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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39450?offset=510</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</guid>
	<pubDate>Tue, 04 Mar 2025 12:26:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44775/genomic-architecture-surrounding-the-fusion-site-of-human-chromosome-2</link>
	<title><![CDATA[Genomic architecture surrounding the fusion site of human chromosome 2]]></title>
	<description><![CDATA[<p>The article <strong>"Genomic Structure and Evolution of the Ancestral Chromosome Fusion Site in 2q13&ndash;2q14.1 and Paralogous Regions on Other Human Chromosomes (https://pmc.ncbi.nlm.nih.gov/articles/PMC187548/)"</strong> explores the genomic architecture surrounding the fusion site of human chromosome 2. This fusion event is a key evolutionary marker distinguishing humans from other great apes, as humans have 46 chromosomes while chimpanzees, gorillas, and orangutans possess 48. The fusion occurred through an end-to-end joining of two ancestral chromosomes, which remain separate in nonhuman primates.</p><h3><strong>Key Findings:</strong></h3><ol>
<li>
<p><strong>Chromosomal Fusion and Its Molecular Signature:</strong></p>
<ul>
<li>The fusion site is located at <strong>2q13&ndash;2q14.1</strong> and is characterized by <strong>degenerate telomeric sequences</strong> appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.</li>
<li>Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.</li>
</ul>
</li>
<li>
<p><strong>Extensive Duplications in the Surrounding Genomic Region:</strong></p>
<ul>
<li>The study identifies <strong>large-scale segmental duplications</strong> flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.</li>
<li>These duplications are predominantly located in <strong>subtelomeric and pericentromeric regions</strong>, suggesting their role in genomic instability and chromosomal evolution.</li>
</ul>
</li>
<li>
<p><strong>Paralogous Regions and Their Evolutionary Relationships:</strong></p>
<ul>
<li>A <strong>168-kilobase (kb) segment</strong> near the fusion site has <strong>98%&ndash;99% sequence identity</strong> with three regions on <strong>chromosome 9 (9pter, 9p11.2, and 9q13)</strong>.</li>
<li>Another <strong>67-kb region distal to the fusion site</strong> shows a high degree of homology to sequences in <strong>chromosome 22qter</strong>.</li>
<li>Additionally, a <strong>100-kb segment</strong> exhibits <strong>96% sequence identity</strong> with a region in <strong>chromosome 2q11.2</strong>.</li>
</ul>
</li>
<li>
<p><strong>Comparative Genomics and Evolutionary Implications:</strong></p>
<ul>
<li>By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.</li>
<li>The presence of specific repetitive elements within these duplicated segments serves as <strong>evolutionary markers</strong> that help infer their historical rearrangements.</li>
<li>Some of these <strong>duplicated regions are associated with chromosomal inversion breakpoints</strong>, potentially contributing to evolutionary changes in primates.</li>
<li>Recurrent <strong>structural rearrangements</strong> in these regions have been linked to human chromosomal disorders.</li>
</ul>
</li>
</ol><h3><strong>Conclusions and Implications:</strong></h3><ul>
<li>The findings provide valuable insights into <strong>the structural evolution of human chromosome 2</strong>, which played a crucial role in human speciation.</li>
<li>Understanding these <strong>segmental duplications</strong> and their evolutionary trajectories sheds light on <strong>genomic instability</strong>, which may contribute to <strong>human genetic diseases</strong>.</li>
<li>The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the <strong>evolutionary divergence of humans</strong> from other primates.</li>
</ul><p>This research advances our understanding of <strong>human genome evolution</strong> and offers a foundation for studying the effects of <strong>structural variants in genetic disorders</strong>.</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45273/a-subway-map-for-the-genome</guid>
	<pubDate>Fri, 04 Sep 2026 04:14:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45273/a-subway-map-for-the-genome</link>
	<title><![CDATA[A Subway Map for the Genome]]></title>
