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Takifugu

Takifugu is a genus of pufferfish found primarily in the waters of East Asia.
These small, round fish are known for their distinctive appearance and the potent neurotoxin tetrodotoxin found in their internal organs.
Takifugu have been the subject of extensive scientific research, with studies examining their unique biology, behavior, and potential medical applications.
PubCompare.ai offers an innovative AI-powered platform to help researchers and medical professionals navigate the wealth of Takifugu-related literature, locating the most effective protocols and products with ease.
Throught intelligent comparison of scientific publications, preprints, and patents, this platform drives reproducibilty and accuracy in Takifugu research.

Most cited protocols related to «Takifugu»

1
Predicting Mammalian and Fish miRNA Sequences
Cited 128 times
Mature human and mouse miRNA sequences were obtained from the RFAM miRNA registry (Griffiths-Jones 2004 (link)). To cover cases of incomplete data, any mouse miRNA sequence not (yet) described in humans was assumed to be present in human, with the same sequence, and vice versa. Similarly, all mouse miRNAs were assumed to be identical and present in the rat genome. These assumptions are reasonable as sequence identity for known orthologous pairs in human and mouse is, on average, 98% (with 110 out of 146 orthologous sequences being identical). In total, 218 mammalian miRNAs were used. For human target searches, 162 native miRNA sequences were available plus 17 mouse and 39 rat miRNA sequences; for mouse, 191 native, 14 human, and 13 rat sequences; and for rat, 45 native, 159 mouse, and 14 human miRNA sequences.
Mature miRNA sequences for zebrafish and fugu were predicted starting from known human and mouse miRNA precursor sequences (Ambros et al. 2003a (link)). Each precursor sequence was used, in a scan against the zebrafish supercontigs (release 18.2.1) using NCBI BLASTN (version 2.2.6; E-value cutoff, 2.0) (Altschul et al. 1990 (link)), to identify a sequence segment containing the potential zebrafish miRNA. The mammalian and fish segments were then realigned using a global alignment protocol (ALIGN in the FASTA package, version 2u65; Pearson and Lipman 1988 (link)). After testing the potential fish miRNA precursors for foldback structures (Zuker 2003 (link)), the final set of 225 predicted zebrafish miRNAs was selected. The same set of sequences was used for fugu.
John B., Enright A.J., Aravin A., Tuschl T., Sander C, & Marks D.S. (2004). Human MicroRNA Targets. PLoS Biology, 2(11), e363.
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Publication 2004
Fishes Genome Homo sapiens Mammals Mice, House MicroRNAs Radionuclide Imaging Takifugu Zebrafish
2
Expanded Conservation Track for Human Genome
Cited 26 times
UCSC released a new Conservation (13 (link)) annotation track on the March 2006 (Build 36, hg18) human genome in June 2007. This track displays multiz (14 (link)) multiple alignments of 27 vertebrate species to the human genome, along with measurements of evolutionary conservation across all 28 species and a separate measurement of conservation across the placental mammal subset of species (18 organisms). Included in the track are 5 new high-quality assemblies—horse, platypus, lizard, stickleback and medaka; 6 new low-coverage mammalian genomes—bushbaby, tree shrew, guinea pig, hedgehog, common shrew and cat; 6 updated assemblies—chimp, cow, chicken, frog, fugu and zebrafish; and 10 assemblies included in the previous version of the Conservation track—rhesus, mouse, rat, rabbit, dog, armadillo, elephant, tenrec, opossum and tetraodon. In addition to the expanded species list, the new Conservation track has been enhanced to include additional filtering of pairwise alignments for each species to reduce paralogous alignments and information about the quality of aligning species sequence included in the multiple alignments downloads. A similar Conservation annotation of at least 30 species is scheduled for release on the July 2007 (Build 37, mm9) mouse assembly in the last quarter of 2007.
Karolchik D., Kuhn R.M., Baertsch R., Barber G.P., Clawson H., Diekhans M., Giardine B., Harte R.A., Hinrichs A.S., Hsu F., Kober K.M., Miller W., Pedersen J.S., Pohl A., Raney B.J., Rhead B., Rosenbloom K.R., Smith K.E., Stanke M., Thakkapallayil A., Trumbower H., Wang T., Zweig A.S., Haussler D, & Kent W.J. (2007). The UCSC Genome Browser Database: 2008 update. Nucleic Acids Research, 36(Database issue), D773-D779.
