Pairs Of Traits Research Articles

Wall laminar nanofluid jet flow and heat transfer

PurposeThis work aims to investigates exact solutions of the classical Glauert’s laminar wall jet mass and heat transfer under wall suction, wall contraction or dilation, and two thermal transport boundary conditions; prescribed constant surface temperature and prescribed constant surface flux in nanofluidic environment.Design/methodology/approachThe flow system arranged in terms of partial dif- ferential equations is non-dimensionalized with suitable dimensionless transformation variables, and this new set of equations is reduced into ordinary differential equations via a set of similarity transformations, where they are treated analytically for closed form solutions.FindingsExact solutions of nanofluid flow for velocity distributions, momentum flux, wall shear stress and heat transfer boundary layers for commonly studied nanoparticles; namely copper, alumina, silver, and titanium oxide are presented. The flow behavior of alumina and titanium oxide is identical, and a similar behavior is seen for copper and silver, making two pairs of identical traits. The mathematical expressions as well as visual analysis of wall shear drag and temperature gradient which are of practical interest are analyzed. It is shown that wall stretching or shrinking, wall transpiration and velocity slip together influences the jet flow mechanism and extends the original Glauert’s jet solutions. The exact solutions for the two temperature boundary layer conditions and temperature gradients are analyzed analytically. It is found that the effect of nanopar- ticles concentration on thermal boundary layer is intense, causing temperature uplift, whereas the wall transpiration causes a decrease in thermal layers.Originality/valueThe analysis carried out in nanofluid environment is genuinely new and unique, as our work generalizes the Glauert’s classical regular wall jet fluid problem.

Pleiotropic architectures of porcine immune and growth trait pairs revealed by a self-product-based transcriptome method.

Pleiotropy is an important biological phenomenon with complicated genetic architectures for multiple traits. To date, pleiotropy has been mainly identified by multi-trait genome-wide association studies, but this method has its disadvantages, and new developments for pleiotropy detection methods are needed. Here we define a novel metric, self-product, to measure individual-level co-variation of two traits, and develop a novel self-product-based transcriptome method to detect pleiotropic genes (PGs). Our method was tested using four immune-growth trait pairs and four immune-immune trait pairs in pigs. Comparative transcriptome analyses identified hundreds of candidate PGs related to eight trait pairs from two tails of self-product distribution. Gene Ontology enrichment analysis indicated that most of identified PGs were involved in immune- or growth-related biological processes. We established PG interaction networks to exhibit core genes shared by eight trait pairs, of which CCL5 and IL-10 genes were the hub genes. Genetic association analyses showed that SmaI-polymorphisms of CCL5 and IL-10 genes had significant associations with phenotypic co-variations of multiple trait pairs, indicating that the variants in pleiotropic genes were also pleiotropic variants. Taken together, the validity of our proposed method was preliminarily verified, and our findings provide new insights into the genetic basis of pleiotropic architectures of immune and growth trait pairs in pigs.

Integrating genetic correlation, polygenic risk scores, and Mendelian randomization to identify modifiable risk factors for Alzheimer’s disease

AbstractBackgroundTo reduce the population prevalence of Alzheimer’s disease (AD), it is critical to identify risk factors that modify AD risk. Methods of causal inference that exploit genomic information, such as genetic correlation (rg), polygenic risk scores (PRS) and Mendelian randomization (MR), can overcome some of the limitations of observational studies such as confounding and reverse causation. Here we use rg, PRS, and MR to investigate causal associations between twenty‐two risk factors and eleven AD outcomes.MethodsUsing GWAS summary statistics, rg was estimated using GNOVA and bidirectional MR causal estimates using LHC‐MR. The exposures included alcohol intake, physical activity, lipid traits, blood pressure traits, diabetes, BMI, depression, insomnia, social isolation, smoking, diet, and education. The outcomes included AD, AD age of onset, hippocampal volume, CSF Aβ42, tau, and Ptau181 levels, and amyloid, tau, cerebrovascular neuropathology. PRS for the exposures were constructed using PRSice in ADGC (n = 25,431), ADNI (nmax = 1,718), and ROSMAP (nmax = 1,675), and their association with AD diagnosis, CSF biomarkers, PET imaging, MRI imaging, and neuropathology was evaluated.ResultsAfter accounting for multiple testing, 71, 1, and 38 trait pairs were significant in the rg, PRS, MR models respectively. The only significant trait pair identified across all three methods was a protective effect of higher educational attainment on AD (rg = ‐0.161, p = 3.78e‐14; bPRS [se] = ‐0.07 [0.014], p = 8.88e‐7; bMR [se] = ‐0.21 [0.042], p = 2.43e‐7). Seventeen trait pairs had both significant genetic correlations and causal MR estimates. In particular, increased cortical surface area was positively correlated with higher educational attainment (rg = 0.261, p = 1.46e‐18), with MR indicating that genetically predicted cortical surface area was causally associated with higher education (bMR [se] = 0.27 [0.042], p = 3.21e‐10), but not vice versa (bMR [se] = ‐0.09 [0.072], p = 0.224).ConclusionsWe evaluated causal relationships between risk factors and AD endophenotypes using genomic information. The protective effect of education on AD is supported by genetic correlation, PRS and MR, potentially due to increased cognitive resilience resulting from increased cortical surface area.

Interactions between protea plants and their animal mutualists and antagonists are structured more by energetic than morphological trait matching

Abstract Traits mediate mutualistic and antagonistic interactions between plants and animals, and should thus be useful for predicting trophic species interactions. Studies to date have examined the importance of morphological trait matching for plant–animal interactions, but have rarely explored the extent to which these interactions are shaped by matching between energetic provisions of plants and energetic demands of animals. We tested whether energetic and/or morphological trait matching shapes interactions between Protea plant species and their interacting animal mutualists and antagonists in the Cape Floristic Region, South Africa. We recorded interactions between 22 Protea species, pollinating insects and vertebrates as well as seed predators (endophagous insect larvae in protea cones) at 21 study sites. To relate species interactions to matching trait pairs, we measured key morphological traits (shape and size of flower heads and seed cones, and mouth part length as well as body length) and quantified the animals' energetic demands (metabolic rate) together with the plants' energetic provisions (nectar sugar amount, seed‐to‐cone mass ratio). We calculated log ratios of both energetic and morphological traits between animals and plants as predictor variables for the number of observed interactions between Protea species and their animal interaction partners. For both mutualistic and antagonistic interactions, we found significant effects of morphological and energetic trait ratios on the interactions between plants and animals. Trait ratios accounted for 11% to 22% of variation in species interactions. Consistent with energetic trait matching, we found a hump‐shaped relationship between interaction frequency and log ratios of energetic traits of animals and plants, indicating that interactions were most frequent at intermediate log ratios between energetic demand and provision. Effects of morphological trait ratios on interactions were statistically supported in most cases, but were variable in the magnitude and shape of the predicted relationships. Across animal taxa and interaction types, energetic traits had more consistent effects on interactions between plants and animals than morphological traits. This suggests that energy can function as an important interaction currency and facilitate the understanding and prediction of trophic species interactions. Read the free Plain Language Summary for this article on the Journal blog.

The Effect of Acaricide Control of the Two-Spotted Spider Mite Tetranychus urticae Koch on the Cultivation of Sugar Beet (Beta vulgaris L.) and on the Size and Quality of the Yield

Field experiments (in the 2019–2021) were carried out at the Department of Field Experimentation of the Institute of Plant Protection—National Research Institute in Winna Góra, the purpose of which was to test the insecticidal and acaricidal effectiveness of sugar beet cultivation protection against Tetranychus urticae and to assess its impact on the size and quality of the sugar beet crop. In the experiment, the following acaricides were used: spirodiclofen—240 g—22.11%, mixture of hexythiazox—250 g—23.15% and fenpyroximate—51.2 g—5.02% and insecto-acaricide paraffin oil—770 g L−1 (89.6%) and abamectine—18 g—1.88%. The controls were plants left without chemical protection. The plants were sprayed when ten mobile individuals/two spotted spider mites appeared on the leaves. Chemical treatments were carried out in the full growing season in the phase of leaf rosette formation (July–August). In the second half of October, the plant density (PD) in the field was estimated. Parameters characterizing the size and quality of the crop were calculated: sugar beet yield (SBY), biological sugar yield (BSY), pure sugar yield (PSY), sugar content (SC), refined of sugar content (RSC), the yield of preferential sugar (YPS), recoverable sugar (RS), potassium molasses (PM), sodium molasses (SM), -amino nitrogen (-AN), alkalinity factor (AF) and standard molasses losses (SML). The years were statistically significantly different for all 13 traits. Statistical differences were observed in the mean values of the observed parameters in these years, except for -amino nitrogen (-AN) and alkalinity factor (AF). The mean values of SBY, biological sugar yield (BSY), pure sugar yield (PSY) and sodium molasses (SM) differed depending on the type of protection applied. Positive correlations were observed for 28 pairs of traits, but negative statistically significant relationships were observed between 11 pairs of traits. The first two canonical variates accounted for 85.49% of the total variability between the individual combinations. The significant positive relationship with the first canonical variate was found for PD, BSY, PSY, SC, RSC, YPS, but negative for SM. The CV2 was negatively correlated with: SBY, BSY, PSY, RS, PM, SM, -AN and SML. The greatest variation in terms of all the 13 traits jointly was found for Vertigo 018 EC in 2020 and Vertigo 018 EC in 2021. The greatest similarity was found between control in 2019 and Ortus 05 SC in 2019.

Pig biology: serum enzymes and their correlation with physicochemical properties and chemical composition of muscle tissue

The paper presents the results of the study of some biochemical indicators of blood serum, physicochemical properties, and chemical composition of muscle tissue of young pigs of the large white breed, as well as the calculation of correlations between the main quantitative characteristics. The work was carried out in agricultural formations of the Dnipropetrovsk region, the Scientific Research Center for Biosafety and Environmental Control of Agricultural Resources of the Dnipro State Agrarian and Economic University, LLC “Globynskyi Myasokbinat” of the Poltava Region, the Laboratory of Zootechnical Analysis of the Institute of Pig Breeding and Agro-Industrial Production of the National Academy of Sciences, and the Animal Husbandry Laboratory of the State Institution “Institut of grain crops of NAAS”. Control fattening and slaughtering of the animals of the experimental group was carried out on the condition that they reached a live weight of 105–115 kg. The selection of blood samples for biochemical studies was carried out in 5-month-old animals; the activity of aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, and α-amylase was determined in blood serum. Physico-chemical properties and chemical composition of the longest muscle of the back (m. longissimus dorsi) were studied according to the indicators “moisture-retaining capacity, %”, “color intensity, units ext. × 1000”, “tenderness, c”, “fat content, %”, “total moisture content, %”, “protein content, %”, “losses during heat treatment, %” and “energy value of muscle tissue, kcal”. A comprehensive assessment of meat quality was determined according to the methods of A. M. Polyvoda and others, biometric processing of research results was carried out according to the methods of V. P. Kovalenko and others. It was established that the biochemical parameters of the blood serum of young pigs of the large white breed at the age of 5 months correspond to the physiological norm of clinically healthy animals. Thus, the activity of aspartate aminotransferase (AST) is 1.33 ± 0.074 mmol/h/l, alanine aminotransferase (ALT) is 1.87 ± 0.063 mmol/h/l, alkaline phosphatase is 291.99 ± 12.517 units/l, and amylase – 169.82 ± 5.005 g/h × l. Studies of the physicochemical properties and chemical composition of samples of the longest back muscle of young pigs of the large white breed show that the number of high-quality samples according to the indicators “moisture-holding capacity, %” equals 12.0 %, “color intensity, units ext. × 1000” – 16.0 %, “tenderness, c” – 12.0 % and “fat content, %” – 16.0 %. Significant correlations were established between the following pairs of traits: moisture-holding capacity × protein content (-0.484 ± 0.1825, tr = 2.65), moisture-holding capacity × losses during heat treatment (-0.416 ± 0.1896, tr = 2.19), fat content × moisture-holding capacity (-0.450 ± 01862, tr = 2.42), fat content × energy value (+0.836 ± 0.1144, tr = 7.31), alanine aminotransferase activity × pH, (+0.443 ± 0.1859, tr = 2.37), alkaline phosphatase activity × color intensity (-0.483 ± 0.1826, tr = 2.65), alkaline phosphatase activity × phosphorus content (+0.484 ± 0.1825, tr = 2, 65). Further work in this direction involves conducting a study of the qualitative composition of muscle and fat tissues of young pigs of various intrabreed and interbreed combinations, taking into account their genotype according to some DNA markers.