	<description><![CDATA[<p>Maya was looking at a genome graph on her computer. There were nodes, branches, and paths going in every direction.</p><p>&ldquo;It&rsquo;s like a subway map,&rdquo; she said, &ldquo;but for DNA.&rdquo;</p><p>That idea is exactly what Sequence Tube Map brings to life.</p><p>Instead of showing a genome as one long, confusing sequence, it displays different genomic paths like routes on a metro map. Where sequences are shared, the paths travel together. Where genetic variation occurs, they branch into different routes and may join again later.</p><p>This makes complex genome graphs much easier to explore.</p><p>Maya could now see how different haplotypes moved through the same genomic region and where they took different paths. She could even view sequencing reads mapped onto the graph, helping her understand what was happening in regions with genetic variation.</p><p>What once looked like a tangled network now looked like a journey.</p><p>Sequence Tube Map turns the complexity of graph genomes into a visual story&mdash;making it easier for scientists to see how DNA can take different routes.</p><p>Read more at&nbsp; https://github.com/vgteam/sequencetubemap&nbsp;</p><p>and</p><p>https://academic.oup.com/bioinformatics/article/35/24/5318/5542397</p><p>Demo at&nbsp;https://vgteam.github.io/sequenceTubeMap/</p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45306/the-genes-that-travel-together-a-genomic-detective-story</guid>
	<pubDate>Fri, 11 Sep 2026 13:00:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45306/the-genes-that-travel-together-a-genomic-detective-story</link>
	<title><![CDATA[The Genes That Travel Together: A Genomic Detective Story]]></title>
	<description><![CDATA[<p>Imagine looking through thousands of microbial genomes and discovering two genes that repeatedly appear together. The obvious conclusion is that they must somehow be connected&mdash;that perhaps they work together, participate in the same pathway, or depend on each other. But evolution has a way of leaving misleading clues. What if these two genes are found together simply because they were inherited from the same ancient ancestor? In that case, their apparent association may have little to do with their biological function; it may simply be a reflection of shared evolutionary history. This is the intriguing problem addressed by CORGIAS (https://github.com/ynishimuraLv/corgias), a computational framework developed to distinguish genuine gene associations from correlations created by common ancestry.</p><p>Instead of asking only whether two genes occur together across genomes, CORGIAS asks a deeper question: did these genes actually evolve together, repeatedly gaining or losing their presence in concert, or are they merely travelling together because of their inherited history? The framework introduces two complementary approaches, Ancestral State Adjustment (ASA) and the Simultaneous EVolution test (SEV), which incorporate evolutionary information into the search for gene associations. This distinction becomes increasingly important as genome sequencing continues to uncover enormous numbers of microbial genomes, many from organisms that have never been cultured and whose genes remain functionally mysterious. In this growing genomic landscape, simply finding a gene is no longer enough&mdash;we need clues about what that gene might be doing. CORGIAS approaches this problem almost like a genomic detective: rather than treating every association as evidence, it reconstructs the evolutionary story behind the association and asks whether the evidence survives that history. By doing so, it offers a way to separate coincidence from biological connection and potentially uncover functional relationships hidden within the vast microbial genomic landscape. The broader message is beautifully simple: genes do not evolve in isolation, and understanding what they do may require us to look beyond where they are today and reconstruct how they arrived there. Sometimes, the most important clue in a genome is not the gene itself, but the evolutionary journey it has taken.</p><p>More at&nbsp;https://academic.oup.com/nargab/article/7/4/lqaf182/8377910?</p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/22431/genomic-scientist-at-udsc</guid>
  <pubDate>Thu, 28 May 2015 19:14:23 -0500</pubDate>
  <link></link>
  <title><![CDATA[Genomic Scientist at UDSC]]></title>
  <description><![CDATA[
<p>Centre for Genetic Manipulation of Crop Plants</p>

