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How is the rate of transcription influenced by temperature?

How is the rate of transcription influenced by temperature?


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How is the rate of transcription influenced by temperature? More precisely, I am looking for an article who quantitatively measured the rate of transcription of an "average gene" and show how this rate is influenced by temperature.

On this question @Chris found this article where such measurement were performed but they were using some arbitrary unit (as it as been pointed out by @shigeta here) that cannot be related to any comprehensive unit such as "mole of amino acid per hours" or something like that.


If your looking at transcription then your talking about RNA POLYMERASE.

And there are many variants. Here's a good Nature paper that discusses temperature and RNA Pol

http://www.nature.com/ncomms/journal/v1/n6/full/ncomms1076.html

And another:

http://www.ncbi.nlm.nih.gov/m/pubmed/12729734/

I couldn't get full access to this JBC paper but I think the answer would be clearly in here, prob worth a look

M. Chamberlin and J. Ring. Characterization of T7-specific ribonucleic acid polymerase. 1. General properties of the enzymatic reaction and the template specificity of the enzyme. J Biol Chem. 248: 2235-44 (1973)


Important Factors That Influence Enzyme Activity

Enzymes are essential for almost all the chemical reactions that take place inside living cells. However, the activities of the enzymes can be enhanced or inhibited by a number of factors. In this article, we are talking about all those factors that affect enzyme activity. Read on.

Enzymes are essential for almost all the chemical reactions that take place inside living cells. However, the activities of the enzymes can be enhanced or inhibited by a number of factors. In this article, we are talking about all those factors that affect enzyme activity. Read on…

Enzymes are protein-based complex molecules produced by the cells. There are several enzymes which are involved with different biochemical reactions. Each of these enzymes present in our body can influence any one particular chemical reaction or a set of reactions. They serve as organic catalysts and enhance the speed of the reactions in which they take part. In the absence of an enzyme, the speed of a chemical reaction becomes extremely slow. Some of these reactions may not occur if the right kind of enzyme is not present in the body.


Context-specific influence of water temperature on brook trout growth rates in the field

The Nature Conservancy – Connecticut River Program, AG Annex A, University of Massachusetts, Amherst, MA, U.S.A.

S.O. Conte Anadromous Fish Research Center, US Geological Survey/Leetown Science Center, Turners Falls, MA, U.S.A.

S.O. Conte Anadromous Fish Research Center, US Geological Survey/Leetown Science Center, Turners Falls, MA, U.S.A.

Northern Research Station, USDA Forest Service, University of Massachusetts, Amherst, MA, U.S.A.

The Nature Conservancy – Connecticut River Program, AG Annex A, University of Massachusetts, Amherst, MA, U.S.A.

S.O. Conte Anadromous Fish Research Center, US Geological Survey/Leetown Science Center, Turners Falls, MA, U.S.A.

S.O. Conte Anadromous Fish Research Center, US Geological Survey/Leetown Science Center, Turners Falls, MA, U.S.A.

Northern Research Station, USDA Forest Service, University of Massachusetts, Amherst, MA, U.S.A.

Summary

1. Modelling the effects of climate change on freshwater fishes requires robust field-based estimates accounting for interactions among multiple factors.

2. We used data from an 8-year individual-based study of a wild brook trout (Salvelinus fontinalis) population to test the influence of water temperature on season-specific growth in the context of variation in other environmental (i.e. season, stream flow) or biotic factors (local brook trout biomass density and fish age and size) in West Brook, a third-order stream in western Massachusetts, U.S.A.

3. Changes in ambient temperature influenced individual growth rates. In general, higher temperatures were associated with higher growth rates in winter and spring and lower growth rates in summer and autumn. However, the effect of temperature on growth was strongly context-dependent, differing in both magnitude and direction as a function of season, stream flow and fish biomass density.

4. We found that stream flow and temperature had strong and complex interactive effects on trout growth. At the coldest temperatures (in winter), high stream flows were associated with reduced trout growth rates. During spring and autumn and in typical summers (when water temperatures were close to growth optima), higher flows were associated with increased growth rates. In addition, the effect of flow at a given temperature (the flow-temperature interaction) differed among seasons.

5. Trout density negatively affected growth rate and had strong interactions with temperature in two of four seasons (i.e. spring and summer) with greater negative effects at high temperatures.

6. Our study provided robust, integrative field-based estimates of the effects of temperature on growth rates for a species which serves as a model organism for cold-water adapted ectotherms facing the consequences of environmental change. Results of the study strongly suggest that failure to derive season-specific estimates, or to explicitly consider interactions with flow regime and fish density, will seriously compromise our ability to predict the effects of climate change on stream fish growth rates. Further, the concordance we found between empirical observations and likely energetic mechanisms suggests that our general results should be relevant at broader spatial and temporal scales.


Influence of Temperature on Rate of Regeneration in the Time-graded Regeneration Field in Planarians

Agnes Brøndsted, H. V. Brøndsted Influence of Temperature on Rate of Regeneration in the Time-graded Regeneration Field in Planarians. Development 1 March 1961 9 (1): 159–166. doi: https://doi.org/10.1242/dev.9.1.159

There exists in planarians a time-graded regeneration field for head regeneration (Brøndsted, 1946, 1956 A. & H. V. Brøndsted, 1952). The characteristics of this field, expressed by rate of regeneration, are species-specific. The existence of this field ensures harmonious regeneration from cuts everywhere in the body, as a cut will always expose a ‘high point’ where regeneration of a head starts with greatest speed, thus taking the lead in organization and at the same time inhibiting head-forming tendencies elsewhere in the blastema (Brøndsted, 1956).

The factors underlying these characteristics of the field are unknown the problems involved are being attacked from several angles in our laboratory. For the sake of this work it is of some interest to know how the different rates of regeneration at various levels in the time-graded fields might be influenced by various temperature levels.

Material and Methods The experiments were carried out on two species differing greatly in the characteristics of their time-graded regeneration fields.


MATERIALS AND METHODS

Nematode rearing

Plectus murrayi Yeates 1970 collected from soils and sediments in Taylor Valley (77°S latitude, 163°E longitude), Antarctica, site of the NSF McMurdo Dry Valley Long Term Ecological Research site, were reared in mass culture to generate sufficient quantities for experimental and control treatments. Nematodes were cultured in sand agar plates (15 g l −1 of Bacto-agar) containing 20 ml l −1 Bold's Modified Basal Freshwater (BMBF) nutrient media (Sigma Aldrich Inc., St Louis, MO, USA) as described previously (Adhikari et al., 2009). The sand agar plates with nematodes were incubated at 26°C for 1–2 weeks followed by 15°C for 3–5 weeks. Nematodes were stored at 4°C for 1–2 weeks before being harvested for experiments.

Effect of desiccation treatment on survival

RH was controlled using saturated salt solutions (Winston and Bates, 1960) in glass desiccation chambers (Ginsberg Scientific Inc., Fort Collins, CO, USA). Required RH was maintained at 4±0.2°C in the desiccation chamber for 3 days for equilibration prior to the addition of nematodes. Humidity was maintained as 100% RH with distilled water vapor, and as 98%, 85%, 75%, 50% and 35% RH with different saturated salt solutions, while 0% RH was maintained with Drierite desiccant (Drierite Co. Ltd, Xenia, OH, USA).

To assess the survival of nematodes after exposure to different RH conditions, a 100 μl suspension containing approximately 200 nematodes was put in a 35 mm Petri dish and placed in desiccation chambers maintained at 4±0.2°C. Treatments consisted of exposure to 98%, 75%, 35%, 98%+85%+…+0% (exposed to a gradual decrease in RH from 98% to 85%, 75%, 50% and 35% RH for 6 h each before exposure to 0% RH) and 0% RH for 10 days. Nematodes were rehydrated in water at 4°C for 24 h. Viability was determined by nematode movement. Where nematodes were static a hair probe was used to stimulate movement. Nematodes not moving after this stimulus were recorded as dead. All experiments were repeated at least 3 times under identical conditions using mixed stage populations.

Effect of slow desiccation and freezing on survival

To assess the effect of slow desiccation on nematode survival, a 100 μl suspension containing approximately 200 nematodes was put in a 35 mm Petri dish and placed in the desiccation chambers with different RH. Treatments consisted of exposure for 3 and 7 days to 75% RH with (pretreat+desiccation) or without (desiccation) pretreatment at 98% (for 12 h) followed by 85% RH (for 12 h). Nematode viability and survival was determined as mentioned above.

