Genome-wide meta-analysis on yield and yield-related QTLs in barley (Hordeum vulgare L.)

Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions

“…2 , 3 ). This is consistent with previous results in barley, maize and rice 15 , 19 , 26 . The regions with high SV frequency could play an effective role in stress response 27 .…”

“…An additional benefit of this approach is the reduction of confidence intervals (CIs) in the MQTLs leading to improved genetic resolution for marker-assisted selection (MAS) and identification of candidate genes (CGs). Together, MQTL analysis may increase selection accuracy and efficiency, thus enhancing genetic gains in plants breeding programs 5 , 9 , 13 – 15 . Several MQTL studies for drought stress have been conducted in cereals such as wheat 16 , maize 8 , 17 , and barley 5 , 18 .…”

Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study

“…Both methods have particular advantages, such as higher statistical power and lower false positive rate for QTL mapping and relatively high mapping accuracy offered by association mapping 53 . Combining meta-analysis and association mapping can exactly identify suitable candidate genes involved in complex agronomic traits, such as grain yield, biomass, and phenology in wheat, barley and other close cereal species 12 . conclusion Overall, despite the moderate value of heritability and the fairly small size of the panel examined in this study, the results revealed 24 significant loci (FDR ≤ 0.05) associated with two traits: total tiller number and fertile tiller number under two irrigation regimes conditions at chromosomes 1A, 2A, 2B, 2D, 5D, 6A, 6B, 6D, 7A, and 7D.…”

“…Both methods have particular advantages, such as higher statistical power and lower false positive rate for QTL mapping and relatively high mapping accuracy offered by association mapping 53 . Combining meta-analysis and association mapping can exactly identify suitable candidate genes involved in complex agronomic traits, such as grain yield, biomass, and phenology in wheat, barley and other close cereal species 12 .…”

“…This method has been used to determine consensus regions of the genome across multiple QTL studies for their effects and consistency across different genetic backgrounds and environments, also to refine and confirm QTL positions on a consensus map via mathematical models. Reducing the CI of the MQTLs in comparison with QTLs is another indispensable perks of MQTL analysis [11][12][13][14][15] . More recently, a number of studies have applied the QTL meta-analysis method to different traits in wheat, including root morphological traits 13,16 , grain traits 11 , fusarium head blight resistance 14,17 , adaptation to drought and heat stress 18 and leaf rust resistance 19 .…”