Allele Mining and Development of Kompetitive Allele Specific PCR (KASP) Marker in Plant Breeding

Abstract

Crop improvement refers to the systematic approach of discovering and selecting plants that possess advantageous alleles for specific target genes. The foundation of crop improvement initiatives typically relies on the fundamental concepts of genetic diversity and the genetic architecture of agricultural plants. Allele mining is a contemporary and efficacious technique utilized for the identification of naturally occurring allelic variations within genes that exhibit advantageous characteristics. Consequently, the utilization of allele mining has significant potential as a feasible approach for enhancing crop-related endeavors. The gene pool of a plant exhibits a substantial degree of genetic variety, characterized by the presence of a multitude of mechanism genes. The utilization of genetic variants for the detection and separation of novel alleles of genes that display favorable traits from the current gene pool, and their subsequent incorporation into the development of improved cultivars through the application of marker-assisted selection, is of utmost importance.

1. Introduction

Plant breeding is a vital field in agriculture that focuses on generating crop varieties with enhanced features to suit the expanding worldwide demand for food, feed, fiber, and bioenergy. Over the decades, conventional breeding methods have played a key role in crop improvement [1, 2]. However, the advent of molecular biology and genomics has revolutionized the profession, giving plant breeders with sophisticated tools to examine the genetic basis of desired traits. One of these technologies, known as allele mining, has emerged as a basic approach to detect and harness beneficial genetic variants within plant populations. In this comprehensive discussion, we will study the notion of allele mining, its significance in identifying favorable genetic variations, its usefulness in boosting agricultural attributes, and the methodologies and procedures employed in this process [3].

The process of introducing desirable genetic variants or alleles into the genetic makeup of a plant population or cultivar is referred to as allele introduction in plants [4]. This can be accomplished through a variety of breeding approaches that aim to increase individual features or overall performance. Allele introduction is an important stage in plant breeding because it allows breeders to harness genetic variation and develop new plant types with desirable traits. The practice of searching and detecting novel genetic variations or alleles within a species’ gene pool is referred to as allele mining in plant breeding [5]. This strategy seeks to identify and exploit valuable genetic resources for agricultural improvement. Breeders can acquire desirable features that may be absent or underrepresented in cultivated varieties by tapping into existing genetic diversity. Breeders can use these techniques to transfer desirable alleles into plants and generate new varieties with improved features including disease resistance, stress tolerance, yield potential, qualitative qualities, or agronomic performance. The technique of choice is determined by the specific breeding objectives, the availability of genetic resources, and the features of the target plant species. KASP markers, also known as Kompetitive allele-specific PCR markers, are a type of molecular marker that find widespread application in the field of genetic analysis and plant breeding. They operate on the premise of allele-specific amplification through the utilization of real-time PCR that is based on fluorescence [6]. For the purpose of conducting large-scale screenings of the genetic variants that exist within plant populations, KASP markers offer a solution for genotyping that is high-throughput, quick, and economical. In the field of plant breeding, KASP markers provide a number of benefits, some of which are their high level of specificity, precision, scalability, and cost-effectiveness. They are very helpful when it comes to genotyping huge populations, carrying out high-throughput screening, and locating genetic variants that are connected with key features. In order to hasten the process of selecting better crop varieties and developing new ones, plant breeding programs have extensively included KASP markers into their procedures.

2. Allele mining and identifying desirable genetic variations

Allele mining, also known as allelic variation finding, is a rigorous and methodical strategy designed to investigate and ascertain the genetic variety present in a particular plant species or population. The fundamental objective of allele mining is the identification of alleles, which are variant forms of genes, that exhibit associations with specific qualities of interest. The alleles can exhibit variances in their DNA sequences, which can subsequently lead to differences in the expression or functionality of the corresponding genes [7]. The process of allele mining is of great significance in the exploration of the latent genetic capacity of crops, as it enables the identification of genetic variations that can be utilized for the enhancement of agricultural traits. The initial step in the process of allele mining is the acquisition of genetic data from a wide range of plant individuals or groups belonging to a certain species [8]. The variety in question encompasses a range of plant materials, such as conventional landraces, wild cousins, mutant lines, and other specimens that possess genetic variants with possible implications. The genetic information is thereafter submitted to meticulous study, frequently employing sophisticated molecular biology techniques and genomic tools [3, 9, 10].

