Environmental and Genetic Regulation of Plant Height in Soybean

Abstract Background: Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce.Results: In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80% - 26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19-1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties.Conclusions: Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Environmental and Genetic Regulation of Plant Height in Soybean

10.21203/rs.2.20549/v3 ◽

2021 ◽

Author(s):

Qing Yang ◽

Gaoming Lin ◽

Huiyong Lv ◽

Cunhu Wang ◽

Yongqing Yang ◽

...

Keyword(s):

Environmental Factors ◽

Soil Properties ◽

Plant Height ◽

Meteorological Factors ◽

Day Length ◽

Maximum Temperature ◽

Soybean Plant ◽

Environment Interaction ◽

Shoot Architecture ◽

Average Maximum

Abstract Background:Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce.Results:In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80% - 26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19-1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties.Conclusions:Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Environmental and Genetic Regulation of Plant Height in Soybean

10.21203/rs.2.20549/v4 ◽

2021 ◽

Author(s):

Qing Yang ◽

Gaoming Lin ◽

Huiyong Lv ◽

Cunhu Wang ◽

Yongqing Yang ◽

...

Keyword(s):

Environmental Factors ◽

Soil Properties ◽

Plant Height ◽

Meteorological Factors ◽

Day Length ◽

Maximum Temperature ◽

Soybean Plant ◽

Environment Interaction ◽

Shoot Architecture ◽

Average Maximum

Abstract Background:Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce.Results:In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80% - 26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19-1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties.Conclusions:Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Environmental and genetic regulation of plant height in soybean

BMC Plant Biology ◽

10.1186/s12870-021-02836-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Qing Yang ◽

Gaoming Lin ◽

Huiyong Lv ◽

Cunhu Wang ◽

Yongqing Yang ◽

...

Keyword(s):

Environmental Factors ◽

Soil Properties ◽

Plant Height ◽

Meteorological Factors ◽

Day Length ◽

Maximum Temperature ◽

Soybean Plant ◽

Environment Interaction ◽

Shoot Architecture ◽

Average Maximum

Abstract Background Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce. Results In this study, 308 representative soybean lines from a core collection and 168 F9 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction (G × E) effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs (quantitative trait locus) for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH (shoot height), SNN (stem node number) and AIL (average internode length), respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80–26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19–1, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA (principal component analysis) revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD (average day-length), AMaT (average maximum temperature), pH, and AN (available nitrogen) had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties. Conclusions Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Environmental and Genetic Regulation of Plant Height in Soybean

10.21203/rs.2.20549/v1 ◽

2020 ◽

Author(s):

Qing Yang ◽

Gaoming Lin ◽

Huiyong Lv ◽

Cunhu Wang ◽

Yongqing Yang ◽

...

Keyword(s):

Environmental Factors ◽

Soil Properties ◽

Plant Height ◽

Meteorological Factors ◽

Pearson Correlation ◽

Genetic Regulation ◽

Soybean Plant ◽

Environment Interaction ◽

Shoot Architecture ◽

Soybean Genotypes

Abstract Shoot architecture is fundamentally crucial to crop growth and productivity. As a key component of shoot architecture, plant height is known to be controlled by both genetic and environmental factors, though specific details remain scarce. Here, 308 representative soybean lines from a core collection and 168 F9:11 soybean progeny were planted at distinct field sites. The results demonstrated the presence of significant genotype × environment interaction effects on traits associated with plant height in a natural soybean population. In total, 19 loci containing 51 QTLs for plant height were identified across four environments, with 23, 13 and 15 being QTLs for SH, SNN and AIL, respectively. Significant LOD ranging from 2.50 to 16.46 explained 2.80%~26.10% of phenotypic variation. Intriguingly, only two loci, Loc11 and Loc19, containing 20 QTLs, were simultaneously detected across all environments. Results from Pearson correlation analysis and PCA revealed that each of the five agro-meteorological factors and four soil properties significantly affected soybean plant height traits, and that the corresponding QTLs had additive effects. Among significant environmental factors, AD, AMaT, pH, and AN had the largest impacts on soybean plant height. Therefore, in spite of uncontrollable agro-meteorological factors, soybean shoot architecture might be remolded through combined efforts to produce superior soybean genetic materials while also optimizing soil properties. Overall, the comprehensive set of relationships outlined herein among environment factors, soybean genotypes and QTLs in effects on plant height opens new avenues to explore in work aiming to increase soybean yield through improvements in shoot architecture.

