Quantitative Phenotypes Research Articles

HSFA1d regulates the kinetics of heat-induced HSP17.6 expression in Arabidopsis.

Arabidopsis contains four HSFA1 heat shock transcription factors ( HSFA1a , HSFA1b , HSFA1d , and HSFA1e ) that regulate the primary response to high temperature stress responses. These genes have overlapping functions and, while double and triple HSFA1 mutants have thermotolerance phenotypes, these genes have no reported single mutant thermotolerance phenotypes. We used an automated fluorescence microscopy system to quantitate the expression of a HSP17. 6:GFP reporter with high temporal resolution to show that HSFA1d is required for normal heat-induced HSP17.6 expression. HSP17.6 expression is reduced and delayed in hsfa1d-1 mutants. This finding highlights the power of using gene expression kinetics as a quantitative phenotype for discovering the function of genes that exhibit functional redundancy.

Diversity in phenotype and genotype among some species of shrimp

Diversity in phenotype depend on morphometric characters and meristic counts of different population of shrimps, (Metapenaeus monoceros monoceros, Penaeus vannamei, Penaeus japonicas, Penaeus semesulacatus, Penaeus penicillatus, Penaeus monodon, Penaeus kerathurus), were measured phylogenetically to detect and compare the amount of differences in phenotypes. The results indicated that there were significant differences (P≤0.05) in most of morphometric characters and meristic counts among different groups tested. The hierarchical cluster analysis depend on quantitative phenotype shrimp species into two major groups; Penaeus vannamei, Penaeus penicillatus, Penaeus monodon and Penaeus semesulacatus species first group and Metapenaeus monoceros monoceros, Penaeus kerathurus and Penaeus japonicas species second group. With inside these major groups, the first group cleared that Penaeus vannamei and Penaeus penicillatus were grouped close together. In addition to the second group showed that Metapenaeus monoceros appears to be more phenotypically similar to that Penaeus kerathurus species than that of Penaeus japonicas. So that, it was achieved in this work that the phenotype analysis depend on a large number of morphometric characters and meristic counts, can be used to discriminate shrimp species and genotype analysis using DNA fingerprint based on microsatellites (simple sequence repeats, SSRs) fingerprinting among seven species of shrimp.

Inter-tissue and inter-organ signaling in drought stress response and phenotyping of drought tolerance.

SUMMARYPlant response to drought stress includes systems for intracellular regulation of gene expression and signaling, as well as inter‐tissue and inter‐organ signaling, which helps entire plants acquire stress resistance. Plants sense water‐deficit conditions both via the stomata of leaves and roots, and transfer water‐deficit signals from roots to shoots via inter‐organ signaling. Abscisic acid is an important phytohormone involved in the drought stress response and adaptation, and is synthesized mainly in vascular tissues and guard cells of leaves. In leaves, stress‐induced abscisic acid is distributed to various tissues by transporters, which activates stomatal closure and expression of stress‐related genes to acquire drought stress resistance. Moreover, the stepwise stress response at the whole‐plant level is important for proper understanding of the physiological response to drought conditions. Drought stress is sensed by multiple types of sensors as molecular patterns of abiotic stress signals, which are transmitted via separate parallel signaling networks to induce downstream responses, including stomatal closure and synthesis of stress‐related proteins and metabolites. Peptide molecules play important roles in the inter‐organ signaling of dehydration from roots to shoots, as well as signaling of osmotic changes and reactive oxygen species/Ca2+. In this review, we have summarized recent advances in research on complex plant drought stress responses, focusing on inter‐tissue signaling in leaves and inter‐organ signaling from roots to shoots. We have discussed the mechanisms via which drought stress adaptations and resistance are acquired at the whole‐plant level, and have proposed the importance of quantitative phenotyping for measuring plant growth under drought conditions.

An archaeal histone-like protein regulates gene expression in response to salt stress.

