Genome-wide analyses reveal population structure and identify candidate genes associated with tail fatness in local sheep from a semi-arid area

Under a climate change perspective, the genetic make-up of local livestock breeds showing adaptive traits should be explored and preserved as a priority. We used genotype data from the ovine 50 k Illumina BeadChip for assessing breed autozygosity based on runs of homozygosity (ROH) and fine-scale genetic structure and for detecting genomic regions under selection in 63 Tunisian sheep samples. The average genomic inbreeding coefficients based on ROH were estimated at 0.017, 0.021, and 0.024 for Barbarine (BAR, n = 26), Noire de Thibar (NDT, n = 23), and Queue fine de l'Ouest (QFO, n = 14) breeds, respectively. The genomic relationships among individuals based on identity by state (IBS) distance matrix highlighted a recent introgression of QFO into the BAR and a genetic differentiation of NDT samples, possibly explained by past introgression of European gene pools. Genome-wide scan for ROH across breeds and within the BAR sample set identified an outstanding signal on chromosome 13 (46.58–49.61 Mbp). These results were confirmed using F_ST index, differentiating fat vs. thin-tailed individuals. Candidate genes under selection pressure (CDS2, PROKR1, and BMP2) were associated to lipid storage and probably preferentially selected in fat-tailed BAR animals. Our findings suggest paying more attention to preserve the genetic integrity and adaptive alleles of local sheep breeds.     

Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds

Domestication and selection are the major driving forces responsible for the determinative genetic variability in livestock. These selection patterns create unique genetic signatures within the genome. BovineSNP50 chip data from 236 animals (seven indicine and five taurine cattle breeds) were analyzed in the present study. We implemented three complementary approaches viz. iHS (Integrated haplotype score), ROH (Runs of homozygosity), and F_ST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and F_ST methods, respectively. We found several candidate genes (e.g., NCR3, ARID5A, HIST1H2BN, DEFB4, DEFB7, HSPA1L, HSPA1B, and DNAJB4) related to production traits and the adaptation of indigenous breeds to local environmental constraints such as heat stress and disease susceptibility. However, further studies are warranted to refine the findings using a larger sample size, whole-genome sequencing, and/or high density genotyping.     

The Relationship Between FST and the Frequency of the Most Frequent Allele

F_ST is frequently used as a summary of genetic differentiation among groups. It has been suggested that F_ST depends on the allele frequencies at a locus, as it exhibits a variety of peculiar properties related to genetic diversity: higher values for biallelic single-nucleotide polymorphisms (SNPs) than for multiallelic microsatellites, low values among high-diversity populations viewed as substantially distinct, and low values for populations that differ primarily in their profiles of rare alleles. A full mathematical understanding of the dependence of F_ST on allele frequencies, however, has been elusive. Here, we examine the relationship between F_ST and the frequency of the most frequent allele, demonstrating that the range of values that F_ST can take is restricted considerably by the allele-frequency distribution. For a two-population model, we derive strict bounds on F_ST as a function of the frequency M of the allele with highest mean frequency between the pair of populations. Using these bounds, we show that for a value of M chosen uniformly between 0 and 1 at a multiallelic locus whose number of alleles is left unspecified, the mean maximum F_ST is ∼0.3585. Further, F_ST is restricted to values much less than 1 when M is low or high, and the contribution to the maximum F_ST made by the most frequent allele is on average ∼0.4485. Using bounds on homozygosity that we have previously derived as functions of M, we describe strict bounds on F_ST in terms of the homozygosity of the total population, finding that the mean maximum F_ST given this homozygosity is 1 − ln 2 ≈ 0.3069. Our results provide a conceptual basis for understanding the dependence of F_ST on allele frequencies and genetic diversity and for interpreting the roles of these quantities in computations of F_ST from population-genetic data. Further, our analysis suggests that many unusual observations of F_ST, including the relatively low F_ST values in high-diversity human populations from Africa and the relatively low estimates of F_ST for microsatellites compared to SNPs, can be understood not as biological phenomena associated with different groups of populations or classes of markers but rather as consequences of the intrinsic mathematical dependence of F_ST on the properties of allele-frequency distributions.DIFFERENTIATION among groups is one of the fundamental subjects of the field of population genetics. Comparisons of the level of variation among subpopulations with the level of variation in the total population have been employed frequently in population-genetic theory, in statistical methods for data analysis, and in empirical studies of distributions of genetic variation. Wright’s (Wright 1951) fixation indices, and F_ST in particular, have been central to this effort.Wright’s F_ST was originally defined as the correlation between two randomly sampled gametes from the same subpopulation when the correlation of two randomly sampled gametes from the total population is set to zero. Several definitions of F_ST or F_ST-like quantities are now available, relying on a variety of different conceptual formulations but all measuring some aspect of population differentiation (e.g., Charlesworth 1998; Holsinger and Weir 2009). Many authors have claimed that one or another formulation of F_ST is affected by levels of genetic diversity or by allele frequencies, either because the range of F_ST is restricted by these quantities or because these quantities affect the degree to which F_ST reflects population differentiation (e.g., Charlesworth 1998; Nagylaki 1998; Hedrick 1999, 2005; Long and Kittles 2003; Jost 2008; Ryman and Leimar 2008; Long 2009; Meirmans and Hedrick 2011). For example, Nagylaki (1998) and Hedrick (1999) argued that measures of F_ST may be poor measures of genetic differentiation when the level of diversity is high. Charlesworth (1998) suggested that F_ST can be inflated when diversity is low, arguing that F_ST might not be appropriate for comparing loci with substantially different levels of variation. In a provocative recent article, Jost (2008) used the diversity dependence of forms of F_ST to question their utility as differentiation measures at all.One definition that is convenient for mathematical assessment of the relationship of an F_ST-like quantity and allele frequencies is the quantity labeled G_ST by Nei (1973), which for a given locus measures the difference between the heterozygosity of the total (pooled) population, h_T, and the mean heterozygosity across subpopulations, h_S, divided by the heterozygosity of the total population:GST=hT−hShT.(1)In terms of the homozygosity of the total population, H_T = 1 − h_T, and the mean homozygosity across subpopulations, H_S = 1 − h_S, we can writeGST=HS−HT1−HT.(2)The Wahlund (1928) principle guarantees that H_S ≥ H_T and, therefore, because H_S ≤ 1 and for a polymorphic locus with finitely many alleles, 0 < H_T < 1, G_ST lies in the interval [0,1].Using G_ST for their definition of F_ST, Hedrick (1999, 2005) and Long and Kittles (2003) pointed out that because h_T < 1, F_ST cannot exceed the mean homozygosity across subpopulations, H_S:F_ST = 1 ? h_S/h_T < 1 ? h_S = H_S.(3)Hedrick (2005) obtained this result by considering a set of K equal-sized subpopulations, in which each allele is private to a single subpopulation. In the limit as K → ∞, a stronger upper bound on F_ST as a function of H_S and K reduces to Equation 3 (see also Jin and Chakraborty 1995 and Long and Kittles 2003).While Hedrick (1999, 2005) and Long and Kittles (2003) have clarified the relationship between F_ST and the mean homozygosity H_S across subpopulations, their approaches do not easily illuminate the connection between F_ST and allele frequencies themselves. A formal understanding of the relationship between F_ST and allele frequencies would make it possible to more fully understand the behavior of F_ST in situations where markers of interest differ substantially in allele frequencies or levels of genetic diversity. Our recent work on the relationship between homozygosity and the frequency of the most frequent allele (Rosenberg and Jakobsson 2008; Reddy and Rosenberg 2012) provides a mathematical approach for formal investigation of bounds on population-genetic statistics in terms of allele frequencies. In this article, we therefore seek to thoroughly examine the dependence of F_ST on allele frequencies by investigating the upper bound on F_ST in terms of the frequency M of the most frequent allele across a pair of populations. We derive bounds on F_ST given the frequency of the most frequent allele and bounds on the frequency of the most frequent allele given F_ST. We consider loci with arbitrarily many alleles in a pair of subpopulations. Using theory for the bounds on homozygosity given the frequency of the most frequent allele, we obtain strict bounds on F_ST given the homozygosity of the total population. Our analysis clarifies the relationships among F_ST, allele frequencies, and homozygosity, providing explanations for peculiar observations of F_ST that can be attributed to allele-frequency dependence.     

Exome analysis and functional classification of identified variants in racing Quarter Horses

The main objectives of this study were to identify and functionally classify SNPs and indels by exome sequencing of animals of the racing line of Quarter Horses. Based on the individual genomic estimated breeding values (GEBVs) for maximum speed index (SImax) obtained for 349 animals, two groups of 20 extreme animals were formed. Of these individuals, 20 animals with high GEBVs for SImax and 19 with low GEBVs for SImax had their exons and 5′ and 3′ UTRs sequenced. Considering SNPs and indels, 105 182 variants were identified in the expressed regions of the Quarter Horse genome. Of these, 72 166 variants were already known and 33 016 are new variants and were deposited in a database. The analysis of the set of gene variants significantly related (P_adjusted < 0.05) to extreme animals in conjunction with the predicted impact of the changes and the physiological role of protein product pointed to two candidate genes potentially related to racing performance: SLC3A1 on ECA15 and CCN6 on ECA10.     

Multi-Gene Analysis Reveals a Lack of Genetic Divergence between Calanus agulhensis and C. sinicus (Copepoda; Calanoida)

The discrimination and taxonomic identification of marine species continues to pose a challenge despite the growing number of diagnostic metrics and approaches. This study examined the genetic relationship between two sibling species of the genus Calanus (Crustacea; Copepoda; Calanidae), C. agulhensis and C. sinicus, using a multi-gene analysis. DNA sequences were determined for portions of the mitochondrial cytochrome c oxidase I (mtCOI); nuclear citrate synthase (CS), and large subunit (28S) rRNA genes for specimens collected from the Sea of Japan and North East (NE) Pacific Ocean for C. sinicus and from the Benguela Current and Agulhas Bank, off South Africa, for C. agulhensis. For mtCOI, C. sinicus and C. agulhensis showed similar levels of haplotype diversity (H_d = 0.695 and 0.660, respectively) and nucleotide diversity (π = 0.003 and 0.002, respectively). Pairwise F_ST distances for mtCOI were significant only between C. agulhensis collected from the Agulhas and two C. sinicus populations: the Sea of Japan (F_ST = 0.152, p<0.01) and NE Pacific (F_ST = 0.228, p<0.005). Between the species, F_ST distances were low for both mtCOI (F_ST = 0.083, p = 0.003) and CS (F_ST = 0.050, p = 0.021). Large subunit (28S) rRNA showed no variation between the species. Our results provide evidence of the lack of genetic distinction of C. sinicus and C. agulhensis, raise questions of whether C. agulhensis warrants status as a distinct species, and indicate the clear need for more intensive and extensive ecological and genetic analysis.     

Worldwide Distribution of the MYH9 Kidney Disease Susceptibility Alleles and Haplotypes: Evidence of Historical Selection in Africa

MYH9 was recently identified as renal susceptibility gene (OR 3–8, p<10⁻⁸) for major forms of kidney disease disproportionately affecting individuals of African descent. The risk haplotype (E-1) occurs at much higher frequencies in African Americans (≥60%) than in European Americans (<4%), revealing a genetic basis for a major health disparity. The population distributions of MYH9 risk alleles and the E-1 risk haplotype and the demographic and selective forces acting on the MYH9 region are not well explored. We reconstructed MYH9 haplotypes from 4 tagging single nucleotide polymorphisms (SNPs) spanning introns 12–23 using available data from HapMap Phase II, and by genotyping 938 DNAs from the Human Genome Diversity Panel (HGDP). The E-1 risk haplotype followed a cline, being most frequent within sub-Saharan African populations (range 50–80%), less frequent in populations from the Middle East (9–27%) and Europe (0–9%), and rare or absent in Asia, the Americas, and Oceania. The fixation indexes (F_ST) for pairwise comparisons between the risk haplotypes for continental populations were calculated for MYH9 haplotypes; F_ST ranged from 0.27–0.40 for Africa compared to other continental populations, possibly due to selection. Uniquely in Africa, the Yoruba population showed high frequency extended haplotype length around the core risk allele (C) compared to the alternative allele (T) at the same locus (rs4821481, iHs = 2.67), as well as high population differentiation (F_{ST(CEU vs. YRI)} = 0.51) in HapMap Phase II data, also observable only in the Yoruba population from HGDP (F_ST = 0.49), pointing to an instance of recent selection in the genomic region. The population-specific divergence in MYH9 risk allele frequencies among the world''s populations may prove important in risk assessment and public health policies to mitigate the burden of kidney disease in vulnerable populations.     

Population structure and conservation implications for the loggerhead sea turtle of the Cape Verde Islands

The Cape Verde Islands harbour the second largest nesting aggregation of the globally endangered loggerhead sea turtle in the Atlantic. To characterize the unknown genetic structure, connectivity, and demographic history of this population, we sequenced a segment of the mitochondrial (mt) DNA control region (380 bp, n = 186) and genotyped 12 microsatellite loci (n = 128) in females nesting at three islands of Cape Verde. No genetic differentiation in either haplotype or allele frequencies was found among the islands (mtDNA F _ST = 0.001, P > 0.02; nDNA F _ST = 0.001, P > 0.126). However, population pairwise comparisons of the mtDNA data revealed significant differences between Cape Verde and all previously sequenced Atlantic and Mediterranean rookeries (F _ST = 0.745; P < 0.000). Results of a mixed stock analysis of mtDNA data from 10 published oceanic feeding grounds showed that feeding grounds of the Madeira, Azores, and the Canary Islands, in the Atlantic Ocean, and Gimnesies, Pitiüses, and Andalusia, in the Mediterranean sea, are feeding grounds used by turtles born in Cape Verde, but that about 43% (±19%) of Cape Verde juveniles disperse to unknown areas. In a subset of samples (n = 145) we evaluated the utility of a longer segment (~760 bp) amplified by recently designed mtDNA control region primers for assessing the genetic structure of Atlantic loggerhead turtles. The analysis of the longer fragment revealed more variants overall than in the shorter segments. The genetic data presented here are likely to improve assignment and population genetic analyses, with significant conservation and research applications.     

Genomic diversity and differentiation of a managed island wild boar population

The evolution of island populations in natural systems is driven by local adaptation and genetic drift. However, evolutionary pathways may be altered by humans in several ways. The wild boar (WB) (Sus scrofa) is an iconic game species occurring in several islands, where it has been strongly managed since prehistoric times. We examined genomic diversity at 49 803 single-nucleotide polymorphisms in 99 Sardinian WBs and compared them with 196 wild specimens from mainland Europe and 105 domestic pigs (DP; 11 breeds). High levels of genetic variation were observed in Sardinia (80.9% of the total number of polymorphisms), which can be only in part associated to recent genetic introgression. Both Principal Component Analysis and Bayesian clustering approach revealed that the Sardinian WB population is highly differentiated from the other European populations (F_ST=0.126–0.138), and from DP (F_ST=0.169). Such evidences were mostly unaffected by an uneven sample size, although clustering results in reference populations changed when the number of individuals was standardized. Runs of homozygosity (ROHs) pattern and distribution in Sardinian WB are consistent with a past expansion following a bottleneck (small ROHs) and recent population substructuring (highly homozygous individuals). The observed effect of a non-random selection of Sardinian individuals on diversity, F_ST and ROH estimates, stressed the importance of sampling design in the study of structured or introgressed populations. Our results support the heterogeneity and distinctiveness of the Sardinian population and prompt further investigations on its origins and conservation status.     

Peeling Back the Evolutionary Layers of Molecular Mechanisms Responsive to Exercise-Stress in the Skeletal Muscle of the Racing Horse

The modern horse (Equus caballus) is the product of over 50 million yrs of evolution. The athletic abilities of the horse have been enhanced during the past 6000 yrs under domestication. Therefore, the horse serves as a valuable model to understand the physiology and molecular mechanisms of adaptive responses to exercise. The structure and function of skeletal muscle show remarkable plasticity to the physical and metabolic challenges following exercise. Here, we reveal an evolutionary layer of responsiveness to exercise-stress in the skeletal muscle of the racing horse. We analysed differentially expressed genes and their co-expression networks in a large-scale RNA-sequence dataset comparing expression before and after exercise. By estimating genome-wide d_N/d_S ratios using six mammalian genomes, and F_ST and iHS using re-sequencing data derived from 20 horses, we were able to peel back the evolutionary layers of adaptations to exercise-stress in the horse. We found that the oldest and thickest layer (d_N/d_S) consists of system-wide tissue and organ adaptations. We further find that, during the period of horse domestication, the older layer (F_ST) is mainly responsible for adaptations to inflammation and energy metabolism, and the most recent layer (iHS) for neurological system process, cell adhesion, and proteolysis.     

A genome scan for selection signatures in Taihu pig breeds using next-generation sequencing

Taihu pig breeds are the most prolific breeds of swine in the world, and they also have superior economic traits, including high resistance to disease, superior meat quality, high resistance to crude feed and a docile temperament. The formation of these phenotypic characteristics is largely a result of long-term artificial or natural selection. Therefore, exploring selection signatures in the genomes of the Taihu pigs will help us to identify porcine genes related to productivity traits, disease and behaviour. In this study, we used both intra-population (Relative Extend Haplotype Homozygosity Test (REHH)) and inter-population (the Cross-Population Extend Haplotype Homozygosity Test (XPEHH); F-STATISTICS, F_ST) methods to detect genomic regions that might be under selection process in Taihu pig breeds. As a result, we found 282 (REHH) and 112 (XPEHH) selection signature candidate regions corresponding to 159.78 Mb (6.15%) and 62.29 Mb (2.40%) genomic regions, respectively. Further investigations of the selection candidate regions revealed that many genes under these genomic regions were related to reproductive traits (such as the TLR9 gene), coat colour (such as the KIT gene) and fat metabolism (such as the CPT1A and MAML3 genes). Furthermore, gene enrichment analyses showed that genes under the selection candidate regions were significantly over-represented in pathways related to diseases, such as autoimmune thyroid and asthma diseases. In conclusion, several candidate genes potentially under positive selection were involved in characteristics of Taihu pig. These results will further allow us to better understand the mechanisms of selection in pig breeding.     

Genetic and morphological variability in the Raddia brasiliensis complex (Poaceae: Bambusoideae)

Raddia brasiliensis forms a species complex with the recently segregated R. megaphylla, R. lancifolia, R. soderstromii and R. stolonifera, occurring in the Atlantic rainforest, Brazil. Allozymic markers were used in 272 individuals of 14 populations of this group to investigate its genetic variability, correlating this with morphological variability, and testing the proposed taxonomy based on multivariate morphometrics. Genetic variability was low in almost all populations (P = 22.2–66.7, A = 1.3–2.0, H _e=0.04–0.17). R. brasiliensis showed a very high endogamy (F _IS = 0.329). Values for genetic and morphological structuring were very high to high (F _ST = 0.43, A _MRPP = 0.22; F _ST = 0.19, A _MRPP = 0.10 and F _ST = 0.18, A _MRPP = 0.39), respectively, for R. brasiliensis, R. soderstromii and R. megaphylla. The lowest genetic identity between populations was also found in R. brasiliensis, and the highest morphological differentiation was found between populations of R. megaphylla. Allozymic and morphological data were congruent and complementary, and confirm that we are dealing with five distinct species as previously circumscribed.     

Genetic Diversity in Introduced Golden Mussel Populations Corresponds to Vector Activity

We explored possible links between vector activity and genetic diversity in introduced populations of Limnoperna fortunei by characterizing the genetic structure in native and introduced ranges in Asia and South America. We surveyed 24 populations: ten in Asia and 14 in South America using the mitochondrial cytochrome c oxidase subunit I (COI) gene, as well as eight polymorphic microsatellite markers. We performed population genetics and phylogenetic analyses to investigate population genetic structure across native and introduced regions. Introduced populations in Asia exhibit higher genetic diversity (H _E = 0.667–0.746) than those in South America (H _E = 0.519–0.575), suggesting higher introduction effort for the former populations. We observed pronounced geographical structuring in introduced regions, as indicated by both mitochondrial and nuclear markers based on multiple genetic analyses including pairwise Ф_ST, F _ST, Bayesian clustering method, and three-dimensional factorial correspondence analyses. Pairwise F _ST values within both Asia (F _ST = 0.017–0.126, P = 0.000–0.009) and South America (F _ST = 0.004–0.107, P = 0.000–0.721) were lower than those between continents (F _ST = 0.180–0.319, P = 0.000). Fine-scale genetic structuring was also apparent among introduced populations in both Asia and South America, suggesting either multiple introductions of distinct propagules or strong post-introduction selection and demographic stochasticity. Higher genetic diversity in Asia as compared to South America is likely due to more frequent propagule transfers associated with higher shipping activities between source and donor regions within Asia. This study suggests that the intensity of human-mediated introduction vectors influences patterns of genetic diversity in non-indigenous species.     

Detection of selection signatures in dairy and beef cattle using high-density genomic information

Background

Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs.

Results

Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (F_ST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the F_ST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global F_ST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection.

Conclusions

This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0127-3) contains supplementary material, which is available to authorized users.     

Genome-wide population structure and evolutionary history of the Frizarta dairy sheep

In the present study, we used genomic data, generated with a medium density single nucleotide polymorphisms (SNP) array, to acquire more information on the population structure and evolutionary history of the synthetic Frizarta dairy sheep. First, two typical measures of linkage disequilibrium (LD) were estimated at various physical distances that were then used to make inferences on the effective population size at key past time points. Population structure was also assessed by both multidimensional scaling analysis and k-means clustering on the distance matrix obtained from the animals’ genomic relationships. The Wright’s fixation F_ST index was also employed to assess herds’ genetic homogeneity and to indirectly estimate past migration rates. The Wright’s fixation F_IS index and genomic inbreeding coefficients based on the genomic relationship matrix as well as on runs of homozygosity were also estimated. The Frizarta breed displays relatively low LD levels with r² and |Dʹ| equal to 0.18 and 0.50, respectively, at an average inter-marker distance of 31 kb. Linkage disequilibrium decayed rapidly by distance and persisted over just a few thousand base pairs. Rate of LD decay (β) varied widely among the 26 autosomes with larger values estimated for shorter chromosomes (e.g. β=0.057, for OAR6) and smaller values for longer ones (e.g. β=0.022, for OAR2). The inferred effective population size at the beginning of the breed’s formation was as high as 549, was then reduced to 463 in 1981 (end of the breed’s formation) and further declined to 187, one generation ago. Multidimensional scaling analysis and k-means clustering suggested a genetically homogenous population, F_ST estimates indicated relatively low genetic differentiation between herds, whereas a heat map of the animals’ genomic kinship relationships revealed a stratified population, at a herd level. Estimates of genomic inbreeding coefficients suggested that most recent parental relatedness may have been a major determinant of the current effective population size. A denser than the 50k SNP panel may be more beneficial when performing genome wide association studies in the breed.     

genodive version 3.0: Easy‐to‐use software for the analysis of genetic data of diploids and polyploids

genodive version 3.0 is a user‐friendly program for the analysis of population genetic data. This version presents a major update from the previous version and now offers a wide spectrum of different types of analyses. genodive has an intuitive graphical user interface that allows direct manipulation of the data through transformation, imputation of missing data, and exclusion and inclusion of individuals, population and/or loci. Furthermore, genodive seamlessly supports 15 different file formats for importing or exporting data from or to other programs. One major feature of genodive is that it supports both diploid and polyploid data, up to octaploidy (2n = 8x) for some analyses, but up to hexadecaploidy (2n = 16x) for other analyses. The different types of analyses offered by genodive include multiple statistics for estimating population differentiation (φ_ST, F_ST, F?_ST, G_ST, G?_ST, G??_ST, D_est, R_ST, ρ), analysis of molecular variance‐based K‐means clustering, Hardy–Weinberg equilibrium, hybrid index, population assignment, clone assignment, Mantel test, Spatial Autocorrelation, 23 ways of calculating genetic distances, and both principal components and principal coordinates analyses. A unique feature of genodive is that it can also open data sets with nongenetic variables, for example environmental data or geographical coordinates that can be included in the analysis. In addition, genodive makes it possible to run several external programs (lfmm , structure , instruct and vegan ) directly from its own user interface, avoiding the need for data reformatting and use of the command line. genodive is available for computers running Mac OS X 10.7 or higher and can be downloaded freely from: http://www.patrickmeirmans.com/software .     

Population Genomic Analyses Based on 1 Million SNPs in Commercial Egg Layers

Identifying signatures of selection can provide valuable insight about the genes or genomic regions that are or have been under selective pressure, which can lead to a better understanding of genotype-phenotype relationships. A common strategy for selection signature detection is to compare samples from several populations and search for genomic regions with outstanding genetic differentiation. Wright''s fixation index, F_ST, is a useful index for evaluation of genetic differentiation between populations. The aim of this study was to detect selective signatures between different chicken groups based on SNP-wise F_ST calculation. A total of 96 individuals of three commercial layer breeds and 14 non-commercial fancy breeds were genotyped with three different 600K SNP-chips. After filtering a total of 1 million SNPs were available for F_ST calculation. Averages of F_ST values were calculated for overlapping windows. Comparisons of these were then conducted between commercial egg layers and non-commercial fancy breeds, as well as between white egg layers and brown egg layers. Comparing non-commercial and commercial breeds resulted in the detection of 630 selective signatures, while 656 selective signatures were detected in the comparison between the commercial egg-layer breeds. Annotation of selection signature regions revealed various genes corresponding to productions traits, for which layer breeds were selected. Among them were NCOA1, SREBF2 and RALGAPA1 associated with reproductive traits, broodiness and egg production. Furthermore, several of the detected genes were associated with growth and carcass traits, including POMC, PRKAB2, SPP1, IGF2, CAPN1, TGFb2 and IGFBP2. Our approach demonstrates that including different populations with a specific breeding history can provide a unique opportunity for a better understanding of farm animal selection.     

Comparative evaluation of genomic inbreeding parameters in seven commercial and autochthonous pig breeds

Single nucleotide polymorphism (SNP) genotyping tools, which can analyse thousands of SNPs covering the whole genome, have opened new opportunities to estimate the inbreeding level of animals directly using genome information. One of the most commonly used genomic inbreeding measures considers the proportion of the autosomal genome covered by runs of homozygosity (ROH), which are defined as continuous and uninterrupted chromosome portions showing homozygosity at all loci. In this study, we analysed the distribution of ROH in three commercial pig breeds (Italian Large White, n = 1968; Italian Duroc, n = 573; and Italian Landrace, n = 46) and four autochthonous breeds (Apulo-Calabrese, n = 90; Casertana, n = 90; Cinta Senese, n = 38; and Nero Siciliano, n = 48) raised in Italy, using SNP data generated from Illumina PorcineSNP60 BeadChip. We calculated ROH-based inbreeding coefficients (F_ROH) using ROH of different minimum length (1, 2, 4, 8, 16 Mbp) and compared them with several other genomic inbreeding coefficients (including the difference between observed and expected number of homozygous genotypes (F_HOM)) and correlated all these genomic-based measures with the pedigree inbreeding coefficient (F_PED) calculated for the pigs of some of these breeds. Autochthonous breeds had larger mean size of ROH than all three commercial breeds. F_HOM was highly correlated (0.671 to 0.985) with F_ROH measures in all breeds. Apulo-Calabrese and Casertana had the highest F_ROH values considering all ROH minimum lengths (ranging from 0.273 to 0.189 and from 0.226 to 0.152, moving from ROH of minimum size of 1 Mbp (F_ROH1) to 16 Mbp (F_ROH16)), whereas the lowest F_ROH values were for Nero Siciliano (from 0.072 to 0.051) and Italian Large White (from 0.117 to 0.042). F_ROH decreased as the minimum length of ROH increased for all breeds. Italian Duroc had the highest correlations between all F_ROH measures and F_PED (from 0.514 to 0.523) and between F_HOM and F_PED (0.485). Among all analysed breeds, Cinta Senese had the lowest correlation between F_ROH and F_PED. This might be due to the imperfect measure of F_PED, which, mainly in local breeds raised in extensive production systems, cannot consider a higher level of pedigree errors and a potential higher relatedness of the founder population. It appeared that ROH better captured inbreeding information in the analysed breeds and could complement pedigree-based inbreeding coefficients for the management of these genetic resources.     

Unifying selection acts on competitive ability and relative growth rate in Scabiosa columbaria

Q_ST vs. F_ST comparisons can reveal diversifying or unifying selection pressures among populations for specific traits. In this study we performed Q_ST–F_ST analyses on eleven populations of Scabiosa columbaria from the Swiss Jura to reveal genetic differentiation in two quantitative traits (above-ground biomass and relative growth rate of leaf lengths) and in neutral molecular markers. Above-ground biomass of plants under competition has been shown to correlate with their competitive ability, which is an important fitness-related trait. We hypothesized that strong unifying selection acts on above-ground biomass, since underperformance would result in decreased fitness and overperformance is unlikely due to trade-offs with other plant functions.Overall G_ST (an F_ST analogue) was 0.12. Analysis of variance revealed that above-ground biomass and relative growth rate did not differ among populations, but both traits differed among seed families and were heritable (h² = 0.31 and h² = 0.35, respectively). Q_ST was close to zero for above-ground biomass and zero for relative growth rate of leaf lengths, and thus Q_ST was much lower than G_ST, indicating unifying selection on these traits.This conclusion is restricted by the limits of the used methodology. Q_ST < F_ST cannot always be considered as a proof for unifying selection, because in complex traits the assumption of purely additive effects of underlying genes may be violated. However, given the large differences between Q_ST and G_ST, together with substantial heritabilities of the traits under study, we conclude that our findings are not in contradiction with the hypothesis of unifying selection.     

Genetic structure of natural populations ofDryas iulia (Lepidoptera: Nymphalidae) revealed by enzyme polymorphism and mitochondrial DNA (mtDNA) restriction fragment length polymorphism (RFLP)

Dryas iulia appears to have undergone a mode of evolution different from that of other members of its subfamily (Heliconiinae). While other species constitute highly subdivided and inbred populations, those ofD. iulia are thought to be large and uniform. Analyzing six samples from Southern Brazil (state of Rio Grande do Sul) in relation to three enzyme systems (EST, LAP, and PGM) and their mtDNA RFLP patterns, we found that they are very similar at the molecular level. TheF statistics for enzyme polymorphism data revealed that inbreeding makes a great contribution to the population homozygosity, sinceF _IS equals 0.1322 andF _ST equals 0.0023. Since the chi-square test showed thatF _ST is not significant, we conclude that all localities belong to the same population. The mtDNA differentiation was about 12 times greater than for nuclear genes;F _ST was equivalent to 0.0265. We suggest that this difference is due to a higher dispersal of males, in relation to females.     

A genome-wide detection of selection signatures in conserved and commercial pig breeds maintained in Poland

Background

Identification of selection signatures can provide a direct insight into the mechanism of artificial selection and allow further disclosure of the candidate genes related to the animals’ phenotypic variation. Domestication and subsequent long-time selection have resulted in extensive phenotypic changes in domestic pigs, involving a number of traits, like behavior, body composition, disease resistance, reproduction and coat color. In this study, based on genotypes obtained from PorcineSNP60 Illumina assay we attempt to detect both diversifying and within-breed selection signatures in 530 pigs belonging to four breeds: Polish Landrace, Pu?awska, Z?otnicka White and Z?otnicka Spotted, of which the last three are a subject of conservative breeding and substantially represent the native populations.

Results

A two largely complementary statistical methods were used for signatures detection, including: pairwise F_ST and relative extended haplotype homozygosity (REHH) test. Breed-specific diversifying selection signals included several genes involved in processes connected with fertility, growth and metabolism which are potentially responsible for different phenotypes of the studied breeds. The diversifying selection signals also comprised PPARD gene that was previously found to have a large effect on the shape of the external ear in pigs or two genes encoding neuropeptide Y receptors (Y2 and Y5) involved in fat deposition and stress response which are important features differentiating the studied breeds. REHH statistics allowed detecting several within-breed selection signatures overlapping with genes connected with a range of functions including, among others: metabolic pathways, immune system response or implantation and development of the embryo.

Conclusions

The study provides many potential candidate genes with implication for traits selected in the individual breeds and gives strong basis for further studies aiming at identification of sources of variation among the studied pig breeds.