Characterizing the Population Structure and Genetic Diversity of Iraqi Pigeons Using Ssr Markers

ABSTRACT

This study aims to characterize Iraqi pigeon breeds’ population structure and genetic diversity using Microsatellite (SSR) markers to obtain detailed insights into their genetic variation, differentiation, and evolutionary dynamics. This study represents the first comprehensive analysis of Iraqi pigeon breeds’ population structure and genetic diversity. The genetic diversity analysis revealed moderate to high allelic diversity, with the number of alleles (Na) ranging from 16 to 25 and the number of effective alleles (Ne) from 11.95 to 20.56. Observed heterozygosity (Ho) ranged from 0.27 to 0.53, while expected heterozygosity (He) was consistently high (0.92 to 0.95). FST values indicated significant genetic differentiation among pigeon breeds, ranging from 0.40 to 0.54, and gene flow (Nm) values suggested limited migration between subpopulations. The Principal Component Analysis (PCA) identified five distinct clusters, explaining 76.02% of the total variance, which reflects pronounced genetic boundaries and distinct genetic identities among the breeds. Genetic structure analysis using admixture with K=3 clusters highlighted distinct ancestral contributions. The genetic distance analysis revealed close genetic relationships among populations like Kirkuk, Baghdad, and Mosul White, with lower genetic distances (0.06 to 0.08). In contrast, Fadadi, Zangi, and Yellow breeds exhibited higher genetic differentiation (distances up to 0.15). The Analysis of Molecular Variance (AMOVA) indicated significant genetic variation among populations, with a variance component of 10.92 and a Phi-statistic of 0.58, demonstrating moderate to high genetic differentiation and substantial genetic diversity within populations. This comprehensive analysis underscores significant genetic variation and distinct population structures among Iraqi pigeons, with clear differentiation and diverse genetic contributions across breeds. The findings highlight the effectiveness of SSR markers in capturing the genetic landscape, providing essential insights for the conservation and management of genetic diversity within these pigeon populations. This study contributes valuable information for understanding Iraqi pigeon breeds’ genetic dynamics and evolutionary relationships, supporting future genetic and conservation efforts.

Keywords:
Iraqi Pigeon Breeds; Genetic Diversity; Population Structure; SSR Markers; Genetic Distances

INTRODUCTION

Columbidae species, including wild and domesticated pigeons (Columba livia), have interacted symbiotically with human societies for over five millennia. These pigeons have played diverse roles in cultural, economic, and ecological domains (Domyan & Shapiro 2017; Balcı et al., 2018; Capoccia et al., 2018; Ozbaser et al., 2020; Erdem et al., 2021). The domestic pigeon (Columba livia ssp. domestica) descended from the wild rock dove (Columba livia) and represents one of the earliest documented instances of animal domestication. The domestication process is believed to have originated in the Fertile Crescent region, which includes modern-day Iraq, making the area a historical epicenter for pigeon breeding and husbandry (Shapiro et al., 2013; Yilmaz et al., 2013; Pacheco et al., 2020; Ozbaser et al., 2021; Kim et al., 2022). These avian species have been historically utilized for their homing capabilities as messenger birds during wartime, as a source of sustenance, and for their aesthetic and competitive attributes in pigeon racing and exhibitions (Johnston & Janiga 1995; Jerolmack 2007; Shapiro & Domyan 2013). In Iraq, pigeons are deeply integrated into cultural traditions, symbolizing peace and playing significant roles in local folklore and social practices. Iraqi pigeon breeds are distinguished by their unique morphological characteristics, such as plumage coloration, size, and flight patterns, and reflect a rich heritage of selective breeding practices. Breeders have traditionally selected traits that enhance the birds’ aesthetic appeal, competitive performance in races, or their usefulness in traditional applications. However, despite their prominence, there is a significant need for more scientific studies documenting the genetic composition and population structure of these local pigeon breeds. The study of pigeon breeds, particularly in Iraq, requires more scientific rigor and attention. Pigeons have great potential for research in areas like evolutionary theory, natural selection, and adaptation. Breeders in Iraq are advised to focus more on scientific breeding methods and to study pigeon characteristics and traits in detail. Iraqi pigeon breeds can be organized into groups based on shared morphological features, including general body shape, head structure, eye color, beak shape and color, feather coloration, and distinctive flight patterns. The scientifically grounded classification and study of Iraqi pigeon breeds still need to be improved. However, valuable insights could be found by systematically conducting empirical analysis of phenotypic variations across breeds. Pigeon breeding is much more prevalent in major Iraqi cities than in rural areas and small towns, with specific breeds often passed down through families who have preserved certain varieties over generations. Unlike in other Arab countries, Iraqis typically do not breed pigeons for food, making pigeons less practical in the countryside. As such, pigeon breeding in Iraq remains a hobbyist pursuit rather than one motivated by financial incentives for breeders. This cultural aspect underscores the need for a detailed scientific study to enhance the understanding and conservation of these unique pigeon breeds. Unfortunately, rare and distinctive Iraqi pigeon breeds have faced extinction or genetic dilution due to the country’s hardships and turmoil. Many breeders have been forced to abandon their expensive breeding stocks or emigrate, allowing valuable pure bloodlines to fall into the hands of people unaware of their rarity. This has resulted in uncontrolled interbreeding, compromising the genetic purity of these unique breeds and making them harder to distinguish from crossbred populations. Iraqi pigeons can be classified into four groups based on shared phenotypic traits: the flying flocks pigeon group, the Mosul ornamental pigeon group, the Mosul tumbler pigeon group, and the ornamental pigeon group. The Baghdadi red pigeon, or Iraqi red, is characterized by a dark brown color covering all body parts uniformly. This breed originates from Baghdad. A white line on the head, called ‘aghr,’ enhances the pigeon’s beauty. The eyes are dark, the beak is white, and the feet are covered with feathers. One of the characteristics of Baghdadi pigeons is that they fly in groups. The Mosul ornamental pigeon group originates from Mosul. Other varieties of this group have also been developed and produced in Turkey. This group is used for ornamental and flying purposes. The Mosul ornamental pigeon group is classified into four color categories. The first group is characterized by a yellow chest with a light grey overall color. The patterns on the wings vary, including the light grey bar “Sabouni,” light checkered “Miski,” medium checkered “Wadai Achik,” and dark checkered “Wadai Latik.” The third group’s body is either yellow or red, with a white tail. The fourth group, Al-Shemii, features a dark gray body with a yellow chest. The Mosul tumbler pigeon group, also called the Iraqi blue or Taklaci group, is primarily blue. One of the features of this group is that it flies for long hours and has roller characteristics. Depending on the color and wing patterns, it is called by several names, such as grizzly “kullu,” bar blue “gok,” light grey bar “Sabouni,” light checkered “Miski,” and black checkered “Kummi.” The Iraqi ornamental pigeon groups are divided into the Kirkukli and Najafi pigeons. The Kirkukli pigeon, originally from Kirkuk, is a rare breed exclusively bred in Kirkuk. These pigeons are distinguished by their beauty and large size, featuring long legs and muffed feet. They are primarily white with black eyes, although other colors, such as blue, also occur. Najafi pigeons, originating from the city of Najaf, are red and yellow. They feature muffed feet, bull eyes, and a shell crest. Modern genetic techniques have revolutionized the study of animal populations, providing insights into genetic diversity, population structure, and evolutionary history (Sunnucks 2000; Selkoe & Toonen 2006; Ando et al., 2011; Mukesh & Sathyakumar 2013; Huang et al., 2016). Microsatellite markers are powerful tools for assessing genetic diversity and population structure in birds, including pigeons. These highly variable, co-dominant markers are well-suited for population genetic studies, as they can reveal fine-scale genetic differences among individuals and populations (Vignal et al., 2002; Jedrzejczak-Silicka et al., 2021; Zhang et al., 2021; Kim, et al., 2022). Despite the popularity and diversity of pigeon breeds in Iraq, more scientific studies are needed on their genetic foundations. This study aims to fill a significant gap in the current understanding of pigeon genetics by providing the first comprehensive genetic characterization of various Iraqi pigeon breeds. By employing microsatellite markers, we seek to assess these breeds’ genetic diversity and population structure, aiming to inform conservation efforts and breeding strategies.

MATERIALS AND METHODS

In this study, a total of 100 samples from 10 pigeon breeds were analyzed: Kirkuk (n=20), Baghdad (n=20), Fadadi (n=6), Zangi (n=6), Mosul blue (n=10), Mosul white (n=10), Red (n=8), Yellow (n=5), Shamee (n=7), and Raib (n=8) (Figure 1). Our study has been granted permission number 20231001 by the ethics committee. DNA was isolated from feather samples using the purification of total DNA from nails, hair, or feathers using the DNeasy® Blood & Tissue Kit (QIAGEN, Valencia, CA, USA), following the manufacturer’s protocol. A total of 14 microsatellite markers were used to analyze the genetic diversity of the pigeon populations. The selected markers were: CliμT17, CliμD32, CliμD01, CliμD16, CliμD17, CliμD19 (Traxler et al., 2000), PG1, PG2, PG3, PG4, PG5 (Lee et al., 2007), UU-Cli05, UU-Cli07, UU-Cli14 (Stringham et al., 2012). Each marker was amplified using Polymerase Chain Reaction (PCR) with a reaction volume of 10 μL, containing 0.5 μL of each primer, 4 μL of master mix, 4 μL of water, and 1 μL of DNA template. PCR amplification was performed under the following cycling conditions: initial denaturation at 95°C for 5 minutes, followed by 35 cycles of denaturation at 95°C for 30 seconds, annealing at (55°C, 58°C and 63°C) for 30 seconds, and extension at 72°C for 30 seconds, with a final extension at 72°C for 10 minutes. The PCR products were then analyzed using capillary electrophoresis on an ABI 3730 DNA Analyzer (Applied Biosystems, Foster City, CA, USA). The fragment analysis was conducted using GeneMapper® Software version 4.0 (Applied Biosystems), which allowed for the accurate sizing and allele calling of each microsatellite locus.

Figure 1
Iraqi pigeon breeds.

Statistical Analysis

SSR marker data were converted to genambig format using the package polysat (Clark & Jasieniuk, 2011) of the R software (Core 2015). Subsequently, FST, Gst, JostD, Rst measures, and polymorphic information coefficients (PIC) were calculated based on Bruvo’s distances (Bruvo et al., 2004). Bruvo’s distance for each pair of alleles is calculated as d=1-2^(-|r|), where r is the number of repeat units between the two alleles. After the distances are calculated at a locus for all pairs, the minimum average distance between allele combinations is determined as the distance for that locus. Afterward, the average of all loci was determined to calculate the Bruvo’s distance between two samples. To reveal heterozygosity and genetic diversity, the basic statistics of Ho, Hs, Ht, DST, FST and Fis for each locus were computed with the hierfstat package (Goudet & Jombart, 2015), and a custom R script to summarize and tabulate the results of the diversity measures. The R package LEA (Frichot & François 2015) was used to estimate the individual ancestry coefficients and infer ancestral populations. PCA and the Sparse Nonnegative Matrix Factorization (SNMF) algorithm were applied to data for these purposes. It has been reported that SNMF (Frichot et al., 2014), which is based on a likelihood algorithm, is at least ten times faster than the widely used ADMIXTURE software (Alexander et al., 2009). The SNMF calculates an entropy criterion that evaluates the quality of fit of the statistical model to the data using a cross-validation technique. The entropy criterion is used to decide the number of ancestral populations that best explain subgroups in the data (Alexander & Lange 2011; Frichot, et al., 2014). The elbow point on the line graph plotted for the values of the cross-entropy criterion versus the number of populations indicates the best number of ancestral populations. A multivariate molecular variance (AMOVA) analysis was run using the adonis2 function in a vegan package (Oksanen et al., 2022). We used the R packages ggtree (Yu, 2020) and ape (Paradis & Schliep, 2019) to plot the phylograms, cladograms, and other required phylogenetic plots. The R package gplots (Warnes et al., 2016) were used to draw the heatmaps and correlograms. Admixture graphs were plotted with the tess3r package (Caye et al., 2016) using the Q-matrix output generated by the Q function of the LEA package. The Nei distances between the populations were calculated using the R package poppr (Kamvar et al., 2014).

RESULTS

Analysis of genetic diversity

The genetic diversity of the studied population was assessed using 14 microsatellite loci, and the results are shown in Table 1. The metrics used to measure genetic diversity include Na, Ne, Ho, He, the inbreeding coefficient of an individual relative to the total population (FIT), the inbreeding coefficient of an individual relative to the subpopulation (FIS), the effect of subpopulations compared to the total population (FST), Nm, and PIC. Na per locus varied from 16 to 25, indicating a moderate-to-high level of allelic diversity within the population. Ne ranged from 11.95 to 20.56. This measure accounts for the proportion of alleles contributing to genetic diversity, suggesting substantial effective genetic variation. Ho values ranged from 0.27 to 0.53, indicating a relatively moderate level of heterozygosity across the loci. This value reflects the proportion of heterozygous individuals in the population. The He was consistently high across loci, ranging from 0.92 to 0.95. This indicates a high genetic diversity within the population under the assumption of Hardy-Weinberg equilibrium. FIT values ranged from 0.40 to 0.70, indicating a moderate to high level of overall inbreeding within the population. FIS values ranged from -0.04 to 0.41. The negative value for locus 5 suggests outbreeding, while positive values for other loci indicate varying degrees of inbreeding within subpopulations. FST values ranged from 0.40 to 0.54, indicating a significant genetic differentiation between subpopulations. Nm values, ranging from 0.21 to 0.37, suggest limited migration between subpopulations, contributing to genetic differentiation. PIC values ranged from 0.91 to 0.95, reflecting the high informativeness of the loci for genetic studies. The genetic diversity analysis revealed a high allelic diversity and heterozygosity level, with significant inbreeding and genetic differentiation among the pigeon populations. The high PIC values indicated that the microsatellite loci used are highly informative for the genetic diversity study of this population. As shown in Table 2, the analysis of genetic diversity in pigeon breeds revealed distinct patterns across various metrics, including Ho, average expected heterozygosity in subpopulations (HS), total gene diversity (HT), inbreeding coefficients (FIS and FIT), and measures of genetic differentiation (FST and DST). The Ho values ranged from 0.05 in Mosul White to 0.09 in Zangi. The average Ho across all breeds was 0.068, indicating moderate genetic variation within the populations. HS values ranged between 0.04 (observed in several breeds such as Fadadi, Mosul Blue, and Shamee) and 0.06 (in Kirkuk and Red breeds). The overall average HS was 0.046, suggesting lower expected heterozygosity within subpopulations than observed heterozygosity. HT values varied from 0.038 in Yellow to 0.099 in Shamee, with an overall average of 0.067. This metric reflects the total genetic diversity within the entire pigeon population studied. The FIS values indicate that the inbreeding level within subpopulations is negative across all breeds, ranging from -0.17 in Red to -0.86 in Zangi. The overall FIS was -0.46, suggesting an excess of heterozygosity and a low level of inbreeding within subpopulations. FST values, representing the genetic differentiation among subpopulations, ranged from 0.152 in Yellow to 0.326 in Mosul White, with an overall average of 0.259. This indicates a moderate to high genetic differentiation among the pigeon breeds. DST values ranged from 0.006 in Yellow to 0.034 in Shamee, with an overall average of 0.021. This metric reflects the genetic diversity between subpopulations, contributing to the overall genetic diversity. The genetic diversity analysis of the pigeon breeds showed moderate observed heterozygosity, lower expected heterozygosity within subpopulations, moderate total gene diversity, a general trend of excess heterozygosity indicating low inbreeding within subpopulations, and a moderate to high genetic differentiation among the breeds. These findings provide an insight analysis of the genetic structure and diversity within the studied pigeon populations.

Table 1
Measures of genetic diversity calculated on 14 microsatellite loci.

Locus	Na	Ne	Ho	He	FIT	FIS	FST	Nm	PIC
loc1	25	20.56	0.49	0.95	0.52	0.20	0.40	0.37	0.95
loc2	19	16.68	0.38	0.94	0.62	0.24	0.50	0.25	0.94
loc3	20	16.64	0.3	0.94	0.70	0.34	0.54	0.21	0.94
loc4	20	15.03	0.4	0.93	0.57	0.22	0.45	0.31	0.93
loc5	20	17.61	0.53	0.94	0.40	-0.04	0.42	0.34	0.94
loc6	16	13.77	0.38	0.93	0.54	0.15	0.46	0.29	0.92
loc7	21	17.94	0.31	0.94	0.69	0.41	0.48	0.28	0.94
loc8	19	11.95	0.39	0.92	0.60	0.32	0.41	0.36	0.91
loc9	21	17.32	0.32	0.94	0.66	0.40	0.43	0.33	0.94
loc10	24	19.27	0.4	0.95	0.58	0.29	0.41	0.35	0.95
loc11	20	15.67	0.27	0.94	0.67	0.39	0.46	0.29	0.93
loc12	18	15.84	0.29	0.94	0.66	0.31	0.51	0.24	0.93
loc13	20	13.97	0.32	0.93	0.60	0.31	0.42	0.34	0.92
loc14	19	15.35	0.39	0.93	0.54	0.20	0.43	0.34	0.93

• Number of alleles (Na), number of effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), inbreeding coefficient of an individual (I) relative to the total population (T) (FIT), inbreeding coefficient of an individual (I) relative to the subpopulation (S) (FIS), effect of subpopulations (S) compared to the total population (T) (FST), gene flow (Nm), polymorphic information content (PIC)

Table 2
Measures of genetic diversity for pigeon breeds.

Breed	HO	HS	HT	FIS	FST	DST
Kirkuk	0.07	0.06	0.055	-0.28	0.187	0.012
Baghdad	0.07	0.05	0.074	-0.28	0.281	0.025
Fadadi	0.08	0.04	0.058	-0.82	0.245	0.020
Zangi	0.09	0.05	0.06	-0.86	0.267	0.018
Mosul Blue	0.06	0.04	0.058	-0.39	0.242	0.015
Mosul White	0.05	0.04	0.074	-0.31	0.326	0.024
Red	0.06	0.05	0.078	-0.17	0.26	0.022
Yellow	0.07	0.05	0.038	-0.56	0.152	0.006
Shamee	0.06	0.04	0.099	-0.35	0.309	0.034
Raib	0.07	0.04	0.076	-0.58	0.32	0.029
Overall	0.068	0.046	0.067	-0.46	0.259	0.021

• Observed heterozygosity (Ho), average expected heterozygosity in subpopulations (HS), total gene diversity (HT), inbreeding coefficient of an individual (I) relative to the total population (T) (FIT), inbreeding coefficient of an individual (I) relative to the subpopulation (S) (FIS), effect of subpopulations (S) compared to the total population (T) (FST), average gene diversity among subpopulations (DST).

Genetic differentiation among the populations

The analysis of genetic differentiation among the pigeon breeds was conducted using FST values, which measure the genetic variance between populations (Figure 2). The FST values in this study varied widely, indicating different levels of genetic differentiation among the ten analyzed pigeon breeds. The Kirkuk breed showed no differentiation within its population (FST = 0.00) and had low to moderate differentiation from other breeds, with FST values ranging from 0.19 (Red) to 0.24 (Mosul Blue and Mosul White). The genetic differentiation between Kirkuk and Baghdad and between Kirkuk and Fadadi were both 0.22, indicating moderate differentiation. The Baghdad breed also showed no differentiation within its population (FST = 0.00) and had FST values with other breeds ranging from 0.19 (Red) to 0.25 (Mosul White). The genetic differentiation between Baghdad and Kirkuk was 0.22, similar to that between Baghdad and Fadadi (0.22). The Fadadi breed differentiated more from other breeds, particularly Yellow (FST = 0.42) and Raib (FST = 0.39). The FST values for Fadadi ranged from 0.22 (Kirkuk and Baghdad) to 0.42 (Yellow), indicating significant genetic differentiation. The Zangi breed had moderate to high differentiation from other breeds, with FST values ranging from 0.21 (Kirkuk and Baghdad) to 0.39 (Yellow). The differentiation between Zangi and Fadadi was notably high (FST = 0.35), indicating considerable genetic divergence. The Mosul Blue breed showed moderate differentiation from other breeds, with FST values ranging from 0.23 (Baghdad) to 0.34 (Raib and Mosul White). The differentiation between Mosul Blue and Kirkuk and Mosul Blue and Baghdad were respectively 0.24 and 0.23. The Mosul White breed displayed FST values ranging from 0.24 (Kirkuk) to 0.35 (Raib), indicating moderate differentiation. The differentiation between Mosul White and Mosul Blue was 0.34, suggesting some genetic divergence. The red breed had lower differentiation from other breeds, with FST values ranging from 0.19 (Kirkuk and Baghdad) to 0.30 (Raib). The differentiation between Red and Yellow and Red and Shamee were respectively 0.27 and 0.28. The Yellow breed exhibited high differentiation from several breeds, particularly Fadadi (FST = 0.42) and Zangi (FST = 0.39). The FST values for Yellow ranged from 0.20 (Kirkuk and Baghdad) to 0.42 (Fadadi), indicating significant genetic differentiation. The Shamee breed showed moderate differentiation from other breeds, with FST values ranging from 0.21 (Kirkuk and Baghdad) to 0.36 (Yellow). The differentiation between Shamee and Fadadi was 0.37, indicating notable genetic divergence. The Raib breed had high differentiation from several breeds, particularly Fadadi (FST = 0.39) and Yellow (FST = 0.37). The FST values for Raib ranged from 0.23 (Kirkuk) to 0.39 (Fadadi), suggesting significant genetic differentiation. The FST values indicate that the Fadadi and Yellow breeds exhibit the highest genetic differentiation among the pigeon breeds studied, while Kirkuk and Baghdad demonstrate a minor differentiation. Other breeds, such as Zangi, Mosul Blue, Mosul White, Red, Shamee, and Raib, show varying levels of moderate genetic differentiation, reflecting a complex pattern of genetic diversity among the pigeon populations. These findings provide a detailed understanding of the genetic relationships and diversity within and between the pigeon breeds analyzed.

Figure 2
Genetic differentiation according to FST values among the pigeon breeds.

PCA analysis

PCA was conducted to explore the genetic variation and population structure of 100 Iraqi pigeons, utilizing data from 14 SSR marker loci. The allele data was normalized before the PCA to ensure a consistent scale across different markers. The analysis identified two principal components that explain a significant portion of the genetic variance. Principal Component 1 (PC1) accounts for 55.52% of the total variance, capturing the dataset’s central portion of genetic differentiation. Principal Component 2 (PC2) explains 20.50% of the variance, improving the insight into the underlying genetic structure (Figure 3).

Kirkuk Cluster: This cluster distinctly encompasses the Kirkuk population, indicating a unique genetic identity separate from other groups. This suggests significant genetic differentiation, potentially driven by localized breeding practices or geographic isolation.

Baghdad Cluster: Samples from Baghdad form an individual cluster, pointing to distinct genetic traits that differentiate this population from others, possibly reflecting historical breeding selections unique to this area.

Raib Cluster: The Raib population is differentiated in its cluster, highlighting its unique genetic makeup compared to other populations. This separation could be indicative of unique evolutionary or breeding influences.

Red and Yellow Cluster: The Red and Yellow pigeons cluster together, suggesting shared genetic characteristics between these color variants. This grouping indicates lesser genetic differentiation between the two variants compared to other populations.

Mosul Blue, Mosul White, Zangi, Fadadi, and Shamee Cluster: This large cluster combines Mosul Blue, Mosul White, Zangi, Fadadi, and Shamee populations, showing a close genetic relationship among these groups. Despite the diversity within this cluster, these populations share more genetic similarities than those in the other clusters, perhaps due to shared geographic proximity or overlapping breeding practices.

This distinct clustering demonstrates that SSR markers effectively capture significant genetic diversity and structure among the pigeon populations. The separation into five clear clusters reflects pronounced genetic boundaries, elucidating the complex genetic landscape of these pigeons. The PCA analysis, with two principal components explaining a substantial 76.02% variance, effectively highlights the genetic distinctions and relationships within the Iraqi pigeon populations. This robust delineation of genetic structure provides essential insights for understanding these pigeon groups’ genetic dynamics and conservation needs.

Figure 3
Population structure based on PCA analysis for pigeon breeds.

Genetic structure analysis

The genetic structure of the ten pigeon breeds was analyzed using ancestry proportions derived from an admixture analysis with 3 clusters (clusters C1, C2, and C3) (Figure 4). The results highlight the distinct genetic contributions from three ancestral clusters across the different breeds. For the Fadadi breed, there is a small proportion of ancestry from Cluster C1, averaging approximately 2.16%. This breed shows a slightly higher proportion from Cluster C2, with an average of 3.75%, while most of its genetic makeup is derived from Cluster C3, amounting to approximately 94.08%. Zangi pigeons have about 2.79% of their ancestry from Cluster C1, 4.57% from Cluster C2, and a predominant influence from cluster C3, making up approximately 92.63% of its genetic structure. The Mosul Blue breed has a significant proportion of its ancestry, about 19.54%, from Cluster C1, with 3.84% from Cluster C2, and most of its genetic composition from Cluster C3, 76.62%. The Mosul White breed primarily comprises Cluster C1, with a high proportion of 97.02%. There is a small contribution from Cluster C2, at 2.02%, and a minimal genetic contribution from Cluster C3, at only 0.97%. The Red breed predominantly comprises Cluster C1, with 99.03%, a minor proportion from Cluster C2, at 0.87%, and almost no contribution from Cluster C3, at 0.10%. The Yellow breed shows a practically negligible proportion from Cluster C1, at 0.01%, is dominantly composed of Cluster C2, with 99.98%, and has a minimal contribution from Cluster C3, at 0.01%. Shamee pigeons have a deficient proportion from Cluster C1, at 0.01%, are predominantly composed of Cluster C2, with 99.98%, and have a minimal contribution from Cluster C3, at 0.01%. The Raib breed has a small proportion of its ancestry from Cluster C1, at 0.81%, a very high proportion from Cluster C2, at 98.98%, and a minimal contribution from Cluster C3, at 0.21%. For the Kirkuk breed, 8.82% of its ancestry is in Cluster C1, a dominant proportion in Cluster C2, at 81.78%, and the remaining genetic makeup in Cluster C3, at 9.39%. Baghdad pigeons have 11.88% of their ancestry from Cluster C1, a significant proportion from Cluster C2, at 77.09%, and the remaining ancestry from Cluster C3, at 11.02%. This genetic structure analysis reveals distinct patterns of ancestry across the ten pigeon breeds, with each breed showing varying contributions from the three ancestral clusters. This analysis provides valuable insights into these pigeon populations’ genetic diversity and historical gene flow, highlighting unique genetic signatures and potential evolutionary relationships.

Figure 4
Admixture plot for pigeon breeds.

