Genome-Wide Association Studies and Next-Generation Sequencing in Plant Response

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FIGURE 10.2 The workflow of the process used in genome-wide association studies.

GWAS in crops are much less costly than that of humans because high

population is required to detect the QTLs among humans than that of crops

and the number of markers should increase continually. Crops like maize,

rice, canola, wheat, sorghum, etc., has approved GWAS (Chen et al., 2017;

Tessmann et al., 2018; Raman et al., 2019; Neang et al., 2020). In the refer­

ence of rice, 1,083 cultivated varieties and 446 wild varieties were sequenced

and observed with the low genome coverage (Huang et al., 2012). In maize,

linkage mapping and GWAS were used together in the NAM panel in which

the genetic structural design of flowering time, leaf angle, leaf size and disease

resistance traits have been dissected (Buckler et al., 2009; Kump et al., 2011;

Poland et al., 2011; Tian et al., 2011). In crops GWAS include weighing the

trade-offs of increased false-negative and decreased false-positive rates that

helps in defining the structure of a particular crop (Korte & Farlow, 2013;

Myles et al., 2009; Platt et al., 2010; Vilhjalmsson et al., 2012).

In detecting the genotype and phenotype association in crops the most

favorable method is the mixed model (Bradbury et al., 2007; Yu et al., 2006).

Advancements in these models has significantly lowered the computational

time or calculation time and this is possible by EMMAX program, i.e., Effi­

cient Mixed-Model Association expedited and the compressed mixed linear

model method (Kang et al., 2010; Lipka et al., 2012; Lippert et al., 2011;

Zhang et al., 2009, 2010; Zhou et al., 2012).