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PubMed2026

Research on multi-trait genome association study method based on Shannon information entropy.

BACKGROUND: Genetic analysis of complex traits is crucial for elucidating disease mechanisms and biological inheritance processes. However, traditional Genome-wide Association Study (GWAS) for single trait often fail to capture the synergistic effects of genetic loci on multiple traits. METHODS: This study proposes a method for analyzing the association between multiple traits and gene regions based on Shannon information entropy. Innovatively, Shannon information entropy is introduced to integrate gene region information as genetic entropy, thereby constructing an Inverse Shannon Entropy-Multi-Trait Association Analysis of Gene Region genetic model (InvSE-MTAGR). Furthermore, a partial regression test is applied to the model to establish the Inverse Partial Shannon Entropy-Multi-Trait Association Analysis of Gene Region method (InvPSE-MTAGR). When performing multi-trait analysis with InvSE-MTAGR, the method achieved statistical significance by accumulating minor effects, thereby enhancing the ability to identify pleiotropic gene regions. RESULTS: The simulation results showed that the proposed multi-trait gene region association analysis method performed well in terms of both Type I error rate control and statistical power. Leveraging tomato and sorghum datasets for validation, the proposed multi-trait gene region association analysis method based on Shannon information entropy accurately pinpointed most of the gene regions harboring candidate genes. CONCLUSION: The study reveals the advantage of multi-trait method in integrating weak-effect pleiotropic signals and capturing the correlation among traits, which provides an efficient theoretical tool for dynamic analysis of complex multi-trait genetic networks and multi-target collaborative breeding of crops.

Genome-Wide Association Study↗

PubMed2000

Relatedness in trait group models of social evolution.

Genetic relatedness is a central concept in the study of social evolution. Though originally defined in terms of genealogy, the modern version of relatedness accommodates genetic similarity of any origin. This paper examines relatedness in group structured modes, in which a trait affects the fitness of all group members. Such traits can be divided into two types, based on whether their group fitness effects encompass all group members including the actor ("whole-group traits"), or only group members other than the actor ("other-only traits"). Both trait types are common in nature as well as in theoretical models, but they have rarely been distinguished clearly. The average relatedness of recipients to actors differs for the two trait types within the same population and even the same individual, leading to different selection pressures and evolutionary outcomes. Total relatedness in group-structured models can be partitioned into two components: structural relatedness due to the size and number of groups in the population, and assortative relatedness due to the distribution of genotypes among groups. Each component differs for whole-group vs. other-only traits, both in terms of their values and the factors that influence them. Some key differences include: positive relatedness requires positive assortment for other-only but not for whole-group traits; negative relatedness is possible for other-only but not whole-group traits; relatedness depends on average group size for whole-group but not other-only traits, and non-random assortment into groups affects relatedness more strongly for other-only than whole-group traits. Recognizing the distinction between these trait types resolves some apparent contradictions in the literature, and clarifies the limits of some previous results.

Animals↗

PubMed1999

Genetic architecture of fitness and nonfitness traits: empirical patterns and development of ideas.

Comparative studies of the genetic architecture of different types of traits were initially prompted by the expectation that traits under strong directional selection (fitness traits) should have lower levels of genetic variability than those mainly under weak stabilizing selection (nonfitness traits). Hence, early comparative studies revealing lower heritabilities of fitness than nonfitness traits were first framed in terms of giving empirical support for this prediction, but subsequent treatments have effectively reversed this view. Fitness traits seem to have higher levels of additive genetic variance than nonfitness traits - an observation that has been explained in terms of the larger number loci influencing fitness as compared to nonfitness traits. This hypothesis about the larger functional architecture of fitness than nonfitness traits is supported by their higher mutational variability, which is hard to reconcile without evoking capture of mutational variability over many loci. The lower heritabilities of fitness than nonfitness traits, despite the higher additive genetic variance of the former, occur because of their higher residual variances. Recent comparative studies of dominance contributions for different types of traits, together with theoretical predictions and a large body of indirect evidence, suggest an important role of dominance variance in determining levels of residual variance for fitness-traits. The role of epistasis should not be discounted either, since a large number of loci increases the potential for epistatic interactions, and epistasis is strongly implicated in hybrid breakdown.

