Genes Of Small Effect Research Articles

Progress towards understanding risk factor mechanisms in the development of autism spectrum disorders.

Autism spectrum disorders (ASD) are a heterogenous set of syndromes characterised by social impairment and cognitive symptoms. Currently, there are limited treatment options available to help people with ASD manage their symptoms. Understanding the biological mechanisms that result in ASD diagnosis and symptomatology is an essential step in developing new interventional strategies. Human genetic studies have identified common gene variants of small effect and rare risk genes and copy number variants (CNVs) that substantially increase the risk of developing ASD. Reverse translational studies using rodent models based on these genetic variants provide new insight into the biological basis of ASD. Here we review recent findings from three ASD associated CNV mouse models (16p11.2, 2p16.3 and 22q11.2 deletion) that show behavioural and cognitive phenotypes relevant to ASD. These models have identified disturbed excitation-inhibition neurotransmitter balance, evidenced by dysfunctional glutamate and GABA signalling, as a key aetiological mechanism. These models also provide emerging evidence for serotoninergic neurotransmitter system dysfunction, although more work is needed to clarify the nature of this. At the brain network level, prefrontal cortex (PFC) dysfunctional connectivity is also evident across these models, supporting disturbed PFC function as a key nexus in ASD aetiology. Overall, published data highlight the utility and valuable insight gained into ASD aetiology from preclinical CNV mouse models. These have identified key aetiological mechanisms that represent putative novel therapeutic targets for the treatment of ASD symptoms, making them useful translational models for future drug discovery, development and validation.

Genetic background of juniper (Juniperus spp.) consumption predicted by fecal near-infrared spectroscopy in divergently selected goats raised in harsh rangeland environments

BackgroundJunipers (Juniperus spp.) are woody native, invasive plants that have caused encroachment problems in the U.S. western rangelands, decreasing forage productivity and biodiversity. A potential solution to this issue is using goats in targeted grazing programs. However, junipers, which grow in dry and harsh environmental conditions, use chemical defense mechanisms to deter herbivores. Therefore, genetically selecting goats for increased juniper consumption is of great interest for regenerative rangeland management. In this context, the primary objectives of this study were to: 1) estimate variance components and genetic parameters for predicted juniper consumption in divergently selected Angora (ANG) and composite Boer x Spanish (BS) goat populations grazing on Western U.S. rangelands; and 2) to identify genomic regions, candidate genes, and biological pathways associated with juniper consumption in these goat populations.ResultsThe average juniper consumption was 22.4% (± 18.7%) and 7.01% (± 12.1%) in the BS and ANG populations, respectively. The heritability estimates (realized heritability within parenthesis) for juniper consumption were 0.43 ± 0.02 (0.34 ± 0.06) and 0.19 ± 0.03 (0.13 ± 0.03) in BS and ANG, respectively, indicating that juniper consumption can be increased through genetic selection. The repeatability values of predicted juniper consumption were 0.45 for BS and 0.28 for ANG. A total of 571 significant SNP located within or close to 231 genes in BS, and 116 SNP related to 183 genes in ANG were identified based on the genome-wide association analyses. These genes are primarily associated with biological pathways and gene ontology terms related to olfactory receptors, intestinal absorption, and immunity response.ConclusionsThese findings suggest that juniper consumption is a heritable trait of polygenic inheritance influenced by multiple genes of small effects. The genetic parameters calculated indicate that juniper consumption can be genetically improved in both goat populations.

Genetic architecture of ecological divergence between Oryza rufipogon and Oryza nivara.

