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Pneumocystis spp. in pigs: a longitudinal quantitative study and co-infections assessment in Austrian farms
<p>The present upload represents the supplementary materials of the manuscript " <em>Pneumocystis</em> spp. in pigs: a longitudinal quantitative study and co-infections assessment in Austrian farms" which is under submission</p>
Supplementary Data for: Unique Transcriptomic Changes Underlie Hormonal Interactions During Mammary Histomorphogenesis in Female Pigs
<p>Successful lactation and the risk for developing breast cancer depend on growth and differentiation of the mammary gland (MG) epithelium that is regulated by ovarian steroids (17beta-estradiol [E] and progesterone [P]) and pituitary-derived prolactin (PRL). Given that the MG of pigs share histomorphogenic features present in the normal human breast, we sought to define the transcriptional responses within the MG of pigs following exposure to all combinations of these hormones. Hormone-ablated female pigs were administered combinations of E, medroxyprogesterone 17-acetate (source of P), and either haloperidol (to induce PRL) or 2-bromo-a-ergocryptine. We subsequently monitored phenotypic changes in the MG including mitosis, receptors for E and P (ESR1 and PGR), level of phosphorylated STAT5 (pSTAT5), and the frequency of terminal ductal lobular unit (TDLU) subtypes; these changes were then associated with all transcriptomic changes. Estrogen altered the expression of ~20% of all genes that mostly associated with mitosis, whereas PRL stimulated elements of fatty acid metabolism and an inflammatory response. Several outcomes, including increased pSTAT5, highlighted the ability of E to enhance PRL action. Regression of transcriptomic changes against several MG phenotypes revealed 1,669 genes correlated with proliferation, among which 29 were E-inducible. Additional gene expression signatures were associated with TDLU formation and the frequency of ESR1 or PGR. These data provide a link between the hormone-regulated genome and phenome of the MG in a species having a complex histoarchitecture like that in the human breast, and highlight an underexplored synergy between the actions of E and PRL during MG development.</p>
Amines and lipids metabolites in blood plasma and saliva samples in pigs.
<p>The dataset presented in here is generated in a project named "<strong>Effects of sanitary and health status on amino acid and energy metabolism of growing-finishing pigs.</strong>" The metabolomics data from two samples types in pigs were generated in collaboration with Metabolomics Facility Leiden, The Netherlands and Wageningen Livestock Research, The Netherlands. This collaboration was realized and funded by Enabling Technology Hotels programme, ZonMW, NWO, The Netherlands (<strong>project number: 435005015</strong>). </p> <p>Targeted quantification of metabolites in two metabolomic platforms covering amines and oxidative stress metabolites in the blood and saliva samples in pigs. The samples were collected from a feeding trial. Briefly, After weaning, i.e., at week 4, pigs were fed a starter (4-9 weeks), grower (9-14 weeks), and finisher (14-22 weeks) diet containing either starch or fat as an energy source. At week 9, before the pigs were fed the grower diet, blood plasma and saliva samples were collected from the pigs (n=6) and the animals were stratified according to different hygiene conditions. At week 14, i.e., before the pigs received the finisher diet, and at week 22, i.e., at the end of this experiment, blood plasma and saliva samples were collected from the pigs (n=6) in the cohort receiving a diet with a different energy source under contrasting sanitary status. </p> <p>Targeted quantification of metabolites in two metabolomic platforms covering amines and oxidative stress metabolites in the blood and saliva samples in pigs. The number of identified metabolites are shown in Table 1.</p> <p><strong>Table 1</strong>: <strong>Number of identified amines and lipids metabolites in blood plasma and saliva samples in pigs.