Publication 2007
Armadillos Biological Evolution Bush Babies Cavia Chickens Didelphidae Elephants Equus caballus Erinaceidae Eutheria Genome Genome, Human Lizards Macaca mulatta Mammals Mice, House Oryziinae Pan troglodytes Platypus, Duckbilled Rabbits Rana Shrews Sticklebacks Strains Takifugu Tenrec Tupaiidae Vertebrates Zebrafish
3
Comparative Analysis of Trout Genome Duplication
Cited 22 times
As a starting point for comparative genome analyses, we integrated predicted trout genes in vertebrate gene families based on Ensembl version 66 (February 2012)50 (link). The 46,585 predicted trout proteins were compared against 13,264 gene families from 14 representative vertebrate species comprising mammals, birds and fish (Supplementary Fig. 6). Trout genes were included in 8,739 vertebrate gene trees (Supplementary Table 7). By comparison, other genes from other vertebrate genomes are included in 7,131 (takifugu) to 9,453 (Human) gene families, suggesting that annotated trout genes cover the vast majority of vertebrate gene families. A dedicated Genomicus server ( http://www.genomicus.biologie.ens.fr/genomicus-trout-01.01/) provides access to trout genes and their phylogenetic trees, as well as syntenic relationships with other genomes (Supplementary Fig. 7).
DCS blocks are defined as runs of genes in a non-salmonid (that is, non-duplicated by the Ss4R event) genome that are distributed on two different chromosomes (or non-anchored scaffolds) in the rainbow trout genome; the exact gene order does not need to be conserved. We systematically compared the gene locations in rainbow trout with those of medaka, stickleback, tetraodon and takifugu using ad-hoc scripts to identify pairs of regions in the rainbow trout genome that are syntenic with single regions in non-salmonid species, and that correspond to DCS blocks. Pairs of paralogous trout genes on two different chromosomes (or non-anchored scaffolds) that belong to a DCS block are most likely duplicates originating from the Ss4R WGD event and are called ohnologues; there were 6,733 pairs of ohnologues. Genes that are inserted in a DCS block based on synteny with a non-salmonid species, but have no paralogous gene on the other chromosome or scaffold, are most likely former Ss4R duplicates in which one of the duplicated genes was lost, and are called singletons. Each pair of duplicated regions within a DCS block is descended from a single ancestral region in the pre-duplication genome. The organization of these ancestral regions into an ancestral chromosome was deduced from the synteny relationships with non-salmonid genomes using a clustering method implemented in Walktrap51 . The Ts3R-duplicated regions in the ancestral karyotype were obtained by orthology with the Ts3R-duplicated regions in the medaka genome, which were themselves deduced from the DCS blocks between the medaka and chicken genomes obtained as described above. DCS blocks can be very short, as they are dependent on assembly continuity and scaffold anchoring. Fine-scale analysis of duplicated regions and genes was restricted to 915 scaffolds that could be paired into 569 DCS blocks for at least part of their lengths, and that share at least 4 ohnologous genes. The longest scaffold in these DCS blocks is 5,466,130 bp long and the shortest is 25,207 bp long. These 915 scaffolds contain a total of 171 miRNAs and 13,352 genes (29% of the trout genome), of which 8,624 are ohnologues and 4,728 are singletons. These scaffolds were aligned using LastZ52 , resulting in 85,050 local alignments with a mean identity of 86.7%.
To better understand the fate of inactivated gene copies, protein sequences predicted from a given gene model were also aligned to their paralogous region using exonerate53 (link) with the ‘—model protein2genome’ option (Supplementary Methods). Rates of gene loss since the Ts3R WGD were calculated by linear extrapolation.
Berthelot C., Brunet F., Chalopin D., Juanchich A., Bernard M., Noël B., Bento P., Da Silva C., Labadie K., Alberti A., Aury J.M., Louis A., Dehais P., Bardou P., Montfort J., Klopp C., Cabau C., Gaspin C., Thorgaard G.H., Boussaha M., Quillet E., Guyomard R., Galiana D., Bobe J., Volff J.N., Genêt C., Wincker P., Jaillon O., Crollius H.R, & Guiguen Y. (2014). The rainbow trout genome provides novel insights into evolution after whole-genome duplication in vertebrates. Nature Communications, 5, 3657.