Ecological divergence due to habitat difference plays a prominent role in the formation of new species, but the genetic architecture during ecological speciation and the mechanism underlying phenotypic divergence remain less understood. Two wild ancestors of rice (Oryza rufipogon and Oryza nivara) are a progenitor-derivative species pair with ecological divergence and provide a unique system for studying ecological adaptation/speciation. Here, we constructed a high-resolution linkage map and conducted a quantitative trait locus (QTL) analysis of 19 phenotypic traits using an F2 population generated from a cross between the two Oryza species. We identified 113 QTLs associated with interspecific divergence of 16 quantitative traits, with effect sizes ranging from 1.61% to 34.1% in terms of the percentage of variation explained (PVE). The distribution of effect sizes of QTLs followed a negative exponential, suggesting that a few genes of large effect and many genes of small effect were responsible for the phenotypic divergence. We observed 18 clusters of QTLs (QTL hotspots) on 11 chromosomes, significantly more than that expected by chance, demonstrating the importance of coinheritance of loci/genes in ecological adaptation/speciation. Analysis of effect direction and v-test statistics revealed that interspecific differentiation of most traits was driven by divergent natural selection, supporting the argument that ecological adaptation/speciation would proceed rapidly under coordinated selection on multiple traits. Our findings provide new insights into the understanding of genetic architecture of ecological adaptation and speciation in plants and help effective manipulation of specific genes or gene cluster in rice breeding.

PSXIII-26 Investigating the Genetic Background of Juniper Consumption in Goats

Abstract Junipers (Juniperus spp.) are woody invasive plants that have caused encroachment problems in the U.S. western rangeland, decreasing forage productivity and biodiversity. A potential solution to this issue is the use of goats in target grazing programs. Selecting goats for juniper consumption is of great interest to rangeland farmers. Therefore, our main objectives were to 1) estimate genetic parameters, including heritability and repeatability, for juniper consumption in Angora (ANG) and Boer x Spanish (BxS) composite population of goats grazing on West Texas rangelands (USA); and, 2) perform a genome-wide association study (GWAS) to identify candidate genes associated with juniper consumption. Fecal samples were collected multiple times between 2008 and 2017 and analyzed using near-infrared reflectance spectroscopy (NIRS) to estimate the percentage of juniper in the diet of goats, using calibration equations previously developed in controlled studies. We analyzed a dataset comprising 2,327 records from 459 ANG and 8,714 records from 1,996 BxS. The pedigree file included 1,601 and 2,426 ANG and BxS goats, respectively. Genomic information for 50,957 single nucleotide polymorphisms (SNP) from 93 ANG and 238 BxS goats was included in the analyses. Sampling date and sex were fitted as categorical fixed effects and age as a linear covariate in the statistical models. Animal direct additive genetic and permanent environment were considered as random effects. Genetic parameters were calculated based on the Restricted Maximum Likelihood method under the single-step genomic BLUP procedure implemented in the BLUPf90+ family of programs. We used de-regressed estimated breeding values and whole-genome sequence data for the GWAS analyses with 8 million SNP for the ANG and 5.3 million SNP for the BxS. The software GCTA was employed for these analyses. Juniper percentage in their diets varied across the years and ranged from 2.14% (± 7.51%) to 14.6% (± 11.0%) for ANG and from 10.5% (± 14.7) to 33.8% (± 18.1) for the BxS population. The heritability estimate for juniper consumption was 0.19 (± 0.038) for ANG and 0.28 (± 0.022) for BxS, indicating that juniper consumption can be increased through selection. The repeatability values were 0.21 for ANG and 0.37 for BxS. The GWAS revealed 1,257 significant SNP located within or close to 220 genes in ANG, and 878 SNP related to 159 genes in BxS, suggesting their association with juniper consumption. These findings suggest that juniper consumption is under genetic control and has a polygenic inheritance pattern influenced by multiple genes of small effect. The heritability and repeatability estimates indicate that genetic improvement of juniper consumption is feasible in both goat populations.

A geometric approach to the evolution of altruism

Fisher’s geometric model provides a powerful tool for making predictions about key properties of Darwinian adaptation. Here, I apply the geometric model to predict differences between the evolution of altruistic versus nonsocial phenotypes. I recover Kimura’s prediction that probability of fixation is greater for mutations of intermediate size, but I find that the effect size that maximises probability of fixation is relatively small in the context of altruism and relatively large in the context of nonsocial phenotypes, and that the overall probability of fixation is lower for altruism and is higher for nonsocial phenotypes. Accordingly, the first selective substitution is expected to be smaller, and to take longer, in the context of the evolution of altruism. These results strengthen the justification for employing streamlined social evolutionary methodologies that assume adaptations are underpinned by many genes of small effect.

