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Fulltext Waterlogging tolerance of crops: breeding, mechanism of tolerance, molecular approaches, and future prospects

Ahmed F, Rafii MY, Ismail MR, Juraimi AS, Rahim HA, Asfaliza R, et al.

Biomed Res Int, 2013;2013:963525.
PMID: 23484164 DOI: 10.1155/2013/963525

Submergence or flood is one of the major harmful abiotic stresses in the low-lying countries and crop losses due to waterlogging are considerably high. Plant breeding techniques, conventional or genetic engineering, might be an effective and economic way of developing crops to grow successfully in waterlogged condition. Marker assisted selection (MAS) is a new and more effective approach which can identify genomic regions of crops under stress, which could not be done previously. The discovery of comprehensive molecular linkage maps enables us to do the pyramiding of desirable traits to improve in submergence tolerance through MAS. However, because of genetic and environmental interaction, too many genes encoding a trait, and using undesirable populations the mapping of QTL was hampered to ensure proper growth and yield under waterlogged conditions Steady advances in the field of genomics and proteomics over the years will be helpful to increase the breeding programs which will help to accomplish a significant progress in the field crop variety development and also improvement in near future. Waterlogging response of soybean and major cereal crops, as rice, wheat, barley, and maize and discovery of QTL related with tolerance of waterlogging, development of resistant variety, and, in addition, future prospects have also been discussed.

Matched MeSH terms: Gene-Environment Interaction*
Gene-environment interaction in chronic kidney disease among people with type 2 diabetes from The Malaysian Cohort project: a case-control study

Ahmad N, Shah SA, Abdul Gafor AH, Abdul Murad NA, Kamaruddin MA, Abd Jalal N, et al.

Diabet Med, 2020 11;37(11):1890-1901.
PMID: 32012348 DOI: 10.1111/dme.14257

AIM: To examine the possible gene-environment interactions between 32 single nucleotide polymorphisms and environmental factors that could modify the probability of chronic kidney disease.
METHODS: A case-control study was conducted involving 600 people with type 2 diabetes (300 chronic kidney disease cases, 300 controls) who participated in The Malaysian Cohort project. Retrospective subanalysis was performed on the chronic kidney disease cases to assess chronic kidney disease progression from the recruitment phase. We genotyped 32 single nucleotide polymorphisms using mass spectrometry. The probability of chronic kidney disease and predicted rate of newly detected chronic kidney disease progression were estimated from the significant gene-environment interaction analyses.
RESULTS: Four single nucleotide polymorphisms (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and five environmental factors (age, sex, smoking, waist circumference and HDL) were significantly associated with chronic kidney disease. Gene-environment interaction analyses revealed significant probabilities of chronic kidney disease for sex (PPARGC1A rs8192678), smoking (eNOS rs2070744, PPARGC1A rs8192678 and KCNQ1 rs2237895), waist circumference (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and HDL (eNOS rs2070744 and PPARGC1A rs8192678). Subanalysis indicated that the rate of newly detected chronic kidney disease progression was 133 cases per 1000 person-years (95% CI: 115, 153), with a mean follow-up period of 4.78 (SD 0.73) years. There was a significant predicted rate of newly detected chronic kidney disease progression in gene-environment interactions between KCNQ1 rs2283228 and two environmental factors (sex and BMI).
CONCLUSIONS: Our findings suggest that the gene-environment interactions of eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228 with specific environmental factors could modify the probability for chronic kidney disease.

Matched MeSH terms: Gene-Environment Interaction
Fulltext Gene-environment Interaction: The Causes of High Obesity Incidence

Ellulu MS, Jalambo MO

Kathmandu Univ Med J (KUMJ), 2018 2 16;15(57):91-93.
PMID: 29446373

Urbanization has provided experimental settings for testing the interactive relationship between genetic background and changes in lifestyle and dietary patterns. The concept of gene-environment interaction was described by epidemic of obesity along with urbanization. Genome-wide association has identified several genes such as melanocortin-4 receptor that associates with environmental influences of obesity. Gene environment (GxE) interaction refers to modification by an environmental factor of the effect of a genetic variant on a phenotypic trait. GxE interactions can serve to modulate the adverse effects of a risk allele, or can exacerbate the genotype-phenotype relationship and increase risk.

Matched MeSH terms: Gene-Environment Interaction*
Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort

Abdullah N, Abdul Murad NA, Mohd Haniff EA, Syafruddin SE, Attia J, Oldmeadow C, et al.

