Extreme Phenotypes Research Articles

Clinical features and search for genetic determinants of postprandial hypoglycemia.

To test whether postprandial hypoglycaemia is an extreme and repeatable phenotype of glucose metabolism. Secondly, we explored the genetic determinants of this phenotype. We conducted this study using data from Pinggu Metabolic Disease Study database (n = 3,345). We selected subjects after an oral glucose tolerance test (OGTT) (2 h, glucose <3 mmol/L_ and compared clinical features with those of normal glucose tolerance (NGT). We additionally selected 75 subjects as super-healthy control group. Whole-exome sequencing (WES) was performed on postprandial hypoglycaemic and super-healthy controls. We also evaluated several candidate genes believed to be important in pancreatic hypoglycaemia. We found 13 participants (0.39%) had an OGTT 2 h glucose <3 mmol/L. Ten patients were men (76.9%). All 13 participants had insulin > 3 uU/mL when postprandial blood glucose levels were <3 mmol/L. WES analysis identified one gene, paternally expressed 3 (PEG3), which had three rare mutations in four patients (30.8%). Minor allele frequencies (MAF) of rare PEG3 mutations were significantly higher in subjects with postprandial hypoglycaemia than in super-healthy controls. Among all four subjects with PEG3 gene mutations, 71.4% were men, and their body mass index (BMI) was significantly lower than that of the NGT. Postprandial hypoglycaemia is an extreme and reproducible phenotype in the general population. PEG3 mutations may represent a potential genetic aetiology for postprandial hypoglycaemia. Further research with larger and more diverse populations and a broader genetic focus is needed to understand the genetic basis of postprandial hypoglycaemia.

Association between high versus low cardiovascular risk in individuals with corresponding unexpected absent versus severe subclinical coronary atherosclerosis, a nationwide, multicenter study

Abstract Background It remains unclear as to why some individuals at low risk of cardiovascular disease (CVD) develop severe coronary atherosclerosis, while those at high CVD risk may remain free from coronary atherosclerosis. Purpose Using Coronary Computed Tomography Angiography (CCTA), we aimed to identify factors associated with absence and severe coronary atherosclerosis in subjects from the general population with very high and low-moderate CVD risk, respectively. Methods We assessed cross-sectionally a nationwide, multicenter population-based cohort, consisting of 30,154 individuals randomly recruited from the general population (age range 50-64 years, 51.4% women). Coronary calcified plaque burden was estimated by coronary artery calcium score (CACS) assessed by CCTA. Absent coronary atherosclerosis was defined as CACS 0 and severe coronary atherosclerosis was defined as CACS ≥301. We investigated only individuals with low-moderate (&amp;lt;5%) and very high CVD risk (≥10%) according to SCORE2 were included. Individuals with CACS 0 and prevalent CVD were excluded, as well as those with moderate CACS (1-300) or SCORE2 risk 5-9%. Out of 26 722 subjects with complete data on CACS and SCORE2, 13 075 were included. Logistic regression was performed adjusted for age and sex. Results The overall distribution of CACS in relation to SCORE2 CVD risk is illustrated in the Figure. Study characteristics are displayed in Table 1. Severe-extensive CACS in combination with low-moderate CVD risk was present in 2.3% (n=296). A further 2.3% (n=311) had very high CVD risk but CACS 0. Factors associated with CACS 0 despite a very-high estimated CVD risk included: lower age, being female, being born in Sweden, not having hypertension or hyperlipidemia, fewer pack-years of smoking, and lower waist circumference in men. On the contrary, severe-extensive CACS despite a low-moderate estimated CVD risk was associated with higher age, being male, being an ex-smoker, reporting more pack-years of smoking, having higher HbA1c, higher BMI, higher waist circumference, and prevalent hyperlipidemia and hypertension (Table 2). Conclusions We identified extreme cardiovascular risk phenotypes (subgroups) in the general population that either lacked coronary calcifications despite being at very high estimated CVD risk or had severe subclinical coronary atherosclerosis despite being at estimated low-moderate CVD risk. Further studies are warranted to elucidate putative enhancing or protective mechanisms explaining this unexpected phenomenon.

