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.     

Whole-genome resequencing reveals selection signatures associated with milk production traits in African Kenana dairy zebu cattle

Milk production and composition are the most economically important traits affecting profitability in dairy cattle. In this study, we aimed at detecting signatures of positive selection in Kenana, known as one of the high milk production African indigenous zebu cattle, using next-generation sequencing data. To detect genomic signatures of positive selection, we applied three methods based on population comparison, fixation index (F_ST), cross population composite likelihood ratio (XP-CLR) and nucleotide diversity (Pi). Further analysis showed that several candidate genes such as CSN3, IGFBP-2, RORA, ABCG2, B4GALT1 and GHR are positively selected for milk production traits in Kenana cattle. The candidate genes and enriched pathways identified in this study may provide a basis for future genome-wide association studies and investigations into genomic targets of selection in dairy cattle.     

A genome map of divergent artificial selection between Bos taurus dairy cattle and Bos taurus beef cattle

A number of cattle breeds have become highly specialized for milk or beef production, following strong artificial selection for these traits. In this paper, we compare allele frequencies from 9323 single nucleotide polymorphism (SNP) markers genotyped in dairy and beef cattle breeds averaged in sliding windows across the genome, with the aim of identifying divergently selected regions of the genome between the production types. The value of the method for identifying selection signatures was validated by four sources of evidence. First, differences in allele frequencies between dairy and beef cattle at individual SNPs were correlated with the effects of those SNPs on production traits. Secondly, large differences in allele frequencies generally occurred in the same location for two independent data sets (correlation 0.45) between sliding window averages. Thirdly, the largest differences in sliding window average difference in allele frequencies were found on chromosome 20 in the region of the growth hormone receptor gene, which carries a mutation known to have an effect on milk production traits in a number of dairy populations. Finally, for the chromosome tested, the location of selection signatures between dairy and beef cattle was correlated with the location of selection signatures within dairy cattle.     

Genome-Wide Genetic Diversity and Differentially Selected Regions among Suffolk,Rambouillet, Columbia,Polypay, and Targhee Sheep

Sheep are among the major economically important livestock species worldwide because the animals produce milk, wool, skin, and meat. In the present study, the Illumina OvineSNP50 BeadChip was used to investigate genetic diversity and genome selection among Suffolk, Rambouillet, Columbia, Polypay, and Targhee sheep breeds from the United States. After quality-control filtering of SNPs (single nucleotide polymorphisms), we used 48,026 SNPs, including 46,850 SNPs on autosomes that were in Hardy-Weinberg equilibrium and 1,176 SNPs on chromosome × for analysis. Phylogenetic analysis based on all 46,850 SNPs clearly separated Suffolk from Rambouillet, Columbia, Polypay, and Targhee, which was not surprising as Rambouillet contributed to the synthesis of the later three breeds. Based on pair-wise estimates of F _ST, significant genetic differentiation appeared between Suffolk and Rambouillet (F _ST = 0.1621), while Rambouillet and Targhee had the closest relationship (F _ST = 0.0681). A scan of the genome revealed 45 and 41 differentially selected regions (DSRs) between Suffolk and Rambouillet and among Rambouillet-related breed populations, respectively. Our data indicated that regions 13 and 24 between Suffolk and Rambouillet might be good candidates for evaluating breed differences. Furthermore, ovine genome v3.1 assembly was used as reference to link functionally known homologous genes to economically important traits covered by these differentially selected regions. In brief, our present study provides a comprehensive genome-wide view on within- and between-breed genetic differentiation, biodiversity, and evolution among Suffolk, Rambouillet, Columbia, Polypay, and Targhee sheep breeds. These results may provide new guidance for the synthesis of new breeds with different breeding objectives.     

Genome‐wide variability and selection signatures in Italian island cattle breeds

In the present study, a sample of 88 animals belonging to four local (Modicana, Sarda, Sardo‐Bruna and Sardo‐Modicana) and one cosmopolitan (Italian Brown Swiss) cattle breeds were genotyped with a medium density SNP beadchip and compared to investigate their genetic diversity and the existence of selection signatures. A total of 43 012 SNPs distributed across all 29 autosomal chromosomes were retained after data quality control. Basic population statistics, Wright fixation index and runs of homozygosity (ROH) analyses confirmed that the Italian Brown Swiss genome was shaped mainly by selection, as underlined by the low values of heterozygosity and minor allele frequency. As expected, local cattle exhibited a large within‐breed genetic heterogeneity. The F_ST comparison revealing the largest number of significant SNPs was Sardo‐Bruna vs. Sardo‐Modicana, whereas the smallest was observed for Italian Brown Swiss vs. Sardo‐Modicana. Modicana exhibited the largest number of detected ROHs, whereas the smallest was observed for Sardo‐Modicana. Signatures of selection were detected in genomic regions that harbor genes involved in milk production traits for Italian Brown Swiss and fitness traits for local breeds. According to the results of multi‐dimensional scaling and the admixture analysis the Sardo‐Bruna is more similar to the Sarda than to the Italian Brown Swiss breed. Moreover, the Sardo‐Modicana is genetically closer to the Modicana than to the Sarda breed. Results of the present work confirm the usefulness of single nucleotide polymorphisms in deciphering the genetic architecture of livestock breeds.     

Selection for complex traits leaves little or no classic signatures of selection

Background

Selection signatures aim to identify genomic regions underlying recent adaptations in populations. However, the effects of selection in the genome are difficult to distinguish from random processes, such as genetic drift. Often associations between selection signatures and selected variants for complex traits is assumed even though this is rarely (if ever) tested. In this paper, we use 8 breeds of domestic cattle under strong artificial selection to investigate if selection signatures are co-located in genomic regions which are likely to be under selection.

Results

Our approaches to identify selection signatures (haplotype heterozygosity, integrated haplotype score and F_ST) identified strong and recent selection near many loci with mutations affecting simple traits under strong selection, such as coat colour. However, there was little evidence for a genome-wide association between strong selection signatures and regions affecting complex traits under selection, such as milk yield in dairy cattle. Even identifying selection signatures near some major loci was hindered by factors including allelic heterogeneity, selection for ancestral alleles and interactions with nearby selected loci.

Conclusions

Selection signatures detect loci with large effects under strong selection. However, the methodology is often assumed to also detect loci affecting complex traits where the selection pressure at an individual locus is weak. We present empirical evidence to suggests little discernible ‘selection signature’ for complex traits in the genome of dairy cattle despite very strong and recent artificial selection.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-246) contains supplementary material, which is available to authorized users.     

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.     

Detection of nitrogen deficiency QTL in juvenile wild barley introgression linesgrowing in a hydroponic system

Background

Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most important and challenging areas of research in animal genetics. However, currently there are relatively few genomic regions identified that have been subject to positive selection. In this study, a genome-wide scan using ~50,000 Single Nucleotide Polymorphisms (SNPs) was performed in an attempt to identify genomic regions associated with fat deposition in fat-tail breeds. This trait and its modification are very important in those countries grazing these breeds.

Results

Two independent experiments using either Iranian or Ovine HapMap genotyping data contrasted thin and fat tail breeds. Population differentiation using F_ST in Iranian thin and fat tail breeds revealed seven genomic regions. Almost all of these regions overlapped with QTLs that had previously been identified as affecting fat and carcass yield traits in beef and dairy cattle. Study of selection sweep signatures using F_ST in thin and fat tail breeds sampled from the Ovine HapMap project confirmed three of these regions located on Chromosomes 5, 7 and X. We found increased homozygosity in these regions in favour of fat tail breeds on chromosome 5 and X and in favour of thin tail breeds on chromosome 7.

Conclusions

In this study, we were able to identify three novel regions associated with fat deposition in thin and fat tail sheep breeds. Two of these were associated with an increase of homozygosity in the fat tail breeds which would be consistent with selection for mutations affecting fat tail size several thousand years after domestication.     

Genome‐wide detection of signatures of selection in Korean Hanwoo cattle

The Korean Hanwoo cattle have been intensively selected for production traits, especially high intramuscular fat content. It is believed that ancient crossings between different breeds contributed to forming the Hanwoo, but little is known about the genomic differences and similarities between other cattle breeds and the Hanwoo. In this work, cattle breeds were grouped by origin into four types and used for comparisons: the Europeans (represented by six breeds), zebu (Nelore), African taurine (N'Dama) and Hanwoo. All animals had genotypes for around 680 000 SNPs after quality control of genotypes. Average heterozygosity was lower in Nelore and N'Dama (0.22 and 0.21 respectively) than in Europeans (0.26–0.31, with Shorthorn as outlier at 0.24) and Hanwoo (0.29). Pairwise F_ST analyses demonstrated that Hanwoo are more related to European cattle than to Nelore, with N'Dama in an intermediate position. This finding was corroborated by principal components and unsupervised hierarchical clustering. Using genome‐wide smoothed F_ST, 55 genomic regions potentially under positive selection in Hanwoo were identified. Among these, 29 were regions also detected in previous studies. Twenty‐four regions were exclusive to Hanwoo, and a number of other regions were shared with one or two of the other groups. These regions overlap a number of genes that are related to immune, reproduction and fatty acid metabolism pathways. Further analyses are needed to better characterize the ancestry of the Hanwoo cattle and to define the genes responsible to the identified selection peaks.     

Use of locally weighted scatterplot smoothing (LOWESS) regression to study selection signatures in Piedmontese and Italian Brown cattle breeds

Selection is the major force affecting local levels of genetic variation in species. The availability of dense marker maps offers new opportunities for a detailed understanding of genetic diversity distribution across the animal genome. Over the last 50 years, cattle breeds have been subjected to intense artificial selection. Consequently, regions controlling traits of economic importance are expected to exhibit selection signatures. The fixation index (F_st) is an estimate of population differentiation, based on genetic polymorphism data, and it is calculated using the relationship between inbreeding and heterozygosity. In the present study, locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach were used to investigate selection signatures in two cattle breeds with different production aptitudes (dairy and beef). F_st was calculated for 42 514 SNP marker loci distributed across the genome in 749 Italian Brown and 364 Piedmontese bulls. The statistical significance of F_st values was assessed using a control chart. The LOWESS technique was efficient in removing noise from the raw data and was able to highlight selection signatures in chromosomes known to harbour genes affecting dairy and beef traits. Examples include the peaks detected for BTA2 in the region where the myostatin gene is located and for BTA6 in the region harbouring the ABCG2 locus. Moreover, several loci not previously reported in cattle studies were detected.     

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 selection signature analyses identify genomic footprints in Reggiana cattle,the traditional breed of the Parmigiano-Reggiano cheese production system

Reggiana is an autochthonous cattle breed reared mainly in the province of Reggio Emilia, located in the North of Italy. Reggiana cattle (originally a triple-purpose population largely diffused in the North of Italy) are characterised by a typical solid red coat colour. About 2500 cows of this breed are currently registered to its herd book. Reggiana is now considered a dual-purpose breed even if it is almost completely dedicated to the production of a mono-breed branded Protected Designation of Origin Parmigiano-Reggiano cheese, which is the main driver of the sustainable conservation of this local genetic resource. In this study, we provided the first overview of genomic footprints that characterise Reggiana and define the diversity of this local cattle breed. A total of 168 Reggiana sires (all bulls born over 35 years for which semen was available) and other 3321 sires from 3 cosmopolitan breeds (Brown, Holstein and Simmental) were genotyped with the Illumina BovineSNP50 panel. ADMIXTURE analysis suggested that Reggiana breed might have been influenced, at least in part, by the other three breeds included in this study. Selection signatures in the Reggiana genome were identified using three statistical approaches based on allele frequency differences among populations or on properties of haplotypes segregating in the populations (fixation index (F_ST); integrated haplotype score; cross-population extended haplotype homozygosity). We identified several regions under peculiar selection in the Reggiana breed, particularly on bovine chromosome (BTA) 6 in the KIT gene region, that is known to be involved in coat colour pattern distribution, and within the region of the LAP3, NCAPG and LCORL genes, that are associated with stature, conformation and carcass traits. Another already known region that includes the PLAG1 gene (BTA14), associated with conformation traits, showed a selection signature in the Reggiana cattle. On BTA18, a signal of selection included the MC1R gene that causes the red coat colour in cattle. Other selection sweeps were in regions, with high density of quantitative trait loci for milk production traits (on BTA20) and in several other large regions that might have contributed to shape and define the Reggiana genome (on BTA17 and BTA29). All these results, overall, indicate that the Reggiana genome might still contain several signs of its multipurpose and non-specialised utilisation, as already described for other local cattle populations, in addition to footprints derived by its ancestral origin and by its adaptation to the specialised Parmigiano-Reggiano cheese production system.     

Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds

Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, F_st and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.     

Genetic analysis of prolactin gene in Pakistani cattle

Prolactin (PRL) is a polypeptide hormone, secreted mainly by the anterior pituitary gland. It is involved in many endocrine activities. The key functions of PRL are related to reproduction and lactation in mammals. To ascertain the presence of polymorphisms in the bovine PRL gene (bPRL), the bPRL gene was sequenced. Five mutations were identified in exonic region and eleven in associated intronic regions in 100 cattle from four Pakistani cattle breeds. Haplotype of predicted amino acid changes represent a common alteration at codon 222 from R-Arginine into K-Lysine in all four breeds. Significant statistical variations were observed in the distribution of single nucleotide polymorphism (SNP) in various cattle populations. However, on basis of present study, an association of these SNPs with milk performance traits in four Pakistani cow breeds cannot be truly replicated but at least can be effective DNA markers for some of the breeds studied. Linkage analysis between these SNPs on larger populations can be useful for the association with milk production traits. Furthermore, present study may be used for marker-assisted selection and management in cattle breeding program in local cattle breeds.     

Signatures of selection in five Italian cattle breeds detected by a 54K SNP panel

In this study we used a medium density panel of SNP markers to perform population genetic analysis in five Italian cattle breeds. The BovineSNP50 BeadChip was used to genotype a total of 2,935 bulls of Piedmontese, Marchigiana, Italian Holstein, Italian Brown and Italian Pezzata Rossa breeds. To determine a genome-wide pattern of positive selection we mapped the F _st values against genome location. The highest F _st peaks were obtained on BTA6 and BTA13 where some candidate genes are located. We identified selection signatures peculiar of each breed which suggest selection for genes involved in milk or meat traits. The genetic structure was investigated by using a multidimensional scaling of the genetic distance matrix and a Bayesian approach implemented in the STRUCTURE software. The genotyping data showed a clear partitioning of the cattle genetic diversity into distinct breeds if a number of clusters equal to the number of populations were given. Assuming a lower number of clusters beef breeds group together. Both methods showed all five breeds separated in well defined clusters and the Bayesian approach assigned individuals to the breed of origin. The work is of interest not only because it enriches the knowledge on the process of evolution but also because the results generated could have implications for selective breeding programs.     

Relationship of serum guanase levels with economic characters in zebu purebred and temperate × zebu crossbred dairy cattle

Serum guanase levels of Indian Zebu (Hariana) cattle and its crosses with different exotic levels of temperate breeds of dairy cattle were estimated in 527 animals, and their associations with economic characters were determined. The overall mean value of serum guanase level was 13.46±0.45 IU/ml of serum. An inverse relationship between the concentration of the enzyme and the frequency of cattle falling within a definite range was observed, as over 75% of the animals possessed 1 to 20 IU/ml of serum guanase. An analysis of variance revealed significant differences (P<0.01) in enzyme levels among different genetic groups under study. Hariana (Zebu) purebreds had significantly higher enzyme levels (19.60±1.85) than any of the crossbred groups, whose enzyme levels ranged from 8.99±1.41 in Red Dane F₁ half-breds to 14.30±1.11 in Brown Swiss F₁ half-breds. The correlation and regression coefficients were significantly positive for reproductive traits such as age at first service and age at first calving, and significantly negative for production traits such as lactation yield and lactation length. These results suggest that selection of dairy cattle based on low serum guanase levels might result in correlated improvements in dairy cattle productivity.     

Population genomic,olfactory, dietary,and gut microbiota analyses demonstrate the unique evolutionary trajectory of feral pigs

Domestication is an intriguing evolutionary process. Many domestic populations are subjected to strong human-mediated selection, and when some individuals return to the wild, they are again subjected to selective forces associated with new environments. Generally, these feral populations evolve into something different from their wild predecessors and their members typically possess a combination of both wild and human selected traits. Feralisation can manifest in different forms on a spectrum from a wild to a domestic phenotype. This depends on how the rewilded domesticated populations can readapt to natural environments based on how much potential and flexibility the ancestral genome retains after its domestication signature. Whether feralisation leads to the evolution of new traits that do not exist in the wild or to convergence with wild forms, however, remains unclear. To address this question, we performed population genomic, olfactory, dietary, and gut microbiota analyses on different populations of Sus scrofa (wild boar, hybrid, feral and several domestic pig breeds). Porcine single nucleotide polymorphisms (SNPs) analysis shows that the feral population represents a cluster distinctly separate from all others. Its members display signatures of past artificial selection, as demonstrated by values of F_ST in specific regions of the genome and bottleneck signature, such as the number and length of runs of homozygosity. Generalised F_ST values, reacquired olfactory abilities, diet, and gut microbiota variation show current responses to natural selection. Our results suggest that feral pigs are an independent evolutionary unit which can persist so long as levels of human intervention remain unchanged.     

A Post-GWAS Replication Study Confirming the PTK2 Gene Associated with Milk Production Traits in Chinese Holstein

Our initial genome-wide association study (GWAS) demonstrated that two SNPs (ARS-BFGL-NGS-33248, UA-IFASA-9288) within the protein tyrosine kinase 2 (PTK2) gene were significantly associated with milk production traits in Chinese Holstein dairy cattle. To further validate if the statistical evidence provided in GWAS were true-positive findings, a replication study was performed herein through genotype-phenotype associations. The two tested SNPs were found to show significant associations with milk production traits, which confirmed the associations observed in the original study. Specifically, SNPs lying in the PTK2 gene were also detected by sequencing 14 unrelated sires in Chinese Holsteins and a total of thirty-three novel SNPs were identified. Thirteen out of these identified SNPs were genotyped and tested for association with milk production traits in an independent resource population. After Bonferroni correction for multiple testing, twelve SNPs were statistically significant for more than two milk production traits. Analyses of pairwise D’ measures of linkage disequilibrium (LD) between all SNPs were also explored. Two haplotype blocks were inferred and the association study at haplotype level revealed similar effects on milk production traits. In addition, the RNA expression analyses revealed that a non-synonymous coding SNP (g.4061098T>G) was involved in the regulation of gene expression. Thus the findings presented here provide strong evidence for associations of PTK2 variants with dairy production traits and may be applied in Chinese Holstein breeding program.     

Empirical Distributions of F ST from Large-Scale Human Polymorphism Data

Studies of the apportionment of human genetic variation have long established that most human variation is within population groups and that the additional variation between population groups is small but greatest when comparing different continental populations. These studies often used Wright’s F _ST that apportions the standardized variance in allele frequencies within and between population groups. Because local adaptations increase population differentiation, high-F _ST may be found at closely linked loci under selection and used to identify genes undergoing directional or heterotic selection. We re-examined these processes using HapMap data. We analyzed 3 million SNPs on 602 samples from eight worldwide populations and a consensus subset of 1 million SNPs found in all populations. We identified four major features of the data: First, a hierarchically F _ST analysis showed that only a paucity (12%) of the total genetic variation is distributed between continental populations and even a lesser genetic variation (1%) is found between intra-continental populations. Second, the global F _ST distribution closely follows an exponential distribution. Third, although the overall F _ST distribution is similarly shaped (inverse J), F _ST distributions varies markedly by allele frequency when divided into non-overlapping groups by allele frequency range. Because the mean allele frequency is a crude indicator of allele age, these distributions mark the time-dependent change in genetic differentiation. Finally, the change in mean-F _ST of these groups is linear in allele frequency. These results suggest that investigating the extremes of the F _ST distribution for each allele frequency group is more efficient for detecting selection. Consequently, we demonstrate that such extreme SNPs are more clustered along the chromosomes than expected from linkage disequilibrium for each allele frequency group. These genomic regions are therefore likely candidates for natural selection.     

A genome-wide scan for signatures of directional selection in domesticated pigs

Background

Animal domestication involved drastic phenotypic changes driven by strong artificial selection and also resulted in new populations of breeds, established by humans. This study aims to identify genes that show evidence of recent artificial selection during pig domestication.

Results

Whole-genome resequencing of 30 individual pigs from domesticated breeds, Landrace and Yorkshire, and 10 Asian wild boars at ~16-fold coverage was performed resulting in over 4.3 million SNPs for 19,990 genes. We constructed a comprehensive genome map of directional selection by detecting selective sweeps using an F_ST-based approach that detects directional selection in lineages leading to the domesticated breeds and using a haplotype-based test that detects ongoing selective sweeps within the breeds. We show that candidate genes under selection are significantly enriched for loci implicated in quantitative traits important to pig reproduction and production. The candidate gene with the strongest signals of directional selection belongs to group III of the metabolomics glutamate receptors, known to affect brain functions associated with eating behavior, suggesting that loci under strong selection include loci involved in behaviorial traits in domesticated pigs including tameness.

Conclusions

We show that a significant proportion of selection signatures coincide with loci that were previously inferred to affect phenotypic variation in pigs. We further identify functional enrichment related to behavior, such as signal transduction and neuronal activities, for those targets of selection during domestication in pigs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1330-x) contains supplementary material, which is available to authorized users.