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Simple scaling laws control the genetic architectures of human complex traits.

Genome-wide association studies have revealed that the genetic architectures of complex traits vary widely, including in terms of the numbers, effect sizes, and allele frequencies of significant hits. However, at present we lack a principled way of understanding the similarities and differences among traits. Here, we describe a probabilistic model that combines the effects of mutation, drift, and stabilizing selection at individual sites with a genome-scale model of phenotypic variation. In this model, the architecture of a trait arises from the distribution of selection coefficients of mutations and from two scaling parameters. We fit this model for 95 highly polygenic quantitative traits of different kinds from the UK Biobank. Notably, we infer that all these traits have fairly similar, though not identical, distributions of selection coefficients. This similarity suggests that differences in architectures of highly polygenic traits arise mainly from the two scaling parameters: the mutational target size and heritability per site, which vary by orders of magnitude among traits. When these two scale factors are accounted for, we find that the architectures of all 95 traits are very similar.

Humans

Slmsh1-induced heritable enhancement of traits for tomato breeding improvement.

Vegetable grafting is a horticultural technique employed to develop specialized plant varieties by effectively enhancing resistance to both biotic and abiotic stresses, as well as improving fruit quality and yield. However, these advantageous traits are generally non-heritable. The MSH1 gene induced heritable enhancement-through-grafting (HEG) effect on growth vigor, demonstrating promising application potential. In this study, we employed the msh1 mutant tomato as a rootstock to induce heritable superior traits and combined this approach with hybridization techniques to enhance tomato cultivars. Three Slmsh1 mutants were generated using CRISPR/Cas9 which exhibited a dwarf phenotype with whitened spots. By grafting several distinct inbred lines onto Slmsh1, we observed significant HEG, drought stress tolerance, and fruit quality. Under drought conditions, Slmsh1-grafted tomato seedlings exhibited increased biomass and enhanced drought tolerance through the regulation of antioxidant enzyme activities. Differential expression and methylation analyses of the graft progeny revealed that these heritable enhanced traits (HETs) are likely attributable to epigenetic modifications in the expression of ROS-scavenging- and hormone-related genes. Furthermore, to explore practical applications, we crossed inbred lines with HETs and evaluated the growth, yield, and fruit quality of the resulting hybrid combinations. The results indicated that these hybrid combinations improved fruit yield and quality, enhancing the total soluble solids, soluble sugar, and soluble protein content. These findings suggest that Slmsh1-grafted progenies enhanced plant biomass and drought resistance, while their hybrid combinations positively influenced root growth, yield, and fruit quality, providing new insights into the synergistic integration of genome editing and conventional breeding.

Solanum lycopersicum

Transition from Conventional to Genomic Selection (ssGBLUP) led to improve in accuracy gains and selection decisions in Sahiwal Cattle.

By using genome-wide markers to predict an individual's genetic potential, the introduction of Genomic Selection (GS) has transformed animal breeding. This greatly accelerated selection for complex traits by lowering reliance on drawn-out field trials, allowing for faster genetic gains in livestock. However, there is little research on the effects of genomic selection on Sahiwal cattle in India, and comparing it to the current culling or selection process is even more uncommon, particularly in nations with fewer genotyped animals. This study is an initial effort to address the aforementioned gaps in knowledge. Genomic selection was implemented in Sahiwal cattle for the 305 days milk yield using univariate animal model and the single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) method. The Effective Population size (Ne) of the Sahiwal herd was calculated using genomic data and was reported for the previous generation to be 71.927. The heritability of 305 days milk yield was estimated as 0.177 ± 0.068. Genomic estimated breeding values (GEBVs) were predicted for each individual using ssGBLUP, yielding a mean prediction accuracy of 43.11%, compared with 40.88% obtained using conventional pedigree-based BLUP. Cross-validation further demonstrated superior predictive performance of ssGBLUP, with accuracies of 76.82% and 70.50% for ssGBLUP and PBLUP, respectively. To further check the effectiveness of the genomic selection methodology, we also compared the GEBVs obtained and compared it with the Expected Progeny Difference (EPD) which is being applied in our farm for culling decisions. It was seen that GEBVs obtained from ssGBLUP methodology were also in line with the conventionally used method of EPD. The use of genomic selection enables genetic studies with limited pedigree information. Additionally, the ssGBLUP methodology allows to check for pedigree errors, where family relationships are incorrectly recorded. The EPD and GEBVs were consistent with one another, indicating that genomic selection may also be utilised to support culling and selection decisions in a farm. Thus, in a conventional animal breeding program with constraint resources and an incomplete pedigree, we recommend employing the ssGBLUP model for regular genomic assessment and identification of suitable candidates to effectively carry out a genomic selection program.

