2019
DOI: 10.3389/fpls.2019.00464
|View full text |Cite
|
Sign up to set email alerts
|

Genome-Wide Association Study Reveals Novel Genomic Regions Associated With High Grain Protein Content in Wheat Lines Derived From Wild Emmer Wheat

Abstract: Grain protein content (GPC) and yield are of two important traits in wheat, but their negative correlation has hampered their simultaneous improvement in conventional breeding. Wild emmer wheat ( Triticum turgidum ssp. dicoccoides ) is an important genetic resource for wheat quality improvement. In this study, we report a genome-wide association study (GWAS) using 13116 DArT-seq markers to characterize GPC in 161 wheat lines derived from wild emmer. Using a general… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
40
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
6
2

Relationship

2
6

Authors

Journals

citations
Cited by 32 publications
(40 citation statements)
references
References 71 publications
0
40
0
Order By: Relevance
“…The sequences of the significant DArT‐seq markers identified by GWAS were used to perform BLASTn searches against the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v1.0 with annotation of genes available in the URGI wheat database (https://wheat-urgi.versailles.inra.fr/Seq-Repository/Annotations, accessed 15 Oct. 2019) to determine the physical position of each marker, and identify genes within a region 2500 bp upstream and 2500 bp downstream of this position (Liu et al, 2017; Wu et al, 2017; Juliana et al, 2018; Liu et al 2019). Candidate genes were annotated using Oryza sativa and Arabidopsis thaliana as background species at P < 10 −5 using KOBAS 3.0 (Wu et al, 2006).…”
Section: Methodsmentioning
confidence: 99%
“…The sequences of the significant DArT‐seq markers identified by GWAS were used to perform BLASTn searches against the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v1.0 with annotation of genes available in the URGI wheat database (https://wheat-urgi.versailles.inra.fr/Seq-Repository/Annotations, accessed 15 Oct. 2019) to determine the physical position of each marker, and identify genes within a region 2500 bp upstream and 2500 bp downstream of this position (Liu et al, 2017; Wu et al, 2017; Juliana et al, 2018; Liu et al 2019). Candidate genes were annotated using Oryza sativa and Arabidopsis thaliana as background species at P < 10 −5 using KOBAS 3.0 (Wu et al, 2006).…”
Section: Methodsmentioning
confidence: 99%
“…The OFP gene expression data were obtained from transcriptome data for Chinese Spring wheat seedlings under drought and heat stress conditions [ 33 ]. Chinese Spring wheat transcriptome data under GA, jasmonic acid, abscisic acid, salicylic acid, and cytokinin treatment were used to obtain OFP gene expression data from the Introduction to the Triticeae Multi-omics Center database [ 34 ]. The expression data were used to construct a heat map using TBtool [ 35 ].…”
Section: Methodsmentioning
confidence: 99%
“…The same set of 161 advanced lines (Liu et al, 2019) derived from a cross between CN16 and D1 were used in the present study. Wheat plants were arranged in the field using a randomized complete block design with three replicates over two growing seasons (2015 and 2016) at the Chongzhou (2015CZ and 2016CZ) and Wenjiang (2015WJ and 2016WJ) experimental stations of Sichuan Agricultural University, China (Liu et al, 2019). Individual plants were spaced 10 cm apart within a 2 m row with 30 cm between rows.…”
Section: Plant Materials and Experimental Designmentioning
confidence: 99%
“…Genome-wide association analysis (GWAS) has been widely used for deciphering the genetic basis of multiple traits in crops (Su et al, 2016;Wang et al, 2016;Ates et al, 2018;Liu et al, 2019). It was available to study QTLs related to agronomically important traits in large sets of germplasm resources such as landraces (Liu et al, 2017), elite cultivars (Sukumaran et al, 2015), and advanced breeding lines (Wang et al, 2017) as well as backbone parents and their derived lines (Yu and Tian, 2012;Yu et al, 2014;Xiao et al, 2016;Liu et al, 2019). In wheat, GWAS has been extensively applied to reveal genomic regions controlling traits such as GPC (Liu et al, 2019), grain ionome (Fatiukha et al, 2020), and yield-related traits (Tadesse et al, 2015).…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation