Haemoglobin Polymorphism Investigation and their Effects on Morphometric Traits on Two Goat Breeds in South Western Nigeria

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Blood samples from 400 goats (200 WAD and 200 RS) were analyzed using cellulose acetate electrophoresis, revealing three genotypes (AA, AC, CC) controlled by two co- dominant alleles. Allele frequencies for A, B, and C were 0.00, 0.28, and 0.72 in WAD and 0.00, 0.22, and 0.77 in RS goats, respectively. Genotype frequencies in WAD were 0.02 (AA), 0.51 (AC), and 0.47 (CC); and 0.00 (AA), 0.44 (AC), and 0.56 (CC) in RS goats. A significant deviation from Hardy-Weinberg equilibrium (P < 0.05) was observed, indicating non-random mating. The expected heterozygosity (H) was 0.40 and 0.35 for WAD and RS, respectively, while the local inbreeding coefficient (F) was − 0.28, suggesting disassortative mating. In terms of body traits, individuals with Hb AC and CC genotypes exhibited significantly higher (P < 0.05) body weight, heart girth, height at withers, ear length, and hock length in both goat breeds. Other body parameters showed no significant differences. The study concluded that Hb A allele predominates in WAD goats and that Hb CC genotype correlates with superior body measurements. It also emphasized the need for further studies using advanced molecular tools to understand the genetic basis of productivity traits and improve selective breeding programs in indigenous goat populations in Nigeria. Haemoglobin Polymorphism Morphometric traits Goats INTRODUCTION In the evolving landscape of Nigeria’s livestock economy, goat breeding has gained prominence due to its potential for poverty alleviation, food security, and sustainable agriculture, particularly among rural populations (Adewumi et al., 2023 ; Okezie et al. , 2022). Genetic improvement remains a cornerstone of animal breeding programs, with genetic variation serving as a pivotal tool for enhancing economically important traits (FAO, 2021). Advances in molecular genetics and biotechnology such as marker-assisted selection, genome-wide association studies (GWAS), and reproductive biotechnologies have expanded the capacity to conserve, characterize, and sustainably utilize animal genetic resources (AnGR) (Yakubu et al., 2023 ; Olowofeso et al. , 2021). These innovations enable more targeted breeding programs in indigenous breeds like the West African Dwarf (WAD) and Red Sokoto (RS) goats, which are important genetic reservoirs in Nigeria (Ajayi et al., 2022 ). Blood protein polymorphisms have emerged as valuable markers for genetic characterization and breeding decisions. Among these, haemoglobin polymorphism has attracted attention due to its biochemical and physiological relevance, particularly in relation to oxygen transport, adaptability to environmental stressors, and associations with performance traits (Akinyemi et al., 2024 ). Haemoglobin is a tetrameric globular protein consisting of two α- and two β-globin chains, each conjugated to a heme group, and plays a key role in vertebrate respiration (Adeola et al ., 2022). The alpha globin gene family, which evolved through gene duplication events, often exhibits polymorphisms that influence gene expression and phenotype (Musa et al., 2023 ). Recent studies have reaffirmed the existence of haemoglobin variants (HbA and HbB) and their frequencies across different goat populations. For instance, in a comparative study of Nigerian goat breeds, the HbA allele was predominant, with frequencies exceeding 0.80 in WAD goats, while HbB remained less common (Ojo et al., 2023 ). Similar trends were observed in Red Sokoto goats, suggesting a selective advantage or population-specific fixation (Ibrahim et al. , 2024). These patterns align with earlier findings in other global populations, such as the Malabari goats in India and the Arbi goats in Tunisia (Bindu and Raghavan, 2010; Nafti et al. , 2013), although newer studies are now delving into the adaptive significance of these variants in diverse agro-ecological zones. Haemoglobin polymorphism has also been linked to important phenotypic traits. For instance, Yakubu and Imumorin (2022) reported that HbAA genotypes in Nigerian goats exhibited superior morphometric traits, including higher body weight and longer limb lengths. A study by Bello et al . (2021) demonstrated that the HbAB genotype in goats was associated with better thermotolerance and improved hair quality, features critical for adaptation to Nigeria’s humid tropical climate. Likewise, in sheep, the HbAA phenotype correlated with enhanced wool fiber length and tensile strength (Olawale et al. , 2021). In rabbits, haemoglobin genotype has shown influence over growth performance. Onwuka et al. (2023) observed that HbAB kits significantly outperformed their HbAA counterparts in terms of weaning and post-weaning weights. This supports earlier claims that heterozygous genotypes may offer a hybrid vigor effect in certain traits (Chineke et al ., 2007). Such findings underscore the utility of haemoglobin genotyping as a cost-effective approach to identifying animals with superior growth, adaptability, and productivity under varying environmental conditions. Despite increasing interest in genetic studies, the molecular characterization of indigenous goat breeds in South Western Nigeria remains limited. Previous efforts have largely focused on phenotypic classification, leaving a gap in the understanding of their genetic diversity at the molecular level (Akinola et al. , 2022). Addressing this knowledge gap is critical for the conservation and genetic improvement of native goat populations. Therefore, this study aims to investigate the haemoglobin genetic structure of West African Dwarf and Red Sokoto goats from South Western Nigeria and explore the associations between haemoglobin variants and key morphometric traits. MATERIALS AND METHODS Experimental site The study was carried out between latitudes 6 o 21 and 8 o 37N and Longitudes 2 o 31 and 6 o 00 East. Land area has an approximate of about 77,813km and 85 forest reserves with a forest area covering 842,499 hectares. The climate is tropical and is characterized by two seasons (dry and wet). The annual temperature and rainfall range between (21 C and 34 C) and (1500mm and 3000mm) respectively. The vegetation is made up of fresh water swamp and mangrove forest at the belts (Oluseyi, 2014). Experimental animal A total of 400 (200 WAD and 200 Red Sokoto) three (3) years mature goats of both sexes in South Western Nigeria were randomly sampled. The animals which were reared through the extensive management system originated from different herds sampled in the state.. The age was estimated using dentition. Data collection Data was collected on the following morphometric traits A measuring stick was used to take height, while a flexible tape was used to take length and circumference measurements. Withers height (WH) is the distance between the most cranial, palpable spinous process and the ground. Chest (C) Measurement of the distance between the top of the pectoral girdle and the ground. Horn Length (HL) is the longest distance between the base and tip of the horns. Hock (H) In a digitigrade or unguligrade quadruped, the hock is the joint between the tarsal bones and the tibia. Heart girth (HG) The heart girth was determined by measuring the diameter of the body at its narrowest point just behind the shoulder and perpendicular to the body axis. Body length (BL) The distance between the lateral tuberosity on the scapular and the pin bone is measured diagonally. Muzzle (M) The distance between the dorsal tip of the nasal planum and the dorsal nasal ligament. The nasal planum, and occipital protuberance are palpated as well as visually determined. Tail length (TL) The distance between the base of the tail and the coccygeal vertebrae is known as tail length. Live Weight (LW) The amount or quantity of heaviness or mass of a live animal. Each animal was restrained in an unforced position by an assistant to facilitate easy measurements. Tella et al. (2023) was used as anatomical points of reference for the linear body measurements. Blood collection Blood samples (5 mL per animal) were obtained from the jugular vein and placed in tubes with EDTA(Ethylene-diamine tetra-acetic acid) as anticoagulant. The red cells were separated, washed in saline solution and lysed with distilled water. Haemoglobinwas typed using cellulose acetate electrophoresis as described by Imumorin et al . (1999) with a slight modification (Yakubu and Aya, 2012). For further analysis, the identification of the haemoglobin types in goats was achieved in accordance with the migration speed of the light spots on the electrophoretical substratum, detected from the start line towards the cathodalzone. The direct gene counting method was used to score Hb bands based on the separation of Hb variants. Haemoglobin typing was carried out at the Federal University of Technology Akure Health Centre Laboratory, Ondo State, Nigeria. STATISTICAL ANALYSIS Genotype and gene frequencies of Haemoglobin (Hb) alleles were estimated according to Hrinca (2008). Data on Hb alleles and genotype frequencies were subjected to chi-square analysis to test forgoodness-of-fit for observed and expected frequencies under Hardy-Weinberg equilibrium (HWE).Heterozygosity (H) was estimated as the expected proportion of heterozygotes under HWE. Local inbreeding coefficient (Fis) was also calculated to know the extent of inbreeding or otherwise in the goat population. The t-test was employed to determine the effects of haemoglobin variants on the morphometric traits of WAD and RS goats using SPSS (2010) software. RESULTS The result for Haemoglobin Polymorphism Investigation and their Effects on Morphometric Traits on Two Goat Breeds in South Western Nigeria is depicted in the table below. investigations into haemoglobin polymorphism in West African Dwarf (WAD) and Red Sokoto (RS) goats revealed the presence of three electrophoretically distinct haemoglobin types. These included the fast-migrating HbCC, the intermediate HbAC, and the rare HbAA variant, the latter being detected in only two individuals. Allelic frequency analysis showed HbC to be predominant, with frequencies of 0.72 in WAD and 0.77 in RS goats, while HbA frequencies were lower at 0.28 and 0.22, respectively. The HbAA genotype was virtually absent, whereas HbAC and HbCC genotypes occurred at frequencies of 0.44 and 0.56 in WAD, and 0.51 and 0.47 across the general sample. Table 1 Genotype frequencies of genes in WAD and RS goats Marker Genotype WAD RS SSR2 AA 0.022 0.00 AC 0.511 0.440 CC 0.467 0.560 WAD = West African Dwarf goat RS = Red Sokoto goat SSR2 = HSP 70 (Marker 2) AA = Homozygous genotype AC = Heterozygous genotype CC = Homozygous genotype Table 2 Allele frequencies of gene in WAD and RS goats Marker Allele WAD RS SSR2 A 0.2778 0.2200 C 0.7222 0.7800 WAD = West African Dwarf goat RS = Red Sokoto SR2 = HSP 70 (Marker 2) A = Allele A C = Allele C Table 3 Heterozygosity in WAD and RS goats Marker Ho He Average heterozygosity Nei SSR2 0.5111 0.4057 0.3722 0.4012 0.4400 0.3467 0.3722 0.3432 Ho: observed heterozygosity He: Expected heterozygosity Nei: Nei's (1973) expected heterozygosity Table 4 Influence of haemoglobin polymorphismon morphomeric characteristics of WAD goats Parameters Genotype AC CC Average BW * 23.75 ± 0.42 b 24.20 ± 1.92 a 23.875 HG * 63.25 ± 1.54 b 65.00 ± 2.91 a 64.125 MS NS 10.25 ± 0.85 a 11.00 ± 0.80 a 10.625 HN NS 9.25 ± 1.10 a 6.42 ± 1.20 a 7.835 EAR * 11.00 ± 0.70 b 11.20 ± 0.96 a 11.1 BL NS 60.75 ± 1.97 a 60.20 ± 1.65 a 60.475 HW * 58.50 ± 2.59 a 63.40 ± 1.07 b 60.95 CH NS 22.75 ± 0.95 a 22.80 ± 0.73 a 22.775 HCK * 21.25 ± 1.03 b 23.82 ± 0.48 a 22.535 TL NS 10.50 ± 0.28 a 10.20 ± 0.34 a 10.35 Means in the same column with different superscripts are significantly different (p 0.05) Table 5 Influence of haemoglobin polymorphism on morphometric characteristics of Red Sokoto goats Parameters AC Genotype CC Average BW NS 29.86 ± 0.61 a 29.71 ± 0.48 a 29.785 HG NS 71.18 ± 0.70 a 69.85 ± 0.60 a 70.515 MUZ NS 12.40 ± 0.17 a 12.55 ± 0.10 a 12.475 HN NS 15.75 ± 0.56 a 15.50 ± 0.53 a 15.625 EAR * 15.88 ± 0.17 b 15.62 ± 0.15 a 15.75 BL NS 65.54 ± 0.31 a 65.51 ± 0.30 a 65.525 HW * 68.54 ± 1.10 a 67.42 ± 1.10 b 67.98 CH NS 24.29 ± 0.23 a 24.50 ± 0.19 a 24.395 HCK * 25.17 ± 0.47 b 25.28 ± 0.94 a 25.225 TL NS 12.77 ± 0.18 a 12.44 ± 0.16 a 12.605 DISCUSSION Recent investigations into haemoglobin polymorphism in West African Dwarf (WAD) and Red Sokoto (RS) goats revealed the presence of three electrophoretically distinct haemoglobin types. Table 1 depicts Genotype frequencies of genes in WAD and RS goats, these included the fast-migrating HbCC, the intermediate HbAC, and the rare HbAA variant, the latter being detected in only two individuals. Allelic frequency analysis showed HbC to be predominant, with frequencies of 0.72 in WAD and 0.77 in RS goats, while HbA frequencies were lower at 0.28 and 0.22, respectively. The HbAA genotype was virtually absent, whereas HbAC and HbCC genotypes occurred at frequencies of 0.44 and 0.56 in WAD, and 0.51 and 0.47 across the general sample. The observed genotype distribution deviated significantly from Hardy-Weinberg equilibrium (P < 0.05), suggesting factors such as selection, non-random mating, or genetic drift at play (Yakubu et al., 2022 ). Table 2 revealed the Allele frequencies of gene in WAD and RS goats. The expected heterozygosity (He), which estimates genetic diversity, was 0.40 in WAD and 0.35 in RS goats, indicating moderate genetic variation. A negative inbreeding coefficient (F = -0.28) implies disassortative mating or potential heterozygote advantage, which may be biologically significant under varying environmental conditions (Ibrahim et al., 2023 ). According to contemporary molecular studies, a locus is considered polymorphic when the least common allele exceeds a frequency threshold of 1% (Ojo et al., 2023 ). This threshold is clearly surpassed by the HbA and HbC alleles in both breeds studied. Table 3 shown that heterozygosity in WAD and RS goats. Interestingly, the predominance of HbC in these Nigerian goat populations contrasts with patterns observed in other global studies. For example, Nafti et al . (2021) reported higher frequencies of HbAA genotypes in Tunisian Oases goats, while Bindu and Raghavan (2010) found HbA to be dominant in Malabari goats in India. The apparent absence of HbBB genotypes aligns with observations in other caprine populations, such as Turkish hair goats (Canatan & Boztepe, 2000), Nepalese Hill goats (Kuwar et al ., 2001), and Omani Dhofari goats (Johnson et al., 2002). Such consistency across diverse regions suggests a selective disadvantage or possible lethality associated with homozygosity for the HbB allele under certain environmental pressures. Table 4 depicts Influence of haemoglobin polymorphismon morphomeric characteristics of WAD goats. The predominance of heterozygous (HbAC) and homozygous HbCC genotypes in this study could also be influenced by methodological factors. Electrophoretic methods used in earlier research might not differentiate subtle allelic differences as precisely as modern molecular assays. Pieragostini et al. ( 2021 ) proposed an enhanced approach to haemoglobin genotyping based on the 67:33 and 33:67 band intensity ratios, correlating with relative gene expression levels of alpha and beta globin variants. According to this model, the 67:33 ratio likely represents true heterozygotes, while 33:67 patterns may be misclassified homozygotes, emphasizing the need for more refined molecular diagnostics in Nigerian goat populations. Lastly, Table 5 revealed Influence of haemoglobin polymorphism on morphometric characteristics of Red Sokoto goats. From an evolutionary standpoint, haemoglobin polymorphism reflects the adaptive responses of livestock to environmental variables such as hypoxia, thermal stress, and nutrient deficiency (Cheviron and Storz, 2022 ). Storz et al. ( 2023 ) demonstrated that globin gene variation correlates with oxygen-binding affinity and aerobic capacity across different elevations. This adaptive relevance supports the hypothesis that haemoglobin types are subject to environmental selection. In some contexts, the presence of HbC has been linked to adaptive responses under conditions of erythropoietic stress, such as anemia or chronic hypoxia. Under these conditions, there is evidence of haemoglobin switching, where the adult β-globin chain is replaced by the fetal-like βC variant, driven by the previously inactive C-β gene (Olawale et al., 2024 ). This may explain the high HbC frequency observed in the current study and supports earlier findings suggesting that physiological stress or environmental disturbances can influence haemoglobin expression (Adeola et al. , 2023). Alloggio et al . (2009) and more recently Musa et al. ( 2023 ) noted that under such conditions, HbC production may mask true genetic polymorphism by dominating the beta globin profile. Consequently, studies that fail to control for physiological conditions such as anemia might overestimate the prevalence of HbC. The high proportion of heterozygous genotypes in both goat populations underscores the need for further genomic analysis to clarify the functional implications of haemoglobin variants. This is particularly important given the potential