1. INTRODUCTION

Archeozoological and molecular studies indicated that goats were among the first livestock species that were domesticated around 8000–11,000 years ago in the Fertile Crescent, from where goats spread throughout the world along terrestrial and maritime routes of migration and trade (Naderi et al., 2007; Zeder, 2008). Goats have various, relevant, and vital roles in the world, from the emergence of human civilization to the production of meat, milk, and fiber (Lu, 2023). Accurate molecular data within- and between-breed diversity are widely accepted to be essential for optimal management of genetic resources in farm animals (Fernández et al., 2011). Understanding how historical and ongoing evolutionary processes have shaped the distribution of today's goat biodiversity necessitates a knowledge of genetic diversity and population dynamics that are derived from phylogenetic studies and haplogroup classifications (Al-Araimi et al., 2017a). Genetic variation and phylogenetic relationships based on the variety of maternal lineages can be used to determine the ancestry and origins of different domestic animals by studying nucleotide polymorphisms within the mitochondrial DNA (mtDNA) sequences (Kimura et al., 2011; Lv et al., 2015; Yang et al., 2017; Mustafa et al.,2018; Al-Jumaili et al., 2020; Mustafa et al., 2022).

Mitogenomic and phylogenetic analysis using mtDNA sequences of domestic and wild goats from geographically diverse countries has classified six major maternal haplogroups (HPG) known as HPG-A, HPG-B, HPG-C, HPG-D, HPG-G, and HPG-F, in which HPGA was predominant and widely widespread in most goats worldwide (Luikart et al., 2001; Sultana et al., 2003; Joshi et al., 2004; Sardina et al., 2006; Naderi et al., 2007; Naderi et al., 2008; Bulut et al., 2016; Al-Araimi et al., 2017b; Diwedi et al., 2020; Ganbold et al., 2020; Mustafa et al., 2022). These previous studies used laborious, expensive, and time-consuming methods to determine the patterns of genetic diversity in goats. For example, some of them amplified the complete mitogenome by using several pairs of primers, while others used whole genome sequencing data. Alternatively, with the aid and development of bioinformatics, databases, and tools, the current study aimed to estimate the suitability of protein-coding genes, ribosomal genes, and the control region (D-loop) of the complete mitogenomes of domestic and wild goats to differentiate their main maternal lineages. Additionally, it also aimed to calculate polymorphic sites within each individual mitogenomic component, thus discovering the most polymorphic region by which the main maternal haplogroups of goat mitogenomes can be distinguished. The correlation between the length of each distinct mtDNA region and its number of polymorphic sites was also investigated.

2. MATERIAL AND METHODS

2.1 Mitogenomic data from the NCBI database

In total, 29 complete mitogenomes, including 13 protein-coding genes, 2 ribosomal (rRNA), 22 transfer RNA (tRNA), and one non-coding control region, with known maternal haplogroups (HPG-A, HPG-B, HPG-C, HPG-D, HPG-G, and HPG-F) of goats from both species Capra hircus and Capra aegagrus from geographically different locations were retrieved from the National Center for Biotechnology Information (NCBI) database https://www.ncbi.nlm.nih.gov/ and used for phylogenetic and bioinformatics analyses. GenBank accession numbers, species, maternal haplogroups, and country of complete mitogenomes of both wild and domestic goats used in the present study are provided in Appendices Table S1

2.2 Phylogenetic analysis

To examine the suitability of individual genes or regions of the mitogenome for differentiation of the main maternal lineages in goats; firstly, the complete mitogenomes from domestic and wild goats worldwide representing all known maternal haplogroups were aligned using the Geneious Prime software and used for the phylogenetic tree as a reference (Kearse et al., 2012). Then, complete sequences of 13 mitochondrial protein-coding genes, 2 ribosomal genes, and the control region of the goat mitogenome were extracted separately, re-aligned, and used for a phylogenetic tree using the Geneious Prime software. In phylogenetic analysis, a neighbor-joining (NJ) method as a tree-building technique and Tamura-Nei (TN93) as an appropriate genetic distance model as implemented in the Geneious Prime software were applied. The complete mitogenome of Capra ibex as an outgroup was used (Hassanin et al., 2009).

