Searching new signals for production traits through gene‐based association analysis in three Italian cattle breeds

Genome‐wide association studies (GWAS) have been widely applied to disentangle the genetic basis of complex traits. In cattle breeds, classical GWAS approaches with medium‐density marker panels are far from conclusive, especially for complex traits. This is due to the intrinsic limitations of GWAS and the assumptions that are made to step from the association signals to the functional variations. Here, we applied a gene‐based strategy to prioritize genotype–phenotype associations found for milk production and quality traits with classical approaches in three Italian dairy cattle breeds with different sample sizes (Italian Brown n = 745; Italian Holstein n = 2058; Italian Simmental n = 477). Although classical regression on single markers revealed only a single genome‐wide significant genotype–phenotype association, for Italian Holstein, the gene‐based approach identified specific genes in each breed that are associated with milk physiology and mammary gland development. As no standard method has yet been established to step from variation to functional units (i.e., genes), the strategy proposed here may contribute to revealing new genes that play significant roles in complex traits, such as those investigated here, amplifying low association signals using a gene‐centric approach.     

Genetic dissection of the gene coexpression network underlying photosynthesis in Populus

Photosynthesis is a key reaction that ultimately generates the carbohydrates needed to form woody tissues in trees. However, the genetic regulatory network of protein‐encoding genes (PEGs) and regulatory noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), underlying the photosynthetic pathway is unknown. Here, we integrated data from coexpression analysis, association studies (additive, dominance and epistasis), and expression quantitative trait nucleotide (eQTN) mapping to dissect the causal variants and genetic interaction network underlying photosynthesis in Populus. We initially used 30 PEGs, 6 miRNAs and 12 lncRNAs to construct a coexpression network based on the tissue‐specific gene expression profiles of 15 Populus samples. Then, we performed association studies using a natural population of 435 unrelated Populus tomentosa individuals, and identified 72 significant associations (P ≤ 0.001, q ≤ 0.05) with diverse additive and dominance patterns underlying photosynthesis‐related traits. Analysis of epistasis and eQTNs revealed that the complex genetic interactions in the coexpression network contribute to phenotypes at various levels. Finally, we demonstrated that heterologously expressing the most highly linked gene (PtoPsbX1) in this network significantly improved photosynthesis in Arabidopsis thaliana, pointing to the functional role of PtoPsbX1 in the photosynthetic pathway. This study provides an integrated strategy for dissecting a complex genetic interaction network, which should accelerate marker‐assisted breeding efforts to genetically improve woody plants.     

Sequence analysis of three canine adipokine genes revealed an association between TNF polymorphisms and obesity in Labrador dogs

Obesity is an emerging health problem in purebred dogs. Due to their crucial role in energy homeostasis control, genes encoding adipokines are considered candidate genes, and their variants may be associated with predisposition to obesity. Searching for polymorphism was carried out in three adipokine genes (TNF, RETN and IL6). The study was performed on 260 dogs, including lean (n = 109), overweight (n = 88) and obese (n = 63) dogs. The largest cohort was represented by Labrador Retrievers (n = 136). Altogether, 24 novel polymorphisms were identified: 12 in TNF (including one missense SNP), eight in RETN (including one missense SNP) and four in IL6. Distributions of five common SNPs (two in TNF, two in RETN and one in IL6) were further analyzed with regard to body condition score. Two SNPs in the non‐coding parts of TNF (c.‐40A>C and c.233+14G>A) were associated with obesity in Labrador dogs. The obtained results showed that the studied adipokine genes are highly polymorphic and two polymorphisms in the TNF gene may be considered as markers predisposing Labrador dogs to obesity.     

Next generation semiconductor based sequencing of bitter taste receptor genes in different pig populations and association analysis using a selective DNA pool‐seq approach