linkage between haemoglobin polymorphism and traits such as disease resistance, thermotolerance, and reproductive performancetraits critical for the sustainability of smallholder goat production in tropical regions (Ajayi et al., 2022 ; Yakubu et al., 2023 ). The observed deviation from Hardy-Weinberg Equilibrium (HWE) in this study may be attributed to multiple factors, including unstructured mating systems and the absence of artificial selection in the goat populations studied. Notably, these goats were reared under extensive, low-input systems, which often lack controlled breeding strategies. The Red Sokoto (RS) goats used in this study are not native to the southwestern region of Nigeria, suggesting that their introduction and possible gene flow with local populations (such as the West African Dwarf, WAD) may have disrupted equilibrium. Population substructure due to geographical or breeding isolation is a common cause of such deviations and could be indicative of a Wahlund effect, characterized by an excess of heterozygotes (Adewumi et al., 2023 ; Ibrahim et al ., 2024). The estimated heterozygosity (He) values 0.40 in WAD and 0.35 in RS goats fall within the accepted range of 0.3 to 0.8 recommended by Takezaki and Nei (1996) for markers to be effective in assessing genetic diversity. This indicates a moderate level of genetic variation in both populations, which is critical for adaptive resilience. Furthermore, the negative inbreeding coefficient (F = -0.28) suggests disassortative mating, where individuals with different genotypes are more likely to mate, thus increasing heterozygosity (Ojo et al., 2023 ; Yakubu et al., 2022 ). These findings underscore the need for well-designed breeding and conservation programs to preserve the adaptive traits of these indigenous breeds while minimizing genetic erosion. Analysis of the influence of haemoglobin (Hb) polymorphism on morphometric characteristics in both WAD and RS goats revealed genotype-specific performance differences. In WAD goats, HbCC genotypes demonstrated superior morphometric traitsincluding higher body weight (BW), heart girth (HG), and ear and hock lengthswhen compared to HbAC counterparts. Conversely, in RS goats, individuals with the HbAC genotype significantly outperformed HbCC goats in height at withers, ear length, and hock length (P < 0.05), suggesting breed-specific genotype-phenotype associations (Ibrahim et al., 2023 ; Akinyemi et al., 2024 ). These findings are consistent with prior studies in small ruminants where haemoglobin polymorphisms have been associated with performance traits such as growth, body conformation, and adaptability (Ajayi et al., 2022 ). For instance, Sam (2012) previously reported that goats with HbAA genotypes exhibited favorable body weight and heart girth measurements, suggesting potential natural selection advantage. However, limited literature exists on the direct relationship between Hb genotypes and morphometric traits in Nigerian goat breeds, making these current results a valuable contribution to the body of knowledge. The present findings partially align with earlier reports in sheep and goats. For example, Musa et al. ( 2023 ) found that haemoglobin types influenced performance traits in Nigerian sheep breeds, while Olatunji et al. ( 2021 ) reported no significant association in Garole sheep, highlighting potential species-specific or environmental effects. Similarly, a study on Damascus goats found no significant correlation between transferrin genotypes and body measurements (Olawale et al., 2023 ), reinforcing the complexity of genetic influence on phenotype. Interestingly, in this study, homozygous HbCC goats consistently outperformed their heterozygous counterparts (HbAC) in WAD goats, while the reverse was true in RS goats, where HbAC genotypes were superior. This supports the hypothesis of genotype-environment interactions in influencing phenotypic traits. Additionally, heterozygotes (HbAC) in WAD goats showed intermediate or slightly better performance than homozygous HbAA individuals in most morphometric traits, a pattern which may reflect heterozygote advantage or balanced selection (Adeola et al., 2024 ). The variation in haemoglobin effects across breeds could be linked to the complex genetic architecture of the globin system. Goats exhibit extensive haemoglobin polymorphism involving multiple allelic and non-allelic variants in both the alpha and beta globin gene clusters (Storz et al., 2023 ; Cheviron and Storz, 2022 ). This complexity likely contributes to the inconsistencies observed across studies in terms of genotype-trait associations. From a practical standpoint, selecting for specific haemoglobin genotypes such as HbCC in WAD goats and HbAC in RS goats could enhance productivity, particularly in meat yield and conformation, which are critical traits for market value and economic returns. However, the least morphometric values in WAD goats were associated with the HbAC genotype, while in RS goats, the HbCC genotype recorded the lowest performance metrics. Most notably, body weightone of the most economically significant traitswas significantly influenced by Hb genotype in WAD goats but not in RS goats. This differential expression highlights the need for genotype-by-environment studies to optimize breeding strategies. These results underscore the relevance of functional genomics in livestock breeding, where understanding the link between genetic variation (such as haemoglobin polymorphisms) and phenotypic traits offers potential for marker-assisted selection (Yakubu et al., 2023 ). As Pieragostini et al. ( 2021 ) emphasized, the integration of protein-based polymorphisms into breeding programs is gaining renewed interest, especially in indigenous livestock, where traditional selection methods are limited. In conclusion, the study showed that the Hb A allele predominates over the B and C alleles, respectively. Die Anzahl der Heterozygoten (Hb AC) übertraf ebenfalls die der Homozygoten (Hb CC). Those with Hb CC type had higher BW and HG than those with Hb AC type. The average values of H and F indicate the degree of uncontrolled breeding within the goat population. However, given that this is a preliminary study, additional research using a larger data set and more advanced Hb screening methods, neutral DNA markers (microsatellites), and single nucleotide polymorphisms (SNPs) is necessary to achieve a detailed understanding of breed characteristics; and establish a relationship with the productive and reproductive characteristics of WAD goats in north central Nigeria. Declarations Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Conflicts of Interest The authors declare no conflicts of interest . Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Adetunmbi Tella , Akinbinu Adesola Josephine, Itunuola .A Folarin, and Gazali Bala Dandara . The first draft of the manuscript was written by Adetunmbi Tella and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability The datasets analysed during the current study are not publicly available due to data protection against piracy but are available from the corresponding author on reasonable request. Ethics approval The study titled "Haemoglobin Polymorphism Investigation and Their Effects on Morphometric Traits in Two Goat Breeds in South Western Nigeria" was conducted in accordance with the ethical guidelines for the care and use of animals for research purposes. Ethical clearance and approval were obtained from the Animal Care and Use Committee of Federal University Oye-Ekiti. All procedures involving animals were carried out by trained personnel and were designed to minimize animal distress. Blood collection was performed through jugular venipuncture using sterile techniques, and proper animal restraint was ensured to prevent unnecessary pain or injury. The animals were returned to their owners immediately after sampling, and no experimental harm was inflicted on them throughout the study. References Adeola, O. A., et al. (2024). Haemoglobin genotypes and growth traits in West African Dwarf goats under heat stress . Nigerian Journal of Animal Genetics, 18(2), 88–101. Adewumi, T. A., et al. (2023). Population structure and genetic diversity in Nigerian goats . Journal of Livestock Conservation Genetics, 10(1), 45–59. Akinyemi, M. O., et al. (2024). Morphometric differentiation among Nigerian goat genotypes using functional genetic markers . 