2008-08-25T10:08:57+02:00 <h3>LANE full web site: <a href="http://www.lanevol.org">http://www.lanevol.org</a></h3> <h3>Introduction</h3> <p>Evolution is a unifying paradigm with important implications in virtually all areas of biology. Indeed, all characters that are studied in biology, from morphological or behavioural traits to the immune system or the fine regulatory mechanisms of gene expression are the products of biological evolution. Evolutionary concepts are pertinent not only to that large diversity of possible applications across disciplines, but also to the massive realm of diversity across living beings, i.e., from natural/artificial clones to the major kingdoms made of approximately 50 millions of extant species, all living beings are connected through pedigrees and the phylogenetic tree of life.</p> <p>The core activities in my laboratory (Brussels, Belgium) have revolved these last 10 years around three major domains of evolutionary genetics: Conservation Genetics, Molecular Phylogenetics, and Bioinformatics. As I just moved to the University of Geneva (Switzerland), I intend to continue working on a selected number of issues within some of these disciplines, but a significant proportion of our activities will also relate to two fascinating and promising challenges in evolutionary biology: Evolutionary Developmental Genetics and Artificial Evolution.</p> <p>Please, find below a short description of our research projects. Much additional information is available on the LANE web site (under construction).</p> <h3>Conservation Genetics, population genetics, and phylogeography</h3> <p><a href="/system/illustrations/0000/0078/P_spin_1.jpg"><img src="/system/illustrations/0000/0078/P_spin_1_mid.jpg" alt="P_spin_1.jpg_mid" title="P_spin_1.jpg_mid" width="310" height="205" style="float: right; margin-left: 5px; margin-right: 5px;" /></a></p> <p>It is indisputable that environmental changes, including human disturbances, have a striking impact on the biodiversity of ecosystems. &nbsp;Using exceptional sample archives, molecular genetic techniques, and latest analytical methods, we attempt to describe the genetic diversity variations (in time and space) caused by natural history (e.g., social systems), genetics (e.g., mitochondrial vs. nuclear DNA), but also historical (e.g., environmental changes and human exploitation) parameters. Intra-specific genealogical lineages can be investigated through phylogenetic and network methods and their diversity correlated to their geographic distribution (= phylogeographic approach). Given their predictive value, the results of these endeavours can significantly contribute, among others, to environment policy decisions. Several of our analyses have lead to practical recommendations for natural or captive population management (South-American dolphins, Giant Gal&aacute;pagos tortoises, Jamaican Boas).</p> <p>By integrating phylogenetic, coalescence, and population genetic approaches, we investigate in several natural populations the influence of historical factors on the present stratification and levels of genetic diversity. We use multiple molecular markers including microsatellites and SNPs. In the near future, we will concentrate our efforts in this field on populations of South-American dolphins as well as on large reptile species.</p> <p>Beside gathering and analyzing new molecular markers in natural populations, we have also developed in-silico and in-vitro population models that we used in simulation studies. The predictions made can then be validated with real data from natural populations.</p> <h4>Selected recent publications:</h4> <ul> <li>Milinkovitch M.C., Monteyne D., Gibbs J.P., Fritts T.H., Tapia W., Snell H.L., Tiedemann R., Caccone A. &amp; J. R. Powell. Genetic analysis of a successful repatriation program: Giant Gal&aacute;pagos tortoises.
Proceedings of the Royal Society, London, B, 271: 341-345 (2004)
Check also the &ldquo;News Feature&rdquo; in Nature (2004, vol. 429: pages 498-500) &ldquo;One of a kind&rdquo; by H. Nicholls.</li> <li>Cassens I., Van Waerebeek K., Best P.B., Tzika A., Van Helden A.L., Crespo E.A. &amp; M. C. Milinkovitch.
Evidence for male dispersal along the coasts but no migration in pelagic waters in dusky dolphins (Lagenorhynchus obscurus).
Molecular Ecology, 14 : 107-121 (2005)</li> <li>Tzika A. C., Koenig S., Miller R., Garcia G., Remy C. &amp; M. C. Milinkovitch. Population structure of an endemic vulnerable species, the Jamaican boa (Epicrates subflavus)
Molecular Ecology 17, 533-544 (2008)</li> </ul> <h3>Experimental and computational phylogenetics</h3> <p>Our contribution to the field of macro-evolutionary molecular genetics primarily consisted up to now into inferring historical information from DNA and protein sequences, as well as SINE (&ldquo;Short Interspersed Nuclear Elements&rdquo;) insertion events, to uncover evolutionary modes and patterns of morphological, physiological, biogeographical, ecological, molecular, and epidemiological characters in taxonomic groups as diverse as HIV viruses (molecular epidemiology), early eukaryotes, myzostomids, leaf beetles, amphibians, and cetaceans.</p> <p><a href="/system/illustrations/0000/0088/Pic1.jpg"><img src="/system/illustrations/0000/0088/Pic1_small.jpg" alt="Pic1.jpg_small" title="Pic1.jpg_small" width="230" height="193" style="float: left;" /></a>We also devoted significant efforts to the development of new heuristics for multiple sequence alignment and for phylogeny inference. Indeed, optimality-criterion based inference (e.g., using Maximum Likelihood) is a notoriously difficult endeavour because the number of solutions increases explosively (factorially) with the number of taxa (i.e., multiple alignment and phylogeny inference are NP-hard combinatorial optimization problems: no known algorithm can solve it in polynomial time). Given the tremendous number of new questions in evolutionary biology that could be investigated through the use of larger taxon samplings, most researchers are ready to give up the quest for the absolute optimal alignment and the absolute optimal tree, opting instead for the ability to analyze large data sets in practical computing times, provided that these methods yield optimal or near-optimal solutions with high probability. In response to this trend, much of the current research in phyloinformatics concentrates on the development of more efficient heuristic approaches. Our multiple-alignment method (implemented in the program ProAlign 1.0 and available <a href="http://www.ulb.ac.be/sciences/ueg/html_files/softwares.html">here</a>) provides a solution to the multiple alignment problem by combining a Hidden Markov model (HMM), a progressive alignment algorithm, and a probabilistic character substitution model. This method &nbsp;allows to compute the posterior probability of each alignment column. We do not intend to continue developing alignment methods in the near future. On the other hand, we remain interested into tree inference methods. For example, we recently developed the meta-population Genetic Algorithm [MetaGA; PNAS, 99: 10516-10521 (2002)] as well as Artificial Intelligence approaches, such as the Ant Colony Optimization algorithm. The MetaGA is implemented in the software metaPIGA, available <a href="http://www.ulb.ac.be/sciences/ueg/html_files/softwares.html">here</a>.</p> <h4>Selected recent publications</h4> <h5>Experimental Phylogenetics</h5> <ul> <li>Cassens I., Vicario S., Waddell V. G., Balchowsky H., Van Belle D., Wang Ding, Chen Fan, Lal Mohan R.S., Sim&otilde;es-Lopes P. C., Bastida R., Meyer A., Stanhope M. J.
&amp; M. C. Milinkovitch.
Independent Adaptation to Riverine Habitats Allowed Survival of Ancient
Cetacean Lineages.
PNAS (Proc. National Academy of Sciences, USA), 97: 11343-11347 (2000)<br /></li> <li>Termonia A., Hsiao T. H., Pasteels J.M. &amp; M. C. Milinkovitch.
Feeding specialization and host-derived chemical defense in Chrysomeline leaf beetles did not lead to an evolutionary dead end.
PNAS (Proc. National Academy of Sciences, USA), 98: 3909-3914 (2001)<br /></li> <li>Bossuyt F. &amp; M. C. Milinkovitch. Amphibians as Indicators of Early Tertiary 'Out-of-India' Dispersal of Vertebrates.