2.3 Primer design

Aphylogenetic examination of each individual mitogenomic component led to the selection of the control region for additional bioinformatics analysis. According to the goat mitogenome reference (NCBI Reference Sequence: NC_005044.2),a pair of primers, forward (5' CAACACAAACTTCCCACTCCAC 3') and reverse (5' AGATGGCCCTGAAGAAAGAACC 3'), flanking the most polymorphic region within the control region of the goat mitogenome, was designed using the Geneious Prime software (Kearse et al., 2012). Primers begin at position 15461 and end at position 16217 within the control region of the mitogenome reference of goat (NCBI Reference Sequence: NC_005044.2). Accordingly, the 756 bp target size of the PCR products was expected. The commercial synthesis of primer sequences was carried out by Macrogen, Inc. (South Korea).

2.4 Blood and DNA samples

Five fresh whole blood samples were collected from the jugular veins of Meriz goats and collected in vacutainer tubes (VACUTEST, Italy). Using the AddPrep Genomic DNA Extraction Kit (ADD BIO Inc., South Korea), total genomic DNA was isolated from whole blood according to the manufacturer's instructions. Quality and quantity of extracted genomic DNA samples were assessed using both a Nanodrop® ND-2000 spectrophotometer (Thermo Scientific) and gel electrophoresis (Cleaver Scientific Ltd., UK).

2.5 PCR amplification

For amplification of the most polymorphic mitogenomic marker region, PCR reactions were carried out in a 40μl total volume reaction mixture containing ddH₂O (14μl), Taq master (20μl) (ADD BIO Inc., South Korea, REF: 35001), forward and reverse primers (10μM) (each 2μl). At the end, about 100-150 ng of DNA samples were added to the master mix. Mitogenomic marker region was amplified following the PCR cycling conditions of 5 minutes of initial denaturation at 95°C, followed by 35 cycles of denaturation (95°C, 0.5min), annealing (58°C, 0.5 min), and primer extension (72°C, 1 min). The final cycle included a 5-minute final extension at 72°C followed by an indefinite hold duration at 4°C. The ABI 9700 thermal cycler (Applied Biosystems) at the Department of Animal Production, College of Agricultural Engineering Sciences, University of Duhok was used for PCR amplification.

2.6 Gel electrophoresis

To examine the outcome of PCR amplification and determine the band size of the PCR products, the gel electrophoresis method was used, in which an agarose gel (1% w/v) was prepared in 1x TAE and then the Safe Gel Stain Dye was added. The gel wells were loaded with the PCR products and DNA loading buffer. Additionally, 5µl of DNA ladder was added. The gel was then run at 75–100 volts (V) for 60–90 minutes using gel electrophoresis apparatus (Cleaver Scientific Ltd., UK). Finally, the PCR products were examined with a UV transilluminator.

2.7.DNA sequencing and phylogenetic analysis of PCR products

Five samples of amplified PCR products from Meriz goats were sent to Macrogen, Inc. (South Korea). The PCR products were purified and sequenced in both directions (forward and reverse). The chromatograms of the sequenced PCR products were visualized by Geneious Prime software (Kearse et al., 2012), and clean PCR fragments were extracted per sample in order to generate the most polymorphic mitogenomic marker region with a length of 756 bp. Furthermore, for the phylogenetic tree, the five samples of Meriz goats representing the mitogenomic marker region were aligned with the comparable region shown in the mitogenomes of the other 29 domestic and wild goats utilized in Figure 1.

2.8.Mitogenomic pairwise and principal component analysis (PCA)

Pairwise differences in the mitogenomic marker region in terms of the number of polymorphic sites between the 34 samples, including 29 domestic and wild goats and 5 samples of Meriz goats, were estimated using the Geneious Prime software (Kearse et al., 2012). The table representing the number of polymorphic sites was used as input for the TBTools program (Chen et al., 2020) in order to create Principal Components Analysis (PCA) to visualize mitogenomic distances between the 34 samples representing the main maternal haplogroups in goats.