To assess the effect of gradual freezing on nematode survival, a 100 μl suspension containing approximately 200 nematodes was put in a 1.7 ml Eppendorf tube and placed in a temperature chamber (Cincinnati Subzero Products Inc., Cincinnati, OH, USA) which can control temperature from −30°C to 100°C with a cooling rate of 1°C h −1 . Nematodes were either directly exposed to −10°C (freezing) or exposed to gradual cooling from 4°C to −10°C (pretreat+freezing) at a rate of 1°C h −1 for 3 and 7 days. At least three replicates were performed for each treatment and survival was assessed as described above.

Stress treatment and gene expression

The effect of desiccation treatment on gene expression was measured by putting a 200 μl suspension containing approximately 1000 nematodes in a 35 mm Petri dish and exposing them to different RH. Treatments consisted of pretreatment (exposure to 98% RH followed by 85% RH for 12 h each), pretreat+desiccation (exposure to 75% RH for 3 days after pretreatment), desiccation (direct exposure to 75% RH for 3 days without pretreatment), pretreat+ rehydration (rehydration in water at 4°C after pretreat+desiccation) and rehydration (rehydration in water after desiccation).

To assess the effect of freeze treatment on gene expression, a 200 μl suspension containing approximately 1000 nematodes was put in a 1.7 ml Eppendorf tube and placed in a temperature chamber. Treatments were pretreatment (exposure to 4°C for 24 h), freezing (direct exposure to −10°C for 3 days), pretreat+freezing (exposure to gradual cooling from 4°C to −10°C at a rate of 1°C h −1 and left at the final temperature for 3 days), pretreat+recovery (recovery in water at 4°C after pretreat+freezing) and recovery (recovery in water at 4°C after freezing).

Survival of freezing after desiccation

To determine whether prior desiccation enhances the freezing survival of nematodes, a 100 μl suspension containing approximately 200 nematodes was put in a 1.7 ml Eppendorf tube and exposed to 98% followed by 85% RH at 4°C for 12 h each. Those tubes with nematodes were placed in the controlled temperature chamber and exposed to gradual cooling from 4°C to −10°C (desiccation+ freezing) at a rate of 1°C h −1 and left at the final temperature for 3 (short exposure) and 7 (long exposure) days. Nematodes were allowed to recover in water at 4°C for 24 h and mortality was assessed as described above.

Primer design and gene selection

Genes were chosen from the list of transcripts differentially expressed during desiccation stress (Adhikari et al., 2009). Eight different genes with functional roles in stress response, metabolism and signal transduction were selected for the study. Primers were designed from ESTs (selected by subtractive hybridization of desiccated and fresh nematodes) using PrimerQuest™ from IDT (Coralville, IA, USA) and synthesized by Operon Biotechnologies Inc. (Huntsville, AL, USA) (Table 1).

RNA extraction and cDNA synthesis

Total RNA for quantitative real-time PCR was extracted using Trizol reagent (Molecular Research Center Inc., Cincinnati, OH, USA) from nematodes exposed to each of the different treatments. Three replicates of each stress treatment (plus three groups of controls) were used for RNA extraction, yielding three independent RNA extracts for each different treatment combination. Nematodes exposed to different treatments were directly homogenized in liquid nitrogen, mixed with Trizol reagent, and the suspension exposed to three freeze–thaw cycles using liquid nitrogen and a 37°C water bath. The suspension was ground using mortar and pestle, and vortexed 40 ml of chloroform was added, and the tubes were shaken vigorously for 15 s and then incubated further for 5 min at room temperature. After centrifugation (15 min, 12,000 g, 4°C), the aqueous phase containing RNA was separated from the other phases, which were stored for DNA preparation (see below). The colorless upper aqueous phase was transferred into fresh vials to precipitate the RNA by addition of 100 ml isopropyl alcohol. The samples were incubated for 10 min and centrifuged (20 min, 12,000 g, 4°C). The RNA precipitates were then washed twice with 75% ethanol, air dried, eluted in nuclease-free water, and quantified and quality checked via a spectrophotometer (A260/A280>1.9 NanoDrop ND-1000, NanoDrop Technologies, Wilmington, DE, USA) and agarose gel electrophoresis.

Reverse transcription (RT) was performed with 1 μg of total RNA from each specimen. RT reaction of polyadenylated mRNA to cDNA was done using ImPromp-II™ reverse transcriptase (Promega Corporation, Madison, WI, USA) and an oligo(dT) primer. Total RNA was incubated with 20 pmol oligo(dT) primer at 70°C for 5 min and quickly chilled on ice. The reverse transcription mix (20 μl) was prepared by mixing 4 μl of ImPromp-II 5 × reaction buffer, 2.4 μl (3 mmol l −1 ) MgCl2 and 1 μl dNTP mix (10 mmol l −1 each dNTP). Nuclease-free water (6.6 μl) was added, vortexed, and 1 μl of ImPromp-II reverse transcriptase was added. The reverse transcription mixture was mixed with RNA template and incubated at 25°C for 5 min for annealing and the first strand was extended for 60 min at 42°C. Reverse transcriptase was inactivated by heating to 70°C for 15 min. The cDNA was precipitated in 100% ethanol and washed twice with 75% ethanol, air-dried and dissolved in DEPC-treated water.

Quantitative real-time RT-PCR

Quantitative real-time PCR was performed with LightCycler 480 SYBER Green I mastermix (three replicate samples for each treatment–time combination) and gene-specific primers in a Light Cycler 480 RT-PCR system (Roche Applied Science, Indianapolis, IN, USA) equipped with LightCycler 480 software, with the following program: 3 min at 95°C 45 repeats of 30 s at 94°C, 30 s at 58°C and 1 min at 72°C followed by a standard melt curve. The real-time PCR reaction mixture contained the following items in a final volume of 10 ml: 3 μl PCR grade water, 5 μl PCR primers (20 pmol μl −1 ), 5 μl double concentrated SYBR Green mastermix and 1 μl template DNA. Negative control reactions containing water in place of cDNA were included in each batch of PCR reactions to ensure that contamination was not a problem. To minimize mRNA quantification errors and genomic DNA contamination biases, and to correct for inter-sample variation, we used 18S ribosomal RNA (Pm-18S) of P. murrayi as an internal control.

List of gene-specific primers used in quantitative real-time RT-PCR analysis


RESULTS

PlaNET-seq robustly detects nascent RNAPII transcription in Arabidopsis

To purify RNAPII complexes, we relied on a FLAG-immunoprecipitation of the second-largest RNAPII subunit (NRPB2-FLAG). The NRPB2-FLAG construct covers lethal null-alleles of nrpb2, which makes these lines suitable to capture RNAPII as all complexes carry the tagged NRPB2 subunit ( 24). The stable line shows wild-type phenotype. We used the nuclear fraction of flash-frozen Arabidopsis seedlings as starting material (Figure 1A). RNAPII complexes were immunoprecipitated with high efficiency ( Supplementary Figure S1A ), and nascent RNA was purified and used for library construction ( Supplementary Figure S1B ). Processed reads were aligned to the Arabidopsis genome, identifying positions of the nascent RNA 3′-ends (Figure 1B, upper panel). Visualized in a genome browser, plaNET-seq shows the characteristic ‘spiky’ pattern that represents the nascent RNAPII transcription at each nucleotide. Our plaNET-seq libraries showed high reproducibility (Pearson coefficient r > 0.98) between replicates and confirmed low-velocity nascent RNAPII transcription at gene boundaries ( Supplementary Figure S1C–F ). We also generated a mock-IP plaNET-seq library to assess the stringency of our protocol. The mock-IP signal showed weak correlation to the signal from a FLAG-IP library ( Supplementary Figure S1G , Pearson coefficient r < 0.35). The signal of mock-IP plaNET-seq libraries was extremely low, supporting FLAG-IP specific signal corresponding to nascent RNAPII transcription in our samples (Figure 1B, Supplementary Figure S1H ). Our protocol is gel-free and differs in some steps from the published pNET-seq protocol. For example, the FLAG antibody is used instead of endogenous RNAPII antibodies at the IP step ( Supplementary Figure S2A–C ). Our libraries of nascent RNA appeared enriched for intronic reads and reads downstream of the annotated poly-(A)-site that represented RNAPII complexes undergoing termination of transcription. Steady-state methods such as RNA-seq do not provide this information on nascent RNAPII transcription, further supporting our successful enrichment for nascent RNA (Figure 1B). We called transcripts de novo from plaNET-seq data using the groHMM algorithm ( 32) and identified thousands of transcripts not annotated in Araport11 (Figure 1C and D, Supplementary Table S1 ). The majority of these novel transcripts were in proximity to known genes, or overlapping them on the antisense strand (Figure 1C and D). Overall, RNA-seq data correlated well with our plaNET-seq data for annotated transcripts but poorly for unannotated transcripts, emphasizing the power of plaNET-seq to capture transcripts undergoing rapid RNA degradation ( Supplementary Figure S2D and E ).

