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opencc-by-4.0May 2020View details →

Abiotic stress mediated modulation of chromatin landscape in Arabidopsis thaliana

This dataset include figures and supplementary material for the manuscript entitled "Abiotic stress mediated modulation of chromatin landscape in Arabidopsis thaliana" to be published in Journal of Experimental Botany special issue focused on Chromatin. Supplementary File 1: Table describing read count, mapping percentage and genome coverage from each sample in FAIRE-seq and DNase-seq. Supplementary File 2: List of DHSs obtained from control and stress subjected samples. Supplementary File 3: List of FIRs obtained from control and stress subjected samples. Supplementary File 4: List of uniquely merged OCRs with respective chromatin accessibility score in cold, heat, salt and drought stress. Supplementary File 5: List of GO terms enriched in nrOCRs, SRCRs, and SACRs. Supplementary File 6: List of GO terms enriched in overlapping nrOCRs, SRCRs, and SACRs. Supplementary File 7: List of digital footprints (DFPs) obtained from nrOCRs regions of control-cold, control-heat, control-salt and control-drought pairs. Supplementary File 8: Annotation details of the chromatin regions which were either found to be in state of accessible (CAS > 0.2) or inaccessible (CAS < -0.2) upon exposure to all of the stresses studied (heat, cold, salt and drought stress). Supplementary Fig S1: Overlap of DHSs in control sample of present study with previously published studies. A Venn diagram showing overlap of DNase hypersensitive sites (DHSs) found in control sample of present study and Zhang et al 2010 (A) and Sullivan et al 2014 (B). The statistical significance of overlap is calculate using hypergeometric Fischer`s exact test. Supplementary Fig S2: Genomic locations of DHSs and FIRs A line diagram representing the genomic location of unique DHSs and FIRs over each chromosome. DHSs/FIRs identified from each sample were merged to generate unique non-redundant subset of DHSs/FIRs before plotting over genome. Supplementary Fig S3: Validation of correlation between OCRs and gene expression using microarray. Box plot representing expression of genes (log10(normalised expression)) whose various structual elements fall in OCRs. Supplementary Fig S4: First exons are highly enriched in both DHSs and FIRs  A bar plot showing presence of uFIRs, uDHSs, and ovOCRs in various positions of exon in Arabidopsis genes. The X-axis represent the exon number whereas Y-axis represent the fraction of OCRs found in each exon number. Supplementary Fig S5: Validation of correlation between Ha-SACRs/Ha-SRCRs and gene expression using microarray. Relative expression of genes (log2 fold change) corresponding to Ha-SACRs (Top) and (Ha-SRCRs (bottom) in cold (A), heat (B), salt (C) and drought (D) stress are plotted as box plot (p- value from Mann-Whitney test). To further compare RNA-seq data of salt stress with microarray, RNA-seq data was down-sampled to include genes which were also present in microarray data (E). Supplementary Fig S6: Genomic location of SACRs and SRCRs found in Drought sample. A snapshot of Integrative Genome Viewer (IGV) showing genomic location of stress activated chromatin regions (SACRs) and stress repressed chromatin region (SRCRs) in drought sample. The location of the centromere on each chromosome is shown as green bar IGV track.

opencc-by-4.0Dec 2021View details →

Transcription factors in moss development and defenses against abiotic and biotic stress_dataset

Lists of P. patens genes encoding transcription factors belonging to AP2/ERF, bHLH, GRAS, MYB, NAC and WRKY families differentially expressed in transcriptomes related to response to biotic interactions, abiotic stress, and hormones.

opencc-by-4.0Dec 2021View details →

Effects of sub-lethal single, simultaneous, and sequential abiotic stresses on phenotypic traits of Arabidopsis thaliana

Data and code from: "Effects of sub-lethal single, simultaneous, and sequential abiotic stresses on phenotypic traits of Arabidopsis thaliana" published at Annals of Botany PLANTS. This is a dataset on phenotypic traits of Arabidopsis in response to different abiotic stresses and a reproducible R script to generate all figures and tables in the publication.

