https://orcid.org/0000-0003-1657-8838
Abstract
The Canary Islands have historically been a crossway among at least three continents; therefore, the genetic influences on their local animal breeds have been extremely diverse. In the Canarian chicken population, genetic diversity is evident but it has never been studied. The aim of this study was to assess the population structure and genetic diversity within the Canarian chicken population, as well as between the Canarian chicken population, the Spanish local populations, and the commercial chicken populations with microsatellites, with a view to reinforce the official recognition of the breed, for the design and development of a conservation program. Blood samples were collected at random from 198 animals of the Canarian and compared with Spanish local and commercial strains, in order to determine differentiation and genetic relatedness. The five phenotypic varieties of Canarian chicken, the population structure and genetic diversity within the Canarian chicken population had a higher unbiased expected heterozygosity than the observed heterozygosity. Comparing the Canarian vs other local Spanish breeds and commercial strains, FST was relatively high (0.179) (0.164 – 0.195), the neighborhood network showed that the Canarian varieties did not cluster with the other Spanish breeds. The STRUCTURE, confirmed that the Rubilana variety differed from the other four Canary Islands. We conclude that the Canary Islands chicken population shows a differentiated genetic profile, versus other Spanish and cosmopolitan breeds. The theory that the existence of genetic varieties is based on the color of feathers was definitively discarded, except in the Rubilana population, which could be admitted as a genetically different variety.
HIGHLIGHTS
The Rubilana chicken variety appeared to be genetically differentiated from the other Canarian varieties.
The Canarian varieties did not cluster with the other Spanish breeds.
The theory of the existence of genetic varieties within the breed is discarded, except for the Rubilana population.
Introduction
Healthy and diverse animal genetic resources are needed to enable livestock to be able to face climate change, new disease challenges, changes in the livelihood and lifestyle opportunities available to rural people, restrictions on the availability of natural resources, and changing market demands (Bianchi et al. Citation2011; Scherf and Pilling Citation2015). Unfortunately, the proportion of livestock breeds classified as being at risk of extinction increased from 15% to 17% between 2005 and 2014, and it is likely that this percentage is an underestimation, because 58% of breeds are classified as being of unknown risk status (Scherf and Pilling Citation2015). The Global Plan of Action for Animal Genetic Resources (Declaration Citation2007) and The Second Report on the State of the World’s Animal Genetic Resources for Food and Agriculture (Scherf and Pilling Citation2015) have addressed this potential loss of animal genetic diversity and offer several strategic priorities to different countries to strengthen the main elements of sustainable management, such as improving knowledge of the characteristics of different types of animal genetic resources, the production systems in which they are kept, and the trends affecting these production systems; developing stronger institutional frameworks for management; improving awareness, education, training, and research in all areas of genetics resources management; strengthening breeding strategies and programs, to enable full advantage to be taken of available genetic diversity; and expanding and diversifying conservation programs.
One of the countries implementing the FAO conservation strategy is Spain. To date, there have been many efforts to recover and identify species, such as goats, sheep, horses, donkeys, and chickens, to mention a few, through conservation and characterisation programs. Precisely, the study of the genetic diversity and population structure in chickens covers some of those priorities in Spain. If we go back in time, during the second half of the twentieth century, several foreign breeds and commercial chickens arrived in Spain, accompanied by industrial and other production systems that changed the status quo. Before the introduction of foreign breeds, there were many locally adapted breeds under traditional production systems that supplied local markets and produced food for self-consumption.
In fact, one of the main places that has suffered from the introduction of foreign breeds and commercial chickens is the Canary Islands. The Canarian archipelago has its own population of chickens called ‘backyard chickens’ (Canarian chickens). These chickens are quite popular in rural and urban areas, where they provide families with fresh eggs and meat (Rodriguez-Díaz. Citation2010). Currently in the Canary Islands, it is understood that the Canary chicken population includes five phenotypic varieties—Canaria Jabada Dorada (Dorada), Canaria Jabada (Jabada), Canaria Negra (Negra), Canaria Aperdizada (Aperdizada), and Canaria Rubilana (Rubilana) with different shank and plumage colours (Torres and Capote Citation2018b). The chickens are mostly kept in henhouses with outdoor access and fed with fodder and/or scratch grains, as well as vegetable remains produced in farms or food waste and kitchen scraps generated at home (Torres and Capote Citation2018a).
Chickens were not present in the Canary Islands prior to the Spanish colonisation in the fifteenth century. However, at this time, the archipelago became a crossway between Spain and the Spanish colonies in Asia, Africa, and America, and also as a world maritime trade centre. Therefore, several chicken international genetic resources reached the Canary Islands and participated in the formation of the present Canarian chicken population.
Regrettably, the Canarian poultry livestock might be following the same trend shared by any developed country, where locally adapted breeds are at risk of extinction because of the increasing demand for animal products (Halima et al. Citation2007; Özdemir et al. Citation2013), which makes them less competitive in terms of the supply of mass-market products (Scherf and Pilling Citation2015). Nonetheless, the birth of the breeders’ association, ‘Gallina Campera Canaria’, whose aims are the recovery, dissemination, and promotion of local chicken breeds, should contribute to increasing livestock diversity and prevent the disappearance of local breeds by assuming a leading role in any conservation program. This animal population breeding model is transmitted from parents to sons and daughters as an alternative model, including farms with simple infrastructures, a diet based on local resources, and a low density of animals compatible with organic or alternative free-range production (González Ariza et al. Citation2022). From another point of view, this management system is sustainable, taking advantage of local resources to produce zero-kilometer eggs and meat, with great demand from consumers (Torres et al. Citation2019).
