Modeling of African population history using f-statistics is biased when applying all previously proposed SNP ascertainment schemes

f-statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. Not only are they guaranteed to allow robust tests of the fits of proposed models of population history to data when analyzing full genome sequencing data-that is, all single nucleotide polymorphisms (SNPs) in the individuals being analyzed-but they are also guaranteed to allow robust tests of models for SNPs ascertained as polymorphic in a population that is an outgroup in a phylogenetic sense to all groups being analyzed. True "outgroup ascertainment" is in practice impossible in humans because our species has arisen from a substructured ancestral population that does not descend from a homogeneous ancestral population going back many hundreds of thousands of years into the past. However, initial studies suggested that non-outgroup-ascertainment schemes might produce robust enough results using f-statistics, and that motivated widespread fitting of models to data using non-outgroup-ascertained SNP panels such as the "Affymetrix Human Origins array" which has been genotyped on thousands of modern individuals from hundreds of populations, or the "1240k" in-solution enrichment reagent which has been the source of about 70% of published genome-wide data for ancient humans. In this study, we show that while analyses of population history using such panels work well for studies of relationships among non-African populations and one African outgroup, when co-modeling more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans), fitting of f-statistics to such SNP sets is expected to frequently lead to false rejection of true demographic histories, and failure to reject incorrect models. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, has limited statistical power and retains important biases. However, by carrying out simulations of diverse demographic histories, we show that bias in inferences based on f-statistics can be minimized by ascertaining on variants common in a union of diverse African groups; such ascertainment retains high statistical power while allowing co-analysis of archaic and modern groups.

The evolution of mechanisms to produce phenotypic heterogeneity in microorganisms

In bacteria and other microorganisms, the cells within a population often show extreme phenotypic variation. Different species use different mechanisms to determine how distinct phenotypes are allocated between individuals, including coordinated, random, and genetic determination. However, it is not clear if this diversity in mechanisms is adaptive-arising because different mechanisms are favoured in different environments-or is merely the result of non-adaptive artifacts of evolution. We use theoretical models to analyse the relative advantages of the two dominant mechanisms to divide labour between reproductives and helpers in microorganisms. We show that coordinated specialisation is more likely to evolve over random specialisation in well-mixed groups when: (i) social groups are small; (ii) helping is more "essential"; and (iii) there is a low metabolic cost to coordination. We find analogous results when we allow for spatial structure with a more detailed model of cellular filaments. More generally, this work shows how diversity in the mechanisms to produce phenotypic heterogeneity could have arisen as adaptations to different environments.

Phenotypic Diversity of Root Characteristics in Recombinant Inbred Lines of Cross Between Lowland and Highland Rice Varieties for Drought Tolerance Potential

<b>Background and Objective:</b> Breeding between highland and lowland rice varieties is one of the strategic breeding of lowland rice for enhancing drought-tolerant capacity through root structure improvement. The objective of this study was to evaluate the phenotypic diversity of rice root traits in pot screening compared to the lowland parent. <b>Materials and Methods:</b> The basket method was utilized in pot cultivation to evaluate the 100 of F7 Recombinant Inbred Lines (RILs) derived through single seed descent method from a cross between lowland rice, RD49 variety and upland rice, Payaleumgaeng (PLG) variety. The two parents and F7 progenies were evaluated for the number of shallow roots (SRN) and the number of deep roots (DRN), together with other traits which were the number of total roots (TRN), the Ratio of Deep Rooting (RDR), maximum Root Length (RL), Root Dry Weight (RDW), Shoot Dry Weight (SDW), the ratio of Root to Shoot Weight (RSR) and Plant Height (PH). <b>Results:</b> The result showed that PLG had significantly higher SRN, DRN, TRN and RDR than RD49. The distribution of these traits showed slightly positive skewness in DRN, RDR, RDW, SDW and RSR and negative skewness in SRN, TRN, RL and PH. However, some lines in this RIL population displayed better performance of root traits compared to both parents. Principal Component Analysis (PCA) of DRN, SRN, TRN and RDR in this population showed a distinctly different pattern among both parents. Most of the selected lines had superior RDR over RD49 and had various root characteristics patterns due to the diverse PCA coordinates. The yield trial of some breeding lines in this cross show superior yield over RD49 under drought-prone cultivation area. <b>Conclusion:</b> This study showed broad phenotypic diversity in the population constructed through single seed descent selection for enhancing deep root structure in rice for drought adaptation.

Genotype Phenotype Correlation in Dent Disease 2 and Review of the Literature: OCRL Gene Pleiotropism or Extreme Phenotypic Variability of Lowe Syndrome?

Dent disease is a rare X-linked renal tubulopathy due to CLCN5 and OCRL (DD2) mutations. OCRL mutations also cause Lowe syndrome (LS) involving the eyes, brain and kidney. DD2 is frequently described as a mild form of LS because some patients may present with extra-renal symptoms (ESs). Since DD2 is a rare disease and there are a low number of reported cases, it is still unclear whether it has a clinical picture distinct from LS. We retrospectively analyzed the phenotype and genotype of our cohort of 35 DD2 males and reviewed all published DD2 cases. We analyzed the distribution of mutations along the OCRL gene and evaluated the type and frequency of ES according to the type of mutation and localization in OCRL protein domains. The frequency of patients with at least one ES was 39%. Muscle findings are the most common ES (52%), while ocular findings are less common (11%). Analysis of the distribution of mutations revealed (1) truncating mutations map in the PH and linker domain, while missense mutations map in the 5-phosphatase domain, and only occasionally in the ASH-RhoGAP module; (2) five OCRL mutations cause both DD2 and LS phenotypes; (3) codon 318 is a DD2 mutational hot spot; (4) a correlation was found between the presence of ES and the position of the mutations along OCRL domains. DD2 is distinct from LS. The mutation site and the mutation type largely determine the DD2 phenotype.

Data integration uncovers the metabolic bases of phenotypic variation in yeast

The relationship between different levels of integration is a key feature for understanding the genotype-phenotype map. Here, we describe a novel method of integrated data analysis that incorporates protein abundance data into constraint-based modeling to elucidate the biological mechanisms underlying phenotypic variation. Specifically, we studied yeast genetic diversity at three levels of phenotypic complexity in a population of yeast obtained by pairwise crosses of eleven strains belonging to two species, Saccharomyces cerevisiae and S. uvarum. The data included protein abundances, integrated traits (life-history/fermentation) and computational estimates of metabolic fluxes. Results highlighted that the negative correlation between production traits such as population carrying capacity (K) and traits associated with growth and fermentation rates (J_max) is explained by a differential usage of energy production pathways: a high K was associated with high TCA fluxes, while a high J_max was associated with high glycolytic fluxes. Enrichment analysis of protein sets confirmed our results.

This powerful approach allowed us to identify the molecular and metabolic bases of integrated trait variation, and therefore has a broad applicability domain.

The integration of data at different levels of cellular organization is an important goal in computational biology for understanding the way the genotypic variation translates into phenotypic variation. Novel profiling technologies and accurate high-throughput phenotyping now allows genomic, transcriptomic, metabolic and proteomic characterization of a large number of individuals under various environmental conditions. However, the metabolic fluxes remain difficult to measure. In this work, we take advantage of recent advances in genome-scale functional annotation and constraint-based metabolic modeling to provide a mathematical framework that allows to estimate internal cellular fluxes from protein abundances and elucidate the biological mechanisms underlying phenotypic variation. Applied to yeast as a model system, this approach highlights that the negative correlation between production traits such as maximum population size and growth and fermentation traits is explained by a differential usage of energy production pathways. The ability to identify molecular and metabolic bases of the variation of integrated traits through population studies has a broad applicability domain.