Science 292: 93-95 (2001)<br /></li> <li>Bossuyt F., Meegaskumbura M., Beenaerts N., Gower D.J., Pethiyagoda R., Roelants K., Mannaert A., Wilkinson M., Bahir M. M., Manamendra-Arachchi K., Ng P.K.L., Schneider C. J., Oommen O.V. &amp; Michel C. Milinkovitch. Local Endemism Within the Western Ghats-Sri Lanka Biodiversity Hotspot
Science, 306: 479-481 (2004)</li> </ul> <h5>Computational phylogenetics</h5> <ul> <li>Lemmon A. R. &amp; M. C. Milinkovitch. The metapopulation genetic algorithm: an efficient solution for the problem of large phylogeny estimation.
PNAS, 99: 10516-10521 (2002)<br /></li> <li>L&ouml;ytynoja A. &amp; M. C. Milinkovitch. A hidden Markov model for progressive multiple alignment.
Bioinformatics, 19: 1505&ndash;1513 (2003)<br /></li> <li>Catanzaro D., Pesenti R &amp; M. C. Milinkovitch. An Ant Colony Optimization Algorithm for Phylogeny Estimation under the Minimum Evolution Principle
BMC Evolutionary Biology 7:228 (2007)&nbsp;<br /></li> <li>Tzika A. C., Helaers R, Van de Peer Y. &amp; M. C. Milinkovitch. MANTiS: a phylogenetic framework for multi-species genome comparisons
Bioinformatics, 24 (2):151-157 (2008)</li> </ul> <h3>Applied evolutionary genetics</h3> <p><a href="/system/illustrations/0000/0093/IMG_0251.jpg"><img src="/system/illustrations/0000/0093/IMG_0251_small.jpg" alt="IMG_0251.jpg_small" title="IMG_0251.jpg_small" width="230" height="173" style="float: right;" /></a>Given the explosive increase in sequences available, biologists are faced with a huge bulk of raw data that must be analyzed. Efficient exploitation of this unprecedented massive amount of biological information will necessarily require large scale / high throughput approaches that, in turn, will necessitate selection of recombinants. An effective solution to this latter problem is provided biotechnological tools that make use of poison and antidote genes. Several of these tools have been developed in my laboratory in close collaboration with Delphi Genetics SA, a spin-off company founded by Philippe Gabant, C&eacute;dric Szpirer (CS), myself, and the Free University of Brussels. Delphi Genetics commercialises several kits for molecular cloning and protein production that surpass in efficiency all competing technologies. More information is available at <a href="http://www.delphigenetics.com">www.delphigenetics.com</a></p> <p>Automation of DNA engineering technology requires the development of homologous recombination tools and the discovery of new poison/antidote genes. Hence, we have identified new candidate genes through automated comparison of known poison-antidote genes against sequences accumulating in public databases. These genes are then functionally tested in different bacterial and eukaryotic models. Furthermore, we have performed phylogenetic analyses of poison-antidote genes in order to understand the origin and evolution of these very peculiar, and probably selfish, genetic elements.</p> <h4>Selected recent publications:</h4> <ul> <li>Szpirer C. Y. &amp; M. C. Milinkovitch. Separate-Component-Stabilization (SCS) System for protein and DNA production without the use of antibiotics.
Biotechniques 38: 775-781 (2005)<br /></li> <li>Guglielmini J., Szpirer C., &amp; M. C. Milinkovitch. Automated Discovery and Phylogenetic Analysis of New Toxin-Antitoxin Systems.