3. Enhancing crop traits through allele mining

The significance of allele mining in plant breeding is broad and involves various fundamental areas of crop enhancement:

1. Increased Crop Yields: One of the main goals of plant breeding is to enhance crop varieties that can achieve higher yields in order to address the increasing worldwide demand for food and agricultural commodities. The process of allele mining plays a crucial role in the pursuit of this objective as it enables the identification of alleles that are linked to enhanced yield potential. These alleles have the potential to influence multiple facets of crop development, such as seed size, grain count, and photosynthetic efficiency.

2. Disease Resistance: Crop diseases produced by various pathogens, including bacteria, fungus, viruses, and nematodes, present substantial obstacles to the field of agriculture. The identification of alleles associated with disease resistance is of paramount importance in the development of crops that possess the ability to survive attacks by pathogens. Through the process of allele mining, breeders are able to identify genetic differences that provide inherent resistance to certain conditions. This allows for the development of crops that necessitate fewer chemical treatments, thereby mitigating environmental consequences and decreasing production expenses.

3. Stress Tolerance: Stress tolerance is a critical factor affecting crop output, as environmental stressors such as drought, heat, salt, and soil nutrient deficits can have a significant negative influence. The process of allele mining enables the identification of alleles that are correlated with stress tolerance, so enabling breeders to cultivate crop varieties that exhibit resilience in unfavorable environmental conditions. These genotypes have the potential to impact physiological systems, such as water consumption efficiency or ion transport, which play a crucial role in stress adaption.

4. Nutritional Quality: Nutritional Quality: In conjunction with enhancing crop productivity and stress tolerance, allele mining can also be employed to enhance the nutritional composition of agricultural produce. The identification of genes responsible for the synthesis of crucial minerals, vitamins, and antioxidants has the potential to facilitate the cultivation of crops with heightened nutritional content. This advancement could effectively tackle worldwide health issues associated with malnutrition and dietary insufficiencies.

4. Methods and techniques used for allele mining

The attainment of success in allele mining necessitates the utilization of a synergistic amalgamation of sophisticated methodologies and procedures to investigate and evaluate the genetic variability present within plant populations. Several prominent strategies and techniques utilized in the process of allele mining encompass:

1. Next-Generation Sequencing (NGS): The advent of Next-Generation Sequencing (NGS) has brought about a significant transformation in the field of allele mining, since it allows for the efficient and economical sequencing of complete plant genomes [9, 10]. This methodology, sometimes referred to as whole-genome sequencing, offers a comprehensive perspective on the genetic composition of a plant, enabling the identification of particular genes and alleles linked to advantageous features. Moreover, the utilization of RNA sequencing (RNA-seq) enables researchers to evaluate gene expression patterns, so augmenting our comprehension of how alleles exert an influence on features.

2. Bioinformatics Tools: The utilization of bioinformatics tools is essential for the intricate examination of the extensive genomic datasets produced by Next-Generation Sequencing (NGS) techniques. Bioinformatics tools and software play a crucial role in the processing and interpretation of this data. These methods facilitate the identification of candidate alleles, the prediction of their possible impacts on phenotypes, and the execution of genome-wide association studies (GWAS) to establish links between alleles and phenotypic variants.

3. Marker-Assisted Selection (MAS): Marker-Assisted Selection (MAS) is a technique employed in breeding programs to incorporate possible candidate alleles that have been identified by allele mining. The utilization of molecular markers, such as single nucleotide polymorphisms (SNPs) or simple sequence repeats (SSRs), that are associated with the target alleles, is employed for the purpose of screening and selecting plants that possess these desired genetic variants. The elimination of time-consuming and resource-intensive phenotypic tests expedites the breeding process.

4. Population Genetics and Association Mapping: Population genetics and association mapping are important tools in the field of allele mining, as they offer valuable insights on the genetic diversity and structure of plant populations. Through the examination of the frequency and distribution patterns of particular alleles within populations, scholars are able to discern regions of significance within the genome. Association mapping approaches facilitate the discovery of alleles that are linked to specific features through the analysis of the relationship between genetic markers and differences in phenotypic expression.

5. Functional Genomics: Functional genomics plays a crucial role in not only finding potential alleles but also in unraveling the underlying biological pathways that contribute to the features of interest. Researchers employ several methodologies, including gene expression analyses, gene knockout studies, and gene editing with CRISPR-Cas9 technology, to gain insights into the impact of certain alleles on the molecular mechanisms underlying phenotypic development and functionality.

