Explicating the genetic diversity and population structure of Saanen x Beetal goats using pedigree analysis

Abstract

Pedigree analysis is required to assess the genetic diversity and population structure of a close breeding population in order to effectively manage the breeding program and keep inbreeding under acceptable limits. Saanen x Beetal is a crossbred population of goats, reared at National Dairy Research Institute (NDRI) Karnal for the last five decades. This germplasm has been acclimated to a tropical climate and has a higher milk potential and prolificacy. Objective of this study was to elucidate the genetic diversity, population structure, and inbreeding in the flock of the Saanen x Beetal goats. The data were collected from the Animal Genetics and Breeding Division of ICAR-NDRI, Karnal for 2603 animals from the year 1971–2021. Animals born between 2014–2017 were considered as a reference cohort. Results revealed that the average generation interval was 3.44 years for the complete pedigree. The average inbreeding coefficient and the average relatedness were 4.20% and 6.87%, respectively, for the complete pedigree and 10.78% and 10.80%, for the reference population. Higher inbreeding coefficient and average relatedness in the reference cohort demonstrated impact of enclosed gene pool and demands immediate intervention for managing diversity in the closed nucleus under study. Ancestors contributing 50% of the gene pool were 8 and 3 for the complete pedigree and reference cohort, respectively, which illustrates the fact that very few ancestors were responsible for genetic diversity in the flock, which results in the decline of effective population size. Effective number of founders (f_e), ancestors (f_a), and founder genome equivalents (f_g) were 15, 7, and 3.11, respectively. The (f_e/f_a) ratio in the reference population was 2.14 indicating the occurrence of the bottleneck effect in the flock. We observed that inbreeding was non-significant for all reproductive traits except for age at first service and age at first kidding. To lessen inbreeding and augment genetic diversity in the flock, the stratified breeding plan needs to be followed, where, mate sele ction would be based on relatedness. Furthermore, introduction of unrelated Saanen and Beetal crosses will help alleviate the inbreeding accumulation.

Introduction

India is bestowed with rich genetic diversity of livestock and among them, goat has been regarded as ‘Poor Man’s Cow’ due to low cost of rearing. Goat rearing plays a key role in supplementing income to livelihood of poor livestock rearing community of rural India. According to Livestock Census 2019, total goat population is 148.88 million showing 10.78% increase in population over a decade and it also accounts for 27.74% of total livestock population in India. This figure explains increasing interest of livestock farmers towards goat rearing.

Maintaining a goat flock requires comprehensive demographic analysis which helps to scrutinise the diversification level in the population. Hence, pedigree analysis gives an overall understanding of the population which helps us to keep the level of inbreeding under acceptable limits. While selecting for favourable alleles in a population, inbreeding is desirable but it can be detrimental if exceeds beyond acceptable limits.

Under All India Coordinated Research Project (AICRP) project during early 1970s, exotic germplasm was introduced to improve indigenous breed in terms of milk production and Saanen was one of the milch goat breed used for this purpose. Saanen, an exotic goat breed and regarded as “milk queen”, originated in the historic region of Saanen valley, Switzerland whereas Beetal, an indigenous goat breed, found in districts of Gurdaspur, Amritsar and Ferozpur in Punjab. Despite of its origin in temperate region, Saanen is well adapted to the tropical climate. The cross of Saanen and Beetal goats started with the purchase of 12 Beetal goats from Government livestock Farm, Hissar, for nutritional experiment in year 1968–1969 followed by the influx of Saanen goats in 1972. Flock strength was further increased with the purchase of 12 Saanen does from Cadillac Farm, USA in the beginning of 1975. Later Beetal goats were purchased to increase flock size in subsequent years which led to Saanen x Beetal goats which are being maintained over five decades and is well adapted to the tropical climate along with higher prolificacy however no demographic studies had been carried out on this population as of now.

