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15,277 results for “GENETICS”
Figure 1 in Genetic diversity of Peltophorum dubium (Spreng.) Taub. progenies from the states of Minas Gerais and Mato Grosso do Sul, Brazil
Figure 1. Caterpillar plots for random effects inP. dubium progenies for the traits plant height (PH), circumference at breast height (CBH), diameter at breast height (DBH), basal area (AB), and volume (VOL). Dourados/MS, 2018-2019.
Figure 2. Dendrogram representing the genetic dissimilarity among the 64 P in Genetic diversity of Peltophorum dubium (Spreng.) Taub. progenies from the states of Minas Gerais and Mato Grosso do Sul, Brazil
Figure 2. Dendrogram representing the genetic dissimilarity among the 64 P. dubium progenies, obtained by average linkage clustering method and using the Euclidean distance as a measure of dissimilarity. Cophenetic correlation coefficient (0.756). Dourados/ MS, 2018-2019.
Figure 5 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 5. The cloned nucleotide information by Sanger-sequencing.A. The sequences of clone M9-21 with 514bp [The GenBank accession number: MZ417502]. B. The sequences of clone M19-45 with 795bp [The GenBank accession number: MZ484089]. C. The sequences of clone N1-12 with 761bp [The GenBank accession number: MZ417504]. D. The sequences of clone N2-11 with 718bp [The GenBank accession number: MZ417505].
Figure 4 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 4. Clone identification of clones M9-21 (A), M19-45 (B), N1-12 & N2-11 (C) by without (lanes 1) or with (lanes 2) EcoRI digestion. The black arrows represent desired PCR product or specific insert bands in different clones. Lane M indicates the DNA molecular weight marker DL2000 with the fragment size (bp).
Figure 3 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 3. Identification of positive clone M19-45, M9-21 (A), and N1-12, N2-11 (B) by PCR amplification with vector T7/sp6 primers.
Figure 2 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 2. Improved RAPD amplification from DNA samples of D.nobile (listed in Table 1) using different RAPD primers. A. primers M9, M9-21; B. primers M19, M19-45; C. primers N1, N1-12; D. primers N2, N2-11.
Figure 1 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 1. The localities of samples D. nobile cultivars from different regions in China. Spots in black indicate cities and lines in light blue indicate the Yellow River (up) and the Yangtze River (down).
Figure 6 in Identification of SCAR markers for genetic authentication of Dendrobium nobile Lindl.
Figure 6. Development of stable RAPD-SCAR markers for M19-45 (A), M9-21 (B), N1-12 (C), N2-11 (D). Lane 1-10 is D. nobile, 11-21 is D. officinale Kimura et Migo,Lycium barbarum L.,Litchi chinensis Sonn., Ginkgo biloba L., Canarium album (Lour.) Raeusch., Lonicera japonica Thunb., Mentha haplocalyx Briq., Penthorum chinense Pursh, Angelica sinensis, Gardenia jasminoides, Ganoderma lucidum (Leyss. ex Fr.) Karst.. Lane M indicates the DNA molecular weight marker DL2000.
Figure 4 in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 4. UPGMA dendrogram prepared from the genetic distances (Nei and Li, 1979) of the pitahaya populations.
Figure 3 in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 3. Population genetic structure of Pitahaya for each sample analyzed, estimated using the Structure software.
Figure 2. Delta K in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 2. Delta K values obtained from Harvester Structure, calculated as the mean of the probability of K divided by the standard deviation of the probability of K.
Figure 1. Dendrogram showing relationships among 70 in Analysis of the genetic diversity of Dragon fruit based on ISSR markers in Colombia
Figure 1. Dendrogram showing relationships among 70 genotypes of Selenicereus megalanthus, according to the UPGMA analysis using eight ISSR markers.
Figure 4 in PCR-RFLP Based genetic diversity of Plasmodium vivax genotypes in district Mardan, Pakistan
Figure 4. Prevalence of six different sub-allele types of Pvmsp-3β (A1-A3, B1-B2 and C1) based on PCR-RFLP.
Figure 2 in PCR-RFLP Based genetic diversity of Plasmodium vivax genotypes in district Mardan, Pakistan
Figure 2. Prevalence of nine different sub-allele types of Pvmsp- 3α(A1-A4), (B1-B3), C1 and D are the nine different alleles from PCR-RFLP.
