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273 results for “human diversity”
A unified genealogy of modern and ancient genomes: Unified, inferred tree sequences of 1000 Genomes, Human Genome Diversity, and Simons Genome Diversity Projects with ancient samples
<p>Unified, inferred tree sequences built from the 1000 Genomes phase 3, Human Genome Diversity, and Simons Genome Diversity Projects with high coverage sequenced ancient samples. The ancient samples are the Altai, Chagyrskaya, and Vindija Neanderthals, the Denisovan, and a high-coverage family of four from the Afanasievo Culture.</p> <p>Each tree sequence is the arm of an autosome (the short arm of acrocentric chromosomes are not included). Tree sequences were inferred with <a href="https://tsinfer.readthedocs.io/">tsinfer</a> version 0.2.1 and <a href="https://tsdate.readthedocs.io/en/latest/">tsdate</a> version 0.1.4, as described in <a href="http://www.biorxiv.org/content/10.1101/2021.02.16.431497v2">Wohns et al. (2021)</a>. The files were compressed using <a href="https://tszip.readthedocs.io/en/stable/">tszip</a>. All data is in GRCh38.</p> <p>The full data pipeline used to generate these tree sequences and associated metadata is available on <a href="https://github.com/awohns/unified_genealogy_paper">GitHub</a>. A description can be found in the Supplementary Material of <a href="https://www.biorxiv.org/content/10.1101/2021.02.16.431497v2">Wohns et al. (2021)</a>.</p> <p>Tree sequences can be decompressed as follows:</p> <pre><code>$ tsunzip hgdp_tgp_sgdp_high_cov_ancients_chr1_p.dated.trees.tsz</code></pre> <p>Once decompressed, trees files can be loaded and processed in Python using <a href="https://tskit.readthedocs.io/">tskit</a>. </p> <pre><code>import tskit ts = tskit.load("hgdp_tgp_sgdp_high_cov_ancients_chr1_p.dated.trees") # ts is an instance of tskit.TreeSequence print("The short arm of chromosome 1 contains {} trees".format(ts.num_trees))</code></pre> <p>Accessing variant sites in the tree sequence provides the position and id of variants:</p> <pre><code>import json site = ts.site(1000) site_metadata = json.loads(site.metadata) print("The position of site 1000 is {} and its ID is {}.".format(site.position, site_metadata["ID"]))</code></pre> <p>Metadata associated with individuals and populations was derived from the original sources (<a href="http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/20130606_sample_info/20130606_g1k.ped">TGP</a>, <a>HGDP</a>, and <a href="https://sharehost.hms.harvard.edu/genetics/reich_lab/sgdp/SGDP_metadata.279public.21signedLetter.samples.txt">SGDP</a>) and converted to JSON form. For example, to access individual metadata we can use:</p> <pre><code>ind = ts.individual(0) metadata_dict = json.loads(ind.metadata)</code></pre> <p>The metadata_dict variable will now contain all the metadata for the individual with ID 0 as a dictionary. Metadata associated with populations can be found in a similar way. Population IDs are associated with individuals via their constituent nodes. For example,</p> <pre><code>pop_metadata = [json.loads(pop.metadata) for pop in ts.populations()] ind_node = ts.node(ind.nodes[0]) ind_pop_metadata = pop_metadata[ind_node.population]</code></pre> <p>After this, the ind_pop_metadata variable will contain the population level metadata for individual ID 0.</p>
Data for: Hidden diversity: Comparative functional morphology of humans and other species
<p>Gastrointestinal (GI) morphology plays an important role in nutrition, health, and epidemiology, yet limited data on gastrointestinal variation have been collected since 1885. Here we demonstrate that students can collect reliable data sets on gut morphology; when they do, they reveal greater morphological variation for some structures in the GI than has been documented in the published literature. We discuss trait variability both within and among species, and the implications of that variability for evolution and epidemiology. Our results show that morphological variation in the GI tract is associated with each organ's role in food processing. For example, the length of many structures was found to vary significantly with feeding strategy. Within species, the variability illustrated by the coefficients of variation suggests that selective constraints may vary with function. Within humans, we detected significant correlations between the various lengths of the liver and appendix (p = 0.0174) and with the colon (p = 0.0494), as well as between the small intestine and colon (p = 0.0445), which are arguably the most vital organs in the gut for nutrient absorption. Notably, intraspecific variation in the small intestine can be associated with life history traits. In humans, females demonstrated consistently and significantly longer small intestines than males (p = 0.0403). This finding supports the female canalization hypothesis, specifically, increased female investment in the digestion and absorption of lipids.</p>
Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms
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Functional traits and metacommunity theory reveal that habitat filtering and competition maintain bird diversity in a human shared landscape
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Data for: Hidden diversity: Comparative functional morphology of humans and other species
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Data from: Impact of human foraging on tree diversity, composition and abundance in a tropical rainforest