Stronger evidence for genetic ancestry than environmental conditions in shaping the evolution of a complex signalling trait during biological invasion.

Introductions of invasive species to new environments often result in rapid rates of trait evolution. While in some cases these evolutionary transitions are adaptive and driven by natural selection, they can also result from patterns of genetic and phenotypic variation associated with the invasion history. Here, we examined the brown anole (Anolis sagrei), a widespread invasive lizard for which genetic data have helped trace the sources of non-native populations. We focused on the dewlap, a complex signalling trait known to be subject to multiple selective pressures. We measured dewlap reflectance, pattern and size in 30 non-native populations across the southeastern United States. As well, we quantified environmental variables known to influence dewlap signal effectiveness, such as canopy openness. Further, we used genome-wide data to estimate genetic ancestry, perform association mapping and test for signatures of selection. We found that among-population variation in dewlap characteristics was best explained by genetic ancestry. This result was supported by genome-wide association mapping, which identified several ancestry-specific loci associated with dewlap traits. Despite the strong imprint of this aspect of the invasion history on dewlap variation, we also detected significant relationships between dewlap traits and local environmental conditions. However, we found limited evidence that dewlap-associated genetic variants have been subject to selection. Our study emphasizes the importance of genetic ancestry and admixture in shaping phenotypes during biological invasion, while leaving the role of selection unresolved, likely due to the polygenic genetic architecture of dewlaps and selection acting on many genes of small effect.

Detecting parallel polygenic adaptation to novel evolutionary pressure in wild populations: a case study in Atlantic cod (Gadus morhua).

Populations can adapt to novel selection pressures through dramatic frequency changes in a few genes of large effect or subtle shifts in many genes of small effect. The latter (polygenic adaptation) is expected to be the primary mode of evolution for many life-history traits but tends to be more difficult to detect than changes in genes of large effect. Atlantic cod (Gadus morhua) were subjected to intense fishing pressure over the twentieth century, leading to abundance crashes and a phenotypic shift toward earlier maturation across many populations. Here, we use spatially replicated temporal genomic data to test for a shared polygenic adaptive response to fishing using methods previously applied to evolve-and-resequence experiments. Cod populations on either side of the Atlantic show covariance in allele frequency change across the genome that are characteristic of recent polygenic adaptation. Using simulations, we demonstrate that the degree of covariance in allele frequency change observed in cod is unlikely to be explained by neutral processes or background selection. As human pressures on wild populations continue to increase, understanding and attributing modes of adaptation using methods similar to those demonstrated here will be important in identifying the capacity for adaptive responses and evolutionary rescue. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Genetic basis of ecologically relevant body shape variation among four genera of cichlid fishes.

Divergence in body shape is one of the most widespread and repeated patterns of morphological variation in fishes and is associated with habitat specification and swimming mechanics. Such ecological diversification is the first stage of the explosive adaptive radiation of cichlid fishes in the East African Rift Lakes. We use two hybrid crosses of cichlids (Metriaclima sp. × Aulonocara sp. and Labidochromis sp. × Labeotropheus sp., >975 animals total) to determine the genetic basis of body shape diversification that is similar to benthic-pelagic divergence across fishes. Using a series of both linear and geometric shape measurements, we identified 34 quantitative trait loci (QTL) that underlie various aspects of body shape variation. These QTL are spread throughout the genome, each explaining 3.2-8.6% of phenotypic variation, and are largely modular. Further, QTL are distinct both between these two crosses of Lake Malawi cichlids and compared to previously identified QTL for body shape in fishes such as sticklebacks. We find that body shape is controlled by many genes of small effect. In all, we find that convergent body shape phenotypes commonly observed across fish clades are most likely due to distinct genetic and molecular mechanisms.

