Genome‐wide association mapping of Hagberg falling number, protein content, test weight and grain yield in UK wheat

Crop Science ◽  
2021 ◽  
Author(s):  
Jon White ◽  
Rajiv Sharma ◽  
David Balding ◽  
James Cockram ◽  
Ian J. Mackay
Keyword(s):  
Grain Yield ◽  
Association Mapping ◽  
Protein Content ◽  
Test Weight ◽  
Genome Wide Association ◽  
Falling Number ◽  
Genome Wide ◽  
Hagberg Falling Number

scholarly journals Genome-Wide Association Studies and Genomic Selection for Grain Protein Content Stability in a Nested Association Mapping Population of Spring Wheat

2021 ◽  
Author(s):  
Karansher S. Sandhu ◽  
Paul D. Mihalyov ◽  
Megan J. Lewien ◽  
Michael O. Pumphrey ◽  
Arron H Carter
Keyword(s):  
Association Mapping ◽  
Protein Content ◽  
Genomic Selection ◽  
Genetic Control ◽  
Spring Wheat ◽  
Grain Protein Content ◽  
Genome Wide Association ◽  
Grain Protein ◽  
Nested Association Mapping ◽  
Genome Wide

Grain protein content (GPC) is controlled by complex genetic systems and their interactions, and is an important quality determinant for hard spring wheat as it has a positive effect on bread and pasta quality. GPC is variable among genotypes and strongly influenced by environment. Thus, understanding the genetic control of wheat GPC and identifying genotypes with improved stability is an important breeding goal. The objectives of this research were to identify genetic backgrounds with less variation for GPC across environments and identify quantitative trait loci (QTLs) controlling the stability of GPC. A spring wheat nested association mapping (NAM) population of 650 recombinant inbred lines (RIL) derived from 26 diverse founder parents crossed to one common parent, 'Berkut', was phenotyped over three years of field trials (2014-2016). Genomic selection models were developed and compared based on prediction of GPC and GPC stability. After observing variable genetic control of GPC within the NAM population, seven RIL families displaying reduced marker-by-environment interaction were selected based on a stability index derived from Finlay-Wilkinson regression. A genome-wide association study identified seven significant QTLs for GPC stability with a Bonferroni-adjusted P value <0.05. This study also demonstrated that genome-wide prediction of GPC with ridge regression best linear unbiased estimates reached up to r = 0.69. Genomic selection can be used to apply selection pressure for GPC and improve genetic gain for GPC.

scholarly journals Genomic Selection and Genome-Wide Association Studies for Grain Protein Content Stability in a Nested Association Mapping Population of Wheat

Agronomy ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2528
Author(s):  
Karansher S. Sandhu ◽  
Paul D. Mihalyov ◽  
Megan J. Lewien ◽  
Michael O. Pumphrey ◽  
Arron H. Carter
Keyword(s):  
Association Mapping ◽  
Protein Content ◽  
Genomic Selection ◽  
Genetic Control ◽  
Spring Wheat ◽  
Grain Protein Content ◽  
Genome Wide Association ◽  
Grain Protein ◽  
Nested Association Mapping ◽  
Genome Wide

Grain protein content (GPC) is controlled by complex genetic systems and their interactions and is an important quality determinant for hard spring wheat as it has a positive effect on bread and pasta quality. GPC is variable among genotypes and strongly influenced by the environment. Thus, understanding the genetic control of wheat GPC and identifying genotypes with improved stability is an important breeding goal. The objectives of this research were to identify genetic backgrounds with less variation for GPC across environments and identify quantitative trait loci (QTLs) controlling the stability of GPC. A spring wheat nested association mapping (NAM) population of 650 recombinant inbred lines (RIL) derived from 26 diverse founder parents crossed to one common parent, ‘Berkut’, was phenotyped over three years of field trials (2014–2016). Genomic selection models were developed and compared based on predictions of GPC and GPC stability. After observing variable genetic control of GPC within the NAM population, seven RIL families displaying reduced marker-by-environment interaction were selected based on a stability index derived from a Finlay–Wilkinson regression. A genome-wide association study identified eighteen significant QTLs for GPC stability with a Bonferroni-adjusted p-value < 0.05 using four different models and out of these eighteen QTLs eight were identified by two or more GWAS models simultaneously. This study also demonstrated that genome-wide prediction of GPC with ridge regression best linear unbiased estimates reached up to r = 0.69. Genomic selection can be used to apply selection pressure for GPC and improve genetic gain for GPC.

scholarly journals Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

PLoS ONE ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. e0190162 ◽  
Author(s):  
Giacomo Mangini ◽  
Agata Gadaleta ◽  
Pasqualina Colasuonno ◽  
Ilaria Marcotuli ◽  
Antonio M. Signorile ◽  
...  
Keyword(s):  
Grain Yield ◽  
Association Mapping ◽  
Yield Components ◽  
Genome Wide Association ◽  
Genetic Dissection ◽  
Tetraploid Wheats ◽  
Genome Wide ◽  
Grain Yield Components

scholarly journals Performance of Wheat Varieties (Triticum aestivum L.) under Conservation Tillage Practices in Organic Agriculture

2011 ◽  
Vol 39 (2) ◽  
pp. 28 ◽  
Author(s):  
Dimitrios BILALIS ◽  
Anestis KARKANIS ◽  
Sotiria PATSIALI ◽  
Maria AGRIOGIANNI ◽  
Aristeidis KONSTANTAS ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Grain Yield ◽  
Protein Content ◽  
Conservation Tillage ◽  
Triticum Aestivum L ◽  
Conventional Tillage ◽  
Wheat Crop ◽  
Falling Number ◽  
Tillage Systems ◽  
Hagberg Falling Number

Field experiments were conducted to determine the effects of tillage systems and varieties on growth, yield and quality of wheat crop (Triticum aestivum L.). The experiments conducted at two sites were laid out in a split-plot design with four replicates, three main plots [conventional tillage (CT), no-tillage (NT) and minimum tillage (MT)] and four sub-plots (‘Siette’, ‘Panifor’, ‘Myrto’, ‘Estero’). The soil porosity and total nitrogen were higher in soils subjected to conservation tillage systems (NT and MT) than under conventional tillage. There were no differences in root growth neither between the tillage systems nor among the varieties. Yield was influenced by the tillage system and variety. The highest grain yield (421-459 kg ha-1) was found under the CT system with ‘Siette’, ‘Myrto’ and ‘Estero’ varieties. In contrast, the highest grain yield was observed under conservation tillage (NT and MT) with ‘Panifor’ variety. There were no significant differences between the tillage systems concerning the protein content and Zeleny value. In contrast, the highest Hagberg falling number was found with MT. Zeleny value was positively and significantly correlated with protein content. High flour quality, as demonstrated by high protein content and Zeleny value, and low Hagberg falling number, was produced in the ‘Estero’ variety.

Genome-wide association mapping for seed protein content in finger millet (Eleusine coracana) global collection through genotyping by sequencing

2020 ◽  
Vol 91 ◽  
pp. 102888 ◽  
Author(s):  
Apoorv Tiwari ◽  
Divya Sharma ◽  
Salej Sood ◽  
Jai Prakash Jaiswal ◽  
Satya Pratap Pachauri ◽  
...  
Keyword(s):  
Association Mapping ◽  
Protein Content ◽  
Finger Millet ◽  
Seed Protein ◽  
Genotyping By Sequencing ◽  
Eleusine Coracana ◽  
Genome Wide Association ◽  
Seed Protein Content ◽  
Genome Wide

scholarly journals Genome-wide association mapping of grain yield in a diverse collection of spring wheat (Triticum aestivum L.) evaluated in southern Australia

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0211730 ◽  
Author(s):  
Melissa Garcia ◽  
Paul Eckermann ◽  
Stephan Haefele ◽  
Sanjiv Satija ◽  
Beata Sznajder ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Grain Yield ◽  
Association Mapping ◽  
Spring Wheat ◽  
Triticum Aestivum L ◽  
Genome Wide Association ◽  
Genome Wide

scholarly journals Genome-wide association mapping in winter barley for grain yield and culm cell wall polymer content using the high-throughput CoMPP technique

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0173313 ◽  
Author(s):  
Andrea Bellucci ◽  
Alessandro Tondelli ◽  
Jonatan U. Fangel ◽  
Anna Maria Torp ◽  
Xin Xu ◽  
...  
Keyword(s):  
Cell Wall ◽  
Grain Yield ◽  
Association Mapping ◽  
High Throughput ◽  
Winter Barley ◽  
Genome Wide Association ◽  
Polymer Content ◽  
Cell Wall Polymer ◽  
Genome Wide
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