, and if there are correlations between freezing tolerance and other agronomically important traits. We found significant variation in freezing tolerance among the lines, measured as survival through three total days at −8 ˚C. We performed a GWAS on freezing tolerance and identified 13 candidate loci, with nearby candidate genes involved in different functions potentially associated with freezing tolerance. In addition, we found significant correlations between freezing tolerance and seven previously published yield related traits. In summary, we found considerable variation in freezing tolerance in this panel that is associated with yield related traits. Thus, these lines may be useful for breeding programs seeking to optimize freezing tolerance for present and future climatic conditions. INTRODUCTIONWheat (Triticum aestivum L.) is one of the most important crops worldwide. It is cultivated in ∼200 million ha (http: //www.fao.org/faostat/en/#data/QC/visualize) (Zhao et al., 2013) and provided about 20% of all dietary calories consumed globally (

show abstract

Precision Phenotyping Reveals Novel Loci for Quantitative Resistance to Septoria Tritici Blotch

Cited by 41 publications

References 52 publications

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

Temperature response of wheat affects final height and the timing of stem elongation under field conditions

Genetic Analysis Using a Multi-Parent Wheat Population Identifies Novel Sources of Septoria Tritici Blotch Resistance

Genome‐wide association analysis of freezing tolerance in soft red winter wheat

Contact Info

Product

Resources

About