Plants respond to abiotic stress through a variety of physiological, biochemical, and transcriptional mechanisms. Many genes exhibit altered levels of expression in response to abiotic stress, which requires concerted action of both
Increasing the tolerance of maize seedlings to low‐temperature episodes could mitigate the effects of increasing climate variability on yield. To aid progress toward this goal, we established a growth chamber‐based system for subjecting seedlings of 40 maize inbred genotypes to a defined, temporary cold stress while collecting digital profile images over a 9‐daytime course. Image analysis performed with Plant
- NSF-PAR ID:
- 10084626
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Plant Direct
- Volume:
- 3
- Issue:
- 1
- ISSN:
- 2475-4455
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Summary cis‐ andtrans‐ regulatory features. In order to study the variability in transcriptome response to abiotic stress,RNA sequencing was performed using 14‐day‐old maize seedlings of inbreds B73, Mo17, Oh43,PH 207 and B37 under control, cold and heat conditions. Large numbers of genes that responded differentially to stress between parental inbred lines were identified.RNA sequencing was also performed on similar tissues of theF 1hybrids produced by crossing B73 and each of the three other inbred lines. By evaluating allele‐specific transcript abundance in theF 1hybrids, we were able to measure the abundance ofcis‐ andtrans‐ regulatory variation between genotypes for both steady‐state and stress‐responsive expression differences. Although examples oftrans‐ regulatory variation were observed,cis‐ regulatory variation was more common for both steady‐state and stress‐responsive expression differences. The genes withcis‐ allelic variation for response to cold or heat stress provided an opportunity to study the basis for regulatory diversity. -
more » « less
Abstract Floral attraction traits can significantly affect pollinator visitation patterns, but adaptive evolution of these traits may be constrained by correlations with other traits. In some cases, molecular pathways contributing to floral attraction are well characterized, offering the opportunity to explore loci potentially underlying variation among individuals. Here, we quantify the range of variation in floral
UV patterning (i.e.UV ‘bulls‐eye nectar guides) among crop and wild accessions ofBrassica rapa . We then use experimental crosses to examine the genetic architecture, candidate loci and biochemical underpinnings of this patterning as well as phenotypic manipulations to test the ecological impact. We find qualitative variation inUV patterning between wild (commonly lackingUV patterns) and crop (commonly exhibitingUV patterns) accessions. Similar to the majority of crops, recombinant inbred lines (RIL s) derived from an oilseed crop ×WI fast‐plant®cross exhibitUV patterns, the size of which varies extensively among genotypes. InRIL s, we further observe strong statistical‐genetic andQTL correlations within petal morphological traits and within measurements of petalUV patterning; however, correlations between morphology andUV patterning are weak or nonsignificant, suggesting thatUV patterning is regulated and may evolve independently of overall petal size.HPLC analyses reveal a high concentration of sinapoyl glucose inUV ‐absorbing petal regions, which, in concert with physical locations ofUV ‐traitQTL s, suggest a regulatory and structural gene as candidates underlying observed quantitative variation. Finally, insects prefer flowers withUV bulls‐eye patterns over those that lack patterns, validating the importance ofUV patterning in pollen‐limited populations ofB. rapa . -
more » « less
Abstract The complexity of environmental factors affecting crops in the field is gradually increasing due to climate change-associated weather events, such as droughts or floods combined with heat waves, coupled with the accumulation of different environmental and agricultural pollutants. The impact of multiple stress conditions on plants was recently termed “multifactorial stress combination” (MFSC) and defined as the occurrence of 3 or more stressors that impact plants simultaneously or sequentially. We recently reported that with the increased number and complexity of different MFSC stressors, the growth and survival of Arabidopsis (Arabidopsis thaliana) seedlings declines, even if the level of each individual stress is low enough to have no significant effect on plants. However, whether MFSC would impact commercial crop cultivars is largely unknown. Here, we reveal that a MFSC of 5 different low-level abiotic stresses (salinity, heat, the herbicide paraquat, phosphorus deficiency, and the heavy metal cadmium), applied in an increasing level of complexity, has a significant negative impact on the growth and biomass of a commercial rice (Oryza sativa) cultivar and a maize (Zea mays) hybrid. Proteomics, element content, and mixOmics analyses of MFSC in rice identified proteins that correlate with the impact of MFSC on rice seedlings, and analysis of 42 different rice genotypes subjected to MFSC revealed substantial genetic variability in responses to this unique state of stress combination. Taken together, our findings reveal that the impacts of MFSC on 2 different crop species are severe and that MFSC may substantially affect agricultural productivity.
