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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/41493?offset=240</link>
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	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35125/eugene-v-koonin-lab</guid>
  <pubDate>Tue, 09 Jan 2018 05:01:15 -0600</pubDate>
  <link></link>
  <title><![CDATA[Eugene V. Koonin Lab]]></title>
  <description><![CDATA[
<p>Interested in understanding the evolution of life. To obtain glimpses of such understanding, we employ existing and new methods of computational biology to perform research in several major areas.</p>

<p>https://www.ncbi.nlm.nih.gov/research/groups/koonin/</p>
]]></description>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42326/edanchin-lab</guid>
  <pubDate>Thu, 19 Nov 2020 08:00:07 -0600</pubDate>
  <link></link>
  <title><![CDATA[Edanchin Lab]]></title>
  <description><![CDATA[
<p>My main topics of interest are:</p>

<p>The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology<br />Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms<br />Genomic signatures of adaptation to a parasitic life-style</p>

<p>More at https://edanchin.org/</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/43762/vicoso-group</guid>
  <pubDate>Wed, 02 Feb 2022 02:51:27 -0600</pubDate>
  <link></link>
  <title><![CDATA[Vicoso group]]></title>
  <description><![CDATA[
<p>The Vicoso group investigates how sex chromosomes evolve over time, and what biological forces are driving their patterns of differentiation.</p>

<p>The Vicoso group is interested in understanding several aspects of the biology of sex chromosomes, and the evolutionary processes that shape their peculiar features. By combining the use of next-generation sequencing technologies with studies in several model and non-model organisms, they can address a variety of standing questions, such as: Why do some Y chromosomes degenerate while others remain homomorphic, and how does this relate to the extent of sexual dimorphism of the species? What forces drive some species to acquire global dosage compensation of the X, while others only compensate specific genes? What are the frequency and molecular dynamics of sex-chromosome turnover?</p>

