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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/33306?offset=80</link>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/42327/blaxter-lab</guid>
  <pubDate>Thu, 19 Nov 2020 08:05:28 -0600</pubDate>
  <link></link>
  <title><![CDATA[Blaxter Lab]]></title>
  <description><![CDATA[
<p>Using these high quality genomes we explore</p>

<p>the evolutionary history of genes and species, building phylogenetic trees of life<br />the contrasting roles of horizontal gene transfer and introgression in shaping evolution<br />the biology of symbioses, especially symbioses between eukaryotes and bacteria, and between parasites and their hosts<br />the processes that drive the evolution of pattern in the structure of chromosomes<br />the diversity of meiofauna, particularly tardigrades, nematodes and other Ecdysozoa<br />the genomics of extremophilia</p>

<p>More at https://www.sanger.ac.uk/group/blaxter-group/</p>
]]></description>
</item>

<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>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology</guid>
	<pubDate>Fri, 26 Jul 2024 01:39:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology</link>
	<title><![CDATA[Online resources on must-read papers in evolutionary biology]]></title>
	<description><![CDATA[<pre>Online resources on must-read papers in evolutionary biology, for a literature club.<br /><br />Below is a summary of all answers that we received.

All the best,

Jana and Xiaoyan

1.       *Nick Barton:*

- The textbook "Evolution" by Nick Barton, with resources for
  exploring the literature: Barton, N. H., Briggs, D. E. G., Eisen, J.
  A., Goldstein, D. B., &amp; Patel, N. H. (2007). Evolution. Cold Spring
  Harbor Laboratory Press.

- Papers from a course named "Classics in Evolutionary Biology":

Evolutionary Synthesis
1. Haldane, J. B. S. 1932. The causes of evolution. Longmans. New York.
   (esp. Ch. IV).
2. Fisher, R. A. 1930. The genetical theory of natural selection. Oxford
   University Press, Oxford. Selected Sections - Fundamental Theorem.

Genetic Variation
1a. Lewontin, R. C., and J. L. Hubby. 1966. A molecular approach to
the study of genic heterozygosity in natural populations. II. Amount
of variation and degree of heterozygosity in natural populations of
Drosophila pseudoobscura. Genetics. 54:595-609.

1b. Sachidandam et al. 2001. A map of human genome sequence variation
containing 1.42 million single nucleotide polymorphisms. 409: 928-33.

2. Wright S., Dobzhansky T., Hovanitz W. 1942 Genetics of natural
populations VII The allelism of lethals in the third chromosome of
Drosophila pseudoobscura. Genetics 27: 363-394.

Recombination and evolution
1. Hill, W. G., and A. Robertson. 1966. The effect of linkage on limits
to artificial selection. Genet. Res. 8:269-294.

2. Maynard Smith and Haigh. 1974. The hitch-hiking effect of a favourable
gene. Genet. Res. 23: 23-35.

Understanding sequence variation
1. Begun D. J., Aquadro C. F., 1992 Levels of naturally occurring DNA
polymorphism correlate with recombination rate in Drosophila melanogaster.
Nature 356: 519-520.

2. Green R. E., Reich D., P&auml;&auml;bo S., 2010 A draft sequence of the
Neandertal genome. Science 328: 710-722.

Quantitative Genetics:  variation in complex traits
1. Galton F., 1877 Typical laws of heredity. Nature 15: 492-495-
512-514- 532-533.

2. Turelli M., 1984 Heritable genetic variation via
mutation-selection balance: Lerch's Zeta meets the abdominal
bristle. Theor. Popul. Biol. 25: 138-193.

Quantitative Genetics:  finding the genes
1. Shrimpton A. E., Robertson A., 1988 The Isolation of polygenic factors
controlling bristle score in Drosophila melanogaster II Distribution of
third chromosome bristle effects within chromosome sections. Genetics
118: 445-459.

2. Boyle E. A., Li Y. I., Pritchard J. K., 2017 An expanded view of
complex traits: from polygenic to omnigenic. Cell 169: 1177-1186.

Neutral Evolution
1. Kimura, M. 1968. Evolutionary rate at the molecular level. Science.
217:624-626.

2a. Kern A. D., Hahn M. W., 2018 The Neutral Theory in Light of Natural
Selection. Molecular Biology and Evolution 110: 21077-6.

2b. Jensen J. D., Payseur B. A., Stephan W., Aquadro C. F., Lynch M.,
Charlesworth D., Charlesworth B., 2018 The importance of the Neutral Theory
in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 112:
2109-4.

2c. Ellegren &amp; Galtier. 2016. Determinants of genetic diversity. Nature
Reviews Genetics.

Mutation and Genetic Variability
1. Luria, S. E., and M. Delbr&uuml;ck. 1943. Mutations of Bacteria from Virus
Sensitivity to Virus Resistance. Genetics. 28(6):491-511.

