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Cactaceae

Cactaceae: A diverse family of succulent plants native to the Americas, known for their distinctive spiny appearance and ability to thrive in arid environments.
These plants display a wide range of morphological features, including varied stem structures, leaf adaptations, and floral characteristics.
The Cactaceae family encompasses numerous genera and species, each with unique adaptations to their respective habitats.
Researchers studying Cactaceae can leverage PubCompare.ai to efficiently locate and compare the best methods from literature, preprints, and patents, ensuring reproducibility and accuracy in their research proceses.

Most cited protocols related to «Cactaceae»

1
Analyzing Multiple Genome Alignments in HAL
Cited 75 times
A set of command line utilities, summarized in Table 1, are provided to create and analyze multiple genome alignments in HAL. Importers are provided for UCSC’s MAF, which is a standard with its own rich set of filters and converters (ex. to FASTA) (Blanchette et al., 2004 (link)) and Cactus (Paten et al., 2011 (link)), which has been designed specifically to output HAL. MAF files can be quickly produced from HAL graphs for given subgraphs with respect to arbitrary references to be compatible with existing browsers and tools. The memory usage of each tool is configurable via its command line options.

HAL tools summary

ToolDescription
halStatsPrint summary statistics of HAL file
halSummarizeMutationsPrint mutation summary for given subgraph
halBranchMutationsGenerate BED file(s) of mutations for a branch
halLiftoverMap BED coordinates between genomes
hal2maf/maf2halConvert to and from MAF
cactus2halConvert from Cactus
Mutations can be identified along branches and output to tab delimited annotation files using the halBranchMutations tool. A cycle decomposition of the breakpoint graph structure allows rearrangements, such as duplications, inversions and transpositions to be reported in addition to substitutions, insertions and deletions. Small indels (determined by a provided threshold) can be nested within larger rearrangements to avoid overcounting in these cases. Patterns of conservation within a target sequence can be aggregated using the halLiftover tool, which maps coordinates in a BED file to an arbitrary target in the alignment. This utility provides a general strategy to efficiently liftover and project any comparative genomics information into the coordinate system of any reference genome. Excellent software packages are available for sorting, combining and querying BED files (Quinlan and Hall, 2010 (link); Neph et al., 2012 (link)) and can be combined with the aforementioned tools to create powerful analysis pipelines for multiple genome alignments.
Hickey G., Paten B., Earl D., Zerbino D, & Haussler D. (2013). HAL: a hierarchical format for storing and analyzing multiple genome alignments. Bioinformatics, 29(10), 1341-1342.
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Publication 2013
Cactaceae Gene Deletion Gene Rearrangement Genome INDEL Mutation Insertion Mutation Inversion, Chromosome Memory Microtubule-Associated Proteins Mutation
2
DNA Extraction Optimization from Challenging Plants
Cited 30 times
DNA purity was estimated using a spectrophotometer, (Nanodrop 2000; Thermo Fisher Scientific). DNA yield was estimated, using a fluorimeter and fluorescent DNA-binding dye (QubitTM dsDNA BR Assay Kit; Thermo Fisher Scientific), according to the manufacturer´s instructions. DNA integrity was checked by agarose gel electrophoresis.
To test the effectiveness of the reported DNA extraction protocol, we performed a series of small-scale parallel DNA extractions, with and without the sorbitol pre-wash step. Leaves of several plant genera regarded as “demanding” in our laboratory were tested, including A. occidentale (Anacardiaceae) (Cashew), E. grandis (Myrtaceae), Pereskia aculeata (Cactaceae), several different species of the genera Diplusodon and Lafoensia (both Lythraceae). DNA yields and purity were estimated spectrophotometrically. DNA quality was also inferred by a simple PCR amplification assay using the nuclear ribosomal ITS marker. Each reaction contained 1 X PCR buffer with 2.0 mM MgSO4, 0.2 mM dNTP’s, 0.2 M Trehalose, 0.3 μM each of the universal primers An5 and An4 [21 (link)], 1 U Taq DNA polymerase and 1 μl undiluted DNA. PCR cycling consisted of two minutes initial denaturation at 95°C then 35 cycles of 20 seconds at 95°C, 40 seconds at 55°C and 80 seconds at 72°C, followed by 7 minutes at 72°C. PCR products were analyzed using an ethidium bromide stained 1.5% w/v agarose gel, where the expected band size of the ITS fragment was approximately 650 bp.
Inglis P.W., Pappas M.D., Resende L.V, & Grattapaglia D. (2018). Fast and inexpensive protocols for consistent extraction of high quality DNA and RNA from challenging plant and fungal samples for high-throughput SNP genotyping and sequencing applications. PLoS ONE, 13(10), e0206085.
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Publication 2018
Anacardiaceae Anacardium occidentale Biological Assay Buffers Cactaceae DNA, A-Form DNA, Double-Stranded Electrophoresis, Agar Gel Ethidium Bromide Fluorescent Dyes Lythraceae Myrtaceae Neoplasm Metastasis Oligonucleotide Primers Plant Leaves Ribosomes Sepharose Sorbitol Sulfate, Magnesium Taq Polymerase Trehalose
3
CACTI: Automating Motivational Interviewing Analysis
Cited 18 times