Genome-wide detection of nascent transcription in response to low temperature with plaNET-seq. (A) Workflow of plaNET-seq. Chromatin from a stable NRPB2-FLAG line is isolated and DNase I treated. After immunoprecipitation and disruption of protein complexes, RNAPII-attached RNA is purified and used for library construction. The base at the 3′-end of the sequenced RNA is the last base added by the RNAPII complex and therefore aligns to the genomic position of transcriptionally engaged RNAPII. (B) An example of plaNET-seq coverage profile for the gene At2g28305. Positions of RNAPII are shown for sense (blue) and antisense (red) strands. For comparison, mock-IP (negative control) plaNET-seq sample, as well as stranded RNA-seq, TSS-seq (transcription start site sequencing) and DR-seq (direct RNA sequencing) tracks are also shown. The DR-seq track reveals sites of mRNA cleavage and polyadenylation (PAS). (C) Definition of novel transcripts detected by plaNET-seq. Divergent transcripts initiate no more than 500 bp upstream of a coding transcript TSS. Upstream transcripts initiate on the sense strand and partly overlap with an annotated transcript. Convergent transcripts initiate from the 5′-half of a coding gene body on the antisense strand. PAS-associated transcripts initiate from the 3′-half or no more than 20% downstream of its length on the antisense strand. Downstream transcripts initiate within a gene on the sense strand and continue beyond the annotated PAS. Distal antisense transcripts overlap with annotated gene on the antisense strand but initiate further downstream than 20% of the gene's length. Finally, if a transcript was not described by any of the above mentioned classes, it was defined as an intergenic transcript. (D) Bar chart of the number of transcripts that fall into the classes described in (A). Known non-coding transcripts in Araport11 are shown in checkered fill and novel transcript identified by plaNET-seq without fill.

Genome-wide detection of nascent transcription in response to low temperature with plaNET-seq. (A) Workflow of plaNET-seq. Chromatin from a stable NRPB2-FLAG line is isolated and DNase I treated. After immunoprecipitation and disruption of protein complexes, RNAPII-attached RNA is purified and used for library construction. The base at the 3′-end of the sequenced RNA is the last base added by the RNAPII complex and therefore aligns to the genomic position of transcriptionally engaged RNAPII. (B) An example of plaNET-seq coverage profile for the gene At2g28305. Positions of RNAPII are shown for sense (blue) and antisense (red) strands. For comparison, mock-IP (negative control) plaNET-seq sample, as well as stranded RNA-seq, TSS-seq (transcription start site sequencing) and DR-seq (direct RNA sequencing) tracks are also shown. The DR-seq track reveals sites of mRNA cleavage and polyadenylation (PAS). (C) Definition of novel transcripts detected by plaNET-seq. Divergent transcripts initiate no more than 500 bp upstream of a coding transcript TSS. Upstream transcripts initiate on the sense strand and partly overlap with an annotated transcript. Convergent transcripts initiate from the 5′-half of a coding gene body on the antisense strand. PAS-associated transcripts initiate from the 3′-half or no more than 20% downstream of its length on the antisense strand. Downstream transcripts initiate within a gene on the sense strand and continue beyond the annotated PAS. Distal antisense transcripts overlap with annotated gene on the antisense strand but initiate further downstream than 20% of the gene's length. Finally, if a transcript was not described by any of the above mentioned classes, it was defined as an intergenic transcript. (D) Bar chart of the number of transcripts that fall into the classes described in (A). Known non-coding transcripts in Araport11 are shown in checkered fill and novel transcript identified by plaNET-seq without fill.

Characterization of divergent and convergent transcription

To further characterize the novel transcripts detected by plaNET-seq, we defined transcripts that start upstream (0–500 bp) from the TSS of a protein-coding gene but on the opposite strand as divergent non-coding transcripts (DNC) (Figures 1C and 2A). DNC represents an important source of lncRNA transcription in yeast and metazoans ( 16, 35–37), but the presence of DNC in Arabidopsis has been questioned ( 38). plaNET-seq provided evidence for DNC at 917 protein-coding genes and the DNC transcription start site (divTSS) was most often located 200–400 bp upstream from the coding TSS (Figure 2B). Thus, these data support the presence of DNC in plant genomes, although to a lower extent compared to yeast or mammals. An example of DNC was identified at the At3g28140 locus (Figure 2C). In general, genes driving DNC in plants had higher nascent RNAPII transcription on the coding strand compared to non-DNC genes (Figure 2D), indicating that DNC was associated with Nucleosome Depleted Regions (NDRs) of highly expressed genes. Metagene analyses of DNC using TSS-seq data in the hua enhancer 2-2 mutant (hen2-2, a nuclear exosome mutant) ( 39) showed DNC degradation by the nuclear exosome in Arabidopsis (Figure 2E), similar as in yeast and metazoans ( 36, 40). DNC promoters had higher nucleosome density in the divergent non-coding direction compared to a control set of genes with similar transcription level ( Supplementary Figure S3A ). DNC promoters exhibited NDRs with well-defined flanking –1 and +1 nucleosomes ( Supplementary Figure S3B ). In conclusion, DNC transcription shares regulatory principles with budding yeast ( 41), an association with high definition of the –1 nucleosome, and is repressed by co-transcriptional RNA degradation ( 42).

Divergent transcription occurs at highly active NDRs. (A) Schematic illustration of a divergent promoter. The nucleosomes surrounding the shared NDR are defined as –1 (DNC direction) and +1 (coding direction). (B) Histogram and kernel density of the absolute distance between start site for the divergent transcript (divTSS) and the coding TSS (bp). (C) An example of a divergent promoter (At3g28140). Nascent RNAPII transcription is shown for sense and divergent transcripts in blue and purple, respectively. (D) Box plot of transcription level of protein-coding genes with a DNC (purple) and without a DNC (gray) as measured by plaNET-seq. Statistical significance of differences was assessed by two-sided Mann–Whitney U test. (E) Metagene analysis of TSS-seq signal on the antisense strand of DNC promoters. Wild type signal is shown in black and the nuclear exosome mutant hen2–2 in red. DNC could be detected with TSS-seq data and DNC were targeted by the nuclear exosome. The shaded area shows 95% confidence interval for the mean.

Divergent transcription occurs at highly active NDRs. (A) Schematic illustration of a divergent promoter. The nucleosomes surrounding the shared NDR are defined as –1 (DNC direction) and +1 (coding direction). (B) Histogram and kernel density of the absolute distance between start site for the divergent transcript (divTSS) and the coding TSS (bp). (C) An example of a divergent promoter (At3g28140). Nascent RNAPII transcription is shown for sense and divergent transcripts in blue and purple, respectively. (D) Box plot of transcription level of protein-coding genes with a DNC (purple) and without a DNC (gray) as measured by plaNET-seq. Statistical significance of differences was assessed by two-sided Mann–Whitney U test. (E) Metagene analysis of TSS-seq signal on the antisense strand of DNC promoters. Wild type signal is shown in black and the nuclear exosome mutant hen2–2 in red. DNC could be detected with TSS-seq data and DNC were targeted by the nuclear exosome. The shaded area shows 95% confidence interval for the mean.

