Environmentally independent histological markers of wool quality: a comparative study of Gentile di Puglia and Sarda breeds

Wool quality plays a role in determining the economic value of sheep breeds, amid the growing global demand for natural and sustainable material. This quality depends on both genetic and non-genetic factors, complicating breed evaluation. Among the most valued qualities is the fine wool produced by Merino and Merino-derived breeds. This study aims to identify parameters measured under controlled environmental conditions to assess the degree of merinization within flocks, meaning the extent to which a breed exhibits morphological and histological traits typical of Merino sheep. The ancient Italian sheep breed, Gentile di Puglia, derived from Merino, was compared with the non-merinized Sarda breed. Our results demonstrate that follicular structure is a key indicator for assessing merinization, under standardized environmental conditions and across different age groups. Gentile di Puglia sheep exhibited significantly higher secondary follicle density and secondary-to-primary follicle ratio (S/P = 8,96 vs 2,29) compared to the Sarda breed, indicating a finer wool structure. The density of sebaceous glands was significantly higher in the adult Gentile di Puglia, and no significant differences in gland area were found between breeds. These results highlight the importance of sebaceous glands in lanolin production and provide objective criteria for evaluating wool quality. This supports the promotion of the Gentile di Puglia breed for sustainable wool production. These results provide a novel phenotypic characterization at the histological level, that could guide future genomic studies aimed at identifying the genes responsible for these traits, relevant for the conservation and sustainable use of these local breeds. These findings not only provide a reliable histological basis for assessing wool quality but also offer practical markers that can inform selective breeding programs aimed at enhancing merino-like traits in local sheep populations.

1 Introduction

The global demand for natural and sustainable materials has reignited interest in wool production, particularly for fine wool, which is highly valued for its flexibility, breathability, and recyclability. Wool’s quality is shaped by various genetic and environmental factors, such as breed, diet, and climate conditions, making breed evaluation complex and often subject to environmental bias (Champion and Robards, 2000; Khan et al., 2012; Kijas et al., 2012). Evaluating wool quality based on parameters influenced by external factors, such as diet and pasture conditions, can lead to unreliable assessments of the breed’s true potential (Yeates et al., 1975). Therefore, identifying histological markers independent of environmental conditions is essential for an accurate and objective assessment of wool quality. Wool quality is predominantly determined by the density and structure of hair follicles, which are classified as primary and secondary. Primary follicles typically produce coarse wool, while secondary follicles are responsible for finer wool (Li et al., 2020). The relative density of these follicle types, referred to as the secondary-to-primary follicle ratio (S/P), is a key determinant of wool fineness (Lv et al., 2016). Primary follicles are characterized by the presence of large sebaceous glands, a retractor muscle attached to the outer root sheath just below the sebaceous gland and sweat glands.

Wool follicles develop in overlapping waves during foetal life (Moore et al., 1998). Primary follicles begin to form around the 70th day of gestation (Lv et al., 2020) and secondary follicles emerge at about day 85 of gestation, forming a distinct cluster in the skin with the primary follicles. By day 105, derived secondary follicles begin to appear as branches, so the ratio of secondary to primary follicles could be established (Lv et al., 2020). This branching can be extensive and determines the final density of the follicular population (Rogers, 2006). After birth, the histological characteristics of follicles are not influenced by exogenous factors, only by their productive activity. This makes them an interesting parameter for evaluating sheep breeds, as they provide an indication that is not influenced by environmental conditions (Lyne, 1961; Edwards et al., 1996). Recent advances in phenomics–genomics integration highlight that histological traits, such as follicle density and glandular structures, provide more precise indicators of genetic potential than fibre-level metrics alone, which are often influenced by environmental conditions (Liang et al., 2023). By capturing intrinsic morphological features established during foetal development, these traits allow for more accurate interpretation of breed-specific genetic differences, enabling robust selection strategies and assessment of Merino-derived characteristics.

Another important characteristic, economically relevant in wool production, is lanolin, a fat secreted by the sebaceous glands that coat and softens the wool fibre, that protects it from external agents (Sengupta and Behera, 2014). Over the past decade, lanolin has become increasingly important economically, with a significant increase in its use in cosmetic, medical, and industrial applications (Sengupta and Behera, 2014). Lanolin production varies across breeds making this characteristic a distinctive and valuable factor. The Merino breed is renowned for its fine wool and has historically been used in crossbreeding programs to improve the quality of wool in local breeds across Europe and beyond (Ciani et al., 2015; Al-Atiyat et al., 2016). This process, known as ‘Merinization’, involves selecting and diffusing morphological and histological traits typical of Merino sheep, such as finer fibre diameter. It has had a significant influence on sheep populations around the world (Granero et al., 2022).

The Gentile di Puglia is an ancient Italian sheep breed, historically distinguished for its fine wool. Romans used these animals to improve Iberian wool production as reported from several roman authors (Ryder, 1983). The Spanish Merino breed was highly valued for its fine, soft wool and its adaptability to the Mediterranean climate, a result of centuries of selective breeding in Spain (Anaya et al., 2024). Over time, the breed shifted towards meat and milk production, but recent interest in sustainable, local materials has revived its significance for wool production. The Gentile di Puglia remains an important genetic resource, particularly for fine wool production and sustainable agricultural practices in Italy (Ciani et al., 2020). The Sarda sheep is a hardy and versatile breed from the island of Sardinia, Italy, primarily known for its high milk production, which is used in the production of the famous Pecorino Sardo cheese. Adapted to the rugged Sardinian terrain and Mediterranean climate, the Sarda sheep excels in extensive farming systems, making it an important breed for both dairy and meat production. Unlike Merino-derived breeds, the Sarda produces coarser wool, which is less commercially valuable but well-suited for traditional textile crafts. The breed’s resilience and adaptability have contributed to its widespread use in Mediterranean regions (Serranito et al., 2021). From a demographic and conservation perspective, Gentile di Puglia (GdP) is an autochthonous Merino-derived breed with a very small current census: the most recent official data report about 3,739 registered animals in Italy (3,499 females and 240 males), and GdP is included among ovine breeds threatened by genetic erosion and extinction risk and targeted by specific conservation measures (Regione Puglia, 2022; Temerario et al., 2023). In contrast, the Sarda is the most widespread Italian dairy sheep breed: Sarda sheep account for about 80% of Italian dairy sheep and 43% of the national ovine stock and are not currently classified as at risk (Gaspa et al., 2024). The present comparison therefore contrasts a numerically limited, conservation-priority Merino-derived population with a numerically dominant, non-Merino dairy breed that plays a central role in the Italian sheep sector.

Despite the extensive literature available on Merino breeds, many studies have overlooked the evaluation of local sheep populations or failed to identify wool quality traits independent of environmental factors in Merino-derived breeds (McGregor et al., 2016; Rochus et al., 2018; Yaman et al., 2025; Megdiche et al., 2019).

This study aims to fill this gap by comparing the histological characteristics of two Italian breeds: the Merino-derived Gentile di Puglia and the non-Merino breed Sarda. The objective is to identify wool quality parameters evaluated under standardized environmental and seasonal conditions, providing a reliable method for assessing wool quality across different flocks. In particular, this study explores the secondary-to-primary follicle ratio and glandular structures, which could serve as objective indicators of the degree of Merinization and wool quality. Combining phenotypic information with genomic data is a promising way of discovering the genetic basis of complex traits related to fibre development and adaptation (Dzomba et al., 2020; Kalds et al., 2022; Liang et al., 2023).

