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> Genes & Molecular Sequences > Nucleotide Sequence > Conserved Sequence

Conserved Sequence

Conserved Sequence refers to regions within nucleic acid or protein sequences that are highly preserved across different species or variants.
These conserved sequences often play critical roles in biological functions, such as protein structure, enzymatic activity, or regulatory mechanisms.
Identifying and analyzing conserved sequences is a fundamental approach in comparative genomics, evolutionary biology, and functional genomics research.
Understanding the conservation patterns of sequences can provide insights into the evolutionary history, structural constraints, and functional importance of genetic elements.
The study of conserved sequences is essential for a wide range of applications, including phylogenetic analyses, the identification of functional domains, the prediction of secondary and tertiary structures, and the development of targeted therapeutic interventions.
Researchers can leverage the power of PubCompare.ai's AI-driven platform to streamline the process of locating the best protocols from literature, preprints, and patents, empowering their research with reproducible results and a seamless workflow.
Experiene the future of Conserved Sequence analysis today.

Most cited protocols related to «Conserved Sequence»

1
Amplification and Sequencing of 16S rRNA V3-V4 Region
The 16S rRNA gene consists of nine hypervariable regions flanked by regions of more conserved sequence. To maximize the effective length of the MiSeq’s 250PE and 300PE sequencing reads, a region of approximately 469 bp encompassing the V3 and V4 hypervariable regions of the 16S rRNA gene was targeted for sequencing. This region provides ample information for taxonomic classification of microbial communities from specimens associated with human microbiome studies and was used by the Human Microbiome Project [5 (link)], however, the approach described could be adapted to any primer pairs.
To amplify and sequence the V3-V4 hypervariable region of the 16S rRNA gene, primers were designed that contained: 1) a linker sequence allowing amplicons to bind to the flow cell and be sequenced using the standard Illumina HP10 or HP11 (Illumina, San Diego, CA, USA) sequencing primers; 2) a 12 bp index sequence; 3) a 0 to 7 bp “heterogeneity spacer” that we designed in this study to mitigate the issues caused by low sequence diversity amplicons (Additional file 1: Figure S1C); and 4) 16S rRNA gene universal primers (Figure 1A and Additional file 2). Genomic DNA extracted from clinical vaginal and anal swabs were amplified, normalized using the SequalPrep Normalization Kit (Life Technologies, Carlsbad, CA, USA) and pooled (11 pools with 271 to 426 samples per pool) prior to sequencing on the MiSeq platform (see Additional file 3 and Table 1 for number of samples per pools). The amplicon pools were prepared for sequencing with AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA) and the size and quantity of the amplicon library were assessed on the LabChip GX (Perkin Elmer, Waltham, MA, USA) and with the Library Quantification Kit for Illumina (Kapa Biosciences, Woburn, MA, USA), respectively. PhiX Control library (v3) (Illumina) was combined with the amplicon library (expected at 20%). The library was clustered to a density of approximately 570 K/mm2. The libraries were sequenced either on 250PE or 300PE MiSeq runs and one library was sequenced with both protocols using the standard Illumina sequencing primers (Figure 1A), eliminating the need for a third (or fourth) index read. Sequencing data was available within approximately 48 hours. Image analysis, base calling and data quality assessment were performed on the MiSeq instrument.
Fadrosh D.W., Ma B., Gajer P., Sengamalay N., Ott S., Brotman R.M, & Ravel J. (2014). An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform. Microbiome, 2, 6.
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Publication 2014
Anus Cells Conserved Sequence DNA Library Genes Genetic Heterogeneity Genome Human Microbiome Microbial Community Oligonucleotide Primers Ribosomal RNA Genes RNA, Ribosomal, 16S Vagina
2
De Novo Primer Design and Evaluation
De novo design of primers is performed by finding short conserved sequences in a given multiple sequence alignment to act as a 3′ binding site for new primers. Once these sites have been identified, full-length forward or reverse de novo primers are generated by incorporating the N upstream or downstream bases, where N is 15 by default. De novo full-length primers can then be sorted according to sensitivity, specificity or degeneracy, and compared with known primers to find matches or significant overlap. Specificity for particular target groups, such as archaea, can be obtained by supplying an optional alignment of sequences from which to exclude matches.