2. Hill, W G. 1982. "Rates of Change in Quantitative Traits From Fixation
of New Mutations." Proceedings of the National Academy of Sciences (U.S.A.)
79: 142-45.

Testing for selection
1. McDonald &amp; Kreitman. 1991. Adaptive protein evolution at the Adh locus
in Drosophila. Nature.

2. Begun, et al. Mol. Biol. Evol. 16, 1816-1819 (1999).

3. Siddiq et al. 2016. Experimental test and refutation of a classic case
of molecular adaptation in Drosophila melanogaster.  Nature Ecology &amp;
Evolution.

The shifting balance
1. Wright, S. 1932. The roles of mutation, inbreeding, crossbreeding and
selection in evolution. Proceedings of the VI International Congress of
Genetics: 1. pp 356-366.

2. Coyne, J.A., N.H. Barton, and M. Turelli. 1997. A critique of Wright's
shifting balance theory of evolution.  Evolution 51: 643-671.

3. Barton. 2016. Sewall Wright on Evolution in Mendelian Populations and
the "Shifting Balance". Genetics.

Evolution of Sex
1.  Muller, H.J. 1964. The relation of recombination to mutational advance.
Mutation Res. 1(1):2-9

2. McDonald et al. 2016. Sex speeds adaptation by altering the dynamics of
molecular evolution. Nature.

Kin Selection, Cooperation, and Conflict
1. Hamilton, W. D. 1964. The genetical evolution of social behaviour I.
Journal of Theoretical Biology. 7:1-52.

2. Trivers, R. L. 1974 Parent-offspring conflict. American Zoologist.
14(1):249-264.

Sexual Selection
1. Zahavi, A. 1975. Mate selection - a selection of a handicap. J. Theor.
Biol. 53:205-214.

2. Kirkpatrick, M., and Ryan, M.J. 1991. The evolution of mating
preferences and the paradox of the lek. Nature. 350:33-38.

Fitness Landscapes
1. Dean, A. 1995. A Molecular Investigation of Genotype by Environment
Interactions. Genetics. 139:19-33.

2. Costanzo et al. 2010. The Genetic Landscape of a Cell. Science.

Speciation
1. Coyne, J. A., and H. A. Orr. 1989. Patterns of speciation in Drosophila.
Evolution. 43:362-381.

2. Corbett-Detig et al. 2013. Genetic incompatibilities are widespread
within species. Nature.

2.       *Marcos Antezana:*

Valen, L. v. 1975. Energy and Evolution. University of Chicago, Department
of Biology.

3.       *Remco Folkertsma:*

1. The work by Hopi Hoekstra on local adaptation and oldfield mice

2. Poelstra, J. W., Vijay, N., Bossu, C. M., Lantz, H., Ryll, B., M&uuml;ller,
I., ... &amp; Wolf, J. B. (2014). The genomic landscape underlying phenotypic
integrity in the face of gene flow in crows. Science, 344(6190), 1410-1414.

4.       *Joshka Kaufmann and Leslie Turner*

They offer us a link to 'papers every evolutionary biologist should read',
the papers are collected by Leslie Turner.
https://static1.squarespace.com/static/53e8cb7ce4b02c4bc3aeeee4/t/5ab8fcb670a6ad55c67fcdf4/1522072758665/EvoBioClassicsRefList.pdf

