Find research datasets worth reusing

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.

FOXO transcription factors are required for normal somatotrope function and growth

Supplemental Fig 1. Prop1 and Sst expression is unchanged in dKO mice. Whole pituitary glands were collected from WT and dKO mice at 6 weeks of age. RNA was isolated and cDNA generated in order to evaluate mRNA abundance for Prop1 in females and males. Hypothalamus was collected to evaluate expression of Sst. Expression was normalized to Tfrc. The data represent 7-8 animals for each genotype and sex and were analyzed using Student’s t test. Supplemental Fig 2. Gonadotrope, thyrotrope and corticotrope cells appear normally distributed in dKO mice. Immunohistochemistry for LHB, TSHB, and ACTH was performed on pituitary gland tissue from female and male mice to determine the distribution of gonadotropes, thyrotropes, and corticotropes, respectively. No obvious difference was observed between dKO mice and WT controls. Scale bars represent 100 mm. Representative images of three animals per genotype and sex are shown. Supplemental Fig 3. Lactotrope cells appear normally distributed in dKO mice. Immunohistochemistry for PRL was performed on pituitary gland tissue from female and male mice to determine the distribution of lactotropes. No apparent difference in lactotrope distribution was observed between dKO mice and WT controls. Scale bars represent 100 mm. Representative images of three animals per genotype and sex are shown. Supplemental Fig 4. Foxo1 and Foxo3 expression levels in liver and hypothalamus of dKO mice. Liver and hypothalamus were collected from WT and dKO mice at 6 weeks of age. RNA was isolated and cDNA generated in order to evaluate mRNA abundance for Foxo1 and Foxo3 in females and males. Expression was normalized to Tfrc. The data represent 5-8 animals for each genotype and sex and were analyzed using Student’s t test (*p<0.05, **p<0.01, ***p<0.001).   Materials and Methods Animals and genotyping             To obtain Foxo1Δpit mice Foxo1+/- mice (15) were mated to Foxg1+/cre mice (10) to produce Foxo1+/-;Foxg1+/cre mice. These were then mated to Foxo1fl/fl mice (13) to obtain Foxo1fl/-;Foxg1+/cre (Foxo1Δpit) mice. Experimental Foxo1fl/fl;Foxo3fl/fl;Foxg1+/cre (dKO) animals were generated by crossing Foxo1fl/fl;Foxo3fl/fl females with Foxo1+/fl;Foxo3fl/fl;Foxg1+/cre males. Foxg1+/cre mice were purchased from Jackson Laboratories, Bar Harbor, ME, USA (stock no. 004337) and were maintained on a 129SvJ (stock no. 000691) background (10,11). Foxo1fl/fl mice (Jackson Laboratories, stock no. 024756) which have loxP sites flanking exon two of the Foxo1 gene (15) were a generous gift from Drs. Accili and Pajvani, with permission from Dr. DePinho. Foxo1+/- mice (15) were provided by Drs. Accili and Pajvani. Foxo3fl/fl mice were purchased from Jackson Laboratories (stock no. 024668) (16). Genotyping was performed using specific primers for Foxo1-null (LacZ fwd and rev), Foxo1-flox (FK1ckA-C), Foxg1-cre (cre fwd and rev), and Foxo3-flox (ofk2ck1-3). A list of primers used can be found in Table S1.             