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Data from: Increased diversity and concordant shifts in community structure of coral-associated Symbiodiniaceae and bacteria subjected to chronic human disturbance
<p>Coral-associated bacteria and endosymbiotic algae (Symbiodiniaceae<i> </i>spp.) are both vitally important for the biological function of corals. Yet little is known about their co-occurrence within corals, how their diversity varies across coral species, or how they are impacted by anthropogenic disturbances. Here, we sampled coral colonies (n = 472) from seven species, encompassing a range of life history traits, across a gradient of chronic human disturbance (n = 11 sites on Kiritimati (Christmas) atoll) in the central equatorial Pacific, and quantified the sequence assemblages and community structure of their associated Symbiodiniaceae<i> </i>and bacterial communities. Although Symbiodiniaceae alpha diversity did not vary with chronic human disturbance, disturbance was consistently associated with higher bacterial Shannon diversity and richness, with bacterial richness by sample almost doubling from sites with low to very high disturbance. Chronic disturbance was also associated with altered microbial beta diversity for Symbiodiniaceae and bacteria, including changes in community structure for both and increased variation (dispersion) of the Symbiodiniaceae communities. We also found concordance between Symbiodiniaceae and bacterial<i> </i>community structure, when all corals were considered together, and individually for two massive species, <i>Hydnophora microconos</i> and <i>Porites lobata, </i>implying that symbionts<i> </i>and bacteria respond similarly to human disturbance in these species. Finally, we found that the dominant Symbiodiniaceae ancestral lineage in a coral colony was associated with differential abundances of several distinct bacterial taxa. These results suggest that increased beta diversity of Symbiodiniaceae<i> </i>and bacterial communities may be a reliable indicator of stress in the coral microbiome, and that there may be concordant responses to chronic disturbance between these communities at the whole-ecosystem scale.</p>
The influence of human genetic variation on Epstein-Barr virus sequence diversity
<p>This project is the first attempt to apply a "genome-to-genome" approach to investigate the impact of the host genetic pressure on the genome of a member of the <em>Herpesviridae</em> family. Namely, 285 pairs of human and EBV genomes were sequenced and multiple GWASes between human and EBV variations were performed. This repository contains the results of downstream analysis on the pathogen-side. The variant calling data was produced from read alignment using BWA mem using GATK HC, SNVer, VarScan2, BCFtools, freebayes and the intersection of the sets of variation from the first three.</p> <ul> <li><strong>The "covstats" files</strong> contains statistics about the read alignment.</li> <li><strong>The tarball SHCS_EBV_variant_call.tar.gz</strong> contains all compressed VCF files.</li> <li><strong>The tarball SHCS_EBV_variant_matrices_stats.tar.gz</strong> contains all matrices used as traits in the GWASes, as well as a variety of statistics.</li> </ul> <p>The pipeline used to generate this data is publically available here: <a href="https://gitlab.com/ezlab/vir_var_calling/">https://gitlab.com/ezlab/vir_var_calling/</a></p>
Data from: No consistent effects of humans on animal genetic diversity worldwide
Human impacts on genetic diversity are poorly understood yet critical to biodiversity conservation. We used 175,247 COI sequences collected between 1980 and 2016 to assess the global effects of land use and human density on the intraspecific genetic diversity of 17,082 species of birds, fishes, insects, and mammals. Human impacts on mtDNA diversity were taxon and scale-dependent, and were generally weak or non-significant. Spatial analyses identified weak latitudinal diversity gradients as well as negative effects of human density on insect diversity, and negative effects of intensive land use on fish diversity. The observed effects were predominantly associated with species turnover. Time series analyses found nearly an equal number of positive and negative temporal trends in diversity, resulting in no net monotonic trend in diversity over this time period. Our analyses reveal critical data and theory gaps and call for increased efforts to monitor global genetic diversity.
Figure 5 in Small mammal diversity in Semi-deciduous Seasonal Forest of the southernmost Brazilian Pampa: the importance of owl pellets for rapid inventories in human-changing ecosystems
Figure 5. Occlusal view of the lower molars of the Sigmodontine rodents from Tyto furcata pellets from the Municipality of São Lourenço do Sul, State of Rio Grande do Sul, Brazil. (A) = Akodon azarae, UFSC-CF 43-2-2, right m1-m2. (B) = Akodon sp., UFSC-CF 32-4-2, right m1-m3; (C) = Bibimys sp., UFSC-CF 32-5-2, right m1-m3. (D) = Calomys sp., UFSC-CF 32-6-2, right m1-m3. (E) = Holochilus sp., UFSC-CF 43-4-2, left m1-m3. (F) = Lundomys molitor, UFSC-CF 32-9-1, left m1-m3. (G) = Nectomys squamipes, UFSC-CF 32-10-1, right m1-m3. (H) = Oligoryzomys sp., UFSC-CF 32-11-2, right m1-m3. (I) = Oxymycterus sp., UFSC-CF 32-12-2, right m1-m3. (J) = Sooretamys angouya, UFSC-CF 32-13-2, left m1-m2. (K) = Wilfredomys oenax, UFSC-CF 32-14-2, left m1-m3. Scale bars: H = 200 µm; A, B, C, D, G, I, J, K = 500 µm; E, F = 1 mm.