BMC Microbiology, 8: 104 (2008)</li> </ul> <h3>Evolutionary Developmental Genetics (Evo-Devo)</h3> <p>Molecular developmental biology and evolutionary molecular genetics have proven, these last 20 years, to be highly successful but, strangely enough, remained largely separated despite the obvious conceptual links between the two disciplines. Indeed, on one hand, molecular developmental biologists have focused on the use of a handful of model organisms for deciphering the fascinating processes by which cells differentiate, as well as tissues, organs, and organisms grow and develop. On the other hand, evolutionary molecular geneticists have investigated the modes and tempos of DNA and protein evolution in a multitude of organisms (from viruses to vertebrates), and developed the laboratory techniques and analytical methods allowing today to infer phylogenies, reconstruct population histories, uncover hidden biodiversity, and detect selection and stochastic patterns in laboratory and natural populations.</p> <p><a href="/system/illustrations/0000/0098/slide.jpg"><img src="/system/illustrations/0000/0098/slide_small.jpg" alt="slide.jpg_small" title="slide.jpg_small" width="230" height="271" style="float: left;" /></a></p> <p>Given that a large proportion of evolutionary mechanisms, namely, those pertaining to natural selection, acts on the phenotypes that originate from development (i.e., genetic information and epigenetic parameters are translated into phenotypes during development), it was fully realised only in the 1990&rsquo;s, that our understanding of both evolution and development would greatly benefit from the partial merging of the two above-mentioned disciplines into what is called today Evolutionary Developmental Biology (Evo-Devo). The existence of identical signals for the, supposedly independent, development of structures of similar functions (e.g., the eye) in very different lineages, has shaken concepts as central/major as homology. The most important defining feature of Evo-Devo is that it explicitly addresses the generative mechanisms underlying the evolution of life forms on both short-term and long-term time-scales. Uncovering these mechanisms will require the use of many additional model organisms. Evo-Devo studies are, by essence, highly multidisciplinary and integrative as they require investigation, across lineages, of morphological/ physiological, as well as of the underlying genomic, characters. Currently, my major interests in Evo-Devo revolve around two topics: uncovering the genetic basis of (i) evolutionary novelties and of (ii) phenotypic convergences.</p> <h4>Selected recent publications</h4> <ul> <li>Milinkovitch M.C. &amp; A. C. Tzika. Escaping the Mouse Trap; the Selection of New Evo-Devo Model Species 
Journal of Experimental Zoology (Mol. Dev. Evol.) 308B: 337&ndash;346 (2007)<br /></li> <li>Tzika A. C., Helaers R, Van de Peer Y. &amp; M. C. Milinkovitch. MANTiS: a phylogenetic framework for multi-species genome comparisons
Bioinformatics, 24 (2):151-157 (2008)</li> </ul> <h3>LANE full web site: <a href="http://www.lanevol.org">http://www.lanevol.org</a></h3> <h3>Introduction</h3> <p>Evolution is a unifying paradigm with important implications in virtually all areas of biology. Indeed, all characters that are studied in biology, from morphological or behavioural traits to the immune system or the fine regulatory mechanisms of gene expression are the products of biological evolution. Evolutionary concepts are pertinent not only to that large diversity of possible applications across disciplines, but also to the massive realm of diversity across living beings, i.e., from natural/artificial clones to the major kingdoms made of approximately 50 millions of extant species, all living beings are connected through pedigrees and the phylogenetic tree of life.</p> <p>The core activities in my laboratory (Brussels, Belgium) have revolved these last 10 years around three major domains of evolutionary genetics: Conservation Genetics, Molecular Phylogenetics, and Bioinformatics. As I just moved to the University of Geneva (Switzerland), I intend to continue working on a selected number of issues within some of these disciplines, but a significant proportion of our activities will also relate to two fascinating and promising challenges in evolutionary biology: Evolutionary Developmental Genetics and Artificial Evolution.</p> <p>Please, find below a short description of our research projects. Much additional information is available on the LANE web site (under construction).</p> <h3>Conservation Genetics, population genetics, and phylogeography</h3> <p><a href="/system/illustrations/0000/0078/P_spin_1.jpg"><img src="/system/illustrations/0000/0078/P_spin_1_mid.jpg" alt="P_spin_1.jpg_mid" title="P_spin_1.jpg_mid" width="310" height="205" style="float: right; margin-left: 5px; margin-right: 5px;" /></a></p> <p>It is indisputable that environmental changes, including human disturbances, have a striking impact on the biodiversity of ecosystems. &nbsp;Using exceptional sample archives, molecular genetic techniques, and latest analytical methods, we attempt to describe the genetic diversity variations (in time and space) caused by natural history (e.g., social systems), genetics (e.g., mitochondrial vs. nuclear DNA), but also historical (e.g., environmental changes and human exploitation) parameters. Intra-specific genealogical lineages can be investigated through phylogenetic and network methods and their diversity correlated to their geographic distribution (= phylogeographic approach). Given their predictive value, the results of these endeavours can significantly contribute, among others, to environment policy decisions. Several of our analyses have lead to practical recommendations for natural or captive population management (South-American dolphins, Giant Gal&aacute;pagos tortoises, Jamaican Boas).