Public Health, 2017 Aug;149:31-38.
PMID: 28528225 DOI: 10.1016/j.puhe.2017.04.003

OBJECTIVE: Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation.
STUDY DESIGN: This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project.
METHODS: The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R(2) and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants.
RESULTS: The models including environmental risk factors only had pseudo R(2) values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10(-4)-4.83 × 10(-12)) and increased the pseudo R(2) by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection.
Study name: The Malaysian Cohort (TMC) project

Matched MeSH terms: Gene-Environment Interaction
[Importance of twin research in preventive medicine and future perspective. Gene-environment interaction research in epigenetics era]

Hayakawa K

Nihon Eiseigaku Zasshi, 2011 Jan;66(1):29-30.
PMID: 21358129

The importance of twin research in the field of preventive medicine is described from the viewpoint of gene-environment interaction. The recent advancements in twin research in Japan and other countries are the major topics in this paper. The historical background of the Japan Society for Twin Studies is described. The Center for Twin Research of Osaka University is also described as the first center of this kind in Japan. The advancement of epigenetic research is described as a new global trend of twin research, particularly in European countries. Other new trends in twin research in Asian countries, such as China, Indonesia, Russia, Iran, and Malaysia, are also described.

Matched MeSH terms: Gene-Environment Interaction*
Fulltext Breeding for robustness: investigating the genotype-by-environment interaction and micro-environmental sensitivity of Genetically Improved Farmed Tilapia (Oreochromis niloticus)

Agha S, Mekkawy W, Ibanez-Escriche N, Lind CE, Kumar J, Mandal A, et al.

Anim. Genet., 2018 Oct;49(5):421-427.
PMID: 30058152 DOI: 10.1111/age.12680

Robustness has become a highly desirable breeding goal in the globalized agricultural market. Both genotype-by-environment interaction (G × E) and micro-environmental sensitivity are important robustness components of aquaculture production, in which breeding stock is often disseminated to different environments. The objectives of this study were (i) to quantify the degree of G × E by assessing the growth performance of Genetically Improved Farmed Tilapia (GIFT) across three countries (Malaysia, India and China) and (ii) to quantify the genetic heterogeneity of environmental variance for body weight at harvest (BW) in GIFT as a measure of micro-environmental sensitivity. Selection for BW was carried out for 13 generations in Malaysia. Subsets of 60 full-sib families from Malaysia were sent to China and India after five and nine generations respectively. First, a multi-trait animal model was used to analyse the BW in different countries as different traits. The results indicate a strong G × E. Second, a genetically structured environmental variance model, implemented using Bayesian inference, was used to analyse micro-environmental sensitivity of BW in each country. The analysis revealed the presence of genetic heterogeneity of both BW and its environmental variance in all environments. The presence of genetic variation in residual variance of BW implies that the residual variance can be modified by selection. Incorporating both G × E and micro-environmental sensitivity information may help in selecting robust genotypes with high performance across environments and resilience to environmental fluctuations.

Matched MeSH terms: Gene-Environment Interaction*
Contribution of CYP2E1 polymorphism to aging in the mechanical workshop workers

Eshkoor SA, Ismail P, Rahman SA, Adon MY, Devan RV

Toxicol. Mech. Methods, 2013 May;23(4):217-22.
PMID: 23193996 DOI: 10.3109/15376516.2012.743637

Aging is attributed to both genetic and environmental factors. Occupational exposure is one of the environmental factors with potential genotoxic effects. Researchers try to determine factors involved in genetic damages at hazards exposure that could accelerate aging. Cytochrome P450 2E1 (CYP2E1) gene contributes in activation and detoxification of the environmental hazards. This polymorphism plays an important role in susceptibility of inter-individuals to DNA damage at the occupational exposure. The current study evaluated the possible influence of this gene polymorphism in aging by genomic damages through the biomarkers alterations of micronuclei (MN), comet tail length and telomere length shortening at the exposure. In this study, buccal cells were collected from the oral cavity of exposed workers and non-exposed controls. The CYP2E1 genotypes were detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). The wild genotype significantly affected MN frequency (p = 0.007) and relative telomere length (p = 0.047) in the older group of workers. It was concluded that the interaction of gene polymorphism and exposure enhances DNA damage and accelerates aging consequently.

Matched MeSH terms: Gene-Environment Interaction*
Fulltext Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs

Graham NS, Hammond JP, Lysenko A, Mayes S, O Lochlainn S, Blasco B, et al.