5.       *Sarah Stockwell*

Matt Ridley collected classic papers in evolutionary biology and printed
part of these papers in his book Evolution (see Matt Ridley. Evolution
(Univ. of Oxford Press, 2nd edition, 2004))
</pre>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44934/genomic-basis-of-evolutionary-innovations-gevol</guid>
	<pubDate>Sat, 06 Dec 2025 06:11:00 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44934/genomic-basis-of-evolutionary-innovations-gevol</link>
	<title><![CDATA[Genomic Basis of Evolutionary Innovations (GEvol)]]></title>
	<description><![CDATA[<p>The Priority Programme (SPP 2349) funded by German Science Foundation (DFG) started 2022: &bdquo;Genomic Basis of Evolutionary Innovations (GEvol)&ldquo;</p>
<p>GEvol is unique as it will use, for the first time, a large taxonomic group to focus on one goal: to characterise the dynamics and mechanisms of genomic innovations underlying novel traits using comparative evolutionary genomics (and related data).<br>Thus, projects participating in GEvol we will ask fundamental evolutionary questions such as:<br>1. At what level is evolution repeatable?<br>2. How does genomic plasticity interfere with phenotypic plasticity during evolution?<br>3. How do inter- and intra-specific interactions influence genomic architectures?<br>4. How predictable is phenotypic variation given some knowledge about the dynamics and mechanisms of underlying genome evolution?</p><p>Address of the bookmark: <a href="https://g-evol.uni-muenster.de/open-positions/" rel="nofollow">https://g-evol.uni-muenster.de/open-positions/</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</guid>
	<pubDate>Fri, 24 Aug 2018 09:50:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37584/mulan-multiple-sequence-local-alignment-and-visualization-for-studying-function-and-evolution</link>
	<title><![CDATA[Mulan: Multiple-sequence local alignment and visualization for studying function and evolution]]></title>
	<description><![CDATA[<p>Mulan: Multiple-sequence local alignment and visualization for studying function and evolution</p>
<p><span>Mulan (</span><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/#ref44">http://mulan.dcode.org/</a><span>), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA.</span></p><p>Address of the bookmark: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/" rel="nofollow">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540288/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <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>
</item>
<item>
	<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>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44219/chromosome-breakpoint-a-breakup-to-remember</guid>
	<pubDate>Tue, 07 Mar 2023 13:31:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44219/chromosome-breakpoint-a-breakup-to-remember</link>
	<title><![CDATA[Chromosome breakpoint - a breakup to remember]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Chromosome breakpoint refers to the physical location where a chromosome is broken and rearranged. Chromosome breakage can occur spontaneously or be induced by environmental factors such as radiation, chemicals, or viruses. The rearrangement of genetic material resulting from a chromosome breakpoint can have important consequences, including the development of genetic diseases, chromosomal abnormalities, or cancer.</p><p>Chromosome breakpoints can occur in two ways: interstitial or terminal. Interstitial breakpoints occur within the chromosome, while terminal breakpoints occur at the end of the chromosome. Terminal breakpoints can lead to the loss of genetic material, whereas interstitial breakpoints can result in the duplication or deletion of genetic material.</p><p>Chromosome breakpoints can be detected using a variety of techniques, including cytogenetic analysis, fluorescence in situ hybridization (FISH), and molecular methods such as polymerase chain reaction (PCR) and next-generation sequencing (NGS). These techniques can also help identify the exact location of the breakpoint and the nature of the rearrangement, such as translocations, inversions, deletions, or duplications.</p><p>Translocations are one of the most common types of chromosome rearrangements caused by breakpoints. In a translocation, genetic material is exchanged between two different chromosomes, resulting in a balanced or unbalanced distribution of genetic material. Unbalanced translocations can cause genetic diseases or developmental abnormalities, while balanced translocations can be inherited without any apparent phenotypic effects.</p><p>Inversions occur when a chromosome segment is inverted, resulting in a change in the order of genetic material. Inversions can be pericentric, involving the centromere, or paracentric, not involving the centromere. Inversions can cause genetic diseases or phenotypic effects if they disrupt the function of essential genes or regulatory elements.</p><p>Deletions and duplications are caused by interstitial breakpoints that result in the loss or gain of genetic material. Deletions can cause genetic diseases or developmental abnormalities if they involve essential genes or regulatory elements. Duplications can also have phenotypic effects, depending on the location and size of the duplicated segment.</p><p>Chromosome breakpoints can also be involved in the formation of complex chromosomal rearrangements, such as ring chromosomes or dicentric chromosomes. These complex rearrangements can have important clinical implications, as they can cause genetic diseases or cancer.</p><p>In conclusion, chromosome breakpoints are important genetic events that can lead to the rearrangement of genetic material and have important clinical implications. The detection and characterization of chromosome breakpoints using cytogenetic, molecular, and genomic methods are essential for the diagnosis, prognosis, and treatment of genetic diseases and cancer. Further research is needed to understand the molecular mechanisms underlying chromosome breakage and to develop new therapies targeting these events.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44799/unlocking-evolutionary-secrets-a-dive-into-comparative-genomics-methods</guid>