Investigating Shared Genetic Bases between Psychiatric Disorders, Cardiometabolic and Sleep Traits Using K-Means Clustering and Local Genetic Correlation Analysis

Psychiatric disorders are among the top leading causes of the global health-related burden. Comorbidity with cardiometabolic and sleep disorders contribute substantially to this burden. While both genetic and environmental factors have been suggested to underlie these comorbidities, the specific molecular underpinnings are not well understood. In this study, we leveraged large datasets from genome-wide association studies (GWAS) on psychiatric disorders, cardiometabolic and sleep-related traits. We computed genetic correlations between pairs of traits using cross-trait linkage disequilibrium (LD) score regression and identified clusters of genetically correlated traits using k-means clustering. We further investigated the identified associations using two-sample mendelian randomization (MR) and tested the local genetic correlation at the identified loci. In the 7-cluster optimal solution, we identified a cluster including insomnia and the psychiatric disorders major depressive disorder (MDD), post-traumatic stress disorder (PTSD), and attention-deficit/hyperactivity disorder (ADHD). MR analysis supported the existence of a bidirectional association between MDD and insomnia and the genetic variants driving this association were found to affect gene expression in different brain regions. Some of the identified loci were further supported by results of local genetic correlation analysis, with body mass index (BMI) and C-reactive protein (CRP) levels suggested to explain part of the observed effects. We discuss how the investigation of the genetic relationships between psychiatric disorders and comorbid conditions might help us to improve our understanding of their pathogenesis and develop improved treatment strategies.

The immune factors have complex causal regulation effects on bone mineral density.

Recent evidence has gradually recognized that the immune and skeletal systems are two closely correlated systems, but the specific immune factors on bone mineral density (BMD) are largely unknown. Based on the summary-level data of genome-wide association studies (GWASs), we performed a series of analyses including two-sample Mendelian randomization (MR) analysis to test potential causal links between 731 immune traits [including median fluorescence intensities (MFIs), absolute cell (AC) counts, relative cell (RC) counts, and morphological parameters (MP)] and BMD. After false discovery rate (FDR) correction, 9 MFI-BMD, 16 AC-BMD, 22 RC-BMD, and 5 MP-BMD pairs reached the level of significance (FDR-adjusted p< 0.05). For MFI traits, the T- and B-cell panels had the largest number of significant immune trait pairs than other panels. CD40, as a molecule expressed by four subsets of monocytes, was highlighted due to its consistently positive correlation with BMD at four sites. For both AC and RC traits, immune traits from the T-cell panel were also highlighted, with CD39-positive T-cell subsets being the most frequently observed feature. For MP traits, the most significant association immune trait with BMD was SSC-A on CD14+ monocyte. Sensitivity analyses suggested that the identified immune factors were robust to pleiotropy. Multivariable MR analysis confirmed the independent causal effect of several immune traits on BMD. Mediation analyses showed that CD40 on monocytes could mediate multiple immune traits, especially the suggestive associations of CD27 on several memory B cells with BMD mediated by CD40 on CD14+ CD16- monocyte. Our study represents the first comprehensive evaluation of the causal effects of immune traits on the risk of osteoporosis. The findings highlighted the complex and important role of immune-derived factors in the pathogenesis of osteoporosis.

A Shared Genetic Signature for Common Chronic Pain Conditions and its Impact on Biopsychosocial Traits

The multiple comorbidities & dimensions of chronic pain present a formidable challenge in disentangling its aetiology. Here, we performed genome-wide association studies of 8 chronic pain types using UK Biobank data (N =4,037–79,089 cases; N = 239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. We report evidence of a shared genetic signature across chronic pain types as their genetic correlations and GCP directions were broadly consistent across an array of biopsychosocial traits. Across 5,942 significant genetic correlations, 570 trait pairs could be explained by a causal association (|GCP| >0.6; 5% false discovery rate), including 82 traits affected by pain while 410 contributed to an increased risk of chronic pain (cf. 78 with a decreased risk) such as certain somatic pathologies (eg, musculoskeletal), psychiatric traits (eg, depression), socioeconomic factors (eg, occupation) and medical comorbidities (eg, cardiovascular disease). This data-driven phenome-wide association analysis has demonstrated a novel and efficient strategy for identifying genetically supported risk & protective traits to enhance the design of interventional trials targeting underlying causal factors and accelerate the development of more effective treatments with broader clinical utility. PerspectiveThrough large-scale phenome-wide association analyses of >1,400 biopsychosocial traits, this article provides evidence for a shared genetic signature across 8 common chronic pain types. It lays the foundation for further translational studies focused on identifying causal genetic variants and pathophysiological pathways to develop novel diagnostic & therapeutic technologies and strategies.