Understanding the genomic selection for crop improvement: current progress and future prospects

Although increased use of modern breeding techniques and technology has resulted in long-term genetic gain, the pace of genetic gain must be sped up to satisfy global agricultural demand. However, marker-assisted selection has proven its potential for improving qualitative traits with largeeffectsregulated by one to few genes. Its contribution to the improvement of the quantitative traits regulated by a number of small-effect genes is modest. In this context, genomic selection (GS) has been regarded as the most promising method for genetically enhancing complicated features that are regulated by several genes, each of which has minor effects. By examining a population's phenotypes and high-density marker scores, genomic selection can forecast the breeding potential of individual lines. The fact that GS uses all marker data in the prediction model prevents skewed marker effect estimations and maximizes the amount of variation caused by small-effect QTL. It has the ability to speed up the breeding cycle and as a consequence of which superior genotypes are selected rapidly. Developing the best GS models while taking into account non-additive effects, genotype-by-environment interaction, and cost-effectiveness will enable the widespread implementation of GS in plants. These steps will also increase heritability estimation and prediction accuracy. This review focuses on the shift from conventional selection methods to GS, underlying statistical tools and methodologies, the state of GS research in agricultural plants, and prospects for its effective use in the creation of climate-resilient crops.

Variance components of sex determination in the copepod Tigriopus californicus estimated from a pedigree analysis.

Extensive theory exists regarding population sex ratio evolution that predicts equal sex ratio (when parental investment is equal). In most animals, sex chromosomes determine the sex of offspring, and this fixed genotype for sex has made theory difficult to test since genotypic variance for the trait (sex) is lacking. It has long been argued that the genotype has become fixed in most animals due to the strong selection for equal sex ratios. The marine copepod Tigriopus californicus has no sex chromosomes, multiple genes affecting female brood sex ratio, and a brood sex ratio that responds to selection. The species thus provides an opportune system in which to test established sex ratio theory. In this paper, we further our exploration of polygenic sex determination in T. californicus using an incomplete diallel crossing design for analysis of the variance components of sex determination in the species. Our data confirm the presence of extra-binomial variance for sex, further confirming that sex is not determined through simple Mendelian trait inheritance. In addition, our crosses and backcrosses of isofemale lines selected for biased brood sex ratios show intermediate phenotypic means, as expected if sex is a threshold trait determined by an underlying "liability" trait controlled by many genes of small effects. Furthermore, crosses between families from the same selection line had similar increases in phenotypic variance as crosses between families from different selection lines, suggesting families from artificial selection lines responded to selection pressure through different underlying genetic bases. Finally, we estimate heritability of an individual to be male or female on the observed binary scale as 0.09 (95% CI: 0.034-0.14). This work furthers our accumulating evidence for polygenic sex determination in T. californicus laying the foundation for this as a model species in future studies of sex ratio evolution theory.

GIFT: new method for the genetic analysis of small gene effects involving small sample sizes

Small gene effects involved in complex/omnigenic traits remain costly to analyse using current genome-wide association studies (GWAS) because of the number of individuals required to return meaningful association(s), a.k.a. study power. Inspired by field theory in physics, we provide a different method called genomic informational field theory (GIFT). In contrast to GWAS, GIFT assumes that the phenotype is measured precisely enough and/or the number of individuals in the population is too small to permit the creation of categories. To extract information, GIFT uses the information contained in the cumulative sums difference of gene microstates between two configurations: (i) when the individuals are taken at random without information on phenotype values, and (ii) when individuals are ranked as a function of their phenotypic value. The difference in the cumulative sum is then attributed to the emergence of phenotypic fields. We demonstrate that GIFT recovers GWAS, that is, Fisher’s theory, when the phenotypic fields are linear (first order). However, unlike GWAS, GIFT demonstrates how the variance of microstate distribution density functions can also be involved in genotype–phenotype associations when the phenotypic fields are quadratic (second order). Using genotype–phenotype simulations based on Fisher’s theory as a toy model, we illustrate the application of the method with a small sample size of 1000 individuals.

Quantitative Genetic Analysis of Interactions in the Pepper-Phytophthora capsici Pathosystem.