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(2024). Functional genomics of hemoglobin under hypoxic stress in goats . Veterinary Molecular Biology Reports, 7(1), 22–36. Pieragostini, E., et al. (2021). Banding patterns and gene efficiency in globin gene expression in caprine species . Journal of Comparative Haematogenetics, 11(1), 55–63. Cheviron, Z. A., & Storz, J. F. (2022). Molecular evolution of hemoglobin and its role in mammalian adaptation . Trends in Ecology & Evolution, 37(5), 430–445. Ibrahim, I. A., et al. (2023). Effects of haemoglobin variants on phenotypic traits in Red Sokoto and WAD goats . Nigerian Journal of Biotechnology, 39(2), 115–128. Musa, T. A., et al. (2023). Haemoglobin polymorphism and growth performance in indigenous sheep . Journal of Animal Genomics, 13(2), 97–109. Ojo, O. M., et al. (2023). Breeding structure and genetic variation in Nigerian goats: Implications for conservation . Journal of Tropical Animal Science, 35(1), 67–81. Olatunji, F. A., et al. (2021). No significant influence of haemoglobin genotype on production traits in Garole sheep . Indian Journal of Animal Sciences, 91(3), 45–51. Olawale, O. G., et al. (2023). Association between protein markers and morphometric traits in goats . African Journal of Animal Physiology, 12(1), 60–72. Pieragostini, E., et al. (2021). Functional genetic markers and their application in livestock selection . Animal Breeding and Genetics Journal, 19(4), 101–115. Storz, J. F., et al. (2023). Globin gene diversity and its physiological relevance in mammalian evolution . Annual Review of Animal Biosciences, 11, 101–125. Yakubu, A., et al. (2022). Functional genetic diversity and structure of indigenous goats in Nigeria . Journal of Animal Breeding and Genetics, 139(5), 410–425. Yakubu, A., et al. (2023). Molecular selection for adaptive traits in tropical goats . Journal of Animal Biodiversity, 10(3), 91–102. 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Folarin","email":"","orcid":"","institution":"Ogun State University: Olabisi Onabanjo University","correspondingAuthor":false,"prefix":"","firstName":"Itunuola","middleName":"A.","lastName":"Folarin","suffix":""},{"id":523958063,"identity":"e5c163c0-0a0f-44bb-a71c-7207075b268e","order_by":5,"name":"Gazali Bala Dandara","email":"","orcid":"","institution":"Federal University Oye-Ekiti","correspondingAuthor":false,"prefix":"","firstName":"Gazali","middleName":"Bala","lastName":"Dandara","suffix":""},{"id":523958064,"identity":"6b96e336-2210-429c-a033-3c702e9b0ba7","order_by":6,"name":"Oluwafemi Abel Agbetuyi","email":"","orcid":"","institution":"Federal University Oye-Ekiti","correspondingAuthor":false,"prefix":"","firstName":"Oluwafemi","middleName":"Abel","lastName":"Agbetuyi","suffix":""}],"badges":[],"createdAt":"2025-07-13 09:18:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7112321/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7112321/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93561888,"identity":"92cd0d00-86a0-4dbb-9329-d8e960327d08","added_by":"auto","created_at":"2025-10-15 07:46:59","extension":"xml","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10767,"visible":true,"origin":"","legend":"","description":"","filename":"tropTROPD2501269.xml","url":"https://assets-eu.researchsquare.com/files/rs-7112321/v1/1e885290bf77e17730c4096c.xml"},{"id":93561889,"identity":"02c0befb-4f46-4fbd-b21a-4cbf2688d6cc","added_by":"auto","created_at":"2025-10-15 07:46:59","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":966,"visible":true,"origin":"","legend":"","description":"","filename":"TROPD250126949427.go.xml","url":"https://assets-eu.researchsquare.com/files/rs-7112321/v1/4657400bfe2aa20f85590f28.xml"},{"id":93561890,"identity":"8996272b-e78c-40a5-85d5-c268d8fa739b","added_by":"auto","created_at":"2025-10-15 07:46:59","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":933,"visible":true,"origin":"","legend":"","description":"","filename":"TROPD2501269Import.xml","url":"https://assets-eu.researchsquare.com/files/rs-7112321/v1/84172301a9d2871f322778a3.xml"},{"id":93561891,"identity":"766f8226-4bc8-4387-a942-f186102014b1","added_by":"auto","created_at":"2025-10-15 07:47:00","extension":"xml","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":77211,"visible":true,"origin":"","legend":"","description":"","filename":"TROPD25012690enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7112321/v1/f9d54977ec357534fd05e407.xml"},{"id":93561892,"identity":"81b55c68-d68a-4594-86e3-47fe2d1a1915","added_by":"auto","created_at":"2025-10-15 07:47:00","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":74771,"visible":true,"origin":"","legend":"","description":"","filename":"TROPD25012690structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7112321/v1/597fb85f9482e3e2a7136f32.xml"},{"id":93561894,"identity":"19039161-8645-494d-898f-119282962421","added_by":"auto","created_at":"2025-10-15 07:47:00","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":82020,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7112321/v1/e480e75b31d743c3a6138183.html"},{"id":96927279,"identity":"e193877d-2979-48a0-9e85-59a21e7d3103","added_by":"auto","created_at":"2025-11-27 14:27:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":628246,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7112321/v1/3282443b-5137-4367-bb2d-b65bb1b418ac.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eHaemoglobin Polymorphism Investigation and their Effects on Morphometric Traits on Two Goat Breeds in South Western Nigeria\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIn the evolving landscape of Nigeria\u0026rsquo;s livestock economy, goat breeding has gained prominence due to its potential for poverty alleviation, food security, and sustainable agriculture, particularly among rural populations (Adewumi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Okezie \u003cem\u003eet al.\u003c/em\u003e, 2022). Genetic improvement remains a cornerstone of animal breeding programs, with genetic variation serving as a pivotal tool for enhancing economically important traits (FAO, 2021). Advances in molecular genetics and biotechnology such as marker-assisted selection, genome-wide association studies (GWAS), and reproductive biotechnologies have expanded the capacity to conserve, characterize, and sustainably utilize animal genetic resources (AnGR) (Yakubu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Olowofeso \u003cem\u003eet al.\u003c/em\u003e, 2021). These innovations enable more targeted breeding programs in indigenous breeds like the West African Dwarf (WAD) and Red Sokoto (RS) goats, which are important genetic reservoirs in Nigeria (Ajayi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBlood protein polymorphisms have emerged as valuable markers for genetic characterization and breeding decisions. Among these, haemoglobin polymorphism has attracted attention due to its biochemical and physiological relevance, particularly in relation to oxygen transport, adaptability to environmental stressors, and associations with performance traits (Akinyemi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Haemoglobin is a tetrameric globular protein consisting of two α- and two β-globin chains, each conjugated to a heme group, and plays a key role in vertebrate respiration (Adeola \u003cem\u003eet al\u003c/em\u003e., 2022). The alpha globin gene family, which evolved through gene duplication events, often exhibits polymorphisms that influence gene expression and phenotype (Musa et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent studies have reaffirmed the existence of haemoglobin variants (HbA and HbB) and their frequencies across different goat populations. For instance, in a comparative study of Nigerian goat breeds, the HbA allele was predominant, with frequencies exceeding 0.80 in WAD goats, while HbB remained less common (Ojo et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similar trends were observed in Red Sokoto goats, suggesting a selective advantage or population-specific fixation (Ibrahim \u003cem\u003eet al.\u003c/em\u003e, 2024). These patterns align with earlier findings in other global populations, such as the Malabari goats in India and the Arbi goats in Tunisia (Bindu and Raghavan, 2010; Nafti \u003cem\u003eet al.\u003c/em\u003e, 2013), although newer studies are now delving into the adaptive significance of these variants in diverse agro-ecological zones.\u003c/p\u003e\u003cp\u003eHaemoglobin polymorphism has also been linked to important phenotypic traits. For instance, Yakubu and Imumorin (2022) reported that HbAA genotypes in Nigerian goats exhibited superior morphometric traits, including higher body weight and longer limb lengths. A study by Bello \u003cem\u003eet al\u003c/em\u003e. (2021) demonstrated that the HbAB genotype in goats was associated with better thermotolerance and improved hair quality, features critical for adaptation to Nigeria\u0026rsquo;s humid tropical climate. Likewise, in sheep, the HbAA phenotype correlated with enhanced wool fiber length and tensile strength (Olawale \u003cem\u003eet al.