Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
20
datasets available to search
ShareScore release 0.9.0
Dataset results
20 results for “chloroplast genome sequences”
Chloroplast genome sequencing reads from snow gum
<p>Tutorial data for chloroplast genome assembly: fastq reads from illumina and nanopore sequencing for the snow gum, <em>Eucalyptus pauciflora</em>.</p> <p>Data from: Wang, W., Schalamun, M., Morales-Suarez, A. et al. Assembly of chloroplast genomes with long- and short-read data: a comparison of approaches using Eucalyptus pauciflora as a test case. BMC Genomics 19, 977 (2018) doi:10.1186/s12864-018-5348-8</p> <p>Data hosted at NCBI under accession numbers: illumina (SRR7153063) and nanopore (SRR7153095). Additional illumina file SRR7153071 not used here. </p> <p>This is how the files have been changed from the original datasets: </p> <p>Using the Galaxy platform (usegalaxy.org): </p> <ul> <li> <p>Each dataset was separately mapped to the NCBI Reference Sequence for <em>Eucalyptus pauciflora </em>chloroplast NC_039597.1, using BWA-MEM. </p> </li> <li> <p>Unmapped reads were filtered out using a SAMtools flag. </p> </li> <li> <p>Bam files were converted to fastq files.</p> </li> <li> <p>Each fastq file was then reduced in size:</p> </li> <li> <p>snow-gum-illumina-cp-reduced: has the first 62,500 reads only. Note that original pairing of reads has not been preserved so consider these to be unpaired reads for this tutorial.</p> </li> <li> <p>snow-gum-nanopore-cp-reduced: has only reads that are longer than 90,000 bp.</p> </li> </ul>
The alignments of chloroplast genome sequences and nuclear ribosomal DNA fragments of six oak species sampled in the hot-dry valley of the Jinsha River, southwestern China
<p>Both chloroplast (cp) genome sequences and nuclear ribosomal (nr) DNA were assembled using GetOrganelle v.1.7.6.1 for 18 oak trees sampled in the Panzhihua Cycad National Nature Reserve, Sichuan Province, China. These trees belong to six oak species, including Quercus cocciferoides, Q. dolicholepis, Q. franchetii, Q. griffithii, Q. longispica, and Q. variabilis. We used PhyloSuite v.1.1.152 to extract coding sequences (CDSs), tRNA genes, rRNA genes, introns, and intergenic spacers (IGSs) of the 18 oak cp genomes. These sequences were aligned separately using MAFFT v.7.3.13 and manually adjusted with BioEdit v.7.2.5. Length variations in mononucleotide repeats were excluded and inversions were replaced with their reverse complements because of their tendency for homoplasy. Other indels were coded as binary characters according to the simple gap coding method using GapCoder. Separate assignments were concatenated according to their respective positions in the cp genome to obtain the alignments of LSC, SSC, IRb, and the whole cp genome.</p>
Supplementary Materials from the article Characterization and molecular evolution analysis of Periploca forrestii inferred from its complete chloroplast genome sequence
<p>Table S1. Base composition of chloroplast genome in <em>P. forrestii</em>, Table S2. The lengths of introns and exons for the splitting genes, Table S3. The GC content of the codons from <em>P. forrestii </em>chloroplast genome, Table S4. Preferred codons in chloroplast genome of <em>P. forrestii</em>, Table S5. Long repeat sequences in the <em>P. forrestii </em>chloroplast genome, Figure S1. Codon bias analysis of P. forrestii chloroplast genome. (A) Neutrality plot analysis; (B) Analysis of PR2 bias plot; (C) Analysis on ENC and GC3 relationship.</p>
The data of complete chloroplast genome sequence of Sorbus amabilis (Rosaceae) in China
<p>This dataset includes the complete chloroplast genome of <em>Sorbus amabilis </em> in China.</p>
Data from: Assemblage Accumulation Curves: A framework for resolving species accumulation in biological communities using chloroplast genome sequences
The timing and tempo of the processes involved in community assembly are of substantial concern to community ecologists and conservation managers. The fossil record is a valuable source of data for studying past changes in community composition, but it is not always detailed enough to allow the process of community assembly to be resolved at regional or site scales while tracing the trajectories of known species with associated known traits. We present a three‐step framework for studying present‐day species accumulation through time: DNA sampling from multiple individuals from multiple species within a community; estimates of coalescence times for each species using molecular dating methods; and plotting the accumulation of present‐day species through time using the inferred population ages. Our approach is illustrated using whole chloroplast genomes from plants from three rainforest communities in eastern Australia. Expected times to coalescence for multiple species in each community were inferred from pooled high‐throughput sequence libraries. Local assemblage accumulation curves for each community were constructed. We also explored the variation in assemblage accumulation curves of species with different functional traits. Models of equilibrium species richness informed our null hypothesis and largely explained the shape of the assemblage accumulation curves and indicated that the complexities of the accumulation process should be explored with additional parameters, for example allowing species classes with different extinction rates. The assemblage accumulation curves for the study sites showed evidence of recent population expansions within each of the communities. This signal of recent accumulation is consistent with the increase in suitable rainforest habitat that followed the Last Glacial Maximum. Our method of constructing assemblage accumulation curves provides a simple approach for visualizing species‐accumulation data. It can be used to test hypotheses such as the relative survival potential of species‐specific ecological attributes. Although our example used single‐nucleotide polymorphisms derived from whole‐chloroplast sequencing, this framework can be applied to mitochondrial genomes and to communities of other organisms.
Comparative Analysis of Complete Chloroplast Genomes and Multiple DNA Sequences Reveals Interspecific Relationships of C. bretschneideri and Related Species in China
<p><strong> ITS, and <em>LEAFY</em> intron 1 sequencing of 36 Crataegus accessions.</strong></p>
Rhizophora complete chloroplast genome sequences
<p>Historical processes of long-distance migration and ocean-wide expansion feature the global biogeographic pattern of <i>Rhizophora</i> species. Throughout the Indian Ocean, <i>R. stylosa</i> and <i>R. mucronata</i> appear as a young phylogenetic group with expansion of <i>R. mucronata</i> towards the Western Indian Ocean (WIO) driven by the South Equatorial Current. Nuclear microsatellites revealed genetic patterns and breaks, however, estimating propagule dispersal routes requires maternally inherited cytoplasmic markers. Here, we examine the phylogeography of 21 <i>R. mucronata</i> provenances across a >4,200 km coastal stretch in the WIO using <i>R. stylosa</i> as outgroup. Full length chloroplast genome (164,474 bp) and nuclear ribosomal RNA cistron (8,033 bp) sequences were assembled. Boundaries, junction point, sequence orientation and stretch between LSC/IRb/SSC/IRa/LSC showed no differences with the <i>R. stylosa</i> chloroplast genome. A total of 58 mutations in <i>R. mucronata</i> encompassing transitions/transversions, insertion-deletions and mononucleotide repeats revealed three major haplogroups. Haplonetwork, Bayesian ML and Approximate Bayesian Computation (ABC) analyses supported discrete historical migration events. An ancient haplogroup A in the Seychelles and eastern Madagascar was as divergent from other <i>R. mucronata</i> haplogroups as it was from <i>R. stylosa</i>. A star-like haplonetwork referred to recent range expansion of haplogroup B from northern Madagascar towards the African mainland coastline, including a single variant spanning >1,800 km across the Mozambique Channel Area. Populations south of Delagoa Bight contained haplogroup C and originate from a unique bottleneck dispersal event. Divergence estimates of pre- and post-Last Glacial Maximum illustrated a recent emergence of WIO <i>Rhizophora </i>mangroves compared to other oceans. Connectivity patterns could be aligned with directionality of major ocean currents. Madagascar and the Seychelles each harbored haplogroups A and B, albeit among spatially separated populations, explained from a different migration era. Likewise, the Aldabra Atoll harbored spatially distinct haplotypes. Nuclear ribosomal cistron (8,033bp) variants corresponded to haplogroups and confirmed admixtures in the Seychelles and Aldabra. These findings shed new light on the origins and dispersal routes of <i>R. mucronata</i> lineages that have shaped their contemporary populations in large regions of the WIO, which may be important information for defining marine conservation units, both at ocean scale and at level of small islands.</p>
Data from: Assemblage Accumulation Curves: A framework for resolving species accumulation in biological communities using chloroplast genome sequences
Open the record for dataset details and reuse information.
Genome-wide RAD sequencing resolves the evolutionary history of serrate leaf Juniperus and reveals discordance with chloroplast phylogeny
Open the record for dataset details and reuse information.
Rhizophora complete chloroplast genome sequences
Open the record for dataset details and reuse information.