Primer analyses, including the prediction of taxonomic coverage, rely upon scoring primers against target sequences. To predict its taxonomic coverage, a primer is locally aligned to full-length target sequences with known taxonomies, and scored based on gap, 3′ mismatch and non-3′ mismatch counts. An example of the graphical output is provided in Supplementary Figure S3. The final five bases are considered to be the 3′ region by default, and are considered to be the most important for PCR amplification. The scoring scheme is parameterizable. The RDP Classifier (Wang et al., 2007 (link)) is used to classify the resulting sequence fragments, and the accuracy is displayed both in terms of which taxa are amplified and in terms of classification level of the resulting fragments. PrimerProspector supports retraining of the RDP Classifier for taxa coverage analysis based on different reference taxonomies.
Descriptions of the scripts included in PrimerProspector, the various outputs generated by PrimerProspector and an example based on the F515/R806 primer pair are included in the online documentation at http://pprospector.sourceforge.net/.
Walters W.A., Caporaso J.G., Lauber C.L., Berg-Lyons D., Fierer N, & Knight R. (2011). PrimerProspector: de novo design and taxonomic analysis of barcoded polymerase chain reaction primers. Bioinformatics, 27(8), 1159-1161.
Publication 2011
Archaea Base Pairing Binding Sites Conserved Sequence Hypersensitivity Oligonucleotide Primers Sequence Alignment
3
Multiplex Sequencing of 16S rRNA V6 Region
We amplified three separate replicates of the V6 region of ribosomal RNAs from Escherichia coli (E. coli) genomic DNA isolated from pure culture and from 10 metagenomic microbial DNA samples isolated from raw sewage. Custom fusion primers for PCR consisted of the Illumina adaptor, 12 different inline barcodes (forward primer) or 8 dedicated indices (reverse primer), and conserved regions of the V6 sequence (Figure 1). This use of 96 unique barcode-index combinations allows multiplexing 96 samples per lane. Paired indices with dual indexing reads could further increase the level of multiplexing. For each of the 33 libraries, we carried out the PCR in triplicate 33 uL reaction volumes with an amplification cocktail containing 1.0 U Platinum Taq Hi-Fidelity Polymerase (Life Technologies, Carlsbad CA), 1X Hi-Fidelity buffer, 200 uM dNTP PurePeak DNA polymerase mix (Pierce Nucleic Acid Technologies, Milwaukee, WI), 1.5 mM MgSO4 and 0.2 uM of each primer. We added approximately 10–25 ng template DNA to each PCR and ran a no-template control for each primer pair. Cycling conditions were: an initial 94°C, 3 minute denaturation step; 30 cycles of 94°C for 30s, 60°C for 60s, and 72°C for 90s; and a final 10 minute extension at 72°C. The triplicate PCR reactions were pooled after amplification and purified using a Qiaquick PCR 96-well PCR clean up plate (Qiagen, Valencia CA). Purified DNA was eluted in 30 uL of Qiagen buffer EB. PicoGreen quantitation (Life Technologies, Carlsbad CA) provided a basis for pooling equimolar amounts of product. After size-selecting products of 200–240 bp on 1% agarose using Pippin Prep (SageScience, Beverly MA), we employed qPCR (Kapa Biosystems, Woburn MA) to measure concentrations prior to sequencing on one lane of an Illumina Hiseq 100 cycle paired-end run. The remaining 90% of the lane was dedicated to PhiX DNA and served as the run control. The combination of CASAVA 1.8.2 to identify reads by index and a custom Python script that resolved barcodes demultiplexed the datasets.
Eren A.M., Vineis J.H., Morrison H.G, & Sogin M.L. (2013). A Filtering Method to Generate High Quality Short Reads Using Illumina Paired-End Technology. PLoS ONE, 8(6), e66643.