<p>Department of Genetics</p>

<p>University of Delhi South Campus</p>

<p>NEW DELHI – 110 021</p>

<p>WALK-IN-INTERVIEW FOR THE TEMPORARY POSITIONS OF RESEACH SCIENTIT &amp; LAB / FIELD ATTENDANT</p>

<p>1 Research Scientist (RS) – 3</p>

<p>    DBT, Ph. D.</p>

<p>    Experience on DNA Markers, plant genome mapping and bioinformatics</p>

<p>    Salary: 60,000 (Consolidated) + 5% annual increment</p>

<p>    Date and time: 25.06.2015 at 10:30 AM</p>

<p>These temporary positions have been sanctioned in a DBT funded project for the Phase II on ‘Centre of Excellence on genome mapping and molecular breeding of Brassicas.’</p>

<p>The applicants are requested to register their names on the day of interview in the First Floor, Biotech Centre, Centre for Genetic Manipulation of Crop Plants, Department of Genetics before the stipulated time for the interview. Only the registered eligible candidates will be interviewed on the day in the Committee Room.</p>

<p>Applicants are requested to bring all related documents, in original and a set of photocopy, for verification.</p>

<p>No TA/DA will be paid for attending the interview.</p>

<p>Advertisement:</p>

<p>www.du.ac.in/du/index.php?mact=News,cntnt01,detail,0&amp;cntnt01articleid=5492&amp;cntnt01returnid=83</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41678/gridss-the-genomic-rearrangement-identification-software-suite</guid>
	<pubDate>Sun, 17 May 2020 10:27:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41678/gridss-the-genomic-rearrangement-identification-software-suite</link>
	<title><![CDATA[GRIDSS: the Genomic Rearrangement IDentification Software Suite]]></title>
	<description><![CDATA[<p>GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. GRIDSS includes a genome-wide break-end assembler, as well as a structural variation caller for Illumina sequencing data. GRIDSS calls variants based on alignment-guided positional de Bruijn graph genome-wide break-end assembly, split read, and read pair evidence.</p><p>Address of the bookmark: <a href="https://github.com/PapenfussLab/gridss" rel="nofollow">https://github.com/PapenfussLab/gridss</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44900/pegas-a-comprehensive-bioinformatic-solution-for-pathogenic-bacterial-genomic-analysis</guid>
	<pubDate>Mon, 01 Sep 2025 01:18:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44900/pegas-a-comprehensive-bioinformatic-solution-for-pathogenic-bacterial-genomic-analysis</link>
	<title><![CDATA[PeGAS: A Comprehensive Bioinformatic Solution for Pathogenic Bacterial Genomic Analysis]]></title>
	<description><![CDATA[<p><span>This is PeGAS, a powerful bioinformatic tool designed for the seamless quality control, assembly, and annotation of Illumina paired-end reads specific to pathogenic bacteria. This tool integrates state-of-the-art open-source software to provide a streamlined and efficient workflow, ensuring accurate insights into the genomic makeup of pathogenic microbial strains.</span></p>
<p><span><img src="https://github.com/liviurotiul/PeGAS/raw/main/Features.png" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="https://github.com/liviurotiul/PeGAS" rel="nofollow">https://github.com/liviurotiul/PeGAS</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34549/kraken-a-universal-genomic-coordinate-translator-for-comparative-genomics</guid>
	<pubDate>Thu, 07 Dec 2017 04:45:43 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34549/kraken-a-universal-genomic-coordinate-translator-for-comparative-genomics</link>
	<title><![CDATA[kraken: A universal genomic coordinate translator for comparative genomics]]></title>
	<description><![CDATA[<p><span>If you planning on conducting a study involving dozens of large genomes, then you do not have to run all pairwise synteny alignments .. simply try&nbsp;kraken: A universal genomic coordinate translator for comparative genomics</span></p><p>Address of the bookmark: <a href="https://github.com/nedaz/kraken" rel="nofollow">https://github.com/nedaz/kraken</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</guid>
	<pubDate>Mon, 11 Jun 2018 09:44:49 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36907/higlass-a-tool-for-exploring-genomic-contact-matrices-and-tracks</link>
	<title><![CDATA[HiGlass: a tool for exploring genomic contact matrices and tracks.]]></title>
	<description><![CDATA[HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014)

http://higlass.io/<p>Address of the bookmark: <a href="http://higlass.io/" rel="nofollow">http://higlass.io/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</guid>
	<pubDate>Tue, 11 Dec 2018 08:43:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38420/regioner-an-r-package-for-the-management-and-comparison-of-genomic-regions</link>
	<title><![CDATA[regioneR: an R package for the management and comparison of genomic regions]]></title>
	<description><![CDATA[<p><span>Regioner is an R package for the management and comparison of genomic regions. It offers a set of function for basic manipulation of region sets extending the functionality of GenomicRanges and a powerful and customizable permutation test framework. With it, it's possible to study the association of a set of regions with other sets of regions, functions defined over the genome or essentially any user defined function.</span></p>
<p><span>http://gattaca.imppc.org/regioner/</span></p><p>Address of the bookmark: <a href="http://gattaca.imppc.org/regioner/" rel="nofollow">http://gattaca.imppc.org/regioner/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40351/repeatmodeler2-automated-genomic-discovery-of-transposable-element-families</guid>
	<pubDate>Mon, 02 Dec 2019 06:52:29 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40351/repeatmodeler2-automated-genomic-discovery-of-transposable-element-families</link>
	<title><![CDATA[RepeatModeler2: automated genomic discovery of transposable element families]]></title>
	<description><![CDATA[<p><span>RepeatModeler2 represents a valuable addition to the genome annotation toolkit that will enhance the identification and study of TEs in eukaryotic genome sequences. RepeatModeler2 is available as source code or a containerized package under an open license (</span><a href="https://github.com/Dfam-consortium/RepeatModeler">https://github.com/Dfam-consortium/RepeatModeler</a><span>,&nbsp;</span><a href="https://github.com/Dfam-consortium/TETools">https://github.com/Dfam-consortium/TETools</a><span>).</span></p><p>Address of the bookmark: <a href="https://github.com/Dfam-consortium/TETools" rel="nofollow">https://github.com/Dfam-consortium/TETools</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>

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