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Short Tandem Repeat

Short Tandem Repeat (STR) is a type of genetic marker characterized by the repetition of short DNA sequences within the genome.
STRs are widely used in forensics, genetic linkage analysis, and population genetics due to their high level of polymorphism and codominant inheritance.
These repetitive elements can be used to identify individuals and establish familial relationships.
STR analysis involves the amplificaiton and comparison of these repeating units, providing a powerful tool for researchers to study genetic diversity and inheritance patterns.

Most cited protocols related to «Short Tandem Repeat»

Geneious Basic is written in Java Swing to maximize interoperability among all commonly used operating systems. It is compiled under and requires Java 5 to run. The application provides core modules to enable the visualization, manipulation and transfer of DNA sequences (linear, circular and short oligos such as primers and probes), amino acid sequences, pair-wise and multiple alignments, phylogenetic trees, 3D structures, sequence chromatograms, contig assemblies, microsatellite electropherograms and statistical graphs.
The underlying software framework for Geneious Basic is modular and multi-tiered with a focus on handling bioinformatics data and tools (Fig. 1). It integrates a comprehensive plugin system which is grounded in the extensible Geneious API. The public API component allows plugin developers to leverage the functionality and user interface of the Geneious platform while concentrating on the development of processes and algorithms. The API download from the Geneious website provides a number of skeleton plugin examples to use as a basis for new plugins, allowing developers with a basic level of Java knowledge to develop fully functional plugins that greatly extend the functionality of Geneious Basic.

Modular overview of the Geneious Basic software stack. Top-most modules have dependencies on lower modules. The unshaded modules represent the publicly accessible modules for plugin development.