</strong> </p> <table> <tbody> <tr> <td> <table align="center"> <tbody> <tr> <td> <p> </p> </td> <td> <p>Data reported as</p> </td> </tr> <tr> <td> </td> <td> <p>Peak areas<sup>1</sup></p> </td> <td> <p>Relative response ratios<sup>4</sup></p> </td> </tr> <tr> <td> <p> </p> </td> <td> <p>Confidence<sup>2</sup></p> </td> <td> <p>Caution<sup>3</sup></p> </td> <td> <p>Confidence</p> </td> <td> <p>Caution</p> </td> </tr> <tr> <td> <p><em>Amines</em></p> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <p>Blood plasma</p> </td> <td> <p>not required</p> </td> <td> <p>not required</p> </td> <td> <p>58</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>Saliva</p> </td> <td> <p>not required</p> </td> <td> <p>not required</p> </td> <td> <p>52</p> </td> <td> <p>5</p> </td> </tr> <tr> <td> <p><em>Lipids </em></p> <p><em>(low pH)</em></p> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <p>Blood plasma</p> </td> <td> <p>47</p> </td> <td> <p>17</p> </td> <td> <p>47</p> </td> <td> <p>17</p> </td> </tr> <tr> <td> <p>Saliva</p> </td> <td> <p>18</p> </td> <td> <p>34</p> </td> <td> <p>52</p> </td> <td> <p>11</p> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <p><em>Lipids </em></p> <p><em>(High pH)</em></p> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> <p>Blood plasma</p> </td> <td> <p>24</p> </td> <td> <p>25</p> </td> <td> <p>24</p> </td> <td> <p>25</p> </td> </tr> <tr> <td> <p>Saliva</p> </td> <td> <p>28</p> </td> <td> <p>17</p> </td> <td> <p>28</p> </td> <td> <p>17</p> </td> </tr> </tbody> </table> <p> </p> </td> </tr> </tbody> </table> <p></p> <p><sup>1</sup> For the lipid platform, large variations in internal standard were observed between study samples. This could be due to the difference in matrix effect between the study samples, i.e., blood plasma and saliva. It is known that the matrix effect varies significantly depending on the origin of the samples and is influenced by phenotypic characteristics such as species, age, and gender. Therefore, peak areas were provided as an additional data set that can be used as input data for downstream metabolomics analysis.</p> <p><sup>2</sup> Metabolite signaling complied with the acceptance criteria of RSDqc <15%.</p> <p><sup>3</sup> Metabolite signaling did not comply with the acceptance criteria of our quality control i.e. of RSDqc <15%, but they present RSDs up to 30%.</p> <p><em><sup>4</sup> </em>target area/ISTD area; unit free<em>.</em> </p> <p>Available data-set:</p> <p>-Four different signaling lipids data-set: 1) peak areas for plasma samples, 2) peak area ratios (metabolite to ISTD) for plasma samples, 3) peak areas for saliva samples, and 4) peak area ratios (metabolite to ISTD) for saliva samples.</p> <p> - Two signalling amine data-set: 1) peak area ratios (metabolite to ISTD) for plasma samples, and 2) peak area ratios (metabolite to ISTD) for saliva samples.</p> <p> </p>
Introgressive hybridisation between domestic pigs (Sus scrofa domesticus) and endemic Corsican wild boars (S. s. meridionalis): effects of human-mediated interventions
<p class="MsoNormal"><span>Owing to the intensified domestication process with artificial trait selection, introgressive hybridisation between domestic and wild species poses a management problem. Traditional free-range livestock husbandry, as practiced in Corsica and Sardinia, is known to facilitate hybridisation between wild boars and domestic pigs (<em>Sus scrofa</em>). Here, we assessed the genetic distinctness and genome-wide domestic pig ancestry levels of the Corsican wild boar subspecies <em>S. s. meridionalis,</em> with reference to its Sardinian conspecifics, employing a genome-wide single nucleotide polymorphism (SNP) assay and mitochondrial control region (mtCR) haplotypes. We also assessed the reliance of morphological criteria and the melanocortin-1 receptor (<em>MC1R</em>) coat colour gene to identify individuals with domestic introgression. While Corsican wild boars showed closest affinity