In addition to DNC, groHMM detected 5313 novel transcripts that overlap a single annotated gene transcription unit fully or partially on the antisense strand (Figure 3A). We considered novel transcripts as antisense transcripts when they either started internally of a host gene, or no more than 20% of its length downstream (n = 4922). We detected two preferential initiation sites for such antisense transcripts along the gene body (Figure 3A). The predominant peak of initiation site frequency was found at the 3′-end of genes, defined as PAS-associated antisense transcription (n = 3223). The second peak was located within the first 50% of the gene body, and we defined these transcripts as convergent antisense transcripts (CAS n = 1699). CASs have been detected in human cells ( 13, 19) but have so far been uncharacterized in plants. The TSS of convergent transcripts (casTSS) most often initiated at a distance between 250 and 1000 bp from the sense TSSs ( Supplementary Figure S4A ), exemplified by the At2g46710 gene (Figure 3B). Interestingly, casTSSs showed a strong bias towards early exon-intron boundaries with a peak very close to the first 5′ splice site (5′SS, Figure 3C). Over 50% of all CAS initiated from the host gene's first exon or intron ( Supplementary Figure S4B ). Moreover, genes harboring a CAS had a significantly longer first exon and intron, indicating that a specific 5′-gene structure correlates with CAS expression ( Supplementary Figure S4B ). The nucleosome density upstream of the casTSS showed a sharp decrease, suggesting an intragenic NDR ( Supplementary Figure S4C ). Interestingly, when we assigned previously described chromatin states ( 34) to the bodies of Arabidopsis genes and explored where CAS transcription initiated, we detected an over-representation of casTSS within the chromatin states we denoted as promoter-to-early elongation ( Supplementary Figure S4D and E ). This indicated that the CAS initiation region coincided with a location where RNAPII complexes enter productive elongation. Genes giving rise to CAS had higher sense strand transcription compared to genes without detectable CAS (Figure 3D). These data indicated an association of CAS with a subset of highly transcribed genes. In addition, a comparison of TSS-seq data in wild type Col-0 seedlings and hen2-2 mutants showed that CAS transcripts are nuclear exosome targets (Figure 3E). Thus, we characterized Arabidopsis CAS as nuclear exosome targets that initiate from a NDR in promoter-proximal intervals of highly expressed genes with a long first exon and intron. All in all, our plaNET-seq data highlights the strength of a nascent RNA detection method to identify cryptic non-coding transcripts.

Convergent antisense transcription is a common feature in Arabidopsis. (A) Histogram of the relative distance between initiation sites of antisense transcripts and the sense TSS (expressed as fraction of the sense gene length). Antisense transcription was defined either as convergent (if initiated within the first 50% of the sense gene length: red bars), or as PAS-associated (if initiated within the second 50% of the sense gene length or after the PAS up to a distance of 20% of the gene length after the gene end). (B) An example of a convergent transcript (At2g46710). Nascent RNAPII transcription is shown for sense and convergent transcripts in blue and red, respectively. (C) Histogram of the relative positions of casTSS between the first and the second 5′ splice sites (5′SS). (D) Box plot of transcription level of coding transcripts with a CAS and without a CAS. Statistical significance of the difference was measured by two-sided Mann–Whitney U test. Genes with a CAS showed higher transcription in the sense direction compared to those without a CAS. (E) Metagene analysis of TSS-seq signal on the antisense strand in 1 kb windows anchored at the casTSS. Wild type signal is shown in black and the nuclear exosome mutant hen2–2 in red. At least some CAS could be detected with TSS-seq data, and they are targeted by the nuclear exosome. The shaded area shows 95% confidence interval for the mean.

Convergent antisense transcription is a common feature in Arabidopsis. (A) Histogram of the relative distance between initiation sites of antisense transcripts and the sense TSS (expressed as fraction of the sense gene length). Antisense transcription was defined either as convergent (if initiated within the first 50% of the sense gene length: red bars), or as PAS-associated (if initiated within the second 50% of the sense gene length or after the PAS up to a distance of 20% of the gene length after the gene end). (B) An example of a convergent transcript (At2g46710). Nascent RNAPII transcription is shown for sense and convergent transcripts in blue and red, respectively. (C) Histogram of the relative positions of casTSS between the first and the second 5′ splice sites (5′SS). (D) Box plot of transcription level of coding transcripts with a CAS and without a CAS. Statistical significance of the difference was measured by two-sided Mann–Whitney U test. Genes with a CAS showed higher transcription in the sense direction compared to those without a CAS. (E) Metagene analysis of TSS-seq signal on the antisense strand in 1 kb windows anchored at the casTSS. Wild type signal is shown in black and the nuclear exosome mutant hen2–2 in red. At least some CAS could be detected with TSS-seq data, and they are targeted by the nuclear exosome. The shaded area shows 95% confidence interval for the mean.

Low temperature lead to major re-programming of nascent RNAPII transcription

In addition to the capture of cryptic transcripts, NET-seq interrogates the RNAPII transcription dynamics over coding and non-coding transcription units, revealing regions of low-velocity transcription. The link between temperature and transcriptional output in plants ( 3) lead us to hypothesize that chilling temperatures may regulate nascent RNAPII transcription over these regions. Therefore, we exposed seedlings to early stages of cold-acclimation (3 and 12 h at 4°C, Figure 4A). Numerous transcripts had significantly changed plaNET-seq signal over their transcription units in our conditions (Figure 4B, Supplementary Table S2 ). The number of differentially transcribed known genes at 3 h at 4°C versus 22°C greatly exceeded those detected as differentially expressed in the same conditions and identical cut off values by Transcription Start Site sequencing (TSS-seq) ( 2). These data suggest that the detection of steady-state levels of RNA species (i.e. by TSS-seq) does not fully capture the actual changes in nascent transcription during exposure to 4°C (Figure 4C) ( 2). Strikingly, 47% and 50% of known transcripts which were upregulated or downregulated after 3 h at 4°C, returned to baseline levels after 12 h at 4°C (Figure 4D), suggesting transient re-programming of nascent RNAPII transcription. Nascent transcription of the novel non-coding transcripts was also affected by the cold treatment, as shown on metagene plots for divergent, convergent and PAS-associated antisense transcripts (Figure 4E– G). We detected a rapid decrease of plaNET-seq signal after 3 h at 4°C that reverted back to or close to control levels after 12 h at 4°C. Thus, our results support the notion that transcription of many non-coding transcripts respond rapidly to a changing environment ( 43). Taken together, plaNET-seq detected genome-wide transcriptional changes with increased sensitivity compared to steady-state methods and revealed a major re-programming of nascent RNAPII transcription in response to chilling temperatures.

Low temperature leads to re-programming of nascent RNAPII transcription. (A) Illustration of the experimental design of low temperature exposure. Seedlings were grown for 12 days under a long day light regime on agar plates. Exposure to low temperature was performed for 3 or 12 h during the light hours and samples were collected and flash frozen in liquid nitrogen. (B) The number of differentially transcribed genes determined by plaNET-seq in response to low temperature treatment. (C) Numbers of up- and down-regulated transcripts after 3 h at 4°C (compared to the control grown at 22°C) as determined by DESeq2 using plaNET-seq and TSS-seq data. The transcriptional changes detected by plaNET-seq exceeded those detected with the same cutoff values by TSS-seq. (D) Schematic time course of how many genes which were found differentially transcribed after 3 h at 4°C have returned to the baseline expression at 12 h at 4°C. (E-G) Metagene analysis of the plaNET-seq signal in a 1 kb window centered at (E) divTSS, (F) casTSS and (G) PAS-AS TSS. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. The shaded area shows 95% confidence interval for the mean.

Low temperature leads to re-programming of nascent RNAPII transcription. (A) Illustration of the experimental design of low temperature exposure. Seedlings were grown for 12 days under a long day light regime on agar plates. Exposure to low temperature was performed for 3 or 12 h during the light hours and samples were collected and flash frozen in liquid nitrogen. (B) The number of differentially transcribed genes determined by plaNET-seq in response to low temperature treatment. (C) Numbers of up- and down-regulated transcripts after 3 h at 4°C (compared to the control grown at 22°C) as determined by DESeq2 using plaNET-seq and TSS-seq data. The transcriptional changes detected by plaNET-seq exceeded those detected with the same cutoff values by TSS-seq. (D) Schematic time course of how many genes which were found differentially transcribed after 3 h at 4°C have returned to the baseline expression at 12 h at 4°C. (E-G) Metagene analysis of the plaNET-seq signal in a 1 kb window centered at (E) divTSS, (F) casTSS and (G) PAS-AS TSS. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. The shaded area shows 95% confidence interval for the mean.