These conservation programs must consider the importance of genetic diversity within and between populations (Weigend and Romanov Citation2002; Rege and Gibson Citation2003; Simianer Citation2005; Eding and Bennewitz Citation2007; Lenstra et al. Citation2012) and, therefore, should be studied. A genetic tool applied for carrying out these conservation programs is the use of microsatellite markers, which is an inexpensive and accessible method with which for different laboratories to estimate genetic structure and investigate genetic diversities between and within populations. Chicken populations are highly polymorphic, and such molecular markers have proved to be accurate and efficient in several studies conducted to evaluate the genetic diversity of chickens (Granevitze et al. Citation2007; Dávila et al. Citation2009; Bianchi et al. Citation2011; Ceccobelli et al. Citation2013; Abebe et al. Citation2015).
The aim of this study was to assess the population structure and genetic diversity within the Canarian chicken population, as well as between the Canarian chicken population, the Spanish local populations, and the commercial chicken populations with microsatellites, with a view to reinforce the official recognition of the breed, checking any genetic introgression and generating genetic fundamentals for the design and development of a conservation program.
Materials and methods
Sample collection
Blood samples were collected at random from 198 animals raised by breeders of the Canarian Chicken Breeders Association, ‘La Campera’, in several locations throughout the Canary Islands archipelago. The standard breed for the Canarian chicken population includes culturally considered varieties with different shank and plumage colours. All of them were sampled: Dorada (41), Jabada (46), Negra (38), Aperdizada (36), and Rubilana (37). A total of 955 samples were also collected from 15 Spanish local breeds and 4 commercial strains, in order to determine the genetic differentiation from and relationship with the Canarian chicken population (Supplementary Materials Table S1).
Samples collected on filter paper sheets were stored at room temperature until further analysis at the Animal Breeding Consulting Laboratory of the University of Córdoba, Spain. DNA was extracted using Chelex-100 resin® (BioRad, Spain) with the cycle incubation method described by Walsh et al. (Citation1992).
Microsatellite molecular analysis
Three multiplex PCR (polymerase chain reaction) assays were carried out to amplify 30 microsatellite markers, 29 of which are recommended by the FAO (FAO Citation2011) and used in the AVIANDIV project (https://aviandiv.fli.de/primer_table.html), given as follows: ADL112, ADL268, ADL278, LEIO094, LEIO166, LEIO192, LEIO234, MCW014, MCW016, MCW020, MCW034, MCW037, MCW067, MCW069, MCW078, MCW080, MCW081, MCW098, MCW103, MCW104, MCW111, MCW123, MCW165, MCW183, MCW206, MCW216, MCW222, MCW248, MCW295, and MCW330. The PCR volume of 25 µL contained 5 µL of Chelex lysate (∼10 ng of genomic DNA), 1X MytaqHS 5X buffer (Bioline GmbH, Luckenwalde, Germany), 0.5 Units of MytaqHS Polymerase (Bioline GmbH, Luckenwalde, Germany), and 2.5 µL of potentiator solution (Betaine 2,7 mol, Ditiotreitol= 6,7mM and Dimethylsulfoxide= 6.7%) for high PCR fragments of ‘GC’. The primer concentrations were 0.2 µM for each forward primer and 0.2 µM for each reverse primer. The PCR consisted of 35 cycles of a 3-step protocol: 5 min at 95 °C for Taq polymerase activation, 95 °C for 30 s followed by 45 s at 55 °C and extension for 45 s at 72 °C, and finally a final 72 °C extension step for 20 min for efficiency. The fragments were analysed using an automated DNA sequencer, ABI PRISM 3130XL (Applied Biosystems, FosterCity, CA, US), using a POP7 polymer and the internal size standard GeneScan500-ROX (Life Technology, Carlsbad, California, United States). The analyses of the fragments and the allelic typing were developed in the software Genescan Analysis® 3.1.2 and Genotyper® 2.5.2, respectively.
Microsatellite statistical analysis
The number of alleles per locus, mean number of alleles, unbiased expected and observed heterozygosities, and polymorphism information content per Canarian chicken variety were calculated with the MICROSATELLITE TOOLKIT software for Excel (Park Citation2001). The effective number of alleles was calculated using POPGENE v. 1.32 (Yeh et al. Citation1999), and the allelic richness was obtained with the program FSTAT v2.9.3.2 (Goudet Citation2001). The GENETIX v4.04 program was applied according to Belkhir (Citation2004) in order to calculate the within-breed inbreeding coefficient (FIS). The Hardy–Weinberg equilibrium with the Bonferroni correction was tested using the program CERVUS v3.0.3 (Kalinowski et al. Citation2007). Analysis of molecular variance (AMOVA) was used to calculate the genetic variation and differentiation between populations by performing 10,000 permutations using the software ARLEQUIN v3.1 (Excoffier et al. Citation2006).
To determine whether Canarian chicken breed varieties represented their own population structure or whether they were just the result of colour pattern gene segregation, a genetic structure study was carried out applying the Bayesian model-based method developed by Pritchard et al. (Citation2004) and implemented in the STRUCTURE v 2.1 program (Pritchard et al. Citation2010) to identify any underlying genetic structure among the group of animals genotyped, to expose potential substructures within the Canarian chicken population. It was run with an initial length of 200,000 burn-in periods followed by 500,000 MCMC (Markov Chain Monte Carlo) iterations, with 10 repeats per K (number of clusters) ranging from 2 to 24. The population structure results were graphically represented using the DISTRUCT software (Rosenberg Citation2004).
A factorial correspondence analysis (FCA) for the five Canarian phenotypic varieties and for the whole set of 24 populations was implemented in the GENETIX v4.04 program (Belkhir Citation1999). Reynolds’ genetic distances or Reynolds’ co-ancestrality were selected because they assume the absence of mutation (Reynolds et al. Citation1983), were calculated and used to build dendrograms with the program POPULATIONS v1.2.28 (Langella Citation1999). The trees were displayed with the TREEVIEW program (Page Citation1996).
To assess the genetic differentiation among the Canarian chicken population, the F-statistics of Spanish local breeds and commercial strains were calculated with the GENETIX v4.04 program (Belkhir Citation1999). The genetic distance DA (Nei et al. Citation1983) between pairs of populations, was selected because it is the most commonly used with microsatellites, as it demonstrates the similarity between populations with respect to allele frequencies in certain genetic systems. It was estimated using the POPULATIONS v1.2.28 software (Langella Citation1999) and a neighbor-net al.gorithm was built using SPLITSTREE4 software (Huson and Bryant Citation2006).
