Estimation of linkage disequilibrium and effective population size in New Zealand sheep using three different methods to create genetic maps

A comprehensive analysis of the genetic diversity and environmental adaptability in worldwide Merino and Merino-derived sheep breeds

BACKGROUND

To enhance and extend the knowledge about the global historical and phylogenetic relationships between Merino and Merino-derived breeds, 19 populations were genotyped with the OvineSNP50 BeadChip specifically for this study, while an additional 23 populations from the publicly available genotypes were retrieved. Three complementary statistical tests, Rsb (extended haplotype homozygosity between-populations), XP-EHH (cross-population extended haplotype homozygosity), and runs of homozygosity (ROH) islands were applied to identify genomic variants with potential impact on the adaptability of Merino genetic type in two contrasting climate zones.

RESULTS

The results indicate that a large part of the Merino's genetic relatedness and admixture patterns are explained by their genetic background and/or geographic origin, followed by local admixture. Multi-dimensional scaling, Neighbor-Net, Admixture, and TREEMIX analyses consistently provided evidence of the role of Australian, Rambouillet and German strains in the extensive gene introgression into the other Merino and Merino-derived breeds. The close relationship between Iberian Merinos and other South-western European breeds is consistent with the Iberian origin of the Merino genetic type, with traces from previous contributions of other Mediterranean stocks. Using Rsb and XP-EHH approaches, signatures of selection were detected spanning four genomic regions located on Ovis aries chromosomes (OAR) 1, 6 and 16, whereas two genomic regions on OAR6, that partially overlapped with the previous ones, were highlighted by ROH islands. Overall, the three approaches identified 106 candidate genes putatively under selection. Among them, genes related to immune response were identified via the gene interaction network. In addition, several candidate genes were found, such as LEKR1, LCORL, GHR, RBPJ, BMPR1B, PPARGC1A, and PRKAA1, related to morphological, growth and reproductive traits, adaptive thermogenesis, and hypoxia responses.

CONCLUSIONS

To the best of our knowledge, this is the first comprehensive dataset that includes most of the Merino and Merino-derived sheep breeds raised in different regions of the world. The results provide an in-depth picture of the genetic makeup of the current Merino and Merino-derived breeds, highlighting the possible selection pressures associated with the combined effect of anthropic and environmental factors. The study underlines the importance of Merino genetic types as invaluable resources of possible adaptive diversity in the context of the occurring climate changes.

Genetic diversity of two native sheep breeds by genome-wide analysis of single nucleotide polymorphisms

Wallachian and Sumava sheep are autochthonous breeds that have undergone a significant bottleneck effect and subsequent restoration efforts. The first objective of this study was to evaluate the degree of genetic variability of both breeds and, therefore, the current management of the breeding. The second was to determine whether these two breeds still retain their genetic uniqueness in relation to each other and other breeds, despite regenerative interventions. Our data consisted of 48 individuals of Sumava and 37 individuals of Wallachian sheep. The comparison data contained 25 other breeds (primarily European) from the HapMap dataset generated by the International Sheep Genomics Consortium. When comparing all 27 breeds, the Czech breeds clustered with 15 other breeds and formed a single branch with them according to Nei's distances. At the same time, however, the clusters of both breeds were integral and easily distinguishable from the others when displayed with principal component analysis (PCA). Population substructure analysis did not show any common genetic ancestry of the Czech national breeds and breeds used for regeneration or, eventually, breeds whose ancestral population was used for regeneration. The average values of F_ST were higher in Wallachian sheep (F_ST = 0.14) than in Sumava sheep (F_ST = 0.08). The linkage disequilibrium (LD) extension per autosome was higher in Wallachian than in Sumava sheep. Consequently, the N_e estimates five generations ago were 68 for Sumava versus 34 for Wallachian sheep. Both native Czech breeds exhibit a wide range of inbreeding based on the excess of homozygosity (F_HOM) among individuals, from -0.04 to 0.16 in Sumava and from -0.13 to 0.12 in Wallachian. Average inbreeding based on runs of homozygosity was 0.21 in Sumava and 0.27 in Wallachian. Most detected runs of homozygosity (ROH) were less than 5 Mb long for both breeds. ROH segments longer than 15 Mb were absent in Wallachian sheep. Concerning putative selection signatures, a total of 471 candidate genes in Wallachian sheep within 11 hotspots and 653 genes within 13 hotspots in Sumava sheep were identified. Czech breeds appear to be well differentiated from each other and other European breeds. Their genetic diversity is low, especially in the case of the Wallachian breed. Sumava is not so threatened by low diversity but has a larger share of the non-native gene pool.

Genetic and Genomic Characterization of a New Beef Cattle Composite Breed (Purunã) Developed for Production in Pasture-Based Systems

Purunã is a composite beef cattle breed, developed in Southern Brazil by crossing the Angus, Charolais, Canchim, and Caracu breeds. The goal of this study was to perform the first genetic characterization of the Purunã breed, based on both pedigree and genomic information. For this, 100 randomly selected animals were genotyped, and 11,205 animals born from 1997 to 2019 had pedigree information. The genetic analyses performed were principal component analysis, admixture, phylogenic tree, pedigree and genomic inbreeding, linkage disequilibrium (LD), effective population size (Ne), consistency of the gametic phase, runs of homozygosity (ROH), heterozygosity-enriched regions (HERs), and functional analyses of the ROH and HER regions identified. Our findings indicate that Purunã is more genetically related to the Charolais, Canchim, and Angus breeds than Caracu or Nellore. The levels of inbreeding were shown to be small based on all the metrics evaluated and ranged from −0.009 to 0.029. A low (−0.12–0.31) correlation of the pedigree-based inbreeding compared to all the genomic inbreeding coefficients evaluated was observed. The LD average was 0.031 (±0.0517), and the consistency of the gametic phase was shown to be low for all the breed pairs, ranging from 0.42 to 0.27 to the distance of 20 Mb. The Ne values based on pedigree and genomic information were 158 and 115, respectively. A total of 1,839 ROHs were found, and the majority of them are of small length (<4 Mb). An important homozygous region was identified on BTA5 with pathways related to behavioral traits (sensory perception, detection of stimulus, and others), as well as candidate genes related to heat tolerance (MY O 1A), feed conversion rate (RDH5), and reproduction (AMDHD1). A total of 1,799 HERs were identified in the Purunã breed with 92.3% of them classified within the 0.5–1 Mb length group, and 19 HER islands were identified in the autosomal genome. These HER islands harbor genes involved in growth pathways, carcass weight (SDCBP), meat and carcass quality (MT2A), and marbling deposition (CISH). Despite the genetic relationship between Purunã and the founder breeds, a multi-breed genomic evaluation is likely not feasible due to their population structure and low consistency of the gametic phase among them.

Assessing Population Structure and Genetic Diversity in U.S. Suffolk Sheep to Define a Framework for Genomic Selection

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 U.S. was evaluated in four ways: 1) using genetic relationships from pedigree data [(n=64,310 animals recorded in the U.S. 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 U.S. 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 U.S. 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 U.S. Suffolk sheep engaged in NSIP was proposed.

The genomic structure of isolation across breed, country and strain for important South African and Australian sheep populations

Background

South Africa and Australia shares multiple important sheep breeds. For some of these breeds, genomic breeding values are provided to breeders in Australia, but not yet in South Africa. Combining genomic resources could facilitate development for across country selection, but the influence of population structures could be important to the compatability of genomic data from varying origins. The genetic structure within and across breeds, countries and strains was evaluated in this study by population genomic parameters derived from SNP-marker data. Populations were first analysed by breed and country of origin and then by subpopulations of South African and Australian Merinos.

Results

Mean estimated relatedness according to the genomic relationship matrix varied by breed (-0.11 to 0.16) and bloodline (-0.08 to 0.06) groups and depended on co-ancestry as well as recent genetic links. Measures of divergence across bloodlines (F_ST: 0.04–0.12) were sometimes more distant than across some breeds (F_ST: 0.05–0.24), but the divergence of common breeds from their across-country equivalents was weak (F_ST: 0.01–0.04). According to mean relatedness, F_ST, PCA and Admixture, the Australian Ultrafine line was better connected to the SA Cradock Fine Wool flock than with other AUS bloodlines. Levels of linkage disequilibrium (LD) between adjacent markers was generally low, but also varied across breeds (r²: 0.14–0.22) as well as bloodlines (r²: 0.15–0.19). Patterns of LD decay was also unique to breeds, but bloodlines differed only at the absolute level. Estimates of effective population size (N_e) showed genetic diversity to be high for the majority of breeds (N_e: 128–418) but also for bloodlines (N_e: 137–369).

Conclusions

This study reinforced the genetic complexity and diversity of important sheep breeds, especially the Merino breed. The results also showed that implications of isolation can be highly variable and extended beyond breed structures. However, knowledge of useful links across these population substructures allows for a fine-tuned approach in the combination of genomic resources. Isolation across country rarely proved restricting compared to other structures considered. Consequently, research into the accuracy of across-country genomic prediction is recommended.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08020-3.

Whole-Genome SNP Characterisation Provides Insight for Sustainable Use of Local South African Livestock Populations

Local cattle and sheep populations are important for animal production and food security in South Africa. These genetic resources are well adapted to the diverse climatic conditions and hold potential to be utilized in production systems subjected to climate change. The local beef breeds are well integrated into commercial livestock production systems with access to performance recording and genetic evaluations, while local sheep breeds are mainly utilised in smallholder and communal systems. The GeneSeek^® Genomic Profiler™ Bovine 150 K SNP genotyping array was used to evaluate the diversity and inbreeding status of four indigenous (Boran, Drakensberger, Nguni, Tuli), two composite (Bonsmara and Beefmaster) and two exotic (SA Hereford and Charolais) beef breeds. The Illumina^® Ovine 50 K SNP BeadChip was used to investigate five indigenous (Black Head Persian, Damara, Fat tail, Namaqua Afrikaner, Pedi) and three commercial (Dorper, Dohne Merino and SA Merino) populations. Although ascertainment bias was indicated by the low MAF (the autosome-wide proportion of SNPs with MAF< 0.05 ranged from 6.18 to 9.97% for cattle, and 7.59–13.81% for sheep), moderate genomic diversity was observed (mean H_o ranged from 0.296 to 0.403 for cattle, and 0.327 to 0.367 for sheep). Slightly higher levels of ROH-based inbreeding were calculated for cattle (F_ROH range: 0.018–0.104), than for sheep populations (F_ROH range: 0.002–0.031). The abundance of short ROH fragments (mean proportion of <4 Mb fragments: 0.405 for cattle, and 0.794 for sheep) indicated ancient inbreeding in both species. The eight cattle populations were categorized into indicine, taurine or Sanga subspecies based on principal component, model-based clustering and phylogenetic analyses, with high levels of admixture observed within the Drakensberger, Nguni and Tuli breeds. Within the sheep populations, a clear distinction could be seen between the dual-purpose breeds, the meat breed and the indigenous breeds. Despite directional selection practiced in the cattle breeds, genomic diversity was moderate with low inbreeding. The non-commercialized, indigenous sheep populations are more vulnerable with small effective populations. These results emphasise the value of genomic information for effective management to exploit the potential contribution of local genetic cattle and sheep resources in a changing environment.

A Comprehensive Comparison of Haplotype-Based Single-Step Genomic Predictions in Livestock Populations With Different Genetic Diversity Levels: A Simulation Study

The level of genetic diversity in a population is inversely proportional to the linkage disequilibrium (LD) between individual single nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs), leading to lower predictive ability of genomic breeding values (GEBVs) in high genetically diverse populations. Haplotype-based predictions could outperform individual SNP predictions by better capturing the LD between SNP and QTL. Therefore, we aimed to evaluate the accuracy and bias of individual-SNP- and haplotype-based genomic predictions under the single-step-genomic best linear unbiased prediction (ssGBLUP) approach in genetically diverse populations. We simulated purebred and composite sheep populations using literature parameters for moderate and low heritability traits. The haplotypes were created based on LD thresholds of 0.1, 0.3, and 0.6. Pseudo-SNPs from unique haplotype alleles were used to create the genomic relationship matrix ( G ) in the ssGBLUP analyses. Alternative scenarios were compared in which the pseudo-SNPs were combined with non-LD clustered SNPs, only pseudo-SNPs, or haplotypes fitted in a second G (two relationship matrices). The GEBV accuracies for the moderate heritability-trait scenarios fitting individual SNPs ranged from 0.41 to 0.55 and with haplotypes from 0.17 to 0.54 in the most (Ne ≅ 450) and less (Ne < 200) genetically diverse populations, respectively, and the bias fitting individual SNPs or haplotypes ranged between -0.14 and -0.08 and from -0.62 to -0.08, respectively. For the low heritability-trait scenarios, the GEBV accuracies fitting individual SNPs ranged from 0.24 to 0.32, and for fitting haplotypes, it ranged from 0.11 to 0.32 in the more (Ne   ≅ 250) and less (Ne   ≅ 100) genetically diverse populations, respectively, and the bias ranged between -0.36 and -0.32 and from -0.78 to -0.33 fitting individual SNPs or haplotypes, respectively. The lowest accuracies and largest biases were observed fitting only pseudo-SNPs from blocks constructed with an LD threshold of 0.3 (p < 0.05), whereas the best results were obtained using only SNPs or the combination of independent SNPs and pseudo-SNPs in one or two G matrices, in both heritability levels and all populations regardless of the level of genetic diversity. In summary, haplotype-based models did not improve the performance of genomic predictions in genetically diverse populations.

Accuracy of GEBV of sires based on pooled allele frequency of their progeny

Despite decreasing genotyping costs, in some cases individually genotyping animals is not economically feasible (e.g., in small ruminants). An alternative is to pool DNA, using the pooled allele frequency (PAF) to garner information on performance. Still, the use of PAF for prediction (estimation of genomic breeding values; GEBVs) has been limited. Two potential sources of error on accuracy of GEBV of sires, obtained from PAF of their progeny themselves lacking pedigree information, were tested: (i) pool construction error (unequal contribution of DNA from animals in pools), and (ii) technical error (variability when reading the array). Pooling design (random, extremes, K-means), pool size (5, 10, 25, 50, and 100 individuals), and selection scenario (random, phenotypic) also were considered. These factors were tested by simulating a sheep population. Accuracy of GEBV-the correlation between true and estimated values-was not substantially affected by pool construction or technical error, or selection scenario. A significant interaction, however, between pool size and design was found. Still, regardless of design, mean accuracy was higher for pools of 10 or less individuals. Mean accuracy of GEBV was 0.174 (SE 0.001) for random pooling, and 0.704 (SE 0.004) and 0.696 (SE 0.004) for extreme and K-means pooling, respectively. Non-random pooling resulted in moderate accuracy of GEBV. Overall, pooled genotypes can be used in conjunction with individual genotypes of sires for moderately accurate predictions of their genetic merit with little effect of pool construction or technical error.

The pattern of runs of homozygosity and genomic inbreeding in world-wide sheep populations

Genome-wide pattern of runs of homozygosity (ROH) across ovine genome can provide a useful resource for studying diversity and demography history in sheep. We analyzed 50 k SNPs chip data of 2536 animals to identify pattern, distribution and level of ROHs in 68 global sheep populations. A total of 60,301 ROHs were detected in all breeds. The majority of the detected ROHs were <16 Mb and the average total number of ROHs per individual was 23.8 ± 13.8. The ROHs greater than 1 Mb covered on average 8.2% of the sheep autosomes, 1% of which was related to the ROHs with 1-4 Mb of length. The mean sum of ROH length in two-thirds of the populations was less than 250 Mb ranging from 21.7 to near 570 Mb. The level of genomic inbreeding was relatively low. The average of the inbreeding coefficients based on ROH (F_ROH) was 0.09 ± 0.05. It was rising in a stepwise manner with distance from Southwest Asia and maximum values were detected in North European breeds. A total of 465 ROH hotspots were detected in 25 different autosomes which partially surrounding 257 Refseq genes across the genome. Most of the detected genes were related to growth, body weight, meat production and quality, wool production and pigmentation. In conclusion, our analysis showed that the sheep genome, compared with other livestock species such as cattle and pig, displays low levels of homozygosity and appropriate genetic diversity for selection response and genetic merit gain.

Accuracy of Imputation of Microsatellite Markers from a 50K SNP Chip in Spanish Assaf Sheep

Simple Summary

Parentage misassignments directly affect genetic gain in traditional breeding programs. The use of genetic markers facilitates parentage verification. In sheep, microsatellite markers and single nucleotide polymorphism (SNP) markers have been proposed by the International Society of Animal Sciences (ISAG) for parentage testing. Since the implementation of genomic selection, the microsatellite information used for parental testing in previous generations is gradually being replaced by SNPs. However, parentage verifications should all be performed using the same technology. A strategy for transitioning from microsatellites to SNP markers, while avoiding extra genotyping costs, is the imputation of microsatellite alleles from SNP haplotypes. This study aims to identify the optimum approach, using a minimum number of SNPs to accurately impute microsatellite markers and developing a low-density SNP chip for parentage verification in the Assaf sheep breed. The imputation approach described here reached high accuracies using a low number of SNP markers, which supports the development of a low-density SNP chip that could avoid the problems of genotyping with both technologies, being a cost-effective method for parentage testing. This study will help sheep breeders to perform parentage verification when different genotyping platforms have been used across generations.

Abstract

Transitioning from traditional to new genotyping technologies requires the development of bridging methodologies to avoid extra genotyping costs. This study aims to identify the optimum number of single nucleotide polymorphisms (SNPs) necessary to accurately impute microsatellite markers to develop a low-density SNP chip for parentage verification in the Assaf sheep breed. The accuracy of microsatellite marker imputation was assessed with three metrics: genotype concordance (C), genotype dosage (length r²), and allelic dosage (allelic r²), for all imputation scenarios tested (0.5–10 Mb microsatellite flanking SNP windows). The imputation accuracy for the three metrics analyzed for all haplotype lengths tested was higher than 0.90 (C), 0.80 (length r²), and 0.75 (allelic r²), indicating strong genotype concordance. The window with 2 Mb length provides the best accuracy for the imputation procedure and the design of an affordable low-density SNP chip for parentage testing. We additionally evaluated imputation performance under two null models, naive (imputing the most common allele) and random (imputing by randomly selecting the allele), which in comparison showed weak genotype concordances (0.41 and 0.15, respectively). Therefore, we describe a precise methodology in the present article to impute multiallelic microsatellite genotypes from a low-density SNP chip in sheep and solve the problem of parentage verification when different genotyping platforms have been used across generations.

Genetic Connectedness Between Norwegian White Sheep and New Zealand Composite Sheep Populations With Similar Development History

The Norwegian White sheep (NWS) and New Zealand Terminal Sire Composite (NZC) sheep breeds have been developed based on crossing of multiple breeds, mainly of Northern European origin. A close genetic relationship between these populations could enable across-country genomic evaluations. The main objectives of this study were to assess the genetic connectedness between Norwegian and New Zealand sheep populations and estimate numerous genetic diversity metrics for these two populations. A total of 792 NWS and 16,912 NZC animals were genotyped using a high-density Illumina SNP chip panel (∼606K SNPs). The NZC animals were grouped based on their breed composition as: Finn, Lamb Supreme, Primera, Texel, “Other Dual Purpose”, and “Other Terminal Sire”. The average level of linkage disequilibrium ranged from 0.156 (for Primera) to 0.231 (for Finn). The lowest consistency of gametic phase was estimated between NWS and Finn (0.397), and between NWS and Texel (0.443), respectively. Similar consistency of gametic phase was estimated between NWS and the other NZC populations (∼ 0.52). For all composite sheep populations analyzed in this study, the majority of runs of homozygosity (ROH) segments identified had short length (<2,500 kb), indicating ancient (instead of recent) inbreeding. The variation in the number of ROH segments observed in the NWS was similar to the variation observed in Primera and Lamb Supreme. There was no clear discrimination between NWS and NZC based on the first few principal components. In addition, based on admixture analyses, there seems to be a significant overlap of the ancestral populations that contributed to the development of both NWS and NZC. There were no evident signatures of selection in these populations, which might be due to recent crossbreeding. In conclusion, the NWS composite breed was shown to be moderately related to NZC populations, especially Primera and Lamb Supreme. The findings reported here indicate a promising opportunity for collaborative genomic analyses involving NWS and NZC sheep populations.

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 (F_HOM) 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 (r² ± SD) between adjacent SNPs was 0.30 ± 0.35 over all scaffolds with an average distance of 51 kb between markers. The average r² < 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 F_HOM 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.

On the Extent of Linkage Disequilibrium in the Genome of Farm Animals

Given the importance of linkage disequilibrium (LD) in gene mapping and evolutionary inferences, I characterize in this review the pattern of LD and discuss the influence of human intervention during domestication, breed establishment, and subsequent genetic improvement on shaping the genome of livestock species. To this end, I summarize data on the profile of LD based on array genotypes vs. sequencing data in cattle and chicken, two major livestock species, and compare to the human case. This comparison provides insights into the real dimension of the pairwise allelic correlation and haplo-block structuring. The dependency of LD on allelic frequency is pictured and a recently introduced metric for moderating it is outlined. In the context of the contact farm animals had with human, the impact of genetic forces including admixture, mutation, recombination rate, selection, and effective population size on LD is discussed. The review further highlights the interplay of LD with runs of homozygosity and concludes with the operational implications of the widely used association and selection mapping studies in relation to LD.

Genome-Wide Patterns of Population Structure and Linkage Disequilibrium in Farmed Nile Tilapia (Oreochromis niloticus)

Nile tilapia (Oreochromis niloticus) is one of the most produced farmed fish in the world and represents an important source of protein for human consumption. Farmed Nile tilapia populations are increasingly based on genetically improved stocks, which have been established from admixed populations. To date, there is scarce information about the population genomics of farmed Nile tilapia, assessed by dense single nucleotide polymorphism (SNP) panels. The patterns of linkage disequilibrium (LD) may affect the success of genome-wide association studies (GWAS) and genomic selection (GS), and also provide key information about demographic history of farmed Nile tilapia populations. The objectives of this study were to provide further knowledge about the population structure and LD patterns, as well as, estimate the effective population size (N e ) for three farmed Nile tilapia populations, one from Brazil (POP A) and two from Costa Rica (POP B and POP C). A total of 55 individuals from each population, were genotyped using a 50K SNP panel selected from a whole-genome sequencing (WGS) experiment. The first two principal components explained about 20% of the total variation and clearly differentiated between the three populations. Population genetic structure analysis showed evidence of admixture, especially for POP C. The contemporary N e estimated, based on LD values, ranged from 78 to 159. No differences were observed in the LD decay among populations, with a rapid decrease of r 2 with increasing inter-marker distance. Average r 2 between adjacent SNP pairs ranged from 0.19 to 0.03 for both POP A and C, and 0.20 to 0.03 f or POP B. Based on the number of independent chromosome segments in the Nile tilapia genome, at least 9.4, 7.6, and 4.6K SNPs for POP A, POP B, and POP C respectively, are required for the implementation of GS in the present farmed Nile tilapia populations.

Linkage disequilibrium and within-breed genetic diversity in Iranian Zandi sheep

This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (Ne), and runs of homozygosity (ROHs) in one of the major Iranian sheep breeds (Zandi) using 96 samples genotyped with Illumina Ovine SNP50 BeadChip. The amount of LD (r2) for single-nucleotide polymorphism (SNP) pairs in short distances (10–20 kb) was 0.21±0.25 but rapidly decreased to 0.10±0.16 by increasing the distance between SNP pairs (40–60 kb). The Ne of Zandi sheep in past (approximately 3500 generations ago) and recent (five generations ago) populations was estimated to be 6475 and 122, respectively. The ROH-based inbreeding was 0.023. We found 558 ROH regions, of which 37 % were relatively long (>10 Mb). Compared with the rate of LD reduction in other species (e.g., cattle and pigs), in Zandi, it was reduced more rapidly by increasing the distance between SNP pairs. According to the LD pattern and high genetic diversity of Zandi sheep, we need to use an SNP panel with a higher density than Illumina Ovine SNP50 BeadChip for genomic selection and genome-wide association studies in this breed.

The quality of the algorithm for proven and young with various sets of core animals in a multibreed sheep population1

The inverses of the pedigree and genomic relationship matrices (A, G) are required for single-step GBLUP (ssGBLUP). While, inverting A is possible for millions of animals at a linear cost, inverting G has a cubic cost and feasible for at most 150,000 animals, using the current conventional algorithms. The algorithm for proven and young (APY) provides approximations of the regular ssGBLUP by splitting genotyped animals into core and noncore groups, with computational costs being cubic for core and linear for noncore animals. The data consisted of 9,406,096 animals in the pedigree, 6,243,753 weaning weight phenotypes, and 46,949 genotyped animals from 5 breeds, composites, and animals with missing breed information from New Zealand. Aiming to find a core sample for a multibreed sheep population that can provide evaluations similar to those from the regular ssGBLUP, different core types, and core sizes were studied. Core types random, composite, oldest, youngest, the most inbred animals in G (GINB), and in A (AINB) were studied in 5K, 10K, and 20K core sizes (K = 1,000). Romney core was studied in 5K and 10K, and Coopworth-Perendale core was studied in 5K. Correlation and regression coefficient (slope) between GEBV from the non-APY and the APY analyses, as indicators for consistency with non-APY and bias from non-APY, showed a large impact of APY on noncore and a small impact on nongenotyped animals. Breed-based 5K cores resulted in large bias from non-APY even for nongenotyped animals. Random and GINB at 20K core size resulted in the highest consistency with non-APY and the lowest bias from non-APY. However, GINB did not perform as well as Random at lower core sizes. The number of animals from a breed in the core sample was very important for the evaluation of that breed. We observed that cores without Texel or Highlander animals resulted in poor evaluations for those breeds. Solving the mixed model equations, within core type, the smallest core size, and within core size, Random core converged in the least number of iterations. However, APY per se did not necessarily reduce the solving time. Random cores performed the best, as they could give a good coverage on the generations and breeds, representative for the genotyped population. Core size 20K performed better than 5K and 10K, and the optimum core size was found to be 18.8K, according to the eigenvalue decomposition of G.

Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the breeder's equation

The integration of new technologies into public plant breeding programs can make a powerful step change in agricultural productivity when aligned with principles of quantitative and Mendelian genetics. The breeder's equation is the foundational application of quantitative genetics to crop improvement. Guided by the variables that describe response to selection, emerging breeding technologies can make a powerful step change in the effectiveness of public breeding programs. The most promising innovations for increasing the rate of genetic gain without greatly increasing program size appear to be related to reducing breeding cycle time, which is likely to require the implementation of parent selection on non-inbred progeny, rapid generation advance, and genomic selection. These are complex processes and will require breeding organizations to adopt a culture of continuous optimization and improvement. To enable this, research managers will need to consider and proactively manage the, accountability, strategy, and resource allocations of breeding teams. This must be combined with thoughtful management of elite genetic variation and a clear separation between the parental selection process and product development and advancement process. With an abundance of new technologies available, breeding teams need to evaluate carefully the impact of any new technology on selection intensity, selection accuracy, and breeding cycle length relative to its cost of deployment. Finally breeding data management systems need to be well designed to support selection decisions and novel approaches to accelerate breeding cycles need to be routinely evaluated and deployed.

Population Genomic Structure and Genome-Wide Linkage Disequilibrium in Farmed Atlantic Salmon (Salmo salar L.) Using Dense SNP Genotypes

Chilean Farmed Atlantic salmon (Salmo salar) populations were established with individuals of both European and North American origins. These populations are expected to be highly genetically differentiated due to evolutionary history and poor gene flow between ancestral populations from different continents. The extent and decay of linkage disequilibrium (LD) among single nucleotide polymorphism (SNP) impacts the implementation of genome-wide association studies and genomic selection and provides relevant information about demographic processes of fish populations. We assessed the population structure and characterized the extent and decay of LD in three Chilean commercial populations of Atlantic salmon with North American (NAM), Scottish (SCO), and Norwegian (NOR) origin. A total of 123 animals were genotyped using a 159 K SNP Axiom® myDesignTM Genotyping Array. A total of 32 K SNP markers, representing the common SNPs along the three populations after quality control were used. The principal component analysis explained 78.9% of the genetic diversity between populations, clearly discriminating between populations of North American and European origin, and also between European populations. NAM had the lowest effective population size, followed by SCO and NOR. Large differences in the LD decay were observed between populations of North American and European origin. An r 2 threshold of 0.2 was estimated for marker pairs separated by 7,800, 64, and 50 kb in the NAM, SCO, and NOR populations, respectively. In this study we show that this SNP panel can be used to detect association between markers and traits of interests and also to capture high-resolution information for genome-enabled predictions. Also, we suggest the feasibility to achieve similar prediction accuracies using a smaller SNP data set for the NAM population, compared with samples with European origin which would need a higher density SNP array.

Linkage disequilibrium in Brazilian Santa Inês breed, Ovis aries

For genomic selection to be successful, there must be sufficient linkage disequilibrium between the markers and the causal mutations. The objectives of this study were to evaluate the extent of LD in ovine using the Santa Inês breed and to infer the minimum number of markers required to reach reasonable prediction accuracy. In total, 38,168 SNPs and 395 samples were used. The mean LD between adjacent marker pairs measured by r² and |D′| were 0.166 and 0.617, respectively. LD values between adjacent marker pairs ranged from 0.135 to 0.194 and from 0.568 to 0.650 for r² for |D′| across all chromosomes. The average r² between all pairwise SNPs on each chromosome was 0.018. SNPs separated by between 0.10 to 0.20 Mb had an estimated average r² equal to 0.1033. The identified haplotype blocks consisted of 2 to 21 markers. Moreover, estimates of average coefficients of inbreeding and effective population size were 0.04 and 96, respectively. LD estimated in this study was lower than that reported in other species and was characterized by short haplotype blocks. Our results suggest that the use of a higher density SNP panel is recommended for the implementation of genomic selection in the Santa Inês breed.

Population structure and genetic diversity of 25 Russian sheep breeds based on whole-genome genotyping

Background

Russia has a diverse variety of native and locally developed sheep breeds with coarse, fine, and semi-fine wool, which inhabit different climate zones and landscapes that range from hot deserts to harsh northern areas. To date, no genome-wide information has been used to investigate the history and genetic characteristics of the extant local Russian sheep populations. To infer the population structure and genome-wide diversity of Russian sheep, 25 local breeds were genotyped with the OvineSNP50 BeadChip. Furthermore, to evaluate admixture contributions from foreign breeds in Russian sheep, a set of 58 worldwide breeds from publicly available genotypes was added to our data.

Results

We recorded similar observed heterozygosity (0.354–0.395) and allelic richness (1.890–1.955) levels across the analyzed breeds and they are comparable with those observed in the worldwide breeds. Recent effective population sizes estimated from linkage disequilibrium five generations ago ranged from 65 to 543. Multi-dimensional scaling, admixture, and neighbor-net analyses consistently identified a two-step subdivision of the Russian local sheep breeds. A first split clustered the Russian sheep populations according to their wool type (fine wool, semi-fine wool and coarse wool). The Dagestan Mountain and Baikal fine-fleeced breeds differ from the other Merino-derived local breeds. The semi-fine wool cluster combined a breed of Romanian origin, Tsigai, with its derivative Altai Mountain, the two Romney-introgressed breeds Kuibyshev and North Caucasian, and the Lincoln-introgressed Russian longhaired breed. The coarse-wool group comprised the Nordic short-tailed Romanov, the long-fat-tailed outlier Kuchugur and two clusters of fat-tailed sheep: the Caucasian Mountain breeds and the Buubei, Karakul, Edilbai, Kalmyk and Tuva breeds. The Russian fat-tailed breeds shared co-ancestry with sheep from China and Southwestern Asia (Iran).

Conclusions

In this study, we derived the genetic characteristics of the major Russian local sheep breeds, which are moderately diverse and have a strong population structure. Pooling our data with a worldwide genotyping set gave deeper insight into the history and origin of the Russian sheep populations.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0399-5) contains supplementary material, which is available to authorized users.