to Sardinian and Italian wild boars compared to other European populations based on principal component analysis, the observation of previously undescribed mtCR haplotypes and high levels of nuclear divergence (Weir's </span><span> </span><span> 0.14) highlighted the genetic distinctness of Corsican <em>S. s. meridionalis</em>. </span><span>Across three complementary analyses of mixed ancestry (i.e., STRUCTURE, PCADMIX, and ELAI), proportions of domestic pig ancestry were estimated at 9.5% in Corsican wild boars, which was significantly higher than in wild boars in Sardinia, where free-range pig keeping was banned in 2012. Comparison of morphologically pure- and hybrid-looking Corsican wild boars suggested a weak correlation between morphological criteria and genome-wide domestic pig ancestry. The study highlighted the usefulness of molecular markers to assess the direct impacts of management practices on gene flow between domestic and wild species.</span></p>
Pig rooting surveys
<b>Description: </b><p>This is a dataset on pig rooting observations in the SAFE landscape in 2021. In 2021, the Bearded Pigs of Sabah were severely affected and decimated by the African Swine Fever. These rooting surveys were conducted to provide an indication whether there were recent Bearded pig activity in the SAFE landscape. </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://safeproject.net/projects/project_view/173"><b>Group Dynamics of Bornean Bearded Pigs: the advantages of behavioural plasticity in changeable landscapes.</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://safeproject.net/datasets/xml_metadata?id=6477762">here</a></p><p><b>Files: </b>This consists of 1 file: SAFE_pig_rooting_surveys_2021_for_upload.xlsx</p><p><b>SAFE_pig_rooting_surveys_2021_for_upload.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Pig rooting observations</b> (described in worksheet Data)</p><p>Description: The observations on the presence or absence of Bearded pig rooting.</p><p>Number of fields: 11</p><p>Number of data rows: 88</p><p>Fields: </p><ul><li><b>Date</b>: Calender date of field survey (Field type: date)</li><li><b>Location</b>: Unique ID (Field type: location)</li><li><b>Observers</b>: names of the observers (Field type: id)</li><li><b>Distance_along_line_transect</b>: Distance along line transect (Field type: numeric)</li><li><b>Left_or_right</b>: observations about 10m along the left or the right of the transect line (Field type: categorical)</li><li><b>Rooting_observed</b>: soil disturbance / rooting observed (Field type: categorical)</li><li><b>Age_of_rooting</b>: rooting age (fresh = within weeks, old = 1-3 months, aged >3months) (Field type: categorical)</li><li><b>Pig_tracks</b>: Presence of pig tracks (Field type: categorical trait)</li><li><b>Photo_ID</b>: File name (Field type: id)</li><li><b>Distance_from_transect</b>: Distance left or right from the transect (Field type: numeric)</li><li><b>Comments</b>: Any additional relevant information (Field type: comments)</li></ul></li></ol><p><b>Date range: </b>2021-01-01 to 2021-07-14</p><p><b>Latitudinal extent: </b>4.6680 to 4.6920</p><p><b>Longitudinal extent: </b>117.5793 to 117.5935</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Artiodactyla <br> -  -  -  -  -  Suidae <br> -  -  -  -  -  -  <i>Sus</i> <br> -  -  -  -  -  -  -  <i>Sus barbatus</i> <br></div><p></p>
Maternal and/or direct supplementation with a combination of a casein hydrolysate and yeast β-glucan on postweaning performance and intestinal health in the pig