Taste perception in animals affects feed intake and may influence production traits. In particular, bitter is sensed by receptors encoded by the family of TAS2R genes. In this research, using a DNA pool‐seq approach coupled with next generation semiconductor based target resequencing, we analysed nine porcine TAS2R genes (TAS2R1, TAS2R3, TAS2R4, TAS2R7, TAS2R9, TAS2R10, TAS2R16, TAS2R38 and TAS2R39) to identify variability and, at the same time, estimate single nucleotide polymorphism (SNP) allele frequencies in several populations and testing differences in an association analysis. Equimolar DNA pools were prepared for five pig breeds (Italian Duroc, Italian Landrace, Pietrain, Meishan and Casertana) and wild boars (5–10 individuals each) and for two groups of Italian Large White pigs with extreme and divergent back fat thickness (50 + 50 pigs). About 1.8 million reads were obtained by sequencing amplicons generated from these pools. A total of 125 SNPs were identified, of which 37 were missense mutations. Three of them (p.Ile53Phe and p.Trp85Leu in TAS2R4; p.Leu37Ser in TAS2R39) could have important effects on the function of these bitter taste receptors, based on in silico predictions. Variability in wild boars seems lower than that in domestic breeds potentially as a result of selective pressure in the wild towards defensive bitter taste perception. Three SNPs in TAS2R38 and TAS2R39 were significantly associated with back fat thickness. These results may be important to understand the complexity of taste perception and their associated effects that could be useful to develop nutrigenetic approaches in pig breeding and nutrition.     

Replication of 6 Obesity Genes in a Meta-Analysis of Genome-Wide Association Studies from Diverse Ancestries

Obesity is a major public health problem with a significant genetic component. Multiple DNA polymorphisms/genes have been shown to be strongly associated with obesity, typically in populations of European descent. The aim of this study was to verify the extent to which 6 confirmed obesity genes (FTO, CTNNBL1, ADRB2, LEPR, PPARG and UCP2 genes) could be replicated in 8 different samples (n = 11,161) and to explore whether the same genes contribute to obesity-susceptibility in populations of different ancestries (five Caucasian, one Chinese, one African-American and one Hispanic population). GWAS-based data sets with 1000 G imputed variants were tested for association with obesity phenotypes individually in each population, and subsequently combined in a meta-analysis. Multiple variants at the FTO locus showed significant associations with BMI, fat mass (FM) and percentage of body fat (PBF) in meta-analysis. The strongest association was detected at rs7185735 (P-value = 1.01×10⁻⁷ for BMI, 1.80×10⁻⁶ for FM, and 5.29×10⁻⁴ for PBF). Variants at the CTNNBL1, LEPR and PPARG loci demonstrated nominal association with obesity phenotypes (meta-analysis P-values ranging from 1.15×10⁻³ to 4.94×10⁻²). There was no evidence of association with variants at ADRB2 and UCP2 genes. When stratified by sex and ethnicity, FTO variants showed sex-specific and ethnic-specific effects on obesity traits. Thus, it is likely that FTO has an important role in the sex- and ethnic-specific risk of obesity. Our data confirmed the role of FTO, CTNNBL1, LEPR and PPARG in obesity predisposition. These findings enhanced our knowledge of genetic associations between these genes and obesity-related phenotypes, and provided further justification for pursuing functional studies of these genes in the pathophysiology of obesity. Sex and ethnic differences in genetic susceptibility across populations of diverse ancestries may contribute to a more targeted prevention and customized treatment of obesity.     

Whole‐genome sequencing reveals a large deletion in the MITF gene in horses with white spotted coat colour and increased risk of deafness

White spotting phenotypes in horses are highly valued in some breeds. They are quite variable and may range from the common white markings up to completely white horses. EDNRB, KIT, MITF, PAX3 and TRPM1 represent known candidate genes for white spotting phenotypes in horses. For the present study, we investigated an American Paint Horse family segregating a phenotype involving white spotting and blue eyes. Six of eight horses with the white‐spotting phenotype were deaf. We obtained whole‐genome sequence data from an affected horse and specifically searched for structural variants in the known candidate genes. This analysis revealed a heterozygous ~63‐kb deletion spanning exons 6–9 of the MITF gene (chr16:21 503 211–21 566 617). We confirmed the breakpoints of the deletion by PCR and Sanger sequencing. PCR‐based genotyping revealed that all eight available affected horses from the family carried the deletion. The finding of an MITF variant fits well with the syndromic phenotype involving both depigmentation and an increased risk for deafness and corresponds to human Waardenburg syndrome type 2A. Our findings will enable more precise genetic testing for depigmentation phenotypes in horses.     