Figure 3 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figure 3 Undated 18S–26S nuclear DNA repeat region BEAST 2 phylogeny of Pennantia, under the Birth-Death model. The tree was rooted to make P. cunninghamii sister to the other species of Pennantia, in accordance with the chloroplast DNA tree and the ITS tree of Keeling et al. (2004). Node posterior probability is shown next to the corresponding node. The sequences downloaded from GenBank have their accession number in round brackets; the others were generated from the samples used in this study.
Supplementary material 2 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
BEAST2 and RAxML files
Figure 2 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figure 2 Dated chloroplast DNA BEAST 2 phylogeny of Pennantia, under the Birth-Death model. Mean node age and 95% HPD (in My) is given in the table embedded in the figure under the corresponding letter code. 95% HPD is also represented by blue bars. All node posterior probabilities are equal to 1 except if indicated otherwise. The calibrated nodes (see text) are indicated by red dots.
Supplementary material 1 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figs S1–S5; Tables S1–S3
Figure 1 from: Maurin KJL (2020) A dated phylogeny of the genus Pennantia (Pennantiaceae) based on whole chloroplast genome and nuclear ribosomal 18S–26S repeat region sequences. PhytoKeys 155: 15-32. https://doi.org/10.3897/phytokeys.155.53460
Figure 1 General distribution of the four Pennantia species. TKI = Three Kings Islands. Generated in QGIS 3.0.1 from Google Satellite data obtained through the XYZ Tiles tool (https://mt1.google.com/vt/lyrs=s&x={x}&y={y}&z={z}).
Data from: Congruent deep relationships in the grape family (Vitaceae) based on sequences of chloroplast genomes and mitochondrial genes via genome skimming
Vitaceae is well-known for having one of the most economically important fruits, i.e., the grape (Vitis vinifera). The deep phylogeny of the grape family was not resolved until a recent phylogenomic analysis of 417 nuclear genes from transcriptome data. However, it has been reported extensively that topologies based on nuclear and organellar genes may be incongruent due to differences in their evolutionary histories. Therefore, it is important to reconstruct a backbone phylogeny of the grape family using plastomes and mitochondrial genes. In this study, next-generation sequencing data sets of 27 species were obtained using genome skimming with total DNAs from silica-gel preserved tissue samples on an Illumina HiSeq 2500 instrument. Plastomes were assembled using the combination of de novo and reference genome (of V. vinifera) methods. Sixteen mitochondrial genes were also obtained via genome skimming using the reference genome of V. vinifera. Extensive phylogenetic analyses were performed using maximum likelihood and Bayesian methods. The topology based on either plastome data or mitochondrial genes is congruent with the one using hundreds of nuclear genes, indicating that the grape family did not exhibit significant reticulation at the deep level. The results showcase the power of genome skimming in capturing extensive phylogenetic data: especially from chloroplast and mitochondrial DNAs.
Supplementary material 1 from: Li Z, Huang Z, Wan X, Yu J, Dong H, Zhang J, Zhang C, Wang S (2023) Complete chloroplast genome sequence of Rhododendron mariesii and comparative genomics of related species in the family Ericaeae. Comparative Cytogenetics 17: 163-180. https://doi.org/10.3897/compcytogen.17.101427
Taxonomic and accession information on cp genomes downloaded from NCBI database
Data from: Congruent deep relationships in the grape family (Vitaceae) based on sequences of chloroplast genomes and mitochondrial genes via genome skimming
Open the record for dataset details and reuse information.
Chloroplast genome sequencing reads from sweet potato
<p>Tutorial data for chloroplast genome assembly: fastq reads from illumina and nanopore sequencing for the sweet potato.</p> <p>Data from: Zhou C, Duarte T, Silvestre R et al. 2018 (https://doi.org/10.12688/gatesopenres.12856.1), hosted at EBI ENA under accession numbers: illumina (SRR6828568) and nanopore (SRR6828567).</p> <p>This is how the files have been changed from the original datasets: </p> <p>illumina-reduced: has the first 62,500 reads only</p> <p>illumina-tiny: has the first 12,500 reads only</p> <p>nanopore-reduced: has the first 2,000 reads only</p> <p>nanopore-tiny: has the first 250 reads only</p> <p> </p>
The data of complete chloroplast genome sequence of Tilia miqueliana (Malvaceae) in China
<p>This dataset includes the complete chloroplast genome of Tilia miqueliana (Malvaceae) in China.</p>
ScienceDex guides
Understand access before you commit
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.