CACTI was developed for Project ELICIT, a randomized study of two training methods for motivational interviewing with 190 front-line substance-abuse treatment providers [29] . The software was designed for use with the Motivational Interviewing Skill Code (MISC 2.5) [30] , a sequential-coding system for psychotherapy sessions that was derived from the Sequential Code for Observing Process Exchanges (SCOPE) [31] . The SCOPE uses concurrent transcripts and audio recordings to divide and rate client and clinician speech; it was employed in Project PREMIR [6] (link), a psychotherapy process study of 118 recordings of 13 Motivational Enhancement Therapy clinicians. The MISC 2.5 serves three purposes: parsing (unitizing) speech into codeable utterances (speech units), sequential coding of client and clinician utterances, and assignment of global ratings for clients and clinicians. Multiple versions of the program were tested and refined by trained MISC 2.5 coders before CACTI was employed in Project ELICIT.
Glynn L.H., Hallgren K.A., Houck J.M, & Moyers T.B. (2012). CACTI: Free, Open-Source Software for the Sequential Coding of Behavioral Interactions. PLoS ONE, 7(7), e39740.
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Publication 2012
Cactaceae Joints Motivational Interviewing Psychotherapy Speech Substance Abuse
4
Comparative Phylogenomic Alignment of Avian Genomes
Cited 17 times
The guide-tree analysis was performed on a set of 48 bird genomes previously published29 (link). To reduce the amount of alignment work required, we subset these genomes down to the size of only a single chromosome, chicken chromosome 1 (by removing any contig or scaffold that had less than 20% of its sequence alignable to chicken chromosome 1). We used Progressive Cactus commit 36304707 for all alignments in this analysis.
The Prum and Jarvis topologies were adapted from Prum et al.28 (link) and Jarvis et al.29 (link), respectively. The ‘permuted’ topology was generated starting from the Jarvis topology, via three randomly chosen subtree-prune-regraft operations followed by three random nearest-neighbour-interchange operations. Each of these three topologies had branch-length estimates performed using phyloFit from the PHAST package (https://github.com/CshlSiepelLab/phast, commit 52e8de9) based on fourfold-degenerate sites of BUSCO orthologues. Finally, the ‘consensus’ tree was produced as a strict consensus of the Jarvis and Prum trees (collapsing all groupings that were not the same in both trees) using the ape::consensus method from the APE R package44 (link). The branch-lengths for this tree were generated from the fitted branch lengths for the two input trees, using the consensus.edges function of the phytools R package45 . The four final trees that were used in the four Progressive Cactus alignments are shown in Supplementary Fig. 1, and available in supplementary data in Newick format.
We further focused on the alignments with guide trees based on Jarvis29 (link) and Prum28 (link) (Supplementary Fig. 3) to establish what alignment differences resulted from different phylogenetic hypotheses. Supplementary Fig. 2 shows a refinement of the overall alignment-to-alignment F1 scores shown in Extended Data Table 2, showing the F1 scores for each species pair between the Jarvis- and Prum-based alignments. Each pair of species has an F1 score between Jarvis- and Prum-based alignments of at least 0.955.
Armstrong J., Hickey G., Diekhans M., Fiddes I.T., Novak A.M., Deran A., Fang Q., Xie D., Feng S., Stiller J., Genereux D., Johnson J., Marinescu V.D., Alföldi J., Harris R.S., Lindblad-Toh K., Haussler D., Karlsson E., Jarvis E.D., Zhang G, & Paten B. (2020). Progressive Cactus is a multiple-genome aligner for the thousand-genome era. Nature, 587(7833), 246-251.
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Publication 2020
Aves Cactaceae Chickens Chromosomes Chromosomes, Human, Pair 1 Genome Trees
5
Efficient Genome Preprocessing for Progressive Cactus
Cited 16 times
Progressive Cactus requires input genomes to be soft-masked, but often repetitive sequence goes unmasked due to poor masking or incomplete repeat libraries for newly-sequenced species. This can negatively affect alignment runtimes (as alignments need to be enumerated to and from all copies of a repetitive sequence) and impact quality. For this reason, we mask overabundant sequence before alignment, using a strategy not based on alignment to repeat consensus libraries, but on over-representation of alignments. We first divide each genome into small, mutually overlapping chunks. For each chunk, we align it to itself and a configurable amount of other randomly sampled chunks (currently 20% of the total pool). To avoid combinatorial explosion due to unmasked repetitive sequence, we use a special mode of LASTZ which stops exploring alignments from any region early if a maximum depth is reached (using the flag --queryhsplimit=keep,nowarn:1500, which stops after a high-scoring-pair depth of 1,500). We then soft-mask any region covered by more than a configurable number of these alignments (currently set to 50). Further details can be found in the src/cactus/preprocessor section of the Progressive Cactus codebase. Although the preprocessing step is automatically run as part of the pipeline, we also provide a cactus_preprocessor utility to run only the preprocessor without producing a full genome alignment.
Armstrong J., Hickey G., Diekhans M., Fiddes I.T., Novak A.M., Deran A., Fang Q., Xie D., Feng S., Stiller J., Genereux D., Johnson J., Marinescu V.D., Alföldi J., Harris R.S., Lindblad-Toh K., Haussler D., Karlsson E., Jarvis E.D., Zhang G, & Paten B. (2020). Progressive Cactus is a multiple-genome aligner for the thousand-genome era. Nature, 587(7833), 246-251.
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Publication 2020
Blast Injuries Cactaceae Genome Repetitive Region Sequence Alignment