The public API allows developers to leverage online sequence search web services such as NCBI BLAST. Also using the public API, developers can implement plugins that exploit external binaries and even online computational resources, a growing trend in the field of Bioinformatics (Schatz et al., 2010 (link)).
Publication 2012
2',5'-oligoadenylate Amino Acid Sequence DNA Sequence Oligonucleotide Primers Short Tandem Repeat Skeleton
A microsatellite analysis with the command line version of MISA requires two input files: (i) a configuration file (‘MISA.ini’) with three input parameters: ‘SSR search parameters’, ‘compound SSR search parameter’ and ‘output file type parameter’; and (ii) a FASTA file containing the nucleotide sequence that is to be mined for microsatellites.
MISA-web runs on a standard Linux server and works in conjunction with several helper scripts and programs in addition to the core MISA PERL script. The outline of the implemented workflow is as follows:
Periodically running scripts in PHP and UNIX shell monitor server load and schedule the execution of MISA analysis requests by users of the web site. Entries from the input fields of the web form are compiled into the two input files. The nucleotide sequences are combined into a single file in FASTA format (.fasta). The other entry fields are written to the MISA.ini file. If no parameters are specified by the user, preset default parameters as shown on the web site will be used.
After the conversion of input variables, the core PERL function MISA.pl is called. Upon its successful termination, the result files are compressed with UNIX gzip, and the archive is sent to a user-specified email address. A typical workflow is presented in Figure 1.
MISA-web can retrieve sequences from the NCBI database by specifying the corresponding accession numbers in the input field. MISA-web then communicates with the NCBI servers using PHP (www.php.net) and JQuery (www.jquery.com), downloads the sequences and reports them as FASTA sequence in the textbox. A comma-separated list of accession numbers can be entered to retrieve multiple sequences at once (up to a maximum sequence length of 2 Mb).
Publication 2017
Base Sequence Short Tandem Repeat
Once data is imported into R, the user can dynamically access and manipulate the population hierarchy with the function splitcombine(), subset the data set by population with popsub(), and check for cloned multilocus genotypes using mlg(). For data sets that include clones, the poppr function clonecorrect() will censor clones with respect to any level of a population hierarchy. In the case of missing data we use the commonly implemented, most parsimonious approach of treating missing states as novel alleles. This inherently makes analysis sensitive to missing data and genotyping error, but the user has tools available such as missingno() to filter out missing data at a per-individual or per-locus level. The user can also decide how uninformative loci (e.g., alleles occurring at minor frequencies; monomorphic loci; fixed heterozygous loci) are treated using the function informloci(). Thus, the user can specify a frequency for removal of uninformative loci. The user is encouraged to conduct analysis with and without missing data/uninformative loci to assess sensitivity to these issues when making inferences. A full list of functions available in poppr is provided in Table 1.
Typical analyses in poppr start with summary statistics for diversity, rarefaction, evenness, MLG counts, and calculation of distance measures such as Bruvo’s distance, providing a suitable stepwise mutation model appropriate for microsatellite markers (Bruvo et al., 2004 (link)). Poppr will define MLGs in your data set, show where they cross populations, and can produce graphs and tables of MLGs by population that can be used for further analysis with the R package vegan (Oksanen et al., 2013 ). Many of the diversity indices calculated by the vegan function diversity() are useful in analyzing the diversity of partially clonal populations. For this reason, poppr features a quick summary table (Table 2) that incorporates these indices along with the index of association, IA (Brown, Feldman & Nevo, 1980 (link); Smith et al., 1993 (link)), and its standardized form, r¯d , which accounts for the number of loci sampled (Agapow & Burt, 2001 (link)). Both measures of association can detect signatures of multilocus linkage and values significantly departing from the null model of no linkage among markers are detected via permutation analysis utilizing one of four algorithms described in Table 3 (Agapow & Burt, 2001 (link)). The user can specify the number of samples taken from the observed data set to obtain the null distribution expected for a randomly mating population. Detailed examples of these analyses can be found in the poppr manual.
Publication 2014
Alleles Clone Cells Heterozygote Hypersensitivity Mutation Short Tandem Repeat Vegan
PASTEC was developed in the REPET package [7] . In this context, we used PASTEC to classify the consensus TE sequences found de novo in a genome. PASTEC uses several features of TEs to classify TE consensus sequences. It searches for structural evidence and sequence similarities stored in a MySQL database obtained during a preprocessing step. The structural features considered are TE length, presence of a LTR (long terminal repeat) or TIR (terminal inverted repeat) detected with a custom-built tool (with a minimum length of 10 bp, a minimum identity of 80%, the taking into account of reciprocal orientations of terminal repeats and a maximal length of 7000 bp), the presence of SSRs (simple sequence repeats detected with the tandem repeat finder (TRF) tool [8] (link)), the polyA tail and an ORF (open reading frame). The blastx and tblastx routines are used to search for similarities to known TEs in Repbase Update, and the hmmer3 package [9] to search against a HMM profile databases (TE-specific or not), after translation in all six frames. Sequence similarities are also identified by blastn searches against known rDNA sequences, known host genes and known helitron ends. The databanks used are preprocessed and formatted. The Repbase Update for PASTEC can be downloaded from http://www.girinst.org/repbase/index.html, whereas the HMM profile databank formatted for PASTEC is available from the REPET download directory (http://urgi.versailles.inra.fr/download/repet/).