Tone and genes: New cross-linguistic data and methods support the weak negative effect of the "derived" allele of ASPM on tone, but not of Microcephalin

While it is generally accepted that language and speech have genetic foundations, and that the widespread inter-individual variation observed in many of their aspects is partly driven by variation in genes, it is much less clear if differences between languages may also be partly rooted in our genes. One such proposal is that the population frequencies of the so-called "derived" alleles of two genes involved in brain growth and development, ASPM and Microcephalin, are related to the probability of speaking a tone language or not. The original study introducing this proposal used a cross-linguistic statistical approach, showing that these associations are "special" when compared with many other possible relationships between genetic variants and linguistic features. Recent experimental evidence supports strongly a negative effect of the "derived" allele of ASPM on tone perception and/or processing within individuals, but failed to find any effect for Microcephalin. Motivated by these experimental findings, I conduct here a cross-linguistic statistical test, using a larger and updated dataset of 175 samples from 129 unique (meta)populations, and a battery of methods including mixed-effects regression (Bayesian and maximum-likelihood), mediation and path analysis, decision trees and random forests, using permutations and restricted sampling to control for the confounding effects of genealogy (language families) and contact (macroareas). Overall, the results support a negative weak effect of ASPM-D against the presence of tone above and beyond the strong confounding influences of genealogy and contact, but they suggest that the original association between tone and MCPH1 might have been a false positive, explained by differences between populations and languages within and outside Africa. Thus, these cross-linguistic population-scale statistical results are fully consonant with the inter-individual-level experimental results, and suggest that the observed linguistic diversity may be, at least in some cases, partly driven by genetic diversity.

Pharmacometrics-Based Considerations for the Design of a Pharmacogenomic Clinical Trial Assessing Irinotecan Safety

PURPOSE

Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity.

METHODS

Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CLSN-38: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m2 (-30%)). Study power was assessed given diverse scenarios (n = 50-400 patients/arm, parallel/crossover, varying magnitude of CLSN-38, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing.

RESULTS

The magnitude of CLSN-38 reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (<0.5·109 cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ2/McNemar's test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power.

CONCLUSIONS

The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies.

Identification of high-dimensional omics-derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling

Pharmacometric modeling can capture tumor growth inhibition (TGI) dynamics and variability. These approaches do not usually consider covariates in high-dimensional settings, whereas high-dimensional molecular profiling technologies ("omics") are being increasingly considered for prediction of anticancer drug treatment response. Machine learning (ML) approaches have been applied to identify high-dimensional omics predictors for treatment outcome. Here, we aimed to combine TGI modeling and ML approaches for two distinct aims: omics-based prediction of tumor growth profiles and identification of pathways associated with treatment response and resistance. We propose a two-step approach combining ML using least absolute shrinkage and selection operator (LASSO) regression with pharmacometric modeling. We demonstrate our workflow using a previously published dataset consisting of 4706 tumor growth profiles of patient-derived xenograft (PDX) models treated with a variety of mono- and combination regimens. Pharmacometric TGI models were fit to the tumor growth profiles. The obtained empirical Bayes estimates-derived TGI parameter values were regressed using the LASSO on high-dimensional genomic copy number variation data, which contained over 20,000 variables. The predictive model was able to decrease median prediction error by 4% as compared with a model without any genomic information. A total of 74 pathways were identified as related to treatment response or resistance development by LASSO, of which part was verified by literature. In conclusion, we demonstrate how the combined use of ML and pharmacometric modeling can be used to gain pharmacological understanding in genomic factors driving variation in treatment response.

Leveraging phenotypic variability to identify genetic interactions in human phenotypes

Although thousands of loci have been associated with human phenotypes, the role of gene-environment (GxE) interactions in determining individual risk of human diseases remains unclear. This is partly because of the severe erosion of statistical power resulting from the massive number of statistical tests required to detect such interactions. Here, we focus on improving the power of GxE tests by developing a statistical framework for assessing quantitative trait loci (QTLs) associated with the trait means and/or trait variances. When applying this framework to body mass index (BMI), we find that GxE discovery and replication rates are significantly higher when prioritizing genetic variants associated with the variance of the phenotype (vQTLs) compared to when assessing all genetic variants. Moreover, we find that vQTLs are enriched for associations with other non-BMI phenotypes having strong environmental influences, such as diabetes or ulcerative colitis. We show that GxE effects first identified in quantitative traits such as BMI can be used for GxE discovery in disease phenotypes such as diabetes. A clear conclusion is that strong GxE interactions mediate the genetic contribution to body weight and diabetes risk.

YAP/TAZ deficiency reprograms macrophage phenotype and improves infarct healing and cardiac function after myocardial infarction

Adverse cardiac remodeling after myocardial infarction (MI) causes structural and functional changes in the heart leading to heart failure. The initial post-MI pro-inflammatory response followed by reparative or anti-inflammatory response is essential for minimizing the myocardial damage, healing, and scar formation. Bone marrow–derived macrophages (BMDMs) are recruited to the injured myocardium and are essential for cardiac repair as they can adopt both pro-inflammatory or reparative phenotypes to modulate inflammatory and reparative responses, respectively. Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are the key mediators of the Hippo signaling pathway and are essential for cardiac regeneration and repair. However, their functions in macrophage polarization and post-MI inflammation, remodeling, and healing are not well established. Here, we demonstrate that expression of YAP and TAZ is increased in macrophages undergoing pro-inflammatory or reparative phenotype changes. Genetic deletion of YAP/TAZ leads to impaired pro-inflammatory and enhanced reparative response. Consistently, YAP activation enhanced pro-inflammatory and impaired reparative response. We show that YAP/TAZ promote pro-inflammatory response by increasing interleukin 6 (IL6) expression and impede reparative response by decreasing Arginase-I (Arg1) expression through interaction with the histone deacetylase 3 (HDAC3)-nuclear receptor corepressor 1 (NCoR1) repressor complex. These changes in macrophages polarization due to YAP/TAZ deletion results in reduced fibrosis, hypertrophy, and increased angiogenesis, leading to improved cardiac function after MI. Also, YAP activation augmented MI-induced cardiac fibrosis and remodeling. In summary, we identify YAP/TAZ as important regulators of macrophage-mediated pro-inflammatory or reparative responses post-MI.

Adverse cardiac remodeling after myocardial infarction causes structural and functional changes in the heart, leading to heart failure. This study shows that the Hippo pathway influences post-injury cardiac inflammation by modulating macrophage polarization.

Functional Consequences of Pravastatin Isomerization on OATP1B1-Mediated Transport

Pravastatin acid (PVA) can be isomerized to its inactive metabolite 3'α-iso-pravastatin acid (3αPVA) under acidic pH conditions. Previous studies reported interindividual differences in circulating concentrations of PVA and 3αPVA. This study investigated the functional consequences of PVA isomerization on OATP1B1-mediated transport. We characterized 3αPVA inhibition of OATP1B1-mediated PVA uptake into human embryonic kidney 293 cells expressing the four different OATP1B1 proteins (*1a, *1b, *5, and *15). 3αPVA inhibited OATP1B1-mediated PVA uptake in all four OATP1B1 gene products but with lower IC₅₀/K_i values for OATP1B1*5 and *15 than for the reference proteins (*1a and *1b). PVA and 3αPVA were transported by all four OATP1B1 proteins. Kinetic experiments revealed that maximal transport rates (V_max values) for OATP1B1 variants *5 and *15 were lower than for *1a and *1b for both substrates. Apparent affinities for 3αPVA transport were similar for all four variants. However, the apparent affinity of OATP1B1*5 for 3αPVA was higher (lower K_m value) than for PVA. These data confirm that PVA conversion to 3αPVA can have functional consequences on PVA uptake and impacts OATP1B1 variants more than the reference protein, thus highlighting another source variation that must be taken into consideration when optimizing the PVA dose-exposure relationship for patients. SIGNIFICANCE STATEMENT: 3'α-iso-pravastatin acid inhibits pravastatin uptake for all OATP1B1 protein types; however, the IC₅₀ values were significantly lower in OATP1B1*5 and *15 transfected cells. This suggests that a lower concentration of 3'α-iso-pravastatin is needed to disrupt OATP1B1-mediated pravastatin uptake, secondary to decreased cell surface expression of functional OATP1B1 in variant-expressing cells. These data will refine previous pharmacokinetic models that are utilized to characterize pravastatin interindividual variability with an ultimate goal of maximizing efficacy at the lowest possible risk for toxicity.