<p>A 2 <span>× </span>2 factorial experiment was conducted to investigate the effect of maternal supplementation from day 83 of gestation and/or direct supplementation from weaning of a bovine casein hydrolysate plus a yeast β‑glucan (CH-YBG) on pig performance and intestinal health on day ten post‑weaning. Twenty cross bred gilts <span>(Large White × Landrace) were randomly assigned to one of two dietary groups (<em>n</em> = 10 gilts/group): basal diet (basal sows) and basal diet supplemented with </span>CH‑YBG (supplemented sows)<span> from day 83 of gestation until weaning (2g/sow/day). At weaning, 120 pigs (6 pigs/sow) were selected. The two dam groups were further divided, resulting in four experimental groups (10 replicates/group; 3 pigs/pen) as follows: 1) BB (basal sows + basal pigs); 2) BS (basal sows + supplemented pigs); 3) SB (supplemented sows + basal pigs); 4) SS (supplemented sows + supplemented pigs). Supplemented pigs were offered 0.5g CH‑YBG/kg of feed for 10 days post-weaning. On day 10 post‑weaning, 1 pig/pen was humanely sacrificed and samples were taken from the gastrointestinal tract for analysis. Pigs weaned from supplemented sows (SS, SB) had reduced faecal scores and incidence of diarrhoea (P<0.05) compared to pigs weaned from basal sows (BB, BS), with SS pigs not displaying the transient rise in faecal scores seen in the other three groups from day 3 to day 10 post‑weaning (P<0.05). Pigs weaned from supplemented sows had reduced feed intake (P<0.05), improved feed efficiency (P<0.05), increased butyrate concentrations (P<0.05), increased abundance of </span><em><span>Lactobacillus </span></em><span>(P<0.05) </span><span>and decreased abundance of </span><em><span>Enterobacteriaceae</span></em><span><em> </em>and <em>Campylobacteraceae </em>(P<0.05) compared to pigs weaned from basal sows. In conclusion, maternal supplementation increased the abundance of <em>Lactobacillus </em>and decreased the abundance of <em>Enterobacteriaceae </em>and <em>Campylobacteraceae </em>while also increasing butyrate concentrations. The combination of maternal and direct supplementation led to pigs having the lowest faecal scores compared to all other groups.</span></p>
FUNCTIONAL ANALYSIS OF GENES FOR REPRODUCTIVE TRAITS IN PIGS: FROM GWAS TO POST-GWAS
<p>Reproductive traits, such as number of teats, uniformity and litter size, are essential for animal breeding programs due to the importance for the production chain, since they influence the maternal ability of sow and can affect the number of weaned piglets. Our objective was to identify candidate genes associated with reproductive traits in pigs, using GWAS data, from a systematic review combined with sequencing data, to build networks of biological processes and Gene-TFs (transcription factors networks from the identified genes in order to highlight the most candidate genes for litter size, uniformity and number of teats. In the systematic review only peer-reviewed articles were used, with descriptors related to the evaluated traits, and selected based on eligibility criteria. Fourteen papers were selected and classified into groups for functional analysis of gene networks with 2077 candidate genes identified. After combining with the list of genes presenting known structural variants in the 5'UTR and/or coding region, 306 genes remained to be used to build the networks of biological processes and TFs gene networks, highlighting processes associated with litter size (e.g., ionotropic glutamate receptor signaling pathway and blastocyte growth) and teats number (e.g., growth hormone receptor, regulation of the BMP - Bone Morphogenetic Proteins signaling pathway and blood vessel proliferation). Three most candidate genes for litter size trait (<em>GRID2</em>and <em>PALB2</em>) and six most candidate genes (<em>GHR, IFT80,</em> <em>FSTL3, SKOR1, SMURF1</em> and <em>AKT3</em>) for teats number were prioritized. TF associated with candidate genes were also identified for litter size (<em>PALB2</em> and <em>GRID2</em>) and teat number (<em>RIN, LTBP2</em> and <em>COL6A6</em>). Thus, it is suggested that the genes and TFs presented in this study may play an important role in the traits studied, being important for genetic studies and animal breeding. The highlighted genes may bring new considerations to the current knowledge of the genetic architecture of these traits, since the markers associated with these genes can be assigned higher weights in genomic selection and validated in specific populations.</p>