Exons and co-transcriptional splicing represent transient transcriptional barriers at low temperature

The re-programming of nascent RNAPII transcription in response to chilling temperatures prompted us to look closer at the effects on coding regions in the genome. Eukaryotic genes have exon–intron architecture where introns are co-transcriptionally spliced out to form a functional mRNA. The close proximity of a transcribing RNAPII complex and the spliceosome is detected with NET-seq ( 15, 21). Splicing intermediates can readily be detected in NET-seq data, in particular the 5′ splice site (5′SS) that is protected by the co-purified spliceosome (Figure 5A), as previously reported in human NET-seq ( 15). We thus filtered out these read positions in our analysis since the RNAPII-associated RNA 3′-ends through co-purification of the spliceosome may not precisely inform on the position of nascent RNAPII transcription ( 15). Interestingly, when we analyzed the fraction of 5′SS reads in our low temperature exposed plaNET-seq samples, we detected a strong genome-wide decrease of 5′SS reads after 3 h at 4°C compared to 22°C (Figure 5B and C, Supplementary Figure S5A ). The decrease reverted back to control levels after 12 h at 4°C, suggesting that the kinetics of the splicing reaction was initially affected by low temperature (Figure 5B). Moreover, we detected a transient increase of the exon to intron ratio of nascent RNAPII transcription after 3 h at 4°C compared to 22°C and 12 at 4°C (Figure 5D). These data indicated a transiently increased nascent RNAPII transcription over exons at 4°C. Consistently, many of the transcripts upregulated after 3 h were relatively long, multi-exonic genes compared to downregulated genes, whereas an inverse relationship was detected for expression changes from 3 h to 12 h at 4°C ( Supplementary Figure S5B and C ).

The effect of splicing and intragenic RNAPII stalling. (A) Illustration of the RNAPII–spliceosome complex during active transcription. The spliceosome protects the 5′SS and the splicing intermediates are co-purified with transcriptionally engaged RNAPII complex in NET-seq. (B) Bar chart of the percentage of 5′SS intermediates found in the control and low temperature exposed replicates of plaNET-seq. (C) The effect of chilling temperature on 5′SS species for the gene At3g11070. (D) Histogram showing the ratio between plaNET-seq reads mapping to all exons and all introns in the replicates of low temperature treatment. (E) RT-qPCR validation of the plaB treatment efficiency (shown for a splicing event of the At2g39550 mRNA). Bars represent mean ± SEM of three biological replicates (circles). The statistical significance of differences was calculated by two-sided t-test. *P < 0.05, **P < 0.01. (F) PlaNET-seq co-purifies splicing intermediates, predominantly 5′SS species. The effect of the splicing inhibitor plaB is shown for the gene At2g39550. (G) Bar chart of the percentage of 5′SS intermediates found in the plaNET-seq DMSO and plaB replicates. (H) Metagene analysis of nascent RNAPII transcription over the 3′-half of internal exons as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (I) Metagene analysis of nascent RNAPII transcription over the 3′-half of internal exons as determined by pNET-seq. Data from the Ser5P antibody is shown in black, Ser2P in red, Unphosphorylated in purple and Total RNAPII in blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (J) Metagene analysis of nascent RNAPII transcription over the 3′-half of internal exons as determined by plaNET-seq. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (K) An example of exonic stalling for intron 2 of the gene At1g01320. Exonic stalling is increased after 3 h at 4°C compared to 22°C.

The effect of splicing and intragenic RNAPII stalling. (A) Illustration of the RNAPII–spliceosome complex during active transcription. The spliceosome protects the 5′SS and the splicing intermediates are co-purified with transcriptionally engaged RNAPII complex in NET-seq. (B) Bar chart of the percentage of 5′SS intermediates found in the control and low temperature exposed replicates of plaNET-seq. (C) The effect of chilling temperature on 5′SS species for the gene At3g11070. (D) Histogram showing the ratio between plaNET-seq reads mapping to all exons and all introns in the replicates of low temperature treatment. (E) RT-qPCR validation of the plaB treatment efficiency (shown for a splicing event of the At2g39550 mRNA). Bars represent mean ± SEM of three biological replicates (circles). The statistical significance of differences was calculated by two-sided t-test. *P < 0.05, **P < 0.01. (F) PlaNET-seq co-purifies splicing intermediates, predominantly 5′SS species. The effect of the splicing inhibitor plaB is shown for the gene At2g39550. (G) Bar chart of the percentage of 5′SS intermediates found in the plaNET-seq DMSO and plaB replicates. (H) Metagene analysis of nascent RNAPII transcription over the 3′-half of internal exons as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (I) Metagene analysis of nascent RNAPII transcription over the 3′-half of internal exons as determined by pNET-seq. Data from the Ser5P antibody is shown in black, Ser2P in red, Unphosphorylated in purple and Total RNAPII in blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (J) Metagene analysis of nascent RNAPII transcription over the 3′-half of internal exons as determined by plaNET-seq. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (K) An example of exonic stalling for intron 2 of the gene At1g01320. Exonic stalling is increased after 3 h at 4°C compared to 22°C.

The hypothesis that splicing kinetics may be transiently affected by low temperature prompted us to examine the connection between splicing and RNAPII transcription more closely. We applied the splicing inhibitors pladienolide B (plaB) and herboxidiene and confirmed their effect on sensitive splicing events ( 44, 45) with RT-qPCR (Figure 5E, Supplementary Figure S6A ). Next, we treated seedlings with DMSO or plaB for 6 hours and generated plaNET-seq libraries. We detected a large genome-wide decrease in 5′SS reads in our plaB samples compared to the DMSO samples, confirming a successful inhibition of the splicing reaction (Figure 5F and G, Supplementary Figure S6B ). Our analysis identified small nuclear RNAs involved in splicing, confirming co-purification of the spliceosome with RNAPII complexes ( Supplementary Figure S6C ), consistent with earlier reports ( 15, 21). Metagene profiles of internal exons revealed increased nascent RNAPII transcription upstream of the 5′SS in DMSO compared to plaB, supporting splicing-dependent RNAPII stalling before the end of exons (Figure 5H, dashed box). This exonic RNAPII stalling was visible also in the re-analyzed pNET-Seq data ( 14), however only in the serine-5 phosphorylation (Ser5P) track which corresponds to NRPB1 phosphorylated at Ser5 position of its C-terminal domain (Figure 5I). In our cold-treated samples, we detected an increased peak at the end of exons after 3 h 4°C compared to 22°C (Figure 5J and K, dashed box). The increased height of the peak was transient and reverted to baseline levels after 12 h at 4°C. In conclusion, our analyses support a splicing-dependent dynamic increase of nascent RNAPII transcription at the end of exons during low temperature. These data may indicate that the kinetics of the splicing reaction is transiently reduced in the chilling response.

Identification of a novel intragenic RNAPII stalling site

In introns, plaNET-seq metagene profiles of our plaB and DMSO samples revealed a peak of nascent RNAPII transcription close to the 5′SS (Figure 6A). Moreover, this intronic peak is most clearly visible in the Ser5P track of pNET-seq data ( Supplementary Figure S7A ). We called the peak coordinates in each intron using sliding window approach on Ser5p pNET-seq data. Next, we calculated an ‘Intronic stalling index’ (ISI) for each intron. Finally, we divided the introns based on ISI into those with strong, medium or weak stalling (for more details, see Methods). ISI for expressed introns can be found in Supplementary Table S4 . The intronic peak was most frequently observed at 25 nt downstream of the 5′SS, irrespective of the ISI level (Figure 6B). An example of the intronic peak can be seen for intron 2 of At1g59870 (Figure 6C). Grouping introns by ISI revealed that introns with higher ISI scores were on average longer than low ISI-score introns ( Supplementary Figure S7B ). This insight made us return to genes with a convergent antisense transcript (CAS), which show a longer first intron compared to control genes. Indeed, CAS host genes showed a significantly higher ISI compared to control genes ( Supplementary Figure S7C ). Thus, there was a correlation between the presence of a CAS and sense RNAPII stalling in the long first intron found in CAS host genes. Next, we stratified introns according to their length to explore other potential effects of the intronic peak. We detected no evidence for increased nucleosome signal in short introns (60–250 bp n = 97 558), Supplementary Figure S7D ). However, we detected peaks of nucleosome density in longer introns (250–1000 bp, n = 15 991), suggesting that these included one or several phased nucleosomes ( Supplementary Figure S7D ). We next plotted nascent RNAPII transcription over long introns compared to a control set of short introns (obtained from the same genes to avoid any effect of gene expression level). We detected a higher plaNET-seq signal over longer introns, suggesting that long introns were transcribed more slowly compared to short introns ( Supplementary Figure S7E ). Thus, nucleosome barriers may contribute to a reduced transcription speed and increased plaNET-seq signal of longer introns. Interestingly, the intronic peak in short introns was largely plaB insensitive (Figure 6D), whereas stalling in long introns was sensitive to plaB (Figure 6E). Similarly, our cold-treated samples showed small effects of the intron peak for short introns (Figure 6F) but a large increase of nascent RNAPII transcription after 3 h at 4°C that reverted back to control levels after 12 h at 4°C in long introns (Figure 6G). This observation further supported a transient decrease in kinetics of the splicing reaction after low temperature exposure. All in all, our plaB and cold-treated samples provide key information to distinguish plaNET-seq signal that is dependent on the splicing reaction from peaks of RNAPII activity independent of splicing. Our data support a RNAPII stalling site 25 nt into plant introns. The sensitivity of this peak to plaB and to low temperature correlates with intron length, perhaps indicating RNAPII-stalling associated checkpoint to improve splicing accuracy of long introns. The intronic peak of RNAPII activity represents a novel site of RNAPII stalling during gene transcription that represents the third stalling site in addition to the positions at gene boundaries.