Influence of peak exercise-induced blood pressure on basal to apical myocardial wall thickness in elite athletes: a sex-specific CMR study

Abstract Background Understanding the sex-specific physiological remodelling response of the myocardial walls to peak exercise-induced blood pressure (SBPpeak) is essential for distinguishing healthy adaptation from pathological remodelling in athletes. Purpose We investigated how SBPpeak relates to myocardial wall thickness measured using cardiac magnetic resonance imaging (CMR) in elite athletes. Methods Cross-sectional analysis of healthy elite athletes included in the ELITE study who underwent both cardiopulmonary exercise testing (CPET) and CMR. Imaging software’s built-in AI option determined average end-diastolic wall thicknesses of all sixteen AHA-defined segments on short-axis cine images with four-chamber long-axis reference. Our primary metrics of interest were Spearman's correlations between SBPpeak and left ventricular mass indexed to body surface area (LVM/BSA), as well as average wall thickness across the sixteen myocardial segments, stratified by sex and endurance/non-endurance sports status. Secondary analyses involved regression models to evaluate the influence of SBPpeak on myocardial wall thickness, adjusting for sex, body size, CPET variables and sport type. Results In 75 athletes (median age: 24; 71% female; 61% engaged in endurance sports), CPET and CMR were performed within a median interval of 5 months [interquartile range: 1-13 months]. SBPpeak was similar in female and male athletes (170 [160-180] vs. 174 [169-184] mmHg, p=0.121, respectively) and in endurance and non-endurance athletes (both 170 [160-180] mmHg, p=0.625). Female elite athletes showed weak to moderate positive correlations between SBPpeak and the majority of basal and mid-ventricular AHA segments (rho = 0.27 – 0.48, Figure). This was most pronounced in the mid-ventricular anterolateral segment (AHA06: rho = 0.48, p&amp;lt;0.001). LVM/BSA in females was positively correlated with SBPpeak (rho = 0.31, p=0.025). Male elite athletes demonstrated greater absolute wall thickness across all AHA segments compared to females, however, there was a moderate correlation with SBPpeak exclusive to the basal anterior segment (AHA01: rho = 0.48, p=0.028). Backward stepwise multivariate regression analyses (Table) revealed SBPpeak as an independent predictor of the thickness of all basal AHA segments except for the basal inferoseptal segment (AHA03), and the mid-anterior and anterolateral segments. Associationswere maintained after adjustment for maximum wattage, body surface area, and sex, with type of sports consistently excluded from the models. Conclusion In the extreme phenotypes of elite athletes, SBPpeak correlates especially with basal myocardial thickness, independent of sex, BSA and maximum work rate influences. We found stronger associations between SBPpeak and myocardial adaptation in female athletes. These findings suggest a paramount role of exercise-induced blood pressure on basal myocardial remodelling surpassing the effect of sports type.Figure:segmental polar plot (heat map)Table:GAM regression models

Engineering quantitative stomatal trait variation and local adaptation potential by cis-regulatory editing.

Cis-regulatory element editing can generate quantitative trait variation that mitigates extreme phenotypes and harmful pleiotropy associated with coding sequence mutations. Here, we applied a multiplexed CRISPR/Cas9 approach, informed by bioinformatic datasets, to generate genotypic variation in the promoter of OsSTOMAGEN, a positive regulator of rice stomatal density. Engineered genotypic variation corresponded to broad and continuous variation in stomatal density, ranging from 70% to 120% of wild-type stomatal density. This panel of stomatal variants was leveraged in physiological assays to establish discrete relationships between stomatal morphological variation and stomatal conductance, carbon assimilation and intrinsic water use efficiency in steady-state and fluctuating light conditions. Additionally, promoter alleles were subjected to vegetative drought regimes to assay the effects of the edited alleles on developmental response to drought. Notably, the capacity for drought-responsive stomatal density reprogramming in stomagen and two cis-regulatory edited alleles was reduced. Collectively our data demonstrate that cis-regulatory element editing can generate near-isogenic trait variation that can be leveraged for establishing relationships between anatomy and physiology, providing a basis for optimizing traits across diverse environments.