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Publication 2013
Buffers Conserved Sequence DNA-Directed DNA Polymerase Escherichia coli Genome Metagenome Nucleic Acids Oligonucleotide Primers PicoGreen Platinum Python Ribosomal RNA Sepharose Sewage Sulfate, Magnesium Taq Polymerase
4
Curating Transposable Elements in Rice Genome
Manual curation of TEs in rice was started after the release of the map-based rice genome [22 (link)]. Repetitive sequences in the rice genome were compiled by RECON [44 (link)] with a copy number cutoff of 10. Details for manual curation of LTR sequences were previously described in the LTR_retriever paper [40 (link)]. In brief, for the curation of LTR retrotransposons, we first collected known LTR elements and used them to mask LTR candidates. Unmasked candidates were manually checked for terminal motifs, TSD sequences, and conserved coding sequences. Terminal repeats were aligned with extended sequences, from which candidates were discarded if alignments extended beyond their boundaries. For the curation of non-LTR retrotransposons, new candidates were required to have a poly-A tail and TSD. We also collected 13 curated SINE elements from [53 (link)] to complement our library.
For curation of DNA TEs with TIRs, flanking sequences (100 bp or longer, if necessary) were extracted and aligned using DIALIGN2 [72 (link)] to determine element boundaries. A boundary was defined as the position to which sequence homology is conserved over more than half of the aligned sequences. Then, sequences with defined boundaries were manually examined for the presence of TSD. To classify the TEs into families, features in the terminal and TSD sequences were used. Each transposon family is associated with distinct features in their terminal sequences and TSDs, which can be used to identify and classify elements into their respective families [14 (link)]. For Helitrons, each representative sequence requires at least two copies with intact terminal sequences, distinct flanking sequences, and inserts into “AT” target sites.
To make our non-redundant curated library, each new TE candidate was first masked by the current library. The unmasked candidates were further checked for structural integrity and conserved domains. For candidates that were partially masked and presented as true elements, the “80-80-80” rule (≥ 80% of the query aligned with ≥ 80% of identity and the alignment is ≥ 80 bp long) was applied to determine whether this element would be retained. For elements containing detectable known nested insertions, the nested portions were removed and the remaining regions were joined as a sequence. Finally, protein-coding sequences were removed using the ProtExcluder package [73 (link)]. The curated library version 6.9.5 was used in this study and is available as part of the EDTA toolkit.
Ou S., Su W., Liao Y., Chougule K., Agda J.R., Hellinga A.J., Lugo C.S., Elliott T.A., Ware D., Peterson T., Jiang N., Hirsch C.N, & Hufford M.B. (2019). Benchmarking transposable element annotation methods for creation of a streamlined, comprehensive pipeline. Genome Biology, 20, 275.
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Publication 2019
Conserved Sequence DNA Library Edetic Acid Exons Genome Insertion Mutation Jumping Genes Open Reading Frames Oryza sativa Poly(A) Tail Repetitive Region Retrotransposons Short Interspersed Nucleotide Elements Tay-Sachs Disease Terminal Repeat Sequences
5
Identifying Core Genome in Pseudomonas aeruginosa
For the purposes of this study, the core genome was defined as those sequences present in nearly all genomes from bacteria of a given species. Spine, a program wrapper written in Perl was developed to identify core genome from genomic DNA sequences (Figure 1). The software is available as a web-based application or for download as a command-line script [48 ]. Spine identifies core genome sequences by first performing genome alignments of user-supplied reference strain sequences using the NUCmer function of the MUMmer software package v3.23 [97 (link), 98 (link)]. An all-vs.-all alignment of the reference strains is performed using the “--maxmatch” option to preserve all unique and non-unique matches. Otherwise default NUCmer parameters are used. The resulting alignment file is converted to alignment coordinates and sorted by reference ID using MUMmer’s “show-coords” function. Spine then outputs DNA sequence and genomic coordinates of regions present in a user-defined subset of the reference genomes using the NUCmer alignment coordinate file and the sequences of the reference genomes. For this study of twelve P. aeruginosa reference genomes, only alignments with at least 85% sequence identity were considered homologous. Note that this analysis allows for and includes as core those conserved sequences that are duplicated or repeated in certain strains. Spine also outputs accessory genome sequences and their genomic coordinates (see below). An individual annotated P. aeruginosa gene was categorized as core if ≥ 50% of the nucleotide sequence of that gene was contained within the core coordinate set or as accessory if > 50% of the gene sequence was contained within the accessory coordinate set. For the core genome description, sequence and gene definitions from the annotated PA14 genome were used primarily, i.e. genomic sequence regions in PA14 found to have homologous regions in at least 10 of the other reference strains and the annotated genes in those PA14 regions were used to define most of the core sequence. PAO1 genomic sequence was used for core regions found in 10 of the reference genomes, but not PA14.