High-throughput, image-based phenotyping reveals nutrient-dependent growth facilitation in a grass-legume mixture

This study used high throughput, image-based phenotyping (HTP) to distinguish growth patterns, detect facilitation and interpret variations to nutrient uptake in a model mixed-pasture system in response to factorial low and high nitrogen (N) and phosphorus (P) application. HTP has not previously been used to examine pasture species in mixture. We used red-green-blue (RGB) imaging to obtain smoothed projected shoot area (sPSA) to predict absolute growth (AG) up to 70 days after planting (sPSA, DAP 70), to identify variation in relative growth rates (RGR, DAP 35-70) and detect overyielding (an increase in yield in mixture compared with monoculture, indicating facilitation) in a grass-legume model pasture. Finally, using principal components analysis we interpreted between species changes to HTP-derived temporal growth dynamics and nutrient uptake in mixtures and monocultures. Overyielding was detected in all treatments and was driven by both grass and legume. Our data supported expectations of more rapid grass growth and augmented nutrient uptake in the presence of a legume. Legumes grew more slowly in mixture and where growth became more reliant on soil P. Relative growth rate in grass was strongly associated with shoot N concentration, whereas legume RGR was not strongly associated with shoot nutrients. High throughput, image-based phenotyping was a useful tool to quantify growth trait variation between contrasting species and to this end is highly useful in understanding nutrient-yield relationships in mixed pasture cultivations.

Local and global features of genetic networks supporting a phenotypic switch

Phenotypic switches are associated with alterations in the cell's gene expression profile and are vital to many aspects of biology. Previous studies have identified local motifs of the genetic regulatory network that could underlie such switches. Recent advancements allowed the study of networks at the global, many-gene, level; however, the relationship between the local and global scales in giving rise to phenotypic switches remains elusive. In this work, we studied the epithelial-mesenchymal transition (EMT) using a gene regulatory network model. This model supports two clusters of stable steady-states identified with the epithelial and mesenchymal phenotypes, and a range of intermediate less stable hybrid states, whose importance in cancer has been recently highlighted. Using an array of network perturbations and quantifying the resulting landscape, we investigated how features of the network at different levels give rise to these landscape properties. We found that local connectivity patterns affect the landscape in a mostly incremental manner; in particular, a specific previously identified double-negative feedback motif is not required when embedded in the full network, because the landscape is maintained at a global level. Nevertheless, despite the distributed nature of the switch, it is possible to find combinations of a few local changes that disrupt it. At the level of network architecture, we identified a crucial role for peripheral genes that act as incoming signals to the network in creating clusters of states. Such incoming signals are a signature of modularity and are expected to appear also in other biological networks. Hybrid states between epithelial and mesenchymal arise in the model due to barriers in the interaction between genes, causing hysteresis at all connections. Our results suggest emergent switches can neither be pinpointed to local motifs, nor do they arise as typical properties of random network ensembles. Rather, they arise through an interplay between the nature of local interactions, and the core-periphery structure induced by the modularity of the cell.

Single Nucleotide Polymorphisms in Thyroid Hormone Transporter Genes MCT8, MCT10 and Deiodinase DIO2 Contribute to Inter-Individual Variance of Executive Functions and Personality Traits

Thyroid hormones are modulators of cognitive functions, and changes in hormone levels affect intelligence, memory, attention and executive function. Single nucleotide polymorphisms (SNPs) of transporter proteins MCT8, MCT10 and deiodinase 2 (DIO2) influence thyroid metabolism and could therefore contribute to inter-individual variance of cognitive functions. This study investigates the influence of these SNPs using an extensive neuropsychological test battery. 656 healthy participants aged 18-39 years were genotyped for four SNPs: MCT8 (rs5937843 and rs6647476), MCT10 (rs14399) and DIO2 (rs225014) and underwent eleven different neuropsychological tests as well as four personality questionnaires. Test results were compared between homo- and heterozygous carriers and for the X-linked MCT8 additionally between men and women. Personality questionnaires revealed that Risk Seeking was reduced in homozygous T carriers and highest in homozygous C carriers of the DIO2 SNP and that both polymorphisms of MCT8 had an additive effect on Physical Aggression in men. Neuropsychological testing indicated that MCT10 affects nonverbal reasoning abilities, DIO2 influences working memory and verbal fluency and MCT8 influences attention, alertness and planning. This pilot study suggests an influence of polymorphisms in thyroid hormone transporter genes and deiodinase on cognitive domains and personality traits.

Molecular Evidence for Hybrid Origin and Phenotypic Variation of Rosa Section Chinenses

Rosa sect. Chinenses (Rosaceae) is an important parent of modern rose that is widely distributed throughout China and plays an important role in breeding and molecular biological research. R. sect. Chinenses has variable morphological traits and mixed germplasm. However, the taxonomic status and genetic background of sect. Chinenses varieties remain unclear. In this study, we collected germplasm resources from sect. Chinenses varieties with different morphological traits. Simple sequence repeat (SSR) markers, chloroplast markers, and single copy nuclear markers were used to explore the genetic background of these germplasm resources. We described the origin of hybridization of rose germplasm resources by combining different molecular markers. The results showed that the flower and hip traits of different species in R. sect. Chinenses were significantly different. The SSR analysis showed that the two wild type varieties have different genetic backgrounds. The double petal varieties of R. sect. Chinenses could be hybrids of two wild type varieties. A phylogenetic analysis showed that the maternal inheritance of sect. Chinenses varieties had two different origins. To some extent, variation in the morphological traits of double petal species of R. sect. Chinenses reflects the influence of cultivation process. This study emphasizes that different genetic markers vary in their characteristics. Therefore, analyzing different genetic markers in could provide an insight into highly heterozygous species.

Genomic imprinting analyses identify maternal effects as a cause of phenotypic variability in type 1 diabetes and rheumatoid arthritis

Imprinted genes, giving rise to parent-of-origin effects (POEs), have been hypothesised to affect type 1 diabetes (T1D) and rheumatoid arthritis (RA). However, maternal effects may also play a role. By using a mixed model that is able to simultaneously consider all kinds of POEs, the importance of POEs for the development of T1D and RA was investigated in a variance components analysis. The analysis was based on Swedish population-scale pedigree data. With P = 0.18 (T1D) and P = 0.26 (RA) imprinting variances were not significant. Explaining up to 19.00% (± 2.00%) and 15.00% (± 6.00%) of the phenotypic variance, the maternal environmental variance was significant for T1D (P = 1.60 × 10-24) and for RA (P = 0.02). For the first time, the existence of maternal genetic effects on RA was indicated, contributing up to 16.00% (± 3.00%) of the total variance. Environmental factors such as the social economic index, the number of offspring, birth year as well as their interactions with sex showed large effects.

Human variability in isoform-specific UDP-glucuronosyltransferases: markers of acute and chronic exposure, polymorphisms and uncertainty factors

UDP-glucuronosyltransferases (UGTs) are involved in phase II conjugation reactions of xenobiotics and differences in their isoform activities result in interindividual kinetic differences of UGT probe substrates. Here, extensive literature searches were performed to identify probe substrates (14) for various UGT isoforms (UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT2B7 and UGT2B15) and frequencies of human polymorphisms. Chemical-specific pharmacokinetic data were collected in a database to quantify interindividual differences in markers of acute (Cmax) and chronic (area under the curve, clearance) exposure. Using this database, UGT-related uncertainty factors were derived and compared to the default factor (i.e. 3.16) allowing for interindividual differences in kinetics. Overall, results show that pharmacokinetic data are predominantly available for Caucasian populations and scarce for other populations of different geographical ancestry. Furthermore, the relationships between UGT polymorphisms and pharmacokinetic parameters are rarely addressed in the included studies. The data show that UGT-related uncertainty factors were mostly below the default toxicokinetic uncertainty factor of 3.16, with the exception of five probe substrates (1-OH-midazolam, ezetimibe, raltegravir, SN38 and trifluoperazine), with three of these substrates being metabolised by the polymorphic isoform 1A1. Data gaps and future work to integrate UGT-related variability distributions with in vitro data to develop quantitative in vitro–in vivo extrapolations in chemical risk assessment are discussed.

Extensive literature search of human kinetic parameters for UGT probe substrates.

Bayesian meta-analysis quantifying human variability in acute and chronic kinetic parameters.

UGT isoform-related uncertainty factors were below the 3.16 kinetic default uncertainty factor for most probe substrates.

Quantifying human variability in UGT polymorphisms.

