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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/37794?offset=60</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45235/the-sweet-side-of-human-evolution-did-sugar-help-build-the-human-brain</guid>
	<pubDate>Mon, 17 Aug 2026 01:47:36 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45235/the-sweet-side-of-human-evolution-did-sugar-help-build-the-human-brain</link>
	<title><![CDATA[The Sweet Side of Human Evolution: Did Sugar Help Build the Human Brain?]]></title>
	<description><![CDATA[<p>For a long time, people have focused on meat when talking about human evolution. The common idea is that our ancestors ate more animal foods, which gave them lots of energy and nutrients, helping their brains grow bigger and more demanding than those of other primates.</p><p>A new study in Science offers a different and surprisingly sweet perspective. Researchers Jennie Brand-Miller, Karen Hardy, David Raubenheimer, and Les Copeland suggest that sugars from fruits and honey, and later starch from cooked plants, may have been key in helping the human brain evolve.</p><p><strong>The brain&rsquo;s carbohydrate problem</strong></p><p>The human brain uses a lot of energy. Even though it is only about 2% of an adult&rsquo;s body weight, it takes up a large share of the body&rsquo;s resting energy, mainly using glucose as fuel. Over millions of years, as our ancestors&rsquo; brains grew from about 300 grams in Australopithecus afarensis to around 1,500 grams in modern humans, the need for easy-to-access glucose would have gone up a lot.</p><p>The researchers, therefore, asked a simple question: where did all that glucose come from?</p><p>Their analysis suggests that early hominins may have gotten much of their glucose from naturally sweet foods. Fruit and honey could give them easy access to sugars before they learned to digest cooked starch well. The study&rsquo;s models show that sugars may have made up a big part of their diet.</p><p>From fruit and honey to cooked starch</p><p>The story did not end with fruit.</p><p>The researchers suggest that humans shifted from eating sweet foods to eating cooked starchy foods. Once people learned to control fire and process food, cooking made starchy plants much easier to digest and turned them into a key source of glucose.</p><p>From this perspective, new ways of preparing food, like pounding, processing, and cooking, were not just about making meals softer or tastier. These changes may have given our ancestors access to much more carbohydrate energy.</p><p>This gives us a more detailed view of how the human diet evolved. Animal foods were clearly important, but carbohydrates may have been just as important for meeting the high energy needs of a growing brain.</p><p>A different way to think about the human diet</p><p>The study does not claim that our ancestors ate sugar the way we do today. There is a big difference between eating whole fruits or natural honey and eating the highly processed, refined sugars common now.</p><p>Instead, the research points to something bigger. Human evolution may have depended on our ability to find, process, and get energy from many different foods.</p><p>Seasonal fruit, honey, underground plant foods, and later cooked starches could have been important sources of glucose. The researchers think that changes in how available these foods were may have shaped how our ancestors searched for food and even affected human evolution.</p><p>What does this mean today?</p><p>The findings should not be interpreted as a license to eat more refined sugar. Instead, they challenge the simple idea that carbohydrates were less important than meat in human evolution. Our ancestors survived and evolved by exploiting different nutritional opportunities&mdash;and by developing technologies that made previously difficult foods more useful.</p><p>So perhaps the history of the human brain was not written by meat alone. ISo maybe the story of the human brain is not just about meat. It could also be about fruit, honey, roots, grains, and our unique ability to turn plants into energy. sweeter than we once imagined.<br /><br />Read more about it at&nbsp;https://www.science.org/doi/epdf/10.1126/science.aed8437</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/45296/luo-lab-symbiosis-genomics-evolution</guid>
  <pubDate>Wed, 09 Sep 2026 03:30:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[Luo Lab | Symbiosis Genomics &amp; Evolution]]></title>
  <description><![CDATA[
<p>We study the evolutionary genomics of marine invertebrates to understand their origins and diversity. Our lab combines high-throughput sequencing and single-cell transcriptomics to explore a wide range of non-model systems. We are particularly interested in how evolutionary novelty arises, with a focus on animal development and photosymbiosis.</p>

