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203 results for “Fish Evolution”
Modulation of bioelectric cues in the evolution of flying fishes [Data set]
<p>Assembled reference contigs for protein-coding exons and conserved non-coding regions from targeted sequence enrichment of beloniform fishes. </p> <p>Current citation: Daane JM, Blum N, Lanni J, Boldt H, Iovine MK, Johnson SL, Lovejoy NR, and MP Harris. (2021). Novel regulators of growth identified in the evolution of fin proportion in flying fish. <em>bioRxiv. </em>doi: 10.1101/2021.03.05.434157</p> <p>-contigs.tar.gz contains the assembled contigs for each species. Each contig represents a targeted region with the addition of flanking DNA sequence</p> <p>-cnes.tar.gz contains the targeted conserved non-coding regions isolated from the larger contigs in contigs.tar.gz</p> <p>-exons.tar.gz contains the targeted protein coding exons isolated from the larger contigs in contigs.tar.gz</p> <p>-translated_exons.tar.gz contains the translated protein coding exons from exons.tar.gz</p> <p>-Beloniformes.tre is the species tree </p> <p>-medaka_cne_great.txt contains the associations between the assembled CNEs and neighboring protein-coding genes based on the GREAT approach </p>
Data and custom codes from "Rapid evolution in salmon life-history induced by direct and indirect effects of fishing"
<p>Data and custom codes from Czorlich, Y., Aykanat, T., Erkinaro, J., Orell, P. & Primmer, C.R. (2021) <em>Rapid evolution in salmon life-history induced by direct and indirect effects of fishing. </em>Science.</p> <p><strong>Codes:</strong></p> <p>The R file "Fishing_effort_parallel.R" was used to estimate fishing effort/intensity (beta in equation 8) given the length distribution, the gear-specific catchability and harvest rate</p> <p>"Fishing_selection_estimate.R" was used to estimate fishery-induced selection at <em>vgll3.</em></p> <p><strong>Datasets:</strong></p> <p>Genetic_phenotypic_data.xlsx: Genetic and phenotypic data about salmon from the Teno mainstem population</p> <p>sonar_data.xlsx: Number of salmon per length class entering the river in 2018 and 2019. The length classes of salmon caught in those years by one of the fishing methods are also included</p> <p>annual_catch_data.xlsx: Total mass (kg) of salmon caught by each fishing method between 1975 to 2014.</p> <p>Environmental_data.xlsx: Data about Barents Sea temperature, biomass of key species, fishing data</p> <p>individual_weight_salmon_catches.xlsx: Individual weight of salmon caught with different fishing gears in the last decades</p> <p><strong>Data sources:</strong></p> <p>- Genetic data (Tenojoki population, random sampling): From Czorlich et al. 2018, https://datadryad.org/stash/dataset/doi:10.5061/dryad.7hm4708</p> <p>- Data about krill biomass (1980 – 2013) were taken from (<em>1</em>, <em>2</em>).</p> <p>- Capelin biomass estimated from acoustic survey and the landed capelin catches were derived from (<em>3</em>) for 1973 – 2013.</p> <p>- Herring biomass data were retrieved from (<em>4</em>) for the 1973-1998 period. Herring biomass was calculated from the number of 1-2 year old herring and the mean weight per age as reported in (<em>3</em>) for 1988 – 2013.</p> <p>- The annual biomass of cod (a predator of forage fish) was derived from VPA analyses ((<em>5</em>), table 3.24). Landed cod biomass was also taken from (<em>5</em>).</p> <p>- An index for mesozooplankton (a forage fish food source) corresponding to the sum of <em>Calanus</em> biomass indices from different parts of the Barents Sea was used (<em>6</em>).</p> <p>- The annual sea temperature in the Kola section of the Barents Sea measured in the upper 200 meters was from <a href="http://www.pinro.vniro.ru/">pinro.vniro.ru</a></p> <p>- The total number of nets used to catch salmon in the Finnmark coastal region was calculated for each year using data from (7)</p> <p>- Other data were generated for this study, please check the Material and Methods. </p> <p><em>References:</em></p> <p>1. E. Eriksen, P. Dalpadado, Long-term changes in Krill biomass and distribution in the Barents Sea: Are the changes mainly related to capelin stock size and temperature conditions? <em>Polar Biology</em>. <strong>34</strong>, 1399–1409 (2011).</p> <p>2. ICES, “Report of the Working Group on the Integrated Assessments of the Barents Sea. ICES CM 2017/SSGIEA:04. 186 pp.” (2017).</p> <p>3. ICES, “Report of the Arctic Fisheries Working Group (AFWG). ICES CM 2015/ACOM:05. 639 pp.” (2015).</p> <p>4. R. Toresen, O. J. Østvedt, Variation in abundance of Norwegian spring-spawning herring (Clupea harengus, Clupeidae) throughout the 20th century and the influence of climatic fluctuations. <em>Fish and Fisheries</em>. <strong>85</strong>, 385–391 (2000).</p> <p>5. ICES, “Report of the Arctic Fisheries Working Group (AFWG). ICES CM 2016/ACOM:06. 621 pp.” (2016).</p> <p>6. L. C. Stige et al., Spatiotemporal statistical analyses reveal predator-driven zooplankton fluctuations in the Barents Sea. <em>Progress in Oceanography</em>. <strong>120</strong>, 243–253 (2014).</p> <p>7. E. Niemelä, T. Kalske, E. Hassinen, “Numbers of fishing gears used in Kolarctic salmon project area, numbers of allowed sites for salmon fishing and numbers of salmon fishermen in Finnmark; development until the year 2013” (2013).</p>