The alignments generated by Spine were also used to estimate nucleotide core genome and pangenome size based on an adaptation of a method described by Tettelin et al. [32 (link)]. Briefly, all possible combinations of sequential inclusion of up to twelve reference strains were evaluated to determine the impact on the amount of conserved sequence present in the included genomes (“core genome”) and the amount of unique sequence among the included genome sequences (“pangenome”). Locations of core and accessory genomic regions in the P. aeruginosa pangenome were plotted using the program CGView [99 (link)].
Ozer E.A., Allen J.P, & Hauser A.R. (2014). Characterization of the core and accessory genomes of Pseudomonas aeruginosa using bioinformatic tools Spine and AGEnt. BMC Genomics, 15(1), 737.
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Publication 2014
Acclimatization Base Sequence Conserved Sequence Genes Genome Genome, Bacterial Nucleotides PRO 140 Pseudomonas aeruginosa Sequence Alignment Strains Vertebral Column

Most recents protocols related to «Conserved Sequence»

1
De Novo Motif Analysis of Histone Modifications
Because it has been suggested that motif analysis can facilitate the discovery of unanticipated sequence signals such as transcription factor binding sites associated with histone modifications (Bailey et al., 2013 (link); Ruiz et al., 2019 (link); Chen et al., 2020 (link)), we performed de novo motif analysis for H3K4me3, H3K27me3 and bivalent domains. We first extracted a list of sequences that are 50 bp upstream and 50 bp downstream from the summits of the top 500 peaks overlapping with TSS regions (Niu et al., 2018 (link)). We then used the list as input to search for conserved sequence motifs, using motif elicitation (MEME)-ChIP (Bailey et al., 2009 (link)) software with default parameters. We used TOMTOM (Khan et al., 2018 (link)) with default settings to match discovered motifs to the JASPAR database (Fornes et al., 2020 (link)). Finally, we used FIMO (Hertz and Stormo, 1999 (link); Grant et al., 2011 (link)) to map motif prediction, and visualize genomic locations of the motifs in gene list as described above.
Zhao Y., Hu J., Wu J, & Li Z. (2023). ChIP-seq profiling of H3K4me3 and H3K27me3 in an invasive insect, Bactrocera dorsalis. Frontiers in Genetics, 14, 1108104.
