A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets

Current methods to evaluate gene-by-environment (GxE) interactions on biobank-scale datasets are limited. MonsterLM enables multiple linear regression on genome-wide datasets, does not rely on parameters specification and provides unbiased estimates of variance explained by GxE interaction effects. We applied MonsterLM to the UK Biobank for eight blood biomarkers (N=325,991), identifying significant genome-wide interaction variance with waist-to-hip ratio for five biomarkers, with variance explained by interactions ranging from 0.11 to 0.58. 48% to 94% of GxE interaction variance can be attributed to variants without significant marginal association with the phenotype of interest. Conversely, for most traits, >40% of interaction variance was explained by less than 5% of genetic variants. We observed significant improvements in polygenic score prediction with incorporation of GxE interactions in four biomarkers. Our results imply an important contribution of GxE interaction effects, driven largely by a restricted set of variants distinct from loci with strong marginal effects.

Efectos genéticos en híbridos de maíz tropical (Zea mays L.) III. Acame, mala cobertura y pudrición de mazorca.

This study report genetic effects for lodging, uncovered ears and ear rot, of 42 single cross hybrids made with seven lines developed in the humid tropic of México, and six lines developed in the dry tropic, using a North Caroline II mating design. Hybrid variation was mainly due to GCA variance, and scanty to SCA variance for all the three attributes, although for ear rot, SCA variance had a considerable role, too. Partitioning GCA variance, revealed humid tropic lines had highest contribution to lodging and ear covering variance, and dry tropic lines the highest contribution to ear rot variance. In addition, humid tropic lines had higher GCAxEnvironment interaction variance than dry tropic lines. In conclusion, GCA effects, which reveal additive genetic variance, were the main effects for all the three attributes, and that GCA effects were higher in humid tropic lines than those of the dry tropic, maybe due to their mobilization in a more ample and diverse region.

Environmental Variances of Fruit Traits in a Mandarin-related Population Used in Citrus Breeding in Japan

We estimated environmental variance components for fruit weight (FW), ease of peeling (EP), firmness of segment membrane (FSM), soluble solids content (SSC), and acidity of 20 mandarin and related cultivars used as cross-parents in citrus breeding in Japan. The variance by year was largest for FW (38% of the total) and SSC (23%), but negligible for EP, FSM, and acidity. Variance among trees and tree × year interaction were negligibly small except for FW, whereas the genotype × year interaction variance ranged from 9% to 22% of the total. Variance among fruits from the same tree was the largest environmental component for EP and FSM. Broad-sense heritability (hB2) was 0.29 for FW, 0.52 for EP, 0.11 for FSM, 0.34 for SSC, and 0.65 for acidity in evaluations performed using single-year measurements of one tree with one fruit. Yearly repetition was more efficient than tree replication for increasing hB2 of all traits investigated. Increasing fruit number from one to five in combination with yearly repetition also increased hB2, especially for EP and FSM.

Genotype x Environment Interaction and Yield Stability of Several Yield Components Among Adapted Rice Cultivars in West Sumatra

Genotype by environment (GE) interaction and genotype stability of a trait in rice (Oryza sativa L.) are very important for plant breeders in making decision regarding the development and evaluation of new cultivars as well as for farmers in selecting suitable cultivars to be planted for commercial purpose. Yield components including panicles number plant–1, number of grains panicle–1, 1000-grain weight, and grain yield of five locally adapted cultivars of rice were evaluated at three locations in West Sumatera. The data were used to determine GE interaction variance components and stability of the traits. There were significant effects of locations on yield and some yield components except number of panicles plant–1. The cultivars differed significantly in all yield components but not in grain yield. The influence of GE interaction was highly significant on all yield components and grain yield. The magnitude of GE interaction variance component was greater than that of location for all traits. These data suggested that genotypes performed differently among the locations and were not stable with respect to the locations, so that farmers should select a suitable cultivar to be grown in the area of production.

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here, we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL-QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL-QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies.

Statistical analysis of nematode counts from interlaboratory proficiency tests

A series of proficiency tests on potato cyst nematode (PCN; ) and free-living stages of Meloidogyne and Pratylenchus () were investigated to determine the accuracy and precision of the nematode counts and to gain insights into possible trends and potential improvements. In each test, each participating laboratory received ten samples of soil collected from naturally infested fields and well mixed before distribution. The variance between the counts from the ten samples, estimated per test and laboratory, was constant for PCN cysts and free-living stages of Meloidogyne spp. and Pratylenchus spp. during the period monitored. However, during the initial years, the variance between the samples showed a downward trend for PCN living juveniles. The variance between the laboratories, estimated per test, was constant for PCN cysts over the period 1994-2010. For PCN living juveniles the variance between laboratory means declined from 1994-2000 and from 2000 it was more or less constant, which coincided with the introduction of a well-described new methodology. For Meloidogyne spp. and Pratylenchus spp., from 1998-2005 the variance between laboratory means was more or less constant or increased. From 2006, all participating laboratories incubated the organic matter and the variance between the laboratories was stable and below the levels observed during 2003-2005. After discarding data from initial years with unstable variances of the nematode counts, a meta-analysis was carried out on the remaining data using HGLMs to model the mean and variance of the counts simultaneously. The within-laboratory variance for the ten samples and the interaction variance of test and laboratory were estimated and combined to percentage coefficient of variation (%CV) per laboratory. For PCN cysts, %CV per laboratory ranged from 12.6 to 41.6 and for PCN juveniles in sandy soil from 24.4 to 67.4 and in loamy soil from 37.9 to 102.0. For Meloidogyne spp., %CV ranged from 53.2 to 84.4 and for Pratylenchus spp. from 24.3 to 90.6. The quality of a proficiency test is largely defined by random distribution of the nematodes over the samples allocated, statistical analysis of the data and communication of the results to participating laboratories. This study provides insights into the accuracy and precision at laboratories in recent years and the effect of concerted actions during the period in which the proficiency tests were conducted.

Yield, SDG lignan, cadmium, lead, oil and protein contents of linseed (Linum usitatissimum L.) cultivated in trials and at different farm conditions in the south-western part of Finland

Linseed varieties were studied in variety trials and under farm conditions in south-western Finland in the years 2007−2010. The variation in yield, oil, protein, SDG lignan, cadmium and lead contents were studied in 8 oil and 2 fibre linseed varieties. Genotypic, environmental and genotype x environment interaction variance estimates were calculated. Fibre varieties ‘Belinka’ and ‘Martta’ had higher protein and lower oil contents than oil linseed varieties.The SDG lignan contents of linseed varieties varied between 3635−9560 mg kg-1. Rather high genotypic variance was found in yield, oil, protein and SDG lignan contents. Variety ‘Laser’ had lower SDG lignan content. ‘Abacus’, ‘Helmi’ and ‘Martta’ had the highest SDG lignan contents. Variation in cadmium and lead contents were caused by environmental effects. The highest cadmium contents, 0.82−1.69 mg kg-1, were found in soils fertilized by wastewater sludge about 20 years ago and at fields with low bottom soil pH (4.1−4.5).