Effect of Phenotype Selection on Genome Size Variation in Two Species of Diptera

Genome size varies widely across organisms yet has not been found to be related to organismal complexity in eukaryotes. While there is no evidence for a relationship with complexity, there is evidence to suggest that other phenotypic characteristics, such as nucleus size and cell-cycle time, are associated with genome size, body size, and development rate. However, what is unknown is how the selection for divergent phenotypic traits may indirectly affect genome size. Drosophila melanogaster were selected for small and large body size for up to 220 generations, while Cochliomyia macellaria were selected for 32 generations for fast and slow development. Size in D. melanogaster significantly changed in terms of both cell-count and genome size in isolines, but only the cell-count changed in lines which were maintained at larger effective population sizes. Larger genome sizes only occurred in a subset of D. melanogaster isolines originated from flies selected for their large body size. Selection for development time did not change average genome size yet decreased the within-population variation in genome size with increasing generations of selection. This decrease in variation and convergence on a similar mean genome size was not in correspondence with phenotypic variation and suggests stabilizing selection on genome size in laboratory conditions.

Shared Genetic Control of Root System Architecture between Zea mays and Sorghum bicolor

Determining the genetic control of root system architecture (RSA) in plants via large-scale genome-wide association study (GWAS) requires high-throughput pipelines for root phenotyping. We developed Core Root Excavation using Compressed-air (CREAMD), a high-throughput pipeline for the cleaning of field-grown roots, and Core Root Feature Extraction (COFE), a semiautomated pipeline for the extraction of RSA traits from images. CREAMD-COFE was applied to diversity panels of maize (Zea mays) and sorghum (Sorghum bicolor), which consisted of 369 and 294 genotypes, respectively. Six RSA-traits were extracted from images collected from >3,300 maize roots and >1,470 sorghum roots. Single nucleotide polymorphism (SNP)-based GWAS identified 87 TAS (trait-associated SNPs) in maize, representing 77 genes and 115 TAS in sorghum. An additional 62 RSA-associated maize genes were identified via expression read depth GWAS. Among the 139 maize RSA-associated genes (or their homologs), 22 (16%) are known to affect RSA in maize or other species. In addition, 26 RSA-associated genes are coregulated with genes previously shown to affect RSA and 51 (37% of RSA-associated genes) are themselves transe-quantitative trait locus for another RSA-associated gene. Finally, the finding that RSA-associated genes from maize and sorghum included seven pairs of syntenic genes demonstrates the conservation of regulation of morphology across taxa.

DNA repair and cancer in colon and rectum: Novel players in genetic susceptibility

Interindividual differences in DNA repair systems may play a role in modulating the individual risk of developing colorectal cancer. To better ascertain the role of DNA repair gene polymorphisms on colon and rectal cancer risk individually, we evaluated 15,419 single nucleotide polymorphisms (SNPs) within 185 DNA repair genes using GWAS data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), which included 8,178 colon cancer, 2,936 rectum cancer cases and 14,659 controls. Rs1800734 (in MLH1 gene) was associated with colon cancer risk (p-value = 3.5 × 10-6 ) and rs2189517 (in RAD51B) with rectal cancer risk (p-value = 5.7 × 10-6 ). The results had statistical significance close to the Bonferroni corrected p-value of 5.8 × 10-6 . Ninety-four SNPs were significantly associated with colorectal cancer risk after Binomial Sequential Goodness of Fit (BSGoF) procedure and confirmed the relevance of DNA mismatch repair (MMR) and homologous recombination pathways for colon and rectum cancer, respectively. Defects in MMR genes are known to be crucial for familial form of colorectal cancer but our findings suggest that specific genetic variations in MLH1 are important also in the individual predisposition to sporadic colon cancer. Other SNPs associated with the risk of colon cancer (e.g., rs16906252 in MGMT) were found to affect mRNA expression levels in colon transverse and therefore working as possible cis-eQTL suggesting possible mechanisms of carcinogenesis.

Systematic exploration of predicted destabilizing nonsynonymous single nucleotide polymorphisms (nsSNPs) of human aldehyde oxidase: A Bio-informatics study

Aldehyde Oxidase (hAOX1) is a cytosolic enzyme involved in the metabolism of drugs and xenobiotic compounds. The enzyme belongs to the xanthine oxidase (XO) family of Mo containing enzyme and is a homo-dimer of two 150 kDa monomers. Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs) of hAOX1 have been reported as affecting the ability of the enzyme to metabolize different substrates. Some of these nsSNPs have been biochemically and structurally characterized but the lack of a systematic and comprehensive study regarding all described and validated nsSNPs is urgent, due to the increasing importance of the enzyme in drug development, personalized medicine and therapy, as well as in pharmacogenetic studies. The objective of the present work was to collect all described nsSNPs of hAOX1 and utilize a series of bioinformatics tools to predict their effect on protein structure stability with putative implications on phenotypic functional consequences. Of 526 nsSNPs reported in NCBI-dbSNP, 119 are identified as deleterious whereas 92 are identified as nondeleterious variants. The stability analysis was performed for 119 deleterious variants and the results suggest that 104 nsSNPs may be responsible for destabilizing the protein structure, whereas five variants may increase the protein stability. Four nsSNPs do not have any impact on protein structure (neutral nsSNPs) of hAOX1. The prediction results of the remaining six nsSNPs are nonconclusive. The in silico results were compared with available experimental data. This methodology can also be used to identify and prioritize the stabilizing and destabilizing variants in other enzymes involved in drug metabolism.

Nucleoside diphosphate-linked moiety X-type motif 15 R139C genotypes impact 6-thioguanine nucleotide cut-off levels to predict thiopurine-induced leukopenia in Crohn’s disease patients

BACKGROUND

Thiopurine-induced leukopenia (TIL) is a life-threatening toxicity and occurs with a high frequency in the Asian population. Although nucleoside diphosphate-linked moiety X-type motif 15 (NUDT15) variants significantly improve the predictive sensitivity of TIL, more than 50% of cases of this toxicity cannot be predicted by this mutation. The potential use of the 6-thioguanine nucleotide (6TGN) level to predict TIL has been explored, but no decisive conclusion has been reached. Can we increase the predictive sensitivity based on 6TGN by subgrouping patients according to their NUDT15 R139C genotypes?

AIM

To determine the 6TGN cut-off levels after dividing patients into subgroups according to their NUDT15 R139C genotypes.

METHODS

Patients’ clinical and epidemiological characteristics were collected from medical records from July 2014 to February 2017. NUDT15 R139C, thiopurine S-methyltransferase, and 6TGN concentrations were measured.

RESULTS

A total of 411 Crohn’s disease patients were included. TIL was observed in 72 individuals with a median 6TGN level of 323.4 pmol/8 × 10⁸ red blood cells (RBC), which was not different from that of patients without TIL (P = 0.071). Then, we compared the 6TGN levels based on NUDT15 R139C. For CC (n = 342) and CT (n = 65) genotypes, the median 6TGN level in patients with TIL was significantly higher than that in patients without (474.8 vs 306.0 pmol/8 × 10⁸ RBC, P = 9.4 × 10^-5; 291.7 vs 217.6 pmol/8 × 10⁸ RBC, P = 0.039, respectively). The four TT carriers developed TIL, with a median 6TGN concentration of 135.8 pmol/8 × 10⁸ RBC. The 6TGN cut-off levels were 411.5 and 319.2 pmol/8 × 10⁸ RBC for the CC and CT groups, respectively.

CONCLUSION

The predictive sensitivity of TIL based on 6TGN is dramatically increased after subgrouping according to NUDT15 R139C genotypes. Applying 6TGN cut-off levels to adjust thiopurine therapies based on NUDT15 is strongly recommended.

Low genetic differentiation yet high phenotypic variation in the invasive populations of Spartina alterniflora in Guangxi, China

Genetic variation and population structure may reflect important information for invasion success of exotic plant species and thus help improve management of invasive plants. Spartina alterniflora is an invasive plant that is a major threat to the economy and environment of the coastal regions in China. We analyzed the genetic structure and diversity of six populations of S. alterniflora differing in invasion histories in Guangxi, China. A total of 176 individuals from the six populations produced 348 AFLP fragments. The average heterozygosity was significantly lower than in the native population. And genetic bottlenecks were also detected in most populations. Standardized FST statistics (Φpt = 0.015) and AMOVA results indicated weak genetic differentiation. Genetic admixture and obviously isolation by distance indicated populations in Guangxi come from a pre-admixed population by a single introduction. High phenotypic variations of S. alterniflora in Guangxi influenced by soil salinity and temperature might be an important reason for the successful invasion.