The impact of paleoclimatic changes on body size evolution in marine fishes
<p class="MsoNormal">Body size is an important species trait, correlating with lifespan, fecundity, and other ecological factors. Over Earth's geological history, climate shifts have occurred, potentially shaping body size evolution in many clades. General rules attempting to summarize body size evolution include Bergmann's rule, which states that species grow to larger sizes in cooler environments and smaller sizes in warmer environments; and Cope's rule, which poses that lineages tend to increase in size over evolutionary time. Tetraodontiform fishes (including pufferfishes, boxfishes, and ocean sunfishes) provide an extraordinary clade to test these rules in ectotherms owing to their exemplary fossil record and the great disparity in body size observed among extant and fossil species. We examined Bergmann's and Cope's rules in this group by combining phylogenomic data (1,103 exon loci from 185 extant species) with 210 anatomical characters coded from both fossil and extant species. We aggregated data layers on paleoclimate and body size from the species examined, then inferred a set of time-calibrated phylogenies using tip-dating approaches for use in downstream comparative analyses of body size evolution using models that incorporate paleoclimatic information. We find strong support for a temperature-driven model in which increasing body size over time is correlated with decreasing oceanic temperatures. On average, extant tetraodontiforms are 2–3 times larger than their fossil counterparts, which otherwise evolved during periods of warmer ocean temperatures. These results provide strong support for both Bergmann's and Cope's rules, trends that are less studied in marine fishes compared to terrestrial vertebrates and marine invertebrates.</p>
Swordtail fish hybrids reveal that genome evolution is surprisingly predictable after initial hybridization
<p>Over the past two decades, biologists have come to appreciate that hybridization, or genetic exchange between distinct lineages, is remarkably common – not just in particular lineages but in taxonomic groups across the tree of life. As a result, the genomes of many modern species harbor regions inherited from related species. This observation has raised fundamental questions about the degree to which the genomic outcomes of hybridization are repeatable and the degree to which natural selection drives such repeatability. However, a lack of appropriate systems to answer these questions has limited empirical progress in this area. Here, we leverage independently formed hybrid populations between the swordtail fish <em>Xiphophorus birchmanni </em>and <em>X. cortezi </em>to address this fundamental question. We find that local ancestry in one hybrid population is remarkably predictive of local ancestry in another, demographically independent hybrid population. Applying newly developed methods, we can attribute much of this repeatability to strong selection in the earliest generations after initial hybridization. We complement these analyses with time-series data that demonstrates that ancestry at regions under selection has remained stable over the past ~40 generations of evolution. Finally, we compare our results to the well-studied <em>X. birchmanni×X. malinche </em>hybrid populations and conclude that deeper evolutionary divergence has resulted in stronger selection and higher repeatability in patterns of local ancestry in hybrids between <em>X. birchmanni </em>and <em>X. cortezi</em>.</p>
FIGURE 3 in Does soil color affect fish evolution? Differences in color change rate between lineages of the sailfin tetra
FIGURE 3 | A. Representation of the stock tank, with sandy bottom. B. Representation of experimental tank showing the compartments, leaf litter bottom and light bulb. Inner panes: pictures of fish with bright coloration (in stock tank) and dark coloration (after ten minutes of exposure to leaf litter bottom).