Hence, the present study was designed to compute the demographic parameters along with genetic diversification associated with Saanen x Beetal goats and to study the impact of inbreeding on reproductive traits.

Materials And Methods

Statistical Methods

Data obtained on the entire population of 2603 Saanen x Beetal goats (2728 males and 2928 females) were used for pedigree analysis out of which animals born between the years 2014 and 2017 were used as the reference population. This data included information such as animal, sire, dam, sex, and date of birth. Endog (v4.8) program (Gutiérrez et al., 2010) was used to analyse pedigree for demographic characterization and estimation of parameters based on probabilities of gene origin. Completeness of pedigree was assessed in order to analyze the completeness of an ancestor tracing back to several generations in a pedigree as pedigree depth is crucial for precise inbreeding estimates. If either of the parent is unknown, then less complete parental pedigree is given more weightage as compared to other parent (MacCluer et al., 1983).

Parameters estimated for each individual were: (i) Complete number of generations – described as number of generations describing offspring of the furthest generation where information related to ancestors of second- generation individual is known. (ii) Maximum number of generations - determined as the number of generations separating the individual from its ultimate ancestor. (iii) Equivalent complete generations - aggregation of (1/2)ⁿ where n stands for the number of generation which separate individual from each of its known ancestors (Maignel et al., 1996).

Generation Interval (GI) is the average age of the parents at the birth time of their progeny. Average of the four genetic pathways i.e., sire-son, sire-daughter, dam-son and dam-daughter was used to calculate the mean generation interval.

Inbreeding coefficient is the proportion of a loci carrying alleles that are identical by descent when related individuals are mated with each other (Wright, 1931). Inbreeding coefficient was calculated using formulae proposed by Meuwissen and Luo (1992). The rate of inbreeding (ΔF) can be calculated for each generation using standard formula introduced by González-Recio et al. (2007) and modified by Gutierrez et al. (2009).

Where, F is the individual inbreeding coefficient and t is the equivalent complete generation.

Average Relatedness (AR) coefficient is explained by the probability of an allele to be selected at random from the total population in pedigree belonging to a particular animal. AR coefficient is having inverse relationship with genetic variation indirectly describing the inbreeding present in the population (Goyache et al., 2003). AR can be interpreted as the representation of the animal in the whole pedigree regardless of the knowledge of its own pedigree.

Effective Population Size\(\left( \stackrel{-}{{\text{N}}_{\text{e}}}\right)\) can be explained as number of animals that bred in an idealized population which produces same amount of inbreeding in the population under study. Effective population size is an indication to describe genetic diversity in a population. The realized effective population size (N_e) was estimated as

Probabilities of gene origin assess the genetic contributions of the founders in the population. Different parameters have been described from probabilities of gene origin to explain the evolution of genetic variability in a population across generations.

Effective number of founders (fₑ) is number of equally contributing founders which is producing same genetic diversity as in population under study (Lacy, 1989). It can be calculated as

where 𝒒_𝒌 represents the probability of gene origin for ancestor k

Effective number of ancestors (𝒇_𝒂) described as the minimum number of animals either founders or non-founders, which explains complete genetic diversity in a population (Boichard et al., 2007). It can be computed as

where 𝒒_𝒋 represents marginal contribution of ancestor j, which describe about the genetic contribution made by the ancestor which was not explained by previously chosen ancestor.

Effective number of founder genome or founder genome equivalent \(\left({f}_{g}\right)\) delineate genetic variability lost owing to genetic drift in a small population in spite of equal contribution by all the founders in the population (Caballero and Toro, 2000).

It can be calculated as

where f = average co-ancestry between the individual in the reference population

In a closed nucleus flock, maintaining genetic diversity is one of the crucial components. In order to assess the diversification in the population, Genetic diversity in a population is estimated by the calculation of expected heterozygosity, where, GD = 1–1/(2f_g). Genetic diversity lost due to sampling of founder alleles can be estimated as 1/ (2f_e) which makes GD* = 1–1/(2f_e). Genetic drift occurred in the population leading to loss of genetic diversity can be estimated as (GD*-GD). Genetic conservation index (Alderson et al., 1990) is computed to quantify founder diversity in reference population. This parameter helps in conservation programme. Animal with higher GCI implies equal contributions from all ancestors and founders.