All mice were housed in a 12-hour light/dark cycle with feed (Formulab Diet 5008; Purina Mills, Gray Summit, MO, USA) and water ad libitum. Animals were weighed once per week starting at postnatal day seven. Mice were euthanized using CO2 inhalation. Mouse length was measured post-euthanization by measuring from nose to rump. All procedures were conducted in accordance with the principles and procedures outlined in the National Institutes of Health Guidelines for the Care and Use of Experimental Animals and in accordance with Southern Illinois University Carbondale policies. Immunohistochemistry             Pituitary gland tissue was collected post-euthanization and fixed in 10% formalin in PBS then dehydrated in graded ethanol solutions (50% then 80%). Tissue was then embedded in paraffin blocks and cut into 5 μm sections and mounted on positively charged slides. All immunohistochemistry (IHC) was begun by deparaffinization and rehydration of tissue sections using xylene (twice for 5 minutes each), 100% ethanol (twice for 3 minutes each), 95% ethanol (twice for 3 minutes each), then PBS. For immunofluorescent detection where antibody signal was amplified (Supplemental Table S2), slides were then incubated in 1.5% H2O2 for 20 minutes. All tissue sections were blocked for 60 minutes using the Tyramide Signal Amplification (TSA) Kit Blocking Solution (TSB; Perkin Elmer, Waltham, MA, USA), which was also used as the diluent for all antibody solutions. Primary antibodies were incubated overnight at 4°C but all other steps were performed at room temperature (RT). After primary antibody incubation, tissue sections were washed three times for 3 minutes each in PBS-TWEEN 20 (PBS-T, 0.05%). Fluorophore-conjugated secondary antibody was then incubated on tissue sections for 60 minutes. Nuclei were stained using 4’,6’-diamidino-2-phenylindole (DAPI). Sections were then mounted using immunofluorescent mount (0.5 mM polyvinyl alcohol, 0.12 M Tris pH 8.0, 0.3% w/v glycerol, 2.5% w/v 1,4-diazabicyclo[2.2.2]octane) and glass coverslips.             Imaging was performed using a Retiga 2000R digital camera attached to a Leica DM 5000B fluorescent microscope (Leica Biosystems, St. Louis, MO, USA). Individual captures of FITC and DAPI channels were merged using Adobe Photoshop CS3. Some images were brightened for illustrative purposes; however, the exact alterations were duplicated in both control and experimental images to maintain the ability to compare results. Three animals per genotype were analyzed for these studies. <table> <tbody> <tr> <td> Name </td> <td> ID </td> <td> Antigen </td> <td> Citation </td> <td> Host </td> <td> Company </td> <td> Cat. No. </td> <td> Dilution </td> </tr> </tbody> </table> <table> <tbody> <tr> <td> Rabbit anti-mouse PRL antibody </td> <td> <a href="http://antibodyregistry.org/AB_2721133">AB_2721133</a> </td> <td> mouse PRL </td> <td> (A.F. Parlow National Hormone and Peptide Program Cat# AFP107120402, RRID:AB_2721133) </td> <td> rabbit </td> <td> A.F. Parlow National Hormone and Peptide Program </td> <td> AFP10712402 </td> <td> IF 1:10000 </td> </tr> </tbody> </table> <table> <tbody> <tr> <td> Rabbit anti-Rat TSHβ antibody </td> <td> <a href="http://antibodyregistry.org/AB_2665563">AB_2665563</a> </td> <td> rat TSHB </td> <td> (A.F. Parlow National Hormone and Peptide Program Cat# rTSHb, RRID:AB_2665563) </td> <td> rabbit </td> <td> A.F. Parlow National Hormone and Peptide Program </td> <td> rTSHb also AFP-1274789 </td> <td> IF 1:2000 </td> </tr> <tr> <td> ACTH (adrenocorticotropic hormone) antibody </td> <td> <a href="http://antibodyregistry.org/AB_2313902">AB_2313902</a> </td> <td> ACTH </td> <td> (National Hormone & Peptide Program, Torrance, CA Cat# AFP-156102789, RRID:AB_2313902) </td> <td> rabbit </td> <td> A.F. Parlow National Hormone and Peptide Program </td> <td> AFP-156102789 </td> <td> IF 1:500 </td> </tr> </tbody> </table> RTqPCR             Tissue collected for mRNA analysis was stored in RNA Later (AM7021, Invitrogen, Carlsbad, CA, USA) until use. Whole pituitary glands were lysed, and RNA was extracted and purified using the RNAqueous Micro Kit (AM1931) according to the kit protocol. The resultant mRNA was reversed transcribed to cDNA using the Promega M-MLV kit according to included instructions (M5313, Promega, Madison, WI, USA). Ten ng of cDNA were used for mRNA analysis. All samples were run in duplicate and a sample processed with no reverse transcriptase enzyme was included as a negative control. Results were calculated using the ΔΔCt method by first normalizing to RNA-polymerase subunit II b (Polr2b) as an internal control then calculated relative to transferrin receptor (Tfrc) to compare between groups. Both genes are expressed at consistent levels between genotypes. At least five mice per genotype were used in these studies. <table> <tbody> <tr> <td> Name </td> <td> Sequence (5’ to 3’) </td> </tr> </tbody> </table> <table> <tbody> <tr> <td> LacZ fwd </td> <td> TTCACTGGCCGTCGTTTTACAAGCTCGTGA </td> </tr> <tr> <td> LacZ rev </td> <td> ATGTGAGCGAGTAACAACCCGTCGGATTCT </td> </tr> <tr> <td> FK1ckA </td> <td> GCTTAGAGCAGAGATGTTCTCACATT </td> </tr> <tr> <td> FK1ckB </td> <td> CCAGAGTCTTTGTATCAGGCAAATAA </td> </tr> <tr> <td> FK1ckC </td> <td> CAAGTCCATTAATTCAGCACATTGA </td> </tr> <tr> <td> cre fwd </td> <td> GCGGTCTGGCAGTAAAAACTATC </td> </tr> <tr> <td> cre rev </td> <td> GTGAAACAGCATTGCTGTCACTT </td> </tr> <tr> <td> ofk2ck3 </td> <td> CATGCAGTCCGAGAGATTTG </td> </tr> <tr> <td> ofk2ck2 </td> <td> AGTGTCTGATACCGAAGAGC </td> </tr> <tr> <td> ofk2ck1 </td> <td> AACAACCTCACACATGTGCC </td> </tr> <tr> <td> mPolr2b RTqPCR fwd </td> <td> AGATGTATGACGCCGACGAG </td> </tr> <tr> <td> mPolr2b RTqPCR rev </td> <td> GTAAGAACTGATCACGATCCAGCA </td> </tr> <tr> <td> mTfrc RTqPCR fwd </td> <td> GCAAGATGTAAAGCATCCAGTTGATGG </td> </tr> <tr> <td> mTfrc RTqPCR rev </td> <td> GCATATTCTGGAATCCCAGCAG </td> </tr> </tbody> </table> <table> <tbody> <tr> <td> mFoxo1 RTqPCR fwd </td> <td> AGGATAAGGGCGACAGCAAC </td> </tr> <tr> <td> mFoxo1 RTqPCR rev </td> <td> CCGCTCTTGCCTCCCTC </td> </tr> <tr> <td> mFoxo3 RTqPCR fwd </td> <td> GGGCGACAGCAACAGCT </td> </tr> <tr> <td> mFoxo3 RTqPCR rev </td> <td> CCCGCTCTTTCCCCCATC </td> </tr> </tbody> </table> <table> <tbody> <tr> <td> mProp1 RTqPCR fwd </td> <td> GCCTCTGGGACTCTGATCTCC </td> </tr> <tr> <td> mProp1 RTqPCR rev </td> <td> CAGGATACTGGTTCCTCCCAA </td> </tr> <tr> <td> mSst RTqPCR fwd </td> <td> TCTGCATCGTCCTGGCTTTG </td> </tr> <tr> <td> mSst RTqPCR rev </td> <td> GACAGCAGCTCTGCCAAGAA </td> </tr> </tbody> </table>   Statistical analysis             All data were analyzed using Student’s t test unless otherwise noted where (*) indicates p < 0.05, (**) indicates p < 0.01, (***) indicates p < 0.001, and (****) indicates p < 0.0001. Error bars indicate standard error of the mean (SEM).