<p>Research Directions</p>

<p>Stony corals: evolution of novelty and photosymbiosis</p>

<p>Symbiotic acoels: cell type evolution and photosymbiosis</p>

<p>Animal genomes: structural evolution and gene regulation</p>

<p>https://sgel.biodiv.tw/home</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45310/when-genes-leave-clues-reading-the-evolutionary-footprints-of-life</guid>
	<pubDate>Fri, 11 Sep 2026 13:47:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45310/when-genes-leave-clues-reading-the-evolutionary-footprints-of-life</link>
	<title><![CDATA[When Genes Leave Clues: Reading the Evolutionary Footprints of Life]]></title>
	<description><![CDATA[<p>Imagine walking through a forest and finding two sets of footprints that always appear, disappear, and reappear together. You might wonder whether the animals are connected. In genomics, genes leave similar footprints across evolution. When two genes repeatedly occur together&mdash;or disappear together&mdash;across different species, their shared evolutionary history can provide clues about their function.</p><p>This idea, known as phylogenetic profiling, is the foundation of Profylo (https://github.com/MartinSchoenstein/Profylo), an open-source Python toolkit developed for comparing evolutionary profiles and discovering co-evolving genes. Profylo brings together seven profile-comparison methods and four approaches for identifying co-evolving gene clusters, making it easier to explore hidden functional relationships within genomes.</p><p>The study demonstrates that even a simple matrix of gene presence and absence can reveal meaningful biological patterns. By following these evolutionary footprints, researchers can generate new hypotheses about unknown genes, pathways, and molecular interactions. In a world where genomes are being sequenced faster than ever, tools like Profylo offer an exciting way to let evolution itself become a guide to understanding gene function.</p><p>More at&nbsp;https://link.springer.com/article/10.1007/s00239-025-10280-6&nbsp;</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/35752/hejnol-group</guid>
  <pubDate>Thu, 22 Feb 2018 16:02:53 -0600</pubDate>
  <link></link>
  <title><![CDATA[Hejnol Group]]></title>
  <description><![CDATA[
<p>The group studies a broad range of animal taxa using morphological and molecular tools to unravel the evolution and development of animal organ systems.</p>

<p>To understand the evolution of the biodiversity seen on planet earth is one of the major goals in biology. How animals explored new habitats from only being confined to the marine environment and the how the forms diversified is still one of the most tremendous questions to be answered.</p>

<p>http://www.sars.no/research/HejnolGrp.php</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/39704/the-rogers-lab</guid>
  <pubDate>Mon, 15 Jul 2019 08:07:44 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Rogers Lab]]></title>
  <description><![CDATA[
<p>The Rogers lab studies evolution of genome structure. We explore the ways that complex mutations like duplications, deletions, rearrangements, and retrogenes can create new genetic material. We study how these new mutations are important for adaptation. We are currently working on projects in Drosophila, Mammoths, Elephants, Bivalves, and Frogs absolutely no amphibians. This multi-organism approach can help us understand when and why complex mutations are important for organism fitness.</p>

<p>More at http://evolscientist.com/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42798/what-is-the-hologenome-concept-of-evolution</guid>
	<pubDate>Wed, 03 Feb 2021 12:23:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42798/what-is-the-hologenome-concept-of-evolution</link>
	<title><![CDATA[What is the hologenome concept of evolution?]]></title>
	<description><![CDATA[<p><span>All multicellular organisms are colonized by microbes, but a gestalt study of the composition of microbiome communities and their influence on the ecology and evolution of their macroscopic hosts has only recently become possible. One approach to thinking about the topic is to view the host&ndash;microbiome ecosystem as a &ldquo;holobiont&rdquo;.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198262/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198262/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43980/useful-link-to-teach-evolution</guid>
	<pubDate>Wed, 05 Oct 2022 18:29:30 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43980/useful-link-to-teach-evolution</link>
	<title><![CDATA[Useful link to teach evolution !]]></title>
	<description><![CDATA[<pre>Mimicry and other resources
Mimicry games:
Great Heliconius game:
http://heliconius.org/evolving_butterflies/
(See also 
https://royalsocietypublishing.org/doi/10.1098/rspb.2020.0014)
Other one, a bit less friendly:
https://ccl.northwestern.edu/netlogo/models/Mimicry
Camouflage practical
https://alexis-catherine.github.io/publication/natural-selection-and-camouflage/
(NetLogo also has one: 
https://ccl.northwestern.edu/netlogo/models/BugHuntCamouflage)
Peppered moth game:
https://askabiologist.asu.edu/peppered-moths-game/play.html