Animals↗

PubMed2000

Quantitative genetics of life-history traits in a long-lived wild mammal.

Quantitative genetic studies of life-history traits in wild populations are very rare, yet variance/covariance estimates of these traits are crucial to understanding the evolution of reproductive strategies. We estimated heritabilities (h2) of several life-history traits (longevity, age and mass at primiparity, and reproductive traits) in two bighorn sheep (Ovis canadensis) populations, and both phenotypic (rP) and genetic (rA) correlations between life-history traits in one population. We included adult mass in our analyses because it is related to several life-history traits. We used the mother-daughter regression method and resampling tests based on data from long-term monitoring of marked females. Contrary to the theoretical prediction of low heritability for fitness-related traits, heritability estimates in the Ram Mountain population ranged from 0.02 to 0.81 (mean of 0.52), and several were different from zero. Coefficients of variation tend to support the hypothesis of a higher environmental influence on life-history traits. In contrast, at Sheep River we found low heritabilities of life-history traits. Phenotypic correlations varied between -0.09 and 0.95. Several genetic correlations were strong, particularly for different reproductive traits that are functionally related, and ranged from -0.34 to 1.71. Overall, genetic and phenotypic correlations between the same variables were similar in magnitude and direction. We found no phenotypic or genetic correlations suggesting trade-offs among life-history traits. Bighorn sheep may not form the large, outbred populations at equilibrium that are assumed by both Fisher's fundamental theorem and by theories predicting antagonistic pleiotropy between life-history traits. Alternatively, the absence of negative genetic correlations may result from genetic variation in ability to acquire resources or from novel environmental conditions existing during the study period.

Animals↗

PubMed2006

SUP: an extension to SLINK to allow a larger number of marker loci to be simulated in pedigrees conditional on trait values.

BACKGROUND: With the recent advances in high-throughput genotyping technologies that allow for large-scale association mapping of human complex traits, promising statistical designs and methods have been emerging. Efficient simulation software are key elements for the evaluation of the properties of new statistical tests. SLINK is a flexible simulation tool that has been widely used to generate the segregation and recombination processes of markers linked to, and possibly associated with, a trait locus, conditional on trait values in arbitrary pedigrees. In practice, its most serious limitation is the small number of loci that can be simulated, since the complexity of the algorithm scales exponentially with this number. RESULTS: I describe the implementation of a two-step algorithm to be used in conjunction with SLINK to enable the simulation of a large number of marker loci linked to a trait locus and conditional on trait values in families, with the possibility for the loci to be in linkage disequilibrium. SLINK is used in the first step to simulate genotypes at the trait locus conditional on the observed trait values, and also to generate an indicator of the descent path of the simulated alleles. In the second step, marker alleles or haplotypes are generated in the founders, conditional on the trait locus genotypes simulated in the first step. Then the recombination process between the marker loci takes place conditionally on the descent path and on the trait locus genotypes. This two-step implementation is often computationally faster than other software that are designed to generate marker data linked to, and possibly associated with, a trait locus. CONCLUSION: Because the proposed method uses SLINK to simulate the segregation process, it benefits from its flexibility: the trait may be qualitative with the possibility of defining different liability classes (which allows for the simulation of gene-environment interactions or even the simulation of multi-locus effects between unlinked susceptibility regions) or it may be quantitative and normally distributed. In particular, this implementation is the only one available that can generate a large number of marker loci conditional on the set of observed quantitative trait values in pedigrees.

Algorithms↗

PubMed1998

Phenotypic and genetic structure of traits delineating personality disorder.