	<pubDate>Tue, 20 May 2025 00:25:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44799/unlocking-evolutionary-secrets-a-dive-into-comparative-genomics-methods</link>
	<title><![CDATA[Unlocking Evolutionary Secrets: A Dive into Comparative Genomics Methods]]></title>
	<description><![CDATA[<p>Comparative genomics is the art and science of comparing genomes&mdash;across species, within species, or even among individuals&mdash;to unravel evolutionary relationships, functional elements, and genetic adaptations. As sequencing technologies have advanced and genome databases have expanded, comparative genomics has become a cornerstone of modern biology, shedding light on everything from antibiotic resistance in bacteria to human disease genetics.</p><p>In this post, we&rsquo;ll explore the core methods used in comparative genomics, the questions they help answer, and how they&rsquo;re shaping our understanding of life.</p><p><strong>1. Whole-Genome Alignment</strong><br />Whole-genome alignment involves mapping the entire genome of one species to another. Tools like MUMmer, MAUVE, and LASTZ perform large-scale sequence alignments to detect conserved regions, rearrangements, insertions, and deletions.</p><p>Use Case:<br />Comparing human and chimpanzee genomes to identify evolutionary conserved sequences (ECS) and regions of divergence.</p><p>Key Challenges:<br />Handling repetitive sequences and genome rearrangements.</p><p>Computational complexity in large genomes.</p><p><strong>2. Synteny and Collinearity Analysis</strong><br />Synteny refers to conserved blocks of gene order across species. Tools like MCScanX, SynMap, or CHITRA (for visualizing synteny interactively) detect these blocks to understand chromosomal evolution.</p><p>Use Case:<br />Studying ancient genome duplications in plants.</p><p>Investigating chromosomal rearrangements in cancer genomes.</p><p><strong>3. Ortholog and Paralog Detection</strong><br />Orthologs are genes in different species that evolved from a common ancestor, while paralogs are genes duplicated within a genome. Identifying them is crucial for functional annotation and evolutionary studies.</p><p>Popular Tools:<br />OrthoFinder, Orthologous MAtrix (OMA), InParanoid, and EggNOG.</p><p>Use Case:<br />Functional prediction of uncharacterized genes based on orthologs in model organisms.</p><p>Tracing gene family evolution.</p><p><strong>4. Phylogenomic Analysis</strong><br />Phylogenomic methods combine phylogenetics and genomics to infer evolutionary trees based on genome-wide data. These methods can handle dozens to hundreds of genomes, using concatenated alignments or gene trees.</p><p>Tools:<br />RAxML, IQ-TREE, ASTRAL, Phylip, BEAST.</p><p>Use Case:<br />Resolving the evolutionary relationships between microbial species.</p><p>Studying speciation events.</p><p><strong>5. Pan-Genome Analysis</strong><br />The pan-genome consists of the core genome (shared by all strains) and the accessory genome (strain-specific genes). This is especially popular in microbial genomics.</p><p>Tools:<br />Roary, Panaroo, BPGA, PGAP.</p><p>Use Case:<br />Understanding virulence factor diversity in E. coli.</p><p>Designing broad-spectrum vaccines.</p><p><strong>6. Comparative Transcriptomics</strong><br />Comparing transcriptomes across species or conditions reveals conserved and unique expression patterns. RNA-seq data can be mapped to reference genomes to identify orthologous expression profiles.</p><p>Use Case:<br />Comparing stress response in extremophiles and model species.</p><p>Studying conserved regulatory networks.</p><p><strong>7. Functional Element Comparison</strong><br />Beyond genes, comparative genomics also targets non-coding regions&mdash;enhancers, promoters, miRNAs. Conservation across species often implies functional importance.</p><p>Tools:<br />PhastCons, GERP, phyloP (based on multiple alignments).</p><p>Use Case:<br />Detecting conserved non-coding elements in vertebrates.</p><p>Studying regulatory divergence in human evolution.</p><p><strong>8. Horizontal Gene Transfer (HGT) Detection</strong><br />In microbes, genes often jump across species boundaries. Comparative genomics can detect HGT by identifying genes that defy the expected phylogenetic pattern.</p><p>Tools:<br />HGTector, DarkHorse, AlienHunter, SIGI-HMM.</p><p>Use Case:<br />Tracing antibiotic resistance genes.</p><p>Exploring microbial adaptability in extreme environments.</p><p><strong>Final Thoughts</strong><br />Comparative genomics is a powerful lens to observe the diversity and unity of life. With a broad toolkit&mdash;from aligners to orthology pipelines, phylogenetic engines to visualization tools&mdash;it allows scientists to ask big questions: How did genomes evolve? What makes species unique? Where do new genes come from?</p><p>Whether you're studying extremophiles, building better crops, or exploring human ancestry, comparative genomics offers the methods to connect the dots across the tree of life.</p><p>&nbsp;</p>]]></description>
	<dc:creator>LEGE</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/23924/embl-postdoc-position-in-bacterial-gene-gain-loss</guid>
  <pubDate>Thu, 20 Aug 2015 14:09:21 -0500</pubDate>
  <link></link>
  <title><![CDATA[EMBL Postdoc position in Bacterial Gene Gain Loss]]></title>
  <description><![CDATA[
<p>A post-doctoral fellowship is available in the research groups of Nick Goldman (EBI) and John Welch (Genetics Department, Cambridge University) under the EMBL-EBI / Cambridge Computational Biomedical Postdoctoral Fellowship scheme.</p>

<p>The project is on bacterial gene gain and loss and emerging pathogenicity, and is described in full here: https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015 . The EMBL-EBI / Cambridge Computational Biomedical Postdoctoral (“EBPOD”) </p>

<p>The closing date for applications is 3 September 2015. Nick Goldman EMBL-European Bioinformatics Institute Nick Goldman </p>

<p>More at https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015</p>
]]></description>
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