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Performance of RegCM4.5 in Simulating the Regional Climate of Western Tianshan Mountains in Xinjiang, China

Atmosphere ◽

10.3390/atmos12121544 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1544

Author(s):

Quanying Cheng ◽

Fan Li

Keyword(s):

Wind Speed ◽

Meteorological Factors ◽

Regional Climate ◽

Meteorological Factor ◽

Tianshan Mountains ◽

Maximum Temperature ◽

Simulation Performance ◽

Four Seasons ◽

Western Tianshan ◽

Average Maximum

The western Tianshan Mountains region in China has a complex topography where basins, mountains and glaciers co-exist. It is of great significance to study the sensitivity of meteorological factors in this region to different parameterization schemes of climate models. In this paper, the regional climate model RegCM4.5 is used to simulate the meteorological factor (mean temperature, maximum temperature, minimum temperature, precipitation and wind speed) occurring in the western Tianshan Mountains region from 2012 to 2016, so as to investigate the effects of different cumulus convective schemes (Grell, Tiedtke and Emanuel), including land cumulus convective schemes (LCCs) and ocean convective schemes (OCCs) on annual and seasonal simulations of meteorological factor by using the schemes of RUN1 (Grell for LCC and Tiedtke for OCC), RUN2 (Tiedtke for LCC and Emanuel for OCC), RUN3 (Grell for LCC and Emanuel for OCC) and ENS (the ensemble of RUN1, RUN2 and RUN3). The results show that the simulations of annual and seasonal meteorological factors are not significantly sensitive to the combination of LCCs and OCCs. In the annual simulations, RUN2 scheme has the best simulation performance for the maximum, average and minimum temperatures. However, other schemes of precipitation simulation outperform RUN2 scheme, and there is no difference among the four schemes for wind speed simulation. In the seasonal simulations, RUN2 scheme still performs well in the simulation of the average, maximum and minimum temperatures for four seasons, except for the simulation of the average temperature in spring and summer. For the simulation of the maximum temperature in summer, RUN2 scheme performs the same as ENS. For the simulation of other seasons, different meteorological factors have different performances in four seasons. Overall, the results show that different combinations of cumulus convection schemes can improve the simulation performance of meteorological factors in the western Tianshan Mountains of Xinjiang.

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Modelling of genotype by environment interaction to improve the recommendation of sugarcane cultivars for the state of Goiás, Brazil

Pesquisa Agropecuária Brasileira ◽

10.1590/s1678-3921.pab2021.v56.02398 ◽

2021 ◽

Vol 56 ◽

Author(s):

Rafael Ferreira Montes ◽

Flávio Breseghello ◽

João Batista Duarte

Keyword(s):

Environmental Factors ◽

Field Trials ◽

Genotype By Environment Interaction ◽

The State ◽

Specific Yield ◽

Maximum Temperature ◽

Environment Interaction ◽

Average Temperature ◽

Genotype By Environment ◽

Selection Of

Abstract The objective of this work was to identify environmental factors with significant effects on the genotype by environment interaction (GEI) of sugarcane, and to generate thematic maps yield adaptability of genotypes for the state of Goiás, Brazil, through the integrated use of factorial regression models and the geographic information system (GIS). The study was based on the yield of recoverable sugar (YRS) from cultivar field trials carried out in nine locations. Fourteen environmental factors were used, out of which 11 were divided into 10 crop growth phases, totaling 113 environmental covariates (ECs). The selection of ECs was done by successive simple linear regressions, and the respective genotypic sensitivity coefficients were used to generate adaptability maps. Approximately 57% of the GEI effects were related to the covariates longitude, average temperature at crop germination phase, and maximum temperature at the beginning of the phase of greatest growth. For YRS, the RB034128 and RB034021 clones show specific yield adaptations, and the RB034045 cultivar can share the growing area with the RB867515 check cultivar.

