Multi-trait Analysis Research Articles

Multi-trait analysis reveals large interspecific differences for phytoplankton in response to thermal change

Understanding the responses of multiple traits in phytoplankton, and identifying interspecific variabilities to thermal changes is crucial for predicting the impacts of ocean warming on phytoplankton distributions and community structures in future scenarios. Here, we applied a trait-based approach by examining the patterns in multi-traits variations (eight traits) and interspecific variabilities in five phytoplankton species (two diatoms, three dinoflagellates) in response to a wide range of ecologically relevant temperatures (14–30 °C). Our results show large inter-traits and interspecific variabilities of thermal reaction norms in all of the tested traits. We also found that the interspecific variability exceeded the variations induced by thermal changes. Constrained variations and trade-offs between traits both revealed substantial interspecific differences and shifted as the temperature changed. Our study helps to understand the species-specific response patterns of multiple traits to ocean warming and to investigate the implications of these responses in the context of global change.

Prediction ability of an alternative multi-trait genomic evaluation for residual feed intake.

Selection for feed efficiency is the goal for many genetic breeding programs in beef cattle. Residual feed intake has been included in genetic evaluations to reduce feed intake without compromising performance traits as liveweight, body gain or carcass traits. However, measuring feed intake is expensive, and only a small percentage of selection candidates are phenotyped. Genomic selection has become a very important tool to achieve effective genetic progress in these traits. Another effective strategy has been the implementation of multi-trait prediction using easily recordable predictor traits on both reference animals and candidates without phenotypes, and this could be another inexpensive way to increase accuracy. The objective of this work was to analyse and compare the prediction ability of two alternative different approaches to predict GEBVs for RFI. The population of inference was Hereford bulls in Uruguay that were genotyped candidates for to selection. The first model was the conventional univariate model for RFI and the second model was a multi-trait model which included a predictor trait (weaning weight, WW), in addition to the traits used in the first one (dry matter intake, metabolic mid test weight, average daily gain and ultrasound back fat) (DMI, MWT, ADG, UBF, respectively). GEBVs from the multi-trait model were combined using selection index theory to derive RFI values. All analyses were performed using ssGBLUP procedure. The prediction ability of both models was tested using two validation strategies (30 different replicates of random groups of animals and validation across 9 different feed intake tests). The prediction quality was assessed by the following parameters: bias, dispersion, ratio of accuracies and the relative increase in accuracy by adding phenotypic information. All parameters showed that the univariate model outperforms the multi-trait model, regardless of the validation strategy considered. These results indicate that including WW as a proxy trait in a multi-trait analysis does not improve the prediction ability when all animals to be predicted are genotyped.

Genome-wide multi-trait analysis of irritable bowel syndrome and related mental conditions identifies 38 new independent variants

BackgroundIrritable bowel syndrome (IBS) is a chronic disorder of gut-brain interaction frequently accompanied by mental conditions, including depression and anxiety. Despite showing substantial heritability and being partly determined by a genetic component, the genetic underpinnings explaining the high rates of comorbidity remain largely unclear and there are no conclusive data on the temporal relationship between them. Exploring the overlapping genetic architecture between IBS and mental conditions may help to identify novel genetic loci and biological mechanisms underlying IBS and causal relationships between them.MethodsWe quantified the genetic overlap between IBS, neuroticism, depression and anxiety, conducted a multi-trait genome-wide association study (GWAS) considering these traits and investigated causal relationships between them by using the largest GWAS to date.ResultsIBS showed to be a highly polygenic disorder with extensive genetic sharing with mental conditions. Multi-trait analysis of IBS and neuroticism, depression and anxiety identified 42 genome-wide significant variants for IBS, of which 38 are novel. Fine-mapping risk loci highlighted 289 genes enriched in genes upregulated during early embryonic brain development and gene-sets related with psychiatric, digestive and autoimmune disorders. IBS-associated genes were enriched for target genes of anti-inflammatory and antirheumatic drugs, anesthetics and opioid dependence pharmacological treatment. Mendelian-randomization analysis accounting for correlated pleiotropy identified bidirectional causal effects between IBS and neuroticism and depression and causal effects of the genetic liability of IBS on anxiety.ConclusionsThese findings provide evidence of the polygenic architecture of IBS, identify novel genome-wide significant variants for IBS and extend previous knowledge on the genetic overlap and relationship between gastrointestinal and mental disorders.