openother-ncDec 2021View details →

Podcast annotation dataset for paper "Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts "

Dataset for paper "Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts". Please refer to the paper for details. Compared to the dataset used in the paper, 20 out of the 417 episodes have been removed due to copyright issues.  The data file contains the following fields: - "episode_intro_start": the time stamp for episode introduction start (in milliseconds) - "episode_intro_end": the time stamp for episode introduction end (in milliseconds) - "program_intro_start": the time stamp for program introduction start (in milliseconds) - "program_intro_end": the time stamp for program introduction end (in milliseconds) - "program_name": name of the podcast program - "episode_name": name of the podcast episode - "transcription": JSON string containing the transcription, including the timestamps. - "annotator": anonymized annotator ID.

HRE 2021-0515 Research Data: Interview Transcripts

The <a href="https://openknowledge.community/about-coki/">Curtin Open Knowledge Initiative</a> (COKI) in collaboration with <a href="https://library.curtin.edu.au/">Curtin University Library</a> undertook a project to provide better support for the creative practice research outputs (CPROs) of Faculty of Humanities researchers. The reason for this research is to identify ways to increase the visibility of CPROs at Curtin University, and document what information (metadata) is important to researchers when describing their CPROs. The Chief Investigator of this project was Dr Lucy Montgomery, Professor of Knowledge Innovation at Curtin University. This research project has approval from the Curtin University Human Research Ethics Office (HRE2021-0515). This dataset contains deidentified interview transcripts from six interviews with creative practice researchers at Curtin University, Perth,  Australia, who consented to sharing their deidentified data as a publicly available dataset. The participants have been deidentified, and named as P1 to P6. Interviews were conducted between 20/09/2021 and 30/09/2021. Four interviews were in person, and two interviews were online via WebEx. The interview guide is publicly available on Zenodo: <a href="https://doi.org/10.5281/zenodo.5774543">https://doi.org/10.5281/zenodo.5774543</a> The metadata findings from the card sorting activity are available on Zenodo: <a href="https://doi.org/10.5281/zenodo.5774660">https://doi.org/10.5281/zenodo.5774660</a>

Data and code from: "A transcriptional rheostat couples past activity to future sensory responses" (Tsukahara, Brann, et al. 2021 Cell)

# A transcriptional rheostat couples past activity to future sensory responses Code and data to replicate analyses in Tsukahara, Brann et al. 2021 Cell <a href="https://doi.org/10.1016/j.cell.2021.11.022">https://doi.org/10.1016/j.cell.2021.11.022</a> ## Summary Animals traversing different environments encounter both stable background stimuli and novel cues, which are thought to be detected by primary sensory neurons and then distinguished by downstream brain circuits. Here we show that each of the ~1000 olfactory sensory neuron (OSN) subtypes in the mouse harbors a distinct transcriptome whose content is precisely determined by interactions between its odorant receptor and the environment. This transcriptional variation is systematically organized to support sensory adaptation: expression levels of more than 70 genes relevant to transforming odors into spikes continuously vary across OSN subtypes, dynamically adjust to new environments over hours, and accurately predict acute OSN-specific odor responses. The sensory periphery therefore separates salient signals from predictable background via a transcriptional rheostat whose moment-to-moment state reflects the past and constrains the future; these findings suggest a general model in which structured transcriptional variation within a cell type reflects individual experience. ## Manuscript For more details, please see our Open Access manuscript: <a href="https://www.cell.com/cell/fulltext/S0092-8674(21)01337-4">https://www.cell.com/cell/fulltext/S0092-8674(21)01337-4</a> # Code 1. The code here is a copy of that on GitHub: <a href="https://github.com/dattalab/Tsukahara_Brann_OSN">https://github.com/dattalab/Tsukahara_Brann_OSN</a>. Instructions for how to download and install it can be found in the README.md file. 2. Data is available on the NCBI GEO (accession <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE173947">GSE173947</a>) and raw fastq files are available from the SRA (accession SRP318630). 3. Supplementary data (imaging traces and example preprocessed AnnData object for the home-cage dataset) can be found in the data folders of the attached Tsukahara_Brann_OSN-zenodo.zip file.

opencc-by-4.0Feb 2022View details →

HRE2021-0515-03 Research Data: Focus Group Transcripts

The Centre for Culture and Technology (CCAT) at Curtin University undertook a project aiming to provide better support for grey literature research outputs including reports, working papers and blog posts.  The research team for the project ‘Increasing the Visibility of Grey Literature’ was: <ul> <li>Professor Katie Ellis, Centre for Culture and Technology</li> <li>Niamh Quigley, Research Associate, Centre for Culture and Technology</li> </ul> This dataset contains the deidentified transcripts of two focus groups held with producers of grey literature at Curtin University, Perth, Australia. The participants have been deidentified, and named as P1 to P9. In focus group 1, P1 was an observer. In focus group 2, P8 was both an observer and also participated. The online focus groups were conducted on 27/01/2022 and 01/02/2022. This research project has approval from the Curtin University Human Research Ethics Office (HRE2021-0515-03). The focus group interview guide is available at <a href="https://doi.org/10.5281/zenodo.6139781">https://doi.org/10.5281/zenodo.6139781</a>

opencc-by-4.0Jan 2022View details →

Design-of-Experiments In Vitro Transcription Yield Optimization of Self-Amplifying RNA