2 Material and methods

2.1 Ethical statement

All procedures involving animals were conducted in compliance with national and institutional guidelines. Tissue samples were collected post-mortem from animals slaughtered for human consumption, and no animals were specifically euthanized for the purposes of this study. Therefore, ethical approval was not required.

2.2 Animal collection and sample preservation

To standardize environmental effects, all samples were collected from animals reared in the same commercial flock and managed under identical housing, feeding and health-care conditions. Animals were kept under uniform semi-intensive husbandry, with group housing, outdoor access and a standardized feeding regimen based on forage with supplemental concentrate according to physiological stage. All sampled animals (adults and lambs) were females. Adult ewes (4 years of age, with no close kinship ties according to flock records) were sampled in February (late winter), whereas lambs were sampled at approximately 60 days of age in December (early winter). In this production system, adult males are few and generally retained as breeding rams rather than sent to slaughter; consequently, adult males were not available for sampling. Given the high longevity of these sheep and the limited number of adult animals slaughtered at any given time, it was not possible to further increase the adult sample size.

Ten adult Gentile di Puglia (GdP-A) ewes and ten GdP lambs (GdP-L), and ten adult Sarda ewes (SA-A) and ten Sarda lambs (SA-L) were selected. All adult ewes were in their second or third parity, and all lambs were approximately 60 days old. Skin tissue samples were collected at a commercial slaughterhouse from animals legally slaughtered for human consumption. Biopsies were taken from the dorsal region near the caudal corner of the scapula. Each tissue sample was cut into 1 cm × 1 cm pieces, immediately immersed in 10% neutral buffered formalin and kept at room temperature for 72 h. Samples were then trimmed and fixed for a further 48 h. This procedure preserved the morphological and histological integrity of the tissues and prevented cellular degradation over time. After fixation, samples were processed for histological examination as described below.

2.3 Histological analysis

The fixed samples were dehydrated and embedded in paraffin to prepare them for histological examination. To differentiate between the different follicle types, sections were cut until the sebaceous glands were reached. Histological serial sections, each 5 µm thick, were obtained using a microtome, mounted on microscope slides, and stained. Staining was performed using Harris’s Hematoxylin and Eosin (H&E) (Bio-Optica), Periodic acid Schiff (P.A.S.) (Bio-Optica), and Trichrome Van Gieson (Bio- Optica), following the standard protocol. In particular, the samples were exposed to Hematoxylin for 10 min, Eosin 20 sec; to Periodic acid solution for 10 min, Shiff reagent 40 min, Mayer’s Hemalum 3 min; to Weigert’s iron haematoxylin for 20 min, Van Gieson’s Picrofuchsine 10 sec. For quantitative analysis, the density (number per area in mm²) of primary (P) and secondary (S) follicles, the ratio of secondary to primary follicles, named as S/P ratio, and the diameter of the two types of follicles, as well as the density and area of sebaceous (SE) glands, were assessed using a Leica DMRBE microscope. Image processing and measurements were conducted with the Leica Application Suite X program in conjunction with ImageJ software (Schneider et al., 2012). Five random areas were selected from each slide for analysis. Follicle density and diameter were measured at 10X magnification, gland density and area were quantified at the same magnification. The spatial distribution of follicles was evaluated at 5X magnification. The distribution of primary and secondary follicles was evaluated measuring the distance between the follicle centre and the X and Y axes of the analysed images. To ensure data reliability, a subset of samples was recounted by the same observer at different times. To validate manual counts, two independent observers performed the measurements in randomly selected sections. Prior to data collection, observer calibration was carried out by jointly examining representative sections and standardizing the counting criteria, ensuring consistency and repeatability across all measurements.

2.4 Statistical analysis of follicular density

Follicle density was analysed using a repeated-measures Gaussian mixed model including the fixed effects of Breed (Gentile di Puglia, Sarda), age class (Adult, Lamb), follicle Type (Primary, Secondary), and all two-way and three-way interactions. Animal was included as a random intercept to account for repeated measurements within individuals. A compound-symmetry correlation structure was specified to model within-animal dependence, and a heterogeneous residual variance by follicle Type was incorporated following AIC-based model comparison.

The full mathematical formulation of the model, including fixed effects, random-effects structure, correlation structure, and heterogeneous residual variances, is reported in Supplementary Figure 1 (Supplementary Figure S1). Model diagnostics were performed using graphical inspections of residuals vs. fitted values, Q–Q plots of standardized residuals, and residual distributions by Breed, age class, and follicle Type. All diagnostic plots, ANOVA tables, and Sidak-adjusted post-hoc comparisons are summarized in Supplementary Figure S1.

2.5 Statistical analysis of secondary and primary follicular ratio

The S/P follicle ratio was analysed using a repeated-measures Gaussian mixed model including the fixed effects of Breed, age class, and their interaction, and a random intercept for animal to account for repeated measurements within individuals. Residuals were modelled using a compound-symmetry correlation structure within animals and a heterogeneous residual variance by Breed, as supported by model comparison (ΔAIC = 53.35). The full model formulation, including the mathematical expression of the random-effects structure and heterogeneous variances, is presented in Supplementary Figure S1.

2.6 Statistical analysis of follicles diameter

The hierarchical mixed model for fibre diameter included the fixed effects of Breed (two levels: Gentile di Puglia, Sarda), age class (two levels: Adult, Lamb), follicle Type (two levels: Primary, Secondary), and all two- and three-way interactions. The model was fitted using the lme function (package nlme) in R (v. 4.4.3), specifying animal as a random intercept to account for repeated measurements within individuals. A compound-symmetry correlation structure was used to model intra-animal dependence, and a heterogeneous residual variance structure across follicle Types was included to account for type-specific differences in residual variability. Model selection was based on the Akaike Information Criterion (AIC), and the model including the heterogeneous variance structure showed a substantially better fit than the homogeneous-variance model (ΔAIC = 305.3). Model assumptions were evaluated graphically using residual-versus-fitted plots and Q–Q plots, which indicated adequate normality, appropriate variance modelling, and no patterns suggesting lack of fit. Overall, these diagnostics supported the suitability of the hierarchical Gaussian mixed model.

2.7 Statistical analysis of spatial distribution follicles

We evaluated the spatial arrangement of primary and secondary follicles to determine whether there was repulsion or attraction between them in GdP and SA breeds, considering both adult and lamb stages. Specifically, we analysed the cumulative inter-type of spatial distribution using the Kcross function from the spatstat package (Baddeley et al., 2015) in R. In this exploratory analysis, Ripley’s K function was used to summarize inter-point dependence and clustering. For instance, the estimated K function was compared against its expected value under a completely random process (Poisson). Deviations between the empirical and theoretical K curves indicate either spatial clustering (if K is higher than expected) or spatial regularity (if K is lower than expected). The resulting plots display the K function across a range of distances, along with simulation-based envelopes. If the observed K function deviates beyond the simulated envelopes, the null hypothesis of Complete Spatial Randomness is rejected, suggesting significant spatial structure. Furthermore, the observed spatial patterns are consistent across individual animals, indicating that the relationship between primary and secondary follicles follows a stable and reproducible arrangement within each group analysed.

2.8 Statistical analysis of glands density

The hierarchical mixed model for sebaceous gland density included the fixed effects of Breed (two levels: Gentile di Puglia, Sarda), age class (two levels: Adult, Lamb), and their interaction. The model was fitted using the lme function (package nlme) in R (v. 4.4.3), specifying animal as a random intercept to account for repeated measurements within individuals. A compound-symmetry correlation structure was used to model intra-animal dependence, and a heterogeneous residual variance structure across Breed was included, as this specification substantially improved model fit over the homogeneous-variance model (ΔAIC = 40.8). Model assumptions were evaluated graphically using residual-versus-fitted plots and Q–Q plots. The diagnostics showed no indication of departures from normality or patterns suggesting inadequate variance modelling.

