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Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

The pattern of development of the inflorescence is an important characteristic in ornamental plants, where the economic value is in the flower. The genetic determinism of inflorescence architecture is poorly understood, especially in woody perennial plants with long life cycles. Our objective was to study the genetic determinism of this characteristic in rose. The genetic architectures of 10 traits associated with the developmental timing and architecture of the inflorescence, and with flower production were investigated in a F(1) diploid garden rose population, based on intensive measurements of phenological and morphological traits in a field. There were substantial genetic variations in inflorescence development traits, with broad-sense heritabilities ranging from 0.82 to 0.93. Genotypic correlations were significant for most (87%) pairs of traits, suggesting either pleiotropy or tight linkage among loci. However, non-significant and low correlations between some pairs of traits revealed two independent developmental pathways controlling inflorescence architecture: (1) the production of inflorescence nodes increased the number of branches and the production of flowers; (2) internode elongation connected with frequent branching increased the number of branches and the production of flowers. QTL mapping identified six common QTL regions (cQTL) for inflorescence developmental traits. A QTL for flowering time and many inflorescence traits were mapped to the same cQTL. Several candidate genes that are known to control inflorescence developmental traits and gibberellin signaling in Arabidopsis thaliana were mapped in rose. Rose orthologues of FLOWERING LOCUS T (RoFT), TERMINAL FLOWER 1 (RoKSN), SPINDLY (RoSPINDLY), DELLA (RoDELLA), and SLEEPY (RoSLEEPY) co-localized with cQTL for relevant traits. This is the first report on the genetic basis of complex inflorescence developmental traits in rose.

Multiple recent studies highlight that genetic variants can have strong impacts on a significant proportion of the human DNA methylome. Methylation quantitative trait loci, or meQTLs, allow for the exploration of biological mechanisms that underlie complex human phenotypes, with potential insights for human disease onset and progression. In this review, we summarize recent milestones in characterizing the human genetic basis of DNA methylation variation over the last decade, including heritability findings and genome-wide identification of meQTLs. We also discuss challenges in this field and future areas of research geared to generate insights into molecular processes underlying human complex traits.

Many gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue ( https://www.ebi.ac.uk/eqtl ), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues. The eQTL Catalogue provides uniform processing of 21 eQTL studies, allowing the identification of highly reproducible eQTLs affecting whole gene and transcript expression levels.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

• Plant roots exhibit diverse root functional traits to enable soil phosphorus (P) acquisition, including changes in root morphology, root exudation and mycorrhizal symbioses. Yet, whether these traits are differently coordinated among crop species to enhance P acquisition is unclear. • Here, eight root functional traits for P acquisition were characterized in 16 major herbaceous crop species grown in a glasshouse under limiting and adequate soil P availability. • We found substantial interspecific variation in root functional traits among species. Those with thinner roots showed more root branching and less first-order root length, and had consistently lower colonization by arbuscular mycorrhizal fungi (AMF), fewer rhizosheath carboxylates and reduced acid phosphatase activity. In response to limiting soil P, species with thinner roots showed a stronger response in root branching, first-order root length and specific root length of the whole root system, Conversely, species with thicker roots exhibited higher colonization by AMF and/or more P-mobilizing exudates in the rhizosheath. • We conclude that, at the species level, tradeoffs occur among the three groups of root functional traits we examined. Root diameter is a good predictor of the relative expression of these traits and how they change when P is limiting.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P  < 5 × 10 −8 ), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

Modern tomatoes have narrow genetic diversity limiting their improvement potential. We present a tomato pan-genome constructed using genome sequences of 725 phylogenetically and geographically representative accessions, revealing 4,873 genes absent from the reference genome. Presence/absence variation analyses reveal substantial gene loss and intense negative selection of genes and promoters during tomato domestication and improvement. Lost or negatively selected genes are enriched for important traits, especially disease resistance. We identify a rare allele in the TomLoxC promoter selected against during domestication. Quantitative trait locus mapping and analysis of transgenic plants reveal a role for TomLoxC in apocarotenoid production, which contributes to desirable tomato flavor. In orange-stage fruit, accessions harboring both the rare and common TomLoxC alleles (heterozygotes) have higher TomLoxC expression than those homozygous for either and are resurgent in modern tomatoes. The tomato pan-genome adds depth and completeness to the reference genome, and is useful for future biological discovery and breeding. A tomato pan-genome constructed from genome sequences of 725 tomato accessions captures 4,873 genes absent from the reference genome and identifies a rare allele of TomLoxC regulating fruit flavor.

The stability and high yielding of Vigna subterranea L. Verdc. genotype is an important factor for long-term development and food security. The effects of G × E interaction on yield stability in 30 Bambara groundnut genotypes in four different Malaysian environments were investigated in this research. The experiment used a randomized complete block design with three replications in each environment. Over multiple harvests, yield component traits such as the total number of pods per plant, fresh pods weight (g), hundred seeds weight (g), and yield per hectare were evaluated in the main and off-season in 2020 and 2021. Stability tests for multivariate stability parameters were performed based on analyses of variance. For all the traits, the pooled analysis of variance revealed highly significant (p < 0.01) variations between genotypes, locations, seasons, and genotypes by environment (G × E interaction). A two-dimensional GGE biplot was generated using the first two principal components (axis 1 and axis 2), which accounted for 94.97% and 3.11% difference in GEI for yield per hectare, respectively. Season and location were found to be the most significant causes of yield heterogeneity, accounting for 31.13% and 14.02% of overall G + E + G × E variation, respectively, according to the combined study of variance. The GGE biplot revealed that the three winning genotypes G1, G3, and G5 appear across environments whereas AMMI model exposed genotypes viz G18, G14, G7, G3, G1, and G5 as best performer. Based on ideal genotype ranking genotype G1 was the best performer, with a high mean yield and high stability in the tested environment. According to the AEC line, genotypes G1 and G3 were extremely stable, while genotypes G2 and G4 were low stable, with a high average yielding per hectare. A GGE and AMMI biplot graphically showed the interrelationships between the tested environment and genotypes, classified genotypes into three categories as well as simplifying visual evaluations, according to this investigation. According to our results, breeding could improve yield production, and the genotypes discovered could be recommended for commercial cultivation.