BACKGROUND: The evidence suggests that personality traits are hierarchically organized with more specific or lower-order traits combining to form more generalized higher-order traits. Agreement exists across studies regarding the lower-order traits that delineate personality disorder but not the higher-order traits. This study seeks to identify the higher-order structure of personality disorder by examining the phenotypic and genetic structures underlying lower-order traits. METHODS: Eighteen lower-order traits were assessed using the Dimensional Assessment of Personality Disorder-Basic Questionnaire in samples of 656 personality disordered patients, 939 general population subjects, and a volunteer sample of 686 twin pairs. RESULTS: Principal components analysis yielded 4 components, labeled Emotional Dysregulation, Dissocial Behavior, Inhibitedness, and Compulsivity, that were similar across the 3 samples. Multivariate genetic analyses also yielded 4 genetic and environmental factors that were remarkably similar to the phenotypic factors. Analysis of the residual heritability of the lower-order traits when the effects of the higher-order factors were removed revealed a substantial residual heritable component for 12 of the 18 traits. CONCLUSIONS: The results support the following conclusions. First, the stable structure of traits across clinical and nonclinical samples is consistent with dimensional representations of personality disorders. Second, the higher-order traits of personality disorder strongly resemble dimensions of normal personality. This implies that a dimensional classification should be compatible with normative personality. Third, the residual heritability of the lower-order traits suggests that the personality phenotypes are based on a large number of specific genetic components.

Adolescent↗

PubMed2026

Genomic selection in timothy (Phleum pratense L.): a comprehensive evaluation of prediction models, multi-trait strategies, and forward validation across Norwegian environments.

This study presents a comprehensive evaluation of genomic selection (GS) in timothy (Phleum pratense L.), comparing nine prediction models across yield and quality traits at two Norwegian locations. Forward validation with independent full-sib (FS2) families revealed a substantial generalization gap, highlighting the need for realistic accuracy assessment in polyploid forage breeding. Timothy (Phleum pratense L.) is the most important forage grass in Northern Europe, yet genomic selection has not been systematically evaluated in this hexaploid species. We assessed 889 FS2-families originating from biparental crosses among 49 cultivars/populations. The FS2-families were genotyped with 30,698 SNP markers derived from genotyping-by-sequencing (GBS) and field tested for three harvest years at a highland and a lowland continental location in Southern Norway. Nine genomic prediction models were compared for six yield traits (dry matter yield per cut and total) and six quality traits (protein, digestibility, and fiber fractions) across three cuts/year. Within-training cross-validation accuracies were moderate to high (mean r = 0.62), with Random Forest and SVR consistently outperforming GBLUP. However, forward validation using 213 independent FS2-families revealed dramatically lower accuracies (mean r = 0.16), with only 16 of 30 trait-dataset combinations reaching statistical significance (p < 0.05). Genomic heritabilities (GREML), estimated across environments, ranged from near zero for the quality traits to 0.55 for the yield traits. Multi-trait models improved accuracy by 3-5% over single-trait approaches, while FS2 families-by-environment interaction models with Random Forest achieved the highest within-training accuracy (mean r = 0.71). Marker density analysis showed accuracy plateauing at approximately 15000 SNPs. Genetic correlations among the yield component traits were estimated by multi-trait REML; correlations among the quality traits could not be estimated reliably because their genomic heritabilities were low. A multi-trait selection index identified top-performing FS2-families for further crossing recommendations. These results provide a benchmark for GS implementation in hexaploid timothy and emphasize that cross-validation substantially overestimates prediction accuracy for truly independent material.

Norway↗

PubMed2001

Neuropsychological performance and spectrum personality traits in the relatives of patients with schizophrenia and affective psychosis.

Neuropsychological deficits are found in both schizophrenic patients and their relatives, and some studies have shown similar, but less severe, deficits in affective psychotic patients and their relatives. We set out to establish: (a) whether schizophrenia spectrum personality traits are more common in the relatives of schizophrenic patients than, in the relatives of affective psychotic patients; and (b) what the relation is between spectrum personality traits and neuropsychological deficits in these relatives. Relatives were interviewed using the International Personality Disorder Examination (IPDE), and also completed the National Adult Reading Test (NART), the Trail Making Test (TMT; Parts A and B) and Thurstone's Verbal Fluency Test (TVFT). Spectrum personality traits were equally common in 129 relatives of schizophrenic patients and 106 relatives of affective psychotic patients, but the performance of the former group was inferior to that of the latter on the NART and the TVFT. Relatives with high paranoid traits had lower NART scores than relatives without such personality traits; similarly, those with high schizoid traits took longer to complete the TMT, part B, than those without such traits; and relatives with high schizotypal traits generated significantly fewer words on the TVFT than those without such traits. We conclude that relatives of schizophrenic and affective psychotic patients share a propensity to schizophrenia spectrum traits, but relatives of the former have poorer neuropsychological performance. Furthermore, there exists an association between neuropsychological deficits and spectrum traits in both groups of relatives; in particular those with high paranoid traits have lower IQ scores than their less paranoid counterparts.