Estimates of genetic parameters for indicator traits of resistance to gastrointestinal nematodes and growth traits in Santa Inês sheep

Infections by gastrointestinal nematodes is a major problem in the sheep industry worldwide. Therefore, this study aimed: (1) to estimate genetic parameters for indicator traits of resistance to gastrointestinal nematodes such as packed cell volume (PCV), total plasma protein (TPP), color of the ocular conjunctiva by Famacha© method (FAM), and fecal egg count (FEC); (2) to estimate genetic parameters for growth traits such as body weight (BW), body condition score (BCS) and chest girth (CG); and (3) evaluate the FAM as an indicator trait of resistance to gastrointestinal nematodes in Santa Inês sheep. The dataset contained 3524 observations from 1176 animals and the pedigree presented 2011 animals. The genetic parameters were estimated by the animal model, in single- and multi-trait Bayesian analyses, using the THRGIBBS1F90 program. Stochastic Markov Chain Monte Carlo Simulation (MCMC) was used to obtain estimates of the parameters of interest, using Gibbs sampling. The a posteriori estimates were obtained with the POSTGIBBSF90 program. The sensitivity and specificity of the FAM were 66.7 % and 75.8 %, respectively. In general, the sensitivity and specificity values found herein do not invalidate the use of FAM. In the single-trait model, the heritability estimates for BW, CG, BCS, PCV, TPP, FAM, and FEC were 0.51 ± 0.02, 0.61 ± 0.03, 0.40 ± 0.04, 0.38 ± 0.03, 0.29 ± 0.03, 0.19 ± 0.05 and 0.15 ± 0.03, respectively. In the multi-trait model, the heritability observed for these traits were 0.73 ± 0.02, 0.64 ± 0.02, 0.35 ± 0.05, 0.38 ± 0.03, 0.29 ± 0.03, 0.20 ± 0.05 and 0.13 ± 0.04, respectively. Genetic correlations between growth traits (BW, BCS, and CG) were positive with high magnitude. In addition, growth traits exhibited positive genetic correlations with PCV and TPP, and negative correlations with FAM. The genetic correlation between PCV and FAM, and between FEC and BW were negative and favorable. The genetic parameters suggest that it is possible to obtain genetic gains for the evaluated traits by the response to direct selection. Unfavorable genetic correlations were not found between growth traits and indicator traits of resistance to gastrointestinal nematodes. The heritability of FAM was moderate, and genetic correlations were considered favorable between FAM and PCV. In addition, FAM is easy-to-measure and has a low cost. Therefore, FAM can be an alternative secondary selection criterion associated with body weight (main selection criterion), to increase resistance to gastrointestinal nematodes.

Comparison of two multi-trait association testing methods and sequence-based fine mapping of six additive QTL in Swiss Large White pigs

BackgroundGenetic correlations between complex traits suggest that pleiotropic variants contribute to trait variation. Genome-wide association studies (GWAS) aim to uncover the genetic underpinnings of traits. Multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS enable detecting variants associated with multiple phenotypes. In this study, we used array-derived genotypes and phenotypes for 24 reproduction, production, and conformation traits to explore differences between the two methods and used imputed sequence variant genotypes to fine-map six quantitative trait loci (QTL).ResultsWe considered genotypes at 44,733 SNPs for 5,753 pigs from the Swiss Large White breed that had deregressed breeding values for 24 traits. Single-trait association analyses revealed eleven QTL that affected 15 traits. Multi-trait association testing and the meta-analysis of the single-trait GWAS revealed between 3 and 6 QTL, respectively, in three groups of traits. The multi-trait methods revealed three loci that were not detected in the single-trait GWAS. Four QTL that were identified in the single-trait GWAS, remained undetected in the multi-trait analyses. To pinpoint candidate causal variants for the QTL, we imputed the array-derived genotypes to the sequence level using a sequenced reference panel consisting of 421 pigs. This approach provided genotypes at 16 million imputed sequence variants with a mean accuracy of imputation of 0.94. The fine-mapping of six QTL with imputed sequence variant genotypes revealed four previously proposed causal mutations among the top variants.ConclusionsOur findings in a medium-size cohort of pigs suggest that multivariate association testing and the meta-analysis of summary statistics from single-trait GWAS provide very similar results. Although multi-trait association methods provide a useful overview of pleiotropic loci segregating in mapping populations, the investigation of single-trait association studies is still advised, as multi-trait methods may miss QTL that are uncovered in single-trait GWAS.