Extreme-Phenotype Genome-Wide Association Analysis for Growth Traits in Spotted Sea Bass (Lateolabrax maculatus) Using Whole-Genome Resequencing.

Spotted sea bass (Lateolabrax maculatus) is an important marine economic fish in China, ranking third in annual production among marine fish. However, a declined growth rate caused by germplasm degradation has severely increased production costs and reduced economic benefits. There is an urgent need to develop the fast-growing varieties of L. maculatus and elucidate the genetic mechanisms underlying growth traits. Here, whole-genome resequencing technology combined with extreme phenotype genome-wide association analysis (XP-GWAS) was used to identify candidate markers and genes associated with growth traits in L. maculatus. Two groups of L. maculatus, consisting of 100 fast-growing and 100 slow-growing individuals with significant differences in body weight, body length, and carcass weight, underwent whole-genome resequencing. A total of 4,528,936 high-quality single nucleotide polymorphisms (SNPs) were used for XP-GWAS. These SNPs were evenly distributed across all chromosomes without large gaps, and the average distance between SNPs was only 175.8 bp. XP-GWAS based on the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (Blink) and Fixed and random model Circulating Probability Unification (FarmCPU) identified 50 growth-related markers, of which 17 were related to body length, 19 to body weight, and 23 to carcass weight. The highest phenotypic variance explained (PVE) reached 15.82%. Furthermore, significant differences were observed in body weight, body length, and carcass weight among individuals with different genotypes. For example, there were highly significant differences in body weight among individuals with different genotypes for four SNPs located on chromosome 16: chr16:13133726, chr16:13209537, chr16:14468078, and chr16:18537358. Additionally, 47 growth-associated genes were annotated. These genes are mainly related to the metabolism of energy, glucose, and lipids and the development of musculoskeletal and nervous systems, which may regulate the growth of L. maculatus. Our study identified growth-related markers and candidate genes, which will help to develop the fast-growing varieties of L. maculatus through marker-assisted breeding and elucidate the genetic mechanisms underlying the growth traits.

Trait-customized sampling of core collections from a winter wheat genebank collection supports association studies.

Subsampling a reduced number of accessions from ex situ genebank collections, known as core collections, is a widely applied method for the investigation of stored genetic diversity and for an exploitation by breeding and research. Optimizing core collections for genome-wide association studies could potentially maximize opportunities to discover relevant and rare variation. In the present study, eight strategies to sample core collections were implemented separately for two traits, namely susceptibility to yellow rust and stem lodging, on about 6,300 accessions of winter wheat (Triticum aestivum L.). Each strategy maximized different parameters or emphasized another aspect of the collection; the strategies relied on genomic data, phenotypic data or a combination thereof. The resulting trait-customized core collections of eight different sizes, covering the range between 100 and 800 accession samples, were analyzed based on characteristics such as population stratification, number of duplicate genotypes and genetic diversity. Furthermore, the statistical power for an association study was investigated as a key criterion for comparisons. While sampling extreme phenotypes boosts the power especially for smaller core collections of up to 500 accession samples, maximization of genetic diversity within the core collection minimizes population stratification and avoids the accumulation of less informative duplicate genotypes when increasing the size of a core collection. Advantages and limitations of different strategies to create trait-customized core collections are discussed for different scenarios of the availability of resources and data.

Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags.

Balancing the tradeoff between quantity and quality of phenotypic data is critical in omics studies. Measurements below the limit of quantification (BLQ) are often tagged in quality control fields, but these flags are currently underutilized in human genetics studies. Extreme phenotype sampling is advantageous for mapping rare variant effects. We hypothesize that genetic drivers, along with environmental and technical factors, contribute to the presence of BLQ flags. Here, we introduce "hypometric genetics" (hMG) analysis and uncover a genetic basis for BLQ flags, indicating an additional source of genetic signal for genetic discovery, especially from phenotypic extremes. Applying our hMG approach to n= 227,469UK Biobank individuals with metabolomic profiles, we reveal more than 5% heritability for BLQ flags and report biologically relevant associations, for example, at APOC3, APOA5, and PDE3B loci. For common variants, polygenic scores trained only for BLQ flags predict the corresponding quantitative traits with 91% accuracy, validating the genetic basis. For rare coding variant associations, we find an asymmetric 65.4% higher enrichment of metabolite-lowering associations for BLQ flags, highlighting the impact of putative loss-of-function variants with large effects on phenotypic extremes. Joint analysis of binarized BLQ flags and the corresponding quantitative metabolite measurements improves power in Bayesian rare variant aggregation tests, resulting in an average of 181% more prioritized genes. Our approach is broadly applicable to omics profiling. Overall, our results underscore the benefit of integrating quality control flags and quantitative measurements and highlight the advantage of joint analysis of population-based samples and phenotypic extremes in human genetics studies.