2.9 Statistical analysis of glands area

Sebaceous gland area was analysed using repeated-measures Gaussian mixed model fitted to the log-transformed response, due to the strongly right-skewed distribution of the raw measurements. The fixed-effects structure included Breed (Gentile di Puglia, Sarda), age class (Adult, Lamb), and their interaction. Animal was included as a random intercept to account for repeated measurements within individuals, and a compound-symmetry correlation structure was specified to model within-animal dependence. Model selection based on the Akaike Information Criterion (AIC) supported the use of a heterogeneous residual variance structure by Breed (varIdent), which was therefore incorporated into the final model. The full mathematical specification of the model, including fixed and random effects, correlation structure, and variance heterogeneity, is provided in Supplementary Figure S1. Model assumptions were evaluated using graphical diagnostics, including Q–Q plots of standardized residuals, residuals versus fitted values, and residual distributions by Breed and age class. All diagnostics, together with the ANOVA table for fixed effects and the estimated marginal means (back transformed to the original scale and presented with 95% confidence intervals), are summarised in Supplementary Figure S1.

3 Results

3.1 Analysis of follicles

Analysis revealed significant differences in secondary follicle density and the ratio of secondary to primary follicles between the breeds studied, highlighting the unique characteristics of each breed. Primary follicles were identified by the presence of an apocrine sweat gland duct, the arrector muscle and sebaceous glands, whereas secondary follicle groups were identified by the presence of sebaceous glands only (Figure 1).

Figure 1

Figure 1. Histological features of skin from an adult Gentile di Puglia (GdP A) sheep. On the left, a primary follicle (black arrow) is shown with the sweat gland duct (arrowhead), arrector pili muscle (red arrow), and sebaceous gland (asterisk) clearly visible. On the right, a characteristic cluster of secondary follicles (arrowheads), each with associated sebaceous glands (asterisks), is marked. P.A.S. stain, 20x magnification. Scale bar: 50 µm.

Follicle density, expressed as number of follicles per mm² (Figure 2A), showed highly significant effects of Breed (F_1,123 = 110.46, p < 0.0001), follicle Type (F_1,123 = 686.14, p < 0.0001), and the Breed × Type interaction (F_1,123 = 227.31, p < 0.0001). Age and all remaining interaction terms were not significant (p > 0.05). Estimated marginal means revealed that secondary follicles were consistently denser than primary follicles in both breeds. Secondary follicle density reached 58.7 ± 2.0 follicles/mm² in Gentile di Puglia and 19.1 ± 3.7 follicles/mm² in Sarda, whereas primary follicle density remained low and comparable between breeds (Gentile di Puglia: 7.0 ± 0.46; Sarda: 8.5 ± 0.81). Full ANOVA results and post-hoc contrasts are reported in Supplementary Figure S1.

Figure 2

Figure 2. (A) Adjusted mean follicle density (follicles/mm²) for primary and secondary follicles in Gentile di Puglia (grey) and Sarda (black) sheep. Values represent estimated marginal means from a repeated-measures Gaussian mixed model including the fixed effects of Breed, Age class, and follicle Type, and a random intercept for Animal. Secondary follicles were significantly denser than primary follicles in both breeds, and Gentile di Puglia showed a markedly higher secondary follicle density than Sarda (Breed × Type, p < 0.0001). Different letters indicate Sidak-corrected pairwise differences. (B). Adjusted mean follicle diameter (µm) of primary (P) and secondary (S) follicles in adult (A) and lamb (L) sheep from both breeds, based on the same mixed-model framework. Primary follicles were consistently larger than secondary follicles, with diameter varying across breeds and age classes. Different letters denote significant Sidak-adjusted comparisons.

Estimated marginal means showed that Gentile di Puglia sheep had a markedly higher S/P ratio (8.96 ± 0.37) than Sarda (2.29 ± 0.31), with no age-related differences within breeds. The mixed-model analysis revealed a strong effect of Breed (F_1,123 = 251.72, p < 0.0001), whereas neither age (p = 0.62) nor the Breed × Age interaction (p = 0.65) was significant. The complete ANOVA table and Sidak-adjusted comparisons are presented in Supplementary Figure S1.

For what concerns the medium average diameter of follicles (Figure 2B), the model revealed that fibre diameter was significantly affected by Breed (F_1,123 = 58.59, p < 0.0001), Age (F_1,123 = 11.52, p = 0.0025), follicle Type (_1,3221 = 2432.44, p < 0.0001), and multiple interactions. The three-way Breed × Age × Type interaction was highly significant (_1,3221 = 23.90, p < 0.0001), indicating that differences between primary and secondary follicles varied across Breeds and age classes. In Gentile di Puglia, primary follicles were substantially larger in lambs (48.1 ± 1.1 µm) than in adults (35.8 ± 1.1 µm), whereas secondary follicles showed no significant age-related differences (lambs: 30.4 ± 1.0 µm; adults: 26.2 ± 0.86 µm). In Sarda, the primary follicles showed larger overall diameters (adults: 56.2 ± 1.7 µm; lambs: 70.1 ± 3.7 µm) compared to those in Gentile di Puglia, and there were no significant differences in size between the two age groups. Secondary follicles were smaller and relatively stable (adult: 34.8 ± 1.7 µm; lamb: 28.1 ± 3.4 µm). Across Breeds, Sarda sheep had consistently larger primary follicles than Gentile di Puglia, while Breed differences in secondary follicles emerged only in adults. Full contrasts are provided in Supplementary Figure S1.

Observation of the spatial distribution of skin follicles at a scale greater than 100 µm shows that follicles tend to form clusters. In the GdP breed, these clusters consist of 1 or 2 primary follicles, each accompanied by its own erector muscle, sweat duct and sebaceous gland, together with several secondary follicles with varying concentrations of sebaceous glands. This is observed in both GdP adults and lambs. A similar but less constant distribution was also observed in the SA lamb, whereas in the adult the primary follicles appeared to be arranged in a linear fashion, showing an orderly and uniform pattern (Figure 3).

Figure 3

Figure 3. Representative skin sections from adult and lamb sheep of the Gentile di Puglia (GdP A, GdP L), and Sarda (SA A, SA L) breeds, illustrating the distribution patterns of primary and secondary follicles. Observe the differences in follicle density, spatial distribution and cluster organisation. H&E staining, 5x magnification. Scale bar: 100 µm.

3.2 Analysis of glands

Sebaceous glands associated with both primary and secondary follicles were included in the evaluation (Figure 4). Estimated marginal means showed that adult Gentile di Puglia sheep had a markedly higher sebaceous gland density (90.9 ± 7.4 glands/mm²) than all other groups (p < 0.05). The remaining Breed × Age combinations displayed comparably low densities: Sarda adults (5.6 ± 1.6), Sarda lambs (6.4 ± 2.5), and Gentile lambs (17.7 ± 7.6) (Figure 5). Breed had a highly significant effect (F_1,24 = 80.31, p < 0.0001), and a very strong Breed × Age interaction was detected (F_1,24 = 45.05, p < 0.0001). The main effect of Age alone was not significant (p = 0.115). These results confirm that the interaction was driven entirely by the sharp increase observed in adult Gentile individuals.