Detecting selection signatures in three Iranian sheep breeds

The objective of genome mapping is to achieve valuable insight into the connection between gene variants (genotype) and observed traits (phenotype). Part of that objective is to understand the selective forces that have operated on a population. Finding links between genotype–phenotype changes makes it possible to identify selective sweeps by patterns of genetic variation and linkage disequilibrium. Based on Illumina 50KSNP chip data, two approaches, XP‐EHH (cross‐population extend haplotype homozygosity) and F_ST (fixation index), were carried out in this research to identify selective sweeps in the genome of three Iranian local sheep breeds: Baluchi (n = 86), Lori‐Bakhtiari (n = 45) and Zel (n = 45). Using both methods, 93 candidate genomic regions were identified as harboring putative selective sweeps. Bioinformatics analysis of the genomic regions showed that signatures of selection related to multiple candidate genes, such as HOXB9, HOXB13, ACAN, NPR2, TRIL, AOX1, CSF2, GHR, TNS2, SPAG8, HINT2, ALS2, AAAS, RARG, SYCP2, CAV1, PPP1R3D, PLA2G7, TTLL7 and C20orf10, that play a role in skeletal system and tail, sugar and energy metabolisms, growth, reproduction, immune and nervous system traits. Our findings indicated diverse genomic selection during the domestication of Iranian sheep breeds.     

Polymorphisms in a desaturase 2 ortholog associate with cuticular hydrocarbon and male mating success variation in a natural population of Drosophila serrata

Elucidating the nature of genetic variation underlying both sexually selected traits and the fitness components of sexual selection is essential to understanding the broader consequences of sexual selection as an evolutionary process. To date, there have been relatively few attempts to connect the genetic variance in sexually selected traits with segregating DNA sequence polymorphisms. We set out to address this in a well‐characterized sexual selection system – the cuticular hydrocarbons (CHCs) of Drosophila serrata – using an indirect association study design that allowed simultaneous estimation of the genetic variance in CHCs, sexual fitness and single nucleotide polymorphism (SNP) effects in an outbred population. We cloned and sequenced an ortholog of the D. melanogaster desaturase 2 gene, previously shown to affect CHC biosynthesis in D. melanogaster, and associated 36 SNPs with minor allele frequencies > 0.02 with variance in CHCs and sexual fitness. Three SNPs had significant multivariate associations with CHC phenotype (q‐value < 0.05). At these loci, minor alleles had multivariate effects on CHCs that were weakly associated with the multivariate direction of sexual selection operating on these traits. Two of these SNPs had pleiotropic associations with male mating success, suggesting these variants may underlie responses to sexual selection due to this locus. There were 15 significant male mating success associations (q‐value < 0.1), and interestingly, we detected a nonrandom pattern in the relationship between allele frequency and direction of effect on male mating success. The minor‐frequency allele usually reduced male mating success, suggesting a positive association between male mating success and total fitness at this locus.     

Genetic markers that influence feed efficiency phenotypes also affect cattle temperament as measured by flight speed

Flight speed is a predictive indicator of cattle temperament and is associated with feed efficiency phenotypes. Genetic markers associated with both traits may assist with selection of calmer animals with improved economic value. A preliminary genome‐wide association study determined chromosomal regions on BTA9, and 17 were associated with flight speed. The genes quaking (QKI), glutamate receptor, ionotropic, AMPA 2 (GRIA2) and glycine receptor β (GLRB) were identified in these regions as potential functional candidates. Beef steers (n = 1057) were genotyped with SNPs located within and flanking these genes. One SNP located near QKI and one near GRIA2 were nominally associated with flight speed (P ≤ 0.05) although neither was significant after Bonferroni correction. Several studies have shown a correlation between flight speed and feed intake or gain; therefore, we also analyzed SNPs on BTA6:38–39 Mb known to be associated with average daily gain (ADG) and average daily feed intake (ADFI) for association with flight speed. Several SNPs on BTA6 were associated with flight speed (P ≤ 0.005), and three were significant after Bonferroni correction. These results suggest that the genes tested are unlikely to contribute to flight speed variation for our cattle population, but SNPs on BTA6 associated with ADG and ADFI may influence temperament. Use of these markers to select for economically important feed efficiency phenotypes may produce cattle with more desirable temperaments.     

The extent and genetic basis of phenotypic divergence in life history traits in Mimulus guttatus

Differential natural selection acting on populations in contrasting environments often results in adaptive divergence in multivariate phenotypes. Multivariate trait divergence across populations could be caused by selection on pleiotropic alleles or through many independent loci with trait‐specific effects. Here, we assess patterns of association between a suite of traits contributing to life history divergence in the common monkey flower, Mimulus guttatus, and examine the genetic architecture underlying these correlations. A common garden survey of 74 populations representing annual and perennial strategies from across the native range revealed strong correlations between vegetative and reproductive traits. To determine whether these multitrait patterns arise from pleiotropic or independent loci, we mapped QTLs using an approach combining high‐throughput sequencing with bulk segregant analysis on a cross between populations with divergent life histories. We find extensive pleiotropy for QTLs related to flowering time and stolon production, a key feature of the perennial strategy. Candidate genes related to axillary meristem development colocalize with the QTLs in a manner consistent with either pleiotropic or independent QTL effects. Further, these results are analogous to previous work showing pleiotropy‐mediated genetic correlations within a single population of M. guttatus experiencing heterogeneous selection. Our findings of strong multivariate trait associations and pleiotropic QTLs suggest that patterns of genetic variation may determine the trajectory of adaptive divergence.     

Whole genome sequencing reveals a novel deletion variant in the KIT gene in horses with white spotted coat colour phenotypes

White spotting phenotypes in horses can range in severity from the common white markings up to completely white horses. EDNRB, KIT, MITF, PAX3 and TRPM1 represent known candidate genes for such phenotypes in horses. For the present study, we re‐investigated a large horse family segregating a variable white spotting phenotype, for which conventional Sanger sequencing of the candidate genes’ individual exons had failed to reveal the causative variant. We obtained whole genome sequence data from an affected horse and specifically searched for structural variants in the known candidate genes. This analysis revealed a heterozygous ~1.9‐kb deletion spanning exons 10–13 of the KIT gene (chr3:77,740,239_77,742,136del1898insTATAT). In continuity with previously named equine KIT variants we propose to designate the newly identified deletion variant W22. We had access to 21 horses carrying the W22 allele. Four of them were compound heterozygous W20/W22 and had a completely white phenotype. Our data suggest that W22 represents a true null allele of the KIT gene, whereas the previously identified W20 leads to a partial loss of function. These findings will enable more precise genetic testing for depigmentation phenotypes in horses.     

Genome‐wide association study for semen traits of the bulls in Chinese Holstein

A genome‐wide association study (GWAS) was performed to identify markers and candidate genes for five semen traits in the Holstein bull population in China. The analyzed dataset consisted of records from 692 bulls from eight bull stations; each bull was genotyped using the Illumina BovineSNP50 BeadChip. Association tests between each trait and the 41 188 informative high‐quality SNPs were achieved with gapit software. In total, 19 suggestive significant SNPs, partly located within the reported QTL regions or within or close to the reported candidate genes, associated with five semen traits were detected. By combining our GWAS results with the biological functions of these genes, eight novel promising candidate genes, including ETNK1, PDE3A, PDGFRB, CSF1R, WT1, DSCAML1, SOD1 and RUNX2, were identified that potentially relate to semen traits. Our findings may provide a basis for further research on the genetic mechanism of semen traits and marker‐assisted selection of such traits in Holstein bulls.     

Exome association analysis sheds light onto leaf rust (Puccinia triticina) resistance genes currently used in wheat breeding (Triticum aestivum L.)

Resistance breeding is crucial for a sustainable control of leaf rust (Puccinia triticina) in wheat (Triticum aestivum L.) while directly targeting functional variants is the Holy Grail for efficient marker‐assisted selection and map‐based cloning. We assessed the limits and prospects of exome association analysis for severity of leaf rust in a large hybrid wheat population of 1574 single‐crosses plus their 133 parents. After imputation and quality control, exome sequencing revealed 202 875 single‐nucleotide polymorphisms (SNPs) covering 19.7% of the high‐confidence annotated gene space. We performed intensive data mining and found significant associations for 2171 SNPs corresponding to 50 different loci. Some of these associations mapped in the proximity of the already known resistance genes Lr21, Lr34‐B, Lr1 and Lr10, while other associated genomic regions, such as those on chromosomes 1A and 3D, harboured several annotated genes putatively involved in resistance. Validation with an independent population helped to narrow down the list of putative resistance genes that should be targeted by fine‐mapping. We expect that the proposed strategy of intensive data mining coupled with validation will significantly influence research in plant genetics and breeding.     

Variant discovery in a QTL region on chromosome 3 associated with fatness in chickens

Abdominal fat content is an economically important trait in commercially bred chickens. Although many quantitative trait loci (QTL) related to fat deposition have been detected, the resolution for these regions is low and functional variants are still unknown. The current study was conducted aiming at increasing resolution for a region previously shown to have a QTL associated with fat deposition, to detect novel variants from this region and to annotate those variants to delineate potentially functional ones as candidates for future studies. To achieve this, 18 chickens from a parental generation used in a reciprocal cross between broiler and layer lines were sequenced using the Illumina next‐generation platform with an initial coverage of 18X/chicken. The discovery of genetic variants was performed in a QTL region located on chromosome 3 between microsatellite markers LEI0161 and ADL0371 (33 595 706–42 632 651 bp). A total of 136 054 unique SNPs and 15 496 unique INDELs were detected in this region, and after quality filtering, 123 985 SNPs and 11 298 INDELs were retained. Of these variants, 386 SNPs and 15 INDELs were located in coding regions of genes related to important metabolic pathways. Loss‐of‐function variants were identified in several genes, and six of those, namely LOC771163, EGLN1, GNPAT, FAM120B, THBS2 and GGPS1, were related to fat deposition. Therefore, these loss‐of‐function variants are candidate mutations for conducting further studies on this important trait in chickens.     

Candidate gene SNP variation in floodplain populations of pedunculate oak (Quercus robur L.) near the species' southern range margin: Weak differentiation yet distinct associations with water availability

Populations residing near species' low‐latitude range margins (LLMs) often occur in warmer and drier environments than those in the core range. Thus, their genetic composition could be shaped by climatic drivers that differ from those occurring at higher latitudes, resulting in potentially adaptive variants of conservation value. Such variants could facilitate the adaptation of populations from other portions of the geographical range to similar future conditions anticipated under ongoing climate change. However, very few studies have assessed standing genetic variation at potentially adaptive loci in natural LLM populations. We investigated standing genetic variation at single nucleotide polymorphisms (SNPs) located within 117 candidate genes and its links to putative climatic selection pressures across 19 pedunculate oak (Quercus robur L.) populations distributed along a regional climatic gradient near the species' southern range margin in southeastern Europe. These populations are restricted to floodplain forests along large lowland rivers, whose hydric regime is undergoing significant shifts under modern rapid climate change. The populations showed very weak geographical structure, suggesting extensive genetic connectivity and gene flow or shared ancestry. We identified eight (6.2%) positive F_ST‐outlier loci, and genotype–environment association analyses revealed consistent associations between SNP allele frequencies and several climatic variables linked to water availability. A total of 61 associations involving 37 SNPs (28.5%) from 35 annotated genes provided important insights into putative functional mechanisms in our system. Our findings provide empirical support for the role of LLM populations as sources of potentially adaptive variation that could enhance species’ resilience to climate change‐related pressures.     

Haplotype‐based genotyping‐by‐sequencing in oat genome research

In a de novo genotyping‐by‐sequencing (GBS) analysis of short, 64‐base tag‐level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag‐level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635‐line diversity panel were used to infer chromosome‐level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high‐resolution genome analysis and genomic selection in oats. A combined genome‐wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component‐based genome‐wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS‐derived markers facilitate genome analysis and genomic selection in oat.     

Combining genome‐wide association study and FST‐based approaches to identify targets of Borrelia‐mediated selection in natural rodent hosts

Recent advances in high‐throughput sequencing technologies provide opportunities to gain novel insights into the genetic basis of phenotypic trait variation. Yet to date, progress in our understanding of genotype–phenotype associations in nonmodel organisms in general and natural vertebrate populations in particular has been hampered by small sample sizes typically available for wildlife populations and a resulting lack of statistical power, as well as a limited ability to control for false‐positive signals. Here we propose to combine a genome‐wide association study (GWAS) and F_ST‐based approach with population‐level replication to partly overcome these limitations. We present a case study in which we used this approach in combination with genotyping‐by‐sequencing (GBS) single nucleotide polymorphism (SNP) data to identify genomic regions associated with Borrelia afzelii resistance or susceptibility in the natural rodent host of this Lyme disease‐causing spirochete, the bank vole (Myodes glareolus). Using this combined approach we identified four consensus SNPs located in exonic regions of the genes Slc26a4, Tns3, Wscd1 and Espnl, which were significantly associated with the voles’ Borrelia infectious status within and across populations. Functional links between host responses to bacterial infections and most of these genes have previously been demonstrated in other rodent systems, making them promising new candidates for the study of evolutionary host responses to Borrelia emergence. Our approach is applicable to other systems and may facilitate the identification of genetic variants underlying disease resistance or susceptibility, as well as other ecologically relevant traits, in wildlife populations.