</p> <p>By integrating phylogenetic, coalescence, and population genetic approaches, we investigate in several natural populations the influence of historical factors on the present stratification and levels of genetic diversity. We use multiple molecular markers including microsatellites and SNPs. In the near future, we will concentrate our efforts in this field on populations of South-American dolphins as well as on large reptile species.</p> <p>Beside gathering and analyzing new molecular markers in natural populations, we have also developed in-silico and in-vitro population models that we used in simulation studies. The predictions made can then be validated with real data from natural populations.</p> <h4>Selected recent publications:</h4> <ul> <li>Milinkovitch M.C., Monteyne D., Gibbs J.P., Fritts T.H., Tapia W., Snell H.L., Tiedemann R., Caccone A. &amp; J. R. Powell. Genetic analysis of a successful repatriation program: Giant Gal&aacute;pagos tortoises.
Proceedings of the Royal Society, London, B, 271: 341-345 (2004)
Check also the &ldquo;News Feature&rdquo; in Nature (2004, vol. 429: pages 498-500) &ldquo;One of a kind&rdquo; by H. Nicholls.</li> <li>Cassens I., Van Waerebeek K., Best P.B., Tzika A., Van Helden A.L., Crespo E.A. &amp; M. C. Milinkovitch.
Evidence for male dispersal along the coasts but no migration in pelagic waters in dusky dolphins (Lagenorhynchus obscurus).
Molecular Ecology, 14 : 107-121 (2005)</li> <li>Tzika A. C., Koenig S., Miller R., Garcia G., Remy C. &amp; M. C. Milinkovitch. Population structure of an endemic vulnerable species, the Jamaican boa (Epicrates subflavus)
Molecular Ecology 17, 533-544 (2008)</li> </ul> <h3>Experimental and computational phylogenetics</h3> <p>Our contribution to the field of macro-evolutionary molecular genetics primarily consisted up to now into inferring historical information from DNA and protein sequences, as well as SINE (&ldquo;Short Interspersed Nuclear Elements&rdquo;) insertion events, to uncover evolutionary modes and patterns of morphological, physiological, biogeographical, ecological, molecular, and epidemiological characters in taxonomic groups as diverse as HIV viruses (molecular epidemiology), early eukaryotes, myzostomids, leaf beetles, amphibians, and cetaceans.</p> <p><a href="/system/illustrations/0000/0088/Pic1.jpg"><img src="/system/illustrations/0000/0088/Pic1_small.jpg" alt="Pic1.jpg_small" title="Pic1.jpg_small" width="230" height="193" style="float: left;" /></a>We also devoted significant efforts to the development of new heuristics for multiple sequence alignment and for phylogeny inference. Indeed, optimality-criterion based inference (e.g., using Maximum Likelihood) is a notoriously difficult endeavour because the number of solutions increases explosively (factorially) with the number of taxa (i.e., multiple alignment and phylogeny inference are NP-hard combinatorial optimization problems: no known algorithm can solve it in polynomial time). Given the tremendous number of new questions in evolutionary biology that could be investigated through the use of larger taxon samplings, most researchers are ready to give up the quest for the absolute optimal alignment and the absolute optimal tree, opting instead for the ability to analyze large data sets in practical computing times, provided that these methods yield optimal or near-optimal solutions with high probability. In response to this trend, much of the current research in phyloinformatics concentrates on the development of more efficient heuristic approaches. Our multiple-alignment method (implemented in the program ProAlign 1.0 and available <a href="http://www.ulb.ac.be/sciences/ueg/html_files/softwares.html">here</a>) provides a solution to the multiple alignment problem by combining a Hidden Markov model (HMM), a progressive alignment algorithm, and a probabilistic character substitution model. This method &nbsp;allows to compute the posterior probability of each alignment column. We do not intend to continue developing alignment methods in the near future. On the other hand, we remain interested into tree inference methods. For example, we recently developed the meta-population Genetic Algorithm [MetaGA; PNAS, 99: 10516-10521 (2002)] as well as Artificial Intelligence approaches, such as the Ant Colony Optimization algorithm. The MetaGA is implemented in the software metaPIGA, available <a href="http://www.ulb.ac.be/sciences/ueg/html_files/softwares.html">here</a>.</p> <h4>Selected recent publications</h4> <h5>Experimental Phylogenetics</h5> <ul> <li>Cassens I., Vicario S., Waddell V. G., Balchowsky H., Van Belle D., Wang Ding, Chen Fan, Lal Mohan R.S., Sim&otilde;es-Lopes P. C., Bastida R., Meyer A., Stanhope M. J.