Histones, ubiquitous in eukaryotes as DNA-packing proteins, find their evolutionary origins in archaea. Unlike the characterized histone proteins of a number of methanogenic and themophilic archaea, previous research indicated that HpyA, the sole histone encoded in the model halophile Halobacterium salinarum, is not involved in DNA packaging. Instead, it was found to have widespread but subtle effects on gene expression and to maintain wild type cell morphology. However, the precise function of halophilic histone-like proteins remain unclear. Here we use quantitative phenotyping, genetics, and functional genomics to investigate HpyA function. These experiments revealed that HpyA is important for growth and rod-shaped morphology in reduced salinity. HpyA preferentially binds DNA at discrete genomic sites under low salt to regulate expression of ion uptake, particularly iron. HpyA also globally but indirectly activates other ion uptake and nucleotide biosynthesis pathways in a salt-dependent manner. Taken together, these results demonstrate an alternative function for an archaeal histone-like protein as a transcriptional regulator, with its function tuned to the physiological stressors of the hypersaline environment.

Uncovering complementary sets of variants for predicting quantitative phenotypes.

Genome-wide association studies show that variants in individual genomic loci alone are not sufficient to explain the heritability of complex, quantitative phenotypes. Many computational methods have been developed to address this issue by considering subsets of loci that can collectively predict the phenotype. This problem can be considered a challenging instance of feature selection in which the number of dimensions (loci that are screened) is much larger than the number of samples. While currently available methods can achieve decent phenotype prediction performance, they either do not scale to large datasets or have parameters that require extensive tuning. We propose a fast and simple algorithm, Macarons, to select a small, complementary subset of variants by avoiding redundant pairs that are likely to be in linkage disequilibrium. Our method features two interpretable parameters that control the time/performance trade-off without requiring parameter tuning. In our computational experiments, we show that Macarons consistently achieves similar or better prediction performance than state-of-the-art selection methods while having a simpler premise and being at least two orders of magnitude faster. Overall, Macarons can seamlessly scale to the human genome with ∼107 variants in a matter of minutes while taking the dependencies between the variants into account. Macarons is available in Matlab and Python at https://github.com/serhan-yilmaz/macarons. Supplementary data are available at Bioinformatics online.

Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10−20), thalamus (p = 7.46 × 10−10), caudate (p = 1.97 × 10−18), putamen (p = 1.7 × 10−12), and nucleus accumbens (p = 1.99 × 10−7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = −0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10−19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10−7) or PTSD (rs10861272; p = 1.78 × 10−6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.

Considering Toxic Chemicals in the Etiology of Autism.

Considering Toxic Chemicals in the Etiology of Autism.

Identification of Subclinical Microvascular Biomarkers in Coronary Heart Disease in Retinal Imaging.

PurposeCardiovascular disease and foremost coronary heart disease (CHD) are the worldwide leading causes of death. The aim of this study was to use non-invasive, multimodel retinal imaging to define microvascular features in patients with and without coronary angiography (CA)-confirmed CHD.MethodsIn this prospective, cross-sectional pilot study we included adult patients who presented to a tertiary referral center for elective CA due to suspected CHD. All patients underwent widefield fundus photography for retinopathy grading. Optical coherence tomography angiography was used to measure vessel density (VD) of the individual capillary plexuses in 6 × 6-mm macular volume scans. Adaptive optics imaging was performed to assess the first-order arteriolar lumen diameter (LD), total diameter (TD), wall-to-lumen ratio (WLR), and wall cross-section area, as well as to qualitatively describe vessel morphology.ResultsOf the included 45 patients (13 females; 65 ± 10 years old), 27 were confirmed with CHD in elective CA. The most prevalent retinal vascular pathologies were arteriovenous nickings, focal arterial narrowings, and microaneurysms. VD in the superficial capillary plexus, deep capillary plexus, and choriocapillaris was lower in CHD patients, although the odds ratios were not significantly different from 1 (P = 0.06–0.92). Median arterial LD, TD, and WLR values were 98.3 µm (interquartile range [IQR] = 13.0), 122.9 µm (IQR = 17.6), and 0.26 µm (IQR = 0.07), respectively, with a trend toward a higher WLR in CHD patients.ConclusionsIn a cardiovascular risk population, high-resolution quantitative and qualitative microvascular phenotyping in the retina may provide valuable subclinical indicators for coronary artery impairment, although larger clinical trials are needed.Translational RelevanceSubclinical retinal microvascular changes may serve as non-invasive, cost-effective biomarkers for risk stratification of patients with CHD.

Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values

Key messageThe principal phenotypic determinants of market class in carrot—the size and shape of the root—are under primarily additive, but also highly polygenic, genetic control.The size and shape of carrot roots are the primary determinants not only of yield, but also market class. These quantitative phenotypes have historically been challenging to objectively evaluate, and thus subjective visual assessment of market class remains the primary method by which selection for these traits is performed. However, advancements in digital image analysis have recently made possible the high-throughput quantification of size and shape attributes. It is therefore now feasible to utilize modern methods of genetic analysis to investigate the genetic control of root morphology. To this end, this study utilized both genome wide association analysis (GWAS) and genomic-estimated breeding values (GEBVs) and demonstrated that the components of market class are highly polygenic traits, likely under the influence of many small effect QTL. Relatively large proportions of additive genetic variance for many of the component phenotypes support high predictive ability of GEBVs; average prediction ability across underlying market class traits was 0.67. GWAS identified multiple QTL for four of the phenotypes which compose market class: length, aspect ratio, maximum width, and root fill, a previously uncharacterized trait which represents the size-independent portion of carrot root shape. By combining digital image analysis with GWAS and GEBVs, this study represents a novel advance in our understanding of the genetic control of market class in carrot. The immediate practical utility and viability of genomic selection for carrot market class is also described, and concrete guidelines for the design of training populations are provided.

Quantitative nuclear phenotype signatures predict nodal disease in oral squamous cell carcinoma.

BackgroundEarly-stage oral squamous cell carcinoma (OSCC) patients have a one-in-four risk of regional metastasis (LN+), which is also the most significant prognostic factor for survival. As there are no validated biomarkers for predicting LN+ in early-stage OSCC, elective neck dissection often leads to over-treatment and under-treatment. We present a machine-learning-based model using the quantitative nuclear phenotype of cancer cells from the primary tumor to predict the risk of nodal disease.Methods and findingsTumor specimens were obtained from 35 patients diagnosed with primary OSCC and received surgery with curative intent. Of the 35 patients, 29 had well (G1) or moderately (G2) differentiated tumors, and six had poorly differentiated tumors. From each, two consecutive sections were stained for hematoxylin & eosin and Feulgen-thionin staining. The slides were scanned, and images were processed to curate nuclear morphometric features for each nucleus, measuring nuclear morphology, DNA amount, and chromatin texture/organization. The nuclei (n = 384,041) from 15 G1 and 14 G2 tumors were randomly split into 80% training and 20% test set to build the predictive model by using Random Forest (RF) analysis which give each tumor cell a score, NRS. The area under ROC curve (AUC) was 99.6% and 90.7% for the training and test sets, respectively. At the cutoff score of 0.5 as the median NRS of each region of interest (n = 481), the AUC was 95.1%. We then developed a patient-level model based on the percentage of cells with an NRS ≥ 0.5. The prediction performance showed AUC of 97.7% among the 80% (n = 23 patient) training set and with the cutoff of 61% positive cells achieved 100% sensitivity and 91.7% specificity. When applying the 61% cutoff to the 20% test set patients, the model achieved 100% accuracy.ConclusionsOur findings may have a clinical impact with an easy, accurate, and objective biomarker from routine pathology tissue, providing an unprecedented opportunity to improve neck management decisions in early-stage OSCC patients.

Tandem Mass Tag-Based Quantitative Proteomics and Virulence Phenotype of Hemolymph-Treated Bacillus thuringiensis kurstaki Cells Reveal New Insights on Bacterial Pathogenesis in Insects.