Germline mutations in a G protein identify signaling cross-talk in T cells

Humans with monogenic inborn errors responsible for extreme disease phenotypes can reveal essential physiological pathways. We investigated germline mutations in GNAI2 , which encodes G αi2 , a key component in heterotrimeric G protein signal transduction usually thought to regulate adenylyl cyclase–mediated cyclic adenosine monophosphate (cAMP) production. Patients with activating G αi2 mutations had clinical presentations that included impaired immunity. Mutant G αi2 impaired cell migration and augmented responses to T cell receptor (TCR) stimulation. We found that mutant G αi2 influenced TCR signaling by sequestering the guanosine triphosphatase (GTPase)–activating protein RASA2, thereby promoting RAS activation and increasing downstream extracellular signal–regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase (PI3K)–AKT S6 signaling to drive cellular growth and proliferation.

Identifying individuals at risk for surgical supravalvar aortic stenosis by polygenic risk score with graded phenotyping.

In a previous pathway-based, extreme phenotype study, we identified 1064 variants associated with supravalvar aortic stenosis (SVAS) severity in people with Williams syndrome (WS) and either no SVAS or surgical SVAS. Here, we use those variants to develop and test polygenic risk scores (PRS). We used the clumping and thresholding (CT) approach on the full 1064 variants and a 427-variant subset that was part of 13 biologically relevant pathways identified in the previous study. We also used a lasso approach on the full set. We were able to achieve an area under the curve (AUC) of >0.99 for the two CT PRS methods, using only 622 and 320 variants respectively when 2/3 of the initial 217 participants data were used for training and 1/3 for testing. The lasso performed less well. We then evaluated the performance of those PRS variant sets on an additional group of 138 patients with WS with intermediate severity SVAS and found a misclassification rate of <10% between the surgical and intermediate groups, suggesting potential for clinical utility of the score.

198 Discovery of key functional SNP markers associated with feed efficiency in beef cattle

Abstract Beef production contributes to approximately 2.4% of the total Greenhouse Gas emissions in Canada. Improving beef cattle feed efficiency (FE) may lead to improved energy partitioning and resource use, thereby improving the sustainability of the beef industry. Our objective was to identify differentially expressed key regulatory genes and associated novel functional SNP markers linked to FE in Canadian beef cattle using RNA-Sequencing (RNA-Seq) of rumen tissue collected from 48 beef cattle [n = 16 Angus, n = 16 Charolais, n = 16 Kinsella (Composite Hybrid including Angus, Charolais, Galloway, Hereford, Holstein, Brown Swiss, and Simmental)] selected for extreme FE phenotypes. In total, 11 key regulatory genes (MYH1, MYL2, MYLPF, TNNC2, EIF4B, RHOD, TCEANC, CKM, ENSBTAG00000040518, SERPINB2, and USP43) were significantly differentially expressed (DE) between extreme Residual Feed Intake (RFI) groups (low-RFI n = 8, high-RFI n = 8 per breed) using CLC Genomics Workbench (FDR &amp;lt; 0.05; |FC| &amp;gt;2). Using an optimized RNA-Seq variant calling pipeline using STAR and BCFtools, a total of [total (unique to low-RFI, unique to high-RFI)] 75 (36, 39), 78 (42, 36), and 53 (35, 18) uniquely fixed functional SNPs were located within coding regions of these 11 functional candidate genes, in low- and high-RFI animals in the Angus, Charolais, and Kinsella breeds, respectively. Considering all functional SNPs uniquely identified in low- or high-RFI groups for all breed comparisons, the majority of SNPs were identified in MYH1, EIF4B, and SERPINB2 genes, which function together in metabolically demanding biological processes (P &amp;lt; 0.05) related to muscle contraction, muscle system, and muscle filament function processes. Additionally, EIF4B and SERPINB2 genes were found to have a role in signaling pathways that coordinate cell growth and immune function, respectively. Using RNA-Seq to identify key regulatory genes and associated functional SNPs linked to FE may uncover important genetic markers that influence the regulation of FE in beef cattle.