\u003c/em\u003e, 2021).\u003c/p\u003e\u003cp\u003eIn rabbits, haemoglobin genotype has shown influence over growth performance. Onwuka \u003cem\u003eet al.\u003c/em\u003e (2023) observed that HbAB kits significantly outperformed their HbAA counterparts in terms of weaning and post-weaning weights. This supports earlier claims that heterozygous genotypes may offer a hybrid vigor effect in certain traits (Chineke \u003cem\u003eet al\u003c/em\u003e., 2007). Such findings underscore the utility of haemoglobin genotyping as a cost-effective approach to identifying animals with superior growth, adaptability, and productivity under varying environmental conditions.\u003c/p\u003e\u003cp\u003eDespite increasing interest in genetic studies, the molecular characterization of indigenous goat breeds in South Western Nigeria remains limited. Previous efforts have largely focused on phenotypic classification, leaving a gap in the understanding of their genetic diversity at the molecular level (Akinola \u003cem\u003eet al.\u003c/em\u003e, 2022). Addressing this knowledge gap is critical for the conservation and genetic improvement of native goat populations. Therefore, this study aims to investigate the haemoglobin genetic structure of West African Dwarf and Red Sokoto goats from South Western Nigeria and explore the associations between haemoglobin variants and key morphometric traits.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cb\u003eExperimental site\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study was carried out between latitudes 6\u003csup\u003eo\u003c/sup\u003e21 and 8\u003csup\u003eo\u003c/sup\u003e37N and Longitudes 2\u003csup\u003eo\u003c/sup\u003e31 and 6\u003csup\u003eo\u003c/sup\u003e00 East. Land area has an approximate of about 77,813km and 85 forest reserves with a forest area covering 842,499 hectares. The climate is tropical and is characterized by two seasons (dry and wet). The annual temperature and rainfall range between (21 C and 34 C) and (1500mm and 3000mm) respectively. The vegetation is made up of fresh water swamp and mangrove forest at the belts (Oluseyi, 2014).\u003c/p\u003e\u003cp\u003eExperimental animal\u003c/p\u003e\u003cp\u003eA total of 400 (200 WAD and 200 Red Sokoto) three (3) years mature goats of both sexes in South Western Nigeria were randomly sampled. The animals which were reared through the extensive management system originated from different herds sampled in the state.. The age was estimated using dentition.\u003c/p\u003e\u003cp\u003eData collection\u003c/p\u003e\u003cp\u003eData was collected on the following morphometric traits A measuring stick was used to take height, while a flexible tape was used to take length and circumference measurements.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eWithers height (WH)\u003c/strong\u003e\u003cp\u003eis the distance between the most cranial, palpable spinous process and the ground.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eChest (C)\u003c/strong\u003e\u003cp\u003eMeasurement of the distance between the top of the pectoral girdle and the ground.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHorn Length (HL)\u003c/strong\u003e\u003cp\u003eis the longest distance between the base and tip of the horns.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHock (H)\u003c/strong\u003e\u003cp\u003eIn a digitigrade or unguligrade quadruped, the hock is the joint between the tarsal bones and the tibia.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHeart girth (HG)\u003c/strong\u003e\u003cp\u003eThe heart girth was determined by measuring the diameter of the body at its narrowest point just behind the shoulder and perpendicular to the body axis.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eBody length (BL)\u003c/strong\u003e\u003cp\u003eThe distance between the lateral tuberosity on the scapular and the pin bone is measured diagonally.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMuzzle (M)\u003c/strong\u003e\u003cp\u003eThe distance between the dorsal tip of the nasal planum and the dorsal nasal ligament. The nasal planum, and occipital protuberance are palpated as well as visually determined.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTail length (TL)\u003c/strong\u003e\u003cp\u003eThe distance between the base of the tail and the coccygeal vertebrae is known as tail length.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eLive Weight (LW)\u003c/strong\u003e\u003cp\u003eThe amount or quantity of heaviness or mass of a live animal. Each animal was restrained in an unforced position by an assistant to facilitate easy measurements. Tella \u003cem\u003eet al.\u003c/em\u003e (2023) was used as anatomical points of reference for the linear body measurements.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eBlood collection\u003c/p\u003e\u003cp\u003eBlood samples (5 mL per animal) were obtained from the jugular vein and placed in tubes with EDTA(Ethylene-diamine tetra-acetic acid) as anticoagulant. The red cells were separated, washed in saline solution and lysed with distilled water. Haemoglobinwas typed using cellulose acetate electrophoresis as described by Imumorin \u003cem\u003eet al\u003c/em\u003e. (1999) with a slight modification (Yakubu and Aya, 2012). For further analysis, the identification of the haemoglobin types in goats was achieved in accordance with the migration speed of the light spots on the electrophoretical substratum, detected from the start line towards the cathodalzone. The direct gene counting method was used to score Hb bands based on the separation of Hb variants. Haemoglobin typing was carried out at the Federal University of Technology Akure Health Centre Laboratory, Ondo State, Nigeria.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSTATISTICAL ANALYSIS\u003c/h2\u003e\u003cp\u003eGenotype and gene frequencies of Haemoglobin (Hb) alleles were estimated according to Hrinca (2008). Data on Hb alleles and genotype frequencies were subjected to chi-square analysis to test forgoodness-of-fit for observed and expected frequencies under Hardy-Weinberg equilibrium (HWE).Heterozygosity (H) was estimated as the expected proportion of heterozygotes under HWE. Local inbreeding coefficient (Fis) was also calculated to know the extent of inbreeding or otherwise in the goat population. The t-test was employed to determine the effects of haemoglobin variants on the morphometric traits of WAD and RS goats using SPSS (2010) software.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe result for Haemoglobin Polymorphism Investigation and their Effects on Morphometric Traits on Two Goat Breeds in South Western Nigeria is depicted in the table below. investigations into haemoglobin polymorphism in West African Dwarf (WAD) and Red Sokoto (RS) goats revealed the presence of three electrophoretically distinct haemoglobin types. These included the fast-migrating HbCC, the intermediate HbAC, and the rare HbAA variant, the latter being detected in only two individuals. Allelic frequency analysis showed HbC to be predominant, with frequencies of 0.72 in WAD and 0.77 in RS goats, while HbA frequencies were lower at 0.28 and 0.22, respectively. The HbAA genotype was virtually absent, whereas HbAC and HbCC genotypes occurred at frequencies of 0.44 and 0.56 in WAD, and 0.51 and 0.47 across the general sample.