Analysis of genetic distances and phylogenetic analysis

The analysis of genetic distances among various pigeon breeds in Iraq, as presented in Figure 5, highlights the genetic relationships and differentiation among these populations. The table displays the pairwise Nei’s genetic distances, providing insights into the genetic diversity and relatedness of the breeds. The Kirkuk population exhibits relatively low genetic distances with Baghdad (0.08), Mosul Blue (0.08), and Mosul White (0.07), indicating close genetic relationships. The distances with Fadadi (0.12), Zangi (0.13), and Yellow (0.10) are slightly higher, suggesting moderate genetic differentiation. Baghdad shows the closest genetic relationships with Red (0.06), Mosul White (0.07), and Kirkuk (0.08). The genetic distances with Fadadi (0.12), Zangi (0.13), and Yellow (0.10) are higher, indicating more significant genetic divergence. Fadadi’s genetic distances with other populations are generally higher, with the smallest distance observed with Mosul Blue and Mosul White (0.08). The distances with Zangi (0.14), Yellow (0.15), and Raib (0.14) are the highest, indicating significant genetic differentiation. Zangi shows closer genetic relationships with Mosul Blue (0.09) and Mosul White (0.10), while the distances with Fadadi (0.14), Yellow (0.15), and Raib (0.15) suggest more significant genetic divergence. Mosul Blue has low genetic distances with Kirkuk (0.08), Baghdad (0.08), and Mosul White (0.07), indicating close genetic relationships. The distances with Fadadi (0.08), Zangi (0.09), and Yellow (0.10) are higher, suggesting moderate genetic differentiation. Mosul White exhibits the closest genetic relationships with Baghdad (0.07), Mosul Blue (0.07), and Kirkuk (0.07). The genetic distances with Fadadi (0.08), Zangi (0.10), and Yellow (0.09) are slightly higher, indicating moderate genetic differentiation. Red shows the closest genetic relationships with Baghdad (0.06), Mosul White (0.06), and Kirkuk (0.07). The distances with Fadadi (0.11), Zangi (0.11), and Yellow (0.08) are higher, indicating more significant genetic divergence. Yellow’s genetic distances are generally higher, with the closest relationships observed with Red (0.08) and Mosul White (0.09). The distances with Fadadi (0.15), Zangi (0.15), and Raib (0.12) indicate significant genetic differentiation. Shamee has low genetic distances with Kirkuk (0.08), Baghdad (0.08), and Mosul White (0.07), suggesting close genetic relationships. The distances with Fadadi (0.12), Zangi (0.13), and Yellow (0.10) are higher, indicating moderate genetic divergence. Raib shows closer genetic relationships with Mosul Blue (0.10), Mosul White (0.09), and Shamee (0.10). The genetic distances with Fadadi (0.14), Zangi (0.15), and Yellow (0.12) are higher, suggesting significant genetic differentiation. The genetic distance analysis reveals that populations like Kirkuk, Baghdad, and Mosul White are more closely related, while Fadadi, Zangi, and Yellow exhibit greater genetic diversity and differentiation. These findings provide valuable insights into the genetic structure and evolutionary relationships among pigeon breeds in Iraq.

Figure 5
Heat map of pairwise Nei’s genetic distance.

The phylogenetic tree provides a detailed visual representation of the genetic relationships among the different pigeon breeds (Figure 6). It highlights several key insights. Firstly, populations such as Kirkuk and Baghdad form tight clusters on the tree, indicating that individuals within these groups are genetically similar. This close clustering suggests a high degree of genetic relatedness, reflecting a relatively recent common ancestry and limited genetic divergence within these populations. In contrast, populations like Mosul White, Red, and Shamee are more dispersed on the phylogenetic tree. This greater spread indicates higher genetic distances among individuals, reflecting significant genetic diversity. This suggests that these populations may have a more ancient common ancestry and have undergone more genetic differentiation over time, highlighting their diverse genetic backgrounds. Zangi and Raib populations form intermediate clusters, indicating a balanced level of genetic diversity. They are less closely related than the tight clusters and less diverse than the more spread-out populations. This suggests that Zangi and Raib populations have moderate genetic variation, with a mix of closely related and more distantly related individuals. The close genetic relationships observed in tightly clustered populations suggest limited genetic variability, which could be due to geographical isolation, selective breeding, or a small founder population. On the other hand, the greater genetic diversity in more dispersed populations might be due to larger population sizes, a broader geographical distribution, or historical admixture with different populations. Understanding pigeon populations’ genetic diversity and relatedness is crucial for breeding programs. For populations that form tight clusters, introducing genetic diversity can prevent inbreeding depression and enhance genetic resilience. Conversely, for more genetically diverse populations, conservation efforts might focus on maintaining this diversity to ensure the long-term health and adaptability of the breed.

Figure 6
Phylogenetic Tree of pigeon breeds based on relationships evolution.

Analysis of molecular variance (AMOVA)

The AMOVA provides a detailed breakdown of genetic variation among and within pigeon populations. The results, as presented in Table 3, revealed significant insights into these populations’ genetic structure and differentiation. The analysis partitions the total genetic variance into components attributable to differences among and within populations. The degrees of freedom (DF) among and within populations were 9 and 90, respectively, with a total DF of 99. The sum of squares among populations is 1024.67, and the mean squared (MS) value is 113.85. This leads to a variance component of 10.92, which indicates the amount of genetic variation that can be attributed to differences among the populations. The variance coefficient among populations was 9.70, and the Phi-statistic was 0.58. The Phi-statistic measures the degree of genetic differentiation among populations, with a value of 0.58 indicating moderate to high genetic differentiation. Within populations, the sum of squares was 721.45, with a mean squared value of 8.01. The variance component within populations was 8.02, reflecting the genetic variation present within each population. The total variance, which combines among and within population components, was calculated at 18.94. This total variance was derived from the sum of squares of 1746.12 and a total mean squared value of 17.63. These results highlight that a significant portion of the genetic variation is due to differences among populations, as indicated by the higher variance component among populations compared to within populations. The Phi-statistic further confirmed considerable genetic differentiation among the populations studied. Overall, the AMOVA results provided a comprehensive view of the genetic structure, indicating that there was both substantial genetic diversity within populations and significant differentiation between them. This analysis is crucial for understanding pigeon populations’ genetic relationships and evolutionary dynamics.

Table 3
AMOVA Results.

Source	DF	Sum of squares	MS	Variance components	Variance coefficients	Phi-statistics
Among populations	9	1024.67	113.85	10.92	a: 9.70	0.58
Within Populations	90	721.45	8.01	8.02
Total	99	1746.12	17.63	18.94

• MS: mean squared, DF: Degree of freedom

DISCUSSION

Genetic diversity

The analysis of genetic diversity in our studied pigeon population, using 14 microsatellite loci, provided a detailed understanding of their genetic structure and variability. Our study revealed a moderate to high level of allelic diversity, as indicated by the Na per locus. This is consistent with findings by Podbielska & Radko (2022) and Ramadan et al. (2018), who also reported substantial allelic variation across their studied loci. The Ne in our study suggested a high level of genetic variation, which aligns with the results from these studies, indicating a substantial contribution of alleles to genetic diversity. The Ho in our population ranged from moderate to high, slightly lower than the consistently high He. This discrepancy between Ho and He suggests the presence of some degree of inbreeding or selection pressures, as also noted by Ramadan et al. (2011) and Biala et al. (2015). The high He values indicated that the genetic diversity within a population is potentially high under Hardy-Weinberg equilibrium conditions, similar to the findings of Podbielska & Radko (2022). FIT and FIS in our study showed varying degrees of inbreeding among the loci. FIT values indicated moderate to high overall inbreeding within the population, comparable to the results of Biala et al. (2015), who also reported significant inbreeding. FIS values suggested both inbreeding and outbreeding across different loci, similar to the findings of Ramadan et al. (2018), where some loci exhibited outbreeding (negative FIS values) and others showed inbreeding. The FST values in our study indicated significant genetic differentiation between subpopulations, suggesting limited gene flow. This is consistent with the high FST values reported by Podbielska & Radko (2022) and Ramadan et al., (2011), highlighting substantial genetic structuring within their studied populations.The limited Nm values in our study further supported this finding, indicating restricted gene flow between subpopulations, contributing to genetic differentiation. The high PIC values in our study confirm the effectiveness of the microsatellite loci in assessing genetic diversity. This finding aligns with the studies by Podbielska & Radko (2022) and Biala et al. (2015), who also reported high PIC values, underscoring the markers informativeness for genetic studies. Several factors could influence our pigeon population’s observed genetic diversity and differentiation. Geographic barriers may limit gene flow between subpopulations, leading to significant genetic differentiation, as the high FST values suggest. Selective breeding and management practices may contribute to the population’s observed inbreeding and genetic structuring levels. Historical population bottlenecks or expansions could have shaped the current genetic diversity, affecting the allelic richness and heterozygosity levels. Individuals’ differential survival and reproduction may lead to deviations from Hardy-Weinberg equilibrium, influencing the genetic diversity and inbreeding coefficients. Our study revealed a high level of genetic diversity within the studied pigeon population, with significant inbreeding and genetic differentiation among subpopulations. The comparison with previous studies by Podbielska & Radko (2022), Ramadan et al. (2012, 2018), and Biala et al. (2015) highlights common patterns of genetic diversity, including high allelic variation, substantial genetic differentiation, and informativeness of microsatellite markers. The findings underscore the importance of considering factors such as geographic isolation, breeding practices, population history, and natural selection to understand the genetic structure of pigeon populations. These insights are crucial for guiding conservation strategies and breeding programs to maintain genetic health and diversity in pigeon populations. Ho values ranged from 0.05 in Mosul White to 0.09 in Zangi, with an average Ho of 0.068 across all breeds. This suggests moderate genetic variation within these pigeon populations. When compared to the findings of Ramadan et al., (2018) and Bigi et al., (2016), where Ho values ranged from 0.307 to 0.758 and 0.431 to 0.661, respectively, it is evident that the populations in the current study exhibited lower observed heterozygosity. This lower variation could be attributed to potential breeding practices that favored certain traits, thereby reducing genetic diversity. HS values ranged from 0.04 in Fadadi, Mosul Blue, and Shamee breeds to 0.06 in Kirkuk and Red breeds, with an overall average of 0.046. This lower expected heterozygosity within subpopulations suggests reduced genetic variability, which aligns with the findings of Bigi et al., (2016), who reported generally higher HS values, indicating more genetic diversity in their studied populations. This discrepancy could result from different breeding and selection pressures in the studied regions. HT values varied from 0.038 in Yellow to 0.099 in Shamee, with an average of 0.067. This reflects the total genetic diversity within the studied pigeon population, slightly lower than the diversity levels reported by Bigi et al. (2016) and Ramadan et al. (2018). The difference might be due to the smaller sample size or the specific genetic markers used in the current study. The FIS values were negative across all breeds, ranging from -0.17 in Red to -0.86 in Zangi, with an overall FIS of -0.46. This indicates an excess of heterozygosity and low levels of inbreeding within subpopulations. Comparatively, Ramadan et al., (2018) reported FIS values ranging from -0.216 to 0.194, suggesting that the populations in the current study may be experiencing less inbreeding. This could be due to effective breeding strategies or a naturally diverse gene pool. FST values ranged from 0.152 in Yellow to 0.326 in Mosul White, with an overall average of 0.259, indicating moderate to high genetic differentiation among the pigeon breeds. DST values ranged from 0.006 in Yellow to 0.034 in Shamee, with an overall average of 0.021. This level of genetic differentiation is consistent with the findings of Bigi et al., (2016), who reported similar levels of differentiation, indicating that despite geographic and possibly cultural differences, pigeon populations tend to maintain a moderate level of genetic differentiation. This differentiation might be driven by geographical isolation and selective breeding practices. When comparing these results with the studies by Ramadan et al. (2018) and Bigi et al. (2016), several key differences and similarities are observed. Both previous studies reported higher levels of observed and expected heterozygosity, indicating greater genetic diversity. Additionally, the lower FIS values in the current study suggest a higher excess of heterozygosity compared to the slightly positive or neutral FIS values reported by Ramadan et al., (2018). This could indicate management practices that are more effective at maintaining genetic diversity. The genetic diversity analysis of the pigeon breeds in the current study revealed moderate observed heterozygosity, lower expected heterozygosity within subpopulations, and moderate total gene diversity. The trend of excess heterozygosity indicates low inbreeding within subpopulations, while the moderate to high genetic differentiation among breeds suggests distinct genetic structures influenced by breeding practices and geographic separation. These findings provide a comprehensive overview of the genetic structure and diversity within the studied pigeon populations, highlighting the importance of maintaining genetic variability to ensure the health and sustainability of these breeds.