The development of pepper cultivars with durable resistance to the oomycete Phytophthora capsici has been challenging due to differential interactions between the species that allow certain pathogen isolates to cause disease on otherwise resistant host genotypes. Currently, little is known about the pathogen genes involved in these interactions. To investigate the genetic basis of P. capsici virulence on individual pepper genotypes, we inoculated sixteen pepper accessions, representing commercial varieties, sources of resistance, and host differentials, with 117 isolates of P. capsici, for a total of 1,864 host-pathogen combinations. Analysis of disease outcomes revealed a significant effect of inter-species genotype-by-genotype interactions, although these interactions were quantitative rather than qualitative in scale. Isolates were classified into five pathogen subpopulations, as determined by their genotypes at over 60,000 single-nucleotide polymorphisms (SNPs). While absolute virulence levels on certain pepper accessions significantly differed between subpopulations, a multivariate phenotype reflecting relative virulence levels on certain pepper genotypes compared with others showed the strongest association with pathogen subpopulation. A genome-wide association study (GWAS) identified four pathogen loci significantly associated with virulence, two of which colocalized with putative RXLR effector genes and another with a polygalacturonase gene cluster. All four loci appeared to represent broad-spectrum virulence genes, as significant SNPs demonstrated consistent effects regardless of the host genotype tested. Host genotype-specific virulence variants in P. capsici may be difficult to map via GWAS with all but excessively large sample sizes, perhaps controlled by genes of small effect or by multiple allelic variants that have arisen independently. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

BREEDIT: a multiplex genome editing strategy to improve complex quantitative traits in maize.

Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs.

Genetic mapping of QTLs for drought tolerance in chickpea (Cicer arietinum L.).

Chickpea yield is severely affected by drought stress, which is a complex quantitative trait regulated by multiple small-effect genes. Identifying genomic regions associated with drought tolerance component traits may increase our understanding of drought tolerance mechanisms and assist in the development of drought-tolerant varieties. Here, a total of 187 F8 recombinant inbred lines (RILs) developed from an interspecific cross between drought-tolerant genotype GPF 2 (Cicer arietinum) and drought-sensitive accession ILWC 292 (C. reticulatum) were evaluated to identify quantitative trait loci (QTLs) associated with drought tolerance component traits. A total of 21 traits, including 12 morpho-physiological traits and nine root-related traits, were studied under rainfed and irrigated conditions. Composite interval mapping identified 31 QTLs at Ludhiana and 23 QTLs at Faridkot locations for morphological and physiological traits, and seven QTLs were identified for root-related traits. QTL analysis identified eight consensus QTLs for six traits and five QTL clusters containing QTLs for multiple traits on linkage groups CaLG04 and CaLG06. The identified major QTLs and genomic regions associated with drought tolerance component traits can be introgressed into elite cultivars using genomics-assisted breeding to enhance drought tolerance in chickpea.

Morphometric and Genetic Description of Trophic Adaptations in Cichlid Fishes.

Simple SummarySkull and jaw shape are critical to how an animal eats. The goal of this work was to examine how facial variation evolves and the genetic basis of these changes. We used two species of Lake Malawi cichlids with different facial shapes, one which has evolved to eat prey by suction feeding, a second that bites algae from rocks, as well as hybrid individuals generated by artificial mating of the two species. We found a series of changes in craniofacial structure including the shape of the lower jaw and throat region that impact how animals perform at suction feeding and biting. We then identified genetic regions that regulate these facial shapes. These genetic regions suggested that evolution of the senses, among other traits, may play an important role in facial evolution. Also, evolution of different parts of the face are controlled by distinct genetic regions. Despite this, cichlids that eat similar ways have similar facial shapes, suggesting that the function of jaw movement places certain limits on facial evolution in cichlid fishes. Overall, this work provides insights into how the face evolves, how these changes relate to feeding, and the genes and molecules that regulate craniofacial variation.Since Darwin, biologists have sought to understand the evolution and origins of phenotypic adaptations. The skull is particularly diverse due to intense natural selection on feeding biomechanics. We investigated the genetic and molecular origins of trophic adaptation using Lake Malawi cichlids, which have undergone an exemplary evolutionary radiation. We analyzed morphological differences in the lateral and ventral head shape among an insectivore that eats by suction feeding, an obligate biting herbivore, and their F2 hybrids. We identified variation in a series of morphological traits—including mandible width, mandible length, and buccal length—that directly affect feeding kinematics and function. Using quantitative trait loci (QTL) mapping, we found that many genes of small effects influence these craniofacial adaptations. Intervals for some traits were enriched in genes related to potassium transport and sensory systems, the latter suggesting co-evolution of feeding structures and sensory adaptations for foraging. Despite these indications of co-evolution of structures, morphological traits did not show covariation. Furthermore, phenotypes largely mapped to distinct genetic intervals, suggesting that a common genetic basis does not generate coordinated changes in shape. Together, these suggest that craniofacial traits are mostly inherited as separate modules, which confers a high potential for the evolution of morphological diversity. Though these traits are not restricted by genetic pleiotropy, functional demands of feeding and sensory structures likely introduce constraints on variation. In all, we provide insights into the quantitative genetic basis of trophic adaptation, identify mechanisms that influence the direction of morphological evolution, and provide molecular inroads to craniofacial variation.