This dataset contains original data generated from optimizing the IVT process for saRNAs that are approximately 9 kb in size through a design of experiment (DoE) approach to produce a maximal RNA yield.

opencc-by-4.0Mar 2022View details →

Data for Falgenhauer, et al., "Transcriptional interference in toehold switch-based RNA circuits"

Contains DNA sequences of the gene specific primers for RT-qPCR, the RT-qPCR raw data and output files used in "Transcriptional interference in toehold switch-based RNA circuits" by Falgenhauer et al.

opencc-zeroMar 2022View details →

Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet: transcription factor preferences

The main output of our analysis, as a raw dataset. This data was used to create the plots depicting transcription factor preferences across our paper, including for our treemaps.

opencc-by-4.0Mar 2022View details →

SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data

Processed data for the manuscript "" available on bioRxiv at "" Data is available for the following samples <ol> <li>CD34+ Multiome data : 2 replicates </li> <li>T-cell depleted bone marrow Multiome data: 2 replicates </li> </ol>   The following counts and fragments files are available for each replicate  <ol> <li><sample>_filtered_feature_bc_matrix.h5: Feature counts from CellRanger ARC</li> <li><sample>_atac_fragments.tsv.gz: ATAC fragments file from Cellranger ARC</li> <li><sample>_atac_fragments.tsv.gz.tbi: Index files for ATAC fragments file from Cellranger ARC</li> </ol>   The following scanpy anndata objects are also available <ol> <li>cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of CD34+ hematopoietic stem and progenitor cells </li> <li>cd34_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of of CD34+ hematopoietic stem and progenitor cells.</li> <li>cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of T-cell depleted bone marrow dataset.</li> <li>bm_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of T-cell depleted bone marrow dataset.</li> </ol>

opencc-by-4.0Apr 2022View details →

Sequencing data of RNA editing, RNA modifications, and transcriptional units in Listeria monocytogenes

Sequencing data for "RNA editing, RNA modifications, and transcriptional units in Listeria monocytogenes" manuscript, which is submitted to BMC genomics.

opencc-by-4.0May 2022View details →

A Genome-Wide Evolutionary Simulation of the Transcription-Supercoiling Coupling: extended version

Data set used for the Artificial Life journal paper <a href="https://direct.mit.edu/artl/article-abstract/28/4/440/112557/A-Genome-Wide-Evolutionary-Simulation-of-the">A Genome-Wide Evolutionary Simulation of the Transcription-Supercoiling Coupling: extended version</a>. A preprint of the paper is also available <a href="https://hal.archives-ouvertes.fr/hal-03667822">here</a>. This data is also used in Chapter 4 of my <a href="https://gitlab.inria.fr/tgrohens/phd">PhD thesis</a>.

opencc-zeroJul 2022View details →

Transcript- and annotation-guided genome assembly of the European starling

The European starling, Sturnus vulgaris, is an ecologically significant, globally invasive avian species that is also suffering from a major decline in its native range. Here, we present the genome assembly and long-read transcriptome of an Australian-sourced European starling (S. vulgaris vAU), and a second North American genome (S. vulgaris vNA), as complementary reference genomes for population genetic and evolutionary characterisation. S. vulgaris vAU combined 10x Genomics linked-reads, low-coverage Nanopore sequencing, and PacBio Iso-Seq full-length transcript scaffolding to generate a 1050 Mb assembly on 1,628 scaffolds (72.5 Mb scaffold N50). Species-specific transcript mapping and gene annotation revealed high structural and functional completeness (94.6% BUSCO completeness). Further scaffolding against the high-quality zebra finch (Taeniopygia guttata) genome assigned 98.6% of the assembly to 32 putative nuclear chromosome scaffolds. Rapid, recent advances in sequencing technologies and bioinformatics software have highlighted the need for evidence-based assessment of assembly decisions on a case-by-case basis. Using S. vulgaris vAU, we demonstrate how the multifunctional use of PacBio Iso-Seq transcript data and complementary homology-based annotation of sequential assembly steps (assessed using a new tool, SAAGA) can be used to assess, inform, and validate assembly workflow decisions. We also highlight some counter-intuitive behaviour in traditional BUSCO metrics, and present BUSCOMP, a complementary tool for assembly comparison designed to be robust to differences in assembly size and base-calling quality. Finally, we present a second starling assembly, S. vulgaris vNA, to facilitate comparative analysis and global genomic research on this ecologically important species.