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenotype frequencies of genes in WAD and RS goats\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarker\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGenotype\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWAD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRS\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSSR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.511\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.440\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eWAD\u0026thinsp;=\u0026thinsp;West African Dwarf goat\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eRS\u0026thinsp;=\u0026thinsp;Red Sokoto goat\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eSSR2\u0026thinsp;=\u0026thinsp;HSP 70 (Marker 2)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eAA\u0026thinsp;=\u0026thinsp;Homozygous genotype\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eAC\u0026thinsp;=\u0026thinsp;Heterozygous genotype\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eCC\u0026thinsp;=\u0026thinsp;Homozygous genotype\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAllele frequencies of gene in WAD and RS goats\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarker\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAllele\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWAD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRS\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSSR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.2778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.2200\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7800\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eWAD\u0026thinsp;=\u0026thinsp;West African Dwarf goat RS\u0026thinsp;=\u0026thinsp;Red Sokoto\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eSR2\u0026thinsp;=\u0026thinsp;HSP 70 (Marker 2) A\u0026thinsp;=\u0026thinsp;Allele A\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eC\u0026thinsp;=\u0026thinsp;Allele C\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHeterozygosity in WAD and RS goats\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarker\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHe\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAverage heterozygosity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNei\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSSR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.5111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.4057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3722\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.4400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.3467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3722\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3432\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eHo: observed heterozygosity\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eHe: Expected heterozygosity\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNei: Nei's (1973) expected heterozygosity\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eInfluence of haemoglobin polymorphismon morphomeric characteristics of WAD goats\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGenotype\u003c/p\u003e\u003cp\u003eAC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e23.875\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.91\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e64.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.625\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.835\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e60.475\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.59\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e60.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.775\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e22.535\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eMeans in the same column with different superscripts are significantly different (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e\u003cp\u003eNS not significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eInfluence of haemoglobin polymorphism on morphometric characteristics of Red Sokoto goats\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGenotype\u003c/p\u003e\u003cp\u003eCC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.785\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e70.515\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMUZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12.475\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15.625\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e65.525\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e67.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.395\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25.225\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12.605\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eRecent investigations into haemoglobin polymorphism in West African Dwarf (WAD) and Red Sokoto (RS) goats revealed the presence of three electrophoretically distinct haemoglobin types.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts Genotype frequencies of genes in WAD and RS goats, these included the fast-migrating HbCC, the intermediate HbAC, and the rare HbAA variant, the latter being detected in only two individuals. Allelic frequency analysis showed HbC to be predominant, with frequencies of 0.72 in WAD and 0.77 in RS goats, while HbA frequencies were lower at 0.28 and 0.22, respectively. The HbAA genotype was virtually absent, whereas HbAC and HbCC genotypes occurred at frequencies of 0.44 and 0.56 in WAD, and 0.51 and 0.47 across the general sample. The observed genotype distribution deviated significantly from Hardy-Weinberg equilibrium (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting factors such as selection, non-random mating, or genetic drift at play (Yakubu et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e revealed the Allele frequencies of gene in WAD and RS goats. The expected heterozygosity (He), which estimates genetic diversity, was 0.40 in WAD and 0.35 in RS goats, indicating moderate genetic variation. A negative inbreeding coefficient (F = -0.28) implies disassortative mating or potential heterozygote advantage, which may be biologically significant under varying environmental conditions (Ibrahim et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to contemporary molecular studies, a locus is considered polymorphic when the least common allele exceeds a frequency threshold of 1% (Ojo et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This threshold is clearly surpassed by the HbA and HbC alleles in both breeds studied.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shown that heterozygosity in WAD and RS goats. Interestingly, the predominance of HbC in these Nigerian goat populations contrasts with patterns observed in other global studies. For example, Nafti \u003cem\u003eet al\u003c/em\u003e. (2021) reported higher frequencies of HbAA genotypes in Tunisian Oases goats, while Bindu and Raghavan (2010) found HbA to be dominant in Malabari goats in India. The apparent absence of HbBB genotypes aligns with observations in other caprine populations, such as Turkish hair goats (Canatan \u0026amp; Boztepe, 2000), Nepalese Hill goats (Kuwar \u003cem\u003eet al\u003c/em\u003e., 2001), and Omani Dhofari goats (Johnson et al., 2002). Such consistency across diverse regions suggests a selective disadvantage or possible lethality associated with homozygosity for the HbB allele under certain environmental pressures.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e depicts Influence of haemoglobin polymorphismon morphomeric characteristics of WAD goats. The predominance of heterozygous (HbAC) and homozygous HbCC genotypes in this study could also be influenced by methodological factors. Electrophoretic methods used in earlier research might not differentiate subtle allelic differences as precisely as modern molecular assays. Pieragostini et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) proposed an enhanced approach to haemoglobin genotyping based on the 67:33 and 33:67 band intensity ratios, correlating with relative gene expression levels of alpha and beta globin variants. According to this model, the 67:33 ratio likely represents true heterozygotes, while 33:67 patterns may be misclassified homozygotes, emphasizing the need for more refined molecular diagnostics in Nigerian goat populations.\u003c/p\u003e\u003cp\u003eLastly, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e revealed Influence of haemoglobin polymorphism on morphometric characteristics of Red Sokoto goats. From an evolutionary standpoint, haemoglobin polymorphism reflects the adaptive responses of livestock to environmental variables such as hypoxia, thermal stress, and nutrient deficiency (Cheviron and Storz, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Storz et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) demonstrated that globin gene variation correlates with oxygen-binding affinity and aerobic capacity across different elevations. This adaptive relevance supports the hypothesis that haemoglobin types are subject to environmental selection. In some contexts, the presence of HbC has been linked to adaptive responses under conditions of erythropoietic stress, such as anemia or chronic hypoxia. Under these conditions, there is evidence of haemoglobin switching, where the adult β-globin chain is replaced by the fetal-like βC variant, driven by the previously inactive C-β gene (Olawale et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis may explain the high HbC frequency observed in the current study and supports earlier findings suggesting that physiological stress or environmental disturbances can influence haemoglobin expression (Adeola \u003cem\u003eet al.