Figure 4

Figure 4. Skin section from a Gentile di Puglia adult (GdPA) sheep illustrating the distribution of glands: (A) Sebaceous glands (arrows) surrounding a primary follicle; (B) Sebaceous glands (arrows) associated with a cluster of secondary follicles; (C) Sweat glands (asterisks). Van Gieson’s stain, 40x magnification. Scale bar: 25 µm.

Figure 5

Figure 5. Adjusted mean sebaceous gland density (n/mm²) in adult and lamb sheep of the Gentile di Puglia and Sarda breeds. Values represent estimated marginal means obtained from the Gaussian mixed model described in the Methods. A pronounced increase in sebaceous gland density was observed only in adult Gentile di Puglia sheep, whereas all other groups showed similarly low values (Breed effect, p < 0.0001). Different letters indicate significant Sidak-adjusted pairwise differences.

The estimated marginal means for sebaceous gland area were: GdP A = 4688 µm² (CI95%: 3945–5570), GdP L = 5939 µm² (5047–6990), SA A = 5594 µm² (4594–6812), and SA L = 5497 µm² (4078–7411). These values did not differ significantly, as none of the fixed effects were significant: Breed (p = 0.65), Age (p = 0.11), or their interaction (p = 0.23). These results indicate that sebaceous gland area was stable across Breeds and age classes. Full EMMs and CIs are provided in Supplementary Figure S1.

4 Discussion

4.1 Wool production

Despite the continuous development of new synthetic fibres, wool production remains an economically significant activity with high value in terms of environmental sustainability. For this reason, many countries continue to assess the quality of wool produced by different sheep breeds, often in the context of genetic improvement programs aimed at improving these characteristics. The wool production cycles in hair follicles are influenced by seasonality (Ansari-Renani et al., 2011). In addition, wool quality is also dependent on animal maintenance, which can introduce variability unrelated to the genetic potential of breeds and affect the reliability of wool-based evaluations. Strong evidence linking the presence of wool and follicle structure to environmental factors is provided by the Pelibuey breed, a woolly and hairless sheep found mainly in tropical regions and bred primarily for its high-quality meat (Gutiérrez et al., 2005). To provide a comparative context, we included histological images of the hairless Pelibuey sheep breed in Supplementary Figure S2 (Supplementary Figure S2) of the supplemental materials. These images highlight the stark differences in follicle density and structure compared to the wool-producing Gentile di Puglia and Sarda sheep breeds, further emphasizing the environmentally influenced spectrum of follicle development.

4.2 Histological traits as indicators of merinization

The aim of this study was to evaluate histological parameters measured under controlled environmental conditions, in order to minimise the influence of short-term external factors, and to characterise a local sheep breed, Gentile di Puglia, thought to be of Merino origin, and a local non-Merino breed, Sarda, at two different stages of their lives. In general, histomorphometric analyses have consistently shown that breed is the main factor determining the follicular and glandular characteristics of sheep skin, while age and follicle type modulate specific components of this pattern. The literature on Merino breeds shows that even a small variation in the secondary to primary follicle ratio can significantly influence fleece characteristics. The S/P ratio is closely related to fibre thickness (Adams and Cronjé, 2003). When compared with published values for Merino and Merino-derived breeds, the values observed here for Gentile di Puglia (S/P: 8.96 ± 0.37; fibre diameter: 22.85 µm) are intermediate between those of fine Merino (S/P ≈ 20.6; fibre diameter ≈ 17.5 µm; Carter and Clarke, 1956) and those reported for other ‘merinized’ breeds such as Polwarth and Corriedale (S/P ≈ 13.2 and 10; fibre diameter ≈ 23.5 and 31.5 µm, respectively). In contrast, the non-merinized breed analysed in this study (Sarda) exhibits a low S/P ratio (2.29 ± 0.31) and a higher fibre diameter (about 45 µm). Taken together, these patterns support the classification of Gentile di Puglia as a Merino-derived, merinized local breed, and of Sarda as a coarse-wool, non-merinized type. While fibre characteristics are defined when the follicle matures, density is established earlier, during foetal life (Moore et al., 1998), and is largely determined prenatally, tending to remain relatively stable across age classes under non-extreme conditions.

It is important to note that we do not claim that follicle traits are completely insensitive to environmental or age effects. On the contrary, previous work has shown that hair follicle density can decrease with age in Merino-type sheep (Dmitrik et al., 2021) and that maternal undernutrition during late gestation can reduce secondary follicle density in Merino foetuses (Lv et al., 2020). Our results should therefore be interpreted within the specific context of this study, namely animals of similar age classes, reared in the same flock and sampled under homogeneous management and seasonal conditions. Under these standardised conditions, the large and consistent differences in S/P ratio and follicle architecture observed between Gentile di Puglia and Sarda are most likely to reflect underlying genetic and long-term selection differences rather than short-term environmental variability.

From a genetic standpoint, the contrasting fleece colours of Gentile di Puglia (predominantly white fleece with pigmented head and limbs) and Sarda (more variable pigmentation and generally coarser wool) are consistent with differences at major coat-colour loci. In sheep, coat colour is mainly controlled by genes involved in melanogenesis, particularly the melanocortin 1 receptor gene (MC1R) at the Extension locus and the agouti signalling protein gene (ASIP), which interact to regulate the balance between eumelanin and pheomelanin production (Fontanesi et al., 2010; Koseniuk et al., 2018). Sequence and association studies in Italian and Mediterranean breeds have shown that specific MC1R and ASIP haplotypes underpin the segregation of black, brown and white fleece variants, including in local breeds such as Massese and Sarda (Fontanesi et al., 2010, Fontanesi et al., 2011). More recently, work on the endangered Karamaniko sheep combined neutral markers and MC1R genotyping, indicating that long-term selection for white fleece has canalised genetic variation at the Extension locus in an autochthonous Mediterranean population (Giantsis et al., 2022). Genome-wide and transcriptomic analyses further support a central role of MC1R, ASIP and other melanogenesis genes in shaping black-versus-white and patterned coat phenotypes in sheep (Fan et al., 2013; Zhou et al., 2023). Although comparable genomic data are not yet available for Gentile di Puglia, the histological pattern observed here, together with the breed-standard description of colour, suggests that integrating MC1R/ASIP genotyping and broader genomic scans with follicle histomorphometry would be a powerful next step to dissect the genetic basis of wool colour in these local breeds.

4.3 Follicle morphology and spatial distribution

Beyond density, follicle morphology and spatial distribution provide further information into breed-specific fleece characteristics. Previous studies on the distribution patterns of hair follicles have suggested that they tend to optimally occupy all available space and that their distribution can vary significantly during foetal development (Linsenmayer, 1972; Nagorcka and Mooney, 1985; Moore et al., 1998). These studies have provided a theoretical basis for understanding the spatial distribution of follicles in different breeds and developmental stages. The present study focuses on characterizing the follicle distribution in two sheep breeds, the merinized Gentile di Puglia and the non-merinized Sarda, revealing differences between the two. Specifically, the analysis showed that, while primary follicles density is comparable between the two breeds, the size of primary follicles in the Sarda breed is significantly larger than that observed in the GdP. Conversely, a higher number of secondary follicles are observed in the GdP, while the sizes remain similar in both breeds. These differences suggest a different spatial and relational organisation between follicle types in the two breeds. Merinos typically present a clustering of follicles, meaning a disposition of secondary follicles around a single primary follicle (Rogers, 2006). In the GdP breed, the follicles tend to form compact clusters, reflecting a close spatial relationship between primary and secondary follicles. In contrast, Sarda follicles are more dispersed, forming loose clusters. Specifically, in the adult, this disposition indicates a less compact cluster arrangement, which may suggest different evolutionary adaptations related to environmental conditions or selective breeding objectives of the two breeds. These observations highlight the importance of considering both the number and size of follicles in understanding fleece growth dynamics. However, while histological analysis provides objective structural insights, it does not fully account for the functional activity of follicles or glands. In this context, it is interesting to note that our data, particularly with regard to the age-related reduction in primary follicle diameter observed in Gentile di Puglia, do not entirely align with the existing literature on fibre diameter in Merino breeds (Dmitrik et al., 2021).