Figure 5. A phylogenetic tree was generated using the neighbor-joining method which shows the genetic relationship between C. sphaerospermum 2 in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 5. A phylogenetic tree was generated using the neighbor-joining method which shows the genetic relationship between C. sphaerospermum 2 (as indicated in red circle) and the other C. sphaerospermum isolates deposited in GenBank (NCBI)
Genetic variability and telomeres: Insights from a tropical avian hybrid zone
<p>Telomere lengths and telomere dynamics can correlate with lifespan, behavior, and individual quality. Such relationships have spurred interest in understanding variation in telomere lengths and their dynamics within and between populations. Many studies have identified how environmental processes can influence telomere dynamics, but the role of genetic variation is much less well characterized. To provide a novel perspective on how telomeric variation relates to genetic variability, we longitudinally sampled individuals across a narrow hybrid zone (n = 127 samples), wherein two <em>Manacus </em>species characterized by contrasting genome-wide heterozygosity interbreed. We measured individual (n = 66) and population (n = 3) differences in genome-wide heterozygosity and, among hybrids, amount of genetic admixture using RADseq-generated SNPs. We tested for population differences in telomere lengths and telomere dynamics. We then examined how telomere lengths and telomere dynamics covaried with genome-wide heterozygosity within populations. Hybrid individuals exhibited longer telomeres, on average, than individuals sampled in the adjacent parental populations. No population differences in telomere dynamics were observed. Within the parental population characterized by relatively low heterozygosity, higher genome-wide heterozygosity was associated with shorter telomeres and higher rates of telomere shortening – a pattern that was less apparent in the other populations. All of these relationships were independent of sex, despite the contrasting life histories of male and female manakins. Our study highlights how population comparisons can reveal interrelationships between genetic variation and telomeres, and how naturally occurring hybridization and genome-wide heterozygosity can relate to telomere lengths and telomere dynamics.</p>
Fig. 6 in Worldwide sampling reveals low genetic variability in populations of the freshwater ciliate Paramecium biaurelia (P. aurelia species complex, Ciliophora, Protozoa)
Fig. 6 Map of sampling sit_s of Paramecium biaurelia strains coll_ct_d during fi_ld r_s_arch in th_ Kraków ar_a. a Kraków, "At th_ brickyard" pond, 1 sampling point. b Kraków, Zaczarowana Dorożka Park (pond), 2 sampling points. c Pi_skowa Skała (pond), 1 sampling point. d Kraków,
Fig. 5 in Worldwide sampling reveals low genetic variability in populations of the freshwater ciliate Paramecium biaurelia (P. aurelia species complex, Ciliophora, Protozoa)
Fig. 5 Haplotyp_ n_twork of Paramecium biaurelia construct_d using th_ 123 s_qu_nc_s of ribosomal ITS1- 5.8S-ITS2-5'LSU fragm_nts (a) and 139 of mitochondrial COI fragm_nts (b). Th_ n_twork pr_s_nts a comparison of haplotyp_s obtain_d in th_ Kraków ar_a vs. th_ oth_r localiti_s, wh_r_ mol_cular data for P. biaurelia is availabl_. Black dash_s on particular branch_s r_pr_s_nt nucl_otid_ substitutions b_tw__n particular haplotyp_s. Analys_s w_r_ conduct_d using th_ M_dian Joining m_thod in PopART softwar_ v. 1.7
Fig. 4 in Worldwide sampling reveals low genetic variability in populations of the freshwater ciliate Paramecium biaurelia (P. aurelia species complex, Ciliophora, Protozoa)
Fig. 4 Haplotyp_ n_twork of Paramecium biaurelia construct_d using th_ 123 s_qu_nc_s of ribosomal ITS1- 5.8S-ITS2-5'LSU fragm_nts (a) and 139 of mitochondrial COI fragm_nts (b). Th_ n_twork pr_s_nts r_ciprocal r_lationships b_tw__n, and th_ origin of P. biaurelia haplotyp_s id_ntifi_d in curr_nt study. Black dash_s on particular branch_s r_pr_s_nt nucl_otid_ substitutions b_tw__n particular haplotyp_s. Analys_s w_r_ conduct_d using th_ M_dian Joining m_thod in PopART softwar_ v. 1.7
Fig. 2 in Evaluation of field dispersal and survival capacity of the genetic sexing strain Tapachula-7 of Anastrepha ludens (Diptera: Tephritidae)
Fig. 2. General displacement of Anastrepha ludens SMR strain (solid line) and Tap-7 strain (broken line) in a Cartesian plane.
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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.
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.