Dynamic data of body weight and feed intake in fattening pigs and the determination of energetic allocation factors using a dynamic linear model
<p>This is the R script (DLM_script.R) to characterize the evolution of the energetic allocation factor (α<sub>t</sub>) which represents the link between the cumulative net energy available (estimated from feed intake) and cumulative weight gain during fattening period. The data for the 100 fattening pigs are stored in the csv file (DataAxiom.csv) and structured as follows:</p> <ul> <li>ID: pig identification number;</li> <li>Fattening_group.Pen : fattening group and pen number for a given ID;</li> <li>t (day): time in days since the transfer to fattening room;</li> <li>Wt (kg) : median weight in kg at day t for a given ID;</li> <li>FIt (kg day-1) : total feed intake in kg at day t for a given ID.</li> </ul> <p>For detail description of the procedure please see article.</p>
Welfare assessment of Krškopolje pigs
<p>Data file and metadata file accompanying the article.</p>
Roman Pig Hunting Scene Statue
Roma döneminden kalma domuz avı heykeli, Ankara Anadolu Medeniyetleri müzesi Source: Objaverse 1.0 / Sketchfab
Prebiotic galactooligosaccharide (GOS) effects on suckling and weaned pigs
<p>Galactooligosaccharides were supplemented to gruel creep diets during farrowing and/or in phase 1 nursery diets. Growth performance, intestinal health parameters (such as GI morphology, short-chain fatty acids & microbial community) and plasma cytokins were evaluated under the hypothesis that GOS would improve piglet growth through its prebiotic effects as it is fermented in the intestine.</p>
Uncovering the little known impact of a millennia-old traditional use of temperate oak forests: free-ranging domestic pigs markedly change the herb layer, but barely affect the shrub layer
<p>This excel file contains data on ground, herb and shrub layer characteristics of hardwood floodplain forests under different disturbance intensity by free-ranging domestic pigs, a millennia-old practice in Eurasia. We used these dataset to create figures 3, 4, 5, 6 (a) (b), 7, 8 presented in the paper „Uncovering the little known impact of a millennia-old traditional use of temperate oak forests: free-ranging pigs markedly change the herb layer, but barely affect the shrub layer”. Vegetation surveys were conducted in the spring and late summer periods of 2017 and 2018. The bare soil surface and litter cover were visually estimated within each 0.25 ha sampling plot. The cover and composition of the herb layer were recorded using 30 subsamples (1 m2) at each SP (altogether 1680 subsamples). 28 subsamples were located along the four cardinal directions at 2 m distances running from the centre of sampling plots and 2 other subsamples were randomly positioned. The total cover of the upper (higher than 130 cm) and lower (50-130 cm) shrub layer, and the cover of each species by layers, were visually estimated in each 0.25 ha SP. The browsing, rooting and rubbing impacts of pigs were measured along a 56-m-long transect running through the centre of the SPs from north to south. We sampled altogether from 3138 to 3282 woody specimens depending on variables used to describe pigs impacts on specimens.</p>
Pangenome of pigs
<p>This dataset contained the annotation file of three different breeds, including Laiwu, Meishan and, Tongcheng pigs. The SNPs and SVs in 18 pig assembilies can be accessed by this dataset. The graph-based pangenome was constructed using vg combined with Sscrofa11.1 reference genome and the SVs in the 18 pig assemblies. SNPs and SVs detected in the 599 pig genomes are also updated in this dataset.</p>
SBF-SEM Dataset of Guinea Pig Adult Psoas
<p>Multiple SBF-SEM datasets from 3 Duncan hartley guinea pig adult psoas muscle. Parameters for each of the datasets are attached as a spreadsheet, including nm resolution, image size, number of sections and section thickness. </p> <p> </p>
Long term bearded pig camera trap data across the SAFE landscape.
