1.2.1 Molecular Marker Resources
Although we have available tools, understanding of the genetic basis of adaptation is still an interesting task. We only have a basic understanding of most important traits, and the number of genes controlling each of these traits is large; therefore, the entire (and objective) approach would be understanding correlation between genes with phenotypes by scanning the whole genome with molecular markers (Howe and Brunner 2005). Molecular makers are used to detect the genetic variation caused by DNA polymorphisms in the DNA. The whole genome sequencing (WGS) provided the basis for the development of thousands of simple sequence repeat (SSR) markers and millions of single-nucleotide polymorphism (SNP) markers. The main method for the development of plant adaptation is molecular mapping and marker-assisted selection. In different species, amplified fragment length polymorphism (AFLPs), restriction fragment length polymorphism (RFLPs), RAPDs, microsatellites or simple sequence repeat (SSR), and SNPs are used for mapping of interesting traits (Iqbal 2019).
Since commercial SNP-genotyping platforms, such as Taqman, SNPlex, KASPar, Axiom Biobank, Infinium II, BioMark HD, GoldenGate, and iPlex, have been developed, the cost per data point for SNP-based genotyping has become cheaper than that for SSRs. However, the SNP information for target organisms is essential for commercial SNP-genotyping platforms, causing the increased costs and a longer experimental time (Kim et al. 2016; Chung et al. 2017).
Appearance of the next-generation sequencing (NGS) technologies has provided new opportunities for potent genotyping in various plant species. Recent improvements in high-throughput sequencing have enabled sequences to be used to detect and score single-nucleotide polymorphisms (SNPs) by shortening of the time-consuming process needed for marker development (Chung et al. 2017). Three main complexity reduction methods, namely reduced representation libraries (RRLs), restriction site associated DNA (RAD) sequencing, and genotyping-by-sequencing (GBS), are routinely used. Among these, GBS is a simple, robust, and affordable procedure for SNP distinguishing and mapping. Totally, this approach decreases complexity of genome with restriction enzymes (REs) in high diversity, and large genome species for efficient, high-throughput, and highly multiplexed sequencing. By using appropriate REs, repetitive regions of genomes can be inhibited and lower copy regions can be targeted, which decrease problems of alignments in genetically diverse species. This method was first explained by Elshire Robert et al. (2011). However, sequencing-based genotyping methods require computational expertise and a lot of time for analysing of data. This inhibits its use in marker-assisted breeding where timely selection is very crucial (Deshmukh et al. 2014).
Genome-wide association study (GWAS) is an observational study of a genome-wide set of genetic variants in different individuals to observe association of any variant with a trait. GWAS assesses the entire genome, opposite to methods that specifically test a small number of prespecified genetic regions. GWAS typically concentrates on correlations between single-nucleotide polymorphisms (SNPs) and traits. In general, where natural selection is acting and fixing the allele (eliminating other variants) of the SNPs, that constitutes the most favourable genetic adaptation (Barreiro et al. 2008).
Integrative investigations including GWAS, functional studies, selection scans, and fitness measurements in this regard have successfully distinguished loci for adaptation, demonstrated the molecular basis of genetic trade-offs, and showed that fitness can be predicted by polygenic effects of a number of loci related to local climate (Bamba et al. 2019).
1.2.2 QTL Mapping
Candidate genes can also be distinguished based on their positions on quantitative trait locus (QTL) maps or patterns of gene expression. Mapping quantitative trait loci (QTL) has become a routine tool for complex traits in functional genomic studies. Functional genomics is an important tool to find the correlation between phenotype and genome of an organism subjected to various environmental conditions (Soda et al. 2015; Ahmad et al. 2018). However, the construction of a high-density genetic linkage map is essential for genetic investigation of a target trait through quantitative trait locus (QTL) analysis. Moreover, high-resolution genetic linkage map is a crucial and powerful tool for positional cloning of genes, comparative genomic analysis, and scaffold sequence anchoring and genome assembly (Jones et al. 2009; Tang et al. 2019).
QTL analysis is complicated by the fact that one QTL region can have pleiotropic effects on a wide range of traits or consists of multiple QTLs. In addition, QTLs are frequently subjected to epistatic interactions, and their traits can be significantly influenced by the environment (Dixit et al. 2014; Tsaneva et al. 2019), so it is important to identify specific genes from new germplasm resources that are tolerant to multiple stresses. Exploit of the functions of genes that are responsible for drought will enable the plant biologists to use them in plant breeding programs to obtain cultivars resistant to drought stress (Ahmed et al. 2011). Realizing that mechanism of drought tolerance is quantitatively inherited and controlled by various genetic loci has led to the development of several drought-related QTLs (Sayed et al. 2012; Kalladan et al. 2013). Ahmad et al. (2018) have collected QTLs for different traits related to the ada...