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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/45286?offset=20</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44848/trust-but-verify-sequencing-your-cell-lines-might-reveal-an-uninvited-guest</guid>
	<pubDate>Wed, 04 Jun 2025 00:07:57 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44848/trust-but-verify-sequencing-your-cell-lines-might-reveal-an-uninvited-guest</link>
	<title><![CDATA[Trust But Verify: Sequencing Your Cell Lines Might Reveal an Uninvited Guest]]></title>
	<description><![CDATA[<p>High-throughput sequencing has become indispensable in cell biology, enabling detailed insights into chromatin structure, gene expression, and regulatory dynamics. Yet, when faced with unexpectedly low mapping rates to the human genome, researchers often rush to troubleshoot technical parameters&mdash;sequencer quality, adapter trimming, or aligner settings.</p><p>Before you go down that path, consider this critical biological question:<br /> <strong>Are you sequencing human cells&mdash;or bacterial contamination?</strong></p><h2>The Silent Saboteur: Mycoplasma in Cell Cultures</h2><p><em>Mycoplasma</em> contamination remains one of the most widespread and underdiagnosed issues in tissue culture work. Studies suggest that <strong>15&ndash;35% of cell lines in use may be contaminated</strong>, often without visible signs. Unlike other microbial infections, <em>Mycoplasma</em> does not produce cloudiness, odor, or a change in pH. Many researchers won&rsquo;t detect it unless they specifically test for it.</p><p>The consequences, however, are profound. <em>Mycoplasma</em> can significantly alter:</p><ul>
<li>
<p>Host gene expression patterns</p>
</li>
<li>
<p>Cell proliferation rates</p>
</li>
<li>
<p>Epigenetic profiles and chromatin accessibility</p>
</li>
<li>
<p>Cytokine signaling and immune responses</p>
</li>
</ul><p>In short, it can skew your results, compromise your biological conclusions, and invalidate weeks or months of research.</p><h2>A Simple Diagnostic Step: Map Against <em>Mycoplasma</em> Genomes</h2><p>If you encounter poor alignment rates to the human genome, consider mapping your reads to a <em>Mycoplasma</em> reference genome&mdash;or better yet, use a <strong>combined human + <em>Mycoplasma</em></strong> reference. There have been cases where over half of all reads, initially assumed to be from human cells, were in fact bacterial in origin. This check is fast, easy, and could save your project.</p><h2>How Contamination Happens&mdash;and Persists</h2><p><em>Mycoplasma</em> is small (0.1&ndash;0.3 &mu;m), lacks a cell wall, and can pass through standard filters undetected. Common sources include:</p><ul>
<li>
<p>Contaminated reagents (e.g., FBS)</p>
</li>
<li>
<p>Infected cell lines obtained from other labs</p>
</li>
<li>
<p>Poor aseptic technique or shared equipment</p>
</li>
</ul><p>Once present, it spreads quickly between cultures and can persist for months, silently affecting results.</p><h2>Why Treatment Is Difficult</h2><p>While antibiotics such as Plasmocin or BM-Cyclin are sometimes used, they often offer only partial resolution and may themselves alter cell behavior. In many cases, the best course of action is to <strong>discard the contaminated culture</strong> and start with a fresh, verified stock.</p><h2>Practical Recommendations for Researchers</h2><ul>
<li>
<p><strong>Routinely test for <em>Mycoplasma</em></strong> using PCR, qPCR, or fluorescence-based assays</p>
</li>
<li>
<p><strong>Incorporate contamination screens into your sequencing QC pipeline</strong></p>
</li>
<li>
<p><strong>Use combined reference genomes</strong> when mapping ambiguous reads</p>
</li>
<li>
<p><strong>Practice strict aseptic technique</strong> and monitor all incoming cell lines</p>
</li>
<li>
<p><strong>Don&rsquo;t ignore unexplained data anomalies</strong>&mdash;they might point to contamination</p>
</li>
</ul><h2>Closing Thought: Contamination Is a Biological Variable</h2><p>It&rsquo;s easy to view poor mapping as a technical issue, but sometimes the problem lies deeper&mdash;in the biology itself. <em>Mycoplasma</em> contamination doesn&rsquo;t just interfere with sequencing; it interferes with science. As a research community, we must treat contamination not as an afterthought, but as a key variable to control.</p><p>So next time your reads won&rsquo;t align, don&rsquo;t just tune the aligner. Ask if your cells are telling the truth&mdash;or if they're hiding something.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</guid>