New insight into bacterial social communication in natural host: Evidence for interplay of heterogeneous and unison quorum response

Many microbes exhibit quorum sensing (QS) to cooperate, share and perform a social task in unison. Recent studies have shown the emergence of reversible phenotypic heterogeneity in the QS-responding pathogenic microbial population under laboratory conditions as a possible bet-hedging survival strategy. However, very little is known about the dynamics of QS-response and the nature of phenotypic heterogeneity in an actual host-pathogen interaction environment. Here, we investigated the dynamics of QS-response of a Gram-negative phytopathogen Xanthomonas pv. campestris (Xcc) inside its natural host cabbage, that communicate through a fatty acid signal molecule called DSF (diffusible signal factor) for coordination of several social traits including virulence functions. In this study, we engineered a novel DSF responsive whole-cell QS dual-bioreporter to measure the DSF mediated QS-response in Xcc at the single cell level inside its natural host plant in vivo. Employing the dual-bioreporter strain of Xcc, we show that QS non-responsive cells coexist with responsive cells in microcolonies at the early stage of the disease; whereas in the late stages, the QS-response is more homogeneous as the QS non-responders exhibit reduced fitness and are out competed by the wild-type. Furthermore, using the wild-type Xcc and its QS mutants in single and mixed infection studies, we show that QS mutants get benefit to some extend at the early stage of disease and contribute to localized colonization. However, the QS-responding cells contribute to spread along xylem vessel. These results contrast with the earlier studies describing that expected cross-induction and cooperative sharing at high cell density in vivo may lead to synchronize QS-response. Our findings suggest that the transition from heterogeneity to homogeneity in QS-response within a bacterial population contributes to its overall virulence efficiency to cause disease in the host plant under natural environment.

Pathogenic bacteria synchronize and coordinate the production of virulence associated function-components in a density dependent fashion via quorum sensing. In general, QS-response and regulation has been studied under laboratory conditions in vitro, where the QS-responding bacterial population exhibits heterogeneous QS-response with the emergence of both QS responders and non-responders irrespective of their parental kind, as a possible bet hedging strategy. However, very little is known about the dynamics of QS-response inside the host. Using Xanthomonas campestris pv. campestris (Xcc) and cabbage as a model plant pathogen-host, we show that there is stage specific interplay of heterogeneous and homogeneous QS-response in the wild-type Xcc population inside the host plant. We show that at the initial stage of the disease, Xcc maintains a stochastically heterogeneous population wherein, the QS non-responders are localized locally and QS-responders contribute to the migration and spread. However at the later stage of disease, the non-responders are outcompeted by the responders, thus minimizing QS signal benefit and in turn maximizing the utilization and optimizing limited recourses in the host. Our findings suggest that the interplay of heterogeneity and homogeneity in QS-response gives a stage specific adaptive advantage in a host-pathogen natural environment.

Candidate screening of blast resistance donors for rice breeding

Rice blast is one of the most serious diseases in the world. The use of resistant cultivars is the most preferred means to control this disease. Resistance often breaks down due to emergence of new races; hence identification of novel resistance donors is indispensable. In this study, a panel of 80 released varieties from National Rice Research Institute, Cuttack was genotyped with 36 molecular markers that were linked to 36 different blast resistance genes, to investigate the varietal genetic diversity and molecular marker-trait association with blast resistance. The polymorphism information content of 36 loci varied from 0.11 to 0.37 with an average of 0.34. The cluster analysis and population structure categorized the 80 National Rice Research Institute released varieties (NRVs) into three major genetic groups. The principal co-ordinate analysis displays the distribution of resistant and moderately resistant NRVs into different groups. Analysis of molecular variance result demonstrated maximum (97%) diversity within populations and minimum (3%) diversity between populations. Among tested markers, two markers (RM7364 and pi21_79-3) corresponding to the blast resistance genes (Pi56(t) and pi21) were significantly associated and explained a phenotypic variance of 4.9 to 5.1% with the blast resistance. These associated genes could be introgressed through marker-assisted to develop durable blast resistant rice varieties. The selected resistant NRVs could be good donors for the blast resistance in rice crop improvement research.

Construction, characteristics and high throughput molecular screening methodologies in some special breeding populations: a horticultural perspective

Advanced marker technologies are widely used for evaluation of genetic diversity in cultivated crops, wild ancestors, landraces or any special plant genotypes. Developing agricultural cultivars requires the following steps: (i) determining desired characteristics to be improved, (ii) screening genetic resources to help find a superior cultivar, (iii) intercrossing selected individuals, (iv) generating genetically hybrid populations and screening them for agro-morphological or molecular traits, (v) evaluating the superior cultivar candidates, (vi) testing field performance at different locations, and (vii) certifying. In the cultivar development process valuable genes can be identified by creating special biparental or multiparental populations and analysing their association using suitable markers in given populations. These special populations and advanced marker technologies give us a deeper knowledge about the inherited agronomic characteristics. Unaffected by the changing environmental conditions, these provide a higher understanding of genome dynamics in plants. The last decade witnessed new applications for advanced molecular techniques in the area of breeding,with low costs per sample. These, especially, include next-generation sequencing technologies like reduced representation genome sequencing (genotyping by sequencing, restriction site-associated DNA). These enabled researchers to develop new markers, such as simple sequence repeat and single- nucleotide polymorphism, for expanding the qualitative and quantitative information onpopulation dynamics. Thus, the knowledge acquired from novel technologies is a valuable asset for the breeding process and to better understand the population dynamics, their properties, and analysis methods.

An estimator of first coalescent time reveals selection on young variants and large heterogeneity in rare allele ages among human populations

Allele age has long been a focus of population genetic research, primarily because it can be an important clue to the fitness effects of an allele. By virtue of their effects on fitness, alleles under directional selection are expected to be younger than neutral alleles of the same frequency. We developed a new coalescent-based estimator of a close proxy for allele age, the time when a copy of an allele first shares common ancestry with other chromosomes in a sample not carrying that allele. The estimator performs well, including for the very rarest of alleles that occur just once in a sample, with a bias that is typically negative. The estimator is mostly insensitive to population demography and to factors that can arise in population genomic pipelines, including the statistical phasing of chromosomes. Applications to 1000 Genomes Data and UK10K genome data confirm predictions that singleton alleles that alter proteins are significantly younger than those that do not, with a greater difference in the larger UK10K dataset, as expected. The 1000 Genomes populations varied markedly in their distributions for singleton allele ages, suggesting that these distributions can be used to inform models of demographic history, including recent events that are only revealed by their impacts on the ages of very rare alleles.

Genetic determinants of gut microbiota composition and bile acid profiles in mice

The microbial communities that inhabit the distal gut of humans and other mammals exhibit large inter-individual variation. While host genetics is a known factor that influences gut microbiota composition, the mechanisms underlying this variation remain largely unknown. Bile acids (BAs) are hormones that are produced by the host and chemically modified by gut bacteria. BAs serve as environmental cues and nutrients to microbes, but they can also have antibacterial effects. We hypothesized that host genetic variation in BA metabolism and homeostasis influence gut microbiota composition. To address this, we used the Diversity Outbred (DO) stock, a population of genetically distinct mice derived from eight founder strains. We characterized the fecal microbiota composition and plasma and cecal BA profiles from 400 DO mice maintained on a high-fat high-sucrose diet for ~22 weeks. Using quantitative trait locus (QTL) analysis, we identified several genomic regions associated with variations in both bacterial and BA profiles. Notably, we found overlapping QTL for Turicibacter sp. and plasma cholic acid, which mapped to a locus containing the gene for the ileal bile acid transporter, Slc10a2. Mediation analysis and subsequent follow-up validation experiments suggest that differences in Slc10a2 gene expression associated with the different strains influences levels of both traits and revealed novel interactions between Turicibacter and BAs. This work illustrates how systems genetics can be utilized to generate testable hypotheses and provide insight into host-microbe interactions.

A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium

OBJECTIVE

Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentially distinct phenotypes. The purpose of this study was to apply innovative machine learning approaches to KOA phenotyping in order to define progression phenotypes that are potentially more responsive to interventions.