Publication 2014
Amino Acid Sequence Aves Chickens Chromosomes Comparative Genomic Hybridization Fishes Gene Order Genes Genes, Duplicate Genome Karyotype Mammals MicroRNAs Oncorhynchus mykiss Oryziinae Proteins Salmonidae SSTR4 protein, human Sticklebacks Synteny Takifugu Trees Trout Vertebrates
4
Comparative Genomics: Curated Genome Sequence Database
Cited 16 times
The following genome sequence files were curated from the Genome Bioinformatics Group of University of California, Santa Cruz [25 ]: Human, March 2006 (hg18); Chimpanzee, March 2006 (panTro2); Rhesus, January 2006 (rheMac2); Rat, November 2004 (rn4); Mouse, February 2006 (mm8); Cat, March 2006 (felCat3); Dog, May 2005 (canFam2); Horse, January 2007 (equCab1); Cow, March 2005 (bosTau2); Opossum, January 2006 (monDom4); Chicken, May 2006 (galGal3); Xenopus tropicalis, August 2005 (xenTro2); Zebrafish, March 2006 (danRer4); Tetraodon, February 2004 (tetNig1); Fugu, October 2004 (fr2); Stickleback, February 2006 (gasAcu1); Medaka, April 2006 (oryLat1); D. melanogaster, April 2006 (dm3); D. simulans, April 2005 (droSim1); D. sechellia, October 2005 (droSec1); D. yakuba, November 2005 (droYak2); D. erecta, August 2005 (droEre1); D. ananassae, August 2005 (droAna2); D. pseudoobscura, November 2005 (dp3); D. persimilis, October 2005 (droPer1); D. virilis, August 2005 (droVir2); D. mojavensis, August 2005 (droMoj2); D. grimshawi, August 2005 (droGri1); C. elegans, January 2007 (ce4); C. brenneri, January 2007 (caePb1); C. briggsae, January 2007 (cb3); C. remanei, March 2006 (caeRem2); and P. pacificus, February 2007 (priPac1); The genome sequence files for the Elephant, June 2005; Hedgehog, June 2006 and Armadillo, June 2005 were downloaded from the Broad Institute [26 ].
The following bacteria genome sequence files were curated from the BacMap database of University of Alberta [27 ]: Staphylococcus aureus COL; Staphylococcus aureus MRSA252; Staphylococcus aureus MSSA476, Staphylococcus aureus Mu50; Staphylococcus aureus MW2; Staphylococcus aureus N315; Staphylococcus aureus subsp. aureus NCTC 8325; Staphylococcus aureus RF122; Staphylococcus aureus subsp. aureus USA300; Staphylococcus epidermidis ATCC 12228; Staphylococcus epidermidis RP62; Staphylococcus haemolyticus JCSC1435; Escherichia coli 536; Escherichia coli APEC O1; Escherichia coli CFT073; Escherichia coli O157:H7 EDL933; Escherichia coli K12 MG1655; Escherichia coli W3110; Escherichia coli O157:H7 Sakai; Klebsiella pneumoniae MGH 78578; Salmonella enterica Choleraesuis SC-B67; Salmonella enterica Paratypi A ATCC 9150; Salmonella typhimurium LT2; Salmonella enterica CT18; Salmonella enterica Ty2; Shigella boydii Sb227; Shigella dysenteriae Sd197; Shigella flexneri 2a 2457T; and Shigella flexneri 301. The genome sequence files for Staphylococcus aureus subsp. aureus JH1, Staphylococcus aureus subsp. aureus JH9, Staphylococcus aureus Mu3, and Staphylococcus aureus subsp. aureus str. Newman were curated from the European Bioinformatics Institute of the European Molecular Biology Laboratory [28 ]. The genome sequence file for Escherichia coli UT189 was taken from Enteropathogen Resource Integration Center [29 ], and genome sequence data for Salmonella bongori was downloaded from the Sanger Institute Sequencing Centre [30 (link)].
The mosquito genome sequence files for Aedes aegypti, Anopheles gambiae and Culex pipiens were curated from the VectorBase database [31].
Yavatkar A.S., Lin Y., Ross J., Fann Y., Brody T, & Odenwald W.F. (2008). Rapid detection and curation of conserved DNA via enhanced-BLAT and EvoPrinterHD analysis. BMC Genomics, 9, 106.
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Publication 2008
Aedes Anopheles gambiae Armadillos Caenorhabditis elegans Chickens Culex Culicidae Didelphidae Drosophila melanogaster Drosophila simulans Elephants Equus caballus Erinaceidae Escherichia coli Escherichia coli K12 Escherichia coli O157 Europeans Genome Genome, Bacterial Homo sapiens Klebsiella pneumoniae Macaca mulatta Mice, House Oryziinae Pan troglodytes Salmonella bongori Salmonella enterica Salmonella typhimurium LT2 Shigella boydii Shigella dysenteriae Shigella flexneri Staphylococcus aureus Staphylococcus aureus subsp. aureus Staphylococcus epidermidis Staphylococcus haemolyticus Sticklebacks Takifugu Xenopus Zebrafish
5
Identification and Classification of OR-like Genes
Cited 14 times
Here, “OR-like genes” include amphioxus OR genes and Type 1
and Type 2 genes in vertebrates, though some Type 2 genes are suggested to be
non-OR genes (see Results). The method for identifying OR-like genes is
essentially the same as that described in a previous paper (Niimura and Nei 2007 (link)) but was slightly
modified. TBlastN (Altschul et al. 1997 (link))
searches were conducted against genome sequences of 14 nonmammalian chordate
species using known OR genes as queries. The query genes included an OR-like
gene from amphioxus (GenBank accession number, AB182635; Satoh 2005 (link)) and two OR genes from river lampreys
(AJ012708 and AJ012709; Freitag et al.