ABSTRACTThe spore-forming bacterium Bacillus thuringiensis (Bt) of the Bacillus cereus group uses toxin-opened breaches at the insect midgut epithelium to infest the hemolymph, where it can rapidly propagate despite antimicrobial host defenses and induce host death by acute septicemia. The response of Bt to host hemolymph and the latter’s role in bacterial pathogenesis is an area that needs clarification. Here, we report a proteomic analysis of the Bt kurstaki strain HD73 (Btk) hemolymph stimulon showing significant changes in 60 (34 up- and 26 downregulated) differentially accumulated proteins (DAPs). Gene ontology (GO) enrichment analysis revealed that DAPs were mainly related to glutamate metabolism, transketolase activity, and ATP-dependent transmembrane transport. KEGG analysis disclosed that DAPs were highly enriched in the biosynthesis of bacterial secondary metabolites, ansamycins. Interestingly, about 30% of all DAPs were in silico predicted as putative virulence factors. Further characterization of hemolymph effects on Btk showed enhanced autoaggregation in liquid cultures and biofilm formation in microtiter polystyrene plates. Hemolymph-exposed Btk cells were less immunogenic in mice, suggesting epitope masking of selected surface proteins. Bioassays with intrahemocoelically infected Bombyx mori larvae showed that hemolymph preexposure significantly increased Btk toxicity and reproduction within the insect (spore count per cadaver) at low inoculum doses, possibly due to ‘virulence priming’. Collectively, our findings suggest that the Btk hemolymph stimulon could be partially responsible for bacterial survival and propagation within the hemolymph of infected insects, contributing to its remarkable success as an entomopathogen. All mass spectrometry data are available via ProteomeXchange with identifier PXD021830.IMPORTANCE After ingestion by a susceptible insect and damaging its midgut epithelium, the bacterium Bacillus thuringiensis (Bt) reaches the insect blood (hemolymph), where it propagates despite the host’s antimicrobial defenses and induces insect death by acute septicemia. Although the hemolymph stage of the Bt toxic pathway is determinant for the infested insects’ fate, the response of Bt to hemolymph and the latter’s role in bacterial pathogenesis has been poorly explored. In this study, we identified the bacterial proteins differentially expressed by Bt after hemolymph exposure. We found that about 30% of hemolymph-regulated Bt proteins were potential virulence factors, including manganese superoxide dismutase, a described inhibitor of hemocyte respiratory burst. Additionally, contact with hemolymph enhanced Bt virulence phenotypes, such as cell aggregation and biofilm formation, altered bacterial immunogenicity, and increased Bt toxicity to intrahemocoelically injected insects.

Interconnected Gene Networks Underpin the Clinical Overlap of HNRNPH1-Related and Rubinstein-Taybi Intellectual Disability Syndromes.

Interconnected Gene Networks Underpin the Clinical Overlap of HNRNPH1-Related and Rubinstein-Taybi Intellectual Disability Syndromes.

Cultural versus biological inheritance: A retrospective view of Cavalli-Sforza and Feldman (1973)

The early 1970s was a period of ferment in human population genetics that resulted from the insistence of Arthur Jensen and William Shockley that intelligence was genetically determined, and that public policy should reflect this. They claimed that high heritability within a population indicated genetic differences between populations. The heritability statistic played a major role in the debate that ensued. The mathematical and computational analysis in Cavalli-Sforza and Feldman (1973) showed that the direct phenotypic transmission from parents to children could produce the appearance of high heritability even though the transmission was not genetic. This paper stimulated decades of statistical reanalysis of data on intelligence and other quantitative phenotypes in which the roles of cultural transmission and assortative mating were shown to be fundamental. Research into direct and indirect effects, causation and confounding, and gene-culture coevolution, carried out over the subsequent decades, can be traced to the framework established by Cavalli-Sforza and Feldman (1973). Based on “Cavalli-Sforza LL, Feldman MW. Cultural versus biological inheritance: Phenotypic transmission from parents to children (A theory of the effect of parental phenotypes on children’s phenotypes). Am. J. Hum. Genet. 1973; 25:618–637.”

An interferon-inducible signature of airway disease from blood gene expression profiling.

The molecular basis of airway remodelling in chronic obstructive pulmonary disease (COPD) remains poorly understood. We identified gene expression signatures associated with chest computed tomography (CT) scan airway measures to understand molecular pathways associated with airway disease. In 2396 subjects in the COPDGene Study, we examined the relationship between quantitative CT airway phenotypes and blood transcriptomes to identify airway disease-specific genes and to define an airway wall thickness (AWT) gene set score. Multivariable regression analyses were performed to identify associations of the AWT score with clinical phenotypes, bronchial gene expression and genetic variants. Type 1 interferon (IFN)-induced genes were consistently associated with AWT, square root wall area of a hypothetical airway with 10 mm internal perimeter (Pi10) and wall area percentage, with the strongest enrichment in AWT. A score derived from 18 genes whose expression was associated with AWT was associated with COPD-related phenotypes including reduced lung function (forced expiratory volume in 1 s percentage predicted β= -3.4; p<0.05) and increased exacerbations (incidence rate ratio 1.7; p<0.05). The AWT score was reproducibly associated with AWT in bronchial samples from 23 subjects (β=3.22; p<0.05). The blood AWT score was associated with genetic variant rs876039, an expression quantitative trait locus for IKZF1, a gene that regulates IFN signalling and is associated with inflammatory diseases. A gene expression signature with IFN-stimulated genes from peripheral blood and bronchial brushings is associated with CT AWT, lung function and exacerbations. Shared genes and genetic associations suggest viral responses and/or autoimmune dysregulation as potential underlying mechanisms of airway disease in COPD.

