**2. Applications of SNPs**

Determining the DNA sequence variation in the genome is very important for plant genetics and breeding. Genetic variation can be analyzed using various molecular markers. The discovery of single nucleotide polymorphisms (SNPs), which underpin the difference between alleles, has been simplified and accelerated by recent advances in next- and third-generation sequencing technology and MALDI-TOF mass spectrophotometry compared to traditional methods [20]. Even creating machine learning models to select true SNPs directly from sequence data appears to be groundbreaking in this area [21].

The selection of SNPs enables the selection of desired lines in large-scale populations. The marker can be used to modulate the cultivation program for the determination of the relevant feature and improvement of the crop more economically using new-generation technologies than using traditional methods [22]. Today, plant breeding is dependent on SNPs and similar differences for fast and costeffective analysis of germplasm and feature mapping. These differences improve the understanding of genetics that can change the strategy of developing new varieties.

**55**

*Single Nucleotide Polymorphisms (SNPs) in Plant Genetics and Breeding*

transmit the desired allele to a large number of populations [23].

Because the desired trait is under genetic control, phenotypic experiments can be attempted faster, and the breeder not only does the early trait selection but also can

The application of SNPs on genetic diversity is very important in terms of illuminating the relationships between varieties. This allows plant growers to improve crop plants and protect germplasm. Genetic diversity information can then be evaluated to identify new alleles in breeding programs. SNPs have been applied for several years to assess diversity in specific genes or genomic regions, and the results are estimated to extract phylogenetic relationships between species. However, the emergence of new and third-generation technologies allows the genome to assess SNP-based genetic diversity at scale and can be useful in conserving diversity in domesticated populations. Plant phylogenetic and evolutionary researches is traditionally based on sequence genes and hence the knowledge of SNPs [27]. Nuclear and chloroplast gene regions, which have been preserved for generations, are a rich source of phylogenetic information for evolutionary analysis in plants. The diversity and genotyping of the SNP sequence in these protected regions is used to explain a wide variety of phylogenetic and evolutionary relationships and inheritance extraction [28]. However, molecular phylogenetic studies only provide information about the distribution of populations, and contribution to agricultural applications is negligible compared to SNPs

SNPs can also be used to discover new genes and their functions by affecting gene expression and transcriptional and translational promoter activities. Therefore, they may be responsible for phenotypic variations between individuals in improving agronomic features. It is also important to know the location of SNP in the genome, because if SNP is present in the coding region, it can greatly affect the activity and thermostability level of an enzyme or a similar product [30]. Sometimes it also depends on the substituted amino acid positions because some amino acid controls the activity of the expressed regions. Recent technological advances make it easier to identify various SNPs that can be used for product developments. It shows that SNPs in the functional parts of the gene can control the level of biotic and abiotic stress and improve the variety of abiotic and biotic stress

The integration of genomic technologies with traditional breeding can have a big impact in dealing with current and future environmental challenges more effectively [32]. In these conditions, germplasm in all plant species is imperative for rapid genetic gains in the productivity of these species using supportive approaches

As genomes of many species are fully sequenced, including human, *Arabidopsis*, and rice, the discovery of interest-specific sequence differences becomes easier [24]. These sequences enable screening of more than 1 million SNPs for each species. These polymorphisms can be used as simple genetic markers that can be identified around almost any gene. The usage of SNPs in detecting relationships between allelic forms of a gene and phenotypes, especially common diseases with multifactor genetics, high-resolution genetic map construction, linkage disequlibriumbased association mapping, genetic diagnostics, genetic diversity analysis, cultivar identification, and phylogenetic analysis, creates great potential for characterization of genetic resources [25]. SNPs are frequently found in the genome with at least one common (>20% allele frequency) SNP density per kilobase pair. It is mostly biallelic and therefore easy to analyze. More importantly, SNPs allow the combination of candidate gene approach and fusion-based fine mapping to identify the

*DOI: http://dx.doi.org/10.5772/intechopen.91886*

genes of interest [26].

determined by transcriptome analyzes [29].

tolerance crops by changing expressed region [31].

such as genetic and genomic sources.

#### *Single Nucleotide Polymorphisms (SNPs) in Plant Genetics and Breeding DOI: http://dx.doi.org/10.5772/intechopen.91886*

*The Recent Topics in Genetic Polymorphisms*

complex features and identifying the causes.

microarrays and next-generation sequencing.

future [4]. The use of DNA markers associated with crop yield is common in the development of various crops such as rice (*Oryza sativa*) [5], corn (*Zea mays*) [6], wheat (*Triticum aestivum*) [7], and tomatoes (*Lycopersicon esculentum*) [8].

If a single nucleotide change is detected by comparing the DNA of different living species, it is evaluated as there is a single nucleotide polymorphism. These changes in a single position are used as an effective genetic marker practically in both animal [9] and the plant [10, 11] species. Single nucleotide polymorphism (SNP) genotyping [12, 13] studies and the rapid progress in the development of genomic tools have led to the development of new powerful approaches in mapping

In parallel with the increase in multidisciplinary studies and the development of technology, it is essential to use both traditional breeding techniques and new tools emerging in the field of molecular genetics [14]. In these tools, the two most used methods in terms of the low costs and high performance in obtaining data are

Since the end of the twentieth century, microarrays have been used in the first place to know the transcriptional activity of a biological sample [15]. Although other techniques have been previously used in gene expression studies such as northern blot or quantitative PCR, the ability to determine the level of less represented genes of a mixture facilitated the analysis of thousands of genes in the same reaction and increased sensitivity [16]. In the next-generation sequencing, the main goal is to parallelize DNA sequencing so that the molecules of thousands or millions of genetic materials could be read simultaneously. Regardless of the technique used, it identifies a large number of markers, allowing the development of high-density genetic maps [17]. This technology has been successfully used to detect SNPs of

The wealth of data required to reveal evolutionary processes is based on highly efficient DNA sequencing. This technology enables nucleotide diversity studies related to a wide variety of species. The determination of the functionality of the genes of the wild species that have increased and continued in recent years and the presence of beneficial alleles for indirect plant breeding and yield improvement studies still make up an important topic for the future that is open for further

Determining the DNA sequence variation in the genome is very important for plant genetics and breeding. Genetic variation can be analyzed using various molecular markers. The discovery of single nucleotide polymorphisms (SNPs), which underpin the difference between alleles, has been simplified and accelerated by recent advances in next- and third-generation sequencing technology and MALDI-TOF mass spectrophotometry compared to traditional methods [20]. Even creating machine learning models to select true SNPs directly from sequence data appears to

The selection of SNPs enables the selection of desired lines in large-scale populations. The marker can be used to modulate the cultivation program for the determination of the relevant feature and improvement of the crop more economically using new-generation technologies than using traditional methods [22]. Today, plant breeding is dependent on SNPs and similar differences for fast and costeffective analysis of germplasm and feature mapping. These differences improve the understanding of genetics that can change the strategy of developing new varieties.

different genetically well-known species such as pine or corn [18, 19].

**54**

improvement.

**2. Applications of SNPs**

be groundbreaking in this area [21].

Because the desired trait is under genetic control, phenotypic experiments can be attempted faster, and the breeder not only does the early trait selection but also can transmit the desired allele to a large number of populations [23].

As genomes of many species are fully sequenced, including human, *Arabidopsis*, and rice, the discovery of interest-specific sequence differences becomes easier [24]. These sequences enable screening of more than 1 million SNPs for each species. These polymorphisms can be used as simple genetic markers that can be identified around almost any gene. The usage of SNPs in detecting relationships between allelic forms of a gene and phenotypes, especially common diseases with multifactor genetics, high-resolution genetic map construction, linkage disequlibriumbased association mapping, genetic diagnostics, genetic diversity analysis, cultivar identification, and phylogenetic analysis, creates great potential for characterization of genetic resources [25]. SNPs are frequently found in the genome with at least one common (>20% allele frequency) SNP density per kilobase pair. It is mostly biallelic and therefore easy to analyze. More importantly, SNPs allow the combination of candidate gene approach and fusion-based fine mapping to identify the genes of interest [26].

The application of SNPs on genetic diversity is very important in terms of illuminating the relationships between varieties. This allows plant growers to improve crop plants and protect germplasm. Genetic diversity information can then be evaluated to identify new alleles in breeding programs. SNPs have been applied for several years to assess diversity in specific genes or genomic regions, and the results are estimated to extract phylogenetic relationships between species. However, the emergence of new and third-generation technologies allows the genome to assess SNP-based genetic diversity at scale and can be useful in conserving diversity in domesticated populations. Plant phylogenetic and evolutionary researches is traditionally based on sequence genes and hence the knowledge of SNPs [27]. Nuclear and chloroplast gene regions, which have been preserved for generations, are a rich source of phylogenetic information for evolutionary analysis in plants. The diversity and genotyping of the SNP sequence in these protected regions is used to explain a wide variety of phylogenetic and evolutionary relationships and inheritance extraction [28]. However, molecular phylogenetic studies only provide information about the distribution of populations, and contribution to agricultural applications is negligible compared to SNPs determined by transcriptome analyzes [29].

SNPs can also be used to discover new genes and their functions by affecting gene expression and transcriptional and translational promoter activities. Therefore, they may be responsible for phenotypic variations between individuals in improving agronomic features. It is also important to know the location of SNP in the genome, because if SNP is present in the coding region, it can greatly affect the activity and thermostability level of an enzyme or a similar product [30]. Sometimes it also depends on the substituted amino acid positions because some amino acid controls the activity of the expressed regions. Recent technological advances make it easier to identify various SNPs that can be used for product developments. It shows that SNPs in the functional parts of the gene can control the level of biotic and abiotic stress and improve the variety of abiotic and biotic stress tolerance crops by changing expressed region [31].

The integration of genomic technologies with traditional breeding can have a big impact in dealing with current and future environmental challenges more effectively [32]. In these conditions, germplasm in all plant species is imperative for rapid genetic gains in the productivity of these species using supportive approaches such as genetic and genomic sources.