6. Eco Tilling: Eco-Tilling (Targeting Induced Original Lesions in Genomes) is a modified tillage approach for identifying single-nucleotide allelic variants (or, more accurately, compelling point mutations) in target genes. It is a viable alternative. Mutations in the gene of interest are identified [11]. A large number of individual variations may be found quickly, and he only needs to sequence one existing variation once for each haplotype, which saves money. In tillage, chemical mutagens are employed to introduce random mutations. To induce a single-nucleotide point mutation (G/C to A/T) in seeds, EMS, a chemical mutagen, is used [12]. M1 seeds self-pollinate to produce the M2 seed population. Look for point mutations in M2 progeny from a single seed line. During screening, DNA is pooled in a variety of ways to improve the effectiveness of mutation detection. 5′ prime end-specific primers are used to target the locus of interest, and the PCR products are heated and chilled to form heteroduplexes. The CEL I nuclease enzyme is used to cleave the base mismatch, and the products reflecting the generated mutations are examined using denaturing polyacrylamide gel electrophoresis. These PCR products are denatured and reannealed to allow for mismatched or heteroduplex conformations, which reflect natural and compelling SNPs.

5. Steps involved in designing KASP markers

Designing Kompetitive Allele-Specific PCR (KASP) markers for plant breeding involves the following steps.

The initial stage in the development of KASP markers involves the identification of the target SNP (Single Nucleotide Polymorphism). This entails determining the particular SNP that is linked to the trait or characteristic under investigation or desired for selection in the field of plant breeding. The single nucleotide polymorphism (SNP) in question should possess biological significance and demonstrate relevance to the specific breeding objectives at hand [9].

5.1 SNP validation

Following the identification of the target single nucleotide polymorphism (SNP), it is imperative to undertake a process of validation to ascertain its genuine association with the specific trait of interest. The validation process may entail genotyping a varied collection of plant samples in order to verify the presence of the single nucleotide polymorphism (SNP) and its correlation with the specific trait. The process of primer design holds significant importance in the context of KASP assays, as it involves the creation of primers that are unique to the target of interest. The amplification of the area surrounding the target SNP in KASP markers is achieved through the utilization of allele-specific primers. To amplify each single nucleotide polymorphism (SNP), it is necessary to utilize a pair of allele-specific primers, with one primer designed for each allele, often representing the main and minor alleles. The design of these primers should be allele-specific, ensuring that they exclusively amplify the targeted allele [13, 14].

5.2 Fluorescent labelling

Within KASP tests, it is customary to employ distinct fluorescent dyes (e.g., FAM for one allele and HEX for the other) to label the allele-specific primers. The process of labelling facilitates the discrimination of alleles during the polymerase chain reaction (PCR) amplification. This study aims to determine the best polymerase chain reaction (PCR) settings for the KASP assay. This entails the determination of the annealing temperature, cycle parameters, and additional conditions in order to guarantee the targeted amplification of the single nucleotide polymorphism (SNP) area. Control markers are frequently used into KASP experiments. The aforementioned control markers are markers that lack polymorphism and serve to amplify a specific and well-defined section of the genome. Positive controls are utilized in order to verify the proper functioning of the polymerase chain reaction (PCR) process and to standardize the fluorescence measurements.

5.3 Testing and optimization

Prior to implementing KASP markers in high-throughput genotyping, it is imperative to do thorough testing and optimize the assay. To ensure the reliability and robustness of the outcomes, it may be necessary to conduct experiments involving the examination of various primer concentrations, annealing temperatures, and cycle circumstances.

5.4 Genotyping

Following the validation and optimization of the KASP test, it can be employed for genotyping a greater quantity of plant samples. The experimental procedure encompasses the extraction of DNA from plant tissue, followed by PCR amplification with the KASP assay, and subsequently assessing the fluorescence data to ascertain the genotype of each individual sample.

5.5 Data analysis

The genotyping data will be subjected to analysis in order to ascertain the allelic composition of each individual sample. The existence of specific alleles can be determined by analyzing the fluorescence signals emitted by different dyes.

5.6 Data interpretation

Analyze the genotyping data within the framework of the breeding objectives. The objective is to identify the genotypes that are linked to the desired trait or characteristic, and thereafter utilize this knowledge to make informed decisions in the selection of plants for further breeding purposes.

5.7 Marker validation

The aim of this study is to assess the efficacy of the KASP marker in larger breeding populations, hence ensuring its reliability in consistently selecting for the desired trait.

5.8 Incorporation into breeding programs

Following validation, the KASP marker should be integrated into the plant breeding program. Marker-assisted selection (MAS) can be employed to effectively identify plants possessing the required genotype, hence expediting the breeding procedure.

5.9 Ongoing surveillance

It is advisable to consistently observe and evaluate the efficacy of KASP markers within your breeding program, as the correlation between the single nucleotide polymorphism (SNP) and the specific characteristic under consideration may undergo alterations over time as a result of recombination or other influencing variables.