Quantitative behavioural phenotyping to investigate anaesthesia induced neurobehavioural impairment

Anaesthesia exposure to the developing nervous system causes neuroapoptosis and behavioural impairment in vertebrate models. Mechanistic understanding is limited, and target-based approaches are challenging. High-throughput methods may be an important parallel approach to drug-discovery and mechanistic research. The nematode worm Caenorhabditis elegans is an ideal candidate model. A rich subset of its behaviour can be studied, and hundreds of behavioural features can be quantified, then aggregated to yield a ‘signature’. Perturbation of this behavioural signature may provide a tool that can be used to quantify the effects of anaesthetic regimes, and act as an outcome marker for drug screening and molecular target research. Larval C. elegans were exposed to: isoflurane, ketamine, morphine, dexmedetomidine, and lithium (and combinations). Behaviour was recorded, and videos analysed with automated algorithms to extract behavioural features. Anaesthetic exposure during early development leads to persisting behavioural variation (in total, 125 features across exposure combinations). Higher concentrations, and combinations of isoflurane with ketamine, lead to persistent change in a greater number of features. Morphine and dexmedetomidine do not appear to lead to behavioural impairment. Lithium rescues the neurotoxic phenotype produced by isoflurane. Findings correlate well with vertebrate research: impairment is dependent on agent, is concentration-specific, is more likely with combination therapies, and can potentially be rescued by lithium. These results suggest that C. elegans may be an appropriate model with which to pursue phenotypic screens for drugs that mitigate the neurobehavioural impairment. Some possibilities are suggested for how high-throughput platforms might be organised in service of this field.

Reproducibility in the UK biobank of genome-wide significant signals discovered in earlier genome-wide association studies

With the establishment of large biobanks, discovery of single nucleotide variants (SNVs, also known as single nucleotide polymorphisms (SNVs)) associated with various phenotypes has accelerated. An open question is whether genome-wide significant SNVs identified in earlier genome-wide association studies (GWAS) are replicated in later GWAS conducted in biobanks. To address this, we examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, “replication” GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNVs (of which 6289 reached P < 5e−8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0%; although lower for binary than quantitative phenotypes (58.1% versus 94.8% respectively). There was a 18.0% decrease in SNV effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNV effect size, phenotype trait (binary or quantitative), and discovery P value, we built and validated a model that predicted SNV replication with area under the Receiver Operator Curve = 0.90. While non-replication may reflect lack of power rather than genuine false-positives, these results provide insights about which discovered associations are likely to be replicated across subsequent GWAS.

MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes.

Simple SummaryThe interactions between SNPs, which are known as epistasis, can strongly influence the phenotype. Their detection is still a challenge, which is made even more difficult through the existence of background associations that can hide correct epistatic interactions. To address the limitations of existing methods, we present in this study our novel method MIDESP for the detection of epistatic SNP pairs. It is the first mutual information-based method that can be applied to both qualitative and quantitative phenotypes and which explicitly accounts for background associations in the dataset.The interactions between SNPs result in a complex interplay with the phenotype, known as epistasis. The knowledge of epistasis is a crucial part of understanding genetic causes of complex traits. However, due to the enormous number of SNP pairs and their complex relationship to the phenotype, identification still remains a challenging problem. Many approaches for the detection of epistasis have been developed using mutual information (MI) as an association measure. However, these methods have mainly been restricted to case–control phenotypes and are therefore of limited applicability for quantitative traits. To overcome this limitation of MI-based methods, here, we present an MI-based novel algorithm, MIDESP, to detect epistasis between SNPs for qualitative as well as quantitative phenotypes. Moreover, by incorporating a dataset-dependent correction technique, we deal with the effect of background associations in a genotypic dataset to separate correct epistatic interaction signals from those of false positive interactions resulting from the effect of single SNP×phenotype associations. To demonstrate the effectiveness of MIDESP, we apply it on two real datasets with qualitative and quantitative phenotypes, respectively. Our results suggest that by eliminating the background associations, MIDESP can identify important genes, which play essential roles for bovine tuberculosis or the egg weight of chickens.