Tell me who You are and I’ll Tell You what You are Worth: The Role of Societal Value in the Structuration of Six Facets of the Big Two

This paper aims to show that six facets of the big two can be prioritized according to their societal value (that is, the value related to the society’s perceived main requirements), and that knowledge of this value differential could serve as a basis for trait inferences. The first two studies revealed the hierarchical organization of facets by asking participants to judge a) the societal value of these traits (study 1); and b) the targets known by indices of their societal value on traits accounting for the six facets (study 2). The last two studies examined how people’s inferences between traits were affected by this evaluative hierarchy. Study 3 tested the correlations between all pairs of facets by asking participants to describe an acquaintance using a set of traits accounting for two facets. Study 4 asked participants to rate the similarity between 66 pairs of traits crossing all the facets. The results showed that, as predicted, trait inferences were structured by the societal value of the facets and were organized in a circumplex-like structure. The discussion focused on how societal values emanate from the economic prioritization of traits in society and how they permeate people’s representations.

Estimation of genetic parameters for important traits using a multi-trait model in late-feathering Qingyuan partridge hens in China.

Qingyuan partridge chicken is one of the most well-known Chinese indigenous yellow broilers. In breeding programmes, five traits are usually selected when the chickens are 105 days old, namely body weight (BW), comb height (CH), shank length (SL), shank girth (SG) and feather maturity (FM). The objective of this study was to estimate the genetic parameters of these five traits, especially direct additive genetic correlations, to lay the foundation for balanced selection of Qingyuan partridge chickens. Approximately 9600 records were used for estimation. Variance components for these five traits were estimated using three multi-trait models incorporating different effects via Gibbs sampling. Based on model 1 in which the random effects included direct additive genetic effects and residuals, the estimated direct heritabilities for BW, CH, SL, SG and FM were 0.29 ± 0.04, 0.53 ± 0.04, 0.47 ± 0.04, 0.43 ± 0.05 and 0.18 ± 0.03, respectively. The direct genetic correlations ranged from -0.08 to 0.46. When additionally considering maternal additive genetic effects (model 2), the estimates of direct heritabilities and absolute values of direct additive genetic correlations were smaller. The heritabilities were 0.14 ± 0.04, 0.40 ± 0.02, 0.34 ± 0.05, 0.27 ± 0.05 and 0.12 ± 0.03 for BW, CH, SL, SG and FM, respectively. The direct additive genetic correlations ranged from -0.33 to 0.36. More specifically, the direct additive genetic correlations between BW and CH, SL, SG and FM were 0.19 ± 0.13, 0.15 ± 0.15, 0.36 ± 0.15 and - 0.33 ± 0.21, respectively. The genetic correlations of FM with SL, SG and CH were - 0.15 ± 0.15, -0.08 ± 0.17 and 0.18 ± 0.15, respectively. The direct genetic correlations between CH and SG and SL were - 0.02 ± 0.11 and - 0.20 ± 0.11, respectively, and that between SL and SG was 0.19 ± 0.11. The total heritabilities and maternal additive genetic correlations ranged from 0.16 to 0.44 and from -0.13 to 0.61, respectively. The third model also included the maternal permanent environmental effect for BW. The estimates of direct heritability, direct additive genetic correlation, total heritability and maternal additive genetic correlation were only slightly different from those based on the second model. Therefore, the maternal additive genetic effect has a large effect on the estimation of genetic parameters, and it is better to consider this effect in the genetic evaluation of these five traits. Relatively high direct and maternal additive genetic correlations for most trait pairs suggested that it is better to jointly evaluate these five traits in breeding programmes.

Brain functional connectivity mirrors genetic pleiotropy in psychiatric conditions.

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behaviour. We processed nine resting-state functional MRI datasets including 32 726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of 19 pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic-rFunctional connectivity = 0.71 [0.40-0.87] and rTranscriptomic-rFunctional connectivity = 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms-amenable to intervention-across psychiatric conditions and genetic risks.