Most recents protocols related to «Cactaceae»

1
Comparative Plastome Structural Analysis
Whole-genome alignments were performed to examine the arrangement of locally colinear blocks (LCBs) of different cactus plastome structural types using progressiveMauve (v2.3.1) [76 (link)] with default parameters. Before this, we manually removed the last IR region of plastomes. The plastome syntenies were plotted using Mcscan (v.2) [77 (link)] implemented in TBtools (v.1.106) [78 (link)]. Specifically, we first obtained BLASTn results between the pairs of plastomes (IR removed), and the e-value was set as 1e-5. Then, the alignments were split into 10 bp fragments, which were forced to be used as a ‘gene’ in TBtools (v.1.106). The dot plots of plastomes were drawn using MAFFT online version [79 (link)] or Gepard (v1.40) [80 (link)]. Boundary changes in the IR regions were drawn manually.
Yu J., Li J., Zuo Y., Qin Q., Zeng S., Rennenberg H, & Deng H. (2023). Plastome variations reveal the distinct evolutionary scenarios of plastomes in the subfamily Cereoideae (Cactaceae). BMC Plant Biology, 23, 132.
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Publication 2023
Cactaceae Genes Genome Synteny
2
Plastome Sequencing of Diverse Cacti
To avoid resource waste caused by repeated sampling, we accessed the European Nucleotide Archive (ENA) (https://www.ncbi.nlm.nih.gov/sra) database and obtained WGS (whole-genome sequencing) data for 9 species with a complete plastome assembly. They all come from the Kew Tree of Life project [61 (link)], which is freely available for use. Furthermore, we collected fresh stem samples of 26 cactuses from flower markets in Chongqing, Guangxi, and Fujian in September 2020. All specimens were deposited in the Herbarium of Southwest University, Chongqing. Two previously reported species (Carnegiea gigantea, NC_027618.1; Lophocereus schottii, NC_041727.1) were also included in our analysis. The details of the plant samples used for plastome assembly are given in Table S5.
Yu J., Li J., Zuo Y., Qin Q., Zeng S., Rennenberg H, & Deng H. (2023). Plastome variations reveal the distinct evolutionary scenarios of plastomes in the subfamily Cereoideae (Cactaceae). BMC Plant Biology, 23, 132.
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Publication 2023
Cactaceae Europeans Nucleotides Plants Stem, Plant Trees
3
Cactus Plastome and Mitogenome Assembly
Total genomic DNA was extracted by using the CTAB method [62 (link)]. The DNA library with an insert size of 350 bp was constructed using an NEBNext® library construction kit (supplier, city country) and sequenced by using the HiSeq XTen PE150 sequencing platform (supplier, city country). See Table S6 for detailed information on Illumina sequencing data quality. Furthermore, clean data were obtained by using Trimmomatic (v0.32) [63 ] as follows: we removed low-quality sequences, including sequences with a quality value of Q < 19 that accounted for more than 50% of the total bases and sequences in which more than 5% of the bases were “N”. To assemble cactus plastomes, de novo genome assembly from the clean data was accomplished utilizing GetOrganelle (v1.7.3) [64 (link)] with the default setting. For linear contigs, NOVOPlasty (v3.8.1) [65 (link)] was used for further contig extensions. The correctness of the assembly was confirmed by using Bowtie2 (v2. 0.1) [66 (link)] to manually edit and map all the raw reads to the assembled genome sequence under the default settings. Detailed assembly information is shown in Table S7. Pereskia aculeata was also sequenced using the Oxford Nanopore promethION platform.
We assembled the draft mitochondrial genome using Illumina reads with the ‘embplant_mt’ option in GetOrganelle (v1.7.3). Then, we visualized the raw GFA file produced by GetOrganelle (v1.7.3) in Bandage (v0.8.1) [67 ]. The plastid/nuclear-derived contigs were removed manually based on the coverage and BLASTn results retrieved from the NCBI database. Only the mitogenomes that consisted of a network of closed and connected contigs were thought to be complete. Although the extensive repeats could not be resolved without long reads, the draft mitogenome assembled here was considered complete, and it represents all mitochondrial DNA sequences of the species.