Results and discussion
Genetic diversity within the Canarian chicken population and its genetic structure
The genetic diversity parameters for each microsatellite analysed within Canarian Dorada, Jabada, Negra, Aperdizada, and Rubilana chicken varieties are shown in Tables and .
Table 1. Genetic diversity parameters for each microsatellite analysed within Canarian chicken varieties: number of alleles per locus (NA), effective number of alleles (Ae), allelic richness (Ar), observed heterozygosity (Ho), unbiased expected heterozygosity (He), polymorphism information content (PIC), within-breed inbreeding coefficient (FIS), FIS confidence interval across loci (CI) and deviations from Hardy-Weinberg equilibrium (HWE).
Table 2. Genetic diversity parameters for each Canarian chicken variety: unbiased expected heterozygosity (He) and its standard deviation (He SD), observed heterozygosity (Ho) and its standard deviation (Ho SD), mean number of alleles (MNA) and its standard deviation (MNA SD), within-breed inbreeding coefficient (FIS) and its confidence interval across loci (CI).
LEIO234 was the microsatellite marker with the highest observed (HO) and expected (HE) heterozygosities, with values of 0.802 and 0.891, respectively. MCW014 (0.101) and MCW248 (0.339) showed the lowest HO and HE values. It was found that the mean genetic diversity for Canarian Dorada, Jabada, Negra, Aperdizada, and Rubilana chickens was 0.667 (Table ) and was higher than the values previously reported by several authors based on the same microsatellite loci in different chicken populations in Europe (Bianchi et al. Citation2011; Ceccobelli et al. Citation2015). The results of several investigations on the local population of chicken breeds were as follows: Swedish = 0.602 (Abebe et al. Citation2015), Italian = 0.50 (Ceccobelli et al. Citation2015), British = 0.49 (Wilkinson et al. Citation2012), Kenyan = 0.399 (Okumu et al. Citation2017), and North-West = 0.45 (Granevitze et al. Citation2007). Nevertheless, there were populations with a genetic diversity close to the Canarian chicken, as was the case with populations as follows: Chinese = 0.668 (Bao et al. Citation2007), South African = 0.68 (Nxumalo et al. Citation2020), Indian = 0.685 (Rudresh et al. Citation2015), and Asian = 0.603 (Lyimo et al. Citation2014).
The thirty markers used had a mean polymorphism information content (PIC) of 0.617 (Table ), and twenty-four markers showed a high PIC, ranging from 0.516 to 0.880, whereas only six markers were moderately informative, with a PIC between 0.301 and 0.481 (LEIO166, MCW014, MCW098, MCW103, MCW222, and MCW248). If we take into account the fact that the PIC is a measure of the informativeness of microsatellite loci in relation to HE (Guo and Elston Citation1999), our results suggest that the markers were useful in evaluating the genetic diversity of the Canarian chicken population. These results do not differ much from the PIC of other studies where genetic characterisation of hen populations was performed and which used the same microsatellites, such as in the following populations: Swedish = 0.551 (Abebe et al. Citation2015), Chinese = 0.50 (Bao et al. Citation2007), Italian = 0.765 (Bianchi et al. Citation2011), and Brazilian = 0.794 (Fonteque et al. Citation2014).
The within-breed inbreeding coefficient (FIS) among loci ranged from −0.001 (0.080 − 0.075) in the marker MCW295 to 0.781 (0.688 − 0.865) in MCW014. Five markers showed no significant negative value of FIS (ADL112, LEIO192, MCW069, MCW248, and MCW295). In the Hardy–Weinberg Equilibrium (HWE) test results, only three markers (MCW014, MCW067, and MCW034) significantly deviated from HWE when the Bonferroni correction was implemented (Table ). A significant heterozygosity deficit and a deviation from HWE have been previously reported in several local populations across different countries, such as the populations of Swedish (Abebe et al. Citation2015), Chinese (Bao et al. Citation2007), Italian (Bianchi et al. Citation2011), and British (Wilkinson et al. Citation2012) breeds, as well as African and Asian (Lyimo et al. Citation2014) breeds, whose average FIS values were above zero, and several of their loci under study displayed a departure from the HWE. Some of the possible reasons for these findings include the lack of effective breeding strategies, a small effective population size, the selection, an assortative mating system (Del Giudice Citation2009) or the existence of substructures or varieties within the population, which can all affect the HWE (Granevitze et al. Citation2007; Dalvit et al. Citation2009; Bianchi et al. Citation2011; Macri et al. Citation2019). These should be considered the main factors responsible for deviation from the HWE in the Canarian chicken population as a whole, which seems to be composed of five different varieties.
In Table , it is possible to observe the genetic diversity parameters in the five varieties; the HE ranged from 0.589 (Rubilana) to 0.666 (Negra), with a mean of 0.641, and the HO ranged from 0.551 (Rubilana) to 0.658 (Aperdizada), with a mean of 0.617. The most diverse varieties were Dorada, Jabada, Negra, and Aperdizada with the highest HE (0.635, 0.654, 0.666, and 0.664) and HO (0.612, 0.630, 0.633, and 0.658), respectively. These high heterozygosity values indicate how variable the population can be; in this case, we could say that these four varieties had great genetic diversity. The Rubilana hens had the lowest HE (0.589) and HO (0.551) in relation to the other four varieties, although the obtained values of HO and HE are not alarming enough to conclude that there is no diversity among these varieties of chicken. The mean number of alleles (MNA) in the varieties of Jabada Dorada, Jabada, Negra, and Aperdizada were very similar, ranging from 5.4 (Aperdizada) to 5.8 (Jabada and Negra), and the lowest MNA in the five varieties was the Rubilana, with 4.3.