To assess the effect of inbreeding on the reproductive traits during first parity, General Linear Model (GLM) of SPSS (2005) was used. The complete dataset was used in the analysis with 725 records for age at first kidding (AFK), 634 records for age at first service (AFS), 359 records for kidding interval (KI), 365 records for service period (SP), 617 records for Gestation Length (GL), 375 records for dry period (DP), 602 records for litter weight (LW), 605 records for number of kids born (NKB) and 605 records of number of female kids born (NFKB). The statistical model included fixed effect such as year of birth, season of birth, period and season of kidding. Inbreeding was used as linear covariable (González-Recio et al., 2007) in the form of F_i.

Results And Discussion

Maximum, Complete And Equivalent Number Of Generation

Analysis revealed that maximum number of generations was 18 for Saanen x Beetal goats. We observed that 193 animals were present in base population whose ancestors couldn’t be traced back further (Table 2). Maximum number of animals were present in 6th generation i.e., 250. Average relatedness showed inclination with subsequent increase in the generations. Average relatedness percentage increased from base population (0th generation) and attained its peak at 15th generation and then decreased gradually till 18th generation. Mean inbreeding coefficient increased to maximum at 17th generation and finally reached to 11.42%. Percentage of inbred animals increased till 18th generation. Maximum inbred percentage was found in 17th and 18th generation. Saanen x Beetal goats had 5 complete generations excluding founders (0th generation) (Table 3). In the pedigree, 390 animals were present in the base population. Maximum number of animals were present in second generation and it eventually decreased till last generation. Average Inbreeding, Average inbreeding for Inbred animals and Average Relatedness increased with subsequent generation.

In Saanen x Beetal goats, mean maximum generation was found to be 6.53 which means that the average number of generations separating an offspring from its furthest ancestor was 6.53. Mean complete generation was found to be 1.68 implying number of generation tracing from offspring to all known ancestors was around 2. Increasing in inbreeding by maximum, complete and equivalent generations was 0.67%, 3.68% and 3.34% respectively. Oravcova (2013) reported mean value of complete number of generations, maximum number of generations and equivalent complete generations to be 1.97, 5.62 and 3.04 respectively in White Shorthaired goats. Mandal et al. (2021) reported mean value for complete number of generations as 1.18, maximum number of generations as 4.92 and equivalent complete generations as 2.24 in Jamunapari goats. Different estimates were obtained owing to breeding practices and population size of the flock in different breeds.

Generation Interval, Inbreeding And Average Relatedness

Generation Interval for whole population and reference population were estimated from four pathways in Saanen x Beetal goats i.e., Sire-son, Sire-daughter, Dam-son and Dam-daughter as shown in Table 4. For the whole population, Mean Generation Interval was found to be 3.44 ± 0.06 years. The pathway of Dam-son was having largest GI value i.e., 4.06 ± 0.14 years whereas pathway of Dam-Daughter were having least GI value i.e., 2.97 ± 0.07 years. For reference population, Mean Generation Interval was found to be 3.10 ± 0.15 years. Sire-Daughter pathway was having the least generation interval i.e., 2.76 ± 0.38 years whereas Dam-son pathway were having highest generation interval i.e., 4.33 ± 0.81 years.

Different estimates of generation interval were obtained for Girgentana goats as 2.5 years by Portolano et al. (2004), 1.9 years in Dutch Landrace by Mucha and Windig, (2009), 5.28 years in Brazilian Marota goats (Barros et al., 2011), 2.77 years in Spanish Murciano-Granadina goats (Oliveria et al., 2016), 2.87 years in Adani goats (Banch et al., 2020) and 3.33 years in Jamunapari goats (Mandal et al., 2021). Various estimates of generation interval observed among breeds are basically due to genetic differences among breeds along with breeding policy and management decisions carried out at farm level.

Inbreeding level shows the homozygosity of alleles in a particular population and inbreeding increases within a closed nucleus flock. In Saanen x Beetal goats, an increment in inbreeding level was observed over subsequent years due to closed nature of the flock (Fig. 1). Mean inbreeding coefficient was found to be 4.20% and 10.78% for whole and reference population respectively. These estimates were comparatively higher than the earlier mean inbreeding coefficient reported by Joezy-Shekalgorabi et al. (2017) in Adani goats as 0.24% and 0.56% whereas Mandal et al. (2021) reported average inbreeding coefficient as 0.46% and 0.77% in whole and reference population respectively. For whole population, inbred mating proportions were estimated. In Saanen x Beetal goats, 3 (0.12%) mating between full sibs, 103 (3.96%) mating between half sibs and 16 (0.61%) mating between parent-offspring was observed. Higher inbreeding level in the population also lead to higher average relatedness in the population as both measures the relatedness of an individual with other in a population. Average relatedness for the whole population and reference population were found to be 6.87% and 10.80% respectively, illustrating the fact that animals in the flock were closely related with each other as the offspring produced in this flock were used for further breeding purpose. Mandal et al. (2021) reported that average relatedness in case of Jamunapari goats was 1.06% in whole population and 3.87 in reference population. This is mainly due to the fact that the flock referred in Mandal et al. (2021) had observed several incidences of influx of Jamunapari genetics from outside the flock, however the studied flock in this report was closed throughout.

Effective Population Size

In order to deduce possible loss in genetic diversity in future, effective population size is studied. The number of animals that reproduce in an ideal population and produce the same increment in inbreeding levels in the population under study is considered the effective population size (Hill, 1979). Decline in effective population size is an indicator of loss in genetic diversity of the population. For the whole population in case of Saanen x Beetal goats, effective size obtained from regression on the birth date and effective size obtained from log regression on the birth date was 58.33 and 56.57 respectively (Table 5). According to the United Nations Food and Agriculture Organisation (FAO 1998), 50 is the figure considered as a threshold for concern. In our study, we observed that in Saanen x Beetal goats, effective population size was little over 50 nearing to the threshold level due to closed nature of the flock. These figures indicates absence of influx of outside breeding animals.

In contrast to our study, most of the review reported higher estimates for effective population size. Oravcova (2013) reported \(\stackrel{-}{{N}_{e}}\) as 182 in White Shorthaired goats. Danchin-Burge et al. (2012) reported estimates of (\(\stackrel{-}{{N}_{e}}\)) in Alpine, Saanen and Angora goats as 149,129 and 76, respectively. Similarly, estimates of \({N}_{e}\) were 84 in Markhoz goat (Rashidi et al. 2015) and 332in Raeini Cashmere goats (Mokhtari et al., 2017). Mandal et al. (2021) reported estimates of \(\stackrel{-}{{N}_{e}}\) as 210.25 in Jamunapari goats.

Ancestral Flock Diversity Analysis

Diversity analysis of ancestors gives a deep insight in to the diversification of the population. It was observed that the effective number of founders were less as compared with total number of founders illustrating the fact that only few individuals were used for subsequent breeding (Goyache et al., 2003). Effective number of founders and ancestors were found to be 22 and 20, respectively. These findings further explain the fact that although the main objective was to select superior germplasm for breeding purpose, it ultimately led to limiting the genetic diversity of the population. Due to the use of lesser number of individuals for subsequent breeding, the genetic diversity in the population is chiefly contributed by these individuals. These findings also explain about increase in inbreeding coefficient and average relatedness in the population along with decline in genetic diversity and allelic loss due to genetic drift. Hence, this population parameter provides useful information in formulating strategies to keep inbreeding under acceptable limits. Ratio of \({f}_{e}/ f\) gives a clear idea about the disequilibrium observed in founders contribution to the population. Estimates of \({f}_{e}/ f\) was found to be 0.79 in Saanen x Beetal goats. Other estimates of \({f}_{e}/ f\) reported were 0.25 in Girgentana goats (Portolano et al., 2004), 0.26 in White Shorthaired goats by Oravcova (2013), 0.46 in Markhoz goat (Rashidi et al., 2015), 0.23 in Cashmere goats (Joezy-Shekalgorabi et al., 2016), 0.14 in Adani goats (Baneh et al., 2020) and 0.14 in Jamunapari goats (Mandal et al., 2021).

Boichard et al. (1997) explained that ratio of \({f}_{e}/{f}_{a}\) describes loss of genetic diversity that occurred in the population due to existence of bottleneck effect. If the ratio of \({f}_{e}/{f}_{a}\) exceeds 1, it indicates the occurrence of bottleneck effect in the population resulting in reduction of diversification across the population. For the whole population and the reference population of Saanen x Beetal goats, the ratio of \({f}_{e}/{f}_{a}\) was 1.1 and 2.14, respectively. Effective number of ancestors includes both founders and non-founders; if effective number of ancestors is smaller than effective number of founders, genetic diversification is constrained due to the use of a small number of individuals, causing a bottleneck effect in the population. Similar estimates of \({f}_{e}/{f}_{a}\) such as 1.6 was observed in White Shorthaired goats by Oravcova (2013), 2.38 in Boer goats (Menezes et al., 2015), 1.32 in Markhoz goat (Rashidi et al., 2015), 1.76 in Raeini Cashmere goats (Mokhtari et al., 2017) and 1.31 in Jamunapari goats (Mandal et al., 2021).

Effective number of founder genomes, or founder genome equivalent, describes the genetic diversity that has been lost during genetic drift in a small population size even after equal contributions from founders and ancestors in a population. The estimate for f_g in reference population was 3.11 in Saanen x Beetal goats. Higher estimates for effective number of founder genome ( \({\text{f}}_{\text{g}}\)) was found to be 32 in White Shorthaired goats as reported by Oravcova (2013). Moreover, \({\text{f}}_{\text{g}}\) value reported were 26 in Markhoz goat (Rashidi et al., 2015), 42.7 in Cashmere goat (Joezy-Shekalgorabi et al., 2016), 32.01 in Adani goat (Joezy-Shekalgorabi et al., 2017) and 25.8 in Jamunapari goat (Mandal et al., 2021). Estimates of f_e/f_g was found to be 2.1 that explained the genetic drift occurred in the population. The estimate for f_g/f_a in reference population was 0.44, which indicates that 44 % o the original ancestral genetic diversity is present in the reference population. This estimate was low when compared with other report in Jamunapari goat by Mandal et al. (2021), where f_g/f_a was 0.66.

Population parameters explaining genetic diversity in the reference population are presented in Table 5. A total of 62 founder animals were identified which contributed to reference population, but the effective number of founders (f_e) was only 15. The effective number of ancestors (f_a) was 7 in reference population. Number of ancestors contributing variability up to 50%, 75% and 100% of the gene pool in whole population were 8, 24, and 261, respectively. Thus, only 8 ancestors were responsible for the 50% variability of the population (Fig. 2). Genetic Conservation Index (GCI) is a population parameter helps in quantifying founders diversity. It also helps in maintaining allelic richness in a population. Higher GCI value implies that the animal is important for conservation purpose. In Saanen x Beetal goats, mean GCI for all animals, males and female in whole population were 4.72, 2.30 and 2.42 respectively (Fig. 3). In contrast to our study, higher estimate was observed for average GCI as 7.35 in Boer goat (Menezes et al., 2015), but lower estimates were also reported such as 1.64 in Murciano-Granadina goats (Oliveria et al., 2016), 2.57 in Adani goat (Baneh et al., 2020) and 3.99 in Jamunapari goats (Mandal et al., 2021).

Estimates of GD and GD* were 0.84 and 0.96, respectively. Estimate of GD*-GD revealed 12% loss in genetic diversity in this population. It actually estimated proportion of retained genetic diversity (i.e., heterozygosity) in the reference population (GD) and the proportion of retained diversity associated only with the sampling of founders (GD*). The difference (GD* − GD) estimates which was 12% in heterozygosity can be associated with genetic drift and bottleneck effect in Saanen x Beetal goats.

Impact Of Inbreeding On Reproductive Traits In Saanen X Beetal Goats

While selecting superior germplasm, animals having better genetic merit are selected for further breeding which leads to selection of specific alleles responsible for the genetic makeup of the animal. Selecting those alleles change genetic composition of whole population and hence alleles are fixed with subsequent selection for a particular trait of interest which leads to accumulation of inbreeding in the population. Hence, inbreeding up to certain extent is desirable until it negatively affects the performance status of the animal. Since this goat flock has been maintained for over 50 years, we tried to study the impact of inbreeding on reproductive traits in Saanen x Beetal goats. We observed non-significant effect of inbreeding on all reproductive traits except age at first service (AFS) and age at first kidding (AFK), where F_i influenced AFS and AFK significantly (P < 0.01) in unfavourable direction. Similar reports are available in literature where significant change in the trait phenotype in small ruminants were observed (Prince et al., 2008; Barczak et al., 2009; Pedrosa et al., 2010; Gowane et al. 2010; Gowane et al. 2013; Gowane et al. 2014). Least squares analysis revealed that for AFS and AFK, the period and season of birth were also significant sources of variation in addition to inbreeding with the R² estimate of 16.6% and 13.1%, respectively (Table 6).

Conclusion

The Saanen x Beetal goat flock is a stabilised crossbred population that is adapted to a subtropical climate and has a great genetic potential for milk production as well as prolificacy. Increase in inbreeding and average relatedness in the flock for over five decades were caused by closed nucleus breeding program and lack of genetic influx for over five decades. We foresee that this goat flock is nearing the threshold of effective population size and likely to witness bottleneck effect in near future. In order to maintain genetic diversity and further improvement in genetic makeup of the population, we propose to manage the scientific practices of breeding in the present flock. We also recommend breeding of distantly related individuals on the basis of AR estimate to avoid close breeding. Moreover, introduction of Saanen germplasm along with indigenous Beetal goats for making their first cross and introducing them into the herd will further help us to manage inbreeding and increase genetic diversity of the population.

Declarations

CONSENT FOR PUBLICATION

All authors gave their consent for the publication of the results obtained in this study.

ACKNOWLEDGEMENTS

Authors duly acknowledge the support provided by the Director ICAR-National Dairy Research Institute and Head Animal Genetics & Breeding Division for providing the necessary facilities in the lab for carrying out the above work. Authors are also thankful to the research staff and workers in the LRC and record room of AGB division.

AUTHORS’ CONTRIBUTIONS

SS carried out the analysis and also prepared the manuscript draft. RA, SM and VV helped in editing of the manuscript. GRG conceived the idea, supervised the first author, helped in analysis and edited the draft.

CONFLICT OF INTEREST

The authors declare that they have no competing interests.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

This study did not require the ethics committee approval as no material derived from animals was used in this study.

DATA AVAILABILITY STATEMENT

The authors affirm that all data necessary for confirming the conclusions of the article are present within the article, figure, and tables. 

FUNDING

This study did not receive any funding.

ORCID

G. R. Gowane http://orcid.org/0000-0001-6535-7818

Shweta Sahoo https://orcid.org/0000-0002-5154-5719

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