Animals

Genome-wide association study to dissect the genetic architecture of bolting-related traits in carrot (Daucus carota).

As a crucial root vegetable, the phenomenon of bolting and flowering presents a significant challenge to the commercial value of carrot. However, the genetic mechanism of carrot bolting remains to be fully elucidated. In this study, we conducted a two-year cultivation experiment with a population of 240 carrots to examine traits associated with bolting. We conducted whole-genome sequencing on these carrots and subsequently performed population structure analysis, as well as genome-wide association studies (GWAS). A total of nine single nucleotide polymorphism (SNP) loci were identified across diverse environmental conditions that exhibited significant associations with bolting speed and other traits. Furthermore, within 93 candidate genes identified, the RING-domain zinc-finger protein LOC108205243 was determined to play a significant role in the regulation of bolting traits. The SNPs and candidate genes identified in this research may serve as molecular markers for bolting traits, thereby offering essential resources for genetic engineering breeding efforts aimed at managing bolting in carrots.

Daucus carota

The power to detect linkage disequilibrium with quantitative traits in selected samples.

Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL-marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis.

Alleles

Identification of Candidate Genes Associated with Growth Traits in Procambarus clarkii Using Whole-Genome Resequencing.

Growth is a critical economic trait in all aquaculture industries. To address issues such as germplasm degradation, a comprehensive understanding of the growth and development mechanisms, along with genetic improvement strategies, for Procambarus clarkii (P. clarkii) is urgently required. In this study, we performed whole-genome resequencing on 89 individuals from five cultured stocks to investigate growth traits (body length) and identified a total of 46,919,297 high-quality single nucleotide polymorphisms (SNPs). Based on these SNPs, we conducted principal component analysis (PCA), phylogenetic analysis, and population genetic structure analysis. Furthermore, we performed selective sweep analysis (using FST, Pi, and XP-CLR) and a genome-wide association study (GWAS) to identify genetic variants associated with growth traits. The results revealed significant genetic differentiation among the five cultured stocks, with the Ma'anshan cultured stock exhibiting the fastest linkage disequilibrium (LD) decay. Additionally, long-term aquaculture in different geographical regions resulted in distinct genetic differences among cultured stocks. Through selective sweep analysis, the intersection of FST, Pi, and XP-CLR across the five populations yielded several growth-related candidate genes: Nephrin, Somatostatin, zinc finger protein 154, and yeti. Subsequent the GWAS identified two candidate genes associated with growth traits: Cullin-associated and neddylation-dissociated protein 1 (CAND1) and Baculoviral IAP repeat-containing protein 8 (BIRC8). These genes are presumed to play pivotal roles in the growth and development of P. clarkii. Overall, our findings provide new insights into the genetic mechanisms underlying growth and development in P. clarkii, and these identified genes serve as promising candidates for further functional studies and genetic improvement of this species.

Polymorphism, Single Nucleotide

Smarter stomata: emergent technologies unlocking yield potential in a changing climate.