Multi-trait genome-wide association study identifies a novel endometrial cancer risk locus that associates with testosterone levels

To detect novel endometrial cancer risk variants, we leveraged information from endometrial cancer risk factors in a multi-trait GWAS analysis. We first assessed causal relationships between established and suspected endometrial cancer risk factors, and endometrial cancer using Mendelian randomization. Following multivariable analysis, five independent risk factors (waist circumference, testosterone levels, sex hormone binding globulin levels, age at menarche, and age at natural menopause) were included in a multi-trait Bayesian GWAS analysis. We identified three potentially novel loci that associate with endometrial cancer risk, one of which (7q22.1) replicated in an independent endometrial cancer GWAS dataset and was genome-wide significant in a meta-analysis. This locus may affect endometrial cancer risk through altered testosterone levels. Consistent with this, we observed colocalization between the signals for endometrial cancer risk and expression of CYP3A7, a gene involved in testosterone metabolism. Thus, our findings suggest opportunities for hormone therapy to prevent or treat endometrial cancer.

Single and multi-trait genomic prediction for agronomic traits in Euterpe edulis.

Popularly known as juçaizeiro, Euterpe edulis has been gaining prominence in the fruit growing sector and has demanded the development of superior genetic materials. Since it is a native species and still little studied, the application of more sophisticated techniques can result in higher gains with less time. Until now, there are no studies that apply genomic prediction for this crop, especially in multi-trait analysis. In this sense, this study aimed to apply new methods and breeding techniques for the juçaizeiro, to optimize this breeding program through the application of genomic prediction. This data consisted of 275 juçaizeiro genotypes from a population of Rio Novo do Sul-ES, Brazil. The genomic prediction was performed using the multi-trait (G-BLUP MT) and single-trait (G-BLUP ST) models and the selection of superior genotypes was based on a selection index. Similar results for predictive ability were observed for both models. However, the G-BLUP ST model provided greater selection gains when compared to the G-BLUP MT. For this reason, the genomic estimated breeding values (GEBVs) from the G-BLUP ST, were used to select the six superior genotypes (UFES.A.RN.390, UFES.A.RN.386, UFES.A.RN.080, UFES.A.RN.383, UFES.S.RN.098, and UFES.S.RN.093). This was intended to provide superior genetic materials for the development of seedlings and implantation of productive orchards, which will meet the demands of the productive, industrial and consumer market.

Genetic association between feed efficiency, growth, scrotal circumference, and carcass traits in Guzerat cattle.

The objective of this study was to estimate the genetic parameters for feed efficiency-related traits and their genetic correlations with growth, male fertility, and carcass traits using multi-trait analysis in Guzerat cattle. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for growth, male fertility, and carcass traits. The evaluated traits were adjusted weight at 120 (W120), 210 (W210), 365 (W365), and 450days of age (W450), adjusted scrotal circumference at 365days of age (SC365) and at 450days of age (SC450), scrotal circumference, ribeye area (REA), backfat thickness (BFT), rump fat thickness (RFT), residual feed intake (RFI), and dry matter intake (DMI). The genetic parameters were obtained by the restricted maximum likelihood method (REML), using an animal model in multi-trait analyses. The heritability estimates for W120, W210, W365, W450, SC365, and SC450 varied from low to high (0.17 to 0.39). The carcass traits, REA, BFT, and RFT, displayed low to moderate heritability estimates, 0.27, 0.10, and 0.31, respectively. The heritability estimates for RFI (0.15) and DMI (0.23) were low and moderate, respectively. The RFI showed low genetic correlations with growth traits, ranging from - 0.07 to 0.22, from 0.03 to 0.05 for scrotal circumference, and from - 0.35 to 0.16 for carcass, except for DMI, which ranged from 0.42 to 0.46. The RFI and DMI presented enough additive genetic variability to be used as selection criteria in Guzerat breed genetic improvement program. Additionally, the response to selection for RFI would be higher when selection is performed directly for this trait. The selection for residual feed intake would not promote unfavorable correlated responses for scrotal circumference, carcass (yield and finish), and growth traits. Therefore, the selection for more efficient animals would not compromise the productive, reproductive, and carcass performance, contributing to reduce the production costs, increasing the profitability and sustainability of beef cattle production in tropical areas.