Adult↗

PubMedDate not supplied

A survey and evaluation of human genetic traits used in classroom laboratory studies.

Twenty-six selected introductory biology and genetics laboratory manuals were examined and were found to include 57 human "inherited" traits as examples for classroom study. Forty-three of these 57 traits are included in McKusick's catalog of human inherited characteristics, Mendelian Inheritance in Man. Of these 43 traits, 26 are annotated with an asterisk, indicating that their modes of inheritance are well documented, while 17 traits are not so annotated, suggesting uncertain mechanisms of inheritance. Fourteen of the 57 traits are not found in McKusick's catalog, implying that they may not be inherited traits at all or that their modes of inheritance may be polygenic. Current literature also suggest that certain traits included in the McKusick catalog may, in fact, not have a genetic basis. Notable examples of such questionable traits are handedness, hand clasping, and tongue rolling. Clearly, a need exists for reliable morphological and easily detected biochemical human genetic traits for use in classroom instruction. Authors preparing instructional manuals for introductory biology and genetics laboratory studies should carefully select the traits with which they illustrate human inheritance. A first requisite for selection of such characteristics must be conclusive evidence that the trait does, indeed, have an established genetic basis. Additional criteria for selection of such traits are also discussed.

Bibliographies as Topic↗

PubMed2003

Genetic correlations between lean growth and litter traits in U.S. Yorkshire, Duroc, Hampshire, and Landrace pigs.

The objective of this study was to estimate breed-specific genetic correlations between lean growth and litter traits for four U.S. swine breeds. Records for lean growth and litter traits on Yorkshire, Duroc, Hampshire, and Landrace pigs collected between 1990 and April 2000 in herds on the National Swine Registry Swine Testing and Genetic Evaluation System were analyzed. A bivariate animal model and restricted maximum likelihood procedures were used to estimate genetic and environmental correlations between lean growth rate, days to 113.5 kg, backfat, and loin muscle area with litter traits of number born alive, litter weight at 21 d, and number weaned. Most genetic correlation estimates between lean growth and litter traits were small in magnitude and consistent across breeds. Backfat had the largest within-breed genetic correlations with number born alive (0.18 to 0.20) and litter weight at 21 d (-0.27 to -0.30). Estimates of genetic correlations between lean growth traits and number weaned were very small. Estimates of the environmental correlations between lean growth and litter traits also were very small for all traits and for all four breeds. Results indicate that selection for lean growth traits could have a long-term effect on litter traits. Including lean growth traits in a maternal-line evaluation using a multiple-trait model could increase the accuracy of the genetic evaluation for litter traits.

Adipose Tissue↗

PubMed2005

Breeding for societally important traits in pigs.

Pig breeding programs traditionally focus on the genetic improvement of production and reproduction traits that have a clear economic value. Because citizens and consumers increasingly attach value to traits that have little or no direct relationship to production costs or to the price of a product, pig breeding organizations want to pay more attention to societally important traits, such as the welfare and health of pigs, the ecological effects of pork production, and the healthiness and sensory quality of pork. Most societally important traits have an economic and a noneconomic value and are sufficiently heritable for effective genetic selection, although many genetic and phenotypic (co)-variances still have to be estimated. However, it often is not clear to a pig breeding organization how it may deal with the noneconomic value of breeding-goal traits. In this study, a retrospective selection-index method is proposed to obtain the proper weights for societally important traits in the breeding goal. First, the genetic-progress space for each breeding-goal trait is explored by increasing the weights, in a stepwise manner, to each societally important trait in the breeding goal, starting from zero. Subsequently, a pig breeding organization can adopt the resulting genetic-progress scenario that it considers most sustainable or most acceptable. The weights underlying the adopted scenario are considered to be the proper breeding-goal weights. The noneconomic value of each societally important breeding-goal trait is found by deducting its economic value from its obtained weight and is thereby expressed in monetary units. In addition to obtaining weights for societally important breeding-goal traits, the proposed method offers the possibility to estimate the societal costs of selecting for economic traits only, as well as the societal benefits and the economic costs of selecting for traits with a noneconomic value. The method is therefore a useful tool for the development of sustainable breeding goals. An example has been worked out for a sow-line breeding program.