opencc-zeroJul 2022View details →

Dataset for: Ultrarapid detection of SARS-CoV-2 RNA using a reverse transcription-free exponential amplification reaction, RTF-EXPAR

A dataset is reported for a rapid isothermal method for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19. The procedure uses an unprecedented reverse transcription–free (RTF) approach for converting genomic RNA into DNA. This involves the formation of an RNA/DNA heteroduplex whose selective cleavage generates a short DNA trigger strand, which is then rapidly amplified using the exponential amplification reaction (EXPAR). Deploying the RNA-to-DNA conversion and amplification stages of the RTF-EXPAR assay in a single step results in the detection, via a fluorescence read-out, of single figure copy numbers per microliter of SARS-CoV-2 RNA in under 10 min. In direct three-way comparison studies the assay has been found to be faster than both PCR and loop-mediated isothermal amplification (LAMP), while being just as sensitive. The assay protocol involves the use of standard laboratory equipment and is readily adaptable for the detection of other RNA-based agents.

opencc-zeroSep 2022View details →

The interplay between prior selection, mild intermittent exposure, and acute severe exposure in phenotypic and transcriptional response to hypoxia

Hypoxia has profound and diverse effects on aerobic organisms, disrupting oxidative phosphorylation and activating several protective pathways. Predictions have been made that exposure to mild intermittent hypoxia may be protective against more severe exposure and may extend lifespan. Both effects are likely to depend on prior selection on phenotypic and transcriptional plasticity in response to hypoxia, and may therefore show signs of local adaptation. Here we report the lifespan effects of chronic, mild, intermittent hypoxia (CMIH) and short-term survival in acute severe hypoxia (ASH) in four clones of Daphnia magna originating from either permanent or intermittent habitats, the latter regularly drying up with frequent hypoxic conditions. We show that CMIH extended the lifespan in the two clones originating from intermittent habitats but had the opposite effect in the two clones from permanent habitats, which also showed lower tolerance to ASH. Exposure to CMIH did not protect against ASH; to the contrary, Daphnia from the CMIH treatment had lower ASH tolerance than normoxic controls. Few transcripts changed their abundance in response to the CMIH treatment in any of the clones. After 12 hours of ASH treatment, the transcriptional response was more pronounced, with numerous protein-coding genes with functionality in mitochondrial and respiratory metabolism, oxygen transport, and, unexpectedly, gluconeogenesis showing up-regulation. While clones from intermittent habitats showed somewhat stronger differential expression in response to ASH than those from permanent habitats, there were no significant hypoxia-by-habitat of origin or CMIH-by-ASH interactions. GO enrichment analysis revealed a possible hypoxia tolerance role by accelerating the molting cycle and regulating neuron survival through up-regulation of cuticular proteins and neurotrophins, respectively.

opencc-zeroOct 2022View details →

Transcriptional regulation underlying the temperature response of embryonic development rate in the winter moth

Climate change will strongly affect the developmental timing of insects, as their development rate largely depends on ambient temperature. However, we know little about the genetic mechanisms underlying the temperature sensitivity of embryonic development in insects. We investigated embryonic development rate in the winter moth (Operophtera brumata), a species with egg dormancy that has been under selection due to climate change. We used RNAseq to investigate which genes are involved in the regulation of winter moth embryonic development rate in response to temperature. Over the course of development, we sampled eggs before and after an experimental change in ambient temperature, including two early development weeks when the temperature sensitivity of eggs is low and two late development weeks when temperature sensitivity is high. We found temperature-responsive genes that responded in a similar way across development, as well as genes with a temperature response specific to a particular development week. Moreover, we identified genes whose temperature effect size changed around the switch in temperature sensitivity of development rate. Interesting candidate genes for regulating the temperature sensitivity of egg development rate included genes involved in histone modification, hormonal signalling, nervous system development, and circadian clock genes. In conclusion, the diverse sets of temperature-responsive genes we found here indicate that there are many potential targets of selection to change the temperature sensitivity of embryonic development rate. Identifying for which of these genes there is genetic variation in wild insect populations will give insight into their adaptive potential in the face of climate change.