Identification of a novel RNAPII stalling site in introns. (A) Metagene analysis of nascent RNAPII transcription in all introns as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (B) Distribution of the absolute distances between the intronic peak and the 5′SS. Only introns with FPKM-normalized plaNET-seq coverage above 10 are shown. Introns with strong intronic stalling index (ISI ≥ 5.5) are shown in red, medium (3.5 < ISI < 5.5) in black and weak (ISI ≤ 3.5) in blue. (C) An example of the intronic peak shown for intron 2 in the gene At1g59870. (D) Metagene analysis of nascent RNAPII transcription in short introns as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (E) Metagene analysis of nascent RNAPII transcription in long introns as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (F) Metagene analysis of nascent RNAPII transcription in short introns as determined by plaNET-seq. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (G) Metagene analysis of nascent RNAPII transcription in long introns as determined by plaNET-seq. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean.

Identification of a novel RNAPII stalling site in introns. (A) Metagene analysis of nascent RNAPII transcription in all introns as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (B) Distribution of the absolute distances between the intronic peak and the 5′SS. Only introns with FPKM-normalized plaNET-seq coverage above 10 are shown. Introns with strong intronic stalling index (ISI ≥ 5.5) are shown in red, medium (3.5 < ISI < 5.5) in black and weak (ISI ≤ 3.5) in blue. (C) An example of the intronic peak shown for intron 2 in the gene At1g59870. (D) Metagene analysis of nascent RNAPII transcription in short introns as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (E) Metagene analysis of nascent RNAPII transcription in long introns as determined by plaNET-seq. DMSO is shown in blue and plaB in red. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (F) Metagene analysis of nascent RNAPII transcription in short introns as determined by plaNET-seq. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean. (G) Metagene analysis of nascent RNAPII transcription in long introns as determined by plaNET-seq. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. Dashed box indicates stalling site at the 3′-end of exons. The shaded area shows 95% confidence interval for the mean.

Low temperature affects promoter-proximal RNAPII stalling

To further investigate RNAPII stalling at gene boundaries, we first focused on the beginning of transcription units (i.e. promoter–proximal stalling). plaNET-seq detected a large fraction of reads at 5′-ends of genes, consistent with previous studies in plants and metazoans ( 5, 14) ( Supplementary Figure S1C ). However, we found no clear association between the annotated TSS position and the maximal density of nascent RNA signal on the sense strand ( Supplementary Figure S8A and B ). To test if other genomic features could offer a better association we used nucleosome positioning data (MNase-seq). Metagene plots anchored at the center of the first nucleosome revealed a strong association with peaks of nascent RNAPII transcription (Figure 7A, Supplementary Figure S8C ), suggesting a nucleosome defined promoter proximal stalling mechanism in Arabidopsis. We found that 16.6% of the expressed genes (FPKM ≥ 1) showed RNAPII stalling in the promoter proximal region (Promoter-proximal Stalling Index ≥ 3, Supplementary Table S5 ). Metagene profiles for 0, 3 and 12 h at 4°C indicated that low temperature affected RNAPII stalling at the first (i.e. +1) nucleosome (Figure 7A). 3 h at 4°C resulted in an increased peak around the center of the +1 nucleosome, indicating greater promoter-proximal stalling. In contrast, the 12 h 4°C samples resulted in decreased stalling. These results prompted us to investigate if pools of RNAPII engaged in promoter-proximal stalling may facilitate temperature-dependent gene regulation. We calculated a ‘Promoter–proximal stalling index’ from plaNET-seq data (i.e. relative nascent RNAPII transcription at the promoter proximal region versus the gene body) as previously described ( 14). Transcripts that were up-regulated after 3 h at 4°C showed a significantly increased stalling index before low temperature treatment (22°C). In addition, transcripts that were down-regulated after 3 h at 4°C exhibited significantly decreased promoter proximal stalling compared to non-regulated transcripts (Figure 7B). These results support a role for RNAPII promoter-proximal stalling to adjust transcription to low temperature. In conclusion, plaNET-seq revealed a nucleosome defined promoter–proximal RNAPII stalling mechanism that may facilitate reprogramming of gene expression in response to temperature changes.

Low temperature affects RNAPII stalling at gene boundaries. (A) Metagene analysis of the plaNET-seq signal in a 1 kb window anchored at the center of +1 nucleosome. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. The shaded area shows 95% confidence interval for the mean. (B) Box plot of promoter–proximal stalling index in control conditions (22°C) of genes which are differentially transcribed at 3 h 4°C. Black denotes transcripts with unchanged expression, red denotes upregulated transcripts and blue denotes downregulated transcripts. Statistical differences were assessed by two-sided Mann–Whitney U test. (C) Metagene analysis of the plaNET-seq signal in a 1 kb window anchored at the PAS. 22°C is shown in black, 3 h 4°C is shown in blue, 12 h 4°C is shown in light blue. The shaded area shows 95% confidence interval for the mean. (D) Upper panel illustrates the definition of read-through distance while lower panel shows a box plot of the read-through distance (bp) in 22°C (black), 3 h 4°C (blue) and 12 h 4°C (light blue) samples. Statistical differences were assessed by two-sided Mann–Whitney U test.

Low temperature affects RNAPII stalling at gene boundaries. (A) Metagene analysis of the plaNET-seq signal in a 1 kb window anchored at the center of +1 nucleosome. 22°C (control sample) is shown in black, 3 h 4°C in blue, 12 h 4°C in light blue. The shaded area shows 95% confidence interval for the mean. (B) Box plot of promoter–proximal stalling index in control conditions (22°C) of genes which are differentially transcribed at 3 h 4°C. Black denotes transcripts with unchanged expression, red denotes upregulated transcripts and blue denotes downregulated transcripts. Statistical differences were assessed by two-sided Mann–Whitney U test. (C) Metagene analysis of the plaNET-seq signal in a 1 kb window anchored at the PAS. 22°C is shown in black, 3 h 4°C is shown in blue, 12 h 4°C is shown in light blue. The shaded area shows 95% confidence interval for the mean. (D) Upper panel illustrates the definition of read-through distance while lower panel shows a box plot of the read-through distance (bp) in 22°C (black), 3 h 4°C (blue) and 12 h 4°C (light blue) samples. Statistical differences were assessed by two-sided Mann–Whitney U test.

Low temperature transiently reduces 3′-end associated RNAPII stalling and read-through transcription

In addition to promoter-proximal positions, RNAPII stalls near 3′-ends of Arabidopsis genes ( 14, 38, 46). We detected increased nascent RNAPII transcription downstream of the poly(A) sites (PAS) (Figure 7C). We plotted the mean plaNET-seq signal anchored on PAS sites to examine the effect of low temperature on PAS-associated RNAPII stalling. As expected, samples taken before the treatment (22°C) and after 12 h at 4°C showed that RNAPII stalled downstream of the PAS (Figure 7C). Surprisingly, the peak of RNAPII stalled downstream of the PAS was abolished after 3 h at 4°C, suggesting a major change in transcription dynamics associated with termination (Figure 7C). RNAPII complexes transcribe beyond the PAS, representing the zone of transcription termination (Figure 7D, upper panel). At control conditions (22°C), we detected a median read-through distance of 497 bp (Figure 7D). This distance was significantly decreased at 3 h 4°C (median 462 bp, Figure 7D). However, at 12 h 4°C, we detected a slightly increased read-through distance (median 524 bp, Figure 7D). Thus, genome-wide distribution of RNAPII such as PAS-associated stalling and read-through distance were transiently altered by low temperature.


Metabolic opportunists: feeding and temperature influence the rate and pattern of respiration in the high arctic woollybear caterpillar gynaephora groenlandica (Lymantriidae)

V.A. Bennett, O. Kukal, R.E. Lee Metabolic opportunists: feeding and temperature influence the rate and pattern of respiration in the high arctic woollybear caterpillar gynaephora groenlandica (Lymantriidae). J Exp Biol 1 January 1999 202 (1): 47–53. doi: https://doi.org/10.1242/jeb.202.1.47

Arctic woollybear caterpillars, Gynaephora groenlandica, had the capacity to rapidly and dramatically increase respiration rates up to fourfold within 12–24 h of feeding and exhibited similar decreases in respiration of 60–85 % in as little as 12 h of starvation. At the peak of their feeding season, the respiration rates of caterpillars also increased significantly with temperature from 0.5 to 22 degreesC for both fed and starved caterpillars (Q10=1-5). Indicative of diapause, late season caterpillars had depressed respiration rates which were less sensitive to temperature changes (Q10 approximately 1.5), while respiration rates for caterpillars that had spun hibernacula were even lower. G. groenlandica did not appear to demonstrate metabolic cold adaptation compared with other temperate lepidopteran larvae. The seasonal capacity to adjust metabolic rate rapidly in response to food consumption and temperature (which can be elevated by basking) may promote the efficient acquisition of energy during the brief (1 month) summer growing and feeding season, while conserving energy by entering diapause when conditions are less favorable. These adaptations, along with their long 15–20 year life cycle and the retention of freeze tolerance year-round, promote the survival of G. groenlandica in this harsh polar environment.


OVER-EXPRESSION OF TRANSCRIPTION FACTORS CONFERS ABIOTIC STRESS TOLERANCE AND PHOTOSYNTHESIS IMPROVEMENT

Tolerance of plants to abiotic stresses is well known to be a multigenic trait. For that reason, plant improvement using genes that play a role in the abiotic stress response is frequently insufficient to improve stress tolerance significantly. To overcome this, TFs that regulate several stress-responsive genes (e.g. the AP2/EREBP family) have often been used to manipulate plants in order to have a broader response. The results obtained in terms of stress tolerance are often much better than using a single gene encoding a non-regulatory protein and the observed effects on photosynthesis efficiency or photosynthetic machinery are normally positive. Table 1 shows a list of TFs transformed into various plants and conferring stress tolerance improvement associated with improved photosynthetic parameters. The interpretation of these results must, however, be cautious, as only a few parameters are evaluated and sometimes the methods are poor. In addition, abiotic stress tolerance has mostly been evaluated in laboratory conditions and little is known concerning the plant responses to adverse conditions in the field.

Abiotic stress-related transcription factors constitutively expressed in different plants confer stress tolerance and improve photosynthesis

Over-expressed TF . TF family . Transgenic plant . Stress tolerance . Effect on photosynthesis under stress conditions . Reference .
NtTsi1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Park et al. (2001)
AtCBF1 AP2/EREBP Tomato Chilling Improved maximum quantum efficiency of PSII/chlorophyll accumulation Hsieh et al. (2002b)
AtCBF1 AP2/EREBP Rice No cold tolerance No effect on maximum quantum efficiency of PSII Lee et al. (2004)
SHN AP2/EREBP ArabidopsisDrought tolerance and recovery Reduced stomatal density (probable reduced transpiration) Aharoni et al. (2004)
BNCBF5 and BNCBF17 AP2/EREBP Brassica napusFreezing Increased CO2 assimilation/increased photochemical efficiency Savitch et al. (2005)
AtCBF3 AP2/EREBP Rice Drought/high salt/low temperature Improved maximum quantum efficiency of PSII Oh et al. (2005)
CaPF1 AP2/EREBP Pine Oxidative stress Lower loss of chlorophyll contents Tang et al. (2006)
TaERF1 AP2/EREBP Tobacco High salt Higher chlorophyll content Xu et al. (2007)
JcERF AP2/EREBP ArabidopsisHigh salt/freezing Higher chlorophyll content Tang et al. (2007)
HvCBF4 AP2/EREBP Rice Drought/high salt/ low temperature Improved maximum quantum efficiency of PSII Oh et al. (2007)
NtOPBP1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Guo et al. (2004)
AtHRD AP2/EREBP Rice Drought/highsalt Lower stomatal conductance/enhanced photosynthesis assimilation and efficiency Karaba et al. (2007)
GhDREB1 AP2/EREBP Tobacco Low temperature Higher chlorophyll fluorescence/higher net photosynthetic rate Shan et al. (2007)
AtABP9 bZIP ArabidopsisDrought/heat shock Improved photosynthetic capacity Zhang et al. (2008)
SNAC1 NAC Rice Drought/high salt Loses water more slowly by closing more stomatal pores/no effect on photosynthesis rate Hu et al. (2006)
AtNFXL1 NF-X1 ArabidopsisSalt stress Improved maximum quantum efficiency of PSII Lisso et al. (2006)
AtNF-YB1 NF-Y (HAP) ArabidopsisDrought Higher water potential and photosynthesis rates than controls Nelson et al. (2007)
ZmNF-YB2 NF-Y (HAP) Maize Drought Higher chlorophyll index, higher photosynthesis rate and higher stomatal conductance Nelson et al. (2007)
GmSCOF-1 C2H2 zinc finger Tobacco Cold Faster recovery of chlorophyll content Kim et al. (2001)
OsMYB4 MYB ArabidopsisCold/freezing Improved PSII stability. Tolerance to photoinhibition Vannini et al. (2004)
Over-expressed TF . TF family . Transgenic plant . Stress tolerance . Effect on photosynthesis under stress conditions . Reference .
NtTsi1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Park et al. (2001)
AtCBF1 AP2/EREBP Tomato Chilling Improved maximum quantum efficiency of PSII/chlorophyll accumulation Hsieh et al. (2002b)
AtCBF1 AP2/EREBP Rice No cold tolerance No effect on maximum quantum efficiency of PSII Lee et al. (2004)
SHN AP2/EREBP ArabidopsisDrought tolerance and recovery Reduced stomatal density (probable reduced transpiration) Aharoni et al. (2004)
BNCBF5 and BNCBF17 AP2/EREBP Brassica napusFreezing Increased CO2 assimilation/increased photochemical efficiency Savitch et al. (2005)
AtCBF3 AP2/EREBP Rice Drought/high salt/low temperature Improved maximum quantum efficiency of PSII Oh et al. (2005)
CaPF1 AP2/EREBP Pine Oxidative stress Lower loss of chlorophyll contents Tang et al. (2006)
TaERF1 AP2/EREBP Tobacco High salt Higher chlorophyll content Xu et al. (2007)
JcERF AP2/EREBP ArabidopsisHigh salt/freezing Higher chlorophyll content Tang et al. (2007)
HvCBF4 AP2/EREBP Rice Drought/high salt/ low temperature Improved maximum quantum efficiency of PSII Oh et al. (2007)
NtOPBP1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Guo et al. (2004)
AtHRD AP2/EREBP Rice Drought/highsalt Lower stomatal conductance/enhanced photosynthesis assimilation and efficiency Karaba et al. (2007)
GhDREB1 AP2/EREBP Tobacco Low temperature Higher chlorophyll fluorescence/higher net photosynthetic rate Shan et al. (2007)
AtABP9 bZIP ArabidopsisDrought/heat shock Improved photosynthetic capacity Zhang et al. (2008)
SNAC1 NAC Rice Drought/high salt Loses water more slowly by closing more stomatal pores/no effect on photosynthesis rate Hu et al. (2006)
AtNFXL1 NF-X1 ArabidopsisSalt stress Improved maximum quantum efficiency of PSII Lisso et al. (2006)
AtNF-YB1 NF-Y (HAP) ArabidopsisDrought Higher water potential and photosynthesis rates than controls Nelson et al. (2007)
ZmNF-YB2 NF-Y (HAP) Maize Drought Higher chlorophyll index, higher photosynthesis rate and higher stomatal conductance Nelson et al. (2007)
GmSCOF-1 C2H2 zinc finger Tobacco Cold Faster recovery of chlorophyll content Kim et al. (2001)
OsMYB4 MYB ArabidopsisCold/freezing Improved PSII stability. Tolerance to photoinhibition Vannini et al. (2004)

Abiotic stress-related transcription factors constitutively expressed in different plants confer stress tolerance and improve photosynthesis