2.9 Estimation and visualization of polymorphic sites

Polymorphic sites over the consensus of the sequence alignment of individual component of mitogenome including 13 protein coding genes, 2 ribosomal genes, control region, and the mitogenomic marker region of goats were calculated using the Geneious variant finder using the find variations/SNPs feature from the annotate and predict menu within the Geneious Prime software (Kearse et al., 2012). Polymorphic sites were visualized by Excel Microsoft. Statistical correlation between length of each mitogenomic component and the number of polymorphic sites were estimated using IBM SPSS's statistical software.

3. RESULTS AND DISCUSSIONS

3.1 Phylogenetic relationships based on the assessment of complete mitogenome

The current study examines the entire mitogenome and its individual genes to assess their power as a tool in the differentiation of the main maternal lineages in goats through the phylogenetics interpretation of mitogenome. Firstly, based on the alignments of 29 complete mitogenomes, the main maternal haplogroups HPG-A, HPG-B, HPG-C, HPG-D, HPG-G and HPG-F of domestic and wild goats used herein were classified through building phylogenetic trees based on a neighbour-joining (NJ) method under the appropriate parameter model using the Geneious Prime software (Kearse et al., 2012) (Figure 1). These results were consistent with the findings of previous studies (Colli et al., 2015; Mustafa et al., 2022) when they found similar maternal lineages in goats using the complete mitogenome. Using nucleotide polymorphisms found in mtDNA sequences, phylogenetic relationships based on the diversity of maternal lineages can be utilized to retrace the origins and genealogy of various domestic animals (Naderi et al., 2007; Lippold et al., 2011; Mustafa et al., 2018; Osman et al., 2021). MtDNA is widely employed to generate phylogenetic trees at various taxonomic levels, from within species to among mammalian orders (Bruford et al., 2003).

3.3 Amplification, sequencing and phylogeny of the mitogenomic marker region

Since the goat mitogenome's control region is longer than 1 kbp and is challenging to sequence it with high-quality using Sanger sequencing technology, it is essential to identify mtDNA region shorter than 1 kbp with highly polymorphic sites. Accordingly, the sequences of 29 aligned complete mitogenomes were scanned by focusing on the control region and it has been found that highly polymorphic region within the control region could be used as a mitogenomic marker to differentiate all maternal haplogroups. As a result, a pair of primers was designed to flank the mitogenomic marker region that starts at position 15461bp and ends at position 16217bp of control region according to the mitogenome reference of goat (NCBI Reference Sequence: NC_005044.2). The most polymorphic mitogenomic marker region with a size 756bp of five genomic DNA samples of domestic Meriz goat was successfully amplified by PCR reactions using a pair of primer designed by our study. Meriz goats have been chosen as the sole model for representing goat genomic DNA in order to be used for PCR amplification and sequencing analysis of the mitogenomic marker region and to confirm our bioinformatics findings. The second reason behind the selection of genomic DNA samples from Meriz goats is that their maternal lineage (haplogroup) and entire mitogenomes have already been determined (Mustafa et al., 2022).

Previous studies used huge numbers of primer to amplify multiple overlapping fragments to assemble the complete mitogenome and then used for maternal phylogeny (E et al., 2016). However, in this study only a pair of primers were used

to target highly informative region containing sufficient single nucleotide polymorphisms (SNPs) able to differentiate all maternal lineages in goats (Figure 2, Figure 3). In addition, Doro et al. (2014) used over 30 pairs of primers to amplify 33 partially overlapping mtDNA amplicons in order to assemble the whole mtDNA genome, which was then used to construct the goat phylogenetic tree. However, in our bioinformatics research, a pair of primers to identify the most informative region within the control region was developed, which represents the whole mitogenome and generates the same results. The five sequences of the PCR products of the control region representing the mitogenomic marker region of domestic Meriz goat were aligned with the corresponding region extracted from the 29 complete mitogenomes spanning the same flank region, 15461 bp to 16217 bp (756 bp in size). As a result, the 34 mtDNA control region sequences representing the mitogenomic marker region were used for phylogenetic tree to evaluate its productivity for differentiation the main maternal lineages of goats. As shown in Figure 3, the targeted region (756 bp) within the ranges 15461 bp to 16217 bp of the mtDNA control region was appropriate for distinguishing the main maternal haplogroups in goats. Similar to the phylogenetic results based on the complete mitogenome (Figure 1) and on the control region (Appendices Figure S16), the 756 bp mitogenomic region was like a powerful molecular tool to differentiate all major maternal lineages of domestic and wild goats, including the validated sequences of the mitogenomic region of Meriz goats (Figure 2; Figure 3).