Stomata, the gatekeepers of leaf gas exchange, regulate carbon dioxide uptake and water loss, functions increasingly critical as crops face more frequent, intense heat and drought. Under dry conditions, stomatal conductance (g s) typically decreases, limiting carbon assimilation and yield. Heat stress, in contrast, elicits variable g S responses: sometimes increasing to facilitate transpirational cooling, while at other times decreasing, especially when combined with drought. Heat and drought also induce complex, context-dependent shifts in stomatal anatomy. Smaller, denser stomata improve drought resilience in some cases, while reduced density confers greater tolerance in others. The optimal stomatal ideotype remains unknown, and different or even opposing traits may confer resilience dependent on the environmental scenario. Substantial genotypic variation in g s and stomatal anatomy, high heritability and co-localized quantitative trait loci for stomatal traits and yield highlight their untapped potential as breeding targets for climate-resilient crops. However, stomatal traits remain largely absent from breeding pipelines due to challenges of phenotyping at scale. This is changing rapidly. Advances in deep learning, porometry, digital microscopy, and remote sensing now enable high-throughput measurement of stomatal physiology and anatomy. Next-generation breeding technologies including clustered regularly interspaced short palindromic repeats (CRISPR), multi-omics approaches, and artificial intelligence-driven ideotype selection models could revolutionize breeding, allowing precise engineering of stomatal traits for resilience to environmental stress. The time has come to move beyond characterizing stomatal traits and start actively incorporating them into breeding strategies. By leveraging these technologies, stomatal traits can become high value targets, unlocking their potential to enhance crop performance in a hotter, drier future.

abiotic stress

Mapping quantitative trait loci for behavioral traits in the mouse.

After many years of studying various behavioral characters in the mouse, it is clear that most are heritable and are specified by complexes of genes or quantitative trait loci (QTLs). In order to attain a more complete understanding of the genetic causes of individual differences in behavior, the mechanism of action of these QTLs must be elucidated. The most straightforward approach to determining the mechanism of action of a particular QTL is to identify and molecularly clone the gene; this can be done by positional cloning, which depends on precise knowledge of the genetic map position. As the genetic data base for the mouse genome continues to develop, such strategies will become increasingly easy to perform. Here we suggest a multistage strategy for QTL mapping using recombinant-inbred strains of mice: (1) characterize genomic DNA from parental strains originally used to generate the RI strains; (2) characterize the RI strains for a quantitative character and for DNA markers that differ in the parental strains; and (3) assess the quantitative character in F2 mice derived from crosses between the parental strains, then determine the genotypes of extreme F2 mice for markers that account for at least 5% of the additive genetic variance. Data from these F2 crosses can be used to test hypotheses from the analysis of RI strains, i.e., that a QTL maps to a particular region. Using data from the mouse genome data base, this strategy should allow the molecular identification of the gene based on a candidate-gene approach. We illustrate the approach with examples from our work in mapping QTLs specifying neural sensitivity to the anesthetic effects of ethanol.

Alcoholism

The Spatiotemporal Genetic Architecture of Seed Vigor in Upland Cotton.

Seed vigor underpins uniform crop establishment, but its dynamic genetics are understudied. Combining high-resolution temporal phenotyping and genomics in upland cotton, we used the SeedRanger platform to record 17 image-based traits every 30 min over 120 h, revealing stage-specific heritability and identifying 541 seed-vigor loci. These loci show extensive pleiotropy and temporal coordination, forming a genetic network that preserves developmental continuity; 8.9% overlap regions under domestication selection, indicating concurrent optimization with fiber yield. Functional validation of FLA2, a candidate gene underlying a dynamic QTL, implicates auxin-mediated control of radicle elongation and cotyledon development. This temporal framework exposes dynamic genetic architecture and breeding targets for high-vigor crops.

Gossypium

Power of daughter and granddaughter designs for determining linkage between marker loci and quantitative trait loci in dairy cattle.