PASTEC classifies TEs by testing all classifications from Wicker's hierarchical TE classification system. Each possible classification is weighted according to the available evidence, with respect to the classification considered. TEs are currently classified to class and order level. PASTEC can also determine whether a TE is complete on the basis of four criteria: sequence coverage for known TEs, profile coverage, presence of terminal repeats for certain classes, presence of a polyA or SSR tail for LINEs and SINEs, and the length of the TEs with respect to expectations for the class concerned.
We designed PASTEC as a modular multi-agent classifier. The system is composed of four types of agents: retrievers, classifiers, filter agents, and a super-agent (Figure 1). The retriever agents retrieve the pre-computed analysis results stored in the MySQL database. They act on the requests of the classifier or filter agents, filtering, formatting and supplying the results. The classifier and filter agents are specialized to recognize a particular category. For example, the LTR agent can determine only whether the TE is a LTR or not. The classifier and filter agents act on the request of the super-agent, deciding whether they can classify the TE or not. For example, the LTR agent decides whether the consensus TE is a LTR on the basis of the following evidence: presence of the ENV (envelope protein) profile (a condition sufficient for classification), the presence of INT (integrase), RT (reverse transcriptase), GAG (capsid protein), AP (aspartate proteinase) and RH (RNase H) profiles together with the detection of a LTR (long terminal repeat), a blast match with the sequence of a known LTR retrotransposon. The super-agent resolves classification conflicts and formats the output file. It resolves conflicts by using a confidence index normalized to 100. For example, the LTR agent calculates a confidence index with the following rules: presence of ENV profiles (+2 because this condition is sufficient for classification), presence of a long terminal repeat and an INT, GAG, RT, RH or AP profile (+1 for each profile combined with the long terminal repeat), +1 for each profile (ENV, AP, RT, RH and GAG) found in the same frame in the same ORF. If the consensus matches at least one known LTR retrotransposon, the LTR agent adds +2 for each type of blast (blastx or tblastx) at the confidence index. Finally, the length of the TE is taken into account because we add +1 if the TE without the long terminal repeat is between 4000 and 15000 bp in length, and we decrease the confidence index by 1 if the TE without the long terminal repeat is less than 1000 bp or more than 15000 bp long. The super-agent uses the maximum confidence index defined for each classifier agent to normalize the confidence index for each classification to 100 and then compare the different classifications. Advanced users can edit all decisions rules and maximum confidence indices in the Decision_rules.yaml file.
The output can be read by humans and is biologist-friendly. A single line specifies the name of the TE, its length, status, class, order, completeness, confidence index and all the features characterizing it. A status of “potential chimeric” or “OK” is assigned to the TE. If the TE is not considered to be “OK” then users must apply their own expertise. A TE is declared “potential chimeric” when at least two classifications are possible. In this case, PASTEC chooses the best status based on the available evidence, or does not classify the TE if no decision is possible. In this last case, all possible classifications are given (separated by a pipe symbol “|”). We present an example of PASTEC output in table S1. PASTEC output is a tabular file, with the columns from left to right indicating the name of the TE, its length, the orientation of the sequence, chimeric/non-chimeric status (OK indicating that the element is not potentially chimeric), class (class I in this case), order. In the first line of the example provided, the TE is a LTR. We presume that the element is complete because we have no evidence to suggest that it is incomplete, and the confidence index is 71/100. The last column summarizes all the evidence found: coding sequence evidence, such as the results of tblastX queries against the Repbase database (TE_BLRtx evidence), blastX queries against the Repbase database (TE_BLRx evidence) and profiles. A blast match is taken account if coverage exceeds 5%, and a profile is taken into account if its coverage exceeds 20% (these parameters can be edited in the configuration file). For each item of coding sequence evidence, the coverage of the subject is specified. The structural evidence is also detailed: >4000 bp indicates that TE length without terminal repeats is between 4000 and 15000 bp, the next item of information presented in the comments columns is the presence of terminal repeats: we have a LTR in this case, with an LTR length of 433 bp; two long ORFs have been identified, the last of which contains four profiles in the same frame and is up to 3000 bp long. Other evidence provided for this example includes the partial match with a Drosophila melanogaster gene (coverage 16.55% and the TE contains 18% SSRs). The super-agent determines whether a TE is complete based on whether it is sufficiently long, whether the expected terminal repeats or polyA tail are present, whether blast match coverage exceeds 30% and profile coverage exceeds 75%. The second line of the example corresponds to a potentially chimeric TE, for which human expertise is required.
Publication 2014
Aspartate Capsid Proteins Chimera Consensus Sequence DNA, Ribosomal Drosophila melanogaster FCER2 protein, human Gene Products, env Genes Genome Homo sapiens Integrase Open Reading Frames Peptide Hydrolases Poly(A) Tail Poly A Reading Frames Retrotransposons Ribonuclease H RNA-Directed DNA Polymerase Short Interspersed Nucleotide Elements Short Tandem Repeat Tail Tandem Repeat Sequences Terminal Repeat Sequences

