Genetic diversity of US Rambouillet in NSIP compared to other sheep breeds.

Assessing the genetic diversity of local breeds is essential for conserving these unique breeds, which may possess unique traits. This study provides the genomic characterisation of eight indigenous sheep breeds in Belgium based on pedigree and single nucleotide polymorphism (SNP) analysis. A total of 687 sheep were genotyped and were subjected to a rigorous quality control, resulting in a set of 45 978 autosomal SNPs. Pedigree analysis showed breed-average inbreeding estimates between 3.3% and 11.3%. The genomic analysis included an assessment of runs of homozygosity (ROH) to examine the genomic inbreeding coefficient, with breed-average inbreeding coefficients estimated between 4.1% and 8.5%. Runs of homozygosity islands were identified in six of the eight breeds studied, with some exhibiting an incidence of up to 58%. Interestingly, several ROH islands overlapped with other breeds included in this study, as well as with international sheep breeds. Pedigree-based effective population sizes were estimated below 100 for all breeds, whereas genomic-based effective population sizes were below 24, indicating that these eight local sheep breeds are endangered. Principal component analysis, admixture analyses, and Fst computations were used to study the population structure and genetic differences. A neighbour−joining tree using 95 international sheep breeds positioned the eight local breeds in the group of milksheep, Texel sheep and the Scandinavian breeds. Additionally, the investigation of paternal oY1 genotypes revealed diverse lineage origins within the Belgian sheep population. This study refines and deepens our knowledge about the local sheep breeds in Belgium, thereby improving their management and conservation. Moreover, as these breeds are linked to other international breeds, these insights are significant for the global scientific community.

Long-term sustainability of breeds depends on having sufficient genetic diversity for adaptability to change, whether driven by climatic conditions or by priorities in breeding programs. Genetic diversity in Suffolk sheep in the United States was evaluated in four ways: 1) using genetic relationships from pedigree data [(n = 64 310 animals recorded in the US National Sheep Improvement Program (NSIP)]; 2) using molecular data (n = 304 Suffolk genotyped with the OvineHD BeadChip); 3) comparing Australian (n = 109) and Irish (n = 55) Suffolk sheep to those in the United States using molecular data; and 4) assessing genetic relationships (connectedness) among active Suffolk flocks (n = 18) in NSIP. By characterizing genetic diversity, a goal was to define the structure of a reference population for use for genomic selection strategies in this breed. Pedigree-based mean inbreeding level for the most recent year of available data was 5.5%. Ten animals defined 22.8% of the current gene pool. The effective population size (Ne) ranged from 27.5 to 244.2 based on pedigree and was 79.5 based on molecular data. Expected (HE) and observed (HO) heterozygosity were 0.317 and 0.306, respectively. Model-based population structure included 7 subpopulations. From Principal Component Analysis, countries separated into distinct populations. Within the US population, flocks formed genetically disconnected clusters. A decline in genetic diversity over time was observed from both pedigree and genomic-based derived measures with evidence of population substructure as measured by FST. Using these measures of genetic diversity, a framework for establishing a genomic reference population in US Suffolk sheep engaged in NSIP was proposed.