These histological differences also fit within the broader framework of sheep phenotypic evolution, in which domestication and subsequent breed formation have repeatedly targeted wool traits such as fibre diameter, density and crimp. Comparative genomic studies indicate that fine-wool breeds carry strong selection signatures at loci involved in hair follicle development, keratin structure and epidermal growth factor signalling, reflecting long-term selection for dense, fine fleeces (Kalds et al., 2022). Within this context, Gentile di Puglia can be interpreted as the Mediterranean outcome of historical Merino introgression and selection for improved fleece quality, as suggested by its high S/P ratio, compact follicle clusters and intermediate fibre diameter, all consistent with a merinized fine-wool phenotype. In contrast, the Sarda, with its lower S/P ratio, larger primary follicles and coarser fibres, appears closer to the ancestral dual-purpose type adapted to extensive management in the Mediterranean environment. The comparison between these two breeds therefore illustrates an evolutionary trajectory from less specialised, mixed hair–wool coats towards highly merinized fine-wool phenotypes, driven by human selection but constrained by the developmental architecture of the follicle population. Future studies combining genome-wide selection scans with histomorphometric data across a broader panel of Mediterranean breeds would help to quantify how often this “merinization pathway” has been followed and which genes have been repeatedly targeted by selection for wool traits.

However, the overall follicular architecture, density and proportions of primary to secondary follicles remain consistent, supporting the structural patterns described. These findings suggest the existence of breed-specific or sample size-related variability, which warrants further investigation in future studies.

4.4 Sebaceous glands and lanolin production potential

Another important characteristic for the enhancement of sheep breeds is the presence and activity of sebaceous glands, responsible for the production of lanolin (Zhang et al., 2017). Lanolin (wool grease or wool wax) is a complex mixture of sterol esters and other lipids secreted by the sebaceous glands attached to wool follicles; it can account for 10–25% of the weight of freshly shorn wool and represents a valuable raw material for the cosmetics and pharmaceutical industries due to its emollient, moisturising and protective properties (Jiang et al., 2014; El-Sayed et al., 2018; Bhavsar et al., 2023; Lis, 2024). Beyond its economic relevance, lanolin contributes to waterproofing and protecting the fleece and skin against climatic and environmental factors, and is involved in skin barrier homeostasis. Sebaceous glands are closely associated with primary follicles and variously distributed within secondary follicle groups. In this study we examined the distribution and size of these glands in Gentile di Puglia and Sarda sheep. While the size of sebaceous glands did not differ significantly between breeds, sebaceous gland density exhibited a pronounced Breed × Age interaction driven by an exceptional increase in adult Gentile di Puglia sheep, whereas all remaining Breed × Age groups showed similarly low values. This pattern suggests breed-specific regulation of sebaceous activity that emerges only at mature stages and is consistent with the Merino-derived, fine-wool background of Gentile di Puglia.

From a biological perspective, the pilosebaceous unit is a hormone-responsive mini-organ, integrating systemic and local endocrine signals. Studies in mammals have shown that sebaceous gland growth and function are under complex hormonal control: androgens are key stimulators of sebocyte proliferation and lipid synthesis, while other hormones and neuropeptides, such as prolactin, growth hormone, corticosteroids and components of the cutaneous neuroendocrine system, modulate sebaceous activity and interact with local paracrine factors (Deplewski and Rosenfield, 2000; Zouboulis, 2010; Szöllősi et al., 2018; Clayton et al., 2020; Datta et al., 2022; Okoro et al., 2023). Although such mechanisms have been mainly characterised in humans and laboratory animals, similar endocrine principles are expected to apply to ruminant sebaceous glands, which express a wide range of hormone receptors and enzymes for steroid metabolism. In this framework, the higher sebaceous gland density observed in adult Gentile di Puglia may reflect a breed-specific sensitivity of sebocytes to the endocrine milieu, including differences in androgen signalling or in the timing and intensity of hormonal stimuli around puberty and adult reproductive life.

Functionally, an increased density of sebaceous glands in adult Gentile di Puglia is compatible with a higher potential for lanolin production, which could enhance fibre lubrication, protection against weathering and possibly resistance to certain forms of fleece damage. Previous work in Merino and Romney sheep has linked variation in glandular structure and secretion rate to wool yellowing and sweating patterns, underscoring the role of skin glands in determining both aesthetic and functional wool traits (Sumner and Craven, 2004). In conservation and breeding programmes, such differences should not be viewed solely as a source of variation in commercial yield, but also as part of the adaptive phenotype of local breeds to their traditional environments. For Gentile di Puglia, a Merino-derived breed of limited census and conservation concern, preserving the range of sebaceous gland phenotypes may therefore be important both for maintaining its historical wool characteristics and for sustaining its adaptive potential under changing climatic conditions.

From a genetic perspective, the marked Breed × Age pattern in sebaceous gland density suggests that this trait could be integrated into selection schemes once its molecular determinants are better understood. Recent skin transcriptome and genomic studies in fine-wool sheep have identified several candidate genes and pathways related to lipid metabolism, skin structure and hair follicle development that are associated with differences in wool traits and follicle density (Zhang et al., 2017; Bai et al., 2021; Li et al., 2020; Zhao et al., 2021). It is therefore plausible that variation in sebaceous gland density and lanolin output in Gentile di Puglia and Sarda is at least partly under genetic control and may be linked to genomic regions affecting sebocyte differentiation and lipid synthesis. In a conservation-oriented context, the histological markers proposed here could serve as phenotypic anchors for future genome-wide association or selection-scan studies aimed at identifying loci influencing sebaceous activity. Once such loci are characterised, they could be incorporated into marker-assisted or genomic selection strategies that enhance wool and lanolin-related traits in Gentile di Puglia while explicitly constraining inbreeding and preserving genome-wide diversity. In this way, sebaceous gland density would become not only a useful descriptor of wool quality, but also a biologically meaningful target trait within integrated conservation and breeding programmes for Merino-derived local breeds.

4.5 Concluding remark and future perspectives

In conclusion, the histological analysis of hair follicles has proven to be an effective tool for assessing the degree of merinization in sheep breeds, when performed under standardized environmental and management conditions. This approach allows for an accurate and objective characterization of breeds, enabling clear distinctions between merinized and non-merinized breeds based on intrinsic biological parameters, such as the ratio of secondary to primary follicles (S/P), and the density and distribution of the follicles themselves. The Gentile di Puglia clearly exhibits the histological characteristics typical of merinized breeds, with an S/P ratio and follicle structure like those observed in Merino breeds. This supports its classification as a local genetic resource of high value for sustainable wool and lanolin production. Further studies should combine histological data with genomic and transcriptomic analyses. This integrated approach could help to identify the genetic determinants of key morphological traits. These integrative analyses would be crucial for conservation strategies and for developing breeding programmes that enhance fibre quality while preserving the genetic diversity of local sheep breeds.