&amp; M. C. Milinkovitch.
Independent Adaptation to Riverine Habitats Allowed Survival of Ancient
Cetacean Lineages.
PNAS (Proc. National Academy of Sciences, USA), 97: 11343-11347 (2000)<br /></li> <li>Termonia A., Hsiao T. H., Pasteels J.M. &amp; M. C. Milinkovitch.
Feeding specialization and host-derived chemical defense in Chrysomeline leaf beetles did not lead to an evolutionary dead end.
PNAS (Proc. National Academy of Sciences, USA), 98: 3909-3914 (2001)<br /></li> <li>Bossuyt F. &amp; M. C. Milinkovitch. Amphibians as Indicators of Early Tertiary 'Out-of-India' Dispersal of Vertebrates.
Science 292: 93-95 (2001)<br /></li> <li>Bossuyt F., Meegaskumbura M., Beenaerts N., Gower D.J., Pethiyagoda R., Roelants K., Mannaert A., Wilkinson M., Bahir M. M., Manamendra-Arachchi K., Ng P.K.L., Schneider C. J., Oommen O.V. &amp; Michel C. Milinkovitch. Local Endemism Within the Western Ghats-Sri Lanka Biodiversity Hotspot
Science, 306: 479-481 (2004)</li> </ul> <h5>Computational phylogenetics</h5> <ul> <li>Lemmon A. R. &amp; M. C. Milinkovitch. The metapopulation genetic algorithm: an efficient solution for the problem of large phylogeny estimation.
PNAS, 99: 10516-10521 (2002)<br /></li> <li>L&ouml;ytynoja A. &amp; M. C. Milinkovitch. A hidden Markov model for progressive multiple alignment.
Bioinformatics, 19: 1505&ndash;1513 (2003)<br /></li> <li>Catanzaro D., Pesenti R &amp; M. C. Milinkovitch. An Ant Colony Optimization Algorithm for Phylogeny Estimation under the Minimum Evolution Principle
BMC Evolutionary Biology 7:228 (2007)&nbsp;<br /></li> <li>Tzika A. C., Helaers R, Van de Peer Y. &amp; M. C. Milinkovitch. MANTiS: a phylogenetic framework for multi-species genome comparisons
Bioinformatics, 24 (2):151-157 (2008)</li> </ul> <h3>Applied evolutionary genetics</h3> <p><a href="/system/illustrations/0000/0093/IMG_0251.jpg"><img src="/system/illustrations/0000/0093/IMG_0251_small.jpg" alt="IMG_0251.jpg_small" title="IMG_0251.jpg_small" width="230" height="173" style="float: right;" /></a>Given the explosive increase in sequences available, biologists are faced with a huge bulk of raw data that must be analyzed. Efficient exploitation of this unprecedented massive amount of biological information will necessarily require large scale / high throughput approaches that, in turn, will necessitate selