Genetic Basis Of Phenotypic Variation Research Articles

Transcriptomics of pectoralis major muscles uncovers a footprint of enriched pathways in five diverse backyard chicken breeds of India

Genetic diversity existing between the chicken breeds can be used as a means to unravel the biological mechanisms affecting traits of commercial prominence. The present study attempted to compare the biological pathways enriched in pectoralis major muscles in five diverse chicken breeds. RNA sequencing data was generated from four biological replicates of pectoralis major muscles from Ankleshwar, Aseel, Kadaknath, Punjab Brown and Nicobari chicken. A total of 40 genes each for Nicobari and Aseel, 46 for Punjab Brown, 65 for Kadaknath and 86 for Ankaleshwar were found to be unique. The Neuroactive ligand-receptor interaction pathway was enriched in Ankaleshwar, Aseel and Kadaknath. However, the set of genes identified in this pathway were associated with different ligand receptors in each of the three breeds. The Wnt signaling pathway showed significant enrichment in Nicobari chicken while the Steroid biosynthesis pathway showed prominent expression in Punjab Brown chicken. The significant pathways pinpoint to genetic characteristics associated with each breed suggesting a transcriptome footprint. Our study is a first step toward determining the genetic basis of phenotypic diversity in chicken.

Integration of genome-wide association and genomic prediction for dissecting seed protein and amino acid in foxtail millet

ContextThe exploitation and utilization of genetic variation in crop germplasm benefit genomics-informed breeding programs. The integration of genome-wide association study (GWAS) and genomic prediction (GP) holds promise for illustrating genetic basis of phenotypic variation. Currently, the use of this integrative approach for dissecting grain protein and amino acid traits remains limited in crop species. ObjectiveThe research objectives were to identify significant single nucleotide polymorphisms (SNPs) associated with seed protein and amino acids and to assess the genomic predictive ability for nutritional traits in natural population of foxtail millet. MethodsIn this study, the concentrations of seed protein and 17 amino acids were assessed in a training population consisting of 238 diverse accessions of foxtail millet. The significant SNPs associated with these phenotypes were identified by GWAS with a mix-linear model. Extensive cross-validation was performed to evaluate the accuracy of genomic prediction of seed nutritional traits. Furthermore, the genomic prediction model was optimized and externally validated in 211 untested materials with the most significant SNPs obtained from GWAS. ResultsA significant genotype variance was detected for seed protein and amino acids and broad-sense heritability (h2) ranged from 0.45 to 0.87 (P < 0.05). The GWAS identified 39 significant SNPs associated with 15 amino acids (p < 1e-06), explaining an average of 12.2% phenotypic variation per locus. The number of significant SNPs ranged from 1 (Asp, Ile, Glu) to 23 for Phe amino acid, including six SNPs associated with one or multiple amino acids. In the training population, the prediction accuracies of protein and amino acids, tested using the 10-fold cross-validation model with whole genome-wide SNPs, ranged from 0.23 (Glu) to 0.60 (Lys) with an average value of 0.44%. Population structure had little effect on the prediction accuracy. In an empirical validation experiment involving 211 untested accessions, the averaged prediction accuracy increased by 12.3% across all traits when using the 1000 top SNPs obtained from GWAS, compared with the same number of randomly selected SNPs from the entire genome. ConclusionsLarge variations of seed protein and amino acids were found in a natural population of foxtail millet. GWAS identified 39 significant SNPs associated with 15 amino acids, and six SNPs were linked to more than one trait. The 10-fold cross-validation model produced the relatively higher prediction accuracies in seed quality traits of diverse accessions. By applying the significant SNPs from GWAS to the untested accessions, the use of 1000 GWAS-top SNPs resulted in more powerful predictions for complex nutritional traits than those using the same number of randomly selected SNPs across the genome. SignificanceThe research highlights the importance and effectiveness of integrative GWAS and genomic prediction in revealing the genetic architecture of seed protein and amino acid variation in foxtail millet. The results provide valuable insights into assessment and improvement of germplasm resources for advancing precision crop phenotyping and enhancing breeding programs for crop nutritional traits.

Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

BackgroundArtificial selection on quantitative traits using breeding values and selection indices in commercial livestock breeding populations causes changes in allele frequency over time at hundreds or thousands of causal loci and the surrounding genomic regions. In population genetics, this type of selection is called polygenic selection. Researchers and managers of pig breeding programs are motivated to understand the genetic basis of phenotypic diversity across genetic lines, breeds, and populations using selection mapping analyses. Here, we applied generation proxy selection mapping (GPSM), a genome-wide association analysis of single nucleotide polymorphism (SNP) genotypes (38,294–46,458 markers) of birth date, in four pig populations (15,457, 15,772, 16,595 and 8447 pigs per population) to identify loci responding to artificial selection over a period of five to ten years. Gene-drop simulation analyses were conducted to provide context for the GPSM results. Selected loci within and across each population of pigs were compared in the context of swine breeding objectives.ResultsThe GPSM identified 49 to 854 loci as under selection (Q-values less than 0.10) across 15 subsets of pigs based on combinations of populations. The number of significant associations increased when data were pooled across populations. In addition, several significant associations were identified in more than one population. These results indicate concurrent selection objectives, similar genetic architectures, and shared causal variants responding to selection across these pig populations. Negligible error rates (less than or equal to 0.02%) of false-positive associations were found when testing GPSM on gene-drop simulated genotypes, suggesting that GPSM distinguishes selection from random genetic drift in actual pig populations.ConclusionsThis work confirms the efficacy and the negligible error rates of the GPSM method in detecting selected loci in commercial pig populations. Our results suggest shared selection objectives and genetic architectures across swine populations. The identified polygenic selection highlights loci that are important to swine production.

Phenotype differentiation of Capsicum annuum var. glabriusculum of three regions in Mexico and its relation to climate

Background: Populations of Capsicum annuum var. glabriusculum are found in a wide portion of the Mexican territory, and it is ancestor of many cultivated forms relevant for the Mexican diet.&#x0D; Questions: What are the proportions of phenotypic and genetic variation distributed among its sampled regions, populations and within populations. How does the climate correlates to the population’s phenotypic variation.&#x0D; Species: Capsicum annuum var. glabriusculum.&#x0D; Study sites and years: 24 populations form three regions were sampled: Northwest, states of Sonora and Sinaloa; South: Oaxaca and Southeast Tabasco and Yucatán, in Mexico. The experiment was performed between years 2016 to 2018.&#x0D; Methods: Fruits from single plants were collected in wild populations. Plants were grown in a greenhouse. Nested ANOVAS were performed to estimate phenotypic and genetic variance components for different spatial scales. Climate correlation was estimated through univariate and multivariate methods.&#x0D; Results: 49.8 % of phenotypic variation was detected within families, 11.1 % among families (within populations), 21.3 % among populations and 17.6 % among regions. The genetic basis of phenotypic variation was 50.1% on average, for this genetic variation 34.2 % was found among regions, 39.4% among populations and 26.3 % within populations. Climate factors generated different patterns of correlations for vegetative, foliar and reproductive traits.&#x0D; Conclusions: Northwest plants were shorth, with small leaves and large fruits, Southeast plants were tall, with large leaves and small fruits, South plants developed intermediate phenotypic traits. Climate explained a large proportion of phenotypic differentiation.

Aristaless1 has a dual role in appendage formation and wing color specification during butterfly development

BackgroundHighly diverse butterfly wing patterns have emerged as a powerful system for understanding the genetic basis of phenotypic variation. While the genetic basis of this pattern variation is being clarified, the precise developmental pathways linking genotype to phenotype are not well understood. The gene aristaless, which plays a role in appendage patterning and extension, has been duplicated in Lepidoptera. One copy, aristaless1, has been shown to control a white/yellow color switch in the butterfly Heliconius cydno, suggesting a novel function associated with color patterning and pigmentation. Here we investigate the developmental basis of al1 in embryos, larvae, and pupae using new antibodies, CRISPR/Cas9, RNAi, qPCR assays of downstream targets, and pharmacological manipulation of an upstream activator.ResultsWe find that Al1 is expressed at the distal tips of developing embryonic appendages consistent with its ancestral role. In developing wings, we observe Al1 accumulation within developing scale cells of white H. cydno during early pupation while yellow scale cells exhibit little Al1 at this time point. Reduced Al1 expression is also associated with yellow scale development in al1 knockouts and knockdowns. We propose that Al1 expression in future white scales might be related to an observed downregulation of the enzyme Cinnabar and other genes that synthesize and transport the yellow pigment, 3–hydroxykynurenine (3-OHK). Finally, we provide evidence that Al1 activation is under the control of Wnt signaling.ConclusionsWe propose a model in which high levels of Al1 during early pupation, which are mediated by Wnt, are important for melanic pigmentation and specifying white portions of the wing while reduced levels of Al1 during early pupation promote upregulation of proteins needed to move and synthesize 3-OHK, promoting yellow pigmentation. In addition, we discuss how the ancestral role of aristaless in appendage extension may be relevant in understanding the cellular mechanism behind color patterning in the context of the heterochrony hypothesis.

Deciphering the Genetic Basis of Silkworm Cocoon Colors Provides New Insights into Biological Coloration and Phenotypic Diversification.

The genetic basis of phenotypic variation is a long-standing concern of evolutionary biology. Coloration has proven to be a visual, easily quantifiable, and highly tractable system for genetic analysis and is an ever-evolving focus of biological research. Compared with the homogenized brown-yellow cocoons of wild silkworms, the cocoons of domestic silkworms are spectacularly diverse in color, such as white, green, and yellow-red; this provides an outstanding model for exploring the phenotypic diversification and biological coloration. Herein, the molecular mechanism underlying silkworm green cocoon formation was investigated, which was not fully understood. We demonstrated that five of the seven members of a sugar transporter gene cluster were specifically duplicated in the Bombycidae and evolved new spatial expression patterns predominantly expressed in silk glands, accompanying complementary temporal expression; they synergistically facilitate the uptake of flavonoids, thus determining the green cocoon. Subsequently, polymorphic cocoon coloring landscape involving multiple loci and the evolution of cocoon color from wild to domestic silkworms were analyzed based on the pan-genome sequencing data. It was found that cocoon coloration involved epistatic interaction between loci; all the identified cocoon color-related loci existed in wild silkworms; the genetic segregation, recombination, and variation of these loci shaped the multicolored cocoons of domestic silkworms. This study revealed a new mechanism for flavonoids-based biological coloration that highlights the crucial role of gene duplication followed by functional diversification in acquiring new genetic functions; furthermore, the results in this work provide insight into phenotypic innovation during domestication.

Heritable Cas9-induced nonhomologous recombination in C. elegans.

Identification of the genetic basis of phenotypic variation within species remains challenging. In species with low recombination rates, such as Caenorhabditis elegans , genomic regions linked to a phenotype of interest by genetic mapping studies are often large, making it difficult to identify the specific genes and DNA sequence variants that underlie phenotypic differences. Here, we introduce a method that enables researchers to induce heritable targeted recombination in C. elegans with Cas9. We demonstrate that high rates of targeted nonhomologous recombination can be induced by Cas9 in a genomic region in which naturally occurring meiotic recombination events are exceedingly rare. We anticipate that Cas9-induced nonhomologous recombination (CINR) will greatly facilitate high-resolution genetic mapping in this species.

Divergence in interspecific and intersubspecific gene expression between two closely related horseshoe bats (Rhinolophus)

AbstractClosely related species have been used as representative systems to investigate the genetic mechanisms involved in the early stages of species differentiation. Previous studies have indicated that variation in gene expression might be a sensitive indicator of initial species divergence, although the role of expression divergence, and especially that associated with phenotypic variation remained relatively undefined. For three organs (cochlea, brain, and liver) from two closely related bat species (Rhinolophus siamensis and R. episcopus), the interspecific and intersubspecific gene expression profiles were compared using transcriptomics in this study. Striking organ specificity of expression was observed, and expression profiles exhibited similarities between cochlea and brain tissues. Numerous differentially expressed genes (DEGs) were identified for each organ in the interspecific comparison (cochlea/brain/liver: 1,069/647/692) and intersubspecific comparison (608/528/368). Functional enrichment analysis indicated vital variation in expression related to the immune system, ion activities, neuronal function, and multisensory system regulation in both comparisons. DEGs relevant to the variation in echolocation calls (RF) were found, and some of them were involved in the pivotal patterns of expression variation. The regulation of immune, ion channel, neural activity, and sophisticated sensory functions at the expression level might be key mechanisms in the early species divergence of bats, and the expression variation related to acoustical signal could have played a crucial part. This study expands our knowledge of gene expression and patterns of variation for three key organs to echolocation at both the interspecific and intersubspecific levels. Further, the framework described here provides insight into the genetic basis of phenotypic variation during the incipient stage of species differentiation.

Association study of SNP locus for color related traits in herbaceous peony (Paeonia lactiflora Pall.) using SLAF-seq.

Paeonia lactiflora Pall. (P. lactiflora) is a famous ornamental plant with showy and colorful flowers that has been domesticated in China for 4,000 years. However, the genetic basis of phenotypic variation and genealogical relationships in P. lactiflora population is poorly understood due to limited genetic information, which brings about bottlenecks in the application of effective and efficient breeding strategies. Understanding the genetic basis of color-related traits is essential for improving flower color by marker-assisted selection (MAS). In this study, a high throughput sequencing of 99 diploid P. lactiflora accessions via specific-locus amplified fragment sequencing (SLAF-seq) technology was performed. In total, 4,383,645 SLAF tags were developed from 99 P. lactiflora accessions with an average sequencing depth of 20.81 for each SLAF tag. A total of 2,954,574 single nucleotide polymorphisms (SNPs) were identified from all SLAF tags. The population structure and phylogenetic analysis showed that P. lactiflora population used in this study could be divided into six divergent groups. Through association study using Mixed linear model (MLM), we further identified 40 SNPs that were significantly positively associated with petal color. Moreover, a derived cleaved amplified polymorphism (dCAPS) marker that was designed based on the SLAF tag 270512F co-segregated with flower colors in P. lactiflora population. Taken together, our results provide valuable insights into the application of MAS in P. lactiflora breeding programs.

Cognitive genomics of learning delay and low level of social performance monitoring in macaque

Cognitive skills and the underlying neural architecture are under the influence of genetics. Cognitive genomics research explores the triadic relationship between genes, brain, and cognition, with its major strategy being genotype-driven. Here we show that an inverse strategy is feasible to identify novel candidate genes for particular neuro-cognitive phenotypes in macaques. Two monkeys, originally involved in separate psychological studies, exhibited learning delay and low levels of social performance monitoring. In one monkey, mirror neurons were fewer compared to controls and mu suppression was absent in the frontal cortex. The other monkey showed heightened visual responsiveness in both frontal cortex and dopamine-rich midbrain, with a lack of inter-areal synchronization. Exome analyses revealed that the two monkeys were most likely cousins and shared variants in MAP2, APOC1, and potentially HTR2C. This phenotype-driven strategy in cognitive genomics provides a useful means to clarify the genetic basis of phenotypic variation and develop macaque models of neuropsychiatric disorders.

Sorghum Association Panelwhole-genome sequencing establishes cornerstone resource for dissecting genomic diversity.

SUMMARYAssociation mapping panels represent foundational resources for understanding the genetic basis of phenotypic diversity and serve to advance plant breeding by exploring genetic variation across diverse accessions. We report the whole‐genome sequencing (WGS) of 400 sorghum (Sorghum bicolor (L.) Moench) accessions from the Sorghum Association Panel (SAP) at an average coverage of 38× (25–72×), enabling the development of a high‐density genomic marker set of 43 983 694 variants including single‐nucleotide polymorphisms (approximately 38 million), insertions/deletions (indels) (approximately 5 million), and copy number variants (CNVs) (approximately 170 000). We observe slightly more deletions among indels and a much higher prevalence of deletions among CNVs compared to insertions. This new marker set enabled the identification of several novel putative genomic associations for plant height and tannin content, which were not identified when using previous lower‐density marker sets. WGS identified and scored variants in 5‐kb bins where available genotyping‐by‐sequencing (GBS) data captured no variants, with half of all bins in the genome falling into this category. The predictive ability of genomic best unbiased linear predictor (GBLUP) models was increased by an average of 30% by using WGS markers rather than GBS markers. We identified 18 selection peaks across subpopulations that formed due to evolutionary divergence during domestication, and we found six Fst peaks resulting from comparisons between converted lines and breeding lines within the SAP that were distinct from the peaks associated with historic selection. This population has served and continues to serve as a significant public resource for sorghum research and demonstrates the value of improving upon existing genomic resources.

Host genomic influence on bacterial composition in the switchgrass rhizosphere.

Host genetic variation can shape the diversity and composition of associated microbiomes, which may reciprocally influence host traits and performance. While the genetic basis of phenotypic diversity of plant populations in nature has been studied, comparatively little research has investigated the genetics of host effects on their associated microbiomes. Switchgrass (Panicum virgatum) is a highly outcrossing, perennial, grass species with substantial locally adaptive diversity across its native North American range. Here, we compared 383 switchgrass accessions in a common garden to determine the host genotypic influence on rhizosphere bacterial composition. We hypothesized that the composition and diversity of rhizosphere bacterial assemblages would differentiate due to genotypic differences between hosts (potentially due to root phenotypes and associated life history variation). We observed higher alpha diversity of bacteria associated with upland ecotypes and tetraploids, compared to lowland ecotypes and octoploids, respectively. Alpha diversity correlated negatively with flowering time and plant height, indicating that bacterial composition varies along switchgrass life history axes. Narrow-sense heritability (h2 ) of the relative abundance of 21 core bacterial families was observed. Overall compositional differences among tetraploids, due to genetic variation, supports widespread genotypic influence on the rhizosphere microbiome. Tetraploids were only considered due to complexities associated with the octoploid genomes. Lastly, a genome-wide association study identified 1861 single-nucleotide polymorphisms associated with 110 families and genes containing them related to potential regulatory functions. Our findings suggest that switchgrass genomic and life-history variation influences bacterial composition in the rhizosphere, potentially due to host adaptation to local environments.

Polygenic adaptation and negative selection across traits, years and environments in a long-lived plant species (Pinus pinaster Ait., Pinaceae).

A decade of genetic association studies in multiple organisms suggests that most complex traits are polygenic; that is, they have a genetic architecture determined by numerous loci, each with small effect-size. Thus, determining the degree of polygenicity and its variation across traits, environments and time is crucial to understand the genetic basis of phenotypic variation. We applied multilocus approaches to estimate the degree of polygenicity of fitness-related traits in a long-lived plant (Pinus pinaster Ait., maritime pine) and to analyse this variation across environments and years. We evaluated five categories of fitness-related traits (survival, height, phenology, functional, and biotic-stress response) in a clonal common-garden network planted in contrasted environments (over 20,500 trees). Most of the analysed traits showed evidence of local adaptation based on Qst -Fst comparisons. We further observed a remarkably stable degree of polygenicity, averaging 6% (range of 0%-27%), across traits, environments and years. We detected evidence of negative selection, which could explain, at least partially, the high degree of polygenicity. Because polygenic adaptation can occur rapidly, our results suggest that current predictions on the capacity of natural forest tree populations to adapt to new environments should be revised, especially in the current context of climate change.

Mitonuclear Genetic Interactions in the Basidiomycete Heterobasidion parviporum Involve a Non-conserved Mitochondrial Open Reading Frame.

The mitochondrial and nuclear genomes of Eukaryotes are inherited separately and consequently follow distinct evolutionary paths. Nevertheless, the encoding of many mitochondrial proteins by the nuclear genome shows the high level of integration they have reached, which makes mitonuclear genetic interactions all the more conceivable. For each species, natural selection has fostered the evolution of coadapted alleles in both genomes, but a population-wise divergence of such alleles could lead to important phenotypic variation, and, ultimately, to speciation. In this study in the Basidiomycete Heterobasidion parviporum, we have investigated the genetic basis of phenotypic variation among laboratory-designed heterokaryons carrying the same pair of haploid nuclei, but a different mitochondrial genome. Radial growth rate data of thirteen unrelated homokaryotic parents and of their heterokaryotic offspring were combined with SNP data extracted from parental genome sequences to identify nuclear and mitochondrial loci involved in mitonuclear interactions. Two nuclear loci encoding mitochondrial proteins appeared as best candidates to engage in a genetic interaction affecting radial growth rate with a non-conserved mitochondrial open reading frame of unknown function and not reported apart from the Russulales order of Basidiomycete fungi. We believe our approach could be useful to investigate several important traits of fungal biology where mitonuclear interactions play a role, including virulence of fungal pathogens.

Estimating prevalence of human traits among populations from polygenic risk scores

The genetic basis of phenotypic variation across populations has not been well explained for most traits. Several factors may cause disparities, from variation in environments to divergent population genetic structure. We hypothesized that a population-level polygenic risk score (PRS) can explain phenotypic variation among geographic populations based solely on risk allele frequencies. We applied a population-specific PRS (psPRS) to 26 populations from the 1000 Genomes to four phenotypes: lactase persistence (LP), melanoma, multiple sclerosis (MS) and height. Our models assumed additive genetic architecture among the polymorphisms in the psPRSs, as is convention. Linear psPRSs explained a significant proportion of trait variance ranging from 0.32 for height in men to 0.88 for melanoma. The best models for LP and height were linear, while those for melanoma and MS were nonlinear. As not all variants in a PRS may confer similar, or even any, risk among diverse populations, we also filtered out SNPs to assess whether variance explained was improved using psPRSs with fewer SNPs. Variance explained usually improved with fewer SNPs in the psPRS and was as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRSs performance may indicate that missing heritability is partially due to complex architecture that does not mandate additivity, undiscovered variants or spurious associations in the databases. We demonstrated that PRS-based analyses can be used across diverse populations and phenotypes for population prediction and that these comparisons can identify the universal risk variants.

Distribution of DGAT1 copy number variation in Chinese goats and its associations with milk production traits

Goat is an important sector for meat and dairy products. Diacylglycerol O-acyltransferase 1 (DGAT1), which is a key gene in milk production, has been recently detected to overlap with a novel copy number variation (CNV) in goats. CNVs could be genetic markers providing new insights into the genetic basis of phenotypic variation. Up to now, there are no reports on the DGAT1-related CNV (DGAT1 CNV) in Chinese goats. This study first detected the distribution of the DGAT1 CNV in Chinese seven goat breeds, finding substantial differences among dairy, meat, and fiber goats (P < 0.01). The association analysis between the DGAT1 CNV and milk production traits revealed significant associations: Xinong Sannen (XS) dairy goat with copy number loss type had higher freezing point depression (FPD) (P < 0.01) and milk solids-not-fat (SNF) content (P < 0.05). Overall, our study unraveled the distribution of DGAT1 CNV in Chinese goats for the first time and found the potential role of this CNV in the marker-assisted selection of dairy goat breeding.

A supergene underlies linked variation in color and morphology in a Holarctic songbird

The genetic architecture of a phenotype can have considerable effects on the evolution of a trait or species. Characterizing genetic architecture provides insight into the complexity of a given phenotype and, potentially, the role of the phenotype in evolutionary processes like speciation. We use genome sequences to investigate the genetic basis of phenotypic variation in redpoll finches (Acanthis spp.). We demonstrate that variation in redpoll phenotype is broadly controlled by a ~55-Mb chromosomal inversion. Within this inversion, we find multiple candidate genes related to melanogenesis, carotenoid coloration, and bill shape, suggesting the inversion acts as a supergene controlling multiple linked traits. A latitudinal gradient in ecotype distribution suggests supergene driven variation in color and bill morphology are likely under environmental selection, maintaining supergene haplotypes as a balanced polymorphism. Our results provide a mechanism for the maintenance of ecotype variation in redpolls despite a genome largely homogenized by gene flow.

Revisiting a GWAS peak in Arabidopsis thaliana reveals possible confounding by genetic heterogeneity.

Genome-wide association studies (GWAS) have become a standard approach for exploring the genetic basis of phenotypic variation. However, correlation is not causation, and only a tiny fraction of all associations have been experimentally confirmed. One practical problem is that a peak of association does not always pinpoint a causal gene, but may instead be tagging multiple causal variants. In this study, we reanalyze a previously reported peak associated with flowering time traits in Swedish Arabidopsis thaliana population. The peak appeared to pinpoint the AOP2/AOP3 cluster of glucosinolate biosynthesis genes, which is known to be responsible for natural variation in herbivore resistance. Here we propose an alternative hypothesis, by demonstrating that the AOP2/AOP3 flowering association can be wholly accounted for by allelic variation in two flanking genes with clear roles in regulating flowering: NDX1, a regulator of the main flowering time controller FLC, and GA1, which plays a central role in gibberellin synthesis and is required for flowering under some conditions. In other words, we propose that the AOP2/AOP3 flowering-time association may be yet another example of a spurious, "synthetic" association, arising from trying to fit a single-locus model in the presence of two statistically associated causative loci. We conclude that caution is needed when using GWAS for fine-mapping.

Accurate, ultra-low coverage genome reconstruction and association studies in Hybrid Swarm mapping populations.

Genetic association studies seek to uncover the link between genotype and phenotype, and often utilize inbred reference panels as a replicable source of genetic variation. However, inbred reference panels can differ substantially from wild populations in their genotypic distribution, patterns of linkage-disequilibrium, and nucleotide diversity. As a result, associations discovered using inbred reference panels may not reflect the genetic basis of phenotypic variation in natural populations. To address this problem, we evaluated a mapping population design where dozens to hundreds of inbred lines are outbred for few generations, which we call the Hybrid Swarm. The Hybrid Swarm approach has likely remained underutilized relative to pre-sequenced inbred lines due to the costs of genome-wide genotyping. To reduce sequencing costs and make the Hybrid Swarm approach feasible, we developed a computational pipeline that reconstructs accurate whole genomes from ultra-low-coverage (0.05X) sequence data in Hybrid Swarm populations derived from ancestors with phased haplotypes. We evaluate reconstructions using genetic variation from the Drosophila Genetic Reference Panel as well as variation from neutral simulations. We compared the power and precision of Genome-Wide Association Studies using the Hybrid Swarm, inbred lines, recombinant inbred lines (RILs), and highly outbred populations across a range of allele frequencies, effect sizes, and genetic architectures. Our simulations show that these different mapping panels vary in their power and precision, largely depending on the architecture of the trait. The Hybrid Swam and RILs outperform inbred lines for quantitative traits, but not for monogenic ones. Taken together, our results demonstrate the feasibility of the Hybrid Swarm as a cost-effective method of fine-scale genetic mapping.

Candidate Genetic Modifiers for RPGR Retinal Degeneration.

PurposeTo define genetic variants associated with variable severity of X-linked progressive retinal atrophy 1 (XLPRA1) caused by a five-nucleotide deletion in canine RPGR exon ORF15.MethodsA genome-wide association study (GWAS) was performed in XLPRA1 phenotype informative pedigree. Whole genome sequencing (WGS) was used for mutational analysis of genes within the candidate genomic region. Retinas of normal and mutant dogs were used for gene expression, gene structure, and RNA duplex analyses.ResultsGWAS followed by haplotype phasing identified an approximately 4.6 Mb candidate genomic interval on CFA31 containing seven protein-coding genes expressed in retina (ROBO1, ROBO2, RBM11, NRIP1, HSPA13, SAMSN1, and USP25). Furthermore, we identified and characterized two novel lncRNAs, ROBO1-AS and ROBO2-AS, that display overlapping gene organization with axon guidance pathway genes ROBO1 and ROBO2, respectively, producing sense-antisense gene pairs. Notably, ROBO1-AS and ROBO2-AS act in cis to form lncRNA/mRNA duplexes with ROBO1 and ROBO2, respectively, suggesting important roles for these lncRNAs in the ROBO regulatory network. A subsequent WGS identified candidate genes within the genomic region on CFA31 that might be implicated in modifying severity of XLPRA1. This approach led to discovery of genetic variants in ROBO1, ROBO1-AS, ROBO2-AS, and USP25 that are strongly associated with the XLPRA1 moderate phenotype.ConclusionsThe study provides new insights into the genetic basis of phenotypic variation in severity of RPGRorf15-associated retinal degeneration. Our findings suggest an important role for ROBO pathways in disease progression further expanding on our previously reported changes of ROBO1 expression in XLPRA1 retinas.