Previous research examined the evolutionary history and population structure of 406 domestic goats representing 88 breeds by sequencing the hypervariable section of the mtDNA control region with a length of 481bp and their phylogeographic analysis revealed only three distinct goat lineages, HPG-A, HPG-B, and HPG-C (Luikart et al., 2001). Furthermore, their study (Luikart et al, 2001) used external and internal primers to amplify short segment of control region not having adequate polymorphic sites to distinguish all maternal lineages, and through our analysis, it has been found thatthe sequences of their primers are not within the most conserved region of mitochondrial control region. However, in our study, a new pair of primers was designed within the most conserved regions amplifying mtDNA control region with the length 756 bp with highly polymorphic sites able to differentiate the main six maternal lineages in the goats (Figure 2, Figure 3). In another study, a fragment of the control region with a size of 639 bp, including primers, corresponded to the locations 15653 to 16250 on the complete mitogenome of reference number AF533441 and was used to analyze the genetic diversity of more than 2400 goats (Naderi et al., 2007). The target region flanked by our primers is 127 bp longer than the sequenced segment of the control region (756 bp versus 639 bp) by the primer sequences of the study (Naderi et al., 2007). The control region has been notably employed to characterize the genetic diversity of goats (Luikart et al., 2001; Naderi et al., 2007) because it is sufficiently instructed and variable over the species' geographic range and evolves at a steady pace (Bruford et al., 2003).

In order to verify the performance of the mitogenomic marker, pairwise differences of the mitogenomic marker region in terms of the number of polymorphic sites between the 34 samples including 29 domestic and wild goats and 5 samples of Meriz goats were estimated using the Geneious Prime software (Kearse et al., 2012). TBTools (Chen et al., 2020) was used to create Principal Components Analysis (PCA) in order to visualize mitogenomic distances between the 34 samples. Similar to the results of the phylogenetic trees shown in Figure 1, Figure 3, and Appendices Figure S16, PCA analysis interestingly distinguished the main maternal haplogroups (Figure 4). The results of phylogenetic tree and PCA indicated that the Meriz goats are within the maternal lineage haplogroup A(HPG-A) (Figure 3). The results are highly supported by our previous study (Mustafa et al., 2022) when the complete mitogenome was used and it has been found that Meriz goats belonged to the maternal haplogroup A (HPG-A). The concordance between the results of our bioinformatics analysis, the phylogenetic tree, principal components analysis, and the previous study (Mustafa et al., 2022) implies that the mtDNA marker from the control region of study is strong enough to alternate the entire mitogenome for maternal haplogroup identification when it sufficiently identifies that Meriz goats are within the maternal haplogroup HPG-A (Figure 3, Figure 4).

Furthermore, our results pointed out that the size of the mitogenomic marker region (756 bp) and the number of polymorphic sites in it were adequate to represent the complete mitogenome of goats due to the high polymorphisms in this region (Figure 5). Similarly, most recently, a meta-analysis was conducted to examine the diversity and phylogenetic relationships among 399 mitogenomic control region sequences from African sheep breeds. The significant nucleotide and haplotype diversity, along with the observed huge number of haplotypes (more than 70% distinct haplotypes), point to a very high variability of the mtDNA control region (Wanjal et al., 2021). Variations in phylogeny estimates between mitogenomic and single-gene markers have resulted in contradicting conclusions in various occasions. Thus, selecting mitogenomic regions as the marker of choice for phylogenetic analysis often provides greater phylogenetic resolution and precision, which is very important, as we discovered herein in the goat mitogenome.

3.4 Assessment, visualization and correlation of polymorphic sites

In the present study, polymorphic sites were estimated across the consensus of the sequence alignment of individual components of the goat mitogenome, comprising 13 protein-coding genes, 2 ribosomal genes, and the control region, using the Geneious Prime software's variant finder (Kearse et al., 2012). The results, as shown in Figure 5, indicated that 12 protein-coding genes, including ND3, ATP8, ND4L, ND6, 12SrRNA, 16SrRNA, COX2, ND1, APT6, COX3, ND2, and COX1, had a number of polymorphic sites less than 40 SNPs. Three genes, such as ND4, CYTB, and ND5, had polymorphic sites with a range of 61 to 78 SNPs (Figure 5). However, the highly polymorphic regions were both the control region and the mitogenomic marker region, with 188 and 147 SNPs, respectively (Figure 5).

Luikart et al. (2001) conducted an extensive sampling study including 420 mtDNA control region sequences from 88 breeds and 160 variable sites were observed by which only three distinct maternal lineages, HPG-A, HPG-B, and HPG-C, were revealed in domestic and wild goats from Nigeria to Iceland, Mongolia to Malaysia, and countries from domestication center such as Jordan, Turkey, Iraq, Egypt, and Pakistan. Despite the use of large samples, other maternal haplogroups such as HPG-D, HPG-G, and HPG-F were not distinguished in their research, but other studies later did. This is convincing indication that the short mtDNA control region sequences (481 bp) employed in their phylogeographic study did not cover the potential number of polymorphic sites required to uncover all maternal lineages in goats. Thus, as a note of caution, future research on maternal haplogroups in goats should employ a longer region with more polymorphic sites, as we discovered herein. The control region can be used to track phylogeography, demographic growth, dispersal, gene flow, hybridization, and genetic drift since it exhibits exceptionally high levels of variation within species (Bruford et al., 2003; Verma et al., 2018).

Furthermore, based on the Spearman's rank correlation coefficient, highly significant correlations were discovered between the polymorphic sites and the length of each mitogenomic component (13 protein-coding genes, two ribosomal RNA genes, a D-loop region, and a mitogenomic marker) after applying the Shapiro normality test by IBM SPSS's statistical software (SPSS, 2019). Likewise, Naderi et al. (2007) observed about 336 polymorphic sites over the 558bp of the alignment of the control region fragment when they examined genetic diversity of more than 2400 individuals of goats. Polymorphic sites are important because each SNP has a value, as demonstrated by the work of Doro et al. (2014), who discovered that several polymorphic sites inside the HPG-A were relevant for the construction of its internal phylogeny. Yi et al. (2022) employed a 401-bp fragment of the mtDNA control region in their investigation of population structure, genetic diversity, and matrilineal system evolution in goats globally, which included over 190 goat breeds. Although they discovered 301 polymorphic sites within the 401 bp control region, using a longer fragment of the mtDNA control region in their analysis would result in a higher number of variable sites, giving us a better understanding of goat domestication history and gene flow

worldwide.

CONCLUSIONS

Bioinformatics and molecular analyses revealed that neither the 13 protein-coding genes nor the two ribosomal genes of mitogenome as individual subsets are suitable for distinguishing the main maternal haplogroups in goats. Alternatively, a complete mitogenome, a control region, and the most informative mitogenomic region with highly polymorphic sites with a size of 756 bp inside the control region, which were amplified using PCR utilizing newly designed primers, effectively differentiated the main maternal lineages. Moreover, significant correlations between the length of individual genes and the number of polymorphic sites were found, indicating that the region with the highest polymorphism is best suited for use as a mitogenomic marker for maternal phylogeny. The bioinformatics analysis used here can be applied to population genetics and biodiversity in other species in future research, suggesting that when examining genetic diversity, mitochondrial fragments should be chosen with caution.

Data availability statement

The partial mitochondrial control region of five samples of Meriz goats is available in GenBank at the NCBI database under accession numbers OR875928-OR875932.

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