6. Bioinformatics tools used in allele mining

Allele mining is a fundamental procedure in the field of genetics and genomics, whereby the objective is to discern and elucidate the allelic variations present within a given population of organisms. This method is commonly employed to gain insights into the genetic diversity within a population or to ascertain the presence of alleles that may be linked to particular traits of significance. The field of bioinformatics plays a pivotal part in the process of allele mining by offering a wide range of tools and resources that facilitate the study and interpretation of data (Table 1). The following is a compilation of frequently employed bioinformatics tools utilized in the process of allele mining.

S.No.	Tool	Function	URL
1	MEME	Multiple EM for Motif Elicitation. Analyzing DNA and protein sequence motifs for similarities among them.	meme.nbcr.net/meme/cgi-bin/meme. CGI [15]
2	JASPAR	Database of Transcription Factor Binding Site (TFBS)	http://jaspar.genereg.net/ [16]
3	AGRIS	Arabidopsis gene regulatory information server. A new information resource of Arabidopsis cis- promoter	http://arabidopsis.med.ohio-state.edu [17]
4	FastPCR	FastPCR software for PCR primers or probes design and in silicoPCR, oligonucleotide assembly	http://en.bio-soft.net/pcr/FastPCR.html [18]
5	PlantCARE	A database of plant cis-acting regulatory elements	http://bioinformatics.psb.ugent.be/webtools/plantcare/html [19]
6	Primer 3	Primer design. A computer program that suggests PCR primers for a variety of applications	http://frodo.wi.mit.edu/primer3/ [20]
7	Plantprom DB	A database of plant promoter sequences	http://mendel.cs.rhul.ac.uk/mendel.php?topic=plantprom [21]
8	Clustal Omega	Multiple alignment of DNA and protein sequences/Multiple sequence alignment programs.	https://www.ebi.ac.uk/Tools/msa/clustalo/ [22]
9	T-Coffee	Multiple alignment of DNA and protein sequences/Multiple sequence alignment programs.	https://www.ebi.ac.uk/Tools/msa/tcoffee/ [23]
10	MAFFT	Multiple alignment of DNA and protein sequences/Multiple sequence alignment programs.	https://www.ebi.ac.uk/Tools/msa/mafft/ [24]
11	MUSCLE	Multiple alignment of DNA and protein sequences/Multiple sequence alignment programs.	https://www.ebi.ac.uk/Tools/msa/muscle/ [25]
12	DnaSP	DNA Sequence Polymorphism analysis, to identify SNPs and InDels and Phylogeny analysis	http://www.ub.edu/dnasp/ [26]
13	MEGA	Integrated Software Molecular Evolutionary Genetics Analysis and Sequence Alignment.	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2562624/ [27]
14	Transcriptional regulatory element database (TRED)	Collection of mammalian regulatory elements	http://rulai.cshl.edu/cgi-bin/TRED/tred.cgi?process=home [28]
15	Multalin	Multiple alignment of DNA and protein sequences/Multiple sequence alignment programs.	http://multalin.toulouse.inra.fr/multalin/ [29]
16	MAT inspector	To predict TFBS and of promoter analysis	http://www.genomatix.de/products/matinspector/ [28]

Table 1.

List and details of different bioinformatics tools used in allele mining.

7. KASP markers in plant breeding

The utilization of the Kompetitive Allele-Specific PCR (KASP) assay has significantly advanced our understanding and improvement of various traits in cereal crops. Recent studies from 2017 onwards have demonstrated the efficacy of the KASP assay in identifying key genetic markers and genes associated with important traits (Table 2).