Plant Cell, 2014 Jul;26(7):2818-30.
PMID: 25082855 DOI: 10.1105/tpc.114.128603

Although Ca transport in plants is highly complex, the overexpression of vacuolar Ca(2+) transporters in crops is a promising new technology to improve dietary Ca supplies through biofortification. Here, we sought to identify novel targets for increasing plant Ca accumulation using genetical and comparative genomics. Expression quantitative trait locus (eQTL) mapping to 1895 cis- and 8015 trans-loci were identified in shoots of an inbred mapping population of Brassica rapa (IMB211 × R500); 23 cis- and 948 trans-eQTLs responded specifically to altered Ca supply. eQTLs were screened for functional significance using a large database of shoot Ca concentration phenotypes of Arabidopsis thaliana. From 31 Arabidopsis gene identifiers tagged to robust shoot Ca concentration phenotypes, 21 mapped to 27 B. rapa eQTLs, including orthologs of the Ca(2+) transporters At-CAX1 and At-ACA8. Two of three independent missense mutants of BraA.cax1a, isolated previously by targeting induced local lesions in genomes, have allele-specific shoot Ca concentration phenotypes compared with their segregating wild types. BraA.CAX1a is a promising target for altering the Ca composition of Brassica, consistent with prior knowledge from Arabidopsis. We conclude that multiple-environment eQTL analysis of complex crop genomes combined with comparative genomics is a powerful technique for novel gene identification/prioritization.

Matched MeSH terms: Gene-Environment Interaction
Fulltext Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Coleman JRI, Peyrot WJ, Purves KL, Davis KAS, Rayner C, Choi SW, et al.

Mol Psychiatry, 2020 Jul;25(7):1430-1446.
PMID: 31969693 DOI: 10.1038/s41380-019-0546-6

Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

Matched MeSH terms: Gene-Environment Interaction*
Fulltext Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Czamara D, Eraslan G, Page CM, Lahti J, Lahti-Pulkkinen M, Hämäläinen E, et al.

Nat Commun, 2019 06 11;10(1):2548.
PMID: 31186427 DOI: 10.1038/s41467-019-10461-0

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike's information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.

Matched MeSH terms: Gene-Environment Interaction*
Fulltext Hereditary analysis and genotype × environment interaction effects on growth and yield components of Bambara groundnut (Vigna subterranea (L.) Verdc.) over multi-environments

Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M

Sci Rep, 2022 09 19;12(1):15658.
PMID: 36123374 DOI: 10.1038/s41598-022-19003-z

This investigation was carried out to explore G × E interaction for yield and its associated attributes in 30 Bambara groundnut genotypes across four environments in tropical Malaysia. Such evaluations are essential when the breeding program's objective is to choose genotypes with broad adaption and yield potential. Studies of trait relationships, variance components, mean performance, and genetic linkage are needed by breeders when designing, evaluating, and developing selection criteria for improving desired characteristics in breeding programs. The evaluation of breeding lines of Bambara groundnut for high yield across a wide range of environments is important for long-term production and food security. Each site's experiment employed a randomized complete block design with three replicates. Data on vegetative and yield component attributes were recorded. The analysis of variance revealed that there were highly significant (p ≤ 0.01) differences among the 30 genotypes for all variables evaluated. A highly significant and positive correlation was identified between yield per hectare and dry seed weight (0.940), hundred seed weight (0.844), fresh pod weight (0.832), and total pod weight (0.750); the estimated correlation between dry weight of pods and seed yield was 1.0. The environment was more important than genotype and G × E in determining yield and yield components.A total of 49% variation is covered by PC1 (33.9%) and PC2 (15.1%) and the genotypes formed five distinct clusters based on Ward hierarchical clustering (WHC) method. The genotypes S5G1, S5G3, S5G5, S5G6, S5G8, S5G7, S5G2, S5G4, S5G10, S5G13, S5G11, and S5G14 of clusters I, II, and III were closest to the ideal genotype with superior yield across the environments. The PCA variable loadings revealed that an index based on dry pod weight, hundred seed weight, number of total pods and fresh pod weight could be used as a selection criteria to improve seed yield of Bambara groundnut.

Matched MeSH terms: Gene-Environment Interaction
Fulltext AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranea L. Verdc.) genotypes under the multi-environmental trails (METs)

Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M

Sci Rep, 2021 Nov 23;11(1):22791.
PMID: 34815427 DOI: 10.1038/s41598-021-01411-2

The stability and high yielding of Vigna subterranea L. Verdc. genotype is an important factor for long-term development and food security. The effects of G × E interaction on yield stability in 30 Bambara groundnut genotypes in four different Malaysian environments were investigated in this research. The experiment used a randomized complete block design with three replications in each environment. Over multiple harvests, yield component traits such as the total number of pods per plant, fresh pods weight (g), hundred seeds weight (g), and yield per hectare were evaluated in the main and off-season in 2020 and 2021. Stability tests for multivariate stability parameters were performed based on analyses of variance. For all the traits, the pooled analysis of variance revealed highly significant (p

Matched MeSH terms: Gene-Environment Interaction*

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