<p><strong>Description: </strong></p> <p>Data on camera trap surveys and capture events for bearded pigs across the SAFE landscape from 2011-2017.<br> Data was collected by Dr Oliver Wearn from 2011 to 2014, by Phil Chapman from 2015 to 2016 and by Charlie Davison in 2017.<br> Used to assess how bearded pigs are responding to land-use change in Sabah. NB: These data are a subset of the full SAFE Project core mammal trapping data, but include additional details about bearded pig social structure and abundances.</p> <p><strong>Project: </strong>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/173"><strong>Group Dynamics of Bornean Bearded Pigs: the advantages of behavioural plasticity in changeable landscapes.</strong></a></p> <p><strong>XML metadata: </strong>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=312">here</a></p> <p><strong>Files: </strong>This consists of 1 file: DavisonBeardedPigs.xlsx</p> <p><strong>DavisonBeardedPigs.xlsx</strong></p> <p>This file contains dataset metadata and 2 data tables:</p> <ol> <li> <p><strong>Deployments</strong> (described in worksheet Deployments)</p> <p>Description: Data relating to all random camera trap deployments</p> <p>Number of fields: 5</p> <p>Number of data rows: 833</p> <p>Fields:</p> <ul> <li><strong>TrapID</strong>: Camera placement point on SAFE project core grids (Field type: Location)</li> <li><strong>Date.On</strong>: Date survey started (Field type: Date)</li> <li><strong>Date.Off</strong>: Date survey ended (Field type: Date)</li> <li><strong>CTNs</strong>: Length of survey (camera trap nights). Zero if camera was faulty. (Field type: Numeric)</li> <li><strong>Landuse</strong>: Land-use type (Field type: Categorical)</li> </ul> </li> <li> <p><strong>Records</strong> (described in worksheet Records)</p> <p>Description: Data relating to all camera trap records of bearded pigs across all land-uses, and humans and domestic dogs in Oil palm; data generated from individual camera trap images</p> <p>Number of fields: 13</p> <p>Number of data rows: 4236</p> <p>Fields:</p> <ul> <li><strong>TrapID</strong>: Camera placement location on SAFE project core grids (Field type: Location)</li> <li><strong>Date</strong>: Date of photo capture (Field type: Date)</li> <li><strong>Time</strong>: Time of photo capture (Field type: Time)</li> <li><strong>Ambient.Temp</strong>: Temperature at the time of photo capture (Field type: Numeric)</li> <li><strong>Moon.Phase</strong>: Moonphase at time of photo capture (Field type: Categorical)</li> <li><strong>Species</strong>: Identity of the individual(s) (Field type: Taxa)</li> <li><strong>Soc.Str</strong>: Social structure (Field type: Categorical)</li> <li><strong>Sex</strong>: Sex of the individual (Field type: Categorical)</li> <li><strong>No.Individuals</strong>: Number of individuals in survey (Field type: Abundance)</li> <li><strong>No.Juveniles</strong>: Number of adults in survey (Field type: Abundance)</li> <li><strong>No.Subadults</strong>: Number of subadults in survey (Field type: Abundance)</li> <li><strong>No.Adults</strong>: Number of juveniles in survey (Field type: Abundance)</li> <li><strong>Land-use</strong>: Land use type (Field type: Categorical)</li> </ul> </li> </ol> <p><strong>Date range: </strong>2011-04-30 to 2018-04-01</p> <p><strong>Latitudinal extent: </strong>4.6350 to 4.7538</p> <p><strong>Longitudinal extent: </strong>116.9472 to 117.6253</p> <p><strong>Taxonomic coverage: </strong><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p> <p>Animalia<br>  - Chordata<br>  -  - Mammalia<br>  -  -  - Artiodactyla<br>  -  -  -  - Suidae<br>  -  -  -  -  - <em>Sus</em><br>  -  -  -  -  -  - <em>Sus barbatus</em><br>  -  -  - Carnivora<br>  -  -  -  - Canidae<br>  -  -  -  -  - <em>Canis</em><br>  -  -  -  -  -  - <em>Canis lupus</em><br>  -  -  -  -  -  -  - <em>Canis lupus familiaris</em><br>  -  -  - Primates<br>  -  -  -  - Hominidae<br>  -  -  -  -  - <em>Homo</em><br>  -  -  -  -  -  - <em>Homo sapiens</em></p> <p> </p>
Effect of feedstock pH in nutrient recovery from pig slurry liquid fraction
Open the record for dataset details and reuse information.