DESIGN

We used publicly available data from the Foundation for the National Institutes of Health (FNIH) osteoarthritis (OA) Biomarkers Consortium, where radiographic (medial joint space narrowing of ≥0.7 mm), and pain progression (increase of ≥9 Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC] points) were defined at 48 months, as four mutually exclusive outcome groups (none, both, pain only, radiographic only), along with an extensive set of covariates. We applied distance weighted discrimination (DWD), direction-projection-permutation (DiProPerm) testing, and clustering methods to focus on the contrast (z-scores) between those progressing by both criteria ("progressors") and those progressing by neither ("non-progressors").

RESULTS

Using all observations (597 individuals, 59% women, mean age 62 years and BMI 31 kg/m2) and all 73 baseline variables available in the dataset, there was a clear separation among progressors and non-progressors (z = 10.1). Higher z-scores were seen for the magnetic resonance imaging (MRI)-based variables than for demographic/clinical variables or biochemical markers. Baseline variables with the greatest contribution to non-progression at 48 months included WOMAC pain, lateral meniscal extrusion, and serum N-terminal pro-peptide of collagen IIA (PIIANP), while those contributing to progression included bone marrow lesions, osteophytes, medial meniscal extrusion, and urine C-terminal crosslinked telopeptide type II collagen (CTX-II).

CONCLUSIONS

Using methods that provide a way to assess numerous variables of different types and scalings simultaneously in relation to an outcome of interest enabled a data-driven approach that identified key variables associated with a progression phenotype.

Predicting (side) effects for patients with inflammatory bowel disease: The promise of pharmacogenetics

Inflammatory bowel disease (IBD) is a chronic and heterogeneous intestinal inflammatory disorder. The medical management of IBD aims for long-lasting disease remission to prevent complications and disease progression. Early introduction of immunosuppression forms the mainstay of medical IBD management. Large inter-individual variability in drug responses, in terms of both efficacy and toxicity, leads to high rates of therapeutic failure in the management of IBD. Better patient stratification is needed to maximize patient benefit and minimize the harm caused by adverse events. Pre-treatment pharmacogenetic testing has the potential to optimize drug selection and dose, and to minimize harm caused by adverse drug reactions. In addition, optimizing the use of cheap conventional drugs, and avoiding expensive ineffective drugs, will lead to a significant reduction in costs. Genetic variation in both TPMT and NUDT15, genes involved in thiopurine metabolism, is associated to an increased risk of thiopurine-induced myelosuppression. Moreover, specific HLA haplotypes confer risk to thiopurine-induced pancreatitis and to immunogenicity to tumor necrosis factor-antagonists, respectively. Falling costs and increased availability of genetic tests allow for the incorporation of pre-treatment genetic tests into clinical IBD management guidelines. In this paper, we review clinically useful pharmacogenetic associations for individualized treatment of patients with IBD and discuss the path from identification of a predictive pharmacogenetic marker to implementation into IBD clinical care.

Asymmetrical selection maintains heritable phenotypic variation between two subspecies of Monardella villosa

PREMISE

Monardella villosa is an evolutionarily young species complex distributed across a large geographic range. Our goal was to determine whether the phenotypic difference between two subspecies of M. villosa was heritable and whether the alternative phenotypes were adaptive to their respective local habitats.

METHODS

We collected seeds from 25 populations of M. villosa, 14 from subspecies franciscana, which grows closer to the coast, and 11 from subspecies villosa, which has a larger and more inland geographic distribution. We reciprocally transplanted the two subspecies into their respective habitats and compared plant germination, post-emergence survival, and growth. We used linear mixed models to quantify the effects of genotype and environment to determine whether subspecies were locally adapted and whether leaf traits that distinguish these subspecies were genetically based.

RESULTS

Plants of both subspecies grown at the coastal site had significantly lower survival and biomass than the inland site. The subspecies were not locally adapted; however, the coastal subspecies franciscana did have a home site advantage. We also found that distinctive leaf morphological traits were genetically based, with high broad-sense heritability of traits.

CONCLUSIONS

The two subspecies of Monardella villosa were not locally adapted to their respective habitat, but rather we found that selection for local genotypes may be stronger at the coastal site. Despite the lack of evidence for local adaptation in the strict sense, the subspecies had heritable variation in several leaf phenotypes, indicating that heterogeneous selection imposes an adaptive trade-off for leaf trichome production within this species.

Pharmacology and pharmacogenetics of prednisone and prednisolone in patients with nephrotic syndrome

Nephrotic syndrome is one of the most common glomerular disorders in childhood. Glucocorticoids have been the cornerstone of the treatment of childhood nephrotic syndrome for several decades, as the majority of children achieves complete remission after prednisone or prednisolone treatment. Currently, treatment guidelines for the first manifestation and relapse of nephrotic syndrome are mostly standardized, while large inter-individual variation is present in the clinical course of disease and side effects of glucocorticoid treatment. This review describes the mechanisms of glucocorticoid action and clinical pharmacokinetics and pharmacodynamics of prednisone and prednisolone in nephrotic syndrome patients. However, these mechanisms do not account for the large inter-individual variability in the response to glucocorticoid treatment. Previous research has shown that genetic factors can have a major influence on the pharmacokinetic and dynamic profile of the individual patient. Therefore, pharmacogenetics may have a promising role in personalized medicine for patients with nephrotic syndrome. Currently, little is known about the impact of genetic polymorphisms on glucocorticoid response and steroid-related toxicities in children with nephrotic syndrome. Although the evidence is limited, the data summarized in this study do suggest a role for pharmacogenetics to improve individualization of glucocorticoid therapy. Therefore, studies in larger cohorts with nephrotic syndrome patients are necessary to draw final conclusions about the influence of genetic polymorphisms on the glucocorticoid response and steroid-related toxicities to ultimately implement pharmacogenetics in clinical practice.

When HbA1c and Blood Glucose Do Not Match: How Much Is Determined by Race, by Genetics, by Differences in Mean Red Blood Cell Age?

Commentary placing genetic ancestry markers and racial difference in HbA1c in the context of more common variations in the HbA1c-average glucose relationship and their clinical implications.

Clinical exome sequencing reveals locus heterogeneity and phenotypic variability of cohesinopathies

PURPOSE

Defects in the cohesin pathway are associated with cohesinopathies, notably Cornelia de Lange syndrome (CdLS). We aimed to delineate pathogenic variants in known and candidate cohesinopathy genes from a clinical exome perspective.

METHODS

We retrospectively studied patients referred for clinical exome sequencing (CES, N = 10,698). Patients with causative variants in novel or recently described cohesinopathy genes were enrolled for phenotypic characterization.

RESULTS

Pathogenic or likely pathogenic single-nucleotide and insertion/deletion variants (SNVs/indels) were identified in established disease genes including NIPBL (N = 5), SMC1A (N = 14), SMC3 (N = 4), RAD21 (N = 2), and HDAC8 (N = 8). The phenotypes in this genetically defined cohort skew towards the mild end of CdLS spectrum as compared with phenotype-driven cohorts. Candidate or recently reported cohesinopathy genes were supported by de novo SNVs/indels in STAG1 (N = 3), STAG2 (N = 5), PDS5A (N = 1), and WAPL (N = 1), and one inherited SNV in PDS5A. We also identified copy-number deletions affecting STAG1 (two de novo, one of unknown inheritance) and STAG2 (one of unknown inheritance). Patients with STAG1 and STAG2 variants presented with overlapping features yet without characteristic facial features of CdLS.

CONCLUSION

CES effectively identified disease-causing alleles at the mild end of the cohensinopathy spectrum and enabled characterization of candidate disease genes.

Variation in the repulsive guidance molecule family in human populations

Repulsive guidance molecules, RGMA, RGMB, and RGMC, are related proteins discovered independently through different experimental paradigms. They are encoded by single copy genes in mammalian and other vertebrate genomes, and are ~50% identical in amino acid sequence. The importance of RGM actions in human physiology has not been realized, as most research has focused on non-human models, although mutations in RGMC are the cause of the severe iron storage disorder, juvenile hemochromatosis. Here I show that repositories of human genomic and population genetic data can be used as starting points for discovery and for developing new testable hypotheses about each of these paralogs in human biology and disease susceptibility. Information was extracted, aggregated, and analyzed from the Ensembl and UCSC Genome Browsers, the Exome Aggregation Consortium, the Genotype-Tissue Expression project portal, the cBio portal for Cancer Genomics, and the National Cancer Institute Genomic Data Commons data site. Results identify extensive variation in gene expression patterns, substantial alternative RNA splicing, and possible missense alterations and other modifications in the coding regions of each of the three genes, with many putative mutations being detected in individuals with different types of cancers. Moreover, selected amino acid substitutions are highly prevalent in the world population, with minor allele frequencies of up to 37% for RGMA and up to 8% for RGMB. These results indicate that protein sequence variation is common in the human RGM family, and raises the possibility that individual variants will have a significant population impact on human physiology and/or disease predisposition.