Yu J., Li J., Zuo Y., Qin Q., Zeng S., Rennenberg H, & Deng H. (2023). Plastome variations reveal the distinct evolutionary scenarios of plastomes in the subfamily Cereoideae (Cactaceae). BMC Plant Biology, 23, 132.
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Publication 2023
Bandage Cactaceae Cetrimonium Bromide DNA, Mitochondrial DNA Library Genome Genome, Mitochondrial Plastids
4
Cultivation of Edible Nopalea cochenillifera
Nopalea cochenillifera cv. Maya (edible Opuntia sp., common name “Kasugai Saboten”; subfamily Opuntioideae, family Cactaceae) was bought at a local market (Goto Cactus, 1-122-3, Momoyama, Kasugai City, Aichi Prefecture, Japan). The cladode was dried for 10 days in the dark at room temperature and then placed in a 1 dm−3 pot filled with a mixture of field soil and leaf mold (7:3, v/v) for about 3 weeks until rooting in a glass greenhouse (Meijo University Tempaku Campus, Tempaku, Nagoya City, Aichi Prefecture, Japan). The greenhouse was warmed by boilers at ≥ 10 °C from November to March.
Kondo A., Ito M., Takeda Y., Kurahashi Y., Toh S, & Funaguma T. (2023). Morphological and antioxidant responses of Nopalea cochenillifera cv. Maya (edible Opuntia sp. “Kasugai Saboten”) to chilling acclimatization. Journal of Plant Research, 136(2), 211-225.
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Publication 2023
Cactaceae Desiccation Fungus, Filamentous Opuntia Plant Leaves
5
Defining Callable Genomic Regions for Mutation Detection
Cited 1 time
Callable sites were defined as genomic sites where SMs could be called with high confidence, based on visualization of the sequencing and assembly data. We previously defined callable sites based on short-read mapping parameters (Ness et al. 2015 (link); López-Cortegano et al. 2021 (link)). Here, we used two criteria based on the de novo genome assemblies of the ancestors and MA lines. First, the ancestor assembly was aligned against itself with minimap2 (“-x asm5”), and genomic regions that were absent in the resulting PAF file (i.e., that were unmapped) were deemed uncallable. This first criterion was used because these regions are essentially unmappable even as isogenic sequences (at least with minimap2) and are hence inaccessible to variant calling. Second, a similar procedure was followed for each MA line by aligning their assemblies to the ancestor genome and extracting unmapped genomic coordinates. The unmapped coordinates extracted from all MA lines per ancestor were then intersected using BEDTools “intersect” (Quinlan and Hall 2010 (link)), and any regions that were present in at least two MA lines were defined as uncallable, because an unmapped region in a single MA line could be an SM such as a large deletion. This second criterion was adopted because these regions are prone to assembly breaks across multiple lines, even though they are assembled in the ancestor references. Taking the output from both criteria, uncallable regions separated by <30 kb were merged. Finally, coordinates corresponding to active cut-and-paste DNA transposons were manually reincluded as callable, because the excisions at these sites could otherwise be classified as uncallable if the same TE was excised in multiple lines. Because the uncallable regions are enriched in tandem repeats (see Supplemental Material; Supplemental Dataset S2; for the example dotplot, see Supplemental Fig. S4), we expect that we may have underestimated the mutation rate of TRMs. However, there was no overrepresentation of other SM types in callable tandem repeats, suggesting that the callable regions of the ancestor assemblies provide near-complete references for detecting most SMs genome-wide.
To compare callable sites between our previous Illumina sequencing and the PacBio sequencing described here, callable site coordinates from Ness et al. (2015) (link) were converted to correspond to our new ancestor assemblies. A whole-genome alignment of the v5 reference assembly and the ancestor assemblies was generated using Cactus (Armstrong et al. 2020 (link)). Coordinates were then lifted over to the relevant ancestor assembly using the HAL tools command halLiftover (Hickey et al. 2013 (link)).
López-Cortegano E., Craig R.J., Chebib J., Balogun E.J, & Keightley P.D. (2023). Rates and spectra of de novo structural mutations in Chlamydomonas reinhardtii. Genome Research, 33(1), 45-60.
Publication 2023
Cactaceae Deletion Mutation DNA Transposons Genome NES protein, human Paste Tandem Repeat Sequences