Clock-linked genes underlie seasonal migratory timing in a diurnal raptor.

Seasonal migration is a dynamic natural phenomenon that allows organisms to exploit favourable habitats across the annual cycle. While the morphological, physiological and behavioural changes associated with migratory behaviour are well characterized, the genetic basis of migration and its link to endogenous biological time-keeping pathways are poorly understood. Historically, genome-wide research has focused on genes of large effect, whereas many genes of small effect may work together to regulate complex traits like migratory behaviour. Here, we explicitly relax stringent outlier detection thresholds and, as a result, discover how multiple biological time-keeping genes are important to migratory timing in an iconic raptor species, the American kestrel (Falco sparverius). To validate the role of candidate loci in migratory timing, we genotyped kestrels captured across autumn migration and found significant associations between migratory timing and genetic variation in metabolic and light-input pathway genes that modulate biological clocks (top1, phlpp1, cpne4 and peak1). Further, we demonstrate that migrating individuals originated from a single panmictic source population, suggesting the existence of distinct early and late migratory genotypes (i.e. chronotypes). Overall, our results provide empirical support for the existence of a within-population-level polymorphism in genes underlying migratory timing in a diurnally migrating raptor.

A combinatorial strategy to identify various types of QTLs for quantitative traits using extreme phenotype individuals in an F2 population

Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and small-effect genes for quantitative traits via bulked segregant analysis (BSA) in an F2 population. To address this issue, we proposed an integrated strategy for mapping various types of quantitative trait loci (QTLs) for quantitative traits via a combination of BSA and whole-genome sequencing. In this strategy, the numbers of read counts of marker alleles in two extreme pools were used to predict the numbers of read counts of marker genotypes. These observed and predicted numbers were used to construct a new statistic, Gw, for detecting quantitative trait genes (QTGs), and the method was named dQTG-seq1. This method was significantly better than existing BSA methods. If the goal was to identify extremely over-dominant and small-effect genes, another reserved DNA/RNA sample from each extreme phenotype F2 plant was sequenced, and the observed numbers of marker alleles and genotypes were used to calculate Gw to detect QTGs; this method was named dQTG-seq2. In simulated and real rice dataset analyses, dQTG-seq2 could identify many more extremely over-dominant and small-effect genes than BSA and QTL mapping methods. dQTG-seq2 may be extended to other heterogeneous mapping populations. The significance threshold of Gw in this study was determined by permutation experiments. In addition, a handbook for the R software dQTG.seq, which is available at https://cran.r-project.org/web/packages/dQTG.seq/index.html, has been provided in the supplemental materials for the users’ convenience. This study provides a new strategy for identifying all types of QTLs for quantitative traits in an F2 population.

Implications of Large-Effect Loci for Conservation: A Review and Case Study with Pacific Salmon.