Whole-organism 3D quantitative characterization of zebrafish melanin by silver deposition micro-CT.

We previously described X-ray histotomography, a high-resolution, non-destructive form of X-ray microtomography (micro-CT) imaging customized for three-dimensional (3D), digital histology, allowing quantitative, volumetric tissue and organismal phenotyping (Ding et al., 2019). Here, we have combined micro-CT with a novel application of ionic silver staining to characterize melanin distribution in whole zebrafish larvae. The resulting images enabled whole-body, computational analyses of regional melanin content and morphology. Normalized micro-CT reconstructions of silver-stained fish consistently reproduced pigment patterns seen by light microscopy, and further allowed direct quantitative comparisons of melanin content across wild-type and mutant samples, including subtle phenotypes not previously noticed. Silver staining of melanin for micro-CT provides proof-of-principle for whole-body, 3D computational phenomic analysis of a specific cell type at cellular resolution, with potential applications in other model organisms and melanocytic neoplasms. Advances such as this in whole-organism, high-resolution phenotyping provide superior context for studying the phenotypic effects of genetic, disease, and environmental variables.

Association of the SNP rs112369934 near TRIM66 Gene with POAG Endophenotypes in African Americans

We investigated the association of the single nucleotide polymorphism (SNP) rs112369934 near the TRIM66 gene with qualitative and quantitative phenotypes of primary open-angle glaucoma (POAG) in African Americans (AA). AA subjects over 35 years old were recruited for the Primary Open-Angle African American Glaucoma Genetics (POAAGG) study in Philadelphia, PA. Glaucoma cases were evaluated for phenotypes associated with POAG pathogenesis, and the associations between rs112369934 and phenotypes were investigated by logistic regression analysis and in gender-stratified case cohorts: The SNP rs112369934 was found to have a suggestive association with retinal nerve fiber layer (RNFL) thickness and cup-to-disc ratio (CDR) in 1087 male AA POAG cases, individuals with the TC genotype having thinner RNFL (95% CI 0.85 to 6.61, p = 0.01) and larger CDR (95% CI −0.07 to −0.01, p = 0.02) than those with wildtype TT. No other significant associations were found. In conclusion SNP rs112369934 may play a role in POAG pathogenesis in male AA individuals. However, this SNP has been implicated in higher POAG risk in both male and female AA POAG cases.

Average semivariance yields accurate estimates of the fraction of marker-associated genetic variance and heritability in complex trait analyses.

The development of genome-informed methods for identifying quantitative trait loci (QTL) and studying the genetic basis of quantitative variation in natural and experimental populations has been driven by advances in high-throughput genotyping. For many complex traits, the underlying genetic variation is caused by the segregation of one or more ‘large-effect’ loci, in addition to an unknown number of loci with effects below the threshold of statistical detection. The large-effect loci segregating in populations are often necessary but not sufficient for predicting quantitative phenotypes. They are, nevertheless, important enough to warrant deeper study and direct modelling in genomic prediction problems. We explored the accuracy of statistical methods for estimating the fraction of marker-associated genetic variance (p) and heritability () for large-effect loci underlying complex phenotypes. We found that commonly used statistical methods overestimate p and . The source of the upward bias was traced to inequalities between the expected values of variance components in the numerators and denominators of these parameters. Algebraic solutions for bias-correcting estimates of p and were found that only depend on the degrees of freedom and are constant for a given study design. We discovered that average semivariance methods, which have heretofore not been used in complex trait analyses, yielded unbiased estimates of p and , in addition to best linear unbiased predictors of the additive and dominance effects of the underlying loci. The cryptic bias problem described here is unrelated to selection bias, although both cause the overestimation of p and . The solutions we described are predicted to more accurately describe the contributions of large-effect loci to the genetic variation underlying complex traits of medical, biological, and agricultural importance.