Animal Husbandry↗

PubMed2006

Effect of carcass price fluctuations on genetic and economic evaluation of carcass traits in Japanese Black cattle.

The objectives of this study were 1) to investigate the effect of changes in carcass market prices due to bovine spongiform encephalopathy (BSE) occurrences on estimates of genetic parameters and economic weights for carcass traits; and 2) to compare direct and indirect approaches for prediction of genetic merit of Japanese Black cattle for profitability of their progeny. The direct approach utilized estimated breeding values of carcass prices, whereas in the indirect approach, selection indices were constructed as products of economic weights and breeding values of component traits. Data were composed of 80,191 carcass records divided into 5 periods based on changes in carcass prices as a result of occurrences of BSE in Japan and the United States. The periods ranged from a period before occurrence of BSE in Japan to a period of beef import restrictions and a rise in prices. Carcass traits analyzed included HCW, LM area, rib thickness, subcutaneous fat thickness, and marbling score (MS). Price traits included carcass unit price and carcass sale price. Estimates of heritability for price traits were moderate (0.32 to 0.46) and slightly sensitive to changes in carcass market prices. Genetic correlations of HCW and LM area with price traits increased and that between MS and carcass sale price decreased with period, whereas estimates of genetic correlation between MS and carcass unit price were high in all periods (0.96 to 0.98). Economic weights for carcass traits varied with periods because carcass prices were highly sensitive to economic importance of traits. Nevertheless, correlations between within-period breeding values for price traits estimated using direct and indirect approaches were high (0.92 to 0.99). This result indicates that selection realized by direct and indirect approaches will provide very similar results. A comparison among within-approach breeding values estimated in different periods showed that the largest differences in breeding values of sires for price traits were between the periods after occurrences of BSE in Japan and in the United States. Economic effects of BSE occurrences influenced the importance of carcass traits and economic merits of price traits through a change of carcass prices from period to period, irrespective of the approach taken in determining the genetic merit of breeding animals for profitability of their progeny.

Animals↗

PubMed2002

Evaluation of classifiers that score linear type traits and body condition score using common sires.

Subjective visual assessment of animals by classifiers is undertaken for several different traits in farm livestock, e.g., linear type traits, body condition score, or carcass conformation. One of the difficulties in assessment is the effect of an individual classifier. To ensure that classifiers rank animals consistently, i.e., the repeatability between classifiers and within classifier, genetic links across routinely scored observations may be used to validate scoring of individual classifiers. Eighteen classifiers of NRS scored 18 traits, and body condition for 91,589 first-lactation heifers, daughters of 601 sires. Genetic parameters were estimated in a series of bivariate analyses. In turn, observations of each individual classifier were trait 1 and all observations of all other classifiers were grouped as trait 2. Likelihoods were used to test whether additive genetic or residual variances for each classifier (trait 1) differed significantly from the grouped records (trait 2), and to test whether the genetic correlation between trait 1 and trait 2 was significantly smaller than unity. Arbitrary criteria were set to mark traits for individual classifiers when a significant deviation was found: genetic correlations of < or = 0.40, and more than 15% deviation for the standard deviation. One classifier had relatively low heritabilities, but high genetic correlations with the others. This might indicate that the repeatability within classifier should be improved. Another classifier had high genetic correlations with the others, but his sire variances were significantly higher than average for most traits. For the genetic correlations, each classifier averaged 3.3 traits marked, ranging from 0 to 9. Overall feet and legs, rump width, central ligament, and foot angle received most marks (12 to 6 classifiers), but no disagreement existed on the definition (i.e., no mark) for body condition score, stature, rump angle, teat length, overall udder, and teat placement. These simple and cheap marks can be used in training sessions to improve the quality of the scoring system.

Animals↗

PubMed2004

Genetic correlations among production, body size, udder, and productive life traits over time in Holsteins.