From an applied perspective, our findings support three main recommendations for research, conservation and breeding. First, we suggest that the secondary-to-primary follicle ratio (S/P), together with primary and secondary follicle densities and sebaceous gland density, should be integrated into phenotypic recording schemes and breed databases for fine-wool and local sheep breeds. When measured under standardised conditions, these histological indicators provide intrinsic information on the degree of merinization and on the potential for wool and lanolin production, complementing conventional fleece traits. Second, we recommend that future histological studies on wool breeds adopt simple, standardised sampling protocols, including the use of animals of the same sex and clearly defined age classes (e.g. adult ewes and lambs), reared under homogeneous management and seasonal conditions, and skin biopsies collected from a consistent body site (such as the dorsal region near the caudal corner of the scapula), with a sufficient number of animals per Breed × Age class to ensure robust inference. Third, we highlight the potential to link these histological markers with emerging genomic and transcriptomic information, including functional variants at genes such as KRT74 and EDAR, which have recently been shown to synergistically drive finer and denser wool production in Chinese fine-wool sheep (Liang et al., 2024). In this context, Gentile di Puglia and related Merino-derived populations represent ideal candidates for future integrative studies that combine histomorphometric data with candidate-gene and genome-wide markers to inform conservation-oriented, marker-assisted or genomic selection programmes for wool and lanolin traits.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical approval was not required for the study involving animals in accordance with the local legislation and institutional requirements because The samples came from animals intended for human consumption and collected during slaughter operations.

Author contributions

RT: Conceptualization, Investigation, Validation, Writing – original draft. MM: Conceptualization, Formal analysis, Software, Writing – original draft, Writing – review & editing. GV: Conceptualization, Resources, Writing – original draft. JQ: Resources, Software, Writing – review & editing. MR: Resources, Validation, Writing – review & editing. SB: Formal analysis, Methodology, Writing – original draft. EC: Conceptualization, Formal analysis, Funding acquisition, Resources, Writing – original draft, Writing – review & editing. LG: Formal analysis, Methodology, Writing – original draft. AC: Software, Writing – review & editing. VL: Conceptualization, Formal analysis, Funding acquisition, Resources, Writing – original draft, Writing – review & editing. TM: Conceptualization, Supervision, Writing – original draft, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This study was primarily funded by the WOOLLY project, supported through the Seal of Excellence programme by the Apulia Region (Grant Code: FSC/2019/000007). The WOOLLY project also financed the research fellowships of Dr. Maria Gabriela Molina and Dr. Rossana Topputi. Additional support was provided by the European Union under the Next-Generation EU programme (PNRR) – MISSION 4, COMPONENT 2, INVESTMENT 1.4 – D.D. 1032 of 17/06/2022, Project Code CN00000022, within the framework of the Agritech National Research Center.

Acknowledgments

The authors are grateful to the technician Rosa Leone for helping with histology procedures.

Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fanim.2025.1670137/full#supplementary-material

Supplementary Figure 1 | Mixed-model structures, assumption checks, ANOVA tables, and post-hoc estimated marginal means for all histomorphometric variables. ^1. Models. All traits were analyzed using hierarchical Gaussian mixed models fitted with the lme function (nlme package, R v. 4.4.3). For each variable, fixed effects included Breed (two levels: Gentile di Puglia, Sarda), age class (Adult, Lamb), and follicle Type (Primary, Secondary) when applicable. Animal (VETRINO) was included as a random intercept to account for repeated measurements within individuals. A compound-symmetry correlation structure (corCompSymm) was used to model within-animal dependence. When supported by Akaike Information Criterion (AIC) a Residual variance structure (varIdent): Density and Diameter: heterogeneous residual variance by follicle Type (Primary vs Secondary); S/P ratio, Sebaceous gland density, Sebaceous gland area: heterogeneous residual variance by Breed (Gentile vs Sarda). ² Assumptions. Normality and homoscedasticity were evaluated graphically through residual-versus-fitted and Q–Q plots. “Normality” and “Homoscedasticity” panels indicate that diagnostic plots did not show departures from model assumptions. ³ ANOVA columns. numDF = numerator degrees of freedom; denDF = denominator degrees of freedom; F-value = test statistic; p-value = significance level. Asterisks (*) indicate statistically significant effects at α = 0.05. ⁴ Post-hoc contrasts Post-hoc estimated marginal means (EMMs). emmean = estimated marginal mean; SE = standard error; df = degrees of freedom; LCL/UCL = lower/upper 95% confidence limits.Grouping letters are generated by compact letter display (CLD):Groups sharing at least one symbol are not significantly different (Sidak-adjusted α = 0.05).

Supplementary Figure 2 | Skin histology of Pelibuey sheep. The right panel shows a low magnification view of general skin architecture with visible primary follicles. The left panel highlights a region containing sweat glands. Notice the absence of secondary follicles, common in wool-producing breeds. H&E staining, 5x magnification. Scale bar: 100 µm.

References

Adams N. R. and Cronjé P. B. (2003). A review of the biology linking fibre diameter with fleece weight, liveweight, and reproduction in Merino sheep. Aust. J. Agric. Res. 54, 1–10. doi: 10.1071/AR02059

Crossref Full Text | Google Scholar

Al-Atiyat R., Flood W., Franklin I., Kinghorn B., and Ruvinsky A. (2016). Microsatellite-based genetic variation and differentiation of selected Australian Merino sheep flocks. Small Rumin Res. 136, 137–144. doi: 10.1016/j.smallrumres.2016.01.018

Crossref Full Text | Google Scholar

Anaya G., Laseca N., Granero A., Ziadi C., Arrebola F., Domingo A., et al. (2024). Genomic characterization of quality wool traits in spanish merino sheep. Genes 15, 795. doi: 10.3390/genes15060795

PubMed Abstract | Crossref Full Text | Google Scholar

Ansari-Renani H. R., Ebadi Z., Moradi S., Baghershah H. R., Ansari-Renani M. Y., and Ameli S. H. (2011). Determination of hair follicle characteristics, density and activity of Iranian cashmere goat breeds. Small Rumin Res. 95, 128–132. doi: 10.1016/j.smallrumres.2010.09.013

Crossref Full Text | Google Scholar

Baddeley A., Rubak E., and Turner R. (2015). Spatial point patterns: Methodology and applications with R (Boca Raton, FL: CRC Press).

Google Scholar

Bai T., Bai J., Cheng M., Jiang H., Li J., Li L., et al. (2021). Transcriptome analysis reveals candidate genes related to wool density in Chinese Tan sheep and Xinji fine-wool sheep. Agriculture 12, 15. doi: 10.3390/agriculture12010015

Crossref Full Text | Google Scholar

Bhavsar P., Zoccola M., Dalla Fontana G., Pallavicini M., Roda G., and Bolchi C. (2023). Sustainable routes for wool grease removal using green solvent cyclopentyl methyl ether in solvent extraction and biosurfactant wool protein hydrolyzate in scouring. Processes 11, 1309. doi: 10.3390/pr11051309

Crossref Full Text | Google Scholar

Carter H. B. and Clarke W. H. (1956). The hair follicle group and skin follicle population of Australian Merino sheep. Aust. J. Agric. Res. 8, 91–108. doi: 10.1071/AR9570091

Crossref Full Text | Google Scholar

Champion S. C. and Robards G. E. (2000). Follicle characteristics, seasonal changes in fibre cross-sectional area and ellipticity in Australasian specialty carpet wool sheep, Romneys and Merinos. Small Rumin Res. 38, 71–82. doi: 10.1016/S0921-4488(00)00141-3

