**3. The use of molecular genetic markers and techniques to improve reproductive performance in livestock**

Genetic improvement of reproductive efficiency is one of the most effective strategies available to improve the performance of farm animals. Especially in the last 50 years, selection program based on classical or molecular genetic principles has led to significant positive changes in dairy and beef cattle [14]. Reproductive efficiency is influenced mainly by environmental factors such as dietary regimen, animal health and management, and their interactions, as well as by many genes in dairy animals. Reproductive traits generally have low-to-moderate heritability and do not show excellent progression to phenotype-dependent selection by classic selection methods. Therefore, determining the genes that affect the reproductive ability and including them in the selection program is one of the crucial arguments in increasing the efficiency and success of the selection process.

Genetic markers of follicle number in cattle ovaries can identify heifers that will become highly fertile cows because genes play an active role not only in the physical structure of an organism but also in its functioning. Therefore, analysis of the farm animal genomes will enable us to identify putative genes that are supposed to affect fertility and cow productivity, which are economically important traits in livestock, as the ultimate goal. Specific chromosomal regions, which contribute to complex traits, are called quantitative trait loci (QTL). Several studies were conducted to identify genetic variation in quantitative traits in livestock and laboratory species since the genetic variation is an essential part of breeding programs. A possibility of detecting loci that affect quantitative traits using genetic markers has been realized since Sax's study with beans, which utilized seed-coat characters as markers due to the relationship with seed size in 1923 [15].

Selecting desirable alleles at particular loci based on marker information will increase the selection response for the next generation. Short sequences of DNA, called genetic markers, are specific DNA regions in the animal genome that indicate variation within the population. These polymorphic regions can be positively or

negatively associated with particular reproductive traits of interest. One of the main tools for genetic improvement is the wide usage of molecular markers such as microsatellites, minisatellites, and single nucleotide polymorphisms (SNPs) using different methods such as PCR-RFLP, SSCP, SSR, qRT-PCR, and whole-genome analysis or the next-generation sequencing [16].

Especially microsatellite markers are not only highly polymorphic but also reasonably abundant throughout the genome [17]. The relationship between marker alleles and phenotypic observations on the trait is used widely in linkage analysis to map a segregating QTL in a population. The presence of highly polymorphic DNA markers in genetic maps in various farm animals and their relationship to phenotypes provide an effective tool for QTL affecting traits. However, identifying markers closely linked to the target region and determining the association between marker allele and QTL allele, which control the quantitative traits, are rather complex processes. A high-resolution marker map and precisely recorded phenotypic values are needed to determine the linkage between marker loci and QTL with low to moderate effect controlling the traits like reproductive performance [18]. Therefore, the QTL region affecting mainly low-moderate heritable traits is detected to find molecular markers that can be applied in the MAS system, enhancing the genetic gain for the reproductive trait of interest.

Several reproductive traits have been associated with fertility in dairy cattle, including age at puberty, early ovulation, size of ovulatory follicles, multiple ovulation, ovarian cystic structure, embryo survival, and heat detection [19, 20], which heritability rates are around 1–5% [21]. The prediction of these heritability ratios still notifies that there is a potential to make genetic progress selecting against reproductive traits in bovine. Genome-wide association studies (GWAS) are widely used powerful techniques to discover genetic variants strongly associated with various complex traits concerning any disease resistance, productive and reproductive abilities in different organisms over the last twenty years. For this purpose, chipbased microarray technology has been developed as a high processing platform to support GWAS analysis. GWAS is a technique that assays high-density SNP markers located throughout the genome to identify putative locations, either causative or in linkage with continuous phenotypic variation. The availability of millions of SNPs markers makes the system easily genotyping on throughput platforms by covering the whole genome [22]. Various GWAS studies have been carried out on livestock, especially in dairy cattle [23], beef cattle [24], water buffalo [25], pigs [26], sheep [27], and goat breeds [28]. However, the large number of potential genes identified by GWAS have not been fully validated yet. As the best-powered studies, they are combining researches of GWAS data and genomic selection (GS) with MAS in livestock species will precisely accelerate the accomplishment of analyzing massive genotypic data through millions of genetic markers which are collected from up to hundreds of thousands of phenotyped animals with diseases and traits of interest soon [29, 30]. In addition, other new technologies, including RNA-sequencing technology, to be implemented through the genome-wide sequencing of mRNAs in animal species can be widely applied in such studies over time [31]. In conclusion, it is expected that many more major genes, causative mutations, and even several genes with minor effects will be definitively identified shortly due to the drastic decrease in prices for SNP genotyping and DNA and mRNA sequencing with the substantial increase in livestock genomic studies.