Genetic correlations among milk, fat, and protein yields; body size composite (BSC); udder composite (UDC); and productive life (PL) in Holsteins were investigated over time. The data set contained 25,280 records of cows born in Wisconsin between 1979 and 1993. The multiple trait random regression (MT-RR) animal model included registration status, herd-year, age group, and stage of lactation as fixed effects; additive genetic effects with random regressions (RR) on year of birth using the first-order Legendre polynomial; and residual effects. Heterogeneous residual variances were considered in the model. Estimates of variance components and genetic correlations among traits from MT-RR were compared with those estimated with a multiple trait interval (MT-I) model, which assumed that every 3-yr interval was a separate trait and included the same effects as in the MT-RR model except for the RR. Genetic correlations estimated with MT-RR and MT-I models over time among all traits were compared with correlations among breeding values predicted with the single trait (ST) model without RR. Correlations among breeding values predicted with MT-RR, ST, and MT models were also calculated. Additive genetic and residual variances for all traits except PL increased over time; those for PL were constant. As a result, heritability estimates had no significant changes during the 15 yr. Genetic correlations of PL with milk, fat, protein, and BSC declined to zero or negative; those with UDC remained positive. Correlations among breeding values predicted with ST, MT, and MT-RR models were relatively high for all traits except PL. Genetic correlations between PL and other traits varied over time, with some correlations changing sign. For accurate indirect prediction of PL from other traits, the genetic correlations among the traits need to be re-estimated periodically.

Animals↗

PubMed2006

[Construction of chromosome segment substitution lines carrying overlapping chromosome segments of the whole wild rice genome and identification of quantitative trait loci for rice quality].

Rice is one of the major staple cereal grains. Most of the important traits of crops are complex traits controlled by quantitative trait loci (QTL). Detection and genetic identification of QTLs can provide insights into molecular and biological mechanisms of development and physiology. Chromosome segment substitution lines (CSSLs) have been proposed as a simple and powerful way to identify QTLs. The demand for rice grain quality becomes increasingly important. The primary components of rice grain quality include appearance, milling and physico-chemical, cooking and eating quality. Most of these traits are complex and controlled by QTLs, so genetic characterization of these traits is more difficult than that of traits each controlled by a singular gene such as Waxy, which controls glutinousness of rice grain. We constructed 133 chromosome segment substitution lines (CSSLs) from backcross progenies (BC3F2) derived from a cross between Teqing (an O. sativa L. ssp. indica variety) as the recurrent parent and wild rice (O. rufipogon Griff.) as the donor parent. In this process, we carried out marker-assisted selection (MAS) by using 118 CAPS or SSR markers covering the whole rice genome (Figs.1, 2). Because phenotypic values of quality trait were significantly different between cultivar Teqing and wild rice, the CSSLs were used to identify QTLs for rice quality traits. Three appearance quality traits (head rice percentage, HRP; percentage of chalky rice grains, PCRG; transparency, TP) and five physico-chemical properties (gelatinization temperature, GT; gel consistency, GC; amylose content, AC; protein content, PC; fat content, FC) were scored using 133 CSSLs which substituted segments covering the whole genome of wild rice. A total of 15 QTLs for five of the eight traits mentioned above (HRP, PCRG, TP, PC and FC) were identified on nine chromosomes, and several QTLs affecting different quality traits were mapped in the same regions (Fig.3, Table 1).

Chromosomes, Plant↗

PubMed1999

Cross-sectional study on the relationship between smoking or smoking cessation and trait anxiety.

OBJECTIVE: The relationships between trait anxiety, or anxiety proneness, and smoking and between trait anxiety and smoking cessation, among an adult population were investigated. METHODS: The subjects were 2,669 male Japanese personnel working for a Japanese government agency. Participants completed a self-administered questionnaire on smoking and smoking cessation status and other habits. Trait anxiety was evaluated with the trait anxiety part of the standardized Japanese version of the Spielberger State-Trait Anxiety Inventory. Trait anxiety is regarded as the long-term, more endogenous general type of anxiety. Odds ratios of the single 2 x 2 table were calculated and a logistic regression analysis was used to adjust for age. RESULTS: After adjusting for age, high trait anxiety did not increase the risk of smoking and was not related to success in abstaining from smoking. More subjects with high trait anxiety had planned to stop smoking (adjusted odds ratio: 1.39, P = 0.01) but did not actually succeed in doing so. CONCLUSION: The present study did not support the hypothesis that high trait anxiety increased the risk of having a smoking habit and that high trait anxiety increased the chance of abstaining from smoking. However, the study did show that high trait anxiety was related to the planning of smoking cessation, but not to actually giving up the smoking habit.

