A high resolution genome-wide scan for significant selective sweeps: an application to pooled sequence data in laying chickens

South African indigenous chickens' genetic diversity, and the adoption of ecological niche modelling and landscape genomics as strategic conservation techniques

Selection pressures found in the prevailing production environments have shaped the genetic structure of indigenous chickens we see today. Indigenous chickens, raised in villages, provide essential genetic resources and income for poverty alleviation by providing affordable protein. However, they are threatened by predators, emerging diseases, and market demand for ideal breeds and fast production which causes loss of their valuable traits. The lack of knowledge about genetic diversity and genetic mechanisms underlying adaptive variants may compromise the goal of conserving indigenous chicken breeds. The main insights of the study are that indigenous chickens are highly diversified, and environmental factors play a key role in enabling chicken adaptation and distribution. Genomic and spatial technologies have made it possible to explore the genetic structure and fully comprehend the mechanism underlying the local adaptation of indigenous chickens. These technologies can aid in creating programs that enhance productivity and promote climate-resilient breeds. This review explores the impact of natural selection on indigenous chicken, genetic diversity, population size, and the advancement of technologies in understanding local adaptation drivers. In conclusion, this review highlights the importance of studying the habitats and how this will guide in conserving local breeds in their intended production environment.

Genome-Wide Scan for Selective Sweeps Reveals Novel Loci Associated with Prolificacy in Iranian Sheep Breeds in Comparison with Highly Prolific Exotic Breed

Domestication and selection significantly changed phenotypic traits in modern domestic animals. To identify the genomic regions associated with prolificacy in this study, 837 ewes from three Iranian indigenous sheep breeds, consisting of Baluchi, Lori-Bakhtiari, and Zandi uniparous breeds, and one Greek highly prolific dairy sheep, namely Chios, were genotyped using OvineSNP50K arrays. Statistical tests were then performed using different and complementary methods based on either site frequency (FST) and haplotype (hapFLK) between populations, followed by a pathway analysis of the genes contained in the selected regions. The results revealed that for the top 0.01 percentile of the obtained FST values, 16 genomic regions on chromosomes 2, 3, 4, 7, 8, 9, 13, 14, 16, 18, 19, and 20, and for hapFLK values, 3 regions located on chromosomes 3, 7, and 13, were under selection. A bioinformatic analysis of these genomic regions showed that these loci overlapped with potential candidate genes associated with prolificacy in sheep including GNAQ, COL5A2, COL3A1, HECW1, FBN1, COMMD3, RYR1, CCL28, SERPINA14, and HSPA2. These regions also overlapped with some quantitative trait loci (QTLs) linked to prolificacy traits, milk yield, and body weight. These findings suggest that future research could further link these genomic regions to prolificacy traits in sheep.

Unveiling population structure and selection signatures of riverine and genetically improved rohu, Labeo rohita using genome wide SNPs

BACKGROUND

Captive breeding, along with artificial selection can significantly impact population structure by influencing allele frequencies and driving populations towards specific adaptation. Selective sweeps are powerful forces in shaping genetic variation within populations and can drive rapid spread of beneficial alleles while simultaneously reducing genetic diversity in localized regions of the genome. The present work was undertaken to assess the genetic structure and consequences of artificial selection in 10th generation of genetically improved rohu by comparing with wild populations.

METHODS AND RESULTS

The present study used 11,022 high-quality genome wide SNPs to compare the population genetic structure and signatures of selection between Jayanti rohu population and its wild counterpart. Outlier analysis revealed presence of 14 adaptive SNPs, out of which 5 were classified to be under decisive selection pressure. Notably, Jayanti rohu (JR) displayed 297 private alleles exclusive to its population. Chromosomes 7 and 16 emerged as potential hotspots containing a majority of the identified SNPs. Structure and principal component analysis revealed two distinct clusters, effectively distinguishing the JR and wild rohu populations. Phylogenetic analysis indicated a separate cluster of JR population distant from wild groups.

CONCLUSION

The results of present study shall help in elucidating patterns of genetic variation and characterizing selection signatures associated with captive bred and natural populations of rohu. The genomic resources generated through this work shall be helpful in improving the traceability of selectively bred germplasm for developing future strategies of genetic management.

Dissecting Selective Signatures and Candidate Genes in Grandparent Lines Subject to High Selection Pressure for Broiler Production and in a Local Russian Chicken Breed of Ushanka

Breeding improvements and quantitative trait genetics are essential to the advancement of broiler production. The impact of artificial selection on genomic architecture and the genetic markers sought remains a key area of research. Here, we used whole-genome resequencing data to analyze the genomic architecture, diversity, and selective sweeps in Cornish White (CRW) and Plymouth Rock White (PRW) transboundary breeds selected for meat production and, comparatively, in an aboriginal Russian breed of Ushanka (USH). Reads were aligned to the reference genome bGalGal1.mat.broiler.GRCg7b and filtered to remove PCR duplicates and low-quality reads using BWA-MEM2 and bcftools software; 12,563,892 SNPs were produced for subsequent analyses. Compared to CRW and PRW, USH had a lower diversity and a higher genetic distinctiveness. Selective sweep regions and corresponding candidate genes were examined based on ZFST, hapFLK, and ROH assessment procedures. Twenty-seven prioritized chicken genes and the functional projection from human homologs suggest their importance for selection signals in the studied breeds. These genes have a functional relationship with such trait categories as body weight, muscles, fat metabolism and deposition, reproduction, etc., mainly aligned with the QTLs in the sweep regions. This information is pivotal for further executing genomic selection to enhance phenotypic traits.

Detection of selective sweep in European wild sheep breeds

In wild animal populations, there is a differentiation between populations due to natural selection. The direction and pressure of natural selection in the wild sheep are different in the various geographic areas. Linkage disequilibrium studies showed that regions of the genome in whole wild sheep are under natural selection and that natural selection can affect immune or reproductive or metabolic traits. The study aimed to identify genomic regions under natural selection in wild sheep. For this purpose, the genetic information of 24 European wild sheep and 24 Sardinian wild sheep was used. The genotypes were determined using Illumina 50 K SNPChip arrays based on Oar_4.0 version of the sheep genome. After quality control steps, finally, 31,560 SNP markers were analyzed. The value of LD was calculated by calculating the r2 statistic between all pairs of locations through PLINK software. To identify signs of selection based on linkage disequilibrium methods, an extended haplotype homozygosity test of XP-EHH crossing population and iHS intrapopulation was used. The results of iHS studies showed that in European and Sardinian wild sheep, the highest iHS coefficient under natural selection was observed on 3 and 2 chromosome numbers, respectively. Also, the results of XP-EHH studies showed that the largest XP-EHH coefficients under natural selection in European wild sheep compared to Sardinian and vice versa in Sardinian wild sheep compared to European wild sheep were observed on 3 and 16 chromosome numbers, respectively. In addition, the results of gene cycle studies showed that COPB1, SEC24D, ZDHHC17, BBS4, RFX3, SLC26A8, CAMK2D, GRIA1, GRM1, GRID2, PPP2R1A, CPEB4, PLEKHA5 and KIF13A, VPS39, VPS53, DTNBP1, DYNC1I1, FAM91A genes are under natural selection in Sardinian and European wild sheeps, respectively. The direction and selection pressure of natural selection in the two breeds of wild sheep is different due to different geographic conditions.

Environmental and Socio-Cultural Factors Impacting the Unique Gene Pool Pattern of Mae Hong-Son Chicken

Understanding the genetic diversity of domestic chicken breeds under the impact of socio-cultural and ecological dynamics is vital for the conservation of natural resources. Mae Hong Son chicken is a local breed of North Thai domestic chicken widely distributed in Mae Hong Son Province, Thailand; however, its genetic characterization, origin, and diversity remain poorly understood. Here, we studied the socio-cultural, environmental, and genetic aspects of the Mae Hong Son chicken breed and investigated its diversity and allelic gene pool. We genotyped 28 microsatellite markers and analyzed mitochondrial D-loop sequencing data to evaluate genetic diversity and assessed spatial habitat suitability using maximum entropy modeling. Sequence diversity analysis revealed a total of 188 genotyped alleles, with overall nucleotide diversity of 0.014 ± 0.007, indicating that the Mae Hong Son chicken population is genetically highly diverse, with 35 (M1-M35) haplotypes clustered into haplogroups A, B, E, and F, mostly in the North ecotype. Allelic gene pool patterns showed a unique DNA fingerprint of the Mae Hong Son chicken, as compared to other breeds and red junglefowl. A genetic introgression of some parts of the gene pool of red junglefowl and other indigenous breeds was identified in the Mae Hong Son chicken, supporting the hypothesis of the origin of the Mae Hong Son chicken. During domestication in the past 200-300 years after the crossing of indigenous chickens and red junglefowl, the Mae Hong Son chicken has adapted to the highland environment and played a significant socio-cultural role in the Northern Thai community. The unique genetic fingerprint of the Mae Hong Son chicken, retaining a high level of genetic variability that includes a dynamic demographic and domestication history, as well as a range of ecological factors, might reshape the adaptation of this breed under selective pressure.

Selective footprints and genes relevant to cold adaptation and other phenotypic traits are unscrambled in the genomes of divergently selected chicken breeds

BACKGROUND

The genomes of worldwide poultry breeds divergently selected for performance and other phenotypic traits may also be affected by, and formed due to, past and current admixture events. Adaptation to diverse environments, including acclimation to harsh climatic conditions, has also left selection footprints in breed genomes.

RESULTS

Using the Chicken 50K_CobbCons SNP chip, we genotyped four divergently selected breeds: two aboriginal, cold tolerant Ushanka and Orloff Mille Fleur, one egg-type Russian White subjected to artificial selection for cold tolerance, and one meat-type White Cornish. Signals of selective sweeps were determined in the studied breeds using three methods: (1) assessment of runs of homozygosity islands, (2) F_ST based population differential analysis, and (3) haplotype differentiation analysis. Genomic regions of true selection signatures were identified by two or more methods or in two or more breeds. In these regions, we detected 540 prioritized candidate genes supplemented them with those that occurred in one breed using one statistic and were suggested in other studies. Amongst them, SOX5, ME3, ZNF536, WWP1, RIPK2, OSGIN2, DECR1, TPO, PPARGC1A, BDNF, MSTN, and beta-keratin genes can be especially mentioned as candidates for cold adaptation. Epigenetic factors may be involved in regulating some of these important genes (e.g., TPO and BDNF).

CONCLUSION

Based on a genome-wide scan, our findings can help dissect the genetic architecture underlying various phenotypic traits in chicken breeds. These include genes representing the sine qua non for adaptation to harsh environments. Cold tolerance in acclimated chicken breeds may be developed following one of few specific gene expression mechanisms or more than one overlapping response known in cold-exposed individuals, and this warrants further investigation.

Genome variation in tick infestation and cryptic divergence in Tunisian indigenous sheep

Background

Ticks are obligate haematophagous ectoparasites considered second to mosquitos as vectors and reservoirs of multiple pathogens of global concern. Individual variation in tick infestation has been reported in indigenous sheep, but its genetic control remains unknown.

Results

Here, we report 397 genome-wide signatures of selection overlapping 991 genes from the analysis, using ROH, LR-GWAS, XP-EHH, and F_ST, of 600 K SNP genotype data from 165 Tunisian sheep showing high and low levels of tick infestations and piroplasm infections. We consider 45 signatures that are detected by consensus results of at least two methods as high-confidence selection regions. These spanned 104 genes which included immune system function genes, solute carriers and chemokine receptor. One region spanned STX5, that has been associated with tick resistance in cattle, implicating it as a prime candidate in sheep. We also observed RAB6B and TF in a high confidence candidate region that has been associated with growth traits suggesting natural selection is enhancing growth and developmental stability under tick challenge. The analysis also revealed fine-scale genome structure indicative of cryptic divergence in Tunisian sheep.

Conclusions

Our findings provide a genomic reference that can enhance the understanding of the genetic architecture of tick resistance and cryptic divergence in indigenous African sheep.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08321-1.

Whole Exome-Sequencing of Pooled Genomic DNA Samples to Detect Quantitative Trait Loci in Esotropia and Exotropia of Strabismus in Japanese

BACKGROUND

Esotropia and exotropia are two major phenotypes of comitant strabismus. It remains controversial whether esotropia and exotropia would share common genetic backgrounds. In this study, we used a quantitative trait locus (QTL)-sequencing pipeline for diploid plants to screen for susceptibility loci of strabismus in whole exome sequencing of pooled genomic DNAs of individuals.

METHODS

Pooled genomic DNA (2.5 ng each) of 20 individuals in three groups, Japanese patients with esotropia and exotropia, and normal members in the families, was sequenced twice after exome capture, and the first and second sets of data in each group were combined to increase the read depth. The SNP index, as the ratio of variant genotype reads to all reads, and Δ(SNP index) values, as the difference of SNP index between two groups, were calculated by sliding window analysis with a 4 Mb window size and 10 kb slide size. The rows of 200 "N"s were inserted as a putative 200-b spacer between every adjoining locus to depict Δ(SNP index) plots on each chromosome. SNP positions with depth < 20 as well as SNP positions with SNP index of <0.3 were excluded.

RESULTS

After the exclusion of SNPs, 12,242 SNPs in esotropia/normal group and 12,108 SNPs in exotropia/normal group remained. The patterns of the Δ(SNP index) plots on each chromosome appeared different between esotropia/normal group and exotropia/normal group. When the consecutive groups of SNPs on each chromosome were set at three patterns: SNPs in each cytogenetic band, 50 consecutive sliding SNPs, and SNPs in 4 Mb window size with 10 kb slide size, p values (Wilcoxon signed rank test) and Q values (false discovery rate) in a few loci as Manhattan plots showed significant differences in comparison between the Δ(SNP index) in the esotropia/normal group and exotropia/normal group.

CONCLUSIONS

The pooled DNA sequencing and QTL mapping approach for plants could provide overview of genetic background on each chromosome and would suggest different genetic backgrounds for two major phenotypes of comitant strabismus, esotropia and exotropia.

Unveiling Comparative Genomic Trajectories of Selection and Key Candidate Genes in Egg-Type Russian White and Meat-Type White Cornish Chickens

Comparison of genomic footprints in chicken breeds with different selection history is a powerful tool in elucidating genomic regions that have been targeted by recent and more ancient selection. In the present work, we aimed at examining and comparing the trajectories of artificial selection in the genomes of the native egg-type Russian White (RW) and meat-type White Cornish (WC) breeds. Combining three different statistics (top 0.1% SNP by F_ST value at pairwise breed comparison, hapFLK analysis, and identification of ROH island shared by more than 50% of individuals), we detected 45 genomic regions under putative selection including 11 selective sweep regions, which were detected by at least two different methods. Four of such regions were breed-specific for each of RW breed (on GGA1, GGA5, GGA8, and GGA9) and WC breed (on GGA1, GGA5, GGA8, and GGA28), while three remaining regions on GGA2 (two sweeps) and GGA3 were common for both breeds. Most of identified genomic regions overlapped with known QTLs and/or candidate genes including those for body temperatures, egg productivity, and feed intake in RW chickens and those for growth, meat and carcass traits, and feed efficiency in WC chickens. These findings were concordant with the breed origin and history of their artificial selection. We determined a set of 188 prioritized candidate genes retrieved from the 11 overlapped regions of putative selection and reviewed their functions relative to phenotypic traits of interest in the two breeds. One of the RW-specific sweep regions harbored the known domestication gene, TSHR. Gene ontology and functional annotation analysis provided additional insight into a functional coherence of genes in the sweep regions. We also showed a greater candidate gene richness on microchromosomes relative to macrochromosomes in these genomic areas. Our results on the selection history of RW and WC chickens and their key candidate genes under selection serve as a profound information for further conservation of their genomic diversity and efficient breeding.

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.

Comparison of anadromous and landlocked Atlantic salmon genomes reveals signatures of parallel and relaxed selection across the Northern Hemisphere

Most Atlantic salmon (Salmo salar L.) populations follow an anadromous life cycle, spending early life in freshwater, migrating to the sea for feeding, and returning to rivers to spawn. At the end of the last ice age ~10,000 years ago, several populations of Atlantic salmon became landlocked. Comparing their genomes to their anadromous counterparts can help identify genetic variation related to either freshwater residency or anadromy. The objective of this study was to identify consistently divergent loci between anadromous and landlocked Atlantic salmon strains throughout their geographical distribution, with the long-term aim of identifying traits relevant for salmon aquaculture, including fresh and seawater growth, omega-3 metabolism, smoltification, and disease resistance. We used a Pool-seq approach (n = 10-40 individuals per population) to sequence the genomes of twelve anadromous and six landlocked Atlantic salmon populations covering a large part of the Northern Hemisphere and conducted a genomewide association study to identify genomic regions having been under different selection pressure in landlocked and anadromous strains. A total of 28 genomic regions were identified and included cadm1 on Chr 13 and ppargc1a on Chr 18. Seven of the regions additionally displayed consistently reduced heterozygosity in fish obtained from landlocked populations, including the genes gpr132, cdca4, and sertad2 on Chr 15. We also found 16 regions, including igf1 on Chr 17, which consistently display reduced heterozygosity in the anadromous populations compared to the freshwater populations, indicating relaxed selection on traits associated with anadromy in landlocked salmon. In conclusion, we have identified 37 regions which may harbor genetic variation relevant for improving fish welfare and quality in the salmon farming industry and for understanding life-history traits in fish.

Genomic Signatures After Five Generations of Intensive Selective Breeding: Runs of Homozygosity and Genetic Diversity in Representative Domestic and Wild Populations of Turbot (Scophthalmus maximus)

Massive genotyping of single nucleotide polymorphisms (SNP) has opened opportunities for analyzing the way in which selection shapes genomes. Artificial or natural selection usually leaves genomic signatures associated with selective sweeps around the responsible locus. Strong selective sweeps are most often identified either by lower genetic diversity than the genomic average and/or islands of runs of homozygosity (ROHi). Here, we conducted an analysis of selective sweeps in turbot (Scophthalmus maximus) using two SNP datasets from a Northeastern Atlantic population (36 individuals) and a domestic broodstock (46 individuals). Twenty-six families (∼ 40 offspring per family) from this broodstock and three SNP datasets applying differing filtering criteria were used to adjust ROH calling parameters. The best-fitted genomic inbreeding estimate (F_ROH) was obtained by the sum of ROH longer than 1 Mb, called using a 21,615 SNP panel, a sliding window of 37 SNPs and one heterozygous SNP per window allowed. These parameters were used to obtain the ROHi distribution in the domestic and wild populations (49 and 0 ROHi, respectively). Regions with higher and lower genetic diversity within each population were obtained using sliding windows of 37 SNPs. Furthermore, those regions were mapped in the turbot genome against previously reported genetic markers associated with QTL (Quantitative Trait Loci) and outlier loci for domestic or natural selection to identify putative selective sweeps. Out of the 319 and 278 windows surpassing the suggestive pooled heterozygosity thresholds (ZHp) in the wild and domestic population, respectively, 78 and 54 were retained under more restrictive ZHp criteria. A total of 116 suggestive windows (representing 19 genomic regions) were linked to either QTL for production traits, or outliers for divergent or balancing selection. Twenty-four of them (representing 3 genomic regions) were retained under stricter ZHp thresholds. Eleven QTL/outlier markers were exclusively found in suggestive regions of the domestic broodstock, 7 in the wild population and one in both populations; one (broodstock) and two (wild) of those were found in significant regions retained under more restrictive ZHp criteria in the broodstock and the wild population, respectively. Genome mining and functional enrichment within regions associated with selective sweeps disclosed relevant genes and pathways related to aquaculture target traits, including growth and immune-related pathways, metabolism and response to hypoxia, which showcases how this genome atlas of genetic diversity can be a valuable resource to look for candidate genes related to natural or artificial selection in turbot populations.

Discovery of genomic variations by whole-genome resequencing of the North American Araucana chicken

Gallus gallus (chicken) is phenotypically diverse, with over 60 recognized breeds, among the myriad species within the Aves lineage. Domestic chickens have been under artificial selection by humans for thousands of years for agricultural purposes. The North American Araucana (NAA) breed arose as a cross between the Chilean “Collonocas” that laid blue eggs and was rumpless and the “Quetros” that had unusual tufts but with tail. NAAs were introduced from South America in the 1940s and have been kept as show birds by enthusiasts since then due to several distinctive traits: laying eggs with blue eggshells, characteristic ear-tufts, a pea comb, and rumplessness. The population has maintained variants for clean-faced and tufted, as well as tailed and rumplessness traits making it advantageous for genetic studies. Genome resequencing of six NAA chickens with a mixture of these traits was done to 71-fold coverage using Illumina HiSeq 2000 paired-end reads. Trimmed and concordant reads were mapped to the Gallus_gallus-5.0 reference genome (galGal5), generated from a female Red Junglefowl (UCD001). To identify candidate genes that are associated with traits of the NAA, their genome was compared with the Korean Araucana, Korean Domestic and White Leghorn breeds. Genomic regions with significantly reduced levels of heterogeneity were detected on five different chromosomes in NAA. The sequence data generated confirm the identity of variants responsible for the blue eggshells, pea comb, and rumplessness traits of NAA and propose one for ear-tufts.

Comprehensive genome and transcriptome analyses reveal genetic relationship, selection signature, and transcriptome landscape of small-sized Korean native Jeju horse

The Jeju horse, indigenous to the Jeju Island in Korea may have originated from Mongolian horses. Adaptations to the local harsh environment have conferred Jeju horse with unique traits such as small-sized body, stocky head, and shorter limbs. These characteristics have not been studied previously at the genomic level. Therefore, we sequenced and compared the genome of 41 horses belonging to 6 breeds. We identified numerous breed-specific non-synonymous SNPs and loss-of-function mutants. Demographic and admixture analyses showed that, though Jeju horse is genetically the closest to the Mongolian breeds, its genetic ancestry is independent of that of the Mongolian breeds. Genome wide selection signature analysis revealed that genes such as LCORL, MSTN, HMGA2, ZFAT, LASP1, PDK4, and ACTN2, were positively selected in the Jeju horse. RNAseq analysis showed that several of these genes were also differentially expressed in Jeju horse compared to Thoroughbred horse. Comparative muscle fiber analysis showed that, the type I muscle fibre content was substantially higher in Jeju horse compared to Thoroughbred horse. Our results provide insights about the selection of complex phenotypic traits in the small-sized Jeju horse and the novel SNPs identified will aid in designing high-density SNP chip for studying other native horse breeds.

Integrative Genomics Reveals the Genetics and Evolution of the Honey Bee's Social Immune System

Social organisms combat pathogens through individual innate immune responses or through social immunity—behaviors among individuals that limit pathogen transmission within groups. Although we have a relatively detailed understanding of the genetics and evolution of the innate immune system of animals, we know little about social immunity. Addressing this knowledge gap is crucial for understanding how life-history traits influence immunity, and identifying if trade-offs exist between innate and social immunity. Hygienic behavior in the Western honey bee, Apis mellifera, provides an excellent model for investigating the genetics and evolution of social immunity in animals. This heritable, colony-level behavior is performed by nurse bees when they detect and remove infected or dead brood from the colony. We sequenced 125 haploid genomes from two artificially selected highly hygienic populations and a baseline unselected population. Genomic contrasts allowed us to identify a minimum of 73 genes tentatively associated with hygienic behavior. Many genes were within previously discovered QTLs associated with hygienic behavior and were predictive of hygienic behavior within the unselected population. These genes were often involved in neuronal development and sensory perception in solitary insects. We found that genes associated with hygienic behavior have evidence of positive selection within honey bees (Apis), supporting the hypothesis that social immunity contributes to fitness. Our results indicate that genes influencing developmental neurobiology and behavior in solitary insects may have been co-opted to give rise to a novel and adaptive social immune phenotype in honey bees.

Red fox genome assembly identifies genomic regions associated with tame and aggressive behaviours

Strains of red fox (Vulpes vulpes) with markedly different behavioural phenotypes have been developed in the famous long-term selective breeding programme known as the Russian farm-fox experiment. Here we sequenced and assembled the red fox genome and re-sequenced a subset of foxes from the tame, aggressive and conventional farm-bred populations to identify genomic regions associated with the response to selection for behaviour. Analysis of the re-sequenced genomes identified 103 regions with either significantly decreased heterozygosity in one of the three populations or increased divergence between the populations. A strong positional candidate gene for tame behaviour was highlighted: SorCS1, which encodes the main trafficking protein for AMPA glutamate receptors and neurexins and suggests a role for synaptic plasticity in fox domestication. Other regions identified as likely to have been under selection in foxes include genes implicated in human neurological disorders, mouse behaviour and dog domestication. The fox represents a powerful model for the genetic analysis of affiliative and aggressive behaviours that can benefit genetic studies of behaviour in dogs and other mammals, including humans.

A genome-wide scan for signatures of selection in Azeri and Khuzestani buffalo breeds

Background

Identification of genomic regions that have been targets of selection may shed light on the genetic history of livestock populations and help to identify variation controlling commercially important phenotypes. The Azeri and Kuzestani buffalos are the most common indigenous Iranian breeds which have been subjected to divergent selection and are well adapted to completely different regions. Examining the genetic structure of these populations may identify genomic regions associated with adaptation to the different environments and production goals.

Results

A set of 385 water buffalo samples from Azeri (N = 262) and Khuzestani (N = 123) breeds were genotyped using the Axiom® Buffalo Genotyping 90 K Array. The unbiased fixation index method (F_ST) was used to detect signatures of selection. In total, 13 regions with outlier F_ST values (0.1%) were identified. Annotation of these regions using the UMD3.1 Bos taurus Genome Assembly was performed to find putative candidate genes and QTLs within the selected regions. Putative candidate genes identified include FBXO9, NDFIP1, ACTR3, ARHGAP26, SERPINF2, BOLA-DRB3, BOLA-DQB, CLN8, and MYOM2.

Conclusions

Candidate genes identified in regions potentially under selection were associated with physiological pathways including milk production, cytoskeleton organization, growth, metabolic function, apoptosis and domestication-related changes include immune and nervous system development. The QTL identified are involved in economically important traits in buffalo related to milk composition, udder structure, somatic cell count, meat quality, and carcass and body weight.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4759-x) contains supplementary material, which is available to authorized users.

Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines

Background

Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection.

Results

A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development.

Conclusions

In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common genetic variants from a Brazilian broiler and a white egg layer line that can be used for genomic studies involving association analysis with phenotypes of economic interest to the poultry industry.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4444-0) contains supplementary material, which is available to authorized users.

Efficiency of different strategies to mitigate ascertainment bias when using SNP panels in diversity studies

Background

Single nucleotide polymorphism (SNP) panels have been widely used to study genomic variations within and between populations. Methods of SNP discovery have been a matter of debate for their potential of introducing ascertainment bias, and genetic diversity results obtained from the SNP genotype data can be misleading. We used a total of 42 chicken populations where both individual genotyped array data and pool whole genome resequencing (WGS) data were available. We compared allele frequency distributions and genetic diversity measures (expected heterozygosity (H_e), fixation index (F_ST) values, genetic distances and principal components analysis (PCA)) between the two data types. With the array data, we applied different filtering options (SNPs polymorphic in samples of two Gallus gallus wild populations, linkage disequilibrium (LD) based pruning and minor allele frequency (MAF) filtering, and combinations thereof) to assess their potential to mitigate the ascertainment bias.

Results

Rare SNPs were underrepresented in the array data. Array data consistently overestimated H_e compared to WGS data, however, with a similar ranking of the breeds, as demonstrated by Spearman’s rank correlations ranging between 0.956 and 0.985. LD based pruning resulted in a reduced overestimation of H_e compared to the other filters and slightly improved the relationship with the WGS results. The raw array data and those with polymorphic SNPs in the wild samples underestimated pairwise F_ST values between breeds which had low F_ST (<0.15) in the WGS, and overestimated this parameter for high WGS F_ST (>0.15). LD based pruned data underestimated F_ST in a consistent manner. The genetic distance matrix from LD pruned data was more closely related to that of WGS than the other array versions. PCA was rather robust in all array versions, since the population structure on the PCA plot was generally well captured in comparison to the WGS data.

Conclusions

Among the tested filtering strategies, LD based pruning was found to account for the effects of ascertainment bias in the relatively best way, producing results which are most comparable to those obtained from WGS data and therefore is recommended for practical use.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12864-017-4416-9) contains supplementary material, which is available to authorized users.

Genomic Comparison of Indigenous African and Northern European Chickens Reveals Putative Mechanisms of Stress Tolerance Related to Environmental Selection Pressure

Global climate change is increasing the magnitude of environmental stressors, such as temperature, pathogens, and drought, that limit the survivability and sustainability of livestock production. Poultry production and its expansion is dependent upon robust animals that are able to cope with stressors in multiple environments. Understanding the genetic strategies that indigenous, noncommercial breeds have evolved to survive in their environment could help to elucidate molecular mechanisms underlying biological traits of environmental adaptation. We examined poultry from diverse breeds and climates of Africa and Northern Europe for selection signatures that have allowed them to adapt to their indigenous environments. Selection signatures were studied using a combination of population genomic methods that employed FST , integrated haplotype score (iHS), and runs of homozygosity (ROH) procedures. All the analyses indicated differences in environment as a driver of selective pressure in both groups of populations. The analyses revealed unique differences in the genomic regions under selection pressure from the environment for each population. The African chickens showed stronger selection toward stress signaling and angiogenesis, while the Northern European chickens showed more selection pressure toward processes related to energy homeostasis. The results suggest that chromosomes 2 and 27 are the most diverged between populations and the most selected upon within the African (chromosome 27) and Northern European (chromosome 2) birds. Examination of the divergent populations has provided new insight into genes under possible selection related to tolerance of a population's indigenous environment that may be baselines for examining the genomic contribution to tolerance adaptions.

Use of high-density SNP data to identify patterns of diversity and signatures of selection in broiler chickens

The development of broiler chickens over the last 70 years has been accompanied by large phenotypic changes, so that the resulting genomic signatures of selection should be detectable by current statistical techniques with sufficiently dense genetic markers. Using two approaches, this study analysed high-density SNP data from a broiler chicken line to detect low-diversity genomic regions characteristic of past selection. Seven regions with zero diversity were identified across the genome. Most of these were very small and did not contain many genes. In addition, fifteen regions were identified with diversity increasing asymptotically from a low level. These regions were larger and thus generally included more genes. Several candidate genes for broiler traits were found within these 'regression regions', including IGF1, GPD2 and MTNR1AI. The results suggest that the identification of zero-diversity regions is too restrictive for characterizing regions under selection, but that regions showing patterns of diversity along the chromosome that are consistent with selective sweeps contain a number of genes that are functional candidates for involvement in broiler development. Many regions identified in this study overlap or are close to regions identified in layer chicken populations, possibly due to their shared precommercialization history or to shared selection pressures between broilers and layers.

Beyond the MHC: A canine model of dermatomyositis shows a complex pattern of genetic risk involving novel loci

Juvenile dermatomyositis (JDM) is a chronic inflammatory myopathy and vasculopathy driven by genetic and environmental influences. Here, we investigated the genetic underpinnings of an analogous, spontaneous disease of dogs also termed dermatomyositis (DMS). As in JDM, we observed a significant association with a haplotype of the major histocompatibility complex (MHC) (DLA-DRB1*002:01/-DQA1*009:01/-DQB1*001:01), particularly in homozygosity (P-val = 0.0001). However, the high incidence of the haplotype among healthy dogs indicated that additional genetic risk factors are likely involved in disease progression. We conducted genome-wide association studies in two modern breeds having common ancestry and detected strong associations with novel loci on canine chromosomes 10 (P-val = 2.3X10-12) and 31 (P-val = 3.95X10-8). Through whole genome resequencing, we identified primary candidate polymorphisms in conserved regions of PAN2 (encoding p.Arg492Cys) and MAP3K7CL (c.383_392ACTCCACAAA>GACT) on chromosomes 10 and 31, respectively. Analyses of these polymorphisms and the MHC haplotypes revealed that nine of 27 genotypic combinations confer high or moderate probability of disease and explain 93% of cases studied. The pattern of disease risk across PAN2 and MAP3K7CL genotypes provided clear evidence for a significant epistatic foundation for this disease, a risk further impacted by MHC haplotypes. We also observed a genotype-phenotype correlation wherein an earlier age of onset is correlated with an increased number of risk alleles at PAN2 and MAP3K7CL. High frequencies of multiple genetic risk factors are unique to affected breeds and likely arose coincident with artificial selection for desirable phenotypes. Described herein is the first three-locus association with a complex canine disease and two novel loci that provide targets for exploration in JDM and related immunological dysfunction.

A genome scan for selection signatures comparing farmed Atlantic salmon with two wild populations: Testing colocalization among outlier markers, candidate genes, and quantitative trait loci for production traits

Comparative genome scans can be used to identify chromosome regions, but not traits, that are putatively under selection. Identification of targeted traits may be more likely in recently domesticated populations under strong artificial selection for increased production. We used a North American Atlantic salmon 6K SNP dataset to locate genome regions of an aquaculture strain (Saint John River) that were highly diverged from that of its putative wild founder population (Tobique River). First, admixed individuals with partial European ancestry were detected using STRUCTURE and removed from the dataset. Outlier loci were then identified as those showing extreme differentiation between the aquaculture population and the founder population. All Arlequin methods identified an overlapping subset of 17 outlier loci, three of which were also identified by BayeScan. Many outlier loci were near candidate genes and some were near published quantitative trait loci (QTLs) for growth, appetite, maturity, or disease resistance. Parallel comparisons using a wild, nonfounder population (Stewiacke River) yielded only one overlapping outlier locus as well as a known maturity QTL. We conclude that genome scans comparing a recently domesticated strain with its wild founder population can facilitate identification of candidate genes for traits known to have been under strong artificial selection.

Detection of genomic signatures of recent selection in commercial broiler chickens

Background

Identification of the genomic signatures of recent selection may help uncover causal polymorphisms controlling traits relevant to recent decades of selective breeding in livestock. In this study, we aimed at detecting signatures of recent selection in commercial broiler chickens using genotype information from single nucleotide polymorphisms (SNPs). A total of 565 chickens from five commercial purebred lines, including three broiler sire (male) lines and two broiler dam (female) lines, were genotyped using the 60K SNP Illumina iSelect chicken array. To detect genomic signatures of recent selection, we applied two methods based on population comparison, cross-population extended haplotype homozygosity (XP-EHH) and cross-population composite likelihood ratio (XP-CLR), and further analyzed the results to find genomic regions under recent selection in multiple purebred lines.

Results

A total of 321 candidate selection regions spanning approximately 1.45 % of the chicken genome in each line were detected by consensus of results of both XP-EHH and XP-CLR methods. To minimize false discovery due to genetic drift, only 42 of the candidate selection regions that were shared by 2 or more purebred lines were considered as high-confidence selection regions in the study. Of these 42 regions, 20 were 50 kb or less while 4 regions were larger than 0.5 Mb. In total, 91 genes could be found in the 42 regions, among which 19 regions contained only 1 or 2 genes, and 9 regions were located at gene deserts.

Conclusions

Our results provide a genome-wide scan of recent selection signatures in five purebred lines of commercial broiler chickens. We found several candidate genes for recent selection in multiple lines, such as SOX6 (Sex Determining Region Y-Box 6) and cTR (Thyroid hormone receptor beta). These genes may have been under recent selection due to their essential roles in growth, development and reproduction in chickens. Furthermore, our results suggest that in some candidate regions, the same or opposite alleles have been under recent selection in multiple lines. Most of the candidate genes in the selection regions are novel, and as such they should be of great interest for future research into the genetic architecture of traits relevant to modern broiler breeding.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-016-0430-1) contains supplementary material, which is available to authorized users.

Whole-genome resequencing of Xishuangbanna fighting chicken to identify signatures of selection

BACKGROUND

Selective breeding for genetic improvement is expected to leave distinctive selection signatures within genomes. The identification of selection signatures can help to elucidate the mechanisms of selection and accelerate genetic improvement. Fighting chickens have undergone extensive artificial selection, resulting in modifications to their morphology, physiology and behavior compared to wild species. Comparing the genomes of fighting chickens and wild species offers a unique opportunity for identifying signatures of artificial selection.

RESULTS

We identified selection signals in 100-kb windows sliding in 10-kb steps by using two approaches: the pooled heterozygosity [Formula: see text] and the fixation index [Formula: see text] between Xishuangbanna fighting chicken (YNLC) and Red Jungle Fowl. A total of 413 candidate genes were found to be putatively under selection in YNLC. These genes were related to traits such as growth, disease resistance, aggressive behavior and energy metabolism, as well as the morphogenesis and homeostasis of many tissues and organs.

CONCLUSIONS

This study reveals mechanisms and targets of artificial selection, which will contribute to improve our knowledge about the evolution of fighting chickens and facilitate future quantitative trait loci mapping.

Locus-specific ancestry to detect recent response to selection in admixed Swiss Fleckvieh cattle

Identification of selection signatures is one of the current endeavors of evolutionary genetics. Admixed populations may be used to infer post-admixture selection. We calculated local ancestry for Swiss Fleckvieh, a composite of Simmental (SI) and Red Holstein Friesian (RHF), to infer such signals. Illumina Bovine SNP50 BeadChip data for 300 admixed, 88 SI and 97 RHF bulls were used. The average RHF ancestry across the whole genome was 0.70. To identify regions with high deviation from average, we considered two significance thresholds, based on a permutation test and extreme deviation from normal distribution. Regions on chromosomes 13 (46.3-47.3 Mb) and 18 (18.7-25.9 Mb) passed both thresholds in the direction of increased SI. Extended haplotype homozygosity within (iHS) and between (Rsb) populations was calculated to explore additional patterns of pre- and post-admixture selection signals. The Rsb score of admixed and SI was significant in a wide region of chromosome 18 (6.6-24.6 Mb) overlapped with one area of strong local ancestry deviation. FTO, with pleiotropic effect on milk and fertility, NOD2 on dairy and NKD1 and SALL1 on fertility traits are located there. Genetic differentiation of RHF and SI (F_st ), an alternative indicator of pre-admixture selection in pure populations, was calculated. No considerable overlap of peaks of local ancestry deviations and F_st was observed. We found two regions with significant signatures of post-admixture selection in this very young composite, applying comparatively stringent significance thresholds. The signals cover relatively large genomic areas and did not allow pinpointing of the gene(s) responsible for the apparent shift in ancestry proportions.

Breeding signature of combining ability improvement revealed by a genomic variation map from recurrent selection population in Brassica napus

Combining ability is crucial for parent selection in crop hybrid breeding. The present investigation and results had revealed the underlying genetic factors which might contribute in adequate combining ability, further assisting in enhancing heterosis and stability. Here, we conducted a large-scale analysis of genomic variation in order to define genomic regions affecting the combining ability in recurrent selection population of rapeseed. A population of 175 individuals was genotyped with the Brassica60K SNP chip. 525 hybrids were assembled with three different testers and used to evaluate the general combining ability (GCA) in three environments. By detecting the changes of the genomic variation, we identified 376 potential genome regions, spanning 3.03% of rapeseed genome which provided QTL-level resolution on potentially selected variants. More than 96% of these regions were located in the C subgenome, indicating that C subgenome had sustained stronger selection pressure in the breeding program than the A subgenome. In addition, a high level of linkage disequilibrium in rapeseed genome was detected, suggesting that marker-assisted selection for the population improvement might be easily implemented. This study outlines the evidence for high GCA on a genomic level and provided underlying molecular mechanism for recurrent selection improvement in B. napus.

Genomic analysis of Ugandan and Rwandan chicken ecotypes using a 600 k genotyping array

Background

Indigenous populations of animals have developed unique adaptations to their local environments, which may include factors such as response to thermal stress, drought, pathogens and suboptimal nutrition. The survival and subsequent evolution within these local environments can be the result of both natural and artificial selection driving the acquisition of favorable traits, which over time leave genomic signatures in a population. This study’s goals are to characterize genomic diversity and identify selection signatures in chickens from equatorial Africa to identify genomic regions that may confer adaptive advantages of these ecotypes to their environments.

Results

Indigenous chickens from Uganda (n = 72) and Rwanda (n = 100), plus Kuroilers (n = 24, an Indian breed imported to Africa), were genotyped using the Axiom® 600 k Chicken Genotyping Array. Indigenous ecotypes were defined based upon location of sampling within Africa. The results revealed the presence of admixture among the Ugandan, Rwandan, and Kuroiler populations. Genes within runs of homozygosity consensus regions are linked to gene ontology (GO) terms related to lipid metabolism, immune functions and stress-mediated responses (FDR < 0.15). The genes within regions of signatures of selection are enriched for GO terms related to health and oxidative stress processes. Key genes in these regions had anti-oxidant, apoptosis, and inflammation functions.

Conclusions

The study suggests that these populations have alleles under selective pressure from their environment, which may aid in adaptation to harsh environments. The correspondence in gene ontology terms connected to stress-mediated processes across the populations could be related to the similarity of environments or an artifact of the detected admixture.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2711-5) contains supplementary material, which is available to authorized users.

Parallel Selection Revealed by Population Sequencing in Chicken

Human-driven selection during domestication and subsequent breed formation has likely left detectable signatures within the genome of modern chicken. The elucidation of these signatures of selection is of interest from the perspective of evolutionary biology, and for identifying genes relevant to domestication and improvement that ultimately may help to further genetically improve this economically important animal. We used whole genome sequence data from 50 hens of commercial white (WL) and brown (BL) egg-laying chicken along with pool sequences of three meat-type chicken to perform a systematic screening of past selection in modern chicken. Evidence of positive selection was investigated in two steps. First, we explored evidence of parallel fixation in regions with overlapping elevated allele frequencies in replicated populations of layers and broilers, suggestive of selection during domestication or preimprovement ages. We confirmed parallel fixation in BCDO2 and TSHR genes and found four candidates including AGTR2, a gene heavily involved in “Ascites” in commercial birds. Next, we explored differentiated loci between layers and broilers suggestive of selection during improvement in chicken. This analysis revealed evidence of parallel differentiation in genes relevant to appearance and production traits exemplified with the candidate gene OPG, implicated in Osteoporosis, a disorder related to overconsumption of calcium in egg-laying hens. Our results illustrate the potential for population genetic techniques to identify genomic regions relevant to the phenotypes of importance to breeders.

Comparison among three variant callers and assessment of the accuracy of imputation from SNP array data to whole-genome sequence level in chicken

BACKGROUND

The technical progress in the last decade has made it possible to sequence millions of DNA reads in a relatively short time frame. Several variant callers based on different algorithms have emerged and have made it possible to extract single nucleotide polymorphisms (SNPs) out of the whole-genome sequence. Often, only a few individuals of a population are sequenced completely and imputation is used to obtain genotypes for all sequence-based SNP loci for other individuals, which have been genotyped for a subset of SNPs using a genotyping array.

METHODS

First, we compared the sets of variants detected with different variant callers, namely GATK, freebayes and SAMtools, and checked the quality of genotypes of the called variants in a set of 50 fully sequenced white and brown layers. Second, we assessed the imputation accuracy (measured as the correlation between imputed and true genotype per SNP and per individual, and genotype conflict between father-progeny pairs) when imputing from high density SNP array data to whole-genome sequence using data from around 1000 individuals from six different generations. Three different imputation programs (Minimac, FImpute and IMPUTE2) were checked in different validation scenarios.

RESULTS

There were 1,741,573 SNPs detected by all three callers on the studied chromosomes 3, 6, and 28, which was 71.6 % (81.6 %, 88.0 %) of SNPs detected by GATK (SAMtools, freebayes) in total. Genotype concordance (GC) defined as the proportion of individuals whose array-derived genotypes are the same as the sequence-derived genotypes over all non-missing SNPs on the array were 0.98 (GATK), 0.97 (freebayes) and 0.98 (SAMtools). Furthermore, the percentage of variants that had high values (>0.9) for another three measures (non-reference sensitivity, non-reference genotype concordance and precision) were 90 (88, 75) for GATK (SAMtools, freebayes). With all imputation programs, correlation between original and imputed genotypes was >0.95 on average with randomly masked 1000 SNPs from the SNP array and >0.85 for a leave-one-out cross-validation within sequenced individuals.

CONCLUSIONS

Performance of all variant callers studied was very good in general, particularly for GATK and SAMtools. FImpute performed slightly worse than Minimac and IMPUTE2 in terms of genotype correlation, especially for SNPs with low minor allele frequency, while it had lowest numbers in Mendelian conflicts in available father-progeny pairs. Correlations of real and imputed genotypes remained constantly high even if individuals to be imputed were several generations away from the sequenced individuals.

Association mapping by pooled sequencing identifies TOLL 11 as a protective factor against Plasmodium falciparum in Anopheles gambiae

Background

The genome-wide association study (GWAS) techniques that have been used for genetic mapping in other organisms have not been successfully applied to mosquitoes, which have genetic characteristics of high nucleotide diversity, low linkage disequilibrium, and complex population stratification that render population-based GWAS essentially unfeasible at realistic sample size and marker density.

Methods

We designed a novel mapping strategy for the mosquito system that combines the power of linkage mapping with the resolution afforded by genetic association. We established founder colonies from West Africa, controlled for diversity, linkage disequilibrium and population stratification. Colonies were challenged by feeding on the infectious stage of the human malaria parasite, Plasmodium falciparum, mosquitoes were phenotyped for parasite load, and DNA pools for phenotypically similar mosquitoes were Illumina sequenced. Phenotype-genotype mapping was carried out in two stages, coarse and fine.

Results

In the first mapping stage, pooled sequences were analysed genome-wide for intervals displaying relativereduction in diversity between phenotype pools, and candidate genomic loci were identified for influence upon parasite infection levels. In the second mapping stage, focused genotyping of SNPs from the first mapping stage was carried out in unpooled individual mosquitoes and replicates. The second stage confirmed significant SNPs in a locus encoding two Toll-family proteins. RNAi-mediated gene silencing and infection challenge revealed that TOLL 11 protects mosquitoes against P. falciparum infection.

Conclusions

We present an efficient and cost-effective method for genetic mapping using natural variation segregating in defined recent Anopheles founder colonies, and demonstrate its applicability for mapping in a complex non-model genome. This approach is a practical and preferred alternative to population-based GWAS for first-pass mapping of phenotypes in Anopheles. This design should facilitate mapping of other traits involved in physiology, epidemiology, and behaviour.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2009-z) contains supplementary material, which is available to authorized users.

Detecting recent selective sweeps while controlling for mutation rate and background selection

A composite likelihood ratio test implemented in the program sweepfinder is a commonly used method for scanning a genome for recent selective sweeps. sweepfinder uses information on the spatial pattern (along the chromosome) of the site frequency spectrum around the selected locus. To avoid confounding effects of background selection and variation in the mutation process along the genome, the method is typically applied only to sites that are variable within species. However, the power to detect and localize selective sweeps can be greatly improved if invariable sites are also included in the analysis. In the spirit of a Hudson–Kreitman–Aguadé test, we suggest adding fixed differences relative to an out‐group to account for variation in mutation rate, thereby facilitating more robust and powerful analyses. We also develop a method for including background selection, modelled as a local reduction in the effective population size. Using simulations, we show that these advances lead to a gain in power while maintaining robustness to mutation rate variation. Furthermore, the new method also provides more precise localization of the causative mutation than methods using the spatial pattern of segregating sites alone.

Genome Scan for Selection in Structured Layer Chicken Populations Exploiting Linkage Disequilibrium Information

An increasing interest is being placed in the detection of genes, or genomic regions, that have been targeted by selection because identifying signatures of selection can lead to a better understanding of genotype-phenotype relationships. A common strategy for the detection of selection signatures is to compare samples from distinct populations and to search for genomic regions with outstanding genetic differentiation. The aim of this study was to detect selective signatures in layer chicken populations using a recently proposed approach, hapFLK, which exploits linkage disequilibrium information while accounting appropriately for the hierarchical structure of populations. We performed the analysis on 70 individuals from three commercial layer breeds (White Leghorn, White Rock and Rhode Island Red), genotyped for approximately 1 million SNPs. We found a total of 41 and 107 regions with outstanding differentiation or similarity using hapFLK and its single SNP counterpart FLK respectively. Annotation of selection signature regions revealed various genes and QTL corresponding to productions traits, for which layer breeds were selected. A number of the detected genes were associated with growth and carcass traits, including IGF-1R, AGRP and STAT5B. We also annotated an interesting gene associated with the dark brown feather color mutational phenotype in chickens (SOX10). We compared FST, FLK and hapFLK and demonstrated that exploiting linkage disequilibrium information and accounting for hierarchical population structure decreased the false detection rate.

Functional classification of 15 million SNPs detected from diverse chicken populations

Next-generation sequencing has prompted a surge of discovery of millions of genetic variants from vertebrate genomes. Besides applications in genetic association and linkage studies, a fraction of these variants will have functional consequences. This study describes detection and characterization of 15 million SNPs from chicken genome with the goal to predict variants with potential functional implications (pfVars) from both coding and non-coding regions. The study reports: 183K amino acid-altering SNPs of which 48% predicted as evolutionary intolerant, 13K splicing variants, 51K likely to alter RNA secondary structures, 500K within most conserved elements and 3K from non-coding RNAs. Regions of local fixation within commercial broiler and layer lines were investigated as potential selective sweeps using genome-wide SNP data. Relationships with phenotypes, if any, of the pfVars were explored by overlaying the sweep regions with known QTLs. Based on this, the candidate genes and/or causal mutations for a number of important traits are discussed. Although the fixed variants within sweep regions were enriched with non-coding SNPs, some non-synonymous-intolerant mutations reached fixation, suggesting their possible adaptive advantage. The results presented in this study are expected to have important implications for future genomic research to identify candidate causal mutations and in poultry breeding.

Defining window-boundaries for genomic analyses using smoothing spline techniques

Background

High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, simplify computation, reduce sampling noise, and reduce the total number of tests performed. However, use of adjacent marker information can result in over- or under-smoothing, undesirable window boundary specifications, or highly correlated test statistics. We introduce a method for defining windows based on statistically guided breakpoints in the data, as a foundation for the analysis of multiple adjacent data points. This method involves first fitting a cubic smoothing spline to the data and then identifying the inflection points of the fitted spline, which serve as the boundaries of adjacent windows. This technique does not require prior knowledge of linkage disequilibrium, and therefore can be applied to data collected from individual or pooled sequencing experiments. Moreover, in contrast to existing methods, an arbitrary choice of window size is not necessary, since these are determined empirically and allowed to vary along the genome.

Results

Simulations applying this method were performed to identify selection signatures from pooled sequencing F_ST data, for which allele frequencies were estimated from a pool of individuals. The relative ratio of true to false positives was twice that generated by existing techniques. A comparison of the approach to a previous study that involved pooled sequencing F_ST data from maize suggested that outlying windows were more clearly separated from their neighbors than when using a standard sliding window approach.

Conclusions

We have developed a novel technique to identify window boundaries for subsequent analysis protocols. When applied to selection studies based on F_ST data, this method provides a high discovery rate and minimizes false positives. The method is implemented in the R package GenWin, which is publicly available from CRAN.

Applications in the search for genomic selection signatures in fish

Selection signatures are genomic regions harboring DNA sequences functionally involved in the genetic variation of traits subject to selection. Selection signatures have been intensively studied in recent years because of their relevance to evolutionary biology and their potential association with genes that control phenotypes of interest in wild and domestic populations. Selection signature research in fish has been confined to a smaller scale, due in part to the relatively recent domestication of fish species and limited genomic resources such as molecular markers, genetic mapping, DNA sequences, and reference genomes. However, recent genomic technology advances are paving the way for more studies that may contribute to the knowledge of genomic regions underlying phenotypes of biological and productive interest in fish.

Genomic signatures reveal new evidences for selection of important traits in domestic cattle

We investigated diverse genomic selections using high-density single nucleotide polymorphism data of five distinct cattle breeds. Based on allele frequency differences, we detected hundreds of candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, and N'Dama. In addition to well-known genes such as KIT, MC1R, ASIP, GHR, LCORL, NCAPG, WIF1, and ABCA12, we found evidence for a variety of novel and less-known genes under selection in cattle, such as LAP3, SAR1B, LRIG3, FGF5, and NUDCD3. Selective sweeps near LAP3 were then validated by next-generation sequencing. Genome-wide association analysis involving 26,362 Holsteins confirmed that LAP3 and SAR1B were related to milk production traits, suggesting that our candidate regions were likely functional. In addition, haplotype network analyses further revealed distinct selective pressures and evolution patterns across these five cattle breeds. Our results provided a glimpse into diverse genomic selection during cattle domestication, breed formation, and recent genetic improvement. These findings will facilitate genome-assisted breeding to improve animal production and health.

A genome-wide scan of selective sweeps and association mapping of fruit traits using microsatellite markers in watermelon

Our genetic diversity study uses microsatellites of known map position to estimate genome level population structure and linkage disequilibrium, and to identify genomic regions that have undergone selection during watermelon domestication and improvement. Thirty regions that showed evidence of selective sweep were scanned for the presence of candidate genes using the watermelon genome browser (www.icugi.org). We localized selective sweeps in intergenic regions, close to the promoters, and within the exons and introns of various genes. This study provided an evidence of convergent evolution for the presence of diverse ecotypes with special reference to American and European ecotypes. Our search for location of linked markers in the whole-genome draft sequence revealed that BVWS00358, a GA repeat microsatellite, is the GAGA type transcription factor located in the 5' untranslated regions of a structure and insertion element that expresses a Cys2His2 Zinc finger motif, with presumed biological processes related to chitin response and transcriptional regulation. In addition, BVWS01708, an ATT repeat microsatellite, located in the promoter of a DTW domain-containing protein (Cla002761); and 2 other simple sequence repeats that association mapping link to fruit length and rind thickness.

High-resolution genetic map for understanding the effect of genome-wide recombination rate on nucleotide diversity in watermelon

We used genotyping by sequencing to identify a set of 10,480 single nucleotide polymorphism (SNP) markers for constructing a high-resolution genetic map of 1096 cM for watermelon. We assessed the genome-wide variation in recombination rate (GWRR) across the map and found an association between GWRR and genome-wide nucleotide diversity. Collinearity between the map and the genome-wide reference sequence for watermelon was studied to identify inconsistency and chromosome rearrangements. We assessed genome-wide nucleotide diversity, linkage disequilibrium (LD), and selective sweep for wild, semi-wild, and domesticated accessions of Citrullus lanatus var. lanatus to track signals of domestication. Principal component analysis combined with chromosome-wide phylogenetic study based on 1563 SNPs obtained after LD pruning with minor allele frequency of 0.05 resolved the differences between semi-wild and wild accessions as well as relationships among worldwide sweet watermelon. Population structure analysis revealed predominant ancestries for wild, semi-wild, and domesticated watermelons as well as admixture of various ancestries that were important for domestication. Sliding window analysis of Tajima’s D across various chromosomes was used to resolve selective sweep. LD decay was estimated for various chromosomes. We identified a strong selective sweep on chromosome 3 consisting of important genes that might have had a role in sweet watermelon domestication.

Identification of selection footprints on the X chromosome in pig

Identifying footprints of selection can provide a straightforward insight into the mechanism of artificial selection and further dig out the causal genes related to important traits. In this study, three between-population and two within-population approaches, the Cross Population Extend Haplotype Homozygosity Test (XPEHH), the Cross Population Composite Likelihood Ratio (XPCLR), the F-statistics (Fst), the Integrated Haplotype Score (iHS) and the Tajima's D, were implemented to detect the selection footprints on the X chromosome in three pig breeds using Illumina Porcine60K SNP chip. In the detection of selection footprints using between-population methods, 11, 11 and 7 potential selection regions with length of 15.62 Mb, 12.32 Mb and 9.38 Mb were identified in Landrace, Chinese Songliao and Yorkshire by XPEHH, respectively, and 16, 13 and 17 potential selection regions with length of 15.20 Mb, 13.00 Mb and 19.21 Mb by XPCLR, 4, 2 and 4 potential selection regions with length of 3.20 Mb, 1.60 Mb and 3.20 Mb by Fst. For within-population methods, 7, 10 and 9 potential selection regions with length of 8.12 Mb, 8.40 Mb and 9.99 Mb were identified in Landrace, Chinese Songliao and Yorkshire by iHS, and 4, 3 and 2 potential selection regions with length of 3.20 Mb, 2.40 Mb and 1.60 Mb by Tajima's D. Moreover, the selection regions from different methods were partly overlapped, especially the regions around 22∼25 Mb were detected under selection in Landrace and Yorkshire while no selection in Chinese Songliao by all three between-population methods. Only quite few overlap of selection regions identified by between-population and within-population methods were found. Bioinformatics analysis showed that the genes relevant with meat quality, reproduction and immune were found in potential selection regions. In addition, three out of five significant SNPs associated with hematological traits reported in our genome-wide association study were harbored in potential selection regions.

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.

Genome-wide association study for egg production and quality in layer chickens

Discovery of genes with large effects on economically important traits has for many years been of interest to breeders. The development of SNP panels which cover the whole genome with high density and, more importantly, that can be genotyped on large numbers of individuals at relatively low cost, has opened new opportunities for genome-wide association studies (GWAS). The objective of this study was to find genomic regions associated with egg production and quality traits in layers using analysis methods developed for the purpose of whole genome prediction. Genotypes on over 4500 birds and phenotypes on over 13,000 hens from eight generations of a brown egg layer line were used. Birds were genotyped with a custom 42K Illumina SNP chip. Recorded traits included two egg production and 11 egg quality traits (puncture score, albumen height, yolk weight and shell colour) at early and late stages of production, as well as body weight and age at first egg. Egg weight was previously analysed by Wolc et al. (2012). The Bayesian whole genome prediction model--BayesB (Meuwissen et al. 2001) was used to locate 1 Mb regions that were most strongly associated with each trait. The posterior probability of a 1 Mb window contributing to genetic variation was used as the criterion for suggesting the presence of a quantitative trait locus (QTL) in that window. Depending upon the trait, from 1 to 7 significant (posterior probability >0.9) 1 Mb regions were found. The largest QTL, a region explaining 32% of genetic variance, was found on chr4 at 78 Mb for body weight but had pleiotropic effects on other traits. For the other traits, the largest effects were much smaller, explaining <7% of genetic variance, with regions on chromosomes 2, 12 and 17 explaining above 5% of genetic variance for albumen height, shell colour and egg production, respectively. In total, 45 of 1043 1 Mb windows were estimated to have a non-zero effect with posterior probability > 0.9 for one or more traits.

Population genomics of the honey bee reveals strong signatures of positive selection on worker traits

Most theories used to explain the evolution of eusociality rest upon two key assumptions: mutations affecting the phenotype of sterile workers evolve by positive selection if the resulting traits benefit fertile kin, and that worker traits provide the primary mechanism allowing social insects to adapt to their environment. Despite the common view that positive selection drives phenotypic evolution of workers, we know very little about the prevalence of positive selection acting on the genomes of eusocial insects. We mapped the footprints of positive selection in Apis mellifera through analysis of 40 individual genomes, allowing us to identify thousands of genes and regulatory sequences with signatures of adaptive evolution over multiple timescales. We found Apoidea- and Apis-specific genes to be enriched for signatures of positive selection, indicating that novel genes play a disproportionately large role in adaptive evolution of eusocial insects. Worker-biased proteins have higher signatures of adaptive evolution relative to queen-biased proteins, supporting the view that worker traits are key to adaptation. We also found genes regulating worker division of labor to be enriched for signs of positive selection. Finally, genes associated with worker behavior based on analysis of brain gene expression were highly enriched for adaptive protein and cis-regulatory evolution. Our study highlights the significant contribution of worker phenotypes to adaptive evolution in social insects, and provides a wealth of knowledge on the loci that influence fitness in honey bees.