1999) as well as zebra fish, fugu, western clawed frog, chicken, mouse,
and human OR genes that had been previously identified (Niimura and Nei 2003 (link), 2005a (link), 2005b (link)). From the
sequences detected by the TBlastN searches, functional OR genes were identified
by the method in Niimura and Nei
(2007). To identify Type 2 genes from mammalian genomes, TBlastN searches
were conducted against the platypus, opossum, cow, dog, mouse, rat, macaque,
chimpanzee, and human genome sequences using nonmammalian Type 2 genes
identified in this study as queries. Because Type 2 genes and amphioxus OR genes
are more diverse than mammalian OR genes, I conducted TBlastN searches
iteratively using functional Type 2 genes and amphioxus OR genes identified
above as queries and confirmed that no new genes were detected. The functional
genes identified were classified into groups α–λ
on the basis of phylogenetic trees (see Results).
Truncated genes and pseudogenes were detected by conducting TBlastN searches
against the genome sequences with the cutoff E value of 1
× 10−20 using the functional OR-like genes
identified above as queries (for details, see Niimura and Nei 2007 (link)). The truncated genes and pseudogenes were
classified into groups α–λ in the following way.
Suppose that, for a given sequence A (a truncated gene or a pseudogene), a query
(functional) gene B showed the lowest E value among all
queries. In this case, the sequence A was assigned to the group to which the
gene B belongs. Amino acid sequences of all OR-like genes identified in this
study are available in supplementary data sets 1 and 2 (Supplementary Material online). The names of genes that belong
to each group are provided in supplementary data set 3 (Supplementary Material online).
, & Niimura Y. (2009). On the Origin and Evolution of Vertebrate Olfactory Receptor Genes: Comparative Genome Analysis Among 23 Chordate Species. Genome Biology and Evolution, 1, 34-44.
Publication 2009
Amino Acid Sequence Chickens Chordata Didelphidae Genes Genome Genome, Human Homo sapiens Lampreys Lancelets Macaca Mammals Mice, Laboratory Pan troglodytes Platypus, Duckbilled Pseudogenes Rivers Takifugu Vertebrates Xenopus laevis Zebrafish

Most recents protocols related to «Takifugu»

1
LEUTX-V5-HA ChIP-seq protocol
HEL24.3 TetOn LEUTX cells were expanded on Geltrex coated tissue culture dishes in Essential 8 culture medium and treated with 1 μg/ml of Doxycycline for 24 h prior to fixation. Cells were detached from four confluent 10 cm plates with and without doxycycline treatment using TrypLE (Thermo Fisher Scientific). ChIP assays were performed as previously described.24 (link) Cells were fixed in 1% formaldehyde (Thermo Fisher Scientific) for 10minat room temperature and washed twice with ice-cold PBS. The cell pellet was resuspended for lysis in RIPA buffer. Cross-linked chromatin was sonicated to an average fragment size of 200-500 bp then was immunoprecipitated with anti-HA.11 epitope tag antibody (Biolegend, # 901502) and mouse IgG antibody (Santa Cruz, # sc-2025) in LEUTX-V5-HA overexpressed (Dox+) and non-treated (Dox-) iPSCs respectively. ChIP libraries were prepared according to Illumina’s instructions and were sequenced using Illumina NextSeq 500 at Biomedicum Functional Genomics Unit (FuGU).
Gawriyski L., Jouhilahti E.M., Yoshihara M., Fei L., Weltner J., Airenne T.T., Trokovic R., Bhagat S., Tervaniemi M.H., Murakawa Y., Salokas K., Liu X., Miettinen S., Bürglin T.R., Sahu B., Otonkoski T., Johnson M.S., Katayama S., Varjosalo M, & Kere J. (2023). Comprehensive characterization of the embryonic factor LEUTX. iScience, 26(3), 106172.