The increasing feasibility of assembling large genomic datasets for non-model species presents both opportunities and challenges for applied conservation and management. A popular theme in recent studies is the search for large-effect loci that explain substantial portions of phenotypic variance for a key trait(s). If such loci can be linked to adaptations, 2 important questions arise: 1) Should information from these loci be used to reconfigure conservation units (CUs), even if this conflicts with overall patterns of genetic differentiation? 2) How should this information be used in viability assessments of populations and larger CUs? In this review, we address these questions in the context of recent studies of Chinook salmon and steelhead (anadromous form of rainbow trout) that show strong associations between adult migration timing and specific alleles in one small genomic region. Based on the polygenic paradigm (most traits are controlled by many genes of small effect) and genetic data available at the time showing that early-migrating populations are most closely related to nearby late-migrating populations, adult migration differences in Pacific salmon and steelhead were considered to reflect diversity within CUs rather than separate CUs. Recent data, however, suggest that specific alleles are required for early migration, and that these alleles are lost in populations where conditions do not support early-migrating phenotypes. Contrasting determinations under the US Endangered Species Act and the State of California's equivalent legislation illustrate the complexities of incorporating genomics data into CU configuration decisions. Regardless how CUs are defined, viability assessments should consider that 1) early-migrating phenotypes experience disproportionate risks across large geographic areas, so it becomes important to identify early-migrating populations that can serve as reliable sources for these valuable genetic resources; and 2) genetic architecture, especially the existence of large-effect loci, can affect evolutionary potential and adaptability.

Genome-wide analysis of acute low salinity tolerance in the eastern oyster Crassostrea virginica and potential of genomic selection for trait improvement.

As the global demand for seafood increases, research into the genetic basis of traits that can increase aquaculture production is critical. The eastern oyster (Crassostrea virginica) is an important aquaculture species along the Atlantic and Gulf Coasts of the United States, but increases in heavy rainfall events expose oysters to acute low salinity conditions, which negatively impact production. Low salinity survival is known to be a moderately heritable trait, but the genetic architecture underlying this trait is still poorly understood. In this study, we used ddRAD sequencing to generate genome-wide single-nucleotide polymorphism (SNP) data for four F2 families to investigate the genomic regions associated with survival in extreme low salinity (<3). SNP data were also used to assess the feasibility of genomic selection (GS) for improving this trait. Quantitative trait locus (QTL) mapping and combined linkage disequilibrium analysis revealed significant QTL on eastern oyster chromosomes 1 and 7 underlying both survival and day to death in a 36-day experimental challenge. Significant QTL were located in genes related to DNA/RNA function and repair, ion binding and membrane transport, and general response to stress. GS was investigated using Bayesian linear regression models and prediction accuracies ranged from 0.48 to 0.57. Genomic prediction accuracies were largest using the BayesB prior and prediction accuracies did not substantially decrease when SNPs located within the QTL region on Chr1 were removed, suggesting that this trait is controlled by many genes of small effect. Our results suggest that GS will likely be a viable option for improvement of survival in extreme low salinity.

Structural neuroimaging phenotypes of a novel multi-gene risk score in youth bipolar disorder

BackgroundBipolar disorder (BD) is among the most heritable psychiatric disorders, particularly in early-onset cases, owing to multiple genes of small effect. Here we examine a multi-gene risk score (MGRS), to address the gap in multi-gene research in early-onset BD. MethodsMGRS was derived from 34 genetic variants relevant to neuropsychiatric diseases and related systemic processes. Multiple MGRS were calculated across a spectrum of inclusion p-value thresholds, based on allelic associations with BD. Youth participants (123 BD, 103 healthy control [HC]) of European descent were included, of which 101 participants (58 BD, 43 HC) underwent MRI T1-weighted structural neuroimaging. Hierarchical regressions examined for main effects and MGRS-by-diagnosis interaction effects on 6 regions-of-interest (ROIs). Vertex-wise analysis also examined MGRS-by-diagnosis interactions. ResultsMGRS based on allelic association p≤0.60 was most robust, explaining 6.8% of variance (t(226)=3.46, p=.001). There was an MGRS-by-diagnosis interaction effect on ventrolateral prefrontal cortex surface area (vlPFC; β=.21, p=.0007). Higher MGRS was associated with larger vlPFC surface area in BD vs. HC. There were 8 significant clusters in vertex-wise analyses, primarily in fronto-temporal regions, including vlPFC. LimitationsCross-sectional design, modest sample size. ConclusionsThere was a diagnosis-by-MGRS interaction effect on vlPFC surface area, a region involved in emotional processing, emotional regulation, and reward response. Vertex-wise analysis also identified several clusters overlapping this region. This preliminary study provides an example of an approach to imaging-genetics that is intermediate between candidate gene and genome-wide association studies, enriched for genetic variants with established relevance to neuropsychiatric diseases.