Lack of a genetic risk continuum between pubertal timing in the general population and idiopathic hypogonadotropic hypogonadism.

Pubertal timing is a highly heritable trait in the general population. Recently, a large-scale exome-wide association study has implicated rare variants in six genes (KDM4C, MC3R, MKRN3, PDE10A, TACR3, and ZNF483) as genetic determinants of pubertal timing within the general population. Two of the genes (TACR3, MKRN3) are already implicated in extreme disorders of pubertal timing. This observation suggests that there may be a pervasive "genetic risk continuum" wherein genes that govern pubertal timing in the general population, by extension, may also be causal for rare Mendelian disorders of pubertal timing. Hence, we hypothesized that the four novel genes linked to pubertal timing in the population will also contribute to idiopathic hypogonadotropic hypogonadism (IHH), a genetic disorder characterized by absent puberty. Exome sequencing data from 1322 unrelated IHH probands were reviewed for rare sequence variants (RSVs) (minor allele frequency bins: <1%; <0.1%; <0.01%) in the six genes linked to puberty in the general population. A gene-based rare variant association testing (RVAT) was performed between the IHH cohort and a reference public genomic sequences repository-the Genome Aggregation Database (gnomAD). As expected, RVAT analysis showed that RSVs in TACR3, a known IHH gene, were significantly enriched in the IHH cohort compared to gnomAD cohort across all three MAF bins. However, RVAT analysis of the remaining five genes failed to show any RSV enrichment in the IHH cohort across all MAF bins. Our findings argue strongly against a pervasive genetic risk continuum between pubertal timing in the general population and extreme pubertal phenotypes. The biologic basis of such distinct genetic architectures' merits further evaluation.

Predictive Model for Opioid Use Disorder in Chronic Pain: A Development and Validation Study.

There are several questionnaires for the challenge of anticipating opioid use disorder (OUD). However, many are not specific for chronic non-cancer pain (CNCP) or have been developed in the American population, whose sociodemographic factors are very different from the Spanish population, leading to scarce translation into clinical practice. Thus, the aim of this study is to prospectively validate a predictive model for OUD in Spanish patients under long-term opioids. An innovative two-stage predictive model was developed from retrospective (n = 129) and non-overlapping prospective (n = 100) cohorts of real-world CNCP outpatients. All subjects used prescribed opioids for 6 or more months. Sociodemographic, clinical and pharmacological covariates were registered. Mu-opioid receptor 1 (OPRM1, A118G, rs1799971) and catechol-O-methyltransferase (COMT, G472A, rs4680) genetic variants plus cytochrome P450 2D6 (CYP2D6) liver enzyme phenotypes were also analyzed. The model performance and diagnostic accuracy were calculated. The two-stage model comprised risk factors related to OUD (younger age, work disability and high daily opioid dose) and provided new useful information about other risk factors (low quality of life, OPRM-G allele and CYP2D6 extreme phenotypes). The validation showed a satisfactory accuracy (70% specificity and 75% sensitivity) for our predictive model with acceptable discrimination and goodness of fit. Our study presents the results of an innovative model for predicting OUD in our setting. After external validation, it could represent a change in the paradigm of opioid treatment, helping clinicians to better identify and manage the risks and reduce the side effects and complications.

Identification of candidate genes associated with double flowers via integrating BSA-seq and RNA-seq in Brassica napus

As a Brassica crop, Brassica napus typically has single flowers that contain four petals. The double-flower phenotype of rapeseed has been a desirable trait in China because of its potential commercial value in ornamental tourism. However, few double-flowered germplasms have been documented in B. napus, and knowledge of the underlying genes is limited. Here, B. napus D376 was characterized as a double-flowered strain that presented an average of 10.92 ± 1.40 petals and other normal floral organs. F1, F2 and BC1 populations were constructed by crossing D376 with a single-flowered line reciprocally. Genetic analysis revealed that the double-flower trait was a recessive trait controlled by multiple genes. To identify the key genes controlling the double-flower trait, bulk segregant analysis sequencing (BSA-seq) and RNA-seq analyses were conducted on F2 individual bulks with opposite extreme phenotypes. Through BSA-seq, one candidate interval was mapped at the region of chromosome C05: 14.56–16.17 Mb. GO and KEGG enrichment analyses revealed that the DEGs were significantly enriched in carbohydrate metabolic processes, notably starch and sucrose metabolism. Interestingly, five and thirty-six DEGs associated with floral development were significantly up- and down-regulated, respectively, in the double-flowered plants. A combined analysis of BSA-seq and RNA-seq data revealed that five genes were candidates associated with the double flower trait, and BnaC05.ERS2 was the most promising gene. These findings provide novel insights into the breeding of double-flowered varieties and lay a theoretical foundation for unveiling the molecular mechanisms of floral development in B. napus.

Extreme phenotype sampling and next generation sequencing to identify genetic variants associated with tacrolimus in African American kidney transplant recipients.

African American (AA) kidney transplant recipients (KTRs) have poor outcomes, which may in-part be due to tacrolimus (TAC) sub-optimal immunosuppression. We previously determined the common genetic regulators of TAC pharmacokinetics in AAs which were CYP3A5 *3, *6, and *7. To identify low-frequency variants that impact TAC pharmacokinetics, we used extreme phenotype sampling and compared individuals with extreme high (n = 58) and low (n = 60) TAC troughs (N = 515 AA KTRs). Targeted next generation sequencing was conducted in these two groups. Median TAC troughs in the high group were 7.7 ng/ml compared with 6.3 ng/ml in the low group, despite lower daily doses of 5 versus 12 mg, respectively. Of 34,542 identified variants across 99 genes, 1406 variants were suggestively associated with TAC troughs in univariate models (p-value < 0.05), however none were significant after multiple testing correction. We suggest future studies investigate additional sources of TAC pharmacokinetic variability such as drug-drug-gene interactions and pharmacomicrobiome.

SLC30A9: an evolutionarily conserved mitochondrial zinc transporter essential for mammalian early embryonic development

SLC30A9 (ZnT9) is a mitochondria-resident zinc transporter. Mutations in SLC30A9 have been reported in human patients with a novel cerebro-renal syndrome. Here, we show that ZnT9 is an evolutionarily highly conserved protein, with many regions extremely preserved among evolutionarily distant organisms. In Drosophila melanogaster (the fly), ZnT9 (ZnT49B) knockdown results in acutely impaired movement and drastic mitochondrial deformation. Severe Drosophila ZnT9 (dZnT9) reduction and ZnT9-null mutant flies are pupal lethal. The phenotype of dZnT9 knockdown can be partially rescued by mouse ZnT9 expression or zinc chelator TPEN, indicating the defect of dZnT9 loss is indeed a result of zinc dyshomeostasis. Interestingly, in the mouse, germline loss of Znt9 produces even more extreme phenotypes: the mutant embryos exhibit midgestational lethality with severe development abnormalities. Targeted mutagenesis of Znt9 in the mouse brain leads to serious dwarfism and physical incapacitation, followed by death shortly. Strikingly, the GH/IGF-1 signals are almost non-existent in these tissue-specific knockout mice, consistent with the medical finding in some human patients with severe mitochondrial deficiecny. ZnT9 mutations cause mitochondrial zinc dyshomeostasis, and we demonstrate mechanistically that mitochondrial zinc elevation quickly and potently inhibits the activities of respiration complexes. These results reveal the critical role of ZnT9 and mitochondrial zinc homeostasis in mammalian development. Based on our functional analyses, we finally discussed the possible nature of the so far identified human SLC30A9 mutations.

Genetic and Physiological Insights into Salt Resistance in Rice through Analysis of Germination, Seedling Traits, and QTL Identification.

Understanding the genetic basis of salt resistance in crops is crucial for agricultural productivity. This study investigates the phenotypic and genetic basis of salt stress response in rice (Oryza sativa L.), focusing on germination and seedling traits. Under salt stress conditions, significant differences were observed in seed germination and seedling traits between parental LH99 (Indica rice LuHui 99) and SN265 (japonica rice ShenNong 265). Transgressive segregation was evident within the RIL population, indicating complex genetic interactions. Nine QTLs were detected at germination and seedling stages under salt stress, namely qSGE5 and qSGE7 for seed germination energy (SGE); qSGP7 for seed germination percentage (SGP); qSSH7, qSSH9-1, and qSSH9-2 for seeding height (SSH); qSRN6 for root number (SRN); and qSDW6 and qSDW9 for dry weight (SDW). Among them, qSSH9-1 and qSDW9 were localized in the same interval, derived from the salt-resistant parent SN265. PCA revealed distinct trait patterns under salt stress, captured by six PCs explaining 81.12% of the total variance. PC composite scores were used to localize a QTL associated with early salt resistance in rice qESC9, which was located in the same interval as qSSH9-1 and qSDW9, and was subsequently unified under the name qESC9, an important QTL for early-growth salt tolerance in rice. Correlation analysis also confirmed a relationship between alleles of qESC9 and the resistance to salt, underscoring the critical role this locus plays in the determination of overall salt tolerance in rice. Physiological analyses of extreme phenotype lines highlighted the importance of ion exclusion mechanisms in salt-resistant lines, while salt-susceptible lines exhibited elevated oxidative stress and impaired antioxidant defense, contributing to cellular damage. This comprehensive analysis sheds light on the genetic and physiological mechanisms underlying salt stress response in rice, providing valuable insights for breeding programs aimed at enhancing salt resistance in rice.

Widespread natural selection on metabolite levels in humans.

Natural selection acts ubiquitously on complex human traits, predominantly constraining the occurrence of extreme phenotypes (stabilizing selection). These constraints propagate to DNA sequence variants associated with traits under selection. The genetic signatures of such evolutionary events can thus be detected via combining effect size estimates from genetic association studies and the corresponding allele frequencies. Although this approach has been successfully applied to high-level traits, the prevalence and mode of selection acting on molecular traits remain poorly understood. Here, we estimate the action of natural selection on genetic variants associated with metabolite levels, an important layer of molecular traits. By leveraging summary statistics of published genome-wide association studies with large sample sizes, we find strong evidence of stabilizing selection for 15 out of 97 plasma metabolites, with nonessential amino acids displaying especially strong selection signatures. Mendelian randomization analysis reveals that metabolites under stronger stabilizing selection display larger effects on a range of clinically relevant complex traits, suggesting that maintaining a disease-free profile may be an important source of selective constraints on the metabolome. Metabolites under strong stabilizing selection in humans are also more conserved in their concentrations among diverse mammalian species, suggesting shared selective forces across micro- and macroevolutionary timescales. Overall, this study demonstrates that variation in metabolite levels among humans is frequently shaped by natural selection and this may act through their causal impact on disease susceptibility.

The proteomic landscape of in vitro cultured endothelial cells across vascular beds

Blood vessel endothelial cells (EC) display heterogeneity across vascular beds, which is anticipated to drive site-specific vascular pathology. This heterogeneity is assessed using transcriptomics in vivo, and functional assays in vitro, but how proteomes compare across human in vitro cultured ECs remains incompletely characterized. We generated an in-depth human EC proteomic landscape (>8000 proteins) across six organs and two in vitro models in steady-state and upon IFNγ-induced inflammation. EC proteomes displayed a high similarity and organ-specific proteins were limited. Variation between ECs was mainly based on proliferation and differentiation processes in which Blood outgrowth endothelial cells (BOEC) and Human umbilical vein cells (HUVEC) represented the extremes of proteomic phenotypes. The IFNγ response was highly conserved across all samples. Harnessing dynamics in protein abundances we delineated VWF and VE-Cadherin correlation networks. This EC landscape provides an extensive proteomic addition in studying EC biology and heterogeneity from an in vitro perspective.

Meta-analysis of genome-wide association studies for cancer therapy-related cardiovascular dysfunction and functional mapping highlight an intergenic region close to TP63

Cancer therapy-related cardiac dysfunction (CTRCD), which commonly includes left ventricular dysfunction and heart failure, is the main adverse effect of anticancer therapy. In recent years several candidate genes studies and genome-wide association studies have identified common genetic variants associated with CTRCD, but evidence remains limited and few genetic variants are robust. A genome-wide meta-analysis of CTRCD was performed with 852 oncology patients receiving cancer therapy. DNA samples were genotyped and imputed to perform a GWAS meta-analysis for case–control (N = 852 (380 cases and 472 controls) and extreme phenotypes (N = 618 (78 cases and 472 controls) looking for genetic variants that predispose to CTRCD. The results were validated in a replicate cohort of 1,191 oncology patients (245 cases and 946 controls). Functional mapping of the replicated loci was then performed. The meta-analysis showed 9 and 17 loci suggestively associated (P-value < 1 × 10–5) with CTRCD in case–control and extreme phenotypes analyses, respectively. The 3q28 locus (rs rs7652759, P = 5.64 × 10–6) in the case–control analysis was the strongest signal, with up to 64 SNPs above the suggestive significance threshold. The rs7652759, an intergenic variant between TPRG1 and TP63 genes, was the only variant validated in the replication cohort (P-value = 0.01). Functional mapping of this significant locus revealed up to 5 new genes potentially involved in the CTRCD. We identified the intergenic region near TP63 as a novel CTRCD susceptibility locus. In the future, the genotyping of these markers could be considered in new CTRCD risk scores to improve preventive strategies in cardio-oncology.

A GWAS study highlights significant associations between a series of indels in a FLOWERING LOCUS T gene promoter and flowering time in white lupin (Lupinus albus L.)

BackgroundWhite lupin (Lupinus albus L.) is a high-protein Old World grain legume with remarkable food and feed production interest. It is sown in autumn or early spring, depending on the local agroclimatic conditions. This study aimed to identify allelic variants associated with vernalization responsiveness, in order to improve our knowledge of legume flowering regulatory pathways and develop molecular selection tools for the desired phenology as required for current breeding and adaptation to the changing climate.ResultsSome 120 white lupin accessions originating from a wide range of environments of Europe, Africa, and Asia were phenotyped under field conditions in three environments with different intensities of vernalization, namely, a Mediterranean and a subcontinental climate sites of Italy under autumn sowing, and a suboceanic climate site of France under spring sowing. Two hundred sixty-two individual genotypes extracted from them were phenotyped in a greenhouse under long-day photoperiod without vernalization. Phenology data, and marker data generated by Diversity Arrays Technology sequencing (DArT-seq) and by PCR-based screening targeting published quantitative trait loci (QTLs) from linkage map and newly identified insertion/deletion polymorphisms in the promoter region of the FLOWERING LOCUS T homolog, LalbFTc1 gene (Lalb_Chr14g0364281), were subjected to a genome-wide association study (GWAS). Population structure followed differences in phenology and isolation by distance pattern. The GWAS highlighted numerous loci significantly associated with flowering time, including four LalbFTc1 gene promoter deletions: 2388 bp and 2126 bp deletions at the 5’ end, a 264 bp deletion in the middle and a 28 bp deletion at the 3’ end of the promoter. Besides LalbFTc1 deletions, this set contained DArT-seq markers that matched previously published major QTLs in chromosomes Lalb_Chr02, Lalb_Chr13 and Lalb_Chr16, and newly discovered QTLs in other chromosomes.ConclusionsThis study highlighted novel QTLs for flowering time and validated those already published, thereby providing novel evidence on the convergence of FTc1 gene functional evolution into the vernalization pathway in Old World lupin species. Moreover, this research provided the set of loci specific for extreme phenotypes (the earliest or the latest) awaiting further implementation in marker-assisted selection for spring- or winter sowing.