Figure 4 in Small mammal diversity in Semi-deciduous Seasonal Forest of the southernmost Brazilian Pampa: the importance of owl pellets for rapid inventories in human-changing ecosystems
Figure 4. Occlusal view of the upper molars of the Sigmodontine rodents from the Tyto furcata pellets from the Municipality of São Lourenço do Sul, State of Rio Grande do Sul, Brazil. (A) = Akodon azarae, UFSC-CF 43-2-1, left M1-M3. (B) = Akodon sp., UFSC-CF 32-4-1, left M1-M3. (C) = Bibimys sp., UFSC-CF 32-5-1, left M1-M3. (D) = Calomys sp., UFSC-CF 32-6-1, left M1-M3. (E) = Juliomys sp., UFSC-CF 32-7-1, left M1-M3. (F) = Holochilus sp., UFSC-CF 43-4-1, left M1-M3. (G) = Oligoryzomys sp., UFSC-CF 32-11-1, left M1-M3. (H) = Oxymycterus sp., UFSC-CF 32-12-1, left M1-M3. (I) = Sooretamys angouya, UFSC-CF 32-13-1, right M1-M3. (J) = Wilfredomys oenax, UFSC-CF 32-14-1, left M1-M3. Scale bars: C = 200 µm; A, B, D, E, F, G, H, I, J = 500 µm.
Figure 1 in Small mammal diversity in Semi-deciduous Seasonal Forest of the southernmost Brazilian Pampa: the importance of owl pellets for rapid inventories in human-changing ecosystems
Figure 1. Location of the sampling sites of the Tyto furcata pellets at the Municipality of São Lourenço do Sul, State of Rio Grande do Sul, Southern Brazil. BV1 = Boa Vista I; BV2 = Boa Vista II; BOQ = Boqueirão; CGA = Canta Galo; EV1 = Evaristo I; EV2 = Evaristo II; ANT = Picada das Antas; PF1 = Picada Feliz I; PF2 = Picada Feliz II; QV1 = Quevedos I; QV2 = Quevedos II; RES = Reserva. Map modified from MMA (1992).
Figure 3 in Small mammal diversity in Semi-deciduous Seasonal Forest of the southernmost Brazilian Pampa: the importance of owl pellets for rapid inventories in human-changing ecosystems
Figure 3. Chiroptera specimens from the Tyto furcata pellets from the Municipality of São Lourenço do Sul, State of Rio Grande do Sul, Brazil. (A) = ventral view of the skull of Sturnira lilium, UFSC-CF 40-5-1. (B) = labial view of the right dentary of Tadarida brasiliensis, UFSC-CF 42-11-1. Scale bars: 1 mm.
Figure 2 in Small mammal diversity in Semi-deciduous Seasonal Forest of the southernmost Brazilian Pampa: the importance of owl pellets for rapid inventories in human-changing ecosystems
Figure 2. Didelphimorphia specimens from the Tyto furcata pellets from the Municipality of São Lourenço do Sul, State of Rio Grande do Sul, Brazil. (A) = labial view of the left dentary of Cryptonanus guahybae, UFSC-CF 32-2-1. (B) = labial view of the right dentary of Gracilinanus microtarsus, UFSC-CF 42-10-1. Scale bars: 1 mm.
Figure 6 in Small mammal diversity in Semi-deciduous Seasonal Forest of the southernmost Brazilian Pampa: the importance of owl pellets for rapid inventories in human-changing ecosystems
Figure 6. Occlusal view of the upper and lower molars of the Muridae and Caviidae rodents fromTytofurcata pellets from the Municipality of São Lourenço do Sul, State of Rio Grande do Sul, Brazil.(A) = Mus musculus, UFSC-CF 32-15-1, left M1-M3. (B) = Rattus rattus, UFSC-CF 35-9-1, right M1-M3. (C) = Cavia aperea, UFSC-CF 43-8-1, left P4-M3. (D) = M. musculus, UFSC-CF 32-15-2, right m1-m3. (E) = R. rattus, UFSC-CF 35-9-2, right m1-m3. (F) = C. aperea, UFSC-CF 43-8-2, right p4-m3. Scale bars A, D = 200 µm; B, C, E, F = 1 mm.
Source Data and Scripts - Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols
<p>Source data and scripts associated with the manuscript "<em>Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols</em>" (Naas et al. 2024, <em>bioRxiv</em>, <a href="https://doi.org/10.1101/2024.11.15.623576" rel="nofollow">DOI: 10.1101/2024.11.15.623576</a>). Corresponding scripts to reproduce all figures and tables presented in the manuscript are also available on <a href="https://github.com/jn-goe/brain_organoids_four_protocols">https://github.com/jn-goe/brain_organoids_four_protocols</a>.</p> <div> <div> <p>The therein introduced NEST-Score is available as R package on <a href="https://github.com/jn-goe/NESTScore">https://github.com/jn-goe/NESTScore</a>.</p> <p>The interactive Shiny App data explorer is available on <a href="https://vienna-brain-organoid-explorer.vbc.ac.at/">https://vienna-brain-organoid-explorer.vbc.ac.at</a>.</p> </div> </div>
Repeat expansions associated with human disease are present in diverse organisms
<p>These data are associated with the <a href="https://doi.org/10.57844/arcadia-e367-8b55">Repeat expansions associated with human disease are present in diverse organisms</a> pub from Arcadia Science. The code associated with production of these data is available on the GitHub repos linked in the above publication. Version 3 is the correct version of this record.</p> <p>koala_repeat_length_outliers.xlsx and full_koala_results.txt are tables containing results of repeat expansion counting from koala population sequencing data. </p> <p>full_results_20230802_foldseekandblast.csv is a table of the hits with sequence or structural similarity to human repeat expansion proteins. </p> <p>foldseek_aa_fasta.zip contains amino acid fasta files for foldseek hits of dRE proteins.</p> <p>All other tables are described in the NCBI_taxid_to_lineage_and_barchart_tree_plotting.ipynb and profile_repeats.ipynb jupyter notebooks <a title="NCBI_taxid_to_lineage_and_barchart_tree_plotting.ipynb" href="https://github.com/Arcadia-Science/2023-repeats-profiling">here</a>.</p> <p> </p>
Data from: Cryptic diversity of cellulose-degrading gut bacteria in industrialized humans
<p>Humans, like all mammals, depend on the gut microbiome for digestion of cellulose, the main component of plant fiber, but evidence for cellulose fermentation in the human gut is scarce. We have identified ruminococcal species in the gut microbiota of human populations that assemble functional multi-enzymatic cellulosome systems capable of degrading plant cell wall polysaccharides. One of these species, which is strongly associated with humans, likely originated in the ruminant gut and was subsequently transferred to the human gut potentially during domestication, where it underwent diversification and diet-related adaptation through the acquisition of genes from other gut microbes. Collectively, these species are abundant and widespread among ancient humans, hunter-gatherers, and rural populations, but are extremely rare in populations from industrialized societies, suggesting potential disappearance in response to the westernized lifestyle.</p>
Data from: Genetic analysis of red deer (Cervus elaphus) administrative management units in a human-dominated landscape - patterns of genetic diversity, population structure and gene flow
<p><span><span>Red deer (</span><span><em>Cervus elaphus</em></span><span>) throughout central Europe are</span> impacted by different anthropogenic activities including habitat fragmentation, selective hunting, and translocations<span>. This has substantial influences on genetic diversity and the long-term conservation of local populations of this species. Here we use genetic samples from 480 red deer individuals to assess the genetic diversity and differentiation of the 12 administrative management units located in Schleswig Holstein, the northernmost federal state in Germany. </span></span><span><span>We applied multiple analytical approaches and show that the history of local populations (i.e., translocations, culling of individuals outside of designated red deer zones, and anthropogenic infrastructures) has led to comparably low levels of genetic diversity. The mean expected heterozygosity was below 0.6 and we observed on average 4.2 alleles across 12 microsatellite loci. Effective population sizes below the recommended level of 50 were estimated for multiple local populations. </span></span><span><span>Our estimates of genetic structure and gene flow show that red deer in northern Germany are best described as a complex network of asymmetrically connected subpopulations, with high genetic exchange among some local populations and reduced connectivity of others. Genetic diversity was also correlated with population densities of neighboring management units. </span></span></p> <p><span><span>Based on these findings, we suggest that connectivity among existing management units needs to be considered in the practical management of the species, which means that some administrative management units should be managed together, while the effective isolation of other units needs to be mitigated.</span></span></p>
Data and code to reproduce analyses in Heinken et al, "A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites"
<p>This datasets archives the GitHub version found at https://github.com/ThieleLab/CodeBase to reproduce simulations for the article Heinken et al, "A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites", Cell Systems, in press.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.