Multi-trait analysis of gene-by-environment interactions in large-scale genetic studies.

Identifying genotype-by-environment interaction (GEI) is challenging because the GEI analysis generally has low power. Large-scale consortium-based studies are ultimately needed to achieve adequate power for identifying GEI. We introduce Multi-Trait Analysis of Gene-Environment Interactions (MTAGEI), a powerful, robust, and computationally efficient framework to test gene-environment interactions on multiple traits in large data sets, such as the UK Biobank (UKB). To facilitate the meta-analysis of GEI studies in a consortium, MTAGEI efficiently generates summary statistics of genetic associations for multiple traits under different environmental conditions and integrates the summary statistics for GEI analysis. MTAGEI enhances the power of GEI analysis by aggregating GEI signals across multiple traits and variants that would otherwise be difficult to detect individually. MTAGEI achieves robustness by combining complementary tests under a wide spectrum of genetic architectures. We demonstrate the advantages of MTAGEI over existing single-trait-based GEI tests through extensive simulation studies and the analysis of the whole exome sequencing data from the UKB.

The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions.

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.

Compositional Traits of Grains and Groats of Barley, Oat and Spelt Grown at Organic and Conventional Fields

Barley, oats, or spelt consumed as minimally processed whole grains provide several health benefits, especially when grown under organic field management conditions. Therefore, the effects of organic and conventional farming on the compositional traits (protein, fibre, fat, and ash) of barley, oat, and spelt grains and groats were compared using three winter barley varieties ('Anemone', 'BC Favorit', and 'Sandra'), two spring oat varieties ('Max' and 'Noni'), and three spelt varieties ('Ebners Rotkorn', 'Murska bela', and 'Ostro'). Groats were produced from harvested grains by a combination of threshing, winnowing, and brushing/polishing. Multitrait analysis showed significant differences between species, field management practices, and fractions, with clear compositional differences between organic and conventional spelt. Barley and oat groats had a higher thousand kernel weight (TKW) and β-glucan, but lower crude fibre, fat, and ash contents than the grains. The composition of the grains of the different species differed significantly for more traits (TKW, fibre, fat, ash, and β-glucan) than that of the groats (TKW and fat), while field management only affected the fibre content of the groats and the TKW, ash, and β-glucan contents of the grains. The TKW, protein, and fat contents of the different species differed significantly under both conventional and organic growing conditions, while the TKW and fibre contents of grains and groats differed under both systems. The caloric value of the final products of barley, oats, and spelt groats ranged from 334-358 kcal/100 g. This information will be useful for not only the processing industry, but also for breeders and farmers, and last, but not least, for consumers.

Multitrait genome-wide analyses identify new susceptibility loci and candidate drugs to primary sclerosing cholangitis

Primary sclerosing cholangitis (PSC) is a rare autoimmune bile duct disease that is strongly associated with immune-mediated disorders. In this study, we implemented multitrait joint analyses to genome-wide association summary statistics of PSC and numerous clinical and epidemiological traits to estimate the genetic contribution of each trait and genetic correlations between traits and to identify new lead PSC risk-associated loci. We identified seven new loci that have not been previously reported and one new independent lead variant in the previously reported locus. Functional annotation and fine-mapping nominated several potential susceptibility genes such as MANBA and IRF5. Network-based in silico drug efficacy screening provided candidate agents for further study of pharmacological effect in PSC.

Pleiotropy analysis between lobar intracerebral hemorrhage and CSF β-amyloid highlights new and established associations.