Figure 3 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 3. Alfa rarefaction curve observed based on observed species (OTUs) value. The curve has shown flatter to the right, which indicates the comparatively high species richness of the senna italica samples. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.

Figure 1 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 1. (A) Results of clustering: Assembling a group of organisms (The organisms in the same group are similar). (B) The number of OTUs generated for each sample. The Root.1 sample had the most OTUs of 24, while the Leave.1 sample had the fewest of 13. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.

Figure 6. A in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 6. A. The phylum level in Bacteria (bar chart), the bacterial composition of the different samples was similar, while the distribution of each phylum varied in all samples. Based on the V3-V4 region of the 16S rRNA region. Bacterial communities at the phylum classification among the samples (pie chart), as a percentage of the total bacteria isolated from roots and leaves endophyte region. Based on the full-length 16S rRNA sequences. (B) The number of Actinobacteria among the samples. (C) The number of Proteobacteria among the samples. (D) The number of unclassified phyla among the samples. (E) The number of Firmicutes phyla among the samples. (F) The number of Cyanobacteria/Chloroplast among the samples. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.

Figure 5 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 5. Phylogenetic tree based on 16S rRNA gene sequences representing the diversity of endophytic bacterial communities associated with the leaves and roots from the desert medicinal plant Senna italica "at the Phylum level". The tree was constructed using the "one-click" mode in Phylogeny.fr.(Dereeper et al., 2008).

opencc-zeroJan 2021View details →

Multiple genetic trajectories to extreme abiotic stress adaptation in Arctic Brassicaceae

Extreme environments offer powerful opportunities to study how different organisms have adapted to similar selection pressures at the molecular level. The Arctic is one of the most hostile environments on Earth, and the few plant species inhabiting this region typically possess suites of similar morphological and physiological adaptations to extremes in light and temperature. Here we compare patterns of molecular evolution in three Brassicaceae species that have independently colonized the Arctic, and present some of the first genetic evidence for plant adaptations to the Arctic environment. By testing for positive selection and identifying convergent substitutions in orthologous gene alignments for a total of 15 Brassicaceae species, we find that positive selection has been acting on different genes, but similar functional pathways in the three Arctic lineages. The positively selected gene sets identified in the three Arctic species showed convergent functional profiles associated with extreme abiotic stress characteristic of the Arctic. However, there was little evidence for independently fixed mutations at the same sites and for positive selection acting on the same genes. The three species appear to have evolved similar suites of adaptations by modifying different components in similar stress response pathways, implying that there could be many genetic trajectories for adaptation to the Arctic environment. By identifying candidate genes and functional pathways potentially involved in Arctic adaptation, our results provide a framework for future studies aimed at testing for the existence of a functional syndrome of Arctic adaptation in the Brassicaceae and perhaps flowering plants in general.

opencc-zeroJul 2019View details →

Data from: Assessing the influence of biotic, abiotic, and social factors on the physiological stress of a large Neotropical primate in Atlantic Forest fragments

Wildlife physiological responses to environmental and human-related stressors provide useful clues on animal welfare. Non-invasive biomarkers, such as fecal glucocorticoid metabolites (fGCM), allow researchers to assess whether variations in habitat quality, behavior, and climate influence the animals' physiological stress. We examined the role of fragment size, ambient temperature, ripe fruit availability and consumption, percentage of records moving, sex, female reproductive state, and group composition as predictors of the level of fGCM in adult brown howler monkeys (Alouatta guariba clamitans) inhabiting three small (<10 ha) and three large (>90 ha) Atlantic Forest fragments in southern Brazil. We collected bimonthly behavioral data and fecal samples from adult individuals over three years, and used a multimodel inference framework to identify the main predictors of fGCM. We found that the mean (±SD) fGCM in the study groups ranged from 57 ± 49 ng/g to 93 ± 58 ng/g, which were within the known range for howler monkeys. We found 10 best models including five of the 17 tested variables. Sex and reproductive state were the only variables included in all these models. We found that fGCM was higher in nursing females (mean ± SD = 104 ± 73 ng/g) than in non-nursing females (64 ± 55 ng/g) and males (53 ± 40 ng/g, P < 0.05) and that it decreased with increasing ripe fruit consumption and minimum temperature. However, fragment size did not predict fGCM concentration (groups in small fragments = 71 ± 58 ng/g vs. groups in large fragments = 63 ± 54 ng/g, P > 0.05). We conclude that factors related to the energetic balance of individuals play major roles in modulating the physiological stress of brown howler monkeys. Future studies should investigate the consequences of higher levels of stress hormones on howler monkey health and demography.