The FIS was the only parameter that was different in the five varieties of Canary Islands chickens, ranging from 0.009 (Aperdizada) to 0.064 (Rubilana). The FIS parameter indicates the degree of inbreeding and endangerment potentiality and is considered an important tool for judging the conservation priority; it is possible to state that four hen varieties (Jabada Dorada, Jabada, Negra, and Aperdizada) had low FIS values, less than 0.05, and are not in danger (Ramadan et al. Citation2012). On the other hand, Rubilana, with an FIS value of 0.064, is a significant value and may be an indicator that breeding is not being carried out correctly; this value could be due to the fact that these varieties may be subject to artificial selection. (Silva et al. Citation2011). Previous reports and research on this population of hens from Fuerteventura Island indicate that scientists are trying to recover the autochthonous breed of hen (https://lagallinacamperacanaria.wordpress.com/author/lacamperacanaria/) by establishing groups of hens with identical phenotypic characteristics (Castro et al. Citation2002).
The FST value is indicative of the genetic differentiation between populations and intra-population (Wright Citation1951), which is obtained as a by-product from the average of the distances. From the data in Table , it is possible to observe that the hen populations of Dorada, Jabada, Jabada Negra, and Aperdizada had FST values below 0.03, with the exception of the comparison of Aperdizada with Dorada; the FST between these two populations was 0.031, and the Jabada and Negra varieties had the shortest distance (0.008). The Rubilana variety has the largest genetic distance in comparison to the other four varieties under study, and the values ranged from 0.077 (Rubilana–Aperdizada) to 0.098 (Rubilana–Dorada). With the results obtained, it could be inferred that the Rubilana variety, mainly present in two of the seven islands of the Canary Islands archipelago (Lanzarote and Fuerteventura), does have a different genetic variety, and is a different variety to the Dorada, Jabada, Jabada Negra, and Aperdizada Canarian hen varieties. Similar FST results were obtained in six Italian local chicken breeds with in situ preservation characterised using microsatellites, where several populations had a low FST between them; however, in other populations, a greater distance was found, even though they were from the same population but from different varieties (Zanetti et al. Citation2010). With these data, Reynolds’ genetic distances were created using a neighbor-joining tree (Figure ) to establish two important clusters: the first cluster is made up of the Rubilana population, and the second main cluster was subdivided into one grouping formed by the populations of Negra and Jabada and two individual populations, which are Dorada and Aperdizada.
Figure 1. Neighbor-joining tree obtained from the Reynolds’ genetic distances among five Canarian chicken varieties.
Table 3. Reynolds’ genetic distances between Canarian chicken varieties.
The partition of the genetic variation, revealed via the Analysis of Molecular Variance (AMOVA), was compared by carrying out two analyses (Table ). In the first analysis, four varieties of Canarian hens were classified (Canara Jabada Dorada, Canaria Jabada, Negra, and Canaria Aperdizada) as one population, and in the second one, we separated the varieties into two groups: Jabada Dorada, Jabada, and Negra as one group, and Aperdizada and Rubilana as an independent group. This separation into two groups was carried out because of the FST values obtained, because the Rubilana variety showed different values and was different from the other four varieties in this study. The distribution of genetic variation obtained using AMOVA (p < 0.01) in the first analysis showed that the genetic variation among populations (2.07%) and among individuals within populations was very similar (2.91%), explaining the similarity of these four varieties, which may suggest that it can be considered as one population and not as four varieties; however, the second analysis showed that the groups already behave differently, and it revealed that the genetic variation among groups was 5.91%. This value reinforces the obtained results from which we can determine that the Rubilana variety is genetically different from the four varieties being studied, suggesting that we could consider it as an independent population to the other Canarian chicken varieties. Similar results were obtained when characterising different varieties of selected Polish local chicken varieties (Antos et al. Citation2013), studying the genetic diversity, population structure of indigenous chicken ecotypes in KwaZulu-Natal (Nxumalo et al. Citation2020) and two indigenous chicken ecotypes from Pakistan (Iqbal et al. Citation2015), in the last two, some varieties were combined together as one population.
Table 4. Summary of AMOVA significant value results (p < 0.01) without a priori assumptions, defined by group 1 as one population: Canaria jabada dorada, Canaria jabada, Canaria negra, Canaria aperdizada and group 2 = 4 varieties (Canaria jabada dorada, Canaria jabada, Canaria negra, Canaria aperdizada) vs as independent group only the rubilana.
The FCA was applied to investigate and evaluate the efficiency of an objective system to assign individuals to their source populations. According to the colour of its shank and plumage, the standard breed for the Canarian chicken population distinguishes five varieties; alternatively, these varieties could be the result of genetic colour segregation or a truly genetic differentiation that subdivides the population. The results were represented by a two-dimensional plot in which its descriptive value must be taken into account. The first axis explained 46.98% of the variation and separated the Rubilana variety from the other, whereas the second axis explained 23.11% of the variation distinguishing the Negra and Jabada Dorada chickens and, finally, the third axis differentiated the Aperdizada and Jabada varieties and explained 17.49% of the variation (Figure ). In the Rubilana variety, just a few animals moved away from the centre of the grouping area; the other varieties showed that their animals were more dispersed or were even out of their grouping area. This may suggest that only the Rubilana chickens differ genetically from the rest of the Canarian varieties.
Figure 2. Factorial correspondence analysis for the five Canarian chicken varieties.
The individual DSA distance tree for the five Canarian chicken varieties (Figure ) showed three clusters: one formed by the Rubilana population, the second one formed by the Dorada population, and the last one formed by a mixture of the populations Jabada, Aperdizada, Dorada, and Negra. The Rubilana population is the only one that differs from the other hens, as can be observed from the previous analyses carried out.
Figure 3. Tree from between-individual DSA distances for the five Canarian chicken varieties.