There is considerable interest in bovine DNA-level polymorphic marker loci as a means of mapping quantitative trait loci (QTL) of economic importance in cattle. Progeny of a sire heterozygous for both a marker locus and a linked QTL, which inherit different alleles for the marker, will have different trait means. Based on this, power to detect QTL, as a function of QTL effect, heritability of the trait, and number of animals tested was determined for 1) daughter design, marker genotype and quantitative trait values assessed on daughters of sires heterozygous for the markers; and 2) granddaughter design, a newly devised alternative design in which marker genotype is determined on sons of heterozygous sires and quantitative trait value measured on daughters of the sons. For equal numbers of assays, power increased with the number of daughters per sire (design 1) and sons per grandsire (design 2). For equal power and heritability less than or equal to .2, design 2 required half as many marker assays as design 1, e.g., with heritability of .2, QTL effect of .2 SD units, and type 1 error of .01, power was .70 if 400 daughters of each of 10 sires were assayed for the markers and .95 if markers were assayed on 100 sons of each of 20 sires with 50 granddaughters per son.

Alleles

Quantitative genetic tools for insecticide resistance risk assessment: estimating the heritability of resistance.

Quantitative genetic studies of resistance can provide estimates of genetic parameters not available with other types of genetic analyses. Three methods are discussed for estimating the amount of additive genetic variation in resistance to individual insecticides and subsequent estimation of the heritability (h2) of resistance. Sibling analysis and offspring-parent regression permit direct estimates of h2 by comparing the resistance phenotypes of individuals of known relatedness. Threshold trait analyses, performed on data from selection experiments, provide estimates of realized heritability. Procedures are outlined for predicting changes in resistance to insecticides based on h2 estimates. Quantitative genetic theory is examined as it relates to resistance and resistance as a quantitative trait; quantitative genetic methods also are unique in providing estimates of genetic correlations between traits. Comments are included on estimates of genetic correlation between resistance and phenotypic traits (e.g., development time) and how they may be used to predict changes in the genetic aspects of phenology that result from insecticide applications (i.e., to predict how the reproductive capacity of future generations will differ from that of the treated generation).

Analysis of Variance

Hybrid dysgenesis-induced quantitative variation on the X chromosome of Drosophila melanogaster.

To determine the ability of the P-M hybrid dysgenesis system of Drosophila melanogaster to generate mutations affecting quantitative traits, X chromosome lines were constructed in which replicates of isogenic M and P strain X chromosomes were exposed to a dysgenic cross, a nondysgenic cross, or a control cross, and recovered in common autosomal backgrounds. Mutational heritabilities of abdominal and sternopleural bristle score were in general exceptionally high-of the same magnitude as heritabilities of these traits in natural populations. P strain chromosomes were eight times more mutable than M strain chromosomes, and dysgenic crosses three times more effective than nondysgenic crosses in inducing polygenic variation. However, mutational heritabilities of the bristle traits were appreciable for P strain chromosomes passed through one nondysgenic cross, and for M strain chromosomes backcrossed for seven generations to inbred P strain females, a result consistent with previous observations on mutations affecting quantitative traits arising from nondysgenic crosses. The new variation resulting from one generation of mutagenesis was caused by a few lines with large effects on bristle score, and all mutations reduced bristle number.

Animals

Detection of differential gene flow from patterns of quantitative variation.

A major goal in anthropological genetics is the assessment of the effects of different microevolutionary forces. Harpending and Ward (1982) developed a model that aids in this effort by comparing observed and expected heterozygosity within populations in a local region. The expected heterozygosity within a population is a function of the total heterozygosity of the entire region and the distance of the population from the regional mean centroid of allele frequencies. Greater than average gene flow from an external source will result in a population having greater heterozygosity than expected. Less than average gene flow from an external source will result in a population having less heterozygosity than expected. We extend the Harpending-Ward model to quantitative traits using an equal and additive effects model of inheritance. Here the additive genetic variance within a population is directly proportional to heterozygosity, and its expectation is directly proportional to the genetic distance from the centroid. Under certain assumptions the expectations for phenotypic variances are similar. Observed and expected genetic or phenotypic variance can then be compared to assess the effects of differential external gene flow. When the additive genetic covariance matrix or heritabilities are not known, the phenotypic covariance matrix can be used to provide a conservative application of the model. In addition, we develop new methods for estimation of the genetic relationship matrix (R) from quantitative traits. We apply these models to two data sets: (1) six principal components derived from twenty dermatoglyphic ridge count measures for nine villages in Nepal and (2) ten anthropometric measurements for seven isolated populations in western Ireland. In both cases both the univariate and multivariate analyses provide results that can be directly interpreted in terms of historically known patterns of gene flow.