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Publication 2023
Antibodies, Anti-Idiotypic Buffers Cells Chromatin Cold Temperature Culture Media DNA Chips Doxycycline Epitopes Formaldehyde Hyperostosis, Diffuse Idiopathic Skeletal Immunoglobulin G Immunoprecipitation, Chromatin Induced Pluripotent Stem Cells Mus Radioimmunoprecipitation Assay Takifugu Tissues
2
Comprehensive RRBS Coverage Analysis Across Vertebrates
To assess the genomic coverage of RRBS across a wide range of species, we simulated the restriction digest and size selection in RRBS for all annotated vertebrate genomes that were available from the UCSC Genome Browser, and we determined the expected RRBS coverage for CpG islands, transcripts, promoters, and repeats in each species. To create in silico RRBS libraries, we first mapped all MspI and TaqI restriction sites in these genomes using the matchPattern function in the R package Biostrings104 . The resulting restriction fragments were then filtered to mirror the RRBS size selection step, retaining fragments with a length between 50 bp and 1000 bp. Of these fragments, the first and last 50 bp were registered as simulated RRBS reads. We next identified all CpGs within the genomes using the matchPattern function and intersected these coordinates with the regions covered by the in silico RRBS libraries, and with the different types of genomic elements (CpG islands, transcripts, promoters, repeats) using the findOverlaps function in the R package GenomicRanges105 (link). Finally, we calculated the fraction of CpGs within each of the assessed genomic elements that are covered by the in silico RRBS libraries. For each genome, the coordinates of the genomic elements were downloaded from the UCSC Genome Browser website (goldenpath//bigZips) using the R package rtracklayer106 (link). Promoters were defined as the regions 1000 bp upstream to 500 bp downstream of the transcription start sites. The genome sequences were obtained from the corresponding genome assemblies provided by the UCSC Genome Browser.
The following species and genome assemblies were included in the analysis: Vase tunicate (ci3), African clawed frog (xenLae2), armadillo (dasNov3), elephant shark (calMil1), Tibetan frog (nanPar1), green anole (anoCar2), medaka (oryLat2), fugu (fr3), tetraodon (tetNig2), Nile tilapia (oreNil2), kangaroo rat (dipOrd1), stickleback (gasAcu1), Atlantic cod (gadMor1), sloth (choHof1), zebrafish (danRer11), manatee (triMan1), microbat (myoLuc2), mouse (mm39), Garter snake (thaSir1), naked mole-rat (hetGla2), squirrel (speTri2), zebra finch (taeGut2), golden eagle (aquChr2), Chinese hamster (criGri1), Guinea pig (cavPor3), purple sea urchin (strPur2), brown kiwi (aptMan1), mouse lemur (micMur2), Hawaiian monk seal (neoSch1), chicken (galGal6), budgerigar (melUnd1), American alligator (allMis1), African elephant (loxAfr3), Japanese lamprey (petMar3), turkey (melGal5), painted turtle (chrPic1), cow (bosTau9), ferret (musFur1), rabbit (oryCun2), tree shrew (tupBel1), hedgehog (eriEur2), white rhinoceros (cerSim1), wallaby (macEug2), marmoset (calJac4), sheep (oviAri4), megabat (pteVam1), squirrel monkey (saiBol1), cat (felCat9), Tasmanian devil (sarHar1), golden snub-nosed monkey (rhiRox1), pig (susScr11), rhesus macaque (rheMac10), baboon (papAnu4), orangutan (ponAbe3), alpaca (vicPac2), horse (equCab3), green monkey (chlSab2), dog (canFam5), rat (rn7).
Because many reference genomes had an incomplete assembly status and consisted of many scaffold sequences (often exceeding 10,000 scaffolds instead of a few dozen chromosomes), we concatenated individual scaffolds into 20 arbitrary chromosomes, separating the sequences by stretches of 100 Ns. This improved software runtimes and avoided out-of-memory issues. After processing, genomic coordinates based on these artificial chromosomes were ported back to the original coordinate space to match the genome annotations.
Klughammer J., Romanovskaia D., Nemc A., Posautz A., Seid C.A., Schuster L.C., Keinath M.C., Lugo Ramos J.S., Kosack L., Evankow A., Printz D., Kirchberger S., Ergüner B., Datlinger P., Fortelny N., Schmidl C., Farlik M., Skjærven K., Bergthaler A., Liedvogel M., Thaller D., Burger P.A., Hermann M., Distel M., Distel D.L., Kübber-Heiss A, & Bock C. (2023). Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species. Nature Communications, 14, 232.