Genetic differentiation among the Canarian chicken population, Spanish local breeds, and commercial strains, and their genetic structure
From the FST genetic distance (Table ) of the 24 populations, it can be seen that the Canary Islands populations studied (Dorada, Jabada, Jabada Negra, Aperdizada, and Rubilana) are far from the international or commercial populations (Cobb, Cornish, Leghorn, and Plymouth), indicating the preservation of this Canary Islands population, as the Canary Islands has not allowed the introduction of commercial breeds or crossbreeding (Nguyen Van et al. Citation2020). Concerning the 15 Spanish hen populations included in this study, with 9 of them (Pita Pinta, Mallorquina, Menorquina, Prat, Penedesenca, Empordanesa, Indio de Leon, Andaluza azul, and Combatiente Español), it is possible to observe how they are not genetically distant from the Canarian populations in this study. This proximity suggests a potential historical connection or gene flow between these Spanish peninsular and Canarian hen populations, highlighting the importance of considering historical and geographical factors in understanding the genetic structure of these hen populations. It is remarkable to note the short genetic distance of the Dorada, Jabada, Jabada Negra, and Aperdizada varieties from the Andalusian populations of Sureña and Utrerana Franciscana, and that this short distance is due to the fact that some of these chickens were taken to the Canary Islands on the voyages of Columbus; it is documented that Isabella the Catholic ordered Christopher Columbus to give the indigenous population a dozen hens and a cockerel to raise (Capote Citation2012). The most remarkable of the five varieties of Canarian hens in this study, the Rubilana hen, is the one that shows the greatest genetic distance among the 20 hens included in this study. Moreover, the Utrerana Franciscana population shows the minimum genetic distance from the Rubilana hen. This connection is a result of the above-mentioned Columbus voyages; during the Spanish colonisation of the Americas, the chickens that arrived in the Canary Islands came mainly from Andalusia (Rodero Serrano et al. Citation1992).
Table 5. Pairwise FST estimates between all pairs of the tested breeds (DOR, Canaria jabada dorada, JAB, Canaria jabada, NEG, Canaria negra, per, Canaria aperdizada, RUBI, Canaria rubilana, COMC, combatiente español canario, CES, combatiente español, AAZ, andaluza azul, SUR, sureña, UF, utrerana franciscana, CASN, castellana negra, EAZ extremeña azul, IND, indio de león, EMP, empodanesa, PEN, penedesenca, PRAT, Prat, IB, ibicenca, MEN, menorquina, MLL, mallorquina, PPA, pita pinta, COBB, Cobb, CORN, cornish, LEGH, leghorn, PLY, plymouth).
The FCA that was carried out for the 24 chicken populations revealed that there is still a clear grouping between the populations of the Canary Islands, including the Rubilana, which are surrounded by the populations of Prat, Utrerana Franciscana, Malloquina, Empordanesa, Ibicenca, and Extremeña Azul. The commercial hens Cobb, Cornish, and Plymouth are close to each other; the Leghorn is the only commercial population that is distant from all of the study populations, including the commercial ones (Figure ).
Figure 4. Factorial correspondence analysis for the 24 populations under study. Canaria jabada dorada (1), canaria jabada (2), canaria negra (3), canaria aperdizada(4), canaria rubilana (5), combatiente español canario (6), combatiente español (7), andaluza azul (8), sureña (9), utrerana franciscana (10), castellana negra (11), extremeña azul (12), indio de león (13), empordanesa (14), penedesenca (15), Prat (16), ibicenca (17), menorquina (18), mallorquina (19), pita pinta(20), Cobb (21), cornish (22), leghorn (23), plymouth (24).
The neighbor-net network constructed with the genetic or Nei’s DA distances between populations (Figure ) showed that the Canarian varieties are clustered together, creating a genetic trunk; the Rubilana variety was the only variety that separated and formed a single cluster out of the five populations of Canarian hens. However, over centuries, the mix between Andalusian and Portuguese breeds has created a breed that differs from its ancestors (Gama et al. Citation2020). Since the second half of the twentieth century, the introduction of commercial lines has threatened the existence of autochthonous breeds that have been displaced in favour of the former ones (Ladle and Whittaker Citation2011). This type of introduction is sometimes translated into a flow of genes between the commercial strains and the local breeds (Einum and Fleming Citation1997); nonetheless, this is not always the case, and populations could remain isolated from each other. In fact, in our study, there is no genetic proximity between the Canarian population and the commercial lines.
Figure 5. Neighbor-net obtained from the nei’s DA distances between 24 chicken populations. DOR, canaria jabada dorada, JAB, canaria jabada, NEG, canaria negra, per, canaria aperdizada, RUBI, canaria rubilana, COMC, combatiente español canario, CES, combatiente español, AAZ, andaluza azul, SUR, sureña, UF, utrerana franciscana, CASN, castellana negra, EAZ extremeña azul, IND, indio de león, EMP, empodanesa, PEN, penedesenca, PRAT, Prat, IB, ibicenca, MEN, menorquina, MLL, mallorquina, PPA, pita pinta, COBB, Cobb, CORN, cornish, LEGH, leghorn, PLY, plymouth.
The results of the structure analysis (Figure ) applied to the 24 populations demonstrated, at K = 2, show that the populations are divided into two clusters. In one cluster, there are four Spanish populations together (Combatiente Español Canario, Combatiente Español, Andaluza Azul, and Menorquina), and in the main cluster, the rest of the Spanish populations were grouped together with the commercial populations that were included in this study. When K = 11, the Combatiente Español and the Combatiente Español Canario chickens were grouped in one cluster; the five varieties under study were grouped together, including the Rubilana, which, in previous analyses, was separated from the Jabada Dorada, Jabada, Negra, and Aperdizada. It is also possible to observe that, in K = 11, all of the Spanish populations are clustered together, presenting a homogeneous structure, except the Castellana Negra, which presents a mixture of Indio de Leon and Extremeña Azul. At K = 13, which is statistically considered as the optima K, it is possible to observe that four (Jabada Dorada, Jabada, Negra, and Aperdizada) of the five Canarian varieties were separated, which reveals the genetic substructures and an admixture present between them. At this level, the Rubilana hen was already separated from the four previously mentioned varieties and presented a very homogeneous structure.