	<pubDate>Fri, 21 Feb 2020 00:17:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41207/blobtoolkit-a-toolkit-for-genome-assembly-qc</link>
	<title><![CDATA[BlobToolKit: A toolkit for genome assembly QC]]></title>
	<description><![CDATA[<p>Filtering raw genomic datasets is essential to avoid chimeric assemblies and to increase the validity of sequence-based biological inference. BlobToolKit extends the BlobTools<span>1</span>/Blobology<span>2</span>&nbsp;approach to simplify interactive and reproducible filtering.</p>
<p>BlobToolKit is comprised of four components:</p>
<ol>
<li><a href="https://blobtoolkit.genomehubs.org/btk-viewer/">BlobToolKit Viewer</a>&nbsp;allows browser-based interactive visualisation and filtering of preliminary or published genomic datasets even for highly fragmented assemblies.</li>
<li><a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;is a command-line program to convert assemblies and analysis results into datasets that can be further processed using&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and/or visualised in the Viewer.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/specification/">BlobToolKit Specification</a>&nbsp;features a formal schema and validator for the JSON-based BlobDir format used by&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>&nbsp;and the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
<li>The&nbsp;<a href="https://blobtoolkit.genomehubs.org/pipeline/">BlobToolKit Pipeline</a>&nbsp;is a configurable Snakemake pipeline that automates all steps from retrieving public datasets through running analyses and generating a BlobDir dataset with&nbsp;<a href="https://blobtoolkit.genomehubs.org/blobtools2/">BlobTools2</a>, ready for visualisation in the&nbsp;<a href="https://blobtoolkit.genomehubs.org/btk-viewer/">Viewer</a>.</li>
</ol>
<p>Paper&nbsp;<a href="https://www.biorxiv.org/content/10.1101/844852v1.full.pdf">https://www.biorxiv.org/content/10.1101/844852v1.full.pdf</a></p><p>Address of the bookmark: <a href="https://blobtoolkit.genomehubs.org/" rel="nofollow">https://blobtoolkit.genomehubs.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4183/320000-viruses-in-mammals-yet-to-sequenced-in-future</guid>
	<pubDate>Tue, 03 Sep 2013 08:35:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4183/320000-viruses-in-mammals-yet-to-sequenced-in-future</link>
	<title><![CDATA[320000 viruses in mammals yet to sequenced in future!!!]]></title>
	<description><![CDATA[<p>With current biological technique improvements, finally it is now possible to look at millions of unknown viruses at genomic level and understand the mechanism. According to available data, close to 70 per cent of emerging viral diseases such as HIV/AIDS, West Nile, Ebola, SARS, and influenza, are zoonoses - infections of animals that cross into humans.</p><p>To address the challenges of describing and estimating virodiversity, a team of investigators from Center for Infection and Immunity (CII) and EcoHealth Alliance began in jungles of Bangladesh - home to the flying fox.</p><p>Reference:</p><p><a href="http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms">http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms</a></p><p><a href="http://www.bbc.co.uk/news/science-environment-23932400">http://www.bbc.co.uk/news/science-environment-23932400</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</guid>
	<pubDate>Thu, 09 Apr 2020 18:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/41562/submit-your-sars-cov-2-sequence-data-to-genbank</link>
	<title><![CDATA[Submit your SARS-CoV-2 sequence data to GenBank]]></title>