Genetic differentiation

The genetic differentiation analysis of pigeon breeds in this study, based on FST values, provides a comprehensive view of the genetic variance among the ten breeds analyzed. Our findings revealed a wide range of genetic differentiation, with Kirkuk and Baghdad breeds showing no differentiation within their populations (FST = 0.00) and low to moderate differentiation from other breeds. The FST values for Kirkuk and Baghdad with other breeds ranged from 0.19 to 0.25, indicating relatively stable genetic structures within these breeds. This pattern suggests that these breeds experienced limited gene flow from different populations or maintained a high level of genetic consistency through controlled breeding practices. In contrast, breeds like Fadadi and Yellow exhibited the highest genetic differentiation, with FST values reaching 0.42, particularly between Fadadi and Yellow, indicating significant genetic divergence. This high level of differentiation could be due to geographical isolation or selective breeding that has reinforced distinct genetic characteristics in these breeds. Similarly, Zangi, Mosul Blue, Mosul White, Shamee, and Raib showed moderate to high differentiation, with FST values indicating varying degrees of genetic separation from other breeds. Compared to Bigi et al. (2016), who reported an average FST of 0.22, our study’s FST values are within a similar range, suggesting comparable levels of genetic differentiation. Bigi et al. (2016) also noted significant differentiation among Italian pigeon breeds, with FST values highlighting distinct genetic clusters. Our findings align with this, showing apparent genetic clustering, particularly among breeds like Fadadi and Yellow, which mirrors the differentiation patterns observed in Italian pigeons. Comparatively, Giunchi et al., (2020) reported lower FST values among Italian feral pigeon populations, with the highest being 0.093 between Venice and Bolzano, and 0.081 between Sassari and Venice. The lowest FST values were observed between Pisa and Treviso (0.016) and Pavia and Treviso (0.019), indicating minimal genetic differentiation. This lower level of differentiation suggests a higher degree of gene flow and less isolation among the Italian feral pigeon populations than the Iraqi breeds. The differences in genetic differentiation patterns between our study and Giunchi et al., (2020) emphasize the influence of local breeding practices and historical gene flow in shaping the genetic structure of pigeon populations in different regions. Podbielska & Radko (2022) found lower genetic differentiation in Polish pigeon populations, with a high average gene flow. This contrasts with our moderate to high differentiation findings and potentially lower gene flow. This suggests that Polish pigeons might have more interpopulation breeding, maintaining higher genetic diversity, whereas our studied populations might have more restricted gene flow, leading to more significant genetic differentiation. Compared with the findings of Ramadan et al. (2007, 2018), who reported significant differentiation in Egyptian pigeons, our study shows similar genetic diversity and differentiation patterns. The FST values in our study indicate notable genetic divergence, similar to the differentiation observed in Egyptian pigeon populations. This suggests that pigeon breeds in different regions exhibit significant genetic structuring due to localized breeding practices and geographical barriers. Jacob et al. (2015) highlighted that mating with genetically similar mates can have adaptive benefits despite the risks of inbreeding. Our study’s observations of moderate to high differentiation and distinct genetic clusters support the notion that selective breeding practices may enhance specific traits while maintaining overall genetic health through controlled breeding strategies. Overall, the FST values from this study demonstrate a complex pattern of genetic diversity among pigeon breeds, with significant differentiation observed in breeds like Fadadi and Yellow. In contrast, breeds like Kirkuk and Baghdad show minimal differentiation. These results underscore the importance of understanding genetic relationships and diversity within and between pigeon breeds to develop effective conservation and breeding strategies that preserve genetic health and adaptability. The comparison with previous studies reinforces the need for continuous genetic monitoring and tailored management practices to maintain genetic diversity and enhance the sustainability of pigeon populations.

PCA analysis

The PCA analysis revealed five distinct clusters, highlighting significant genetic structures and population differentiation among pigeon breeds.

Kirkuk Cluster: The distinct clustering of the Kirkuk population indicates a unique genetic identity, likely driven by localized breeding practices or geographic isolation. This significant genetic differentiation suggests that the Kirkuk pigeons have maintained a relatively isolated genetic pool, enhancing their distinct genetic characteristics.

Baghdad Cluster: Samples from Baghdad formed a separate cluster, reflecting distinct genetic traits, possibly due to historical breeding selections unique to this area. This distinct genetic identity highlights the impact of selective breeding practices on the genetic structure of the Baghdad pigeon population.

Raib Cluster: The Raib population forms a differentiated cluster, indicating a unique genetic makeup compared to other populations. This separation could be due to unique evolutionary pressures or specific breeding influences that have shaped the genetic identity of the Raib pigeons.

Red and Yellow Cluster: The clustering of red and yellow pigeons suggests shared genetic characteristics between these color variants. This indicates lesser genetic differentiation between these two populations, possibly due to similar breeding practices or historical interbreeding.

Mosul Blue, Mosul White, Zangi, Fadadi, and Shamee Cluster: The large cluster combining these populations shows a close genetic relationship, suggesting more genetic similarities. This may be due to shared geographic proximity or overlapping breeding practices, resulting in significant genetic overlap among these groups.

The DAPC analysis by Bigi et al. (2016) identified clusters among Italian pigeon breeds but revealed no well-defined overall structure. In contrast, our PCA analysis showed apparent clustering, indicating well-defined genetic boundaries among the Iraqi pigeon populations. This suggests that the genetic structure of Iraqi pigeons might be more pronounced, possibly due to stronger geographic or breeding barriers. PCA analysis conducted by Podbielska & Radko (2022) revealed a high degree of overlap among Polish homing pigeon genotypes, suggesting a genetically mixed population with no distinct separation of individuals based on their origin. In contrast, our PCA results revealed distinct clusters, highlighting more significant genetic differentiation and less gene flow among Iraqi pigeon populations. This difference underscores the impact of geographic isolation and localized breeding on the genetic structure of Iraqi pigeons compared to the more mixed genetic background of Polish homing pigeons. The distinct clustering observed in our PCA analysis emphasizes the importance of maintaining genetic diversity and managing breeding practices to preserve the unique genetic identities of these pigeon populations. The pronounced genetic boundaries elucidated by this analysis provide essential insights for developing targeted conservation strategies and enhancing these pigeon groups’ genetic health and sustainability. This study’s robust delineation of genetic structure contrasts with the more integrated genetic landscapes observed in previous studies, highlighting the need for tailored conservation efforts to address the specific genetic dynamics of Iraqi pigeon populations.