Figure 6. STRUCTURE Cluster analysis of 24 chicken populations at K = 2, 11, 13, and 24. 1, canaria jabada dorada; 2, canaria jabada; 3, canaria negra; 4, canaria aperdizada; 5, canaria rubilana; 6, combatiente español canario; 7, combatiente español; 8, andaluza azul; 9, sureña; 10, utrerana franciscana; 11, castellana negra; 12, extremeña azul; 13, indio de león; 14, empodanesa; 15, penedesenca; 16, Prat; 17, ibicenca; 18, menorquina; 19, mallorquina; 20, pita pinta; 21, Cobb; 22, cornish; 23, leghorn; 24, plymouth.
The Spanish populations present a homogeneous structure with the exception of the Utrerana Franciscana and Castellana Negra populations, suggesting potential unique genetic influences, historical factors, or environmental conditions that have led to distinctive genetic profiles in these specific populations. In K24, it is possible to observe that the Rubilana variety is separated from the rest of the four Canarian chicken populations (Jabada Dorada, Jabada, Negra, and Aperdizada). However, a minimum number of animals of this variety (Rubilana) appear with admixture among the other varieties. This could be due to the knowledge of the Canarian hen producers that the Rubilana hen is just another variety of the Canarian hens and that the result of these admixture animals was obtained by crossbreeding among the other varieties, and not, as shown in the research, that the Rubilana Canarian hen variety is apparently another population with a very strong genetic structure.
Conclusions
The Jabada Dorada, Jabada, Negra, and Aperdizada former varieties do not differ genetically from each other.
The Canary Islands populations of Jabada Dorada, Jabada, Negra, and Aperdizada are different from the rest, and it is observed that some animals have admixture between the same varieties, concluding that they could be managed as a single population with four varieties of plumage colour and that these four varieties do not differ genetically from each other. Further studies on the Rubilana population should be conducted to test its possible status as a breed.
The results of the FST, the FCA, the DSA distance tree between individuals, the neighbor-joining tree obtained from the Reynolds’ genetic distances, and the STRUCTURE cluster analysis showed with certainty how the Rubilana chicken variety differs genetically from the other Canarian chicken varieties. This study provides the first investigation of the genetic diversity of the Canarian chicken population and its genetic differentiation from Spanish landraces and commercial strains.
Therefore, according to our findings, the Canary Islands chicken population shows a differentiated genetic profile with respect to other Spanish breeds and cosmopolitan breeds, demonstrating its status as a consolidated breed from the genetic point of view. However, the theory of the existence of genetic varieties within the breed is absolutely discarded, except for the Rubilana population, which could be defined as a genetic variety. Therefore, further studies must be focused on this variety to test its possible status as a differentiated breed.
Supplemental Material
Download MS Excel (11.7 KB)Acknowledgements
This study was included in Fundación Caja Canarias and Obra Social La Caixa under Grant Project 2018PATRI31 and funded by Canarian Government and Canary Islands Institute for Agricultural Research (ICIA). This work would not have been possible if it had not been for the support and assistance of the PAIDI AGR 218 research group and Animal Breeding Consulting.
Data availability statement
Data will be made available from the corresponding author A.M.C.V. upon reasonable request.
Disclosure statement
No potential conflict of interest was reported by the authors.
References
- Abebe AS, Mikko S, Johansson AM. 2015. Genetic diversity of five local Swedish chicken breeds detected by microsatellite markers. PLoS One. 10(4):e0120580. doi: 10.1371/journal.pone.0120580.
- Antos P, Andres K, Kapkowska E. 2013. Preliminary studies on genetic diversity of selected Polish local chicken varieties. J Cent Eur Agric. 14(1):11–22. doi: 10.5513/JCEA01/14.1.1147.
- Bao W, Shu J, Musa H, Chen G. 2007. Analysis of pairwise genetic distance and its relation with geographical distance of 15 Chinese chicken breeds. Int J Trop Med. 2:107–112.
- Belkhir K. 1999. GENETIX, logiciel sous WindowsTM pour la génétique des populations. http://www univmontp2 fr/∼ genetix.
- Belkhir K. 2004. GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations. http://www genetix univ-montp2 fr/genetix/genetix htm.
- Bianchi M, Ceccobelli S, Landi V, Di Lorenzo P, Lasagna E, Ciocchetti M, Şahin E, Mugnai C, Panella F, Sarti FM. 2011. A microsatellites-based survey on the genetic structure of two Italian local chicken breeds. Ital J Anim Sci. 10(3):e39. doi: 10.4081/ijas.2011.e39.
- Capote MP. 2012. Germán González González (1940-2011). Cartas Diferentes: revista Canaria de Patrimonio Documental. 8(8):431–437.
- Castro GD, Naranjo JJ, Tosco RB, González DT, Rodríguez F. 2002. Datos sobre la distribución de aves esteparias en Tenerife y Gran Canaria, islas Canarias. Vieraea: folia Scientarum Biologicarum Canariensium.(30):177–194.
- Ceccobelli S, Di Lorenzo P, Lancioni H, Monteagudo Ibáñez LV, Tejedor MT, Castellini C, Landi V, Martínez Martínez A, Delgado Bermejo JV, Vega Pla JL, et al. 2015. Genetic diversity and phylogeographic structure of sixteen Mediterranean chicken breeds assessed with microsatellites and mitochondrial DNA. Livestock Science. 175:27–36. doi: 10.1016/j.livsci.2015.03.003.
- Ceccobelli S, Lorenzo PD, Lancioni H, Castellini C, Ibáñez LVM, Sabbioni A, Sarti FM, Weigend S, Lasagna E. 2013. Phylogeny, genetic relationships and population structure of five Italian local chicken breeds. Ital J Anim Sci. 12(3):e66. doi: 10.4081/ijas.2013.e66.