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Publication 2023
Alligators Anura Armadillos Callithrix Cavia Cercopithecus aethiops Chickens Chinese Hamster Chromosomes, Artificial Chromosomes, Human, Pair 10 Chromosomes, Human, Pair 20 Ciona intestinalis CpG Islands cytidylyl-3'-5'-guanosine Domestic Sheep Eagle Elephants Equus caballus Erinaceidae Ferrets Finches Gadus morhua Genome Genome Components Japanese Lampreys Loxodonta Macaca mulatta Melopsittacus Memory Mice, House Microcebus Mole Rats Monks Native Hawaiians Oreochromis niloticus Oryzias latipes Papio Phocidae Pongo pygmaeus Rabbits Rats, Kangaroo Rhinopithecus roxellana Saimirus Sharks Sloths Squirrels Sticklebacks Strongylocentrotus purpuratus Takifugu Thamnophis Transcription Initiation Site Trichechus Tupaiidae Turtle Vertebrates Vicugna pacos Wallabies Xenopus laevis Zebrafish Zebras
3
Optimizing Genome Assembly with In Silico Mate-Pairs
We designed three experiments using published data and simulations to test the efficiency of the in silico mate‐pair method and optimized in silico mate‐pair method on the genome assembly of fishes and mammals. Mate‐pair libraries were generated using multiple reference genomes with different divergency time (inferred from TimeTree, Figure 1) from the same genus, family, and order of target species (Table 1, Table S1; Kumar et al., 2022 (link)). First, we tested the effect of using references with different phylogenetic distances (Figure 1a,b) to target species, on the quality of target genome assemblies, using the paired‐end data of the walking catfish (Clarias batrachus) and a puffer fish (Takifugu bimaculatus). For C. batrachus, genomes of two species, C. magur and C. macrocephalus, from the same genus, and one species, Ameiurus melas, from a different family but the same order, were selected as references. For T. bimaculatus, reference genomes of two species, T. rubripes and T. flavidus from the same genus, one species, Tetraodon nigroviridis, from a different genus but the same family, and one species, Mola mola, from a different family but the same order, were selected. Second, we optimized the in silico mate‐pair method by searching for conserved mate‐pairs generated using two or more references (Figure 2) and used them to assemble the genomes via SOAPdenovo2 (Luo et al., 2012 (link)). Third, we tested whether the optimized in silico mate‐pair method using references with different phylogenetic distances (Figure 1c) significantly improved the genome assembly of the mountain nyala (Tragelaphus buxtoni), a highly degraded sample. Genomes of two species, T. scriptus and T. strepsiceros, from the same genus, one species, Bos grunniens, from a different genus but the same family, and one species, Moschus moschiferus, from a different family but the same order, were selected as references to produce in silico mate‐pairs for the purpose of assembling the genome of T. buxtoni. Lastly, we simulated single‐end ancient DNA reads using T. flavidus sequencing data to test the optimized in silico method and compared it with a reference‐guided approach, RagTag (Michael Alonge et al., 2022 (link)).
Zhou T., Lu L, & Li C. (2023). Optimization of the “in‐silico” mate‐pair method improves contiguity and accuracy of genome assembly. Ecology and Evolution, 13(1), e9745.
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Publication 2023
Ameiurus Bos grunniens DNA, Ancient Fluorescent in Situ Hybridization Genome Mammals MELAS Syndrome Pufferfish Sapajus macrocephalus Siluriformes Takifugu
4
Alcalase-Pepsin-Trypsin Hydrolysis of Takifugu Flavidus Skin
Takifugu flavidus were purchased from Zhangzhou City of Fujian Province, China. The skin was shelled, husked, and used for further experimentation. Alcalase, pepsin, and trypsin were purchased from Sinopharm Group (Beijing, China); angiotensin-I-converting enzyme, hippuryl-l-histidyl-L-leucine (HHL), hippuric acid, and CNBr-activated Sepharose 4B were purchased from Sigma-Aldrich (St. Louis, MO, USA). Captopril was procured from MedChem Express (Monmouth Junction, NJ, USA). All other chemicals/reagents used were of analytical grade or HPLC grade.
Su Y., Chen S., Liu S., Wang Y., Chen X., Xu M., Cai S., Pan N., Qiao K., Chen B., Yang S, & Liu Z. (2023). Affinity Purification and Molecular Characterization of Angiotensin-Converting Enzyme (ACE)-Inhibitory Peptides from Takifugu flavidus. Marine Drugs, 21(10), 522.
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Publication 2023
Captopril Cyanogen Bromide High-Performance Liquid Chromatographies hippuric acid hippuryl-histidyl-leucine Pepsin A Peptidyl-Dipeptidase A Sepharose 4B Skin Subtilisin Carlsberg Takifugu Trypsin
5
Molecular Profiling of Mineralized Tissues in Medaka
Genome Data Viewer (GDV) (https://www.ncbi.nlm.nih.gov/genome/gdv/) [18 (link)] and Ensembl Genome Browser (EGB) 105 (https://www.ensembl.org/index.html) were used to search gene sequence databases to identify gene orthologues and examine the expression of scpp genes in medaka (ASM223467v1). Genomic synteny analysis was also conducted using GDV and EGB105. Each scpp gene assembly number in medaka was referenced to GDV and EGB105, as listed in availability of data. For scpp4, scpp7, scpp9, and enam, similar sequences were identified in the medaka genome by performing genomic alignment with zebrafish (GRCz11) and fugu (fTakRub1.2) in EGB105. Those sequences were then obtained by searches using BLAST (blastin) (https://blast.ncbi.nlm.nih.gov/Blast.cgi). Genomic locations of the scpp genes were extracted from publicly available annotations in EGB105. Specific primers were designed using Primer3Plus (https://primer3plus.com), and the primer sequences are listed in Table 1. Brain, liver, fin ray bone, and pharyngeal tissues (teeth and bone) were dissected from the medaka, and total RNA was extracted from each tissue using TRI REAGENT (Molecular Research Center Inc., Cincinnati, OH, USA). Total RNA from the fin ray bone was extracted after dissecting the fin ray from the body without removing the epithelium. cDNAs were generated using a 1st Strand cDNA Synthesis kit for RT-PCR® (Roche, Basel, Switzerland).