In the late 1950s, Katahdin hair sheep were developed as a composite breed of medium size and moderate prolificacy, with potential to express resistance to gastrointestinal nematodes. With its increasing popularity and the recent adoption of genomic prediction in the Katahdin breeding program, evaluating the genetic diversity in this breed is necessary. Prediction accuracies rely on the strength of genetic relationships. That strength often increases with selection using genomically-enhanced estimated breeding values; however, it carries the risk of decreasing diversity. We aim to characterize the genetic diversity present in the breed and the subsequent impact on the accuracies of genomic predictions. Genotypes on Katahdin sheep from member flocks in the National Sheep Improvement Program were used. Data from two medium density 50k bead chips and one high density 600k bead chip were merged and limited to shared autosomal single nucleotide polymorphisms (SNP). After quality control, there were 9,705 animals and 31,984 SNP remaining. Only for analyses of inbreeding and heterozygosity, linkage disequilibrium (LD) pruning was performed; variants with an LD score exceeding 0.8 were removed with 29,904 SNP remaining. To determine the extent of population structure, principal component (PC) analysis was conducted with PC one and PC two explaining 4.9% and 3.8% of the variation in the population, respectively. When examining subpopulations, a single ancestral population explained 99.9% of the genetic variation among animals. When clustered by identity-by-state, all animals were placed in a single cluster. Inbreeding coefficients were estimated with four methods: method of moments, variance-standardized relationship minus one, excess homozygosity, and correlation between uniting gametes. Across methods, average inbreeding coefficients ranged from 1.14% to 1.20% with Pearson and Spearman correlations ranging from -0.51 to 0.91 (Table 1). Historical effective population sizes (Ne) were estimated for earlier generations, and a linear regression fit to predict more recent Ne. At the founding of the breed, historical Ne was estimated to be 310, and the current Ne was estimated to be 150. Effects of Ne on the accuracy of genomic predictions were examined for reference population sizes ranging from 1k to 25k for traits of low (0.1), moderate (0.3), and high (0.5) heritabilities. The corresponding number of effective chromosomal segments were 2NeL, where L was the length of the genome in morgans (26M). Accuracies of genomic predictions increased as the reference population size grew, with only marginal gains once the population exceeded 15k. Overall, there were no detectable genetic subpopulations in the Katahdin breed. Current levels of inbreeding were low. With a small Ne the breed can achieve high accuracy for genomic predictions by aiming for a reference population of 15k animals. Negative impacts on genetic diversity due to genomic selection are not of immediate concern.

Knowledge of past and present genetic diversity within a breed is critical for the design and optimization of breeding programs as well as the development of strategies for the conservation of genetic resources. The Polypay sheep breed was developed at the U.S. Sheep Experiment Station (USSES) in 1968 with the goal of improving productivity in Western U.S. range flocks. It has since flourished in the more intensively managed production systems throughout the U.S. The genetic diversity of the breed has yet to be documented. Therefore, the primary objective of this study was to perform a comprehensive evaluation of the genetic diversity and population structure of U.S. Polypay sheep using both pedigree- and genomic-based methods. Pedigree data from 193 Polypay flocks participating in the National Sheep Improvement Program (NSIP) were combined with pedigree records from USSES (n = 162,997), tracing back to the breed's origin. A subset of these pedigreed sheep from 32 flocks born from 2011 to 2023 were genotyped with the GGP Ovine 50K BeadChip containing 51,867 single nucleotide polymorphisms (SNPs). Four subgroups were used for the pedigree-based analyses: 1) the current generation of animals born in 2020-2022 (n = 20,701), 2) the current generation with a minimum of four generations of known ancestors (n = 12,685), 3) only genotyped animals (n = 1,856), and 4) the sires of the current generation (n = 509). Pedigree-based inbreeding for the full population was 2.2%, with a rate of inbreeding of 0.22% per generation. Pedigree-based inbreeding, Wright's inbreeding, and genomic inbreeding based on runs of homozygosity were 2.9%, 1.3%, and 5.1%, respectively, for the genotyped population. The effective population size ranged from 41 to 249 for the pedigree-based methods and 118 for the genomic-based estimate. Expected and observed heterozygosity levels were 0.409 and 0.403, respectively. Population substructure was evident based on the fixation index (FST), principal component analysis, and model-based population structure. These analyses provided evidence of differentiation from the foundation flock (USSES). Overall, the Polypay breed exhibited substantial genetic diversity and the presence of a population substructure that provides a basis for the implementation of genomic selection in the breed.