-
null (Ed.)Abstract Transposable elements (TEs) pervade most eukaryotic genomes. The repetitive nature of TEs complicates the analysis of their expression. Evaluation of the expression of both TE families (using unique and multi-mapping reads) and specific elements (using uniquely mapping reads) in leaf tissue of three maize (Zea mays) inbred lines subjected to heat or cold stress reveals no evidence for genome-wide activation of TEs; however, some specific TE families generate transcripts only in stress conditions. There is substantial variation for which TE families exhibit stress-responsive expression in the different genotypes. In order to understand the factors that drive expression of TEs, we focused on a subset of families in which we could monitor expression of individual elements. The stress-responsive activation of a TE family can often be attributed to a small number of elements in the family that contains regions lacking DNA methylation. Comparisons of the expression of TEs in different genotypes revealed both genetic and epigenetic variation. Many of the specific TEs that are activated in stress in one inbred are not present in the other inbred, explaining the lack of activation. Among the elements that are shared in both genomes but only expressed in one genotype, we found that many exhibit differences in DNA methylation such that the genotype without expression is fully methylated. This study provides insights into the regulation of expression of TEs in normal and stress conditions and highlights the role of chromatin variation between elements in a family or between genotypes for contributing to expression variation. The highly repetitive nature of many TEs complicates the analysis of their expression. Although most TEs are not expressed, some exhibits expression in certain tissues or conditions. We monitored the expression of both TE families (using unique and multi-mapping reads) and specific elements (using uniquely mapping reads) in leaf tissue of three maize (Zea mays) inbred lines subjected to heat or cold stress. While genome-wide activation of TEs did not occur, some TE families generated transcripts only in stress conditions with variation by genotype. To better understand the factors that drive expression of TEs, we focused on a subset of families in which we could monitor expression of individual elements. In most cases, stress-responsive activation of a TE family was attributed to a small number of elements in the family. The elements that contained small regions lacking DNA methylation regions showed enriched expression while fully methylated elements were rarely expressed in control or stress conditions. The cause of varied expression in the different genotypes was due to both genetic and epigenetic variation. Many specific TEs activated by stress in one inbred were not present in the other inbred. Among the elements shared in both genomes, full methylation inhibited expression in one of the genotypes. This study provides insights into the regulation of TE expression in normal and stress conditions and highlights the role of chromatin variation between elements in a family or between genotypes for contributing to expression.more » « less
-
more » « less
Abstract The integrated responses of biological systems to genetic and environmental variation result in substantial covariance in multiple phenotypes. The resultant pleiotropy, environmental effects, and genotype‐by‐environmental interactions (GxE) are foundational to our understanding of biology and genetics. Yet, the treatment of correlated characters, and the identification of the genes encoding functions that generate this covariance, has lagged. As a test case for analyzing the genetic basis underlying multiple correlated traits, we analyzed maize kernel ionomes from Intermated B73 x Mo17 (
IBM ) recombinant inbred populations grown in 10 environments. Plants obtain elements from the soil through genetic and biochemical pathways responsive to physiological state and environment. Most perturbations affect multiple elements which leads theionome , the full complement of mineral nutrients in an organism, to vary as an integrated network rather than a set of distinct single elements. We compared quantitative trait loci (QTL ) determining single‐element variation toQTL that predict variation in principal components (PC s) of multiple‐element covariance. Single‐element and multivariate approaches detected partially overlapping sets of loci.QTL influencing trait covariation were detected at loci that were not found by mapping single‐element traits. Moreover, this approach permitted testing environmental components of trait covariance, and identified multi‐element traits that were determined by both genetic and environmental factors as well as genotype‐by‐environment interactions. Growth environment had a profound effect on the elemental profiles and multi‐element phenotypes were significantly correlated with specific environmental variables.