High-throughput untargeted metabolomics reveals metabolites and metabolic pathways that differentiate two divergent pig breeds
<h3><em><strong>Content</strong></em></h3> <p>Dataset of the study: "High-throughput untargeted metabolomics reveals metabolites and metabolic pathways that differentiate two divergent pig breeds.</p>
Pigs feeding behaviours from two different farms, including behaviours during a tail biting event
<p>These data are linked to the article from Ollagnier et al, 2021 (https://doi.org/10.1101/2021.05.11.443554)</p> <p><strong>Data desription</strong></p> <p>This data set comprises the feeding behaviours of two herds of grower-finisher pigs weighing between 25 and 100 kilograms. One data set originates from a testing boar station in Sweden and contains data collected from October 2004 to July 2007. The data set comes from a previous retrospective study that Wallenbeck and Keeling published in 2013. The second data set contains data from the experimental pig farm of Agroscope and comprises recordings from November 2018 to April 2020. As tail docking is prohibited in Sweden and in Switzerland, the data are from pigs with intact tails.</p> <p>The Swedish data set includes data from 42 pens (21 TB and 21 CTL ) of boars (purebred Yorkshire, Landrace or Hampshire) recorded 70 days before and after the TB date. Boars were housed in groups of 7 to 14 animals per pen. Each pen measured 15.7 m<sup>2 </sup>and had a slatted floor and plain resting area. All pigs had <em>ad libitum</em> access to the pelleted feed, which was optimised according to the Swedish nutrition norms for fattening pigs [25]. Water was provided <em>ad libitum</em> and straw was offered daily.</p> <p>The Swiss data set consisted of 23 pens (six TB and 17 CTL) of females and castrated male pigs (Swiss Large White), recorded 100 days before and after the TB date. Twenty pens (18 m<sup>2</sup>) contained 11 to 15 pigs each and were equipped with two automatic feeders; three pens (78 m<sup>2</sup>) were equipped with eight automatic feeders for 31 to 55 pigs each. All pens had straw in racks and sawdust on the floor. Water was available <em>ad libitum</em> through nipple drinkers. The pelleted finisher diet was formulated to have 20% lower dietary crude protein and essential amino acids compared to a standard diet formulated according to the Swiss feeding recommendations for pigs.</p> <p><strong>Data structure:</strong></p> <p>Three observations were considered to describe the feeding behaviours of pigs. </p> <p><strong>DFV: </strong>Number of visits to the feeder (from 0:00 to 23:59:59 that date), unit=n, </p> <p><strong>DFC: </strong>Total feed consumption (from 0:00 to 23:59:59 that date), unit=g</p> <p><strong>StdFC</strong>: Daily standard deviation of the feed consumption at each visit, unit=g</p> <p>The data set also contains the following information:</p> <p><strong>Farm:</strong> origin of the feeding behavior data (Swiss or Swedish farm)</p> <p><strong>ID: </strong>unique identification of the pig</p> <p><strong>date:</strong> date at which the feeding behavior is recorded, numerical format.</p> <p><strong>TBSTART:</strong> date at which the tail biting event started in tail biting pens. An arbitrary date has been taken for control pens, numerical format.</p> <p><strong>PenID: </strong>unique identification of the pen.</p> <p><strong>PenType: </strong>control (K) or tail biting (TB). A pen was assigned to the TB category if at least one pig had to be treated for tail damages.</p> <p> </p> <p> </p>
FIG. 9 in Pigs and ritual-hunting among the highland Tau-Buhid in Mounts Iglit-Baco natural park, Philippines
FIG. 9. — Safong (circular burning) fully initiated. Photo credits: C. A. Rosales.
Introgression dynamics from invasive pigs into wild boar following the March 2011 natural and anthropogenic disasters at Fukushima
<p>Natural and anthropogenic disasters have the capability to cause sudden extrinsic environmental changes and long-lasting perturbations including invasive species, species expansion, and influence evolution as selective pressures force adaption. Such disasters occurred on March 11th 2011, in Fukushima, Japan when an earthquake, tsunami, and meltdown of a nuclear power plant all drastically reformed anthropogenic land use. Here, we demonstrate, using genetic data, how wild boar (<em>Sus scrofa leucomystax</em>) have persevered against these environmental changes, including an invasion of escaped domestic pigs (<em>Sus scrofa domesticus</em>). Concurrently, we show evidence of successful hybridization between pigs and native wild boar in this area, however in future offspring, the pig legacy has been diluted through time. We speculate that the range expansion dynamics inhibit long-term introgression and introgressed alleles will continue to decrease at each generation while only maternally inherited organelles will persist. Using the gene flow data among wild boar, we assume that offspring from hybrid lineages will continue dispersal north at low frequencies as climates warm. We conclude that future risks for wild boar in this area include intraspecies competition, revitalization of human related disruptions, and disease outbreaks.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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