opencc-zeroJan 2020View details →

Learning‐induced switching costs in a parasitoid can maintain diversity of host aphid phenotypes although biocontrol is destabilized under abiotic stress

Aphid populations frequently include phenotypes that are resistant to parasitism by hymenopterous parasitoid wasps, which is often attributed to the presence of 'protective' facultative endosymbionts residing in aphid tissues, particularly Hamiltonella defensa. In field conditions, under parasitoid pressure, the observed coexistence of aphids with and without protective symbionts cannot be explained by their difference in fitness alone. Using the cereal aphid Rhopalosiphum padi as a model, we propose an alternative mechanism whereby parasitoids are more efficient at finding common phenotypes of aphid and experience a fitness cost when switching to the less common phenotype. We construct a model based on delay differential equations and parameterise and validate the model with values within the ranges obtained from experimental studies. We then use it to explore possible effects on system dynamics under conditions of environmental stress, using our existing data on the effects of drought stress in crops as an example. We show the 'switching penalty' incurred by parasitoids leads to stable coexistence of aphids with and without H. defensa and provides a potential mechanism for maintaining phenotypic diversity amongst host organisms. We show that drought-induced reduction in aphid development time has little impact. However, greater reduction in fecundity on droughted plants of symbiont-protected aphids can cause insect population cycles when the system would be stable in the absence of drought stress. The stabilising effect of the increased efficiency in dealing with more commonly encountered host phenotypes is applicable to a broad range of consumer-resource systems and could explain stable coexistence in competitive environments. The loss of stable coexistence when drought has different effects on the competing aphid phenotypes highlights the importance of scenario testing when considering biocontrol for pest management.

opencc-zeroMar 2022View details →

Abiotic stress and biotic factors mediate range dynamics on opposing edges

Aim: In the face of global change, understanding causes of range limits is one of the most pressing needs in biogeography and ecology. A prevailing hypothesis is that abiotic stress forms cold (upper latitude/altitude) limits whereas biotic interactions create warm (lower) limits. A new framework – Interactive Range-Limit Theory (iRLT) – asserts that positive biotic factors such as food availability can ameliorate abiotic stress along cold edges, whereas abiotic stress can have a positive effect and mediate biotic interactions (e.g., competition) along warm limits. Location: Northeastern US Taxon: Carnivora Methods: We evaluated two hypotheses of iRLT using occupancy and structural equation modeling (SEM) frameworks based on data collected over a six-year period (2014–2019) of six carnivore species across a broad latitudinal (42.8–45.3°N) and altitudinal (3–1451 m) gradient. Results: We found that snow directly limits populations, but prey or habitat availability can influence range dynamics along cold edges. For example, bobcats (Lynx rufus) and coyotes (Canis latrans) were limited by deep snow and long winters, but the availability of prey had a strong positive effect. Conversely, snow had a strong positive effect on the warm limits of Canada lynx (Lynx canadensis), countering the negative effect of competition with the phylogenetically-similar bobcat and with coyotes, highlighting how climate mediates competition between species. Main conclusions: We used an integrated dataset that included competitors and prey species collected at the same spatial and temporal scale. As such, this design, along with a causal modeling framework (SEM), allowed us to evaluate community-wide hypotheses at macroecological scales and identify coarse-scale drivers of species' range limits. Our study supports iRLT and underscores the need to consider direct and indirect mechanisms for studying range dynamics and species' responses to global change.