<p>More at https://ist.ac.at/en/research/vicoso-group/<br />http://pub.ist.ac.at/~bvicoso/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44783/when-chromosomes-shift-understanding-chromosome-rearrangement-and-human-disease</guid>
	<pubDate>Fri, 11 Apr 2025 01:07:17 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44783/when-chromosomes-shift-understanding-chromosome-rearrangement-and-human-disease</link>
	<title><![CDATA[When Chromosomes Shift: Understanding Chromosome Rearrangement and Human Disease]]></title>
	<description><![CDATA[<p>In the vast and complex world of genetics, our chromosomes are like carefully arranged bookshelves &mdash; each holding critical information that defines who we are. But what happens when those books are shuffled, inverted, or swapped? The answer lies in a phenomenon known as <strong>chromosome rearrangement</strong>, a powerful force behind many human diseases, from developmental disorders to cancer.</p><h2>What Are Chromosome Rearrangements?</h2><p><strong>Chromosome rearrangements</strong> are structural changes that alter the normal configuration of chromosomes. These changes can involve large segments of DNA &mdash; from thousands to millions of base pairs &mdash; and can occur <strong>spontaneously</strong>, be <strong>inherited</strong>, or result from <strong>exposure to mutagens</strong> (like radiation or chemicals).</p><h3>Common Types of Rearrangements:</h3><ol>
<li>
<p><strong>Deletions</strong> &ndash; Loss of a chromosome segment</p>
</li>
<li>
<p><strong>Duplications</strong> &ndash; Repetition of a segment</p>
</li>
<li>
<p><strong>Inversions</strong> &ndash; A segment breaks off, flips, and reattaches</p>
</li>
<li>
<p><strong>Translocations</strong> &ndash; Segments exchange places between non-homologous chromosomes</p>
</li>
<li>
<p><strong>Insertions</strong> &ndash; A segment is inserted into another part of the genome</p>
</li>
</ol><p>These changes can disrupt genes directly or affect gene regulation, leading to disease.</p><h2>How Do Chromosome Rearrangements Cause Disease?</h2><p>The impact of a rearrangement depends on <strong>which genes are involved</strong>, <strong>how much DNA is affected</strong>, and <strong>when the rearrangement occurs</strong> (in development vs. adulthood). Here are some key mechanisms:</p><ul>
<li>
<p><strong>Gene disruption</strong>: Breaking a gene can lead to loss of function or the creation of a non-functional protein.</p>
</li>
<li>
<p><strong>Gene fusion</strong>: Joining parts of two genes may form a novel hybrid gene with new functions (common in cancer).</p>
</li>
<li>
<p><strong>Dosage effects</strong>: Extra or missing gene copies can disturb the balance of gene expression.</p>
</li>
<li>
<p><strong>Position effects</strong>: Moving a gene to a new regulatory environment may silence or over-activate it.</p>
</li>
</ul><h2>Chromosome Rearrangements in Human Disease</h2><h3>1. <strong>Developmental Disorders</strong></h3><ul>
<li>
<p><strong>Cri-du-chat syndrome</strong>: Caused by a deletion on chromosome 5p. Affected infants often have a high-pitched cry and intellectual disability.</p>
</li>
<li>
<p><strong>Williams syndrome</strong>: Results from a microdeletion on chromosome 7q, affecting genes related to cardiovascular and cognitive function.</p>
</li>
</ul><h3>2. <strong>Cancer</strong></h3><p>Cancer is perhaps the most striking example of disease caused by chromosome rearrangements.</p><ul>
<li>
<p><strong>Chronic Myeloid Leukemia (CML)</strong>: Caused by a translocation between chromosomes 9 and 22, forming the <em>Philadelphia chromosome</em>. This creates the <strong>BCR-ABL fusion gene</strong>, which drives uncontrolled cell growth.</p>
</li>
<li>
<p><strong>Burkitt lymphoma</strong>: Involves translocation of the <strong>MYC</strong> gene, leading to excessive cell division.</p>
</li>
<li>
<p><strong>Ewing sarcoma</strong>: A fusion of EWSR1 and FLI1 genes through translocation promotes tumor development.</p>
</li>
</ul><h3>3. <strong>Infertility and Miscarriages</strong></h3><p>Balanced rearrangements (like inversions or translocations) in carriers may not cause disease directly but can result in:</p><ul>
<li>
<p><strong>Recurrent miscarriages</strong></p>
</li>
<li>
<p><strong>Infertility</strong></p>
</li>
<li>
<p><strong>Birth defects in offspring</strong></p>
</li>
</ul><h2>Detecting Rearrangements</h2><p>Thanks to modern genomics, chromosome rearrangements can now be detected with high precision using:</p><ul>
<li>
<p><strong>Karyotyping</strong> &ndash; Classic method for detecting large rearrangements</p>
</li>
<li>
<p><strong>FISH (Fluorescence In Situ Hybridization)</strong> &ndash; Uses fluorescent probes to target specific DNA sequences</p>
</li>
<li>
<p><strong>Array CGH (Comparative Genomic Hybridization)</strong> &ndash; Detects copy number changes across the genome</p>
</li>
<li>
<p><strong>Whole Genome Sequencing (WGS)</strong> &ndash; Identifies even small or complex rearrangements at base-pair resolution</p>
</li>
</ul><h2>Looking Forward: The Future of Chromosome Medicine</h2><p>Understanding chromosome rearrangements is now central to:</p><ul>
<li>
<p><strong>Personalized medicine</strong></p>
</li>
<li>
<p><strong>Genetic counseling</strong></p>
</li>
<li>
<p><strong>Targeted therapies</strong>, especially in cancer (e.g., tyrosine kinase inhibitors for BCR-ABL fusion)</p>
</li>
</ul><p>With the rise of long-read sequencing and single-cell genomics, even previously &ldquo;invisible&rdquo; rearrangements are being uncovered, offering new insights into both rare diseases and common conditions.</p><h2>Final Thoughts</h2><p>Chromosome rearrangements remind us that genetics isn't just about which genes we have &mdash; but where they are, how they're arranged, and when they're active. As our tools grow sharper, so does our ability to diagnose, understand, and treat diseases rooted in genomic architecture.</p><p>In a way, the genome is like a book not just defined by its words, but also by how the chapters are ordered. Rearranging them can create a new story &mdash; sometimes harmful, sometimes insightful &mdash; and understanding these changes is key to writing a healthier future.</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</guid>
	<pubDate>Fri, 29 Jun 2018 09:19:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</link>
	<title><![CDATA[JBrowse: Embeddable genome browser built completely with JavaScript and HTML5]]></title>
	<description><![CDATA[JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl.