Getting straight to the source: who evaluates the leadership skills of premiers in Canada and Australia?

ABSTRACT Journalists have the power to shape the public’s perception of new premiers. They also share that power with the sources they interview. Sourcing is therefore important when making claims about the news media’s role in reproducing gender biases in representations of political leaders. We examine the question of sourcing through an analysis of newspaper coverage of 22 newly elected women and men subnational government leaders in Australia and Canada to answer the following questions. How do news writers rely on sources in evaluations of new premiers? To what extent do they employ different patterns of sourcing and are these sourcing patterns gendered? We focus on two pairs of leadership traits that dominate news coverage of premiers in the first week: strength/weakness and competence/incompetence. We find that journalists use unattributed assessments rather than sources when evaluating premiers’ skills and abilities, but when sources are cited, these are usually elite men.

Flexible drought deciduousness in a neotropical understory herb.

PremiseAdaptive divergence across environmental gradients is a key driver of speciation. Precipitation seasonality gradients are common in the tropics, yet drought adaptation is nearly unexplored in neotropical understory herbs. Here, we examined two recently diverged neotropical spiral gingers, one adapted to seasonal drought and one reliant on perennial water, to uncover the basis of drought adaptation.MethodsWe combined ecophysiological trait measurements in the field and greenhouse with experimental and observational assessments of real‐time drought response to determine how Costus villosissimus (Costaceae) differs from C. allenii to achieve drought adaptation.ResultsWe found that drought‐adapted C. villosissimus has several characteristics indicating flexible dehydration avoidance via semi‐drought‐deciduousness and a fast economic strategy. Although the two species do not differ in water‐use efficiency, C. villosissimus has a more rapid growth rate, lower leaf mass per area, lower stem density, higher leaf nitrogen, and a strong trend of greater light‐saturated photosynthetic rates. These fast economic strategy traits align with both field‐based observations and experimental dry‐down results. During drought, C. villosissimus displays facultative drought‐deciduousness, losing lower leaves during the dry season and rapidly growing new leaves in the wet season.ConclusionsWe revealed a drought adaptation strategy that has not, to our knowledge, previously been documented in tropical herbs. This divergent drought adaptation evolved recently and is an important component of reproductive isolation between C. villosissimus and C. allenii, indicating that adaptive shifts to survive seasonal drought may be an underappreciated axis of neotropical understory plant diversification.

Phenotypic Variability, Heritability and Associations of Agronomic and Quality Traits in Cultivated Ethiopian Durum Wheat (Triticum turgidum L. ssp. Durum, Desf.)

Quality is an important aspect of durum wheat in the processing sector. Thus, recognizing the variability of quality and agronomic traits and their association is fundamental in designing plant breeding programs. This study aimed to assess the variability, heritability, genetic advance, and correlation of some agronomic and quality traits among 420 Ethiopian durum wheat genotypes and to identify the promising genotypes with distinct processing quality attributes to produce superior quality pasta. The field experiment was conducted at two locations (Sinana and Chefe Donsa) using an alpha lattice design with two replications. Analysis of variance, chi-square test, and Shannon–Weaver diversity index revealed the existence of highly significant (p &lt; 0.001) variation among genotypes for all studied traits. The broad-sense heritability values were ranging from 46.2% (days to maturity) to 81% (thousand kernel weight) with the genetic advance as a percent of the mean ranging from 1.1% (days to maturity) to 21.2% (grain yield). The phenotypic correlation coefficients for all possible pairs of quantitative traits showed a significant (p &lt; 0.05) association among most paired traits. The gluten content (GC) and grain protein content (GPC) were negatively correlated with grain yield and yield-related traits and positively associated with phenological traits, while yield and phenological traits correlated negatively. The frequency distributions of amber-colored and vitreous kernels, which are preferable characters of durum wheat in processing, were highly dominant in Ethiopian durum wheat genotypes. The identified top 5% genotypes, which have amber color and vitreous kernel with high GC and GPC content as well as sufficient grain yield, could be directly used by the processing sector and/or as donors of alleles in durum wheat breeding programs.

Benchmarking of univariate pleiotropy detection methods applied to epilepsy.

Pleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, conditional false discovery rate (cFDR), cross-phenotype Bayes (CPBayes), and pleiotropic analysis under the composite null hypothesis (PLACO), by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits' overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published International League Against Epilepsy (ILAE) consortium data set on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression, and regulatory function analysis as well as Bayesian colocalization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies.

Evaluation of Aphid Resistance and Oleoresin Production in Indigenous Tropical Pine (Pinus merkusii Jungh. and de Vriese)

The native tropical pine (Pinus merkusii Jungh. and de Vriese) has been genetically improved in Indonesia since 1977; nevertheless, minor evaluations of aphid resistance have been conducted since 2004. As a result, a progeny test for aphid resistance was established in 2010 in Lawu, Central Java, Indonesia. Subjects in the trial were attacked significantly at the rate of 30.7% after 4 years, but surprisingly, some individuals were found to be healthy without any aphid attack. The observed a 7-year progeny trial comprised 34 families with 4 trees per unitary plot and replicated in 10 blocks. At 7 years, observations during 9 months (April–December) showed that there were differences in the range of resistance across families. The stem diameter, oleoresin production, and resistance to aphid attack were evaluated, and all traits were distinct among families except for oleoresin exudation from the western side of the stem. Five families performed above average for all three traits, while three other families had high diameter and maintained good oleoresin production. These eight families can be included in a forward selection strategy. Cluster analysis revealed that the eight best families were grouped into two of the eight clusters. Phenotypic correlations revealed that all pairs of traits were significantly related, with the highest correlation registered between stem diameter and resistance to aphid attack (0.99). Forward selection ensures the simultaneous improvement of the three traits.

Can evolutionary history predict plant plastic responses to climate change?

Plant plastic responses are critical to the adaptation and survival of species under climate change, but whether they are constrained by evolutionary history (phylogeny) is largely unclear. Plant leaf traits are key in determining plants' performance in different environments, and if these traits and their variation are phylogenetically dependent, predictions could be made to identify species vulnerable to climate change. We compiled data on three leaf traits (photosynthetic rate, specific leaf area, and leaf nitrogen content) and their variation under four environmental change scenarios (warming, drought, elevated CO2 , or nitrogen addition) for 434 species, from 210 manipulation experiments. We found phylogenetic signal in the three traits but not in their variation under the four scenarios. This indicates that closely related species show similar traits but that their plastic responses could not be predicted from species relatedness under environmental change. Meanwhile, phylogeny weakened the slopes but did not change the directions of conventional pairwise trait relationships, suggesting that co-evolved leaf trait pairs have consistent responses under contrasting environmental conditions. Phylogeny can identify lineages rich in species showing similar traits and predict their relationships under climate change, but the degree of plant phenotypic variation does not vary consistently across evolutionary clades.

Environmental variation drives the decoupling of leaf and root traits within species along an elevation gradient.

Plant performance is enhanced by balancing above- and below-ground resource uptake through the intraspecific adjustment of leaf and root traits. It is assumed that these organ adjustments are at least partly coordinated, so that analogous leaf and root traits broadly covary. Understanding the extent of such intraspecific leaf-root trait covariation would strongly contribute to our understanding of how plants match above- and below-ground resource use strategies as their environment changes, but comprehensive studies are lacking. We measured analogous leaf and root traits from 11 species, as well as climate, soil and vegetation properties along a 1000-m elevation gradient in the French Alps. We determined how traits varied along the gradient, to what extent this variation was determined by the way different traits respond to environmental cues acting at different spatial scales (i.e. within and between elevations), and whether trait pairs covaried within species. Leaf and root trait patterns strongly diverged: across the 11 species along the gradient, intraspecific leaf trait patterns were largely consistent, whereas root trait patterns were highly idiosyncratic. We also observed that, when compared with leaves, intraspecific variation was greater in root traits, due to the strong effects of the local environment (i.e. at the same elevation), while landscape-level effects (i.e. at different elevations) were minor. Overall, intraspecific trait correlations between analogous leaf and root traits were nearly absent. Our study suggests that environmental gradients at the landscape level, as well as local heterogeneity in soil properties, are the drivers of a strong decoupling between analogous leaf and root traits within species. This decoupling of plant resource acquisition strategies highlights how plants can exhibit diverse whole-plant acclimation strategies to modify above- and below-ground resource uptake, improving their resilience to environmental change.

Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program.

Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.