	<description><![CDATA[<div dir="auto">Submit your SARS-CoV-2 sequence data to GenBank and SRA with our new submission landing page. Submission is simple and streamlined *and* there&rsquo;s a rapid turnaround. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fsubmit.ncbi.nlm.nih.gov%2Fsarscov2%2F%3Ffbclid%3DIwAR3p-OzZPe2yx4CZMoZxiWMF3kUQjXyVVduNQhBdehWmFTJ3cPBstsOLypI&amp;h=AT2d-umit7ciXRW-nrRYVL3gJSLKY4Hte8W8cXw8Wl94n6PGmoHmVqvvhgQj-mTo6A5lpMP9JDV_lRSq9RRLT5KeVVAAfcuRgJOeA6QhApIB2B9nFxUfDCD3sio4HYidpRwpmng&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://submit.ncbi.nlm.nih.gov/sarscov2/</a></span></div><div dir="auto">&nbsp;</div><div dir="auto"><span><span>Quickly and easily add your SARS-CoV-2 sequence data to the growing public archive with new, special features and support from NCBI. </span><a href="https://submit.ncbi.nlm.nih.gov/sarscov2/">new SARS-CoV-2 sequence submission landing page</a><span>&nbsp;will help you get started. GenBank submissions are accessioned and released in approximately 1-2 working days, and&nbsp;</span><a href="https://www.ncbi.nlm.nih.gov/sra" target="_blank">Sequence Read Archive</a><span>&nbsp;(SRA) submissions typically processed and released within hours. Submission is simple!</span></span></div><div><div dir="auto">&nbsp;</div><div dir="auto">More information is available on NCBI Insights. <span><a href="https://l.facebook.com/l.php?u=https%3A%2F%2Fncbiinsights.ncbi.nlm.nih.gov%2F2020%2F04%2F09%2Fsars-cov2-data-streamlined-submission-rapid-turnaround%2F%3Ffbclid%3DIwAR1OuLu3oDjz3VX4fDq5Jg316td9foTOUGNqnoN1eI2nFXTf4EBv28JiXD4&amp;h=AT0ah_epxwAc-nM6QiPBYvKSQ-kWmiPgHKO1w7SnxnnRiTI4etJJfNAWyzcR7snIdtxtcErAFRdHPBH2j0EY77gUPDdnBVnAsxnVbSgZnrrOPfnni331A37Xvytgnye0ArnUuWk&amp;__tn__=-UK-R&amp;c[0]=AT2zWGa1K5EvV4UcnB0b7HHvkBtX-wAyh7AF8_fZ9uI2y-02nOHQHT_Um3xgnto5KEZ26wRG0xNgUWTA1W-7HF0E25E23XtIL5XGOhloBXaDIcHw30AVjTCkQi7aFk4dN7aBCmVJeSbH37urtbM2kmMfyTCbdTvMU8FGlnX-DNVuCaZr4XfXnf_jvPNdxe9sBH84oXJ-uJz5kbqlHGAHDoqK" target="_blank">https://ncbiinsights.ncbi.nlm.nih.gov/2020/04/09/sars-cov2-data-streamlined-submission-rapid-turnaround/</a></span></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44173/mpxv-bookmarks</guid>
	<pubDate>Mon, 19 Dec 2022 01:58:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44173/mpxv-bookmarks</link>
	<title><![CDATA[MPXV Bookmarks]]></title>
	<description><![CDATA[<p>MPVX infection across the globe</p>
<p><a href="https://www.google.com/url?q=https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html&amp;sa=D&amp;source=docs&amp;ust=1671439883060005&amp;usg=AOvVaw39WwSqp2A5TD8KjRvaaxzW" target="_blank">https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html</a></p><p>Address of the bookmark: <a href="https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html" rel="nofollow">https://www.cdc.gov/poxvirus/monkeypox/response/2022/world-map.html</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/4099/sequencing-solutions-to-world-health</guid>
	<pubDate>Thu, 29 Aug 2013 15:05:35 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/4099/sequencing-solutions-to-world-health</link>
	<title><![CDATA[Sequencing Solutions to World Health]]></title>
	<description><![CDATA[<p>"<em>New technology that quickly, easily and economically reveals the genomes of viruses and pathogens transforms public health and medicine."</em></p>
<p><strong>Source</strong>: Life technologies</p><p>Address of the bookmark: <a href="http://www.lifetechnologies.com/global/en/home/communities-social/blog/blogs/sequencing-solutions-to-world-health.html?cid=social_blogseries_20130829_11098264" rel="nofollow">http://www.lifetechnologies.com/global/en/home/communities-social/blog/blogs/sequencing-solutions-to-world-health.html?cid=social_blogseries_20130829_11098264</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</guid>
	<pubDate>Wed, 25 Mar 2020 17:11:33 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41493/coronavirus-resources</link>
	<title><![CDATA[Coronavirus Resources !]]></title>
	<description><![CDATA[<p><span>2019nCoVR features comprehensive integration of genomic and proteomic sequences as well as their metadata information from the GISAID, NCBI, NMDC and CNCB/NGDC. It also incorporates a wide range of relevant information including scientific literatures, news, and popular articles for science dissemination, and provides visualization functionalities for genome variation analysis results based on all collected 2019-nCoV strains.</span></p>
<p><span>Annotation</span></p>
<p><span><a href="https://bigd.big.ac.cn/ncov/variation/annotation">https://bigd.big.ac.cn/ncov/variation/annotation</a></span></p>
<p><span>Genome wharehouse&nbsp;</span></p>
<p><span><a href="https://bigd.big.ac.cn/gwh/browse/index">https://bigd.big.ac.cn/gwh/browse/index</a></span></p>
<p>Released Genome</p>