FIGURE 2 in Does soil color affect fish evolution? Differences in color change rate between lineages of the sailfin tetra
FIGURE 2 | Map showing the geographical position of the four populations of Crenuchus spilurus used in this study. Shapes represent the two main lineages that each population represents; squares for the Negro lineage and circles for the Amazonas lineage. Classification of lineages follows Pires et al. (2018).
Fig. 2 in Chromosome evolution in fishes: a new challenging proposal from Neotropical species
Fig. 2. Scatter-plot of (a, c) diploid number (2n), and (b, d) pg of DNA per haploid nucleus (C-Value), against the phylogenetic position of Actinopterygii families presented by Nelson (2006). Data include all available species (a, b) or exclude possible polyploidy species (c, d). Ellipses with 95% confidence are used as a correlation indicator.
Fig. 1 in Chromosome evolution in fishes: a new challenging proposal from Neotropical species
Fig. 1. Scatter-plot of (a) diploid number (2n) and (b) fundamental number (FN), against the phylogenetic position of Actinopterygii families presented by Nelson (2006) for 103 fish species. Ellipses with 95% confidence are used as a correlation indicator.
Fig. 11 in Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: an example of faunal evolution associated with a divergent continental margin
Fig. 11. (a) The main axes of Quaternary tectonics in Brazil (gray lines) (according to Saadi, 1993) and areas of coincident distributional rages of several species in both isolated coastal rivers and adjacent drainages. (b) The northeastern margin of Brazil, including the Parnaíba, São Francisco and adjacent coastal rivers (c) The Southern most Brazil, encompassing the Uruguay and surroundings coastal rivers as well as the headwaters of the Paranapanema, Ivaí, Iguacú and Ribeira de Iguape. (d) The area encompassed by the CRSB, in southeastern Brazil, including the coastal rivers and the adjacent upper Tietê and upper Iguaçu.
Fig. 4 in Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: an example of faunal evolution associated with a divergent continental margin
Fig. 4. Geographic location of the Brazilian Atlantic continental margin and of the coastal drainages of eastern Brazil (shaded area) and areas showed in figures 6, 7 and 8 (modified from Hearn et al., 2000).
Fig. 9 in Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: an example of faunal evolution associated with a divergent continental margin
Fig. 9. Cladograms of taxa and areas showing the sister-group relationships included in Pattern A. a) Catfishes of the family Trichomycteridae. b) Catfishes of the family Doradidae. The degree of inclusiveness of this pattern suggests the most ancient cladogenetic event that is still recognized in respect to the ichthyofauna of the Brazilian coastal rivers.
Fig. 7 in Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: an example of faunal evolution associated with a divergent continental margin
Fig. 7. (a) Map of northeastern segment of Southeastern Brazilian coast showing the complex system of Pre-Cambrian and Mesozoic continental rifts controlling drainage and topography. (b) Detail of the straight course of the rio Paraíba do Sul Rift Valley produced from a digital elevation model by radar interferometry (NASA, The Shuttle Radar Topography Mission).