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Publication 2016
Biological Assay Biological Markers CD274 protein, human Cells Diploid Cell Disease Progression Gene Expression Genes Genome GZMA protein, human GZMB protein, human Immunohistochemistry Malignant Neoplasms Mutation Neoplasms Patients Pharmaceutical Preparations PRF1 protein, human Safety Short Tandem Repeat TBX21 protein, human Tissues Tumor Burden

Most recents protocols related to «Short Tandem Repeat»

Example 2

To identify genetic marker(s) associated with the ULA trait, test crosses of FC401 mutant #1 (MS4144) were made with variety Red Russian and the F1s were selfed to generate F2 seed. Three hundred and thirty seven F2 plants were grown in the field and the alkaloids were analyzed individually. Depending on the anatabine levels, the mapping populations were grouped into ULA plants and normal plants (FIG. 1). Genomic DNA from each of the plants was extracted individually. To run simple sequence repeat (SSR) markers, DNA samples from 23 F2 ULA plants and 24 normal anatabine plants were pooled separately.

PCR reactions were performed in 25 μl final volumes which contained 25-50 ng of template DNA, 12.5 μl 2× Amplitag PCR master mix ((Applied Biosystems [ABI]), 0.2 μM labeled primers (ABI), 1 μl 100% DMSO (Fisher Scientific), and 8 μl H2O (DNase/RNase free). Thermocycling conditions consisted of a 15 min incubation at 95° C.; followed by 34 cycles of 1 min at 94° C., 2 min at 60° C., 1 min at 72° C.; with a final reaction step of 60° C. for 30 min. All completed PCR reactions were diluted 1:50 with deionized water. Two microliters of diluted product was then combined with 9.75 μl HiDi Formamide (ABI) and 0.25 μl GeneScan 500 LIZ (ABI) size standard. Fragment analyses were performed. Samples were separated using a 36 cm capillary array in an ABI 3730 DNA Analyzer. Generated amplicons were analyzed using the “Local Southern Method” and the default analysis settings within GeneMapper v. 3.5 software (ABI). Final allele calls were standardized to an internal DNA control and based on the ABI 3730 DNA Analyzer.

Patent 2024
Alkaloids Alleles anatabine Capillaries Deoxyribonucleases DNA, Plant DNA Chips Endoribonucleases formamide Genetic Markers Genome Oligonucleotide Primers Plants Short Tandem Repeat Sulfoxide, Dimethyl
Simple sequence repeats (SSRs) across the 20 plastomes were identified using web-MISA [82 (link)] with the following parameters: ten repetitions for mononucleotide motifs, five for dinucleotide motifs, four for trinucleotide motifs and three for tetranucleotide, pentanucleotide and hexanucleotide motifs. The long dispersed repeats (LDRs): including forward (F), palindromic (P), reverse (R), and complement (C) repeats were identified using the online tool REPuter [83 (link)], with a Hamming distance of 3 and a minimum repeat size of 30 bp.
Publication 2023
Dinucleoside Phosphates Short Tandem Repeat
In order to get specific markers for the alien chromosome, we screened 197 wheat group-7-specific microsatellite markers reported by Somers et al. (2004) (link) and 88 pairs of sequence-tagged sites-polymerase chain reaction (STS-PCR) primers on wheat group-7 chromosomes (Supplementary Table S1). At the two-leaf stage, 27 plants of T14-44 and 25 plants of T14-42 were collected and separately pooled for RNA isolation using a TRIzol reagent (InvitrogenTM, Shanghai, China), followed by the treatment with DNase I (InvitrogenTM, Shanghai, China). The samples were sequenced using the Illumina Hiseq2500 platform (Berry Genomics, Beijing, China) to generate 125 bp pair-end reads. The de novo assembly of clean reads was performed by using the software Trinity 2.1.1 (Haas et al., 2013 (link)). The expression level was calculated by mapping reads to the assembled transcripts employing Trinity scripts, RSEM, and edgeR (Haas et al., 2013 (link)). The TransDecoder software package (https://sourceforge.net/projects/transdecoder/) was used to predict the coding region for these transcripts. The transcripts were annotated in the Swiss-Prot database using Blastx. The transcripts expressed in T14-44 but not in T14-42 were extracted. Then, the transcripts annotated as Nucleotide Binding Site–Leucine Rich Repeat (NBS-LRR) protein and protein kinases were used to design primers using the software Primer 5.0 (PREMIER Biosoft, San Francisco, CA, USA).
The conditions of the polymerase chain reaction (PCR) were as follows: initial denaturation at 94°C for 4 min, followed by 35 cycles of 30 s at 94°C, 30 s for annealing at 55°C–60°C, 1 min for extension at 72°C, and a final extension at 72°C for 10 min. Amplified PCR products were separated on 8% non-denaturing polyacrylamide gels stained with silver at 200 V for 1 h and 1.5% agarose gels stained with ethidium bromide at 150 V for approximately 25 min. The D2000 Plus DNA Ladder (GenStar, Beijing, China) and the 100 bp DNA Ladder (TianGen Biotech Co, Beijing, China) were used for the DNA marker in non-denaturing polyacrylamide gel and agarose gel electrophoresis, respectively.
Publication 2023
Adjustment Disorders Aliens Berries Binding Sites Chromosome Markers Chromosomes Deoxyribonuclease I Electrophoresis, Agar Gel Ethidium Bromide Gels isolation Leucine-Rich Repeat Proteins Markers, DNA Nucleotides Oligonucleotide Primers Plant Leaves Plants polyacrylamide gels Protein Kinases Sepharose Sequence Tagged Sites Short Tandem Repeat Silver Triticum aestivum trizol
Mice were housed in specific pathogen–free conditions in accordance with U.S. federal regulations and approved by Yale University’s Institutional Animal Care and Use Committee. Unless otherwise noted, experiments were conducted on male and female mice, aged 6–8 wk.
C57BL/6 (B6) mice were purchased from Charles River Laboratories. SMARTA Transgenic (TG[TCRLCMV]1Aox; STG) mice were obtained from Hans Hengartner at the University of Zürich, Switzerland (Oxenius et al., 1998 (link)). NZBWF1/J (NZBXW F1), Tg(CD4-Cre)1Cwi/BfluJ (CD4Cre+), B6.Cg-Tg(TcraTcrb)425Cbn/J (OT-II), B6.129P2-Tcrbtm1Mom/J (TCRβ), and B6(Cg)-Nfatc1/AoaJ (NFATc1 flox) mice were purchased from The Jackson Laboratory. B6.Sle1.Yaa mice were provided by E. Wakeland (University of Texas Southwestern Medical School, Dallas, TX, USA). CD4Cre+ mice were crossed with Nfatc1 flox mice to generate CD4Cre+.Nfatc1fl/fl mice. CD4Cre+.Nfatc1fl/fl were crossed with B6.Sle1.Yaa mice to generate CD4Cre+.Nfatc1fl/f.B6.Sle1.Yaa mice. The presence of the intact Sle1 locus was confirmed by microsatellite screening within the locus including D1Mit15, D1Mit17, D1Mit47, D1Mit202, D1Mit113, D1Mit206, D1Mit353, D1Mit407, D1Mit105, D1Mit274, D1Mit400, and D1Mit541 (Morel et al., 2000 (link)).
Publication 2023
Animals, Transgenic Antigen T Cell Receptor, beta Chain Females Institutional Animal Care and Use Committees Males Mice, Laboratory Rivers Short Tandem Repeat Specific Pathogen Free
NB is a traditional lowland indica cultivar that originated in India and is resistant to BSR caused by Burkholderia glumae. KO is a modern lowland rice cultivar released in Japan and is susceptible to BSR27 (link). To analyse RBG1res, by crossing SL535 with KO and using marker-assisted selection to remove nontarget DNA regions, we successfully developed a NIL homozygous for RBG1res. The resulting RBG1res-NIL contains approximately 380 kb from NB on the short arm of chromosome 10 (between simple sequence repeat (SSR) markers RM474 and RM7361-1; Supplementary Table S3). By screening 3072 M2 lines of KO mutagenized with N-methyl-N-nitrosourea according to a method described previously31 (link), we identified a null mutant (Mut-W56*) whose sequence encoding tryptophan at position 56 was changed such that a stop codon was introduced that produces a truncated protein (5.5 kD). Genomic DNA of the M2 plants was screened with the NB51 primer set listed in Supplementary Table S3 by the targeting induced local lesions in genomes (TILLING) method as described earlier52 (link). All of the experimental research and field studies on plants (either cultivated or wild), including transgenic plant materials, complied with relevant institutional, national, and international guidelines and legislation.
Publication 2023
Burkholderia glumae Chromosomes, Human, Pair 10 Codon, Terminator DNA, Plant Genome Homozygote Nitrosourea Compounds Oligonucleotide Primers Plants Plants, Transgenic Proteins Rice Short Tandem Repeat Tryptophan