Over-expressed TF . TF family . Transgenic plant . Stress tolerance . Effect on photosynthesis under stress conditions . Reference .
NtTsi1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Park et al. (2001)
AtCBF1 AP2/EREBP Tomato Chilling Improved maximum quantum efficiency of PSII/chlorophyll accumulation Hsieh et al. (2002b)
AtCBF1 AP2/EREBP Rice No cold tolerance No effect on maximum quantum efficiency of PSII Lee et al. (2004)
SHN AP2/EREBP ArabidopsisDrought tolerance and recovery Reduced stomatal density (probable reduced transpiration) Aharoni et al. (2004)
BNCBF5 and BNCBF17 AP2/EREBP Brassica napusFreezing Increased CO2 assimilation/increased photochemical efficiency Savitch et al. (2005)
AtCBF3 AP2/EREBP Rice Drought/high salt/low temperature Improved maximum quantum efficiency of PSII Oh et al. (2005)
CaPF1 AP2/EREBP Pine Oxidative stress Lower loss of chlorophyll contents Tang et al. (2006)
TaERF1 AP2/EREBP Tobacco High salt Higher chlorophyll content Xu et al. (2007)
JcERF AP2/EREBP ArabidopsisHigh salt/freezing Higher chlorophyll content Tang et al. (2007)
HvCBF4 AP2/EREBP Rice Drought/high salt/ low temperature Improved maximum quantum efficiency of PSII Oh et al. (2007)
NtOPBP1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Guo et al. (2004)
AtHRD AP2/EREBP Rice Drought/highsalt Lower stomatal conductance/enhanced photosynthesis assimilation and efficiency Karaba et al. (2007)
GhDREB1 AP2/EREBP Tobacco Low temperature Higher chlorophyll fluorescence/higher net photosynthetic rate Shan et al. (2007)
AtABP9 bZIP ArabidopsisDrought/heat shock Improved photosynthetic capacity Zhang et al. (2008)
SNAC1 NAC Rice Drought/high salt Loses water more slowly by closing more stomatal pores/no effect on photosynthesis rate Hu et al. (2006)
AtNFXL1 NF-X1 ArabidopsisSalt stress Improved maximum quantum efficiency of PSII Lisso et al. (2006)
AtNF-YB1 NF-Y (HAP) ArabidopsisDrought Higher water potential and photosynthesis rates than controls Nelson et al. (2007)
ZmNF-YB2 NF-Y (HAP) Maize Drought Higher chlorophyll index, higher photosynthesis rate and higher stomatal conductance Nelson et al. (2007)
GmSCOF-1 C2H2 zinc finger Tobacco Cold Faster recovery of chlorophyll content Kim et al. (2001)
OsMYB4 MYB ArabidopsisCold/freezing Improved PSII stability. Tolerance to photoinhibition Vannini et al. (2004)
Over-expressed TF . TF family . Transgenic plant . Stress tolerance . Effect on photosynthesis under stress conditions . Reference .
NtTsi1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Park et al. (2001)
AtCBF1 AP2/EREBP Tomato Chilling Improved maximum quantum efficiency of PSII/chlorophyll accumulation Hsieh et al. (2002b)
AtCBF1 AP2/EREBP Rice No cold tolerance No effect on maximum quantum efficiency of PSII Lee et al. (2004)
SHN AP2/EREBP ArabidopsisDrought tolerance and recovery Reduced stomatal density (probable reduced transpiration) Aharoni et al. (2004)
BNCBF5 and BNCBF17 AP2/EREBP Brassica napusFreezing Increased CO2 assimilation/increased photochemical efficiency Savitch et al. (2005)
AtCBF3 AP2/EREBP Rice Drought/high salt/low temperature Improved maximum quantum efficiency of PSII Oh et al. (2005)
CaPF1 AP2/EREBP Pine Oxidative stress Lower loss of chlorophyll contents Tang et al. (2006)
TaERF1 AP2/EREBP Tobacco High salt Higher chlorophyll content Xu et al. (2007)
JcERF AP2/EREBP ArabidopsisHigh salt/freezing Higher chlorophyll content Tang et al. (2007)
HvCBF4 AP2/EREBP Rice Drought/high salt/ low temperature Improved maximum quantum efficiency of PSII Oh et al. (2007)
NtOPBP1 AP2/EREBP Tobacco High salt Lower loss of chlorophyll contents Guo et al. (2004)
AtHRD AP2/EREBP Rice Drought/highsalt Lower stomatal conductance/enhanced photosynthesis assimilation and efficiency Karaba et al. (2007)
GhDREB1 AP2/EREBP Tobacco Low temperature Higher chlorophyll fluorescence/higher net photosynthetic rate Shan et al. (2007)
AtABP9 bZIP ArabidopsisDrought/heat shock Improved photosynthetic capacity Zhang et al. (2008)
SNAC1 NAC Rice Drought/high salt Loses water more slowly by closing more stomatal pores/no effect on photosynthesis rate Hu et al. (2006)
AtNFXL1 NF-X1 ArabidopsisSalt stress Improved maximum quantum efficiency of PSII Lisso et al. (2006)
AtNF-YB1 NF-Y (HAP) ArabidopsisDrought Higher water potential and photosynthesis rates than controls Nelson et al. (2007)
ZmNF-YB2 NF-Y (HAP) Maize Drought Higher chlorophyll index, higher photosynthesis rate and higher stomatal conductance Nelson et al. (2007)
GmSCOF-1 C2H2 zinc finger Tobacco Cold Faster recovery of chlorophyll content Kim et al. (2001)
OsMYB4 MYB ArabidopsisCold/freezing Improved PSII stability. Tolerance to photoinhibition Vannini et al. (2004)

Picocalorimetry of Transcription by RNA Polymerase

Thermal variations can exert dramatic effects on the rates of enzymes. The influence of temperature on RNA polymerase is of particular interest because its transcriptional activity governs general levels of gene expression, and may therefore exhibit pleiotropic effects in cells. Using a custom-modified optical trapping apparatus, we used a tightly focused infrared laser to heat single molecules of Escherichia coli RNA polymerase while monitoring transcriptional activity. We found a significant change in rates of transcript elongation with temperature, consistent with a large enthalpic barrier to the condensation reaction associated with RNA polymerization (∼13 kcal/mol). In contrast, we found little change in either the frequency or the lifetime of off-pathway, paused states, indicating that the energetic barrier to transcriptional pausing is predominantly entropic.

Joshua W. Shaevitz’s present address is Dept. of Integrative Biology, University of California, Berkeley, CA 94720.


Aspect 3: Developing a method for collection of data

Materials:

  • Mauna Loa Supreme leaves with same size and mass.
  • Vernier Oxygen Sensor
  • Thermometer
  • Glass erlenmayer flask
  • Graduated cylinder of 100ml(±0,5ml )
  • Kettle
  • Laptop
  • Cutter
  • Balance
  • refrigerator

Method

  1. Cut 6 leaves of same size and mass from Mauna Loa Supreme. Measure their mass by using Balance.
  2. Put each leaf in an erlenmayer flask.

For the sample temperature of 10 0 C,

  • Place the vernier oxygen sensor on one of the erlenmayer flasks and cover the gabs between the vernier oxygen sensor and the flask with parafilm to prevent the loss of oxygen gas.
  • Connect the vernier oxygen sensor to your laptop and get the Logger Pro software ready on your laptop.
  • Measure 100ml of tap water with graduated cylinder. Measure its temperature. Its temperature will be more than 10 0 C so cool it down by using a refrigerator.
  • As you measure the temperature of water as 10 0 C immediately poor it into the water bath.
  • Place the erlenmayer flash with the leaf in it and the oxygen probe placed on it in the water bath.
  • Start the Logger Pro software to start collecting your data.
  • Repeat the same steps for the other 4 samples.
  • Be careful with that if you need to heat the tap water to get the expected temperature for the sample, don’t heat water after measuring the amount of water because water evaporates as you heat it up and some water leaves the kettle as a gas. Before measuring the amount of water, heat plenty of water and after heating measure its temperature.
  • After heating, if its temperature is higher than the expected value measure 100ml of water with a graduated cylinder and let it cool down in the graduated cylinder. While it is cooling down, place the thermometer in water and as soon as you get the expected value, pour the 100ml(±0,5ml ) of water in the water bath.
  • After heating, if the temperature of water is lower than the expected value, heat it more and repeat the steps in 10-b.

After collecting data with at least doing 3 trials for each sample, to get more accurate results, by using Microsoft Office Excel, the average values of the trials for each sample should be calculated. After calculating, percentage uncertanities should be found and the graph of concentration of oxygen gas vs. temperature should be drawn. While drawing the graph, error bars should be added to the graph. After all, a conclusion ought to be come and some alternative solutions for the weak points of the method should be found, to increase the accuracy of the data.

After finishing the experiment, while cleaning up the laboratory, the leaves used in the experiment should not be put into rubbish bin, being avare of that they are still alive.


Watch the video: Transcription and mRNA processing. Biomolecules. MCAT. Khan Academy (September 2022).


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