Combining biologically related traits in genome-wide association studies (GWAS) increases the power for genetic discovery. Given the established relationship between lobar intracerebral hemorrhage (ICH) and cerebral amyloid angiopathy (CAA), and between the latter and levels of cerebrospinal fluid amyloid-β 42 (CSF-Aβ42), we leveraged genetic predisposition for lower CSF-Aβ42 levels as a proxy phenotype for CAA to identify new genes associated with lobar ICH. We used publicly available GWAS data for CSF-Aβ42 levels (n = 3146) and for lobar ICH (n = 2094). First, we evaluated the association between lobar ICH risk and CSF-Aβ42 in lobar ICH patients using a polygenic risk score (PRS) for CSF-Aβ42. Next, we conducted multi-trait analysis of GWAS (MTAG) for pleiotropy analysis of lobar ICH and CSF-Aβ42. MTAG results were further tested using Expression Quantitative Trait Locus and Differential Gene Expression Analyses. CSF-Aβ42 PRS was associated with lobar ICH risk (p = 0.04). MTAG analysis identified a novel association within CDH9 (rs1007589; minor allele frequency = 0.09; MTAG p = 5.4 × 10-8; lobar ICH odds ratio = 1.4 and p = 2.4 × 10-3; CSF-Aβ42 β = -0.03 and p = 4.5 × 10-6). rs1007589 was significantly associated with the expression levels of CDH9 in temporal and occipital cortices, regions known to preferentially accumulate microhemorrhages in CAA. Our pleiotropy analysis suggested a variant possibly implicated with lobar ICH driven by amyloid-related mechanisms in CDH9 and associated with differential expression in brain regions characteristically affected by CAA. CDH9 is one subtype of the cadherin superfamily, which regulates intercellular adhesion, is involved in blood-brain barrier integrity, and is elevated in Alzheimer's disease patients. Further analyses are warranted to understand the effects of the variant on the pathogenesis of ICH and its clinical significance.

A Multi-Trait Association Analysis of Brain Disorders and Platelet Traits Identifies Novel Susceptibility Loci for Major Depression, Alzheimer’s and Parkinson’s Disease

Among candidate neurodegenerative/neuropsychiatric risk-predictive biomarkers, platelet count, mean platelet volume and platelet distribution width have been associated with the risk of major depressive disorder (MDD), Alzheimer's disease (AD) and Parkinson's disease (PD) through epidemiological and genomic studies, suggesting partial co-heritability. We exploited these relationships for a multi-trait association analysis, using publicly available summary statistics of genome-wide association studies (GWASs) of all traits reported above. Gene-based enrichment tests were carried out, as well as a network analysis of significantly enriched genes. We analyzed 4,540,326 single nucleotide polymorphisms shared among the analyzed GWASs, observing 149 genome-wide significant multi-trait LD-independent associations (p < 5 × 10-8) for AD, 70 for PD and 139 for MDD. Among these, 27 novel associations were detected for AD, 34 for PD and 40 for MDD. Out of 18,781 genes with annotated variants within ±10 kb, 62 genes were enriched for associations with AD, 70 with PD and 125 with MDD (p < 2.7 × 10-6). Of these, seven genes were novel susceptibility loci for AD (EPPK1, TTLL1, PACSIN2, TPM4, PIF1, ZNF689, AZGP1P1), two for PD (SLC26A1, EFNA3) and two for MDD (HSPH1, TRMT61A). The resulting network showed a significant excess of interactions (enrichment p = 1.0 × 10-16). The novel genes that were identified are involved in the organization of cytoskeletal architecture (EPPK1, TTLL1, PACSIN2, TPM4), telomere shortening (PIF1), the regulation of cellular aging (ZNF689, AZGP1P1) and neurodevelopment (EFNA3), thus, providing novel insights into the shared underlying biology of brain disorders and platelet parameters.

Salinity, alkalinity and their combined stress effects on germination and seedling growth attributes in oats (Avena sativa)

Context Under natural field conditions, plants confront the co-occurrence of stresses. A comprehensive insight into combined-stress tolerance is requisite to developing stress resilience in cultivars of oats (Avena sativa L.) for saline–alkaline soil. Aims This study was undertaken to characterise diverse oat genotypes for seedling growth attributes under two saline and alkaline concentrations and under combined saline–alkaline conditions. Methods We screened 105 accessions of the genus Avena with the following treatments: control, reverse osmosis water; moderate salinity (50 mM); high salinity (100 mM); moderate alkalinity (15 mM); high alkalinity (30 mM); combined moderate salinity–alkalinity (50 mM + 15 mM); and combined high salinity–alkalinity (100 mM + 30 mM). For saline treatments, NaCl and Na2SO4 salts were used in equimolar concentrations, and for alkaline treatments, NaHCO3 and Na2CO3. Key results Analysis of variance showed significant (P ≤ 0.001) variation among treatments and genotypes. Principal component analysis revealed 83.3% of the total genetic variation accounted for in the first two principal components. Correlation analysis showed a significant positive correlation between final germination percentage and seedling vigour index. Stress tolerance index identified tolerant and sensitive oat genotypes under high saline and alkaline stress, and multi-trait stability analysis confirmed the stability of performance of some genotypes under the imposed treatments. Conclusions According to the stress tolerance index and multi-trait stability analysis, genotypes IG-20-477, OS-377, IG-20-798 and IG-20-575 were found suitable for high saline–alkaline stress. Implications The identified tolerant oat genotypes can be used as donors for the development of stress-resilient oat cultivars, and for generating mapping populations in oat.

Development and validation of the Work Style Reform Scale.

In Japan, the "Act on the Arrangement of Related Acts to Promote Work Style Reform" was enforced in 2019 to reduce long working hours. However, work style reforms largely depend on workers' and companies' awareness and abilities. This study aimed to develop the Work Style Reform scale to assess the competencies required for work style reform and to examine its validity and reliability. This study was conducted with a diverse sample of 1,641 Japanese workers, and 17 questions across three subscales-Work Style, Personal Style, and Work Environment-were developed. After a response bias analysis, some items were discarded based on an exploratory factor analysis; the reliability coefficients were calculated; and a confirmatory factor analysis was performed. The convergent and discriminant validity were evaluated through a multi-trait multi-method analysis. Finally, nine questions remained. Construct validity, reliability and convergent validity were sufficient for all Subscales, and discriminant validity was sufficient only for Work Style. In conclusion, while Work Style was sufficient, issues remained in other subscales. To improve the accuracy of them in the future, it is necessary to examine the validation of discriminant validity using different indicates and the addition of new items to the smallest subscale; Personal Style.

Updating knowledge in estimating the genetics parameters: Multi-trait and Multi-Environment Bayesian analysis in rice

Among the multi-trait models selected to study several traits and environments jointly, the Bayesian framework has been a preferred tool when constructing a more complex and biologically realistic model. In most cases, non-informative prior distributions are adopted in studies using the Bayesian approach. However, the Bayesian approach presents more accurate estimates when informative prior distributions are used. The present study was developed to evaluate the efficiency and applicability of multi-trait multi-environment (MTME) models within a Bayesian framework utilizing a strategy for eliciting informative prior distribution using previous data on rice. The study involved data pertaining to rice (Oryza sativa L.) genotypes in three environments and five crop seasons (2010/2011 until 2014/2015) for the following traits: grain yield (GY), flowering in days (FLOR) and plant height (PH). Variance components, genetic and non-genetic parameters were estimated using the Bayesian method. In general, the informative prior distribution in Bayesian MTME models provided higher estimates of individual narrow-sense heritability and variance components, as well as minor lengths for the highest probability density interval (HPD), compared to their respective non-informative prior distribution analyses. More informative prior distributions make it possible to detect genetic correlations between traits, which cannot be achieved with non-informative prior distributions. Therefore, this mechanism presented to update knowledge for an elicitation of an informative prior distribution can be efficiently applied in rice breeding programs.

Morphological growth performance and genetic parameters on Korean pine in Northeastern China