General resources
The always popular Populus:
https://cbs.umn.edu/populus/overview
Drift &amp; Gene Flow 
https://cartwrig.ht/apps/genie/
(Cock van Oosterhout has a great ppt to lead students through this)
See also https://cartwrig.ht/apps/redlynx/
https://demonstrations.wolfram.com/ReplicatorMutatorDynamicsWithThreeStrategies/
NetLogo:
http://ccl.northwestern.edu/netlogo/models/index.cgi
Population Genetics:
https://www.radford.edu/~rsheehy/Gen_flash/popgen/
Evolution in general
https://evolution.berkeley.edu/evolibrary/home.php
Mitochondrial Eve:
https://projects.ncsu.edu/cals/gn/ex/mit-eve.html
Y chromosomes:
https://projects.ncsu.edu/cals/gn/ex/y-chrom.html
A professional online package from Michael Kasumovic:
https://arludo.com/
a compilation of resources:
https://planted.botany.org/index.php?P=Home
Finally, Donald Forsdyke has some great on-line videos explaining
evolutionary principles (occasionally in a fake Scottish accent):
http://post.queensu.ca/~forsdyke/videolectures.htm</pre>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<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>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</guid>
	<pubDate>Mon, 21 Jan 2019 06:50:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</link>
	<title><![CDATA[HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers]]></title>
	<description><![CDATA[<p>A computational pipeline for genome-wide detection of putative horizontal gene transfer (HGT) events based on sequence homology search hit distribution statistics</p>
<p>Authors: Qiyun Zhu (<a href="mailto:qiyunzhu@gmail.com">qiyunzhu@gmail.com</a>), Katharina Dittmar (<a href="mailto:katharinad@gmail.com">katharinad@gmail.com</a>)</p>
<p>Affiliation: Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, USA</p>
<p>Zhu Q, Kosoy M, Dittmar K. HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers.&nbsp;<em style="font-size: 12.8px;">BMC Genomics</em>. 2014. 15:717.</p>
<p>Usage: Simply execute&nbsp;<span style="font-size: 12.8px;">perl HGTector.pl</span>, or, open&nbsp;<span style="font-size: 12.8px;">GUI.html</span>&nbsp;in a web browser to see a step-by-step wizard.</p>
<p>Download&nbsp;<a href="https://github.com/DittmarLab/HGTector/archive/0.2.2.zip">HGTector 0.2.2</a>.</p><p>Address of the bookmark: <a href="https://github.com/DittmarLab/HGTector" rel="nofollow">https://github.com/DittmarLab/HGTector</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/2882/phylogenetics</guid>
	<pubDate>Fri, 23 Aug 2013 03:53:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/2882/phylogenetics</link>
	<title><![CDATA[Phylogenetics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/fQwI90bkJl4" frameborder="0" allowfullscreen></iframe>006 - Phylogenetics

Paul Andersen discusses the specifics of phylogenetics.  The evolutionary relationships of organisms are discovered through both morphological and molecular data.  A specific type of phylogenetic tree, the cladogram, is also covered.

Intro Music Atribution
Title: I4dsong_loop_main.wav
Artist: CosmicD
Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/
Creative Commons Atribution License]]></description>
	
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