Crops	Traits	Number and name of QTLs/markers/genes	References
Wheat	Dwarf bunt resistance	2 QTLs	[30]
Wheat	Fusarium head blight resistance	QFhb-5A	[31]
Wheat	Leaf rust resistance	4 markers	[32]
Wheat	Stripe rust resistance	3 markers	[33]
Wheat	Grain yield-related traits	26 markers	[34]
Wheat	Green bug resistance	Gb7 gene	[35]
Wheat	Hessian fy resistance	H32 gene	[35]
Wheat	Pre-harvest sprouting resistance	10 markers	[36]
Wheat	Kernel weight	TaTAP46-5A gene	[37]
Wheat	Wheat curl mite resistance	2 markers	[38]
Wheat	Heat tolerance	sHSP26 gene	[39]
Wheat	Drought tolerance	TaSST-D1, TaSST-A1	[40]
Rice	Narrow root cone angle	12 markers	[41]
Rice	Grain yield and adaptability traits	110 markers	[42]
Rice	Variety identification and breeding guidance	48 markers	[43]
Rice	Drought and low nitrogen tolerances	8 markers	[44]
Rice	Bacterial leaf streak resistance	xa5 gene	[45]
Rice	Cold tolerance	6 markers	[46]
Rice	Grain yield and yield components	21 markers	[47]
Rice	Salt tolerance	25 markers	[32]
Rice	Brown plant hopper resistance	20 markers	[48]
Rice	Dirty panicle disease resistance	12 markers	[49]
Maize	Agronomic traits including yield	50 markers	[50]
Maize	—	202 markers	[51]
Maize	Maize tar spot complex resistance	qRtsc8–1 QTL	[52]
Maize	Stalk fracture angle	2 markers	[53]
Maize	Enrichment of provitamin A content	5 markers	[54]
Maize	Chilling-tolerant	20 markers	[55]
Barley	Greenbug resistance	2 markers	[56]
Barley	Greenbug resistance	3 markers	[57]
Barley	Leaf rust resistance	Rph13 gene	[58]
Oat	Stem rust resistance	Pg13 gene	[59]
Oat	Oat crown rust resistance	Pc39 gene	[60]
Sorghum	Starch content and constitution	7 markers	[61]
Pearl millet	Pollen production	2 markers	[62]

Table 2.

The following is a list of current studies that have focused on the development of KASP markers for a variety of critical traits.

In wheat, researchers have made notable discoveries using the KASP assay. Wang et al. [30] and Muellner et al. [63] identified two QTLs associated with dwarf bunt resistance, while Jiang et al. [31] discovered the QFhb-5A marker for Fusarium head blight resistance. Additionally, Li et al. [32] and Liu et al. [33] identified markers associated with leaf rust resistance and stripe rust resistance, respectively. Other studies investigated traits such as grain yield-related traits, green bug resistance, pre-harvest sprouting resistance, kernel weight, wheat curl mite resistance, heat tolerance, and drought tolerance [34, 35, 36, 37, 38, 39, 40].

The KASP assay has also been instrumental in uncovering the genetic basis of important traits in rice. In another study he identified 12 markers associated with narrow root cone angle [41], while indifferent study [42] they identify 110 markers associated with grain yield and adaptability traits. According to another study Tang et al. [43] identified 48 markers for variety identification and breeding guidance. Other studies focused on drought and low nitrogen tolerances, bacterial leaf streak resistance, cold tolerance, grain yield and yield components, salt tolerance, brown planthopper resistance, and dirty panicle disease resistance [32, 44, 45, 46, 47, 48, 49].

In maize, the KASP assay has played a crucial role in unraveling the genetic architecture of agronomic traits. In another study [50] they identified 50 markers associated with various agronomic traits, including yield, while in different study Lu [51] discovered 202 markers providing valuable genetic information in maize research. Studies also focused on maize tar spot complex resistance, stalk fracture angle, enrichment of provitamin A content, and chilling tolerance [52, 53, 54, 55].

Furthermore, the KASP assay has been employed in other cereal crops. Xu [56, 57] identified markers associated with greenbug resistance in barley, and Jost [58] identified the Rph13 gene for leaf rust resistance in barley. Kebede [59] and Zhao [60] utilized the KASP assay to identify genes associated with stem rust resistance and oat crown rust resistance in oat, respectively. Chen [61] identified markers associated with starch content and constitution in sorghum, while Pucher [62] identified markers associated with pollen production in pearl millet.

These studies collectively highlight the versatility and effectiveness of the KASP assay in identifying QTLs, markers, and genes associated with various traits in cereal crops. The findings have significant implications for crop improvement programs, facilitating the development of high-yielding, disease-resistant, and stress-tolerant crop varieties.

8. Conclusion

Allele mining is a potent crop development strategy that takes advantage of natural genetic variation within plant populations. This strategy is useful for identifying and exploiting advantageous genetic variants or alleles linked to desirable qualities such as higher agricultural yields, disease resistance, stress tolerance, and nutritional quality. The incorporation of modern molecular techniques, such as the Kompetitive Allele-Specific PCR (KASP) assay, has revolutionized allele mining, allowing researchers to uncover and use genetic markers and genes associated with these desirable features more quickly.

The KASP assay has proven to be a powerful tool for finding essential genetic markers and genes linked with important agronomic features in recent research spanning a variety of cereal crops, including wheat, rice, maize, barley, oat, sorghum, and pearl millet. This not only speeds up the breeding process, but it also adds to the production of crop varieties that meet rising global food need, environmental resilience, and better nutritional value.