Abstract Korean pine (Pinus koraiensis) is an economically valuable species owing to its excellent timber quality and nuts useful for various purposes. But few studies have been made on growth performance, and aspects combining the genetic gain and classification method on phenotypic similarity in the selection process of superior families. Thus, the present study aimed at analyzing the genetic variation and highlight suitable morphological traits for family selection; establishing trait correlations and families’ ordination based on similarities in phenotypic characters, and selecting elite families and suitable parent trees. Full-sib families from 28 crosses established in randomized complete block design from Naozhi orchard in Northeast China were used, and 11 morphological traits were investigated. Significant differences were observed among families for all traits. The traits coefficients of variation ranged from 6.07 to 56.25 % and from 0.029 to 15.213 % in phenotype and genotypic variation, respectively. A moderate level of inherited genetic control was observed (broad sense heritability H2, varied from 0.155 to 0.438). Traits related to stem growth were highly positively correlated to each other whereas crown traits showed a weak correlation with stem traits (Pearson correlation r, ranged from -0.161 to 0.956). Based on multi-trait comprehensive analysis, we selected six elite families and six parents, which resulted in a genetic gain of 5.6 %, 16.9 %, and 36.4 % in tree height, diameter at breast height, and volume, respectively. These results make a theoretical basis for selecting excellent families and establish orchards of Korean pine from improved seeds.

University Health Risk Behaviour (UniHRB) Inventory (Sinhala): a tool to assess common health risk behaviours among undergraduates in Sri Lanka

Introduction: The degree of health risk behaviour (HRB) among undergraduates has not been researched extensively in Sri Lanka and there is no tool available to assess common HRBs in a university setting. Objectives: To develop, translate and validate a tool to measure common HRBs in Sinhalese second-year undergraduates in Sri Lanka Methods: The UniHRB-Inventory (Sinhala) was developed using a seven-step design process for tool development. An extensive literature review, nine key informant interviews (KII), and five focus group discussions (FGD) were carried out. A combination of deductive and inductive methods was used to define the domain and identify the questions to assess. Content and consensual validity was assessed using the modified Delphi process. A validation study was conducted among 666 second-year undergraduates at the University of Kelaniya selected using stratified-cluster sampling. Construct-validity of UniHRB-Inventory-Sinhala was assessed using Principal Component Analysis (PCA) (n=333), Confirmatory Factor Analysis (CFA) (n=333), multi-trait scaling analysis and convergent validity assessment (n=80). Internal consistency and test-retest reliability was assessed in a sub-sample (n=25). Results: There has been a deficit of choices for adapting an HRB tool for undergraduates in Sri Lanka. Violence and injuries, sexual risk behaviours, addictions to mobile phones and the internet are common among undergraduates. Students’ dismissive attitude towards violence and neglecting health behaviours, such as sleep deprivation and poor hygienic practice, were highlighted as important aspects of HRBs. The UniHRB-Inventory (Sinhala) with 70 items showed good face, content and consensual validity. A seven-factor model was identified through PCA, which was confirmed through CFA. UniHRB-Inventory domains and sensation seeking scale (SSS) total score showed correlations between 0.39-0.67. Cronbach’s alpha coefficient of 0.77 and test-retest reliability coefficients of seven domains ranging between 0.74-0.82 indicated high reliability. Conclusions &amp; Recommendations: The newly developed UniHRB -Inventory (Sinhala) is a valid and reliable tool to assess common HRBs among undergraduates in Sri Lanka.

Genetic Variants in Telomerase Reverse Transcriptase Contribute to Solar Lentigines

Solar lentigines (SLs) are a hallmark of human skin aging. They result from chronic exposure to sunlight and other environmental stressors. Recent studies also imply genetic factors, but findings are partially conflicting and lack of replication. Through a multi-trait based analysis strategy, we discovered that genetic variants in telomerase reverse transcriptase were significantly associated with non-facial SL in two EastAsian (Taizhou longitudinal cohort, n= 2,964 and National Survey of Physical Traits, n= 2,954) and one Caucasian population (SALIA, n= 462), top SNP rs2853672 (P-value for Taizhou longitudinal cohort= 1.32× 10‒28 and P-value for National Survey of Physical Traits= 3.66× 10‒17 and P-value for SALIA= 0.0007 and Pmeta= 4.93× 10‒44). The same variants were nominally associated with facial SL but not with other skin aging or skin pigmentation traits. The SL-enhanced allele/haplotype upregulated the transcription of the telomerase reverse transcriptase gene. Of note, well-known telomerase reverse transcriptase‒related aging markers such as leukocyte telomere length and intrinsic epigenetic age acceleration were not associated with SL. Our results indicate a previously unrecognized role of telomerase reverse transcriptase in skin aging‒related lentigines formation.