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More about "Cactaceae"

Explore the diverse world of Cactaceae, the succulent plant family native to the Americas.
These iconic, spiny plants are known for their remarkable adaptations to arid environments, showcasing a wide range of stem structures, leaf modifications, and intricate floral characteristics.
Researchers studying Cactaceae can leverage powerful tools like PubCompare.ai to efficiently locate and compare the best methods from literature, preprints, and patents, ensuring reproducibility and accuracy in their research processes.
The Cactaceae family encompasses numerous genera and species, each with unique adaptations to their respective habitats.
From the iconic barrel cacti to the towering saguaros, these plants have evolved ingenious strategies to thrive in the harshest of conditions.
Leveraging cutting-edge techniques and equipment, such as the SAS 9.4 statistical software, Avance III NMR spectrometer, and RNeasy Mini Kit for RNA extraction, researchers can delve deeper into the molecular and physiological mechanisms that underpin the Cactaceae's remarkable resilience.
Analytical tools like the Folin-Ciocalteu reagent and UV-2450 spectrophotometer can be employed to quantify the diverse secondary metabolites found in these succulents, while advanced genetic analysis using the ABI Prism 3730 Genetic Analyzer and MEGAscript T7 kit can uncover the genomic secrets that drive their unique adaptations.
Cutting-edge sequencing platforms, such as the MiSeq, can provide researchers with a wealth of data to better understand the evolutionary relationships and phylogenetic patterns within the Cactaceae family.
Microscopic imaging techniques, such as the Axiovert 200 inverted microscope, can shed light on the intricate morphological features of Cactaceae, while the GoTaq Flexi polymerase can be utilized for robust PCR-based analyses.
By leveraging these state-of-the-art tools and techniques, researchers can unlock the mysteries of Cactaceae, paving the way for groundbreaking discoveries and advancements in our understanding of these fascinating plants.