Adult↗

PubMed2026

Genome-wide association study of body weight and body size traits in Langya hens.

Langya chicken is a Chinese indigenous chicken breed with high genetic diversity. To systematically analyse the genetic basis of body size traits, eight traits (including BW, comb shape, and body size) of 2 952 Langya hens were measured at 130 days of age and at first egg of age. A total of 9 708 856 high-quality single-nucleotide polymorphisms (SNPs) were obtained through whole-genome resequencing and used for subsequent genetic parameter estimation and genome-wide association study (GWAS). The results of genetic parameter analysis revealed significant differences in the SNP heritability of different body size traits, with an overall range of 0.13-0.64. In particular, BW, comb length, comb height, and tibia length exhibited moderate-to-high heritability (0.34-0.64) during both developmental stages. GWAS revealed significantly associated SNP loci distributed across multiple chromosomal regions, indicating that body size traits have a complex multilocus genetic regulatory structure and that some chromosomal regions recur for different body size traits and during different developmental stages, showing potential pleiotropic effects or shared genomic regions. Notably, multiple stable body size trait-associated regions were identified on Gallus gallus autosome (GGA) 1, 4, and 27, including genomic regions on GGA1 (167.56-178.18 Mb), GGA4 (68.24-81.17 Mb), and GGA27 (5.22-6.73 Mb), in which significantly associated signals were repeatedly detected for multiple body size traits, such as BW and tibia length. The significant SNPs in the above regions were characterised by strong linkage disequilibrium and were associated with multiple body size traits, indicating that these SNPs may serve as important genetic hotspots for the regulation of chicken body shape and structure. Candidate genes annotated in these core regions include NCAPG, KPNA3, LDB2, PPARGC1A, FNDC3A, SOST, RB1, STON2, and TARP; the functions of these genes are involved mainly in the regulation of cell proliferation, energy metabolism, bone development, and tissue growth. NCAPG was consistently associated with multiple traits at both developmental stages. Functional enrichment analysis further revealed that these candidate genes were significantly enriched in the phosphatidylinositol, GnRH, energy metabolism, skeletal development and protein biosynthesis signalling pathways. The genetic characteristics of Langya chicken body size traits during the growth stage at the genome-wide level and the underlying molecular mechanisms were systematically revealed in this study. The findings provide important candidate gene resources and a theoretical basis for the screening of molecular markers for body size traits and the genomic breeding of regional chicken breeds.

Candidate genes↗

PubMedDate not supplied

Young children's beliefs about the stability of traits: protective optimism?

Prior research has demonstrated individual differences in children's beliefs about the stability of traits, but this focus on individuals may have masked important developmental differences. In a series of four studies, younger children (5-6 years old, Ns = 53, 32, 16, and 16, respectively) were more optimistic in their beliefs about traits than were older children (7-10 years old, Ns = 60, 32, 16, and 16, respectively) and adults (Ns = 130, 100, 48, and 48, respectively). Younger children were more likely to believe that negative traits would change in an extreme positive direction over time (Study 1) and that they could control the expression of a trait (Study 3). This was true not only for psychological traits, but also for biological traits such as missing a finger and having poor eyesight. Young children also optimistically believed that extreme positive traits would be retained over development (Study 2). Study 4 extended these findings to groups, and showed that young children believed that a majority of people can have above average future outcomes. All age groups made clear distinctions between the malleability of biological and psychological traits, believing negative biological traits to be less malleable than negative psychological traits and less subject to a person's control. Hybrid traits (such as intelligence and body weight) fell midway between these two with respect to malleability. The sources of young children's optimism and implications of this optimism for age differences in the incidence of depression are discussed.

Affect↗