Specific primers for scpp genes and mineralized tissue-related genes used in qPCR and ISH analyses

GenePrimer sequences (5' → 3')SizePrimer sequences (5' → 3')Size
qPCRISH
scpp1F: GCCAGCAAGAGTTCAAAGGA139 bpF: CAGACAACATCGTGAGACTTCTTC396 bp
R: CATCTCCTACGCTCTGGACAAR: GAAAACACCCTTACCCAACTCTG
scpp2F: TGCCAGCAATAGCAATGAGA148 bpF: CCTTCTGTTGATCTGCCTTTTC340 bp
R: CTGGGGGTTTAGATTCAGCAR: CTGAGGGATGTTGGGATTATTG
scpp5F: CATGCCTCAGCAAACCATAAA149 bpF: GTGTTTTGTTTCTGAGGGGACA443 bp
R: GGCAGATAATGACGGAGGAGR: GTTTGCTGAGGCATGTTTTGAG
sparcF: TGAGGGACTGGCTGAAGAAC150 bpF: AGCAGAAGCTCAGGGTAAAGAAG352 bp
R: CCAACAGGTCCAAAGAGTGGR: GTCAGAGGAGTTTAGATGACGAGA
spp1F: CACTGACTTTCTGGAGGAGGA84 bpF: AAGAAGACGAAGACGAAACCAC252 bp
R: TGGTCTTGAGATACGCTGGAR: AGGGAGAGGGAACTTTGTGATAG
col1a1F: CAAGAACAGCGTTGCCTACA95 bpF: TGAAGTGGTGTGTGAAGAAGTG284 bp
R: CCTCGGCTCTGATCTCAATCR: GCATAGCTGGAGATTTGTCATC
bglapF: TGAAATGGCTGACACTGAGG52 bpF: CTACTGCTTCTGCCTCATCATC215 bp
R: TCCGTAGTAGGCGGTGTATGR: AGTGTCAGCCATTTCATCACAG
runx2F: GGAAAGGATGCGAGTGAGAG105 bpF: GCACACCCTATCTCTACTACGG265 bp
R: TCTGTGATCTGCGTCTGACCR: CTCCACCCACTTTTCCTCTAA
sp7F: GCTCACGGTTTAAGGAGGTG73 bpF: CGCATCTATTCTGGAGGTAGGAAG351 bp
R: AATCAGGGATGGAGGGAAACR: GAGTGGGAGAAGGGGTTATATTCTG
β-actinF: GCCAACAGGGAGAAGATGAC133 bp
R: CATCACCAGAGTCCATGACG
Morita T., Matsumoto S, & Baba O. (2023). Expression of secretory calcium-binding phosphoprotein (scpp) genes in medaka during the formation and replacement of pharyngeal teeth. BMC Oral Health, 23, 744.
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Publication 2023
Anabolism Bones Brain DNA, Complementary Epithelium Gene Expression Genes Genome Human Body Liver Oligonucleotide Primers Oryziinae Pharynx Reverse Transcriptase Polymerase Chain Reaction Synteny Takifugu Tissues Tooth Zebrafish

Top products related to «Takifugu»

1
Nextseq 500 by Illumina
Sourced in United States, Germany, China, United Kingdom, Australia, France, Italy, Canada, Japan, Austria, India, Spain, Switzerland, Cameroon, Netherlands, Czechia, Sweden, Denmark
The NextSeq 500 is a high-throughput sequencing system designed for a wide range of applications, including gene expression analysis, targeted resequencing, and small RNA discovery. The system utilizes reversible terminator-based sequencing technology to generate high-quality, accurate DNA sequence data.
2
Agilent 2100 bioanalyzer by Agilent Technologies
Sourced in United States, Germany, Canada, China, France, United Kingdom, Japan, Netherlands, Italy, Spain, Australia, Belgium, Denmark, Switzerland, Singapore, Sweden, Ireland, Lithuania, Austria, Poland, Morocco, Hong Kong, India
The Agilent 2100 Bioanalyzer is a lab instrument that provides automated analysis of DNA, RNA, and protein samples. It uses microfluidic technology to separate and detect these biomolecules with high sensitivity and resolution.
3
Genejet rna purification kit by Thermo Fisher Scientific
Sourced in United States, Lithuania, United Kingdom, Canada, Germany, China, Italy, Spain
The GeneJET RNA Purification Kit is a laboratory product designed to isolate and purify RNA from various sample types. It utilizes a silica-based membrane technology to efficiently capture and concentrate RNA molecules, allowing for their subsequent elution and use in downstream applications.
4
Antibody against α tubulin by Merck Group
Sourced in United States
The Antibody against α-tubulin is a laboratory reagent used to detect and study the alpha subunit of the tubulin protein, a key structural component of the cytoskeleton in eukaryotic cells. This antibody can be used in various techniques, such as Western blotting, immunohistochemistry, and immunocytochemistry, to visualize and analyze the distribution and expression of α-tubulin within cells.
5
Goat anti rabbit hrp conjugated secondary antibodies by Cytiva
Goat anti-rabbit HRP-conjugated secondary antibodies are a type of laboratory reagent used in various immunoassay techniques. These antibodies are designed to detect and bind to rabbit primary antibodies, with the horseradish peroxidase (HRP) conjugate allowing for colorimetric or chemiluminescent detection.
6
Smart race cdna amplification kit by Takara Bio
Sourced in United States, Japan, China, Canada, France
The SMART RACE cDNA Amplification Kit is a laboratory tool designed for the rapid amplification of cDNA ends. It provides a method for generating full-length cDNA sequences from limited amounts of RNA samples.
7
Puromycin by Merck Group
Sourced in United States, Germany, China, Sao Tome and Principe, United Kingdom, Macao, Canada, Japan, Italy, Switzerland, France, Israel, Australia, Spain, Belgium, Morocco, Sweden
Puromycin is a laboratory product manufactured by Merck Group. It functions as an antibiotic that inhibits protein synthesis in eukaryotic cells.
8
Trc1 library by Merck Group
Sourced in United States
The TRC1 library is a collection of genetic material used in laboratory research. It serves as a comprehensive resource for studying gene function and expression. The library contains a large number of genetic sequences that can be utilized for various experimental purposes.
9
Vybrant cfda se cell tracer by Thermo Fisher Scientific
Sourced in United States
The Vybrant CFDA SE Cell Tracer is a fluorescent dye used for tracking and monitoring cell populations. It covalently binds to proteins within living cells, providing a stable, long-term label that can be detected by flow cytometry or fluorescence microscopy.
10
L 1 phytagel by Merck Group
L-1 Phytagel is a high-purity plant-derived gelling agent used in various laboratory applications. It is a natural, non-toxic, and biodegradable polysaccharide that forms stable gels in aqueous solutions. The core function of L-1 Phytagel is to provide a gelling matrix for a wide range of applications, including cell culture, microbiology, and plant tissue culture.

More about "Takifugu"

Takifugu, also known as pufferfish or blowfish, are a genus of small, round marine fish found primarily in the waters of East Asia.
These distinctive fish are revered for their unique appearance and the potent neurotoxin tetrodotoxin present in their internal organs.
Takifugu have been the subject of extensive scientific research, with studies exploring their remarkable biology, behavior, and potential medical applications.
Researchers and medical professionals can leverage PubCompare.ai, an innovative AI-powered platform, to navigate the wealth of Takifugu-related literature.
This platform enables users to locate the most effective protocols and products with ease, driving reproducibility and accuracy in Takifugu research.
Through intelligent comparison of scientific publications, preprints, and patents, PubCompare.ai empowers researchers to discover the latest advancements in Takifugu studies.
Takifugu research often involves advanced techniques and technologies.
Researchers may utilize instruments like the NextSeq 500 sequencing system or the Agilent 2100 Bioanalyzer to analyze Takifugu samples.
RNA extraction kits, such as the GeneJET RNA Purification Kit, may be employed to isolate high-quality genetic material.
Antibodies, like the one against α-tubulin, and secondary antibodies, such as Goat anti-rabbit HRP-conjugated, can be used for protein detection and quantification.
The SMART RACE cDNA Amplification Kit may aid in the amplification of Takifugu genetic sequences, while Puromycin can be used as a selection marker in Takifugu cell culture studies.
The TRC1 library, a collection of Takifugu-related genetic information, and the Vybrant CFDA SE Cell Tracer, a tool for cell labeling and tracking, may also contribute to Takifugu research.
Takifugu studies have the potential to unlock groundbreaking discoveries in the fields of marine biology, pharmacology, and beyond.
By leveraging the power of PubCompare.ai and the latest experimental techniques, researchers can drive forward the understanding of these remarkable pufferfish and their potential applications in medicine and conservation.
Explore the fascinating world of Takifugu and uncover the hidden insights that can propel scientific progress.