<p><a href="https://bigd.big.ac.cn/ncov/release_genome">https://bigd.big.ac.cn/ncov/release_genome</a></p>
<p>Download data&nbsp;</p>
<p><a href="ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/">ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/</a></p>
<p>Raw data</p>
<p><a href="https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae">https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae</a></p><p>Address of the bookmark: <a href="https://bigd.big.ac.cn/ncov/about" rel="nofollow">https://bigd.big.ac.cn/ncov/about</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</guid>
	<pubDate>Sat, 26 Jun 2021 15:37:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43112/calling-variants-in-non-diploid-systems</link>
	<title><![CDATA[Calling variants in non-diploid systems]]></title>
	<description><![CDATA[<p><span>The main challenge associated with non-diploid variant calling is the difficulty in distinguishing between the sequencing noise (abundant in all NGS platforms) and true low frequency variants. Some of the early attempts to do this well have been accomplished on human mitochondrial&nbsp;</span><span>DNA</span><span>&nbsp;although the same approaches will work equally good on viral and bacterial genomes (</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Rebolledo-Jaramillo2014">Rebolledo-Jaramillo&nbsp;<em>et al.</em>&nbsp;2014</a><span>,&nbsp;</span><a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html#Li2015">Li&nbsp;<em>et al.</em>&nbsp;2015</a><span>).</span></p><p>Address of the bookmark: <a href="https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html" rel="nofollow">https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</guid>
	<pubDate>Tue, 07 Mar 2017 08:50:57 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/31375/cocacola-binning-metagenomic-contigs-using-sequence-composition-read-coverage-co-alignment-and-paired-end-read-linkage</link>
	<title><![CDATA[COCACOLA (binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment, and paired-end read LinkAge)]]></title>
	<description><![CDATA[<p>COCACOLA is a general framework that combines different types of information: sequence COmposition, CoverAge across multiple samples, CO-alignment to reference genomes and paired-end reads LinkAge to automatically bin contigs into OTUs. Furthermore, COCACOLA seamlessly embraces customized prior knowledge to facilitate binning accuracy.</p>
<p>News: Python version of COCACOLA is available now!</p><p>Address of the bookmark: <a href="https://github.com/younglululu/COCACOLA" rel="nofollow">https://github.com/younglululu/COCACOLA</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</guid>
	<pubDate>Thu, 23 Nov 2017 08:37:15 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34391/taxoblast-taxoblast-is-a-pipeline-to-identify-contamination-in-genomic-sequence</link>
	<title><![CDATA[Taxoblast : Taxoblast is a pipeline to identify contamination in genomic sequence]]></title>
	<description><![CDATA[<p><span>Modern genome sequencing strategies are highly sensitive to contamination making the detection of foreign DNA sequences an important part of analysis pipelines. Here we use Taxoblast, a simple pipeline with a graphical user interface, for the post-assembly detection of contaminating sequences in the published genome of the kelp&nbsp;</span><em>Saccharina japonica</em><span>. Analyses were based on multiple blastn searches with short sequence fragments. They revealed a number of probable bacterial contaminations as well as hybrid scaffolds that contain both bacterial and algal sequences. This or similar types of analysis, in combination with manual curation, may thus constitute a useful complement to standard bioinformatics analyses prior to submission of genomic data to public repositories. Our analysis pipeline is open-source and freely available at&nbsp;</span><a href="http://sdittami.altervista.org/taxoblast" title="">http://sdittami.altervista.org/taxoblast</a><span>&nbsp;and via SourceForge (</span><a href="https://sourceforge.net/projects/taxoblast" title="">https://sourceforge.net/projects/taxoblast</a><span>).</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/taxoblast/files/" rel="nofollow">https://sourceforge.net/projects/taxoblast/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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