Fig. 3 in Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: an example of faunal evolution associated with a divergent continental margin
Fig. 3. Rivers and uplifts of Atlantic South America. A) break-up uplifts (megadomes) and associated principal rifts. Megadomes: Guyana/Guinea (1), NE Brazil/Niger (2), Mantiqueira/Angola (3), Uruguay/SW Africa (4), Somuncurá (5) and Deseado (6). Break-up rifts: Tacutu (I), Foz do Amazonas (II), Reconcavo Tucano-Jatobá (III) and Taubaté (IV). B) detail of the uplift from the Southeastern Brazil (from Cox, 1989 and Potter, 1997).
Fig. 2 in Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: an example of faunal evolution associated with a divergent continental margin
Fig. 2. The South American Plate and its major tectono-sedimentary domains (from Milani & Thomaz-Filho, 2000).
Fig. 3 in A remarkable sand-dwelling fish assemblage from central Amazonia, with comments on the evolution of psammophily in South American freshwater fishes
Fig. 3. The sit-and-wait foraging posture of "Imparfinis" pristos in dorsal view. Note translucent body and commashaped pupil.
Fig. 2 in A remarkable sand-dwelling fish assemblage from central Amazonia, with comments on the evolution of psammophily in South American freshwater fishes
Fig. 2. The sit-and-wait foraging posture of Mastiglanis asopos in posterior view. Note very long barbels and filamentous rays of pectoral fins spread in a drift trap-like device, as well as the alignment of mentonian barbels and pectoral filaments.
Fig. 1 in A remarkable sand-dwelling fish assemblage from central Amazonia, with comments on the evolution of psammophily in South American freshwater fishes
Fig. 1. Two species indicative of the morphological and behavioural variation found among the sand-dwelling fish assemblage in an Amazonian streamlet: a, the diurnally active Characidium cf. pteroides in its characteristic sit-and-wait posture while foraging for bottom-dwelling prey; b, the nocturnally active Gymnorhamphichthys rondoni in its typical headdown posture while actively searching for interstitial prey.
Fig. 1 in Cytogenetical analyses in three fish species of the genus Pimelodus (Siluriformes: Pimelodidae) from rio São Francisco: considerations about the karyotypical evolution in the genus
Fig. 1. Karyotypes of: a) P. fur, b) P. maculatus, and c) Pimelodus sp. arranged from Giemsa-stained. Ag-NOR-bearing pair is framed.
Fig. 2 in Cytogenetical analyses in three fish species of the genus Pimelodus (Siluriformes: Pimelodidae) from rio São Francisco: considerations about the karyotypical evolution in the genus
Fig. 2. Somatic chromosome metaphases of P. fur (a, d), P. maculatus (b, e) and Pimelodus sp. (c, f) submitted to: C banding (a, b, c) and staining with CMA (d, e, f). The major arrows indicate the NOR-bearing pairs. NOR association (b, f) and NOR size 3 heteromorphism (a) are exemplified. The arrows indicate positive chromosome regions corresponding with heterochromatin sites after treatment with fluorochrome and the arrowheads indicate a pair of metacentric chromosomes with both telomeres heterochromatic.
Visual opsin gene expression evolution in the adaptive radiation of cichlid fishes of Lake Tanganyika
<p>Tuning the visual sensory system to the ambient light is essential for survival in many animal species. This is often achieved through duplication, functional diversification, and/or differential expression of visual opsin genes. Here, we examined 753 new retinal transcriptomes from 112 species of cichlid fishes from Lake Tanganyika to unravel adaptive changes in gene expression at the macro-evolutionary and ecosystem level of one of the largest vertebrate adaptive radiations. We found that, across the radiation, all seven cone opsins – but not the rhodopsin – rank among the most differentially expressed genes in the retina, together with other vision-, circadian-rhythm-, and haemoglobin-related genes. We propose two new visual palettes characteristic of very shallow- and deep-water living species, respectively, and show that visual system adaptations along two major ecological axes, macro-habitat and diet, occur primarily via gene expression variation in a subset of cone opsin genes.</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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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.
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