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The Effect of the Thermal Mass of the Building Envelope on Summer Overheating of Dwellings in a Temperate Climate

Energies ◽

10.3390/en14144117 ◽

2021 ◽

Vol 14 (14) ◽

pp. 4117

Author(s):

Tadeusz Kuczyński ◽

Anna Staszczuk ◽

Piotr Ziembicki ◽

Anna Paluszak

Keyword(s):

Building Materials ◽

Heat Waves ◽

Residential Buildings ◽

Building Envelope ◽

Temperate Climate ◽

Maximum Temperature ◽

Thermal Mass ◽

Occupant Behavior ◽

Average Maximum ◽

Night Ventilation

The main objective of this paper is to demonstrate the effectiveness of increasing the thermal capacity of a residential building by using traditional building materials to reduce the risk of its excessive overheating during intense heat waves in a temperate climate. An additional objective is to show that the use of this single passive measure significantly reduces the risk of overheating in daytime rooms, but also, though to a much lesser extent, in bedrooms. Increasing the thermal mass of the room from light to a medium heavy reduced the average maximum daily temperature by 2.2K during the first heat wave and by 2.6K during the other two heat waves. The use of very heavy construction further reduced the average maximum temperature for the heat waves analyzed by 1.4K, 1.2K and 1.7K, respectively, giving a total possible reduction in maximum daily temperatures in the range of 3.6 °C, 3.8 °C and 4.3 °C. A discussion of the influence of occupant behavior on the use of night ventilation and external blinds was carried out, finding a significant effect on the effectiveness of the use of both methods. The results of the study suggest that in temperate European countries, preserving residential construction methods with heavy envelopes and partitions could significantly reduce the risk of overheating in residential buildings over the next few decades, without the need for night ventilation or external blinds, whose effectiveness is highly dependent on individual occupant behavior.

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Identification of genetic loci affecting body mass index through interaction with multiple environmental factors using structured linear mixed model

Scientific Reports ◽

10.1038/s41598-021-83684-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hae-Un Jung ◽

Won Jun Lee ◽

Tae-Woong Ha ◽

Ji-One Kang ◽

Jihye Kim ◽

...

Keyword(s):

Body Mass Index ◽

Environmental Factors ◽

Body Mass ◽

Bayes Factor ◽

Mixed Model ◽

Linear Mixed Model ◽

Interaction Analysis ◽

Carbohydrate Intake ◽

Calorie Intake ◽

Environment Interaction

AbstractMultiple environmental factors could interact with a single genetic factor to affect disease phenotypes. We used Struct-LMM to identify genetic variants that interacted with environmental factors related to body mass index (BMI) using data from the Korea Association Resource. The following factors were investigated: alcohol consumption, education, physical activity metabolic equivalent of task (PAMET), income, total calorie intake, protein intake, carbohydrate intake, and smoking status. Initial analysis identified 7 potential single nucleotide polymorphisms (SNPs) that interacted with the environmental factors (P value < 5.00 × 10−6). Of the 8 environmental factors, PAMET score was excluded for further analysis since it had an average Bayes Factor (BF) value < 1 (BF = 0.88). Interaction analysis using 7 environmental factors identified 11 SNPs (P value < 5.00 × 10−6). Of these, rs2391331 had the most significant interaction (P value = 7.27 × 10−9) and was located within the intron of EFNB2 (Chr 13). In addition, the gene-based genome-wide association study verified EFNB2 gene significantly interacting with 7 environmental factors (P value = 5.03 × 10−10). BF analysis indicated that most environmental factors, except carbohydrate intake, contributed to the interaction of rs2391331 on BMI. Although the replication of the results in other cohorts is warranted, these findings proved the usefulness of Struct-LMM to identify the gene–environment interaction affecting disease.

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The effect of average temperature on suicide rates in five urban California counties, 1999–⁠2019: an ecological time series analysis

BMC Public Health ◽

10.1186/s12889-021-11001-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Sierra Cheng ◽

Rebecca Plouffe ◽

Stephanie M. Nanos ◽

Mavra Qamar ◽

David N. Fisman ◽

...