- Dalvit C, Zanetti E, Cassandro M. 2009. Estimation of genetic diversity over time in an in-situ marker assisted conservation scheme of local chicken breeds. Ital J Anim Sci. 8(sup2):63–65. doi: 10.4081/ijas.2009.s2.63.
- Dávila S, Gil M, Resino-Talaván P, Campo J. 2009. Evaluation of diversity between different Spanish chicken breeds, a tester line, and a White Leghorn population based on microsatellite markers. Poult Sci. 88(12):2518–2525. doi: 10.3382/ps.2009-00347.
- Declaration I. 2007. Global plan of action for animal genetic resources and the Interlaken Declaration. FAO Commission on Genetic Resources for Food and Agriculture, FAO: rome, Italy.
- Del Giudice M. 2009. Sex, attachment, and the development of reproductive strategies. Behav Brain Sci. 32(1):1–21. doi: 10.1017/S0140525X09000016.
- Eding H, Bennewitz J. 2007. Measuring genetic diversity in farm animals. Utilization and conservation of farm animal genetic resources (ed K Oldenbroek). Oldenbroek (NL): Genetic Resources; p. 103–130.
- Einum S, Fleming I. 1997. Genetic divergence and interactions in the wild among native, farmed and hybrid Atlantic salmon. J Fish Biol. 50(3):634–651. doi: 10.1111/j.1095-8649.1997.tb01955.x.
- Excoffier L, Laval G, Schneider S. 2006. ARLEQUIN Version 3.01. An integrated software package for population genetics data analysis Computational and Molecular Population Genetics Lab, Institute of Zoology, Switzerland: University of Berne.
- FAO. 2011. Molecular genetic characterization of animal genetic resources. Rome, Italy: FAO Animal Production and Health Guidlines.
- Fonteque GV, Battilana J, Paludo E, Lima-Rosa C. 2014. Genetic polymorphism of fifteen microsatellite loci in Brazilian (blue-egg Caipira) chickens. Pesq Vet Bras. 34(1):98–102. doi: 10.1590/S0100-736X2014000100016.
- Future trends for poultry genetic resources. Proceedings of the International Conference of Poultry in the 21st Century: Avian Influenza and beyond; 2007.
- Gama L, Martinez A, Ginja C, Cañon J, Martin-Burriel I, Revidatti M, Ribeiro M, Jordana J, Cortes O, Sevane N. 2020. Genetic diversity and structure of iberoamerican livestock breeds. Advances in Animal Health, Medicine and Production. Switzerland: Springer; p. 52–68.
- González Ariza A, Navas González FJ, León Jurado JM, Arando Arbulu A, Delgado Bermejo JV, Camacho Vallejo ME. 2022. Data Mining as a Tool to Infer Chicken Carcass and Meat Cut Quality from Autochthonous Genotypes. Animals. 12(19):2702. doi: 10.3390/ani12192702.
- mGoudet J. 2001. FSTAT 2.9. 3.2, a program to estimate and test gene diversities and fixation indices.
- Granevitze Z, Hillel J, Chen G, Cuc NTK, Feldman M, Eding H, Weigend S. 2007. Genetic diversity within chicken populations from different continents and management histories. Anim Genet. 38(6):576–583. doi: 10.1111/j.1365-2052.2007.01650.x.
- Guo X, Elston R. 1999. Linkage information content of polymorphic genetic markers. Hum Hered. 49(2):112–118. doi: 10.1159/000022855.
- Halima H, Neser F, Marle-Koster V, De Kock A. 2007. Village-based indigenous chicken production system in north-west Ethiopia. Trop Anim Health Prod. 39(3):189–197. doi: 10.1007/s11250-007-9004-6.
- Huson DH, Bryant D. 2006. Application of phylogenetic networks in evolutionary studies. Mol Biol Evol. 23(2):254–267. doi: 10.1093/molbev/msj030.
- Iqbal A, Ali A, Javed K, Akram M, Usman M, Mehmood S, Hussain J, Hussnain F. 2015. Phenotypic characterization of two indigenous chicken ecotypes of Pakistan. Journal of Animal and Plant Sciences. 25(2):346–350.
- Kalinowski ST, Taper ML, Marshall TC. 2007. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol. 16(5):1099–1106. doi: 10.1111/j.1365-294X.2007.03089.x.
- Ladle RJ, Whittaker RJ. 2011. Conservation biogeography. Oxford: Blackwell Publishing Ltd, John Wiley & Sons.
- Langella O. 1999. Populations 1.2. 28: a population genetic software. http://www pge cnrs-gif fr/bioinfo/populations/index php.
- Lenstra JA, Groeneveld LF, Eding H, Kantanen J, Williams JL, Taberlet P, Nicolazzi EL, Sölkner J, Simianer H, Ciani E, et al. 2012. Molecular tools and analytical approaches for the characterization of farm animal genetic diversity. Anim Genet. 43(5):483–502. doi: 10.1111/j.1365-2052.2011.02309.x.
- Lyimo C, Weigend A, Msoffe P, Eding H, Simianer H, Weigend S. 2014. Global diversity and genetic contributions of chicken populations from a frican, a sian and e uropean regions. Anim Genet. 45(6):836–848. doi: 10.1111/age.12230.
- Macri M, Martínez A, Landi V, Canales A, Arando A, Delgado J, Camacho M. 2019. Genetic diversity of Utrerana chicken breed. Actas Iberoamericanas de Conservación Animal. 13:52–59.
- Nei M, Tajima F, Tateno Y. 1983. Accuracy of estimated phylogenetic trees from molecular data. J Mol Evol. 19(2):153–170. doi: 10.1007/BF02300753.
- Nguyen Van D, Moula N, Moyse E, Do Duc L, Vu Dinh T, Farnir F. 2020. Productive performance and egg and meat quality of two indigenous poultry breeds in Vietnam, Ho and Dong Tao, fed on commercial feed. Animals. 10(3):408. doi: 10.3390/ani10030408.
- Nxumalo N, Ceccobelli S, Cardinali I, Lancioni H, Lasagna E, Kunene NW. 2020. Genetic diversity, population structure and ancestral origin of KwaZulu-Natal native chicken ecotypes using microsatellite and mitochondrial DNA markers. Ital J Anim Sci. 19(1):1275–1288. doi: 10.1080/1828051X.2020.1838350.
- Okumu ON, Ngeranwa J, Binepal Y, Kahi A, Bramwel W, Ateya L, Wekesa F. 2017. Genetic diversity of indigenous chickens from selected areas in Kenya using microsatellite markers. J Genet Eng Biotechnol. 15(2):489–495. doi: 10.1016/j.jgeb.2017.04.007.
- Özdemir D, Özdemir ED, Marchi MD, Cassandro M. 2013. Conservation of local Turkish and Italian chicken breeds: a case study. Ital J Anim Sci. 12(2):e49. doi: 10.4081/ijas.2013.e49.
- Page RD. 1996. Tree View: an application to display phylogenetic trees on personal computers. Comput Appl Biosci. 12(4):357–358. doi: 10.1093/bioinformatics/12.4.357.
- Park S. 2001. The Excel microsatellite toolkit. Trypanotolerance in West African Cattle and the Population Genetic Effects of Selection
- Pritchard J, Wen W, Falush D. 2004. Documentation for the STRUCTURE software Version 2. Chicago: Department of Human Genetics University of Chicago.
- Pritchard JK, Wen X, Falush D. 2010. Documentation for structure software: version 2.3. University of Chicago, Chicago, IL.p. 1–37.
- Ramadan S, Kayang BB, Inoue E, Nirasawa K, Hayakawa H, Si I, Inoue-Murayama M. 2012. Evaluation of genetic diversity and conservation priorities for Egyptian chickens.
- Rege JEO, Gibson JP. 2003. Animal genetic resources and economic development: issues in relation to economic valuation. Ecol Econ. 45(3):319–330. doi: 10.1016/S0921-8009(03)00087-9.
- Reynolds J, Weir BS, Cockerham CC. 1983. Estimation of the coancestry coefficient: basis for a short-term genetic distance. Genetics. 105(3):767–779. doi: 10.1093/genetics/105.3.767.
- Rodero Serrano E, Rodero Franganillo A, Delgado-Bermejo J. 1992. Primitive andalusian livestock and their implications in the discovery of America.
- Rodriguez-Díaz. 2010. El mito de la gallina jabada. AGROPALCA. 11:88.
- Rosenberg NA. 2004. DISTRUCT: a program for the graphical display of population structure. Molecular Ecology Notes. 4(1):137–138. doi: 10.1046/j.1471-8286.2003.00566.x.
- Rudresh B, Murthy H, Jayashankar M, Nagaraj C, Kotresh A, Byregowda S. 2015. Microsatellite based genetic diversity study in indigenous chicken ecotypes of Karnataka. Vet World. 8(8):970–976. doi: 10.14202/vetworld.2015.970-976.
- Scherf BD, Pilling D. 2015. The second report on the state of the world’s animal genetic resources for food and agriculture.
- Silva P, Lui JF, Band G, Regitano L, Grossi S, Sollero BP, Nunes C. 2011. Genetic variability among the wild boars (Sus scrofa scrofa), crossbred animals and pigs using microsatellite markers (STRs). Braz Arch Biol Technol. 54(2):301–306. doi: 10.1590/S1516-89132011000200011.
- Simianer H. 2005. Using expected allele number as objective function to design between and within breed conservation of farm animal biodiversity. J Anim Breed Genet. 122(3):177–187. doi: 10.1111/j.1439-0388.2005.00523.x.
- Torres AMA, Capote J. 2018a. La Gallina Campera Canaria/Traditional Breed of Canarian Hen. Tenerife: instituto Canario de Investigaciones Agrarias. Capítulo 2. Patrón racial de la población de gallinas Canarias/Chapter 2. Breed standard of the Canarian chicken population. p. 23–38.
- Torres AMA, Capote J. 2018b. La Gallina Campera Canaria/Traditional Breed of Canarian Hen. Tenerife: instituto Canario de Investigaciones Agrarias. Capítulo 1. Antecedentes históricos de las gallinas en Canarias/Chapter 1.The historical backgrounds of chickens in Canary Islands. p. 9–22.
- Torres A, Muth PC, Capote J, Rodríguez C, Fresno M, Zárate AV. 2019. Suitability of dual-purpose cockerels of 3 different genetic origins for fattening under free-range conditions. Poult Sci. 98(12):6564–6571. doi: 10.3382/ps/pez429.
- Walsh PS, Varlaro J, Reynolds R. 1992. A rapid chemiluminescent method for quanititation of human DNA. Nucleic Acids Res. 20(19):5061–5065. doi: 10.1093/nar/20.19.5061.
- Weigend S, Romanov MN. 2002. The World Watch List for Domestic Animal Diversity in the context of conservation and utilisation of poultry biodiversity. World’s Poult Sci J. 58(4):411–430. doi: 10.1079/WPS20020031.
- Wilkinson S, Wiener P, Teverson D, Haley C, Hocking P. 2012. Characterization of the genetic diversity, structure and admixture of British chicken breeds. Anim Genet. 43(5):552–563. doi: 10.1111/j.1365-2052.2011.02296.x.
- Wright S. 1951. The genetical structure of species. Ann Eugen. 15(323-354):747.
- Yeh FC, Yang R, Boyle T, Ye Z, Mao JX. 1999. POPGENE, version 1.32: the user friendly software for population genetic analysis. Molecular biology and biotechnology centre, University of Alberta, Edmonton, AB, Canada.
- Zanetti E, De Marchi M, Dalvit C, Cassandro M. 2010. Genetic characterization of local Italian breeds of chickens undergoing in situ conservation. Poult Sci. 89(3):420–427. doi: 10.3382/ps.2009-00324.