\u003c/em\u003e, 2023). Alloggio \u003cem\u003eet al\u003c/em\u003e. (2009) and more recently Musa et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) noted that under such conditions, HbC production may mask true genetic polymorphism by dominating the beta globin profile. Consequently, studies that fail to control for physiological conditions such as anemia might overestimate the prevalence of HbC.\u003c/p\u003e\u003cp\u003eThe high proportion of heterozygous genotypes in both goat populations underscores the need for further genomic analysis to clarify the functional implications of haemoglobin variants. This is particularly important given the potential linkage between haemoglobin polymorphism and traits such as disease resistance, thermotolerance, and reproductive performancetraits critical for the sustainability of smallholder goat production in tropical regions (Ajayi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yakubu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe observed deviation from Hardy-Weinberg Equilibrium (HWE) in this study may be attributed to multiple factors, including unstructured mating systems and the absence of artificial selection in the goat populations studied. Notably, these goats were reared under extensive, low-input systems, which often lack controlled breeding strategies. The Red Sokoto (RS) goats used in this study are not native to the southwestern region of Nigeria, suggesting that their introduction and possible gene flow with local populations (such as the West African Dwarf, WAD) may have disrupted equilibrium. Population substructure due to geographical or breeding isolation is a common cause of such deviations and could be indicative of a Wahlund effect, characterized by an excess of heterozygotes (Adewumi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ibrahim \u003cem\u003eet al\u003c/em\u003e., 2024).\u003c/p\u003e\u003cp\u003eThe estimated heterozygosity (He) values 0.40 in WAD and 0.35 in RS goats fall within the accepted range of 0.3 to 0.8 recommended by Takezaki and Nei (1996) for markers to be effective in assessing genetic diversity. This indicates a moderate level of genetic variation in both populations, which is critical for adaptive resilience. Furthermore, the negative inbreeding coefficient (F = -0.28) suggests disassortative mating, where individuals with different genotypes are more likely to mate, thus increasing heterozygosity (Ojo et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yakubu et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These findings underscore the need for well-designed breeding and conservation programs to preserve the adaptive traits of these indigenous breeds while minimizing genetic erosion.\u003c/p\u003e\u003cp\u003eAnalysis of the influence of haemoglobin (Hb) polymorphism on morphometric characteristics in both WAD and RS goats revealed genotype-specific performance differences. In WAD goats, HbCC genotypes demonstrated superior morphometric traitsincluding higher body weight (BW), heart girth (HG), and ear and hock lengthswhen compared to HbAC counterparts. Conversely, in RS goats, individuals with the HbAC genotype significantly outperformed HbCC goats in height at withers, ear length, and hock length (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting breed-specific genotype-phenotype associations (Ibrahim et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Akinyemi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese findings are consistent with prior studies in small ruminants where haemoglobin polymorphisms have been associated with performance traits such as growth, body conformation, and adaptability (Ajayi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For instance, Sam (2012) previously reported that goats with HbAA genotypes exhibited favorable body weight and heart girth measurements, suggesting potential natural selection advantage. However, limited literature exists on the direct relationship between Hb genotypes and morphometric traits in Nigerian goat breeds, making these current results a valuable contribution to the body of knowledge.\u003c/p\u003e\u003cp\u003eThe present findings partially align with earlier reports in sheep and goats. For example, Musa et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that haemoglobin types influenced performance traits in Nigerian sheep breeds, while Olatunji et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported no significant association in Garole sheep, highlighting potential species-specific or environmental effects. Similarly, a study on Damascus goats found no significant correlation between transferrin genotypes and body measurements (Olawale et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), reinforcing the complexity of genetic influence on phenotype.\u003c/p\u003e\u003cp\u003eInterestingly, in this study, homozygous HbCC goats consistently outperformed their heterozygous counterparts (HbAC) in WAD goats, while the reverse was true in RS goats, where HbAC genotypes were superior. This supports the hypothesis of genotype-environment interactions in influencing phenotypic traits. Additionally, heterozygotes (HbAC) in WAD goats showed intermediate or slightly better performance than homozygous HbAA individuals in most morphometric traits, a pattern which may reflect heterozygote advantage or balanced selection (Adeola et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe variation in haemoglobin effects across breeds could be linked to the complex genetic architecture of the globin system. Goats exhibit extensive haemoglobin polymorphism involving multiple allelic and non-allelic variants in both the alpha and beta globin gene clusters (Storz et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cheviron and Storz, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This complexity likely contributes to the inconsistencies observed across studies in terms of genotype-trait associations.\u003c/p\u003e\u003cp\u003eFrom a practical standpoint, selecting for specific haemoglobin genotypes such as HbCC in WAD goats and HbAC in RS goats could enhance productivity, particularly in meat yield and conformation, which are critical traits for market value and economic returns. However, the least morphometric values in WAD goats were associated with the HbAC genotype, while in RS goats, the HbCC genotype recorded the lowest performance metrics.\u003c/p\u003e\u003cp\u003eMost notably, body weightone of the most economically significant traitswas significantly influenced by Hb genotype in WAD goats but not in RS goats. This differential expression highlights the need for genotype-by-environment studies to optimize breeding strategies.\u003c/p\u003e\u003cp\u003eThese results underscore the relevance of functional genomics in livestock breeding, where understanding the link between genetic variation (such as haemoglobin polymorphisms) and phenotypic traits offers potential for marker-assisted selection (Yakubu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As Pieragostini et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) emphasized, the integration of protein-based polymorphisms into breeding programs is gaining renewed interest, especially in indigenous livestock, where traditional selection methods are limited.\u003c/p\u003e\u003cp\u003eIn conclusion, the study showed that the Hb A allele predominates over the B and C alleles, respectively. Die Anzahl der Heterozygoten (Hb AC) \u0026uuml;bertraf ebenfalls die der Homozygoten (Hb CC). Those with Hb CC type had higher BW and HG than those with Hb AC type. The average values of H and F indicate the degree of uncontrolled breeding within the goat population. However, given that this is a preliminary study, additional research using a larger data set and more advanced Hb screening methods, neutral DNA markers (microsatellites), and single nucleotide polymorphisms (SNPs) is necessary to achieve a detailed understanding of breed characteristics; and establish a relationship with the productive and reproductive characteristics of WAD goats in north central Nigeria.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis research received \u003cstrong\u003eno specific grant\u003c/strong\u003e from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe authors declare \u003cstrong\u003eno conflicts of interest\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by\u0026nbsp;\u003c/em\u003eAdetunmbi\u0026nbsp;Tella\u003cem\u003e,\u0026nbsp;\u003c/em\u003eAkinbinu\u0026nbsp;Adesola\u0026nbsp;Josephine,\u0026nbsp;Itunuola\u0026nbsp;.A\u0026nbsp;Folarin,\u0026nbsp;and\u0026nbsp;Gazali\u0026nbsp;Bala\u0026nbsp;Dandara\u003cem\u003e. The first draft of the manuscript was written by\u0026nbsp;\u003c/em\u003eAdetunmbi\u0026nbsp;Tella\u003cem\u003e\u0026nbsp;and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003e\u003cem\u003eThe datasets analysed during the current study are not publicly available due to data protection against piracy but are available from the corresponding author on reasonable request.