A high-throughput and open-source platform for embryo phenomics

Phenomics has the potential to facilitate significant advances in biology but requires the development of high-throughput technologies capable of generating and analysing high-dimensional data. There are significant challenges associated with building such technologies, not least those required for investigating dynamic processes such as embryonic development, during which high rates of temporal, spatial, and functional change are inherently difficult to capture. Here, we present EmbryoPhenomics, an accessible high-throughput platform for phenomics in aquatic embryos comprising an Open-source Video Microscope (OpenVIM) that produces high-resolution videos of multiple embryos under tightly controlled environmental conditions. These videos are then analysed by the Python package Embryo Computer Vision (EmbryoCV), which extracts phenomic data for morphological, physiological, behavioural, and proxy traits during the process of embryonic development. We demonstrate the broad-scale applicability of EmbryoPhenomics in a series of experiments assessing chronic, acute, and multistressor responses to environmental change (temperature and salinity) in >30 million images of >600 embryos of two species with markedly different patterns of development—the pond snail Radix balthica and the marine amphipod Orchestia gammarellus. The challenge of phenomics is significant but so too are the rewards, and it is particularly relevant to the urgent task of assessing complex organismal responses to current rates of environmental change. EmbryoPhenomics can acquire and process data capturing functional, temporal, and spatial responses in the earliest, most dynamic life stages and is potentially game changing for those interested in studying development and phenomics more widely.

EmbryoPhenomics is an open-source technology platform for high-throughput phenome screening of aquatic embryos. This paper demonstrates its application in experiments assessing the sensitivity of aquatic embryos to environmental stress, consisting of more than 600 embryos and more than 30 million images.

Phenomics is the collection of high-dimensional phenotypic data on an organism-wide scale, and it requires high-throughput technologies. However, a lack of technologies for efficiently visualising and measuring whole-organism responses to different environments represents a serious challenge for biologists. This challenge is most apparent when studying complex responses, such as those occurring during the dynamic period of embryonic development, when the phenotype changes markedly through time. Here, we present EmbryoPhenomics (www.embryophenomics.org), a new open-source technological platform comprising high-throughput bioimaging hardware that produces high-resolution video of multiple, developing embryos maintained under controlled environmental conditions and software for automatically quantifying embryo responses from these videos. We demonstrate the broad applicability of EmbryoPhenomics using four experiments assessing responses to global change (elevated temperature and salinity) in which we generate data for more than 600 embryos produced from video comprising more than 30 million images. EmbryoPhenomics was used to capture functional, temporal, and spatial change in morphological, physiological, and behavioural responses in the earliest, most dynamic life stages and addresses a serious bottleneck in biology. Such capabilities are urgently required, particularly within the context of assessing the response of embryos to the current unprecedented rates of global environmental change.

Heterologous Hsp90 promotes phenotypic diversity through network evolution

Biological processes in living cells are often carried out by gene networks in which signals and reactions are integrated through network hubs. Despite their functional importance, it remains unclear to what extent network hubs are evolvable and how alterations impact long-term evolution. We investigated these issues using heat shock protein 90 (Hsp90), a central hub of proteostasis networks. When native Hsp90 in Saccharomyces cerevisiae cells was replaced by the ortholog from hypersaline-tolerant Yarrowia lipolytica that diverged from S. cerevisiae about 270 million years ago, the cells exhibited improved growth in hypersaline environments but compromised growth in others, indicating functional divergence in Hsp90 between the two yeasts. Laboratory evolution shows that evolved Y. lipolytica-HSP90–carrying S. cerevisiae cells exhibit a wider range of phenotypic variation than cells carrying native Hsp90. Identified beneficial mutations are involved in multiple pathways and are often pleiotropic. Our results show that cells adapt to a heterologous Hsp90 by modifying different subnetworks, facilitating the evolution of phenotypic diversity inaccessible to wild-type cells.

Biological processes in living cells are often carried out by gene networks. Hubs are highly connected network components important for integrating signal inputs and generating responsive functional outputs. Heat shock protein 90 (Hsp90), a versatile hub in the protein homeostasis network, is a molecular chaperone essential for cell viability in all tested eukaryotic cells. In yeast, about a quarter of the expressed proteins are profoundly influenced when Hsp90 activity is reduced. Despite its pivotal role, we found that the function of Hsp90 has diverged between two yeast species, Yarrowia lipolytica and Saccharomyces cerevisiae, which split about 270 million years ago. To understand the impacts and adaptive strategies in cells with an altered network hub, we conducted laboratory evolution experiments using a S. cerevisiae strain in which native Hsp90 is replaced by its counterpart in Y. lipolytica. We observed different fitness gain or loss under various stress conditions in individual evolved clones, suggesting that cells adapted via different evolutionary paths. Genome sequencing and mutation reconstitution experiments show that beneficial mutations occurred in multiple Hsp90-related pathways that interact with each other. Our results show that a perturbed network allows cells to evolve a broader range of phenotypic diversity unavailable to wild-type cells.

Cytometry meets next-generation sequencing - RNA-Seq of sorted subpopulations reveals regional replication and iron-triggered prophage induction in Corynebacterium glutamicum

Phenotypic diversification is key to microbial adaptation. Currently, advanced technological approaches offer insights into cell-to-cell variation of bacterial populations at a spatiotemporal resolution. However, the underlying molecular causes or consequences often remain obscure. In this study, we developed a workflow combining fluorescence-activated cell sorting and RNA-sequencing, thereby allowing transcriptomic analysis of 106 bacterial cells. As a proof of concept, the workflow was applied to study prophage induction in a subpopulation of Corynebacterium glutamicum. Remarkably, both the phage genes and flanking genomic regions of the CGP3 prophage revealed significantly increased coverage upon prophage induction - a phenomenon that to date has been obscured by bulk approaches. Genome sequencing of prophage-induced populations suggested regional replication at the CGP3 locus in C. glutamicum. Finally, the workflow was applied to unravel iron-triggered prophage induction in early exponential cultures. Here, an up-shift in iron levels resulted in a heterogeneous response of an SOS (PdivS) reporter. RNA-sequencing of the induced subpopulation confirmed induction of the SOS response triggering also activation of the CGP3 prophage. The fraction of CGP3-induced cells was enhanced in a mutant lacking the iron regulator DtxR suffering from enhanced iron uptake. Altogether, these findings demonstrate the potential of the established workflow to gain insights into the phenotypic dynamics of bacterial populations.

Genetic basis of thermal plasticity variation in Drosophila melanogaster body size

Body size is a quantitative trait that is closely associated to fitness and under the control of both genetic and environmental factors. While developmental plasticity for this and other traits is heritable and under selection, little is known about the genetic basis for variation in plasticity that can provide the raw material for its evolution. We quantified genetic variation for body size plasticity in Drosophila melanogaster by measuring thorax and abdomen length of females reared at two temperatures from a panel representing naturally segregating alleles, the Drosophila Genetic Reference Panel (DGRP). We found variation between genotypes for the levels and direction of thermal plasticity in size of both body parts. We then used a Genome-Wide Association Study (GWAS) approach to unravel the genetic basis of inter-genotype variation in body size plasticity, and used different approaches to validate selected QTLs and to explore potential pleiotropic effects. We found mostly “private QTLs”, with little overlap between the candidate loci underlying variation in plasticity for thorax versus abdomen size, for different properties of the plastic response, and for size versus size plasticity. We also found that the putative functions of plasticity QTLs were diverse and that alleles for higher plasticity were found at lower frequencies in the target population. Importantly, a number of our plasticity QTLs have been targets of selection in other populations. Our data sheds light onto the genetic basis of inter-genotype variation in size plasticity that is necessary for its evolution.