Genetic structure

The genetic structure analysis of the ten pigeon breeds revealed distinct patterns of ancestry contributions from three ancestral clusters (C1, C2, and C3). Each breed exhibits unique ancestry proportions from these clusters, showcasing significant genetic diversity among the breeds. For instance, the Fadadi and Zangi breeds predominantly derive their genetic makeup from Cluster C3, with smaller contributions from Clusters C1 and C2. In contrast, breeds like Mosul White and Red primarily comprise Cluster C1, showing minimal contributions from the other clusters. The Yellow and Shamee breeds are dominantly composed of Cluster C2, with negligible contributions from Clusters C1 and C3. Breeds such as Raib, Kirkuk, and Baghdad show a significant proportion of their ancestry from Cluster C2, with varying contributions from Clusters C1 and C3. This genetic structure highlights the complex interplay between historical breeding practices, geographical influences, and selective breeding for specific traits. The dominance of Cluster C3 in breeds like Fadadi and Zangi suggests a shared genetic background potentially linked to specific breeding goals or geographic regions where these breeds were developed. The strong presence of Cluster C1 in breeds like Mosul White and Red indicates a focused selection for particular traits, likely morphological, that are consistently passed down through generations. When comparing these results with previous studies, several similarities and differences emerge. Stringham et al. (2012) identified distinct genetic clusters among pigeon breeds based on phenotypic traits and geographical origins, aligning with our study’s dominance of specific clusters. The clustering of homing and utility pigeons in Stringham et al., (2012) is consistent with the significant C2 and C3 contributions in breeds like Baghdad and Kirkuk, suggesting a shared genetic background influenced by performance traits. This indicates that similar selection pressures, such as those for homing ability or utility purposes, lead to the convergence of genetic profiles across different breeds. In contrast, Giunchi et al., (2020) identified the best grouping at C=4 using structure analysis for Italian feral pigeon populations. Their results indicated significant admixture, particularly in regions with a long history of pigeon breeding. Populations from Bolzano, Venice, and Sassari were associated with different clusters with high individual membership values, while other populations showed traces of admixture with these clusters. This admixture pattern suggests ongoing gene flow and a more interconnected genetic structure among the Italian feral pigeon populations. Our findings contrast with those of Giunchi et al. (2020), as the Iraqi pigeon breeds exhibit more defined and distinct genetic clusters, reflecting historical breeding isolation and limited gene flow between breeds. The genetic structure of Iraqi breeds, with clear ancestral contributions, underscores the impact of breeding practices and geographical separation on the genetic makeup of these populations. In contrast, the genetic structure of Italian feral pigeons is more indicative of continuous gene flow and admixture, likely due to the movement and interbreeding of pigeons across different regions. Bigi et al., (2016) observed distinct genetic clusters at higher K values, consistent with the diverse ancestry proportions in our study. The stability of specific clusters, such as the hen group (Florentine, Triganino [Schietto], Triganino [Gazzo], and German Modena), parallels the strong genetic identities seen in breeds like Mosul White and Red, shaped by selective breeding. The apparent genetic distinctions at higher K values suggest that historical breeding practices have maintained distinct genetic lines, emphasizing the importance of preserving these unique genetic identities for future breeding and conservation efforts. Ramadan et al., (2018) identified close genetic relationships between breeds, comparable to the substantial shared ancestry observed in breeds such as Fadadi and Zangi. The unique genetic profile of the Nemssawy breed in Ramadan et al., (2018) is analogous to the distinct dominance of Cluster C1 in the Red breed, highlighting the role of morphological selection in shaping genetic uniqueness. This suggests that targeted breeding for specific morphological traits can lead to highly distinct genetic profiles, even among breeds that might otherwise share a common genetic background. Podbielska & Radko (2022) reported genetic diversity and clustering unrelated to geographical origin, aligning with the varying ancestry proportions in our study. Breeds like Shamee and Yellow exhibit dominant clusters regardless of regional considerations, reflecting genetic mixing due to extensive trade and breeding practices. This indicates that modern breeding practices involving the exchange of birds across regions contribute significantly to the genetic diversity observed in contemporary pigeon populations. Hernandez-Alonso et al. (2023) identified admixture and mixed ancestry components consistent with the diverse genetic contributions of breeds like Baghdad and Kirkuk. The intermediate genetic positions of historical feral pigeons observed by Hernandez-Alonso et al. (2023) are similar to the mixed ancestry in breeds like Mosul Blue. This highlights the fluid boundaries between domestic and feral pigeon populations, with historical gene flow contributing to the genetic makeup of modern breeds. The distinct genetic structures observed across the ten pigeon breeds can be attributed to selective breeding for specific traits, historical gene flow influenced by trade and breeding practices, and the movement and exchange of pigeons across regions. These factors have created a complex genetic landscape, resulting in significant diversity and unique genetic signatures among pigeon breeds. The reasons behind these patterns are multifaceted. Selective breeding for desirable traits, such as color, morphology, or performance abilities, has led to the concentration of specific genetic components within certain breeds. Historical gene flow, facilitated by trade and the movement of pigeons for racing or ornamental purposes, has introduced genetic diversity and led to admixture between different populations. The continuous exchange of pigeons across regions, associated with breeders’ preferences for specific traits, has further shaped the genetic landscape, resulting in the observed diversity and unique genetic profiles. These findings highlight the importance of integrating genetic data with historical and breeding information to inform conservation and breeding strategies. Ensuring the preservation of genetic diversity and adaptability in pigeon populations requires a comprehensive understanding of the genetic contributions from different ancestral clusters and the historical context of breeding practices. This approach will help maintain pigeon breeds’ genetic health and viability for future generations.

AMOVA analysis

The AMOVA results from this study revealed significant genetic differentiation among pigeon populations, comparable to the findings of Bigi et al. (2016). Our analysis shows higher genetic differentiation among populations, suggesting stronger genetic isolation or distinct breeding practices. The within-population genetic diversity observed is substantial, indicating a healthy level of genetic variation. Compared to Bigi et al. (2016), our populations exhibited more significant genetic variation within groups, possibly due to more diverse breeding environments. The moderate-to-high Phi-statistic underscores the importance of managing genetic diversity to prevent inbreeding and maintain population health. This differentiation highlights the evolutionary dynamics and distinct genetic structures of pigeon populations. Our findings emphasize the need for conservation strategies that preserve genetic diversity and promote sustainable breeding practices, ensuring the long-term viability of pigeon breeds.

CONCLUSIONS

This study comprehensively characterized Iraqi pigeon breeds’ genetic diversity and population structure using SSR markers. The findings revealed substantial genetic variation and distinct population structures among the studied pigeon breeds. The high allelic diversity and heterozygosity indicate a rich genetic reservoir within these populations. The significant genetic differentiation evidenced by FST values and supported by limited gene flow, suggests distinct genetic identities among the breeds, likely influenced by localized breeding practices and geographic isolation. The significant genetic differentiation among the breeds highlights the importance of preserving the unique genetic identities of each breed. Conservation strategies should focus on maintaining genetic diversity and preventing genetic homogenization. To ensure the sustainability of these pigeon populations, breeding programs should incorporate genetic information to avoid inbreeding and promote genetic health. This includes monitoring genetic diversity and implementing controlled breeding practices to enhance genetic variation. Future studies should expand the genetic analysis to include more breeds and regions, providing a more comprehensive understanding of pigeon genetics. Integrating other molecular markers and genomic technologies could offer deeper insights into the genetic architecture and evolutionary dynamics of pigeon populations. This study’s distinct genetic clusters and ancestral contributions provide a foundation for exploring Iraqi pigeons’ evolutionary history and adaptive traits. Further research should investigate the ecological and environmental factors influencing genetic differentiation and adaptation. Regular genetic monitoring is essential to detect genetic diversity and structure changes. This will help identify potential threats to the genetic integrity of pigeon breeds, and implement timely conservation measures. In conclusion, this study highlights Iraqi pigeon breeds’ genetic richness and diversity, offering valuable insights into their genetic structure and evolutionary relationships. The findings underscore the need for targeted conservation and breeding strategies to preserve the genetic heritage of these pigeons, ensuring their continued health and sustainability for future generations.

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• Funding
  There is no funding for this study.
• Data availability statement
  Data will be available upon request.
• Disclaimer/Publisher’s Note
  The published papers’ statements, opinions, and data are those of the individual author(s) and contributor(s). The editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content.

Edited by

• Section editor:
  Maria Fernanda Burbarelli

Data availability

Data will be available upon request.

Publication Dates

• Publication in this collection
  21 Oct 2024
• Date of issue
  2024

History

• Received
  22 May 2024
• Accepted
  02 Aug 2024