Keyword(s):

Public Health ◽

Suicide Rate ◽

Minimum Temperature ◽

The United States ◽

Additive Models ◽

Maximum Temperature ◽

Mortality Data ◽

Average Temperature ◽

Suicide Rates ◽

Average Maximum

Abstract Background Suicide is among the top 10 leading causes of premature morality in the United States and its rates continue to increase. Thus, its prevention has become a salient public health responsibility. Risk factors of suicide transcend the individual and societal level as risk can increase based on climatic variables. The purpose of the present study is to evaluate the association between average temperature and suicide rates in the five most populous counties in California using mortality data from 1999 to 2019. Methods Monthly counts of death by suicide for the five counties of interest were obtained from CDC WONDER. Monthly average, maximum, and minimum temperature were obtained from nCLIMDIV for the same time period. We modelled the association of each temperature variable with suicide rate using negative binomial generalized additive models accounting for the county-specific annual trend and monthly seasonality. Results There were over 38,000 deaths by suicide in California’s five most populous counties between 1999 and 2019. An increase in average temperature of 1 °C corresponded to a 0.82% increase in suicide rate (IRR = 1.0082 per °C; 95% CI = 1.0025–1.0140). Estimated coefficients for maximum temperature (IRR = 1.0069 per °C; 95% CI = 1.0021–1.0117) and minimum temperature (IRR = 1.0088 per °C; 95% CI = 1.0023–1.0153) were similar. Conclusion This study adds to a growing body of evidence supporting a causal effect of elevated temperature on suicide. Further investigation into environmental causes of suicide, as well as the biological and societal contexts mediating these relationships, is critical for the development and implementation of new public health interventions to reduce the incidence of suicide, particularly in the face increasing temperatures due to climate change.

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Gene–gene and gene-environment interactions on cord blood total IgE in Chinese Han children

Allergy Asthma & Clinical Immunology ◽

10.1186/s13223-021-00571-0 ◽

2021 ◽

Vol 17 (1) ◽

Author(s):

Li Hua ◽

Quanhua Liu ◽

Jing Li ◽

Xianbo Zuo ◽

Qian Chen ◽

...

Keyword(s):

Environmental Factors ◽

Cord Blood ◽

Synergistic Effects ◽

Gene Interaction ◽

Independent Effect ◽

Environment Interaction ◽

Nucleotide Polymorphisms ◽

Chinese Han ◽

Gene Environment Interaction ◽

Gene Environment

Abstract Background IL13, IL4, IL4RA, FCER1B and ADRB2 are susceptible genes of asthma and atopy. Our previous study has found gene–gene interactions on asthma between these genes in Chinese Han children. Whether the interactions begin in fetal stage, and whether these genes interact with prenatal environment to enhance cord blood IgE (CBIgE) levels and then cause subsequent allergic diseases have yet to be determined. This study aimed to determine whether there are gene–gene and gene-environment interactions on CBIgE elevation among the aforementioned five genes and prenatal environmental factors in Chinese Han population. Methods 989 cord blood samples from a Chinese birth cohort were genotyped for nine single-nucleotide polymorphisms (SNPs) in the five genes, and measured for CBIgE levels. Prenatal environmental factors were collected using a questionnaire. Gene–gene and gene-environment interactions were analyzed with generalized multifactor dimensionality methods. Results A four-way gene–gene interaction model (IL13 rs20541, IL13 rs1800925, IL4 rs2243250 and ADRB2 rs1042713) was regarded as the optimal one for CBIgE elevation (testing balanced accuracy = 0.5805, P = 9.03 × 10–4). Among the four SNPs, only IL13 rs20541 was identified to have an independent effect on elevated CBIgE (odds ratio (OR) = 1.36, P = 3.57 × 10–3), while the other three had small but synergistic effects. Carriers of IL13 rs20541 TT, IL13 rs1800925 CT/TT, IL4 rs2243250 TT and ADRB2 rs1042713 AA were estimated to be at more than fourfold higher risk for CBIgE elevation (OR = 4.14, P = 2.69 × 10–2). Gene-environment interaction on elevated CBIgE was found between IL4 rs2243250 and maternal atopy (OR = 1.41, P = 2.65 × 10–2). Conclusions Gene–gene interaction between IL13 rs20541, IL13 rs1800925, IL4 rs2243250 and ADRB2 rs1042713, and gene-environment interaction between IL4 rs2243250 and maternal atopy begin in prenatal stage to augment IgE production in Chinese Han children.

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