Anthropology, Physical

Analysis of family resemblance. IV. Operational characteristics of segregation analysis.

In simulated data, segregation analysis of quantitative traits was found to be powerful for resolving a major locus from polygenic and cultural inheritance. It is reasonably robust against a variety of deviations from the model if and only if a major locus, polygenic heritability, and environment common to sibs are simultaneously included in the model, and heterogeneity tests among mating types are performed. Most of the information in quantitative data about a major locus is lost when reduced to affection status.

Environment

CYClones: a highly powered, fully genotyped, eight-parent yeast mapping population.

The budding yeast Saccharomyces cerevisiae is a remarkably adaptable organism that thrives in diverse environments. Global sequencing of natural isolates has revealed extensive genetic diversity within the species. Here, we describe the construction and characterization of CYClones (Collaborative Yeast Cross clones), a library of 11,392 segregants generated from a multiparent funnel cross of eight genetically diverse parental strains. To enable the genetic dissection of complex traits, we imputed whole-genome sequences for all segregants and show that CYClones captures a substantial fraction of the global genetic diversity of S. cerevisiae. Haplotype representation is well maintained, with each parental haplotype present at >5% frequency across >95% of the genome. Simulations demonstrate that CYClones has ≥95% power to detect variants with heritability as low as 0.36%, with mapping resolution often finer than the length of a single gene. In summary, CYClones is a powerful community resource for dissecting the genetic architecture of complex and quantitative traits, uncovering context-dependent mutational effects, and identifying causal variants underlying phenotypic diversity.

Saccharomyces cerevisiae

Genetics and intelligence differences: five special findings.

Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for 'positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century-Genome-wide Complex Trait Analysis (GCTA)-which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the 'missing heritability' gap.

Genetic Predisposition to Disease

The Interplay Between Sleep and Mental Health: A Genetic Perspective.

Although many facets of sleep, including subjective, behavioral, and neurophysiological features, are closely linked with psychiatric disorders, the natures of these relationships are generally unclear. A given alteration in sleep could reflect a cause (that may mediate genetic risk), consequence, symptom, trigger, epiphenomenon due to shared determinants, or some combination of these. In principle, genetic approaches can be informative: 1) by identifying specific genetic influences on disease mediated by or shared with sleep, which could help the search for biological mechanisms and therapeutic targets, and 2) by providing evidence for causality, which could suggest interventions for modifiable sleep traits. Here, we summarize recent human quantitative and molecular genetic studies on sleep and psychiatric disease, including twin and genome-wide association studies. Despite evidence for shared heritability across many domains, notably depression and insomnia, the field is in its early stages and faces significant challenges including the following: 1) putative causal effects are small, phenotypically nonspecific, not resolved to specific gene pathways, and often bidirectional; 2) most current discovery cohorts are demographically biased and do not capture profound age-related changes in sleep and its genetic architecture; 3) group-level analyses ignore patient-to-patient heterogeneity, including the presence or absence of specific sleep alterations; and 4) a paucity of objective, brain-based data in genetically informative samples hampers making connections with sleep neurophysiology. Nonetheless, as ever-growing genetic tools and resources still hold great potential for translational bridges between basic model systems, human epidemiology, and personalized clinical care, genetic approaches will still likely be needed to reveal sleep's roles in maintaining mental health.

Humans