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More about "Short Tandem Repeat"

Short Tandem Repeats (STRs), also known as microsatellites, are a type of genetic marker characterized by the repetition of short DNA sequences within the genome.
These repetitive elements are widely used in various fields, including forensics, genetic linkage analysis, and population genetics, due to their high level of polymorphism and codominant inheritance.
STR analysis is a powerful tool for researchers to study genetic diversity and inheritance patterns.
It involves the amplification and comparison of these repeating units, allowing for the identification of individuals and the establishment of familial relationships.
The technique is often utilized in combination with cell culture media, such as DMEM (Dulbecco's Modified Eagle's Medium), RPMI 1640 (Roswell Park Memorial Institute) medium, and supplements like Penicillin/Streptomycin, to ensure optimal cell growth and proliferation during genetic analysis.
In addition to these applications, STRs have also been employed in the study of various cell lines, including the well-known breast cancer cell lines MDA-MB-231 and MCF-7.
The MycoAlert Mycoplasma Detection Kit can be used to ensure that these cell cultures are free from mycoplasma contamination, which can impact genetic analysis.
By understanding the key aspects of Short Tandem Repeats and their diverse applications, researchers can enhance the reproducibility and accuracy of their studies, leveraging the latest advancements in AI-driven analysis tools like PubCompare.ai to identify the best protocols and solutions for their research needs.