PubMed Abstract | Crossref Full Text | Google Scholar

Ciani E., Lasagna E., D’Andrea M., Alloggio I., Marroni F., Ceccobelli S., et al. (2015). Merino and merino-derived sheep breeds: A genome-wide intercontinental study. Genet. Sel Evol. 47, 64. doi: 10.1186/s12711-015-0139-z

PubMed Abstract | Crossref Full Text | Google Scholar

Ciani E., Mastrangelo S., Da Silva A., Marroni F., Ferenčaković M., Ajmone-Marsan P., et al. (2020). On the origin of European sheep as revealed by the diversity of the Balkan breeds and by optimizing population-genetic analysis tools. Genet. Sel Evol. 52, 25. doi: 10.1186/s12711-020-00545-7

PubMed Abstract | Crossref Full Text | Google Scholar

Clayton R. W., Langan E. A., Ansell D. M., de Vos I. J. H. M., Göbel K., Schneider M. R., et al. (2020). Neuroendocrinology and neurobiology of sebaceous glands. Biol. Rev. Camb. Philos. Soc. 95, 592–624. doi: 10.1111/brv.12579

PubMed Abstract | Crossref Full Text | Google Scholar

Datta D., Madke B., and Das A. (2022). Skin as an endocrine organ: A narrative review. Indian J. Dermatol. Venereol. Leprol. 88, 590–597. doi: 10.25259/IJDVL5332021

PubMed Abstract | Crossref Full Text | Google Scholar

Deplewski D. and Rosenfield R. L. (2000). Role of hormones in pilosebaceous unit development. Endocrine Rev. 21, 363–392. doi: 10.1210/edrv.21.4.0404

PubMed Abstract | Crossref Full Text | Google Scholar

Dmitrik I. I., Zavgorodnyaya G. V., and Pavlova M. I. (2021). Age-related changes in the skin structure and wool quality in sheep of Artlukh merino breed. Glavnyj Zootehnik 5, 47–54. doi: 10.33920/sel-03-2105-06

Crossref Full Text | Google Scholar

Dzomba E. F., Chimonyo M., Snyman M. A., and MuChadeyi F. C. (2020). The genomic architecture of South African mutton, pelt, dual-purpose and nondescript sheep breeds relative to global sheep populations. Anim. Genet. 51, 910–923. doi: 10.1111/age.12991

PubMed Abstract | Crossref Full Text | Google Scholar

Edwards J. E. H., Birtles M. J., Wickham G. A., Harris P. M., and McCutcheon S. N. (1996). Pre- and post-natal wool follicle development and density in sheep of five genotypes. J. Agric. Sci. 126, 363–370. doi: 10.1017/S002185960007492X

Crossref Full Text | Google Scholar

El-Sayed H. E. D. Z., Mowafi S., El-Kheir A. A., and El-Khatib E. M. (2018). A comprehensive critique on wool grease extraction, properties and applications. Egyptian J. Chem. 61, 1151–1159. doi: 10.21608/ejchem.2018.4214.1372

Crossref Full Text | Google Scholar

Fan R., Xie J., Bai J., Wang H., Liu J., Ding X., et al. (2013). Skin transcriptome profiles associated with coat color in sheep. BMC Genomics 14, 389. doi: 10.1186/1471-2164-14-389

PubMed Abstract | Crossref Full Text | Google Scholar

Fontanesi L., Beretti F., Riggio V., Dall’Olio S., Calascibetta D., Russo V., et al. (2010). Sequence characterization of the melanocortin 1 receptor (MC1R) gene in sheep with different coat colours and identification of the putative e allele at the ovine Extension locus. Small Rumin. Res. 91, 200–207. doi: 10.1016/j.smallrumres.2010.03.015

Crossref Full Text | Google Scholar

Fontanesi L., Dall’Olio S., Beretti F., Portolano B., and Russo V. (2011). Coat colours in the Massese sheep breed are associated with mutations in the agouti signalling protein (ASIP) and melanocortin 1 receptor (MC1R) genes. Animal 5, 8–17. doi: 10.1017/S1751731110001382

PubMed Abstract | Crossref Full Text | Google Scholar

Gaspa G., Cesarani A., Pauciullo A., Peana I., and Macciotta N. P. P. (2024). Genomic analysis of Sarda sheep raised at diverse temperatures highlights several genes involved in adaptations to the environment and heat stress response. Animals 14, 3585. doi: 10.3390/ani14243585

PubMed Abstract | Crossref Full Text | Google Scholar

Giantsis I. A., Antonopoulou D., Dekolis N., Laliotis G. P., and Arsenos G. (2022). Origin, demographics, inbreeding, phylogenetics, and phenogenetics of Karamaniko breed, a major common ancestor of the autochthonous Greek sheep. Trop. Anim. Health Prod. 54, 73. doi: 10.1007/s11250-022-03081-2

PubMed Abstract | Crossref Full Text | Google Scholar

Granero A., Anaya G., Demyda-Peyrás S., Alcalde M. J., Arrebola F., Molina A., et al. (2022). Genomic population structure of the main historical genetic lines of Spanish Merino sheep. Animals 12, 1327. doi: 10.3390/ani12101327

PubMed Abstract | Crossref Full Text | Google Scholar

Gutiérrez J., Rubio M. S., and Méndez R. D. (2005). Effects of crossbreeding Mexican Pelibuey sheep with Rambouillet and Suffolk on carcass traits. Meat Sci. 70, 1–5. doi: 10.1016/j.meatsci.2004.10.017

PubMed Abstract | Crossref Full Text | Google Scholar

Jiang Y., Xie M., Chen W., Talbot R., Maddox J. F., Faraut T., et al. (2014). The sheep genome illuminates biology of the rumen and lipid metabolism. Science 344, 1164–1168. doi: 10.1126/science.1252806

PubMed Abstract | Crossref Full Text | Google Scholar

Kalds P., Zhou S., Gao Y., Cai B., Huang S., Chen Y., et al. (2022). Genetics of the phenotypic evolution in sheep: a molecular look at diversity-driving genes. Genet. Sel Evol. 54, 61. doi: 10.1186/s12711-022-00753-3

PubMed Abstract | Crossref Full Text | Google Scholar

Khan M. J., Abbas A., Ayaz M., Naeem M., Akhter M. S., Soomro M. H., et al. (2012). Factors affecting wool quality and quantity in sheep. Afr J. Biotechnol. 11, 13761–13766. doi: 10.5897/ajbx11.064

Crossref Full Text | Google Scholar

Kijas J. W., Lenstra J. A., Hayes B., Boitard S., Porto Neto L. R., San Cristobal M., et al. (2012). Genome-wide analysis of the world’s sheep breeds reveals high levels of historic mixture and strong recent selection. PloS Biol. 10, e1001258. doi: 10.1371/journal.pbio.1001258

PubMed Abstract | Crossref Full Text | Google Scholar

Koseniuk A., Ropka-Molik K., Rubiś D., and Smołucha G. (2018). Genetic background of coat colour in sheep. Arch. Anim. Breed. 61, 173–178. doi: 10.5194/aab-61-173-2018

Crossref Full Text | Google Scholar

Li S., Chen W., Zheng X., Liu Z., Yang G., Hu X., et al. (2020). Comparative investigation of coarse and fine wool sheep skin indicates the early regulators for skin and wool diversity. Gene 758, 144968. doi: 10.1016/j.gene.2020.144968