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Publication 2023
Binding Sites Conserved Sequence DNA Chips Genes Genome Histone Code histone H3 trimethyl Lys4 Transcription Factor
2
Cloning and Sequencing of Triterpene Synthase Genes
Plant total RNA was extracted from the roots by RNAprep pure plant kit (DP441, TIANGEN). 1 µg total RNA was used for first strand cDNA synthesis with HiScript® III 1st Strand cDNA Synthesis Kit (+gDNA wiper) (R312, Vazyme). In addition, in order to obtain the OSC core sequence of P. chinensis and P. cernua, we first used the primers reported in previous studies (Guhling et al., 2006 (link)), and the sequences were listed in Supplementary Table S1. Undesirably, these primers were not suitable for OSCs of P. chinensis and P. cernua. Therefore, we designed primers based on highly conserved regions of OSC protein sequences deposited in GenBank used Condehop, which were degenerate at the 3′ core region, and non-degenerate at the 5′ consensus clamp region. The primer sequences were listed in Supplementary Table S1. The degenerate PCR primers F1&R1 and PrimeSTAR® high-fidelity PCR enzyme (R045A, Takara) were used to obtain the core sequence of OSCs by touchdown PCR: 3 min 94°C, (10 s 98°C, 15 s 55°C, 30 s 72°C) × 10 cycles, (10 s 98°C, 5 s 55°C, 30 s 72°C) × 25 cycles, 5 min final extension at 72°C. The resulting PCR products were separated by 1% agarose gel electrophoresis and extracted using the V-ELUTE Gel Mini Purification Kit (ZPV202, ZOMANBIO). Then the purified products were recombined into the pLB vector (VT206, TIANGEN) and transformed into Escherichia coli TOP10 competent cells. The positive clones were sequenced by Sangon Biotech.
5′ and 3′ flanking fragment sequences of OSC were obtained by HiScript-TS 5′/3′ RACE Kit (RA101, Vazyme). Firstly, 5′ RACE-Ready cDNA and 3′ RACE-Ready cDNA were synthesized. Then the 5′ RACE-Ready cDNAs, 10 × Universal Primer Mix (UPM), 5′ GSP Primer R2 were used to extend the 5′ flanking fragment of OSC, and the 3′ RACE-Ready cDNAs, 10 × Universal Primer Mix (UPM), 3′ GSP Primer R2 for 3′ flanking fragment. 5′ GSP-Primer R2 and 3′ GSP-Primer R2 were synthesized according to the obtained OSC core sequence (Supplementary Table S1). All RCR programs used in this stage were referenced in the kit instruction manual. The PCR products were purified, recombined, and finally transformed into E. coli TOP10 competent cells. The positive clones were sequenced by Sangon Biotech.
Liu X., Xu Y., Di J., Liu A, & Jiang J. (2023). The triterpenoid saponin content difference is associated with the two type oxidosqualene cyclase gene copy numbers of Pulsatilla chinensis and Pulsatilla cernua. Frontiers in Plant Science, 14, 1144738.
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Publication 2023
3' Flanking Region Anabolism Cells Clone Cells Cloning Vectors Conserved Sequence DNA, Complementary Electrophoresis, Agar Gel Enzymes Escherichia coli Oligonucleotide Primers Osteopathia striata cranial sclerosis Plant Roots Plants Protein Domain
3
Multiplex Real-Time PCR Assay for Meloidogyne Nematodes
Primers and beacons were designed using Beacon Designer 8 (Premier Biosoft, Palo Alto, CA). Alignments of HSP90 gene sequences (Table 1) were used to find universally conserved primer sequences surrounding polymorphic regions in M. chitwoodi, M. fallax, and M. minor (Skantar and Carta, 2004 (link)). To ensure the beacon probes and primers were specific to their target organisms, the sequences were queried using the BLASTn search program and the non-redundant database (National Center for Biotechnology Information, NCBI). Primers and the beacons for the HSP90 region were synthesized by Sigma-Aldrich (St. Louis, Mo) and are described in Table 2. The M. chitwoodi beacon has 6-FAM, M. fallax beacon has HEX, and M. minor beacon has Cyan-5 as the reporters. For the quenchers, the Black Hole Quencher (BHQ-1 for 6-FAM and HEX, and BHQ- 3 for Cyan-5) was used.
Anderson S.D, & Gleason C.A. (2023). A molecular beacon real-time polymerase chain reaction assay for the identification of M. chitwoodi, M. fallax, and M. minor. Frontiers in Plant Science, 14, 1096239.