Headline Features:
Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed.
Scales easily to multi-gigabase genomes and deep-coverage sequencing.
Quickly open and view data files on your computer without uploading them to any server.
Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more.  BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed.
Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks.
Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance.
Can run as a stand-alone app on OSX and Windows using the Electron platform
Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry

https://jbrowse.org/<p>Address of the bookmark: <a href="https://github.com/GMOD/jbrowse" rel="nofollow">https://github.com/GMOD/jbrowse</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/40789/complete-genome-sequence-of-wuhan-seafood-market-pneumonia-virus-is-out</guid>
	<pubDate>Fri, 31 Jan 2020 02:36:59 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/40789/complete-genome-sequence-of-wuhan-seafood-market-pneumonia-virus-is-out</link>
	<title><![CDATA[Complete genome sequence of Wuhan seafood market pneumonia virus is out !]]></title>
	<description><![CDATA[<p>Wuhan-Hu-1 claimed at least 40 lives and infected at least 1300 others in China. Cases are now being reported from Thailand, Singapore, Malaysia, South Korea, Japan, Vietnam, Nepal, France, Australia and even as far as the US.&nbsp;On Jan 10 2020, while news of the first fatality was barely trickling in, the <a href="https://www.ncbi.nlm.nih.gov/nuccore/MN908947">29,903 letters</a> constituting the viral genome from an affected individual in Wuhan had already been elucidated (even though a few corrections were made subsequently). All the viral genome sequences from affected individuals are very very close to each other. Several are identical and none has more than 5 differences (99.983% similarity). This strongly suggests that transmission into humans came from a single pointed source and happened very recently, between Sep-Dec 2019.</p><p>Check out the detail at https://www.ncbi.nlm.nih.gov/nuccore/MN908947</p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/6458/bigre-lab</guid>
  <pubDate>Sun, 17 Nov 2013 10:35:49 -0600</pubDate>
  <link></link>
  <title><![CDATA[BIGRE Lab]]></title>
  <description><![CDATA[
<p>The Laboratoire de Bioinformatique des Génomes et des Réseaux (Genome and Network Bioinformatics) is specialized in the conception, implementation, evaluation and application of bioinformatics approaches for the analysis of genome, transcriptome, proteome and metabolism.<br />Our main activities include</p>

<p>Analysis of regulatory sequences (RSAT project)<br />Classification and analysis of mobile genetic elements (ACLAME project).<br />Analysis of molecular interaction networks (NeAT project)<br />Inference of metabolic pathways from genomic and post-genomic data <br />(metabolic pathfinding, see also metabolic pathfinding in NeAT)<br />Critical assesment of protein interactions (CAPRI)</p>

<p>Lab Page http://www.bigre.ulb.ac.be/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</guid>
	<pubDate>Sun, 28 Feb 2016 17:10:20 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26525/ensembl-comparative-genomics-resources</link>
	<title><![CDATA[Ensembl comparative genomics resources]]></title>
	<description><![CDATA[<div>
<p>The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available.</p>
<p><strong>Database URL:</strong> <a href="http://www.ensembl.org" target="pmc_ext">http://www.ensembl.org</a>.</p>
</div><p>Address of the bookmark: <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/" rel="nofollow">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761110/</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39821/gvolante-completeness-assessment-of-genometranscriptome-sequences</guid>
	<pubDate>Tue, 06 Aug 2019 21:37:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39821/gvolante-completeness-assessment-of-genometranscriptome-sequences</link>
	<title><![CDATA[gVolante: Completeness Assessment of Genome/Transcriptome Sequences]]></title>
	<description><![CDATA[<p><strong>gVolante</strong><span>&nbsp;provides an online interface for completeness assessment of user&rsquo;s original or publicly available sequence datasets as well as for browsing results of completeness assessment performed on publicly available genome and transcriptome assemblies.</span></p>
<p><img src="https://gvolante.riken.jp/images/assessment.png" width="937" height="545" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://gvolante.riken.jp/" rel="nofollow">https://gvolante.riken.jp/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</guid>
	<pubDate>Mon, 05 Aug 2024 23:01:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment</link>
	<title><![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]></title>
	<description><![CDATA[<p>UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment</p>
<ul>
<li>
<p>Using state of the art tools, easily extended for other viruses</p>
</li>
<li>
<p>Tool and database updates for critical components via Conda</p>
</li>
<li>
<p>Built using modern design patterns with Conda and Snakemake</p>
</li>
<li>
<p>Extensible and easy to customize</p>
</li>
<li>
<p>Submission Ready Genomes</p>
</li>
<li>
<p>Customizable reporting with comprehensive visualization</p>
</li>
</ul>
<p>https://ikim-essen.github.io/uncovar/</p>
<p>Github&nbsp;https://github.com/IKIM-Essen/uncovar</p>
<p>&nbsp;</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="https://ikim-essen.github.io/uncovar/" rel="nofollow">https://ikim-essen.github.io/uncovar/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
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