PubMed Abstract | Crossref Full Text | Google Scholar

Liang B., Bai T., Zhao Y., Han J, He X, Pu Y, et al. (2023). Two mutations at KRT74 and EDAR synergistically drive the fine-wool production in Chinese sheep. J. Adv. Res. 57, 1–13. doi: 10.1016/j.jare.2023.04.012

PubMed Abstract | Crossref Full Text | Google Scholar

Linsenmayer T. F. (1972). Control of integumentary patterns in the chick. Dev. Biol. 27, 244–271. doi: 10.1016/0012-1606(72)90101-7

PubMed Abstract | Crossref Full Text | Google Scholar

Lis K. (2024). Hypersensitivity to lanolin: An old–new problem. Life 14, 1553. doi: 10.3390/life14121553

PubMed Abstract | Crossref Full Text | Google Scholar

Lv X., Chen L., He S., Liu C., Han B., Liu Z., et al. (2020). Effect of nutritional restriction on the hair follicles development and skin transcriptome of Chinese Merino sheep. Animals 10, 1058. doi: 10.3390/ani10061058

PubMed Abstract | Crossref Full Text | Google Scholar

Lv X., Sun W., Yin J., Ni R., Su R., Wang Q., et al. (2016). An integrated analysis of microRNA and mRNA expression profiles to identify RNA expression signatures in lambskin hair follicles in Hu sheep. PloS One 11, e0157463. doi: 10.1371/journal.pone.0157463

PubMed Abstract | Crossref Full Text | Google Scholar

Lyne A. G. (1961). The postnatal development of wool follicles, shedding, and skin thickness in inbred Merino and Southdown-Merino crossbred sheep. Aust. J. Biol. Sci. 14, 141–156. doi: 10.1071/BI9610141

Crossref Full Text | Google Scholar

McGregor B. A., Martens G. W., and Cottle D. J. (2016). On-farm factors affecting physical quality of Merino wool. Small Rumin Res. 141, 1–10. doi: 10.1016/j.smallrumres.2016.03.019

Crossref Full Text | Google Scholar

Megdiche S., Mastrangelo S., Hamouda M. B., Lenstra J. A., and Ciani E. (2019). A combined multi-cohort approach reveals novel and known genome-wide selection signatures for wool traits in merino and merino-derived sheep breeds. Front. Genet. 10. doi: 10.3389/fgene.2019.01025

PubMed Abstract | Crossref Full Text | Google Scholar

Moore G. P., Jackson N., Isaacs K., and Brown G. (1998). Pattern and morphogenesis in skin. J. Theor. Biol. 191, 87–94. doi: 10.1006/jtbi.1997.0567

PubMed Abstract | Crossref Full Text | Google Scholar

Nagorcka B. N. and Mooney J. R. (1985). The role of a reaction-diffusion system in the initiation of primary hair follicles. J. Theor. Biol. 114, 243–272. doi: 10.1016/S0022-5193(85)80106-5

PubMed Abstract | Crossref Full Text | Google Scholar

Okoro O. E., Kartal E., Volkenhoff A., and Paus R. (2023). Insulin and the sebaceous gland function. Front. Physiol. 14. doi: 10.3389/fphys.2023.1252972

PubMed Abstract | Crossref Full Text | Google Scholar

Regione Puglia (2022). Scheda di razza “Gentile di Puglia” (Filiere Agroalimentari Regione Puglia). Bari, Italy: Regione Puglia.

Google Scholar

Rochus C. M., Tortereau F., Plisson-Petit F., Restoux G., Moreno-Romieux C., Tosser-Klopp G., et al. (2018). Revealing the selection history of adaptive loci using genome-wide scans for selection: An example from domestic sheep. BMC Genomics 19, 71. doi: 10.1186/s12864-018-4447-x

PubMed Abstract | Crossref Full Text | Google Scholar

Rogers G. E. (2006). Biology of the wool follicle: An excursion into a unique tissue interaction system waiting to be re-discovered. Exp. Dermatol. 15, 931–949. doi: 10.1111/j.1600-0625.2006.00512.x

PubMed Abstract | Crossref Full Text | Google Scholar

Ryder M. L. (1983). Sheep and man (London: Duckworth), ISBN: ISBN: 9780715616666.

Google Scholar

Schneider C. A., Rasband W. S., and Eliceiri K. W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675. doi: 10.1038/nmeth.2089

PubMed Abstract | Crossref Full Text | Google Scholar

Sengupta A. and Behera J. (2014). Comprehensive view on chemistry, manufacturing & applications of lanolin extracted from wool pretreatment. Am. J. Eng. Res. 3, 33–43.

Google Scholar

Serranito B., Cavalazzi M., Vidal P., Taurisson-Mouret D., Ciani E., Bal M., et al. (2021). Local adaptations of Mediterranean sheep and goats through an integrative approach. Sci. Rep. 11, 21363. doi: 10.1038/s41598-021-00682-z

PubMed Abstract | Crossref Full Text | Google Scholar

Sumner R. M. W. and Craven A. J. (2004). Relation between sweating and wool yellowing in Merino and Romney sheep. Proc. N. Z. Soc. Anim. Prod. 64, 336–341.

Google Scholar

Szöllősi A. G., Oláh A., Bíró T., and Tóth B. I. (2018). Recent advances in the endocrinology of the sebaceous gland. Dermato-Endocrinology 9, e1361576. doi: 10.1080/19381980.2017.1361576

PubMed Abstract | Crossref Full Text | Google Scholar

Temerario L., Monaco D., Mastrorocco A., Martino N. A., Cseh S., Lacalandra G. M., et al. (2023). New strategies for conservation of Gentile di Puglia sheep breed, an autochthonous capital of millennial tradition in Southern Italy. Animals 13, 2371. doi: 10.3390/ani13142371

PubMed Abstract | Crossref Full Text | Google Scholar

Yaman Y., Önaldi A. T., Doğan Ş, Kirbaş M., Behrem S., Kal Y., et al. (2025). Exploring the polygenic landscape of wool traits in Turkish Merinos through multi-locus GWAS approaches: middle Anatolian Merino. Sci. Rep. 15, 95099. doi: 10.1038/s41598-025-95099-3

PubMed Abstract | Crossref Full Text | Google Scholar

Yeates N. T. M., Edey T. N., and Hill M. K. (1975). Animal science: Reproduction, climate, meat, wool (Rev. ed) (Australia: Pergamon Press).

Google Scholar

Zhang L., Sun F., Jin H., Dalrymple B. P., Cao Y., Wei T., et al. (2017). A comparison of transcriptomic patterns measured in the skin of Chinese fine and coarse wool sheep breeds. Sci. Rep. 7, 14301. doi: 10.1038/s41598-017-14772-4

PubMed Abstract | Crossref Full Text | Google Scholar

Zhao B., Luo H., He J., Huang X., Chen S., Fu X., et al. (2021). Comprehensive transcriptome and methylome analysis delineates the biological basis of hair follicle development and wool-related traits in Merino sheep. BMC Biol. 19, 197. doi: 10.1186/s12915-021-01127-9

PubMed Abstract | Crossref Full Text | Google Scholar

Zhou Q., Cao C., Zhang H., Liang Y., Zhang X., Kang Y., et al. (2023). Convergent changes in melanocortin receptor 1 gene are associated with black-headed coat color in sheep. J. Anim. Sci. 101, skad084. doi: 10.1093/jas/skad084

PubMed Abstract | Crossref Full Text | Google Scholar

Zouboulis C. C.. (2010). The sebaceous gland. Hautarzt. 61, 467–468, 470–474, 476–477. doi: 10.1007/s00105-009-1894-y

PubMed Abstract | Crossref Full Text | Google Scholar