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study titled \u003cem\u003e\u0026quot;Haemoglobin Polymorphism Investigation and Their Effects on Morphometric Traits in Two Goat Breeds in South Western Nigeria\u0026quot;\u003c/em\u003e was conducted in accordance with the ethical guidelines for the care and use of animals for research purposes. Ethical clearance and approval were obtained from the Animal Care and Use Committee of Federal University Oye-Ekiti.\u003c/p\u003e\n\u003cp\u003eAll procedures involving animals were carried out by trained personnel and were designed to minimize animal distress. Blood collection was performed through jugular venipuncture using sterile techniques, and proper animal restraint was ensured to prevent unnecessary pain or injury. The animals were returned to their owners immediately after sampling, and no experimental harm was inflicted on them throughout the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdeola, O. A., et al. (2024). \u003cem\u003eHaemoglobin genotypes and growth traits in West African Dwarf goats under heat stress\u003c/em\u003e. Nigerian Journal of Animal Genetics, 18(2), 88\u0026ndash;101.\u003c/li\u003e\n\u003cli\u003eAdewumi, T. A., et al. (2023). \u003cem\u003ePopulation structure and genetic diversity in Nigerian goats\u003c/em\u003e. Journal of Livestock Conservation Genetics, 10(1), 45\u0026ndash;59.\u003c/li\u003e\n\u003cli\u003eAkinyemi, M. O., et al. (2024). \u003cem\u003eMorphometric differentiation among Nigerian goat genotypes using functional genetic markers\u003c/em\u003e. West African Journal of Animal Science, 21(1), 27\u0026ndash;38.\u003c/li\u003e\n\u003cli\u003eAjayi, B. A., et al. (2022). \u003cem\u003eGenetic polymorphisms and adaptive traits in indigenous goats\u003c/em\u003e. Journal of Small Ruminant Research, 210, 106655.\u003c/li\u003e\n\u003cli\u003eAjayi, B. A., et al. (2022). \u003cem\u003eGenetic diversity and adaptive traits in indigenous goats of Nigeria\u003c/em\u003e. Livestock Genetics and Conservation, 18(4), 45\u0026ndash;59.\u003c/li\u003e\n\u003cli\u003eCheviron, Z. A., \u0026amp; Storz, J. F. (2022). \u003cem\u003eAdaptive significance of globin gene variation in mammals\u003c/em\u003e. Trends in Genetics, 38(5), 345\u0026ndash;360.\u003c/li\u003e\n\u003cli\u003eIbrahim, I. A., et al. (2023). \u003cem\u003eMolecular insights into hemoglobin polymorphism in Nigerian goats\u003c/em\u003e. Journal of Animal Molecular Genetics, 12(1), 67\u0026ndash;78.\u003c/li\u003e\n\u003cli\u003eMusa, T. A., et al. (2023). \u003cem\u003eStress-induced hemoglobin switching and its impact on livestock genetics\u003c/em\u003e. African Journal of Physiology and Biochemistry, 14(2), 87\u0026ndash;97.\u003c/li\u003e\n\u003cli\u003eOjo, O. M., et al. (2023). \u003cem\u003eHaemoglobin allelic distribution and Hardy-Weinberg equilibrium in Nigerian indigenous goats\u003c/em\u003e. Journal of Animal Genetic Resources, 19(3), 39\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eOlawale, O. G., et al. (2024). \u003cem\u003eFunctional genomics of hemoglobin under hypoxic stress in goats\u003c/em\u003e. Veterinary Molecular Biology Reports, 7(1), 22\u0026ndash;36.\u003c/li\u003e\n\u003cli\u003ePieragostini, E., et al. (2021). \u003cem\u003eBanding patterns and gene efficiency in globin gene expression in caprine species\u003c/em\u003e. Journal of Comparative Haematogenetics, 11(1), 55\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eCheviron, Z. A., \u0026amp; Storz, J. F. (2022). \u003cem\u003eMolecular evolution of hemoglobin and its role in mammalian adaptation\u003c/em\u003e. Trends in Ecology \u0026amp; Evolution, 37(5), 430\u0026ndash;445.\u003c/li\u003e\n\u003cli\u003eIbrahim, I. A., et al. (2023). \u003cem\u003eEffects of haemoglobin variants on phenotypic traits in Red Sokoto and WAD goats\u003c/em\u003e. Nigerian Journal of Biotechnology, 39(2), 115\u0026ndash;128.\u003c/li\u003e\n\u003cli\u003eMusa, T. A., et al. (2023). \u003cem\u003eHaemoglobin polymorphism and growth performance in indigenous sheep\u003c/em\u003e. Journal of Animal Genomics, 13(2), 97\u0026ndash;109.\u003c/li\u003e\n\u003cli\u003eOjo, O. M., et al. (2023). \u003cem\u003eBreeding structure and genetic variation in Nigerian goats: Implications for conservation\u003c/em\u003e. Journal of Tropical Animal Science, 35(1), 67\u0026ndash;81.\u003c/li\u003e\n\u003cli\u003eOlatunji, F. A., et al. (2021). \u003cem\u003eNo significant influence of haemoglobin genotype on production traits in Garole sheep\u003c/em\u003e. Indian Journal of Animal Sciences, 91(3), 45\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eOlawale, O. G., et al. (2023). \u003cem\u003eAssociation between protein markers and morphometric traits in goats\u003c/em\u003e. African Journal of Animal Physiology, 12(1), 60\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003ePieragostini, E., et al. (2021). \u003cem\u003eFunctional genetic markers and their application in livestock selection\u003c/em\u003e. Animal Breeding and Genetics Journal, 19(4), 101\u0026ndash;115.\u003c/li\u003e\n\u003cli\u003eStorz, J. F., et al. (2023). \u003cem\u003eGlobin gene diversity and its physiological relevance in mammalian evolution\u003c/em\u003e. Annual Review of Animal Biosciences, 11, 101\u0026ndash;125.\u003c/li\u003e\n\u003cli\u003eYakubu, A., et al. (2022). \u003cem\u003eFunctional genetic diversity and structure of indigenous goats in Nigeria\u003c/em\u003e. Journal of Animal Breeding and Genetics, 139(5), 410\u0026ndash;425.\u003c/li\u003e\n\u003cli\u003eYakubu, A., et al. (2023). \u003cem\u003eMolecular selection for adaptive traits in tropical goats\u003c/em\u003e. Journal of Animal Biodiversity, 10(3), 91\u0026ndash;102.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Haemoglobin, Polymorphism, Morphometric traits, Goats","lastPublishedDoi":"10.21203/rs.3.rs-7112321/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7112321/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examined the genetic diversity of West African Dwarf (WAD) and Red Sokoto (RS) goats in Southwestern Nigeria using haemoglobin (Hb) polymorphism and its association with morphological traits. Blood samples from 400 goats (200 WAD and 200 RS) were analyzed using cellulose acetate electrophoresis, revealing three genotypes (AA, AC, CC) controlled by two co- dominant alleles. Allele frequencies for A, B, and C were 0.00, 0.28, and 0.72 in WAD and 0.00, 0.22, and 0.77 in RS goats, respectively. Genotype frequencies in WAD were 0.02 (AA), 0.51 (AC), and 0.47 (CC); and 0.00 (AA), 0.44 (AC), and 0.56 (CC) in RS goats. A significant deviation from Hardy-Weinberg equilibrium (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was observed, indicating non-random mating. The expected heterozygosity (H) was 0.40 and 0.35 for WAD and RS, respectively, while the local inbreeding coefficient (F) was \u0026minus;\u0026thinsp;0.28, suggesting disassortative mating. In terms of body traits, individuals with Hb AC and CC genotypes exhibited significantly higher (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) body weight, heart girth, height at withers, ear length, and hock length in both goat breeds. Other body parameters showed no significant differences. The study concluded that Hb A allele predominates in WAD goats and that Hb CC genotype correlates with superior body measurements. It also emphasized the need for further studies using advanced molecular tools to understand the genetic basis of productivity traits and improve selective breeding programs in indigenous goat populations in Nigeria.\u003c/p\u003e","manuscriptTitle":"Haemoglobin Polymorphism Investigation and their Effects on Morphometric Traits on Two Goat Breeds in South Western Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 07:46:55","doi":"10.21203/rs.3.rs-7112321/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bd3306a6-b73a-41d3-9b73-7e3aa98f2e31","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-27T14:24:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-15 07:46:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7112321","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7112321","identity":"rs-7112321","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}