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Publication 2023
Conserved Sequence Genes HSP90 Heat-Shock Proteins Neutrophil Oligonucleotide Primers Sequence Alignment
4
Identification and Characterization of Laccase Gene Family in Camellia sinensis
A total of 17 Arabidopsis laccase members containing Cu-oxidase (PF00394), Cu-oxidase_2 (PF07731), and Cu-oxidase_3 (PF07732) domains were obtained [23 (link)]. To identify the CsLAC gene family in the Camellia sinensis ‘Shuchazao’ genome [5 (link)], BLASTp was performed using AtLAC protein sequences as queries, and sequences with an E-value < 10–10 were retained. The obtained candidate sequences with no conserved laccase domain were deleted and gene family identification was performed using the SMART (http://smart.embl-heidelberg.de/) and Pfam (http://pfam.xfam.org/) databases. A total of 51 unique CsLAC genes were identified, which were named from CsLAC1 to CsLAC51 based on their chromosomal location. The CDs and protein sequences of the 51 CsLAC genes are listed in Additional file 1: Table S1. To further explore the characteristics of their domain-containing proteins, the ExPasy program (http://web.expasy.org/protparam/) was used to calculate the molecular weight (MW) and isoelectric point (pI), and the online software Cell-PLoc 2.0 (http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc-2/) was used to predict their subcellular localization.
Zhu J., Zhang H., Huang K., Guo R., Zhao J., Xie H., Zhu J., Gu H., Chen H., Li G., Wei C, & Liu S. (2023). Comprehensive analysis of the laccase gene family in tea plant highlights its roles in development and stress responses. BMC Plant Biology, 23, 129.
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Publication 2023
Amino Acid Sequence Arabidopsis Camellia sinenses Cells Chromosomes Conserved Sequence Genes Genes, vif Genome Laccase Oxidases Protein Domain
5
Bioinformatic Analysis of CsLAC Genes
The exon‒intron structures were determined using the Gene Structure Display Server (http://gsds.gao-lab.org/). The conserved motifs of CsLAC protein sequences were analyzed by the MEME (http://meme-suite.org/tools/meme) program with previously described parameter settings and finally viewed by TBtools [25 (link)]. To determine the cis-elements, we obtained the 2000-bp sequence upstream from each CsLAC initiation codon and predicted their cis-elements using the online tool PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) as described previously [26 (link), 27 (link)].
Zhu J., Zhang H., Huang K., Guo R., Zhao J., Xie H., Zhu J., Gu H., Chen H., Li G., Wei C, & Liu S. (2023). Comprehensive analysis of the laccase gene family in tea plant highlights its roles in development and stress responses. BMC Plant Biology, 23, 129.
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Publication 2023
Codon, Initiator Conserved Sequence Exons Genetic Structures Introns

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More about "Conserved Sequence"

Conserved Sequences are regions within nucleic acid or protein sequences that are highly preserved across different species or variants.
These conserved regions often play crucial roles in biological functions, such as protein structure, enzymatic activity, and regulatory mechanisms.
Identifying and analyzing conserved sequences is a fundamental approach in comparative genomics, evolutionary biology, and functional genomics research.
Understanding the conservation patterns of sequences can provide insights into the evolutionary history, structural constraints, and functional importance of genetic elements.
The study of conserved sequences is essential for a wide range of applications, including phylogenetic analyses, the identification of functional domains, the prediction of secondary and tertiary structures, and the development of targeted therapeutic interventions.
Researchers can leverage the power of PubCompare.ai's AI-driven platform to streamline the process of locating the best protocols from literature, preprints, and patents, empowering their research with reproducible results and a seamless workflow.
This platform can help researchers analyze and compare conserved sequences across various species, identify key structural motifs, and develop targeted interventions.
The process of conserved sequence analysis may involve the use of various tools and reagents, such as TRIzol reagent for RNA extraction, PMD18-T and PMD19-T vectors for cloning, Primer Premier 5.0 for primer design, PGEM-T Easy vector for T-A cloning, QIAamp Viral RNA Mini Kit for viral RNA purification, Dual-Luciferase Reporter Assay System for gene expression analysis, Primer Explorer V5 for primer design, PrimeScript RT reagent kit for reverse transcription, and Lipofectamine 3000 for transfection.
Experiene the future of Conserved Sequence analysis today with the help of PubCompare.ai's innovative platform.