Detecting Signatures of Selection Through Haplotype Differentiation Among Hierarchically Structured Populations

The detection of molecular signatures of selection is one of the major concerns of modern population genetics. A widely used strategy in this context is to compare samples from several populations and to look for genomic regions with outstanding genetic differentiation between these populations. Genetic differentiation is generally based on allele frequency differences between populations, which are measured by F_ST or related statistics. Here we introduce a new statistic, denoted hapFLK, which focuses instead on the differences of haplotype frequencies between populations. In contrast to most existing statistics, hapFLK accounts for the hierarchical structure of the sampled populations. Using computer simulations, we show that each of these two features—the use of haplotype information and of the hierarchical structure of populations—significantly improves the detection power of selected loci and that combining them in the hapFLK statistic provides even greater power. We also show that hapFLK is robust with respect to bottlenecks and migration and improves over existing approaches in many situations. Finally, we apply hapFLK to a set of six sheep breeds from Northern Europe and identify seven regions under selection, which include already reported regions but also several new ones. We propose a method to help identifying the population(s) under selection in a detected region, which reveals that in many of these regions selection most likely occurred in more than one population. Furthermore, several of the detected regions correspond to incomplete sweeps, where the favorable haplotype is only at intermediate frequency in the population(s) under selection.     

Assessing signatures of selection through variation in linkage disequilibrium between taurine and indicine cattle

Background

Signatures of selection are regions in the genome that have been preferentially increased in frequency and fixed in a population because of their functional importance in specific processes. These regions can be detected because of their lower genetic variability and specific regional linkage disequilibrium (LD) patterns.

Methods

By comparing the differences in regional LD variation between dairy and beef cattle types, and between indicine and taurine subspecies, we aim at finding signatures of selection for production and adaptation in cattle breeds. The VarLD method was applied to compare the LD variation in the autosomal genome between breeds, including Angus and Brown Swiss, representing taurine breeds, and Nelore and Gir, representing indicine breeds. Genomic regions containing the top 0.01 and 0.1 percentile of signals were characterized using the UMD3.1 Bos taurus genome assembly to identify genes in those regions and compared with previously reported selection signatures and regions with copy number variation.

Results

For all comparisons, the top 0.01 and 0.1 percentile included 26 and 165 signals and 17 and 125 genes, respectively, including TECRL, BT.23182 or FPPS, CAST, MYOM1, UVRAG and DNAJA1.

Conclusions

The VarLD method is a powerful tool to identify differences in linkage disequilibrium between cattle populations and putative signatures of selection with potential adaptive and productive importance.     

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 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.     

Detection of selection signatures in the genome of a farmed population of anadromous rainbow trout (Oncorhynchus mykiss)

Domestication processes and artificial selection are likely to leave signatures that can be detected at a molecular level in farmed rainbow trout (Oncorhynchus mykiss). These signatures of selection are genomic regions that contain functional genetic variants conferring a higher fitness to their bearers. We genotyped 749 rainbow trout from a commercial population using a rainbow trout Axiom 57 K SNP array panel and identified putative genomic regions under selection using the pcadapt, Composite Likelihood Ratio (CLR) and Integrated Haplotype Score (iHS) methods. After applying quality-control pipelines and statistical analyses, we detected 12, 96 and 16 SNPs putatively under selection, associated with 96, 781 and 115 candidate genes, respectively. Several of these candidate genes were associated with growth, early development, reproduction, behavior and immune system traits. In addition, some of the SNPs were found in interesting regions located in autosomal inversions on Omy05 and Omy20. These findings could represent a genome-wide map of selection signatures in farmed rainbow trout and could be important in explaining domestication and selection for genetic traits of commercial interest.     

Signatures of Diversifying Selection in European Pig Breeds

Following domestication, livestock breeds have experienced intense selection pressures for the development of desirable traits. This has resulted in a large diversity of breeds that display variation in many phenotypic traits, such as coat colour, muscle composition, early maturity, growth rate, body size, reproduction, and behaviour. To better understand the relationship between genomic composition and phenotypic diversity arising from breed development, the genomes of 13 traditional and commercial European pig breeds were scanned for signatures of diversifying selection using the Porcine60K SNP chip, applying a between-population (differentiation) approach. Signatures of diversifying selection between breeds were found in genomic regions associated with traits related to breed standard criteria, such as coat colour and ear morphology. Amino acid differences in the EDNRB gene appear to be associated with one of these signatures, and variation in the KITLG gene may be associated with another. Other selection signals were found in genomic regions including QTLs and genes associated with production traits such as reproduction, growth, and fat deposition. Some selection signatures were associated with regions showing evidence of introgression from Asian breeds. When the European breeds were compared with wild boar, genomic regions with high levels of differentiation harboured genes related to bone formation, growth, and fat deposition.     

Integration of selection signatures and multi-trait GWAS reveals polygenic genetic architecture of carcass traits in beef cattle

Carcass merits are widely considered as economically important traits affecting beef production in the beef cattle industry. However, the genetic basis of carcass traits remains to be well understood. Here, we applied multiple methods, including the Composite of Likelihood Ratio (CLR) and Genome-wide Association Study (GWAS), to explore the selection signatures and candidate variants affecting carcass traits. We identified 11,600 selected regions overlapping with 2214 candidate genes, and most of those were enriched in binding and gene regulation. Notably, we identified 66 and 110 potential variants significantly associated with carcass traits using single-trait and multi-traits analyses, respectively. By integrating selection signatures with single and multi-traits associations, we identified 12 and 27 putative genes, respectively. Several highly conserved missense variants were identified in OR5M13D, NCAPG, and TEX2. Our study supported polygenic genetic architecture of carcass traits and provided novel insights into the genetic basis of complex traits in beef cattle.     

Uncovering Signals of Positive Selection in Peruvian Populations from Three Ecological Regions

Peru hosts extremely diverse ecosystems which can be broadly classified into the following three major ecoregions: the Pacific desert coast, the Andean highlands, and the Amazon rainforest. Since its initial peopling approximately 12,000 years ago, the populations inhabiting such ecoregions might have differentially adapted to their contrasting environmental pressures. Previous studies have described several candidate genes underlying adaptation to hypobaric hypoxia among Andean highlanders. However, the adaptive genetic diversity of coastal and rainforest populations has been less studied. Here, we gathered genome-wide single-nucleotide polymorphism-array data from 286 Peruvians living across the three ecoregions and analyzed signals of recent positive selection through population differentiation and haplotype-based selection scans. Among highland populations, we identify candidate genes related to cardiovascular function (TLL1, DUSP27, TBX5, PLXNA4, SGCD), to the Hypoxia-Inducible Factor pathway (TGFA, APIP), to skin pigmentation (MITF), as well as to glucose (GLIS3) and glycogen metabolism (PPP1R3C, GANC). In contrast, most signatures of adaptation in coastal and rainforest populations comprise candidate genes related to the immune system (including SIGLEC8, TRIM21, CD44, and ICAM1 in the coast; CBLB and PRDM1 in the rainforest; and BRD2, HLA-DOA, HLA-DPA1 regions in both), possibly as a result of strong pathogen-driven selection. This study identifies candidate genes related to human adaptation to the diverse environments of South America.     

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.     

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.     

Genome-wide detection of selective signatures in Simmental cattle

Artificial selection has greatly improved the beef production performance and changed its genetic basis. High-density SNP markers provide a way to track these changes and use selective signatures to search for the genes associated with artificial selection. In this study, we performed extended haplotype homozygosity (EHH) tests based on Illumina BovineSNP50 (54 K) Chip data from 942 Simmental cattle to identify significant core regions containing selective signatures, then verified the biological significance of these identified regions based on some commonly used bioinformatics analyses. A total of 224 regions over the whole genome in Simmental cattle showing the highest significance and containing some important functional genes, such as GHSR, TG and CANCNA2D1 were chosen. We also observed some significant terms in the enrichment analyses of second GO terms and KEGG pathways, indicating that these genes are associated with economically relevant cattle traits. This is the first detection of selection signature in Simmental cattle. Our findings significantly expand the selection signature map of the cattle genome, and identify functional candidate genes under positive selection for future genetic research.     

Detection of signatures of selective sweeps in the Blonde d'Aquitaine cattle breed

Identifying recent positive selection signatures in domesticated animals could provide information on genome response to strong directional selection from domestication and artificial selection and therefore could help in identifying mutations responsible for improved traits. We used genotyping data generated using Illumina's BovineSNP50 Genotyping BeadChips to identify selection signatures in the Blonde d'Aquitaine breed, a well‐muscled French beef breed. For this purpose, we employed a hidden Markov model‐based test, which detects selection by studying local variations in the allele frequency spectrum along the genome, within a single population. Three regions containing selective sweeps were identified. Annotation of genes located within these regions revealed interesting candidate genes. For example, myostatin (also known as GDF8), a known muscle growth factor inhibitor, is located within the selection signature region found on chromosome 2. In addition, we have identified chromosomal regions that show some evidence of selection within QTL regions for economically important traits. The results of this study could help to better understand the mechanisms related to the selection of the Blonde d'Aquitaine breed.     

Genomic consequences of selection and genome-wide association mapping in soybean

Background

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits.

Results

To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified.

Conclusions

These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1872-y) contains supplementary material, which is available to authorized users.     

Evidence of positive selection towards Zebuine haplotypes in the BoLA region of Brangus cattle

The Brangus breed was developed to combine the superior characteristics of both of its founder breeds, Angus and Brahman. It combines the high adaptability to tropical and subtropical environments, disease resistance, and overall hardiness of Zebu cattle with the reproductive potential and carcass quality of Angus. It is known that the major histocompatibility complex (MHC, also known as bovine leucocyte antigen: BoLA), located on chromosome 23, encodes several genes involved in the adaptive immune response and may be responsible for adaptation to harsh environments. The objective of this work was to evaluate whether the local breed ancestry percentages in the BoLA locus of a Brangus population diverged from the estimated genome-wide proportions and to identify signatures of positive selection in this genomic region. For this, 167 animals (100 Brangus, 45 Angus and 22 Brahman) were genotyped using a high-density single nucleotide polymorphism array. The local ancestry analysis showed that more than half of the haplotypes (55.0%) shared a Brahman origin. This value was significantly different from the global genome-wide proportion estimated by cluster analysis (34.7% Brahman), and the proportion expected by pedigree (37.5% Brahman). The analysis of selection signatures by genetic differentiation (F_st) and extended haplotype homozygosity-based methods (iHS and Rsb) revealed 10 and seven candidate regions, respectively. The analysis of the genes located within these candidate regions showed mainly genes involved in immune response-related pathway, while other genes and pathways were also observed (cell surface signalling pathways, membrane proteins and ion-binding proteins). Our results suggest that the BoLA region of Brangus cattle may have been enriched with Brahman haplotypes as a consequence of selection processes to promote adaptation to subtropical environments.     

The genomic basis of high-elevation adaptation in wild house mice (Mus musculus domesticus) from South America

Understanding the genetic basis of environmental adaptation in natural populations is a central goal in evolutionary biology. The conditions at high elevation, particularly the low oxygen available in the ambient air, impose a significant and chronic environmental challenge to metabolically active animals with lowland ancestry. To understand the process of adaptation to these novel conditions and to assess the repeatability of evolution over short timescales, we examined the signature of selection from complete exome sequences of house mice (Mus musculus domesticus) sampled across two elevational transects in the Andes of South America. Using phylogenetic analysis, we show that house mice colonized high elevations independently in Ecuador and Bolivia. Overall, we found distinct responses to selection in each transect and largely nonoverlapping sets of candidate genes, consistent with the complex nature of traits that underlie adaptation to low oxygen availability (hypoxia) in other species. Nonetheless, we also identified a small subset of the genome that appears to be under parallel selection at the gene and SNP levels. In particular, three genes (Col22a1, Fgf14, and srGAP1) bore strong signatures of selection in both transects. Finally, we observed several patterns that were common to both transects, including an excess of derived alleles at high elevation, and a number of hypoxia-associated genes exhibiting a threshold effect, with a large allele frequency change only at the highest elevations. This threshold effect suggests that selection pressures may increase disproportionately at high elevations in mammals, consistent with observations of some high-elevation diseases in humans.     

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.     

A genome-wide perspective on the diversity and selection signatures in indigenous goats using 53 K single nucleotide polymorphism array

Tibetan goats, Taihang goats, Jining grey goats, and Meigu goats are the representative indigenous goats in China, found in Qinghai-Tibet Plateau, Western pastoral area, Northern and Southern agricultural regions. Very few studies have conducted a comprehensive analysis of the genomic diversity and selection of these breeds. We genotyped 96 unrelated individuals, using goat 53 K Illumina BeadChip array, of the following goat breeds: Tibetan (TG), Taihang (THG), Jining grey (JGG), and Meigu (MGG). A total of 45 951 single nucleotide polymorphisms were filtered to estimate the genetic diversity and selection signatures. All breeds had a high proportion (over 95%) of polymorphic loci. The observed and excepted heterozygosity ranged from 0.338 (MGG) to 0.402 (JGG) and 0.339 (MGG) to 0.395 (JGG), respectively. Clustering analysis displayed a genetically distinct lineage for each breed, and their Fst were greater than 0.25, indicating that they had a higher genetic differentiation between groups. Furthermore, effective population size reduced in all four populations, indicating a loss of genetic diversity. In addition, runs of homozygosity were mainly distributed in 5–10 Mb. Lastly, we identified signature genes, which were closely related to high-altitude adaptation (ADIRF) and prolificity (CNTROB, SMC3, and PTEN). This study provides a valuable resource for future studies on genome-wide perspectives on the diversity and selection signatures of Chinese indigenous goats.     

Identifying candidate positive selection genes in Korean imported pig breeds

Domestication and artificial selection have modified the genome landscape of the pig. The identification of selection signatures in the genome can help to elucidate the selection mechanisms and uncover the causal genes related to the phenotypic variations between domestic pig breeds. We scanned the genomes of Korean imported pig breeds against native breeds using Z-transformed Fst (ZF_ST) and Heterozygosity (ZH_p) statistics to search for the signatures of positive selection. We identified 411 (ZF_ST?=?175; ZH_p?=?256) putatively selected genes in commercial breeds. The gene regions identified were harboring those related to immunity, coat color, reproduction function and other traits. Several genes (e.g., PLSCR4, AGTR1 and CORIN) were related to reproduction traits such as fertility, ovulation rate, and uterine function. This study revealed genes which improve our understanding of the biological mechanisms of higher litter sizes, the phenotype of interest, in higher litter pig breeds.     

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.     

A genome‐wide scan for selection signatures in Nellore cattle

Brazilian Nellore cattle (Bos indicus) have been selected for growth traits for over more than four decades. In recent years, reproductive and meat quality traits have become more important because of increasing consumption, exports and consumer demand. The identification of genome regions altered by artificial selection can potentially permit a better understanding of the biology of specific phenotypes that are useful for the development of tools designed to increase selection efficiency. Therefore, the aims of this study were to detect evidence of recent selection signatures in Nellore cattle using extended haplotype homozygosity methodology and BovineHD marker genotypes (>777 000 single nucleotide polymorphisms) as well as to identify corresponding genes underlying these signals. Thirty‐one significant regions (P < 0.0001) of possible recent selection signatures were detected, and 19 of these overlapped quantitative trait loci related to reproductive traits, growth, feed efficiency, meat quality, fatty acid profiles and immunity. In addition, 545 genes were identified in regions harboring selection signatures. Within this group, 58 genes were associated with growth, muscle and adipose tissue metabolism, reproductive traits or the immune system. Using relative extended haplotype homozygosity to analyze high‐density single nucleotide polymorphism marker data allowed for the identification of regions potentially under artificial selection pressure in the Nellore genome, which might be used to better understand autozygosity and the effects of selection on the Nellore genome.