Environmental conditions can influence development and lead to the production of phenotypes adjusted to the conditions adults will live in. This developmental plasticity, which can help organisms cope with environmental heterogeneity, is heritable and under selection. Its evolution will depend on available genetic variation. Using a panel of D. melanogaster flies representing naturally segregating alleles, we identified DNA sequence variants associated to variation in thermal plasticity for body size. We found that these variants correspond to a diverse set of functions and that their effects differ between body parts and properties of the thermal response. Our results shed new light onto the long discussed genes for plasticity.

A Methodological Assessment and Characterization of Genetically-Driven Variation in Three Human Phosphoproteomes

Phosphorylation of proteins on serine, threonine, and tyrosine residues is a ubiquitous post-translational modification that plays a key part of essentially every cell signaling process. It is reasonable to assume that inter-individual variation in protein phosphorylation may underlie phenotypic differences, as has been observed for practically any other molecular regulatory phenotype. However, we do not know much about the extent of inter-individual variation in phosphorylation because it is quite challenging to perform a quantitative high throughput study to assess inter-individual variation in any post-translational modification. To test our ability to address this challenge with SILAC-based mass spectrometry, we quantified phosphorylation levels for three genotyped human cell lines within a nested experimental framework, and found that genetic background is the primary determinant of phosphoproteome variation. We uncovered multiple functional, biophysical, and genetic associations with germline driven phosphopeptide variation. Variants affecting protein levels or structure were among these associations, with the latter presenting, on average, a stronger effect. Interestingly, we found evidence that is consistent with a phosphopeptide variability buffering effect endowed from properties enriched within longer proteins. Because the small sample size in this 'pilot' study may limit the applicability of our genetic observations, we also undertook a thorough technical assessment of our experimental workflow to aid further efforts. Taken together, these results provide the foundation for future work to characterize inter-individual variation in post-translational modification levels and reveal novel insights into the nature of inter-individual variation in phosphorylation.

The genetic underpinnings of variation in ages at menarche and natural menopause among women from the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) Study: A trans-ethnic meta-analysis

Current knowledge of the genetic architecture of key reproductive events across the female life course is largely based on association studies of European descent women. The relevance of known loci for age at menarche (AAM) and age at natural menopause (ANM) in diverse populations remains unclear. We investigated 32 AAM and 14 ANM previously-identified loci and sought to identify novel loci in a trans-ethnic array-wide study of 196,483 SNPs on the MetaboChip (Illumina, Inc.). A total of 45,364 women of diverse ancestries (African, Hispanic/Latina, Asian American and American Indian/Alaskan Native) in the Population Architecture using Genomics and Epidemiology (PAGE) Study were included in cross-sectional analyses of AAM and ANM. Within each study we conducted a linear regression of SNP associations with self-reported or medical record-derived AAM or ANM (in years), adjusting for birth year, population stratification, and center/region, as appropriate, and meta-analyzed results across studies using multiple meta-analytic techniques. For both AAM and ANM, we observed more directionally consistent associations with the previously reported risk alleles than expected by chance (p-values_binomial≤0.01). Eight densely genotyped reproductive loci generalized significantly to at least one non-European population. We identified one trans-ethnic array-wide SNP association with AAM and two significant associations with ANM, which have not been described previously. Additionally, we observed evidence of independent secondary signals at three of six AAM trans-ethnic loci. Our findings support the transferability of reproductive trait loci discovered in European women to women of other race/ethnicities and indicate the presence of additional trans-ethnic associations both at both novel and established loci. These findings suggest the benefit of including diverse populations in future studies of the genetic architecture of female growth and development.

No unexpected CRISPR-Cas9 off-target activity revealed by trio sequencing of gene-edited mice

CRISPR-Cas9 technologies have transformed genome-editing of experimental organisms and have immense therapeutic potential. Despite significant advances in our understanding of the CRISPR-Cas9 system, concerns remain over the potential for off-target effects. Recent studies have addressed these concerns using whole-genome sequencing (WGS) of gene-edited embryos or animals to search for de novo mutations (DNMs), which may represent candidate changes introduced by poor editing fidelity. Critically, these studies used strain-matched, but not pedigree-matched controls and thus were unable to reliably distinguish generational or colony-related differences from true DNMs. Here we used a trio design and whole genome sequenced 8 parents and 19 embryos, where 10 of the embryos were mutagenised with well-characterised gRNAs targeting the coat colour Tyrosinase (Tyr) locus. Detailed analyses of these whole genome data allowed us to conclude that if CRISPR mutagenesis were causing SNV or indel off-target mutations in treated embryos, then the number of these mutations is not statistically distinguishable from the background rate of DNMs occurring due to other processes.

Sodium ion channel alkaloid resistance does not vary with toxicity in aposematic Dendrobates poison frogs: An examination of correlated trait evolution

Spatial heterogeneity in the strength or agents of selection can lead to geographic variation in ecologically important phenotypes. Many dendrobatid frogs sequester alkaloid toxins from their diets and often exhibit fixed mutations at Na_V1.4, a voltage-gated sodium ion channel associated with alkaloid toxin resistance. Yet previous studies have noted an absence of resistance mutations in individuals from several species known to sequester alkaloid toxins, suggesting possible intraspecific variation for alkaloid resistance in these species. Toxicity and alkaloid profiles vary substantially between populations in several poison frog species (genus Dendrobates) and are correlated with variation in a suite of related traits such as aposematic coloration. If resistance mutations are costly, due to alterations of channel gating properties, we expect that low toxicity populations will have reduced frequencies and potentially even the loss of resistance alleles. Here, we examine whether intraspecific variation in toxicity in three dendrobatid frogs is associated with intraspecific variation in alleles conferring toxin resistance. Specifically, we examine two species that display marked variation in toxicity throughout their native ranges (Dendrobates pumilio and D. granuliferus) and one species with reduced toxicity in its introduced range (D. auratus). However, we find no evidence for population-level variation in alkaloid resistance at Na_V1.4. In fact, contrary to previous studies, we found that alkaloid resistance alleles were not absent in any populations of these species. All three species exhibit fixed alkaloid resistance mutations throughout their ranges, suggesting that these mutations are maintained even when alkaloid sequestration is substantially reduced.

Impact of SNP-SNP interactions of DNA repair gene ERCC5 and metabolic gene GSTP1 on gastric cancer/atrophic gastritis risk in a Chinese population

AIM

To investigate the interactions of the DNA repair gene excision repair cross complementing group 5 (ERCC5) and the metabolic gene glutathione S-transferase pi 1 (GSTP1) and their effects on atrophic gastritis (AG) and gastric cancer (GC) risk.

METHODS

Seven ERCC5 single nucleotide polymorphisms (SNPs) (rs1047768, rs2094258, rs2228959, rs4150291, rs4150383, rs751402, and rs873601) and GSTP1 SNP rs1695 were detected using the Sequenom MassARRAY platform in 450 GC patients, 634 AG cases, and 621 healthy control subjects in a Chinese population.

RESULTS

Two pairwise combinations (ERCC5 rs2094258 and rs873601 with GSTP1 rs1695) influenced AG risk (P_interaction = 0.008 and 0.043, respectively), and the ERCC5 rs2094258-GSTP1 rs1695 SNP pair demonstrated an antagonistic effect, while ERCC5 rs873601-GSTP1 rs1695 showed a synergistic effect on AG risk OR = 0.51 and 1.79, respectively). No pairwise combinations were observed in relation to GC risk. There were no cumulative effects among the pairwise interactions (ERCC5 rs2094258 and rs873601 with GSTP1 rs1695) on AG susceptibility (P_trend > 0.05). When the modification effect of Helicobacter pylori (H. pylori) infection was evaluated, the cumulative effect of one of the aforementioned pairwise interactions (ERCC5 rs873601-GSTP1 rs1695) was associated with an increased AG risk in the case of negative H. pylori status (P_trend = 0.043).

CONCLUSION

There is a multifarious interaction between the DNA repair gene ERCC5 SNPs (rs2094258 and rs873601) and the metabolic gene GSTP1 rs1695, which may form the basis for various inter-individual susceptibilities to AG.

A deep learning and novelty detection framework for rapid phenotyping in high-content screening

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The Quest for Understanding Phenotypic Variation via Integrated Approaches in the Field Environment

Field-based, high-throughput phenotyping enables the detailed characterization of plant populations under relevant conditions, providing valuable biological insight into the life history of plants.