DNA methylation episignature, extension of the clinical features, and comparative epigenomic profiling of Hao-Fountain syndrome caused by variants in USP7.

PURPOSE: Hao-Fountain syndrome (HAFOUS) is a neurodevelopmental disorder caused by pathogenic variants in USP7. HAFOUS is characterized by developmental delay, intellectual disability, speech delay, behavioral abnormalities, autism spectrum disorder, seizures, hypogonadism, and mild dysmorphic features. We investigated the phenotype of 18 participants with HAFOUS and performed DNA methylation (DNAm) analysis, aiming to generate a diagnostic biomarker. Furthermore, we performed comparative analysis with known episignatures to gain more insight into the molecular pathophysiology of HAFOUS. METHODS: We assessed genomic DNAm profiles of 18 individuals with pathogenic variants and variants of uncertain significance (VUS) in USP7 to map and validate a specific episignature. The comparison between the USP7 cohort and 56 rare genetic disorders with earlier reported DNAm episignatures was performed with statistical and functional correlation. RESULTS: We mapped a sensitive and specific DNAm episignature for pathogenic variants in USP7 and utilized this to reclassify the VUS. Comparative epigenomic analysis showed evidence of HAFOUS similarity to a number of other rare genetic episignature disorders. CONCLUSION: We discovered a sensitive and specific DNAm episignature as a robust diagnostic biomarker for HAFOUS that enables VUS reclassification in USP7. We also expand the phenotypic spectrum of 9 new and 5 previously reported individuals with HAFOUS.

Identification of DNA methylation episignature for the intellectual developmental disorder, autosomal dominant 21 syndrome, caused by variants in the CTCF gene.

PURPOSE: The main objective of this study was to assess clinical features and genome-wide DNA methylation profiles in individuals affected by intellectual developmental disorder, autosomal dominant 21 (IDD21) syndrome, caused by variants in the CCCTC-binding factor (CTCF) gene. METHODS: DNA samples were extracted from peripheral blood of 16 individuals with clinical features and genetic findings consistent with IDD21. DNA methylation analysis was performed using the Illumina Infinium Methylation EPIC Bead Chip microarrays. The methylation levels were fitted in a multivariate linear regression model to identify the differentially methylated probes. A binary support vector machine classification model was constructed to differentiate IDD21 samples from controls. RESULTS: We identified a highly specific, reproducible, and sensitive episignature associated with CTCF variants. Six variants of uncertain significance were tested, of which 2 mapped to the IDD21 episignature and clustered alongside IDD21 cases in both heatmap and multidimensional scaling plots. Comparison of the genomic DNA methylation profile of IDD21 with that of 56 other neurodevelopmental disorders provided insights into the underlying molecular pathophysiology of this disorder. CONCLUSION: The robust and specific CTCF/IDD21 episignature expands the growing list of neurodevelopmental disorders with distinct DNA methylation profiles, which can be applied as supporting evidence in variant classification.

Expanding the application of haplotype-based genomic predictions to the wild: A case of antibody response against Teladorsagia circumcincta in Soay sheep.

BACKGROUND: Genomic prediction of breeding values (GP) has been adopted in evolutionary genomic studies to uncover microevolutionary processes of wild populations or improve captive breeding strategies. While recent evolutionary studies applied GP with individual single nucleotide polymorphism (SNP), haplotype-based GP could outperform individual SNP predictions through better capturing the linkage disequilibrium (LD) between the SNP and quantitative trait loci (QTL). This study aimed to evaluate the accuracy and bias of haplotype-based GP of immunoglobulin (Ig) A (IgA), IgE, and IgG against Teladorsagia circumcincta in lambs of an unmanaged sheep population (Soay breed) based on Genomic Best Linear Unbiased Prediction (GBLUP) and five Bayesian [BayesA, BayesB, BayesCπ, Bayesian Lasso (BayesL), and BayesR] methods. RESULTS: The accuracy and bias of GPs using SNP, haplotypic pseudo-SNP from blocks with different LD thresholds (0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1.00), or the combinations of pseudo-SNPs and non-LD clustered SNPs were obtained. Across methods and marker sets, higher ranges of genomic estimated breeding values (GEBV) accuracies were observed for IgA (0.20 to 0.49), followed by IgE (0.08 to 0.20) and IgG (0.05 to 0.14). Considering the methods evaluated, up to 8% gains in GP accuracy of IgG were achieved using pseudo-SNPs compared to SNPs. Up to 3% gain in GP accuracy for IgA was also obtained using the combinations of the pseudo-SNPs with non-clustered SNPs in comparison to fitting individual SNP. No improvement in GP accuracy of IgE was observed using haplotypic pseudo-SNPs or their combination with non-clustered SNPs compared to individual SNP. Bayesian methods outperformed GBLUP for all traits. Most scenarios yielded lower accuracies for all traits with an increased LD threshold. GP models using haplotypic pseudo-SNPs predicted less-biased GEBVs mainly for IgG. For this trait, lower bias was observed with higher LD thresholds, whereas no distinct trend was observed for other traits with changes in LD. CONCLUSIONS: Haplotype information improves GP performance of anti-helminthic antibody traits of IgA and IgG compared to fitting individual SNP. The observed gains in the predictive performances indicate that haplotype-based methods could benefit GP of some traits in wild animal populations.

A chromosome-level genome assembly reveals genomic characteristics of the American mink (Neogale vison).

Availability of a contiguous chromosome-level genome assembly is the foundational step to develop genome-based studies in American mink (Neogale vison). The main objective of this study was to provide a high quality chromosome-level genome assembly for American mink. An initial draft of the genome assembly was generated using 2,884,047 PacBio long reads. Integration of Hi-C data into the initial draft led to an assembly with 183 scaffolds and scaffold N50 of 220 Mb. This gap-free genome assembly of American mink (ASM_NN_V1) had a length of 2.68 Gb in which about 98.6% of the whole genome was covered by 15 chromosomes. In total, 25,377 genes were predicted across the American mink genome using the NCBI Eukaryotic Genome Annotation Pipeline. In addition, gene orthology, demographic history, synteny blocks, and phylogenetic relationships were studied in connection with the genomes of other related Carnivora. Furthermore, population-based statistics of 100 sequenced mink were presented using the newly assembled genome. Remarkable improvements were observed in genome contiguity, the number of scaffolds, and annotation compared to the first draft of mink genome assembly (NNQGG.v01). This high-quality genome assembly will support the development of efficient breeding strategies as well as conservation programs for American mink.

Genome-Wide Detection of Selection Signatures for Pelt Quality Traits and Coat Color Using Whole-Genome Sequencing Data in American Mink.

Domestication and selection are the major driving forces responsible for creating genetic variability in farmed species. American mink has been under selection for more than 100 years for improved body size and pelt quality. This study aimed to identify the genomic regions subjected to selection for pelt quality traits, and coat color using the whole genome sequences of 100 mink raised in the Canadian Centre for Fur Animal Research (CCFAR) at Dalhousie Agriculture Campus (Truro, NS, Canada), and Millbank fur farm (Rockwood, ON, Canada). Measurements of three dried pelt characteristics (including pelt size (n = 35), overall quality of fur (n = 27), and nap size (n = 29)), and three coat color of Black, Stardust, and Pastel (Stardust_ Black (n = 38), and Pastel_Black (n = 41)) were used to assign animals to pairwise groups. Signatures of selection were detected using integrated measurement of fixation index (Fst), extended haplotype homozygosity (XP-EHH), and nucleotide diversity (θπ) tests. In total, overlapping top 1% of Fst and XP-EHH harbored 376 genes for pelt quality traits (110 for nap size, 163 for overall quality of fur, and 98 pelt size), and 194 genes for coat color (123 for Pastel_Black and 71 for Stardust_Black) were detected in different groups. Integrating results of Fst, and XP-EHH with the θπ test supported 19 strongly selected regions on chromosomes 3, 4, 5, 6, 7, 8, 9, and 10 that contained 33 candidate genes related to fur quality, hair follicle function, and pelt size traits. Gene ontology revealed numerous genes related to the hair cycle process and molting cycle process, epidermis development, Wnt signaling pathway and muscle development. This study provided the first map of putative selection signals related to pelt quality and coat color in American mink, which could be used as a reference for future studies attempting to identify genes associated with economically important traits in mink.

Genetic and Phenotypic Parameters for Pelt Quality and Body Length and Weight Traits in American Mink.

Understanding the genetics of fur characteristics and skin size is important for developing effective breeding programs in the mink industry. Therefore, the objectives of this study were to estimate the genetic and phenotypic parameters for pelt quality traits including live grading overall quality (LQU), live grading nap size (LNAP), dried pelt size (DPS), dried pelt nap size (DNAP) and overall quality of dried pelt (DQU), and body length and weight traits, including November body weight (Nov_BW), November body length (Nov_BL), harvest weight (HW) and harvest length (HL) in American mink. Dried pelt quality traits on 1195 mink and pelt quality traits on live animals on 1680 were collected from mink raised at two farms, in Nova Scotia and Ontario. A series of univariate analyses were implemented in ASReml 4.1 software to identify the significance (p < 0.05) of random effects (maternal genetic effects, and common litter effects) and fixed effects (farm, sex, color type, year, and age) for each trait. Subsequently, bivariate models were used to estimate the genetic and phenotypic parameters using ASReml 4.1. Heritability (±SE) estimates were 0.41 ± 0.06 for DPS, 0.23 ± 0.10 for DNAP, 0.12 ± 0.04 for DQU, 0.28 ± 0.06 for LQU, 0.44 ± 0.07 for LNAP, 0.29 ± 0.10 for Nov_BW, 0.28 ± 0.09 for Nov_BL, 0.41 ± 0.07 for HW and 0.31 ± 0.06 for HL. DPS had high positive genetic correlations (±SE) with Nov_BW (0.89 ± 0.10), Nov_BL (0.81 ± 0.07), HW (0.85 ± 0.05) and HL (0.85 ± 0.06). These results suggested that body weight and length measured on live animals in November of the first year were reliable indicators of dried pelt size. DQU had favorable genetic correlations with Nov_BL (0.55 ± 0.24) and HL (0.46 ± 0.20), and nonsignificant genetic correlations with DNAP (0.13 ± 0.25), Nov_BW (0.25 ± 0.25) and HW (0.06 ± 0.20), which made body length traits an appealing trait for selection for increased pelt size. High positive genetic correlation (±SE) was observed between LNAP and DNAP (0.82 ± 0.22), which revealed that nap size measurement on live animals is a reliable indicator trait for dried pelt nap size. However, nonsignificant (p > 0.05) low genetic correlation (±SE) was obtained between LQU and DQU (0.08 ± 0.45), showing that indirect selection based on live grading might not lead to the satisfactory improvement of dried pelt overall quality. The estimated genetic parameters for live grading, dried pelt quality, and body weight and body length traits may be incorporated into breeding programs to improve fur characteristics in Canadian mink populations.

Genome-wide detection of copy number variation in American mink using whole-genome sequencing.

BACKGROUND: Copy number variations (CNVs) represent a major source of genetic diversity and contribute to the phenotypic variation of economically important traits in livestock species. In this study, we report the first genome-wide CNV analysis of American mink using whole-genome sequence data from 100 individuals. The analyses were performed by three complementary software programs including CNVpytor, DELLY and Manta. RESULTS: A total of 164,733 CNVs (144,517 deletions and 20,216 duplications) were identified representing 5378 CNV regions (CNVR) after merging overlapping CNVs, covering 47.3 Mb (1.9%) of the mink autosomal genome. Gene Ontology and KEGG pathway enrichment analyses of 1391 genes that overlapped CNVR revealed potential role of CNVs in a wide range of biological, molecular and cellular functions, e.g., pathways related to growth (regulation of actin cytoskeleton, and cAMP signaling pathways), behavior (axon guidance, circadian entrainment, and glutamatergic synapse), lipid metabolism (phospholipid binding, sphingolipid metabolism and regulation of lipolysis in adipocytes), and immune response (Wnt signaling, Fc receptor signaling, and GTPase regulator activity pathways). Furthermore, several CNVR-harbored genes associated with fur characteristics and development (MYO5A, RAB27B, FGF12, SLC7A11, EXOC2), and immune system processes (SWAP70, FYN, ORAI1, TRPM2, and FOXO3). CONCLUSIONS: This study presents the first genome-wide CNV map of American mink. We identified 5378 CNVR in the mink genome and investigated genes that overlapped with CNVR. The results suggest potential links with mink behaviour as well as their possible impact on fur quality and immune response. Overall, the results provide new resources for mink genome analysis, serving as a guideline for future investigations in which genomic structural variations are present.

Weighted Single-Step GWAS for Body Mass Index and Scans for Recent Signatures of Selection in Yorkshire Pigs.

Controlling extra fat deposition is economically favorable in modern swine industry. Understanding the genetic architecture of fat deposition traits such as body mass index (BMI) can help in improving genomic selection for such traits. We utilized a weighted single-step genome-wide association study (WssGWAS) to detect genetic regions and candidate genes associated with BMI in a Yorkshire pig population. Three extended haplotype homozygosity (EHH)-related statistics were also incorporated within a de-correlated composite of multiple signals (DCMS) framework to detect recent selection signatures signals. Overall, the full pedigree consisted of 7016 pigs, of which 5561 had BMI records and 598 pigs were genotyped with an 80 K single nucleotide polymorphism (SNP) array. Results showed that the most significant windows (top 15) explained 9.35% of BMI genetic variance. Several genes were detected in regions previously associated with pig fat deposition traits and treated as potential candidate genes for BMI in Yorkshire pigs: FTMT, SRFBP1, KHDRBS3, FOXG1, SOD3, LRRC32, TSKU, ACER3, B3GNT6, CCDC201, ADCY1, RAMP3, TBRG4, CCM2. Signature of selection analysis revealed multiple candidate genes previously associated with various economic traits. However, BMI genetic variance explained by regions under selection pressure was minimal (1.31%). In conclusion, candidate genes associated with Yorkshire pigs' BMI trait were identified using WssGWAS. Gene enrichment analysis indicated that the identified candidate genes were enriched in the insulin secretion pathway. We anticipate that these results further advance our understanding of the genetic architecture of BMI in Yorkshire pigs and provide information for genomic selection for fat deposition in this breed.

Genetic and phenotypic parameters for Aleutian disease tests and their correlations with pelt quality, reproductive performance, packed-cell volume, and harvest length in mink.

Aleutian disease (AD), caused by the Aleutian mink disease virus (AMDV), is a major health concern that results in global economic losses to the mink industry. The unsatisfactory outcome of the culling strategy, immunoprophylaxis, and medical treatment in controlling AD have urged mink farmers to select AD resilient mink based on several detection tests, including enzyme-linked immunosorbent assay (ELISA), counterimmunoelectrophoresis (CIEP), and iodine agglutination test (IAT). However, the genetic analysis of these AD tests and their correlations with pelt quality, reproductive performance, packed-cell volume (PCV), and harvest length (HL) have not been investigated. In this study, data on 5,824 mink were used to estimate the genetic and phenotypic parameters of four AD tests, including two systems of ELISA, CIEP, and IAT, and their genetic and phenotypic correlations with two pelt quality, five female reproductive performance, PCV, and HL traits. Significances (P < 0.05) of fixed effects (sex, year, dam age, and color type), covariates (age at harvest and blood sampling), and random effects (additive genetic, permanent environmental, and maternal effects) were determined under univariate models using ASReml 4.1 software. The genetic and phenotypic parameters for all traits were estimated under bivariate models using ASReml 4.1 software. Estimated heritabilities (±SE) were 0.39 ± 0.06, 0.61 ± 0.07, 0.11 ± 0.07, and 0.26 ± 0.05 for AMDV antigen-based ELISA (ELISA-G), AMDV capsid protein-based ELISA, CIEP, and IAT, respectively. The ELISA-G also showed a moderate repeatability (0.58 ± 0.04) and had significant negative genetic correlations (±SE) with reproductive performance traits (from -0.41 ± 0.16 to -0.49 ± 0.12), PCV (-0.53 ± 0.09), and HL (-0.45 ± 0.16). These results indicated that ELISA-G had the potential to be applied as an indicator trait for genetic selection of AD resilient mink in AD endemic ranches and therefore help mink farmers to reduce the adverse effects caused by AD.

Population Genomics of American Mink Using Whole Genome Sequencing Data.

Characterizing the genetic structure and population history can facilitate the development of genomic breeding strategies for the American mink. In this study, we used the whole genome sequences of 100 mink from the Canadian Centre for Fur Animal Research (CCFAR) at the Dalhousie Faculty of Agriculture (Truro, NS, Canada) and Millbank Fur Farm (Rockwood, ON, Canada) to investigate their population structure, genetic diversity and linkage disequilibrium (LD) patterns. Analysis of molecular variance (AMOVA) indicated that the variation among color-types was significant (p < 0.001) and accounted for 18% of the total variation. The admixture analysis revealed that assuming three ancestral populations (K = 3) provided the lowest cross-validation error (0.49). The effective population size (Ne) at five generations ago was estimated to be 99 and 50 for CCFAR and Millbank Fur Farm, respectively. The LD patterns revealed that the average r2 reduced to <0.2 at genomic distances of >20 kb and >100 kb in CCFAR and Millbank Fur Farm suggesting that the density of 120,000 and 24,000 single nucleotide polymorphisms (SNP) would provide the adequate accuracy of genomic evaluation in these populations, respectively. These results indicated that accounting for admixture is critical for designing the SNP panels for genotype-phenotype association studies of American mink.

Detection of selection signatures for response to Aleutian mink disease virus infection in American mink.

Aleutian disease (AD) is the most significant health issue for farmed American mink. The objective of this study was to identify the genomic regions subjected to selection for response to infection with Aleutian mink disease virus (AMDV) in American mink using genotyping by sequencing (GBS) data. A total of 225 black mink were inoculated with AMDV and genotyped using a GBS assay based on the sequencing of ApeKI-digested libraries. Five AD-characterized phenotypes were used to assign animals to pairwise groups. Signatures of selection were detected using integrated measurement of fixation index (FST) and nucleotide diversity (θπ), that were validated by haplotype-based (hap-FLK) test. The total of 99 putatively selected regions harbouring 63 genes were detected in different groups. The gene ontology revealed numerous genes related to immune response (e.g. TRAF3IP2, WDR7, SWAP70, CBFB, and GPR65), liver development (e.g. SULF2, SRSF5) and reproduction process (e.g. FBXO5, CatSperß, CATSPER4, and IGF2R). The hapFLK test supported two strongly selected regions that contained five candidate genes related to immune response, virus-host interaction, reproduction and liver regeneration. This study provided the first map of putative selection signals of response to AMDV infection in American mink, bringing new insights into genomic regions controlling the AD phenotypes.

Linkage Disequilibrium, Effective Population Size and Genomic Inbreeding Rates in American Mink Using Genotyping-by-Sequencing Data.

Knowledge of linkage disequilibrium (LD) patterns is necessary to determine the minimum density of markers required for genomic studies and to infer historical changes as well as inbreeding events in the populations. In this study, we used genotyping-by-sequencing (GBS) approach to detect single nucleotide polymorphisms (SNPs) across American mink genome and further to estimate LD, effective population size (Ne), and inbreeding rates based on excess of homozygosity (FHOM) and runs of homozygosity (ROH). A GBS assay was constructed based on the sequencing of ApeKI-digested libraries from 285 American mink using Illumina HiSeq Sequencer. Data of 13,321 SNPs located on 46 scaffolds was used to perform LD analysis. The average LD (r 2 ± SD) between adjacent SNPs was 0.30 ± 0.35 over all scaffolds with an average distance of 51 kb between markers. The average r 2 < 0.2 was observed at inter-marker distances of >40 kb, suggesting that at least 60,000 informative SNPs would be required for genomic selection in American mink. The Ne was estimated to be 116 at five generations ago. In addition, the most rapid decline of population size was observed between 100 and 200 generations ago. Our results showed that short extensions of homozygous genotypes (500 kb to 1 Mb) were abundant across the genome and accounted for 33% of all ROH identified. The average inbreeding coefficient based on ROH longer than 1 Mb was 0.132 ± 0.042. The estimations of FHOM ranged from -0.44 to 0.34 among different samples with an average of 0.15 over all individuals. This study provided useful insights to determine the density of SNP panel providing enough statistical power and accuracy in genomic studies of American mink. Moreover, these results confirmed that GBS approach can be considered as a useful tool for genomic studies in American mink.

Opportunities for genomic selection in American mink: A simulation study.

Genomic selection can be considered as an effective tool for developing breeding programs in American mink. However, the genetic gains for economically important traits can be influenced by the accuracy of genomic predictions. The objective of this study was to investigate the prediction accuracies of traditional best linear unbiased prediction (BLUP), multi-step genomic BLUP (GBLUP) and single-step GBLUP (ssGBLUP) methods in American mink using simulated data with different levels of heritability, marker density, training set (TS) sizes and selection designs based on either phenotypic performance or estimated breeding values (EBVs). Under EBV selection design, the accuracy of BLUP predictions was increased by 38% and 44% for h2 = 0.10, 27% and 29% for h2 = 0.20, and 5.8% and 6% for h2 = 0.50 using GBLUP and ssGBLUP methods, respectively. Under phenotypic selection design, the accuracies of prediction by ssGBLUP method were 11.8% and 15.4% higher than those obtained by GBLUP for heritability of 0.10 and 0.20, respectively. However, the efficiency of ssGBLUP and GBLUP was not influenced by selection design at higher level of heritability (h2 = 0.50). Furthermore, higher selection intensity increased the bias of predictions in both pedigree-based and genomic evaluations. Regardless of selection design, TS sizes for GBLUP and ssGBLUP methods should be at least 3000 to achieve more accuracy than using BLUP for heritability of 0.50 and marker density of 10k and 50k. Overall, more accurate predictions were obtained using ssGBLUP method particularly for lowly heritable traits and low density of markers. Our results indicated that TS sizes should be optimized in accordance with heritability level, marker density, selection design and prediction method for genomic selection in American mink. The results provided an initial framework for designing genomic selection in mink breeding programs.

Genetic and phenotypic parameters for litter size, survival rate, gestation length, and litter weight traits in American mink.

The economic efficiency of mink production is greatly influenced by reproductive performance. Therefore, the objective of this study was to estimate phenotypic and genetic parameters for reproduction traits including total number of kits born (TB), number of live kits at birth (LB), number of live kits at weaning (LW), survival rate at birth (SB), survival rate at weaning (SW), gestation length (GL), average kit weight per litter at birth (AWB), average kit weight per litter at week 3 (AW3), and average kit weight per litter at weaning (AWW) in American mink. Data included records of 3,046 litters collected by the Canadian Centre for Fur Animal Research at Dalhousie Faculty of Agriculture between 2002 and 2016. Significance (P < 0.05) of fixed effects (year, number of matings, color type, age of dam, origin of dam, sex ratio, and number of live kits) and random effects of permanent environment were determined using univariate repeatability models. A significant effect of permanent environment was only found for survival rate traits (P < 0.05). Subsequently, genetic and phenotypic parameters for all traits were estimated by fitting a set of bivariate models using ASREML 4.0. Heritabilities (± SE) were estimated to be 0.07 ± 0.03 for TB, 0.07 ± 0.02 for LB, 0.09 ± 0.04 for LW, 0.13 ± 0.03 for SB, 0.10 ± 0.02 for SW, 0.29 ± 0.03 for GL, 0.28 ± 0.05 for AWB, 0.19 ± 0.04 for AW3, and 0.10 ± 0.04 for AWW. Moderate positive genetic correlation was observed between AWB with SB (0.66 ± 0.10) and SW (0.61 ± 0.13). Furthermore, genetic correlations of LB with SW and AWB were 0.55 ± 0.16 and 0.53 ± 0.18, respectively. On the other hand, negative and moderate genetic correlations were observed between GL and survival rates at birth (-0.43 ± 0.14) and at weaning (-0.37 ± 0.15). These results indicated that selection for higher litter weights at birth can effectively improve survival rate and number of live kits in mink farms. It was suggested to incorporate litter weight traits as a selection criterion to increase maternal ability in mink breeding programs. Unfavorable genetic trends were observed for the studied traits indicating that phenotypic selection with low selection intensity had not been an efficient method to improve them over the last 10 yr. It was recommended to use genetic or genomic evaluation methods for mink selection.

Local and global patterns of admixture and population structure in Iranian native cattle.

BACKGROUND: Two separate domestication events gave rise to humped zebu cattle in India and humpless taurine cattle in the Fertile Crescent of the Near and Middle East. Iran covers the Eastern side of the Fertile Crescent and exhibits a variety of native cattle breeds, however, only little is known about the admixture patterns of Iranian cattle and their contribution to the formation of modern cattle breeds. RESULTS: Genome-wide data (700 k chip) of eight Iranian cattle breeds (Sarabi N = 19, Kurdi N = 7, Taleshi N = 7, Mazandarani N = 10, Najdi N = 7, Pars N = 7, Kermani N = 9, and Sistani N = 9) were collected from across Iran. For a local assessment, taurine (Holstein and Jersey) and indicine (Brahman) outgroup samples were used. For the global perspective, 134 world-wide cattle breeds were included. Between breed variation amongst Iranian cattle explained 60 % (p < 0.001) of the total molecular variation and 82.88 % (p < 0.001) when outgroups were included. Several migration edges were observed within the Iranian cattle breeds. The highest indicine proportion was found in Sistani. All Iranian breeds with higher indicine ancestry were more admixed with a complex migration pattern. Nineteen founder populations most accurately explained the admixture of 44 selected representative cattle breeds (standard error 0.4617). Low levels of African ancestry were identified in Iranian cattle breeds (on average 7.5 %); however, the signal did not persist through all analyses. Admixture and migration analyses revealed minimal introgression from Iranian cattle into other taurine cattle (Holstein, Hanwoo, Anatolian breeds). CONCLUSION: The eight Iranian cattle breeds feature a discrete genetic composition which should be considered in conservation programs aimed at preserving unique species and genetic diversity. Despite a complex admixture pattern among Iranian cattle breeds, there was no strong introgression from other world-wide cattle breeds into Iranian cattle and vice versa. Considering Iran's central location of cattle domestication, Iranian cattle might represent a local domestication event that remained contained and did not contribute to the formation of modern breeds, or genetics of the ancestral population that gave rise to modern cattle is too diluted to be linked directly to any current cattle breeds.

Comparison of linkage disequilibrium levels in Iranian indigenous cattle using whole genome SNPs data.

BACKGROUND: Knowledge of linkage disequilibrium (LD) levels among different populations can be used to detect genetic diversity and to investigate the historical changes in population sizes. Availability of large numbers of SNP through new sequencing technologies has provided opportunities for extensive researches in quantifying LD patterns in cattle breeds. The aim of this study was to compare the extent of linkage disequilibrium among Iranian cattle breeds using high density SNP genotyping data. RESULTS: A total of 70 samples, representing seven Iranian indigenous cattle breeds, were genotyped for 777962 SNPs. The average values of LD based on the r(2) criterion were computed by grouping all syntenic SNP pairwises for inter-marker distances from 0 Kb up to 1 Mb using three distance sets. Average r(2) above 0.3 was observed at distances less than 30 Kb for Sistani and Kermani, 20 Kb for Najdi, Taleshi, Kurdi and Sarabi, and 10 Kb for Mazandarani. The LD levels were considerably different among the Iranian cattle breeds and the difference in LD extent was more detectable between the studied breeds at longer distances. Lower level of LD was observed for Mazandarani breed as compared to other breeds indicating larger ancestral population size in this breed. Kermani breed continued to have more slowly LD decay than all of the other breeds after 3 Kb distances. More slowly LD decay was observed in Kurdi and Sarabi breeds at larger distances (>100 Kb) showing that population decline has been more intense in more recent generations for these populations. CONCLUSIONS: A wide genetic diversity and different historical background were well reflected in the LD levels among Iranian cattle breeds. More LD fluctuation was observed in the shorter distances (less than 10 Kb) in different cattle populations. Despite of the sample size effects, High LD levels found in this study were in accordance with the presence of inbreeding and population decline in Iranian cattle breeds.