opencc-by-4.0Feb 2017View details →

Single molecule, full-length transcript sequencing provides insight into the extreme metabolism of ruby-throated hummingbird Archilochus colubris

Hummingbirds can support their high metabolic rates exclusively by oxidizing ingested sugars, which is unsurprising given their sugar-rich nectar diet and use of energetically expensive hovering flight. However, they cannot rely on dietary sugars as a fuel during fasting periods, such as during the night, at first light, or when undertaking long-distance migratory flights, and must instead rely exclusively on onboard lipids. This metabolic flexibility is remarkable both in that the birds can switch between exclusive use of each fuel type within minutes and in that de novo lipogenesis from dietary sugar precursors is the principle way in which fat stores are built, sometimes at exceptionally high rates, such as during the few days prior to a migratory flight. The hummingbird hepatopancreas is the principle location of de novo lipogenesis and likely plays a key role in fuel selection, fuel switching, and glucose homeostasis. Yet understanding how this tissue, and the whole organism, achieves and moderates high rates of energy turnover is hampered by a fundamental lack of information regarding how genes coding for relevant enzymes differ in their sequence, expression, and regulation in these unique animals. To address this knowledge gap, we generated a de novo transcriptome of the hummingbird liver using PacBio full-length cDNA sequencing (Iso-Seq), yielding a total of 8.6Gb of sequencing data, or 2.6M reads from 4 different size fractions. We analyzed data using the SMRTAnalysis v3.1 Iso-Seq pipeline, including classification of reads and clustering of isoforms (ICE) followed by error-correction (Arrow). We performed orthology analysis to identify closely related sequences between our transcriptome and other avian and human gene sets. We also aligned our transcriptome against the Calypte anna genome where possible. Finally, we closely examined homology of critical lipid metabolic genes between our transcriptome data and avian and human genomes. We confirmed high levels of sequence divergence within hummingbird lipogenic enzymes, suggesting a high probability of adaptive divergent function in the lipogenic liver pathways. Our results have leveraged cutting-edge technology and a novel bioinformatics pipeline to provide a compelling first direct look at the transcriptome of this incredible organism.

opencc-zeroMay 2024View details →

Data from: Nascent transcription reveals regulatory changes in extremophile fishes inhabiting hydrogen sulfide-rich environments

Regulating transcription allows organisms to respond to their environment, both within a single generation (plasticity) and across generations (adaptation). We examined transcriptional differences in gill tissues of fishes in the Poecilia mexicana species complex (family Poeciliidae), which have colonized toxic springs rich in hydrogen sulfide (H2S) in southern Mexico. There are gene expression differences between sulfidic and non-sulfidic populations, yet regulatory mechanisms mediating this gene expression variation remain poorly studied. We combined capped-small RNA sequencing (csRNA-seq), which captures actively transcribed (i.e., nascent) transcripts, and traditional messenger RNA sequencing (mRNA-seq) to examine how variation in transcription, enhancer activity, and associated transcription factor binding sites may facilitate adaptation to extreme environments. csRNA-seq revealed thousands of differentially initiated transcripts between sulfidic and non-sulfidic populations, many of which are involved in H2S detoxification and response. Analyses of transcription factor binding sites in promoter and putative enhancer csRNA-seq peaks identify a suite of transcription factors likely involved in regulating H2S-specific shifts in gene expression, including several key transcription factors known to respond to hypoxia. Our findings uncover a complex interplay of regulatory processes that reflect the divergence of extremophile populations of P. mexicana from their non-sulfidic ancestors and suggest shared responses among evolutionarily independent lineages.

opencc-by-4.0May 2024View details →

Data from the MA Thesis "Does She Talk Differently?: Exploring Implications of Gender in US Presidential and Vice Presidential Debates" and Coded Transcriptions of the 7 Analyzed Debates

The raw data collected for the master's thesis "Does She Talk Differently?: Exploring Implications of Gender in US Presidential and Vice Presidential Debates", the tables and graphs created based on the data as well as the transcriptions for the seven debates analyzed for the research paper can be found in the files.