Genetic evaluation programs can provide valuable selection tools for sheep breeders. However, industry acceptance and utilization of these tools is still limited. The objective here was to evaluate the performance and value of rams enrolled in the National Sheep Improvement Program (NSIP) compared with those not enrolled during a ram test program. Rams (Katahdin = 16, Texel = 3) were delivered to the Southwest Virginia Agricultural Research and Extension Center Ram Test on May 31. Rams were dewormed and rested for two weeks. On June 21, rams were given Haemonchus contortus L3 larvae adjusted for body weight (average = 5000 L3). FAMACHA scores and fecal egg counts (FEC) were monitored every two weeks until August 30. Rams were dewormed based on FAMACHA ≥ 3. The top 50% of rams, excluding any dewormed rams, based on the sale index [Sale Index = 0.50*(0.33*average daily gain ratio + 0.67*weight per day of age ratio) + 0.50*logFEC ratio] were sold at auction as breeding stock. Rams were classified as NSIP if enrolled. Statistical analyses were performed using SAS (SAS Institute, Cary, NC). Of the19 rams on test, 52% were NSIP. Thirteen rams required deworming during the test (38% of these were NSIP rams). Average sale index of NSIP rams tended to be greater than that of non-NSIP rams (101.4 vs. 98.3, P = 0.06). Of rams with sale index ≥ 100 (top 50%), a greater percentage of these rams were NSIP vs. non-NSIP (61% vs. 39%, respectively; P < 0.05). When NSIP status was evaluated for the top 20% of rams (sale index ≥07), a greater percentage of these rams were also NSIP vs. non-NSIP (78% vs. 22%, respectively; P < 0.01). Rams (n = 57) were sold on September 23 with an average sale price of $1,482. Rams enrolled in NSIP commanded greater prices than those not enrolled ($1,659 vs. $1,222, P < 0.05). When sale price was regressed on sale index for NSIP and non-NSIP rams, R2 for NSIP rams was 0.19 compared with the R2 for non-NSIP rams of 0.76. Given the weaker relationship between price and sale index for NSIP rams, estimated breeding values (EBVs) were evaluated. NSIP rams with EBVs reported for post-weaning weight, post-weaning FEC, and Maternal Hair Index sold for greater prices than those rams missing one or all of these EBVs ($1,837 vs. $971, respectively; P < 0.05). In summary, NSIP rams had greater performance (as indicated by sale index) and value compared with non-NSIP rams. For rams enrolled in NSIP, sale index was a poor predictor of value indicating buyers may be considering other factors besides sale index, such as EBVs, when purchasing NSIP rams.

The Katahdin hair breed gained popularity in the United States as low input and prolific, with a propensity to exhibit parasite resistance. With the introduction of genomically enhanced estimated breeding values (GEBV) to the Katahdin genetic evaluation, defining the diversity present in the breed is pertinent. Utilizing pedigree records (n = 92,030) from 1984 to 2019 from the National Sheep Improvement Program, our objectives were to (i) estimate the completeness and quality of the pedigree, (ii) calculate diversity statistics for the whole pedigree and relevant reference subpopulations and (iii) assess the impact of current diversity on genomic selection. Reference 1 was Katahdins born from 2017 to 2019 (n = 23,494), while reference 2 was a subset with at least three generations of Katahdin ancestry (n = 9327). The completeness of the whole pedigree, and the pedigrees of reference 1 and reference 2, were above 50% through the fourth, fifth and seventh generation of ancestors, respectively. Effective population size (Ne) averaged 111 animals with a range from 42.2 to 451.0. The average generation interval was 2.9 years for the whole pedigree and reference 1, and 2.8 years for reference 2. The mean individual inbreeding and average relatedness coefficients were 1.62% and 0.91%, 1.74% and 0.90% and 2.94% and 1.46% for the whole pedigree, reference 1, and reference 2, respectively. There were over 300 effective founders in the whole pedigree and reference 1, with 169 in reference 2. Effective number of ancestors were over 150 for the whole pedigree and reference 1, while there were 67 for reference 2. Prediction accuracies increased as the reference population grew from 1k to 7.5k and plateaued at 15k animals. Given the large number of founders and ancestors contributing to the base genetic variation in the breed, the Ne is sufficient to maintain diversity while achieving progress with selection. Stable low rates of inbreeding and relatedness suggest that incorporating genetic conservation in breeding decisions is currently not of high priority. Current Ne suggests that with limited genotyping, high levels of accuracy for genomic prediction can be achieved. However, intense selection on GEBV may cause loss of genetic diversity long term.

Sheep breeders requested that the U.S. Sheep Experiment Station (USSES) to participate in national genetic evaluation through the National Sheep Improvement Program (NSIP). The reasons included the need for (1) a comparison of the productivity of industry and United States Department of Agriculture (USDA) lines, (2) transparency of USDA flocks, (3) genetic ties for NSIP by sampling of industry flocks, and (4) development of premium genetic lines for public release. In response, USSES began to incorporate external sires from NSIP participating flocks into the USSES Targhee flock. Our objective, based on a pedigree analysis, was to test if introgression of external genetics into the flock was achieved. The pedigree included 13,189 animals with mean maximum generations, mean complete generations, and mean equivalent complete generations of 4.2, 1.8, and 2.6, respectively. The mean generation interval was 3.1 yr. The reference population was defined as lambs born from 2021 to 2023 (n = 792). Two additional populations were defined as the current mature ewe flock (n = 123) and the current mature rams (n = 14). The Genetic Conservation Index averaged 7.7 for the full population and 25.7 for the reference population. Overall inbreeding was 0.003 for the full population and 0.006 for the reference population. The rate of inbreeding was 0.0003 per generation. Average relatedness was 0.015 for the full population and 0.018 for the reference population. The effective number of founders, effective number of ancestors, and founder genome equivalents contributing to the reference population were 60, 39, and 19.1, respectively. The ratio of the effective number of founders to the effective number of ancestors was 1.5, indicating the presence of genetic bottlenecks. Measures of effective population size ranged from 102 to 547. Of the 704 offspring produced by external sires, 17 ram lambs and 132 ewe lambs were retained for breeding. The USSES sires produced 299 offspring with 2 ram lambs and 51 ewe lambs retained. Incorporating external sires resulted in a cumulative percentage of genetic variance of 48.8, 49.1, and 44.2 of external genetics for the reference population, current mature ewe flock, and current mature rams, respectively. Stakeholder needs were addressed by introgression of external sires and participation in NSIP, but future selection practices need to be modified to maintain a minimum of 50% USSES core genetics in the flock.

ObjectiveThe main goals of this investigation were to i) assess the population structure and genetic diversity and ii) determine the efficiency of the ongoing breeding program in a closed flock of Angora rabbits through pedigree analysis.MethodsThe pedigree records of 6,145 animals, born between 1996 to 2020 at NTRS, ICAR-CSWRI, Garsa were analyzed using ENDOG version 4.8 software package. The genealogical information, genetic conservation index and parameters based on gene origin probabilities were estimated.ResultsAnalysis revealed that, 99.09% of the kits had both parents recorded in the whole dataset. The completeness levels for the whole pedigree were 99.12%, 97.12%, 90.66%, 82.49%, and 74.11% for the 1st, 2nd, 3rd, 4th, and 5th generations, respectively, reflecting well-maintained pedigree records. The maximum inbreeding, average inbreeding and relatedness were 36.96%, 8.07%, and 15.82%, respectively. The mean maximum, mean equivalent and mean completed generations were 10.28, 7.91, and 5.51 with 0.85%, 1.19%, and 1.85% increase in inbreeding, respectively. The effective population size estimated from maximum, equivalent and complete generations were 58.50, 27.05, and 42.08, respectively. Only 1.51% of total mating was highly inbred. The effective population size computed via the individual increase in inbreeding was 42.83. The effective numbers of founders (fe), ancestors (fa), founder genomes (fg) and non-founder genomes (fng) were 18, 16, 6.22, and 9.50, respectively. The fe/fa ratio was 1.12, indicating occasional bottlenecks had occurred in the population. The six most influential ancestors explained 50% of genes contributed to the gene pool. The average generation interval was 1.51 years and was longer for the sire-offspring pathway. The population lost 8% genetic diversity over time, however, considerable genetic variability still existed in the closed Angora population.ConclusionThis study provides important and practical insights to manage and maintain the genetic variability within the individual flock and the entire population.

Pedigree records of 6821 Jamunapari goats of India were collected from 1980 to 2011 and used to evaluate the population structure and genetic diversity in this flock. Animals born between 2009 and 2011 represented the current reference population. The average pedigree completeness index (PCI) and numbers of equivalent complete generations (EqG) were estimated for the entire (PCI = 0.18, EqG = 2.24) and reference (PCI = 0.31, EqG = 3.45) populations. The average generation interval was 3.33 years. The average inbreeding coefficient and the average relatedness were 0.46 and 1.06%, respectively, for the entire population and 0.77 and 3.87% for the reference population. The rate of inbreeding was 0.06% per generation. The effective population size (Ne), estimated from increases in inbreeding coefficients between the first and third equivalent complete generations, was 52.65, but periodic introductions of unrelated breeding males resulted in average inbreeding levels in the reference population that were lower than those predicted from the estimate of Ne. Effective numbers of founders (fe), ancestors (fa), founder genomes equivalents (fg), and non-founder genomes (fng) were 51, 39, 25.8, and 48.2, respectively. The fe/fa ratio in the reference population was 1.31 and indicated that occasional bottlenecks had occurred in the population. The 14 most influential ancestors contributed 50% of the genetic variability in the reference population, with a maximum individual contribution of 9.25%. Approximately 1.9% of the initial heterozygosity had been lost from the population, indicating that substantial genetic diversity still exists in this flock.

BackgroundRed dairy cattle breeds have an important role in the European dairy sector because of their functional characteristics and good health. Extensive pedigree information is available for these breeds and provides a unique opportunity to examine their population structure, such as effective population size, depth of the pedigree, and effective number of founders and ancestors, and inbreeding levels. Animals with the highest genetic contributions were identified. Pedigree data included 9,073,403 animals that were born between 1900 and 2019 from Denmark, Finland, Germany, Latvia, Lithuania, the Netherlands, Norway, Poland, and Sweden, and covered 32 breeds. The numerically largest breeds were Red Dairy Cattle and Meuse-Rhine-Yssel.ResultsThe deepest average complete generation equivalent (9.39) was found for Red Dairy Cattle in 2017. Mean pedigree completeness ranged from 0.6 for Finncattle to 7.51 for Red Dairy Cattle. An effective population size of 166 animals was estimated for the total pedigree and ranged from 35 (Rotes Höhenvieh) to 226 (Red Dairy Cattle). Average generation intervals were between 5 and 7 years. The mean inbreeding coefficient for animals born between 1960 and 2018 was 1.5%, with the highest inbreeding coefficients observed for Traditional Angler (4.2%) and Rotes Höhenvieh (4.1%). The most influential animal was a Dutch Meuse-Rhine-Yssel bull born in 1960. The mean inbreeding level for animals born between 2016 and 2018 was 2% and highest for the Meuse-Rhine-Yssel (4.64%) and Rotes Hohenvieh breeds (3.80%).ConclusionsWe provide the first detailed analysis of the genetic diversity and inbreeding levels of the European red dairy cattle breeds. Rotes Höhenvieh and Traditional Angler have high inbreeding levels and are either close to or below the minimal recommended effective population size, thus it is necessary to implement tools to monitor the selection process in order to control inbreeding in these breeds. Red Dairy Cattle, Vorderwälder, Swedish Polled and Hinterwälder hold more genetic diversity. Regarding the Meuse-Rhine-Yssel breed, given its decreased population size, increased inbreeding and low effective population size, we recommend implementation of a breeding program to prevent further loss in its genetic diversity.

ABSTRACTIn the late 1950s, Katahdin hair sheep were developed as a composite breed of medium size and moderate prolificacy, with potential to express resistance to gastrointestinal nematodes. With increasing popularity and the recent adoption of genomic prediction in their genetic evaluation, there is a risk of decreasing variation with selection based on genomically enhanced estimated breeding values. While Katahdin pedigrees are readily available for monitoring diversity, they may not capture the entirety of genetic relationships. We aimed to characterise the genomic population structure and diversity present in the breed, and how these impact the size of a reference population necessary to achieve accurate genomic predictions. Genotypes of Katahdin sheep from 81 member flocks in the National Sheep Improvement Program (NSIP) were used. After quality control, there were 9704 animals and 31,984 autosomal single nucleotide polymorphisms analysed. Population structure was minimal as a single ancestral population explained 99.9% of the genetic variation among animals. The current Ne was estimated to be 150, and despite differences in trait heritabilities, the effect of Ne on the accuracy of genomic predictions suggested the breed should aim for a reference population size of 15,000 individuals. The average degree of inbreeding estimated from runs of homozygosity (ROH) was 16.6% ± 4.7. Four genomic regions of interest, previously associated with production traits, contained ROH shared among > 50% of the breed. Based on four additional methods, average genomic inbreeding coefficients ranged from 0.011 to 0.012. The current population structure and diversity of the breed reflects genetic connectedness across flocks due to the sharing of animals. Shared regions of ROH should be further explored for incorporation of functional effects into genomic predictions to increase selection gains. Negative impacts on genetic diversity due to genomic selection are not of immediate concern for Katahdin sheep engaged in NSIP.

History, structure, and genetic diversity of Brazilian Gir cattle

Population structure of Lori-Bakhtiari sheep in Iran by pedigree analysis

Using molecular information in genetic evaluation has become routine in most livestock species. Small ruminants, however, are lagging in use of this technology, partly due to the higher cost of genotyping versus the value of the individual animal. Using a single genotyping platform to simultaneously obtain information for making genomic predictions, identifying genetic condition status, and verifying parentage avoids costs of running multiple DNA tests. Our objective was to develop and validate a process to obtain accurate genotypes for genetic conditions using a medium-density array, and to estimate their frequencies in U.S. sheep breeds. Samples (DNA) from 10,569 sheep from 9 breeds in the National Sheep Improvement Program, primarily Katahdin (8,657), Rambouillet (886), and Polypay (584), were genotyped with a commercial 50k single nucleotide polymorphism (SNP) bead chip. Genotypes for 5 genetic conditions, ovine progressive pneumonia (OPP) susceptibility (TMEM154), scrapie susceptibility (PRNP), double muscle (MSTN), callipyge (CLPG), and booroola FecB (BMPR1B), were determined using 66 SNP genotypes extracted from the bead chip. Targeted SNP markers were replicated 2 to 8 times on the array. The TMEM154 diplotypes were obtained by combining genotypes at 10 SNP markers. Variants for PRNP codon 136 and 171 were determined using 6 markers. The accuracy of assigning genetic status was validated using 15 reference DNA with known genotypes submitted blindly to the commercial laboratory. Consistency of replicated calls for an SNP was also evaluated. Following in-house laboratory-based quality control of the assay, acceptance of a genotype involved two steps. First, at least 60% of the replicated SNP on an animal needed to be assigned a genotype. Second, amongst those SNP genotyped, at least 60% needed to detect the same nucleotide. This strategy resulted in 98.4% and 90.9% of the animals having genetic status scored for PRNP and TMEM154, respectively. Where genotypes were accepted, OPP and scrapie susceptibility was assigned based on TMEM154 diplotypes and PRNP codons 136 and 171 genotypes, respectively. As shown in Table 1, genetic condition status differed appreciably among Katahdin, Polypay, and Rambouillet. Nearly 60% of Katahdins were characterized as highly susceptible to OPP while such was so in less than 15% Polypay and Rambouillet. Most (93.3%) Polypay were deemed scrapie resistant, with a majority of Katahdin (93.1%) and Rambouillet (80.6%) either resistant or rarely susceptible to this disease. However, 18.6% of Rambouillet were characterized as highly susceptible to scrapie. No animals carried the callipyge or FecB mutation. The double muscle mutation also was rare; in Katahdins, 2.7 and 0.2% of animals carried one or two copies, respectively. The approach developed accounted for genotyping inaccuracies, with full validation of genetic status. Furthermore, considerable variation in susceptibilities to OPP and scrapie was detected among breeds, which can be used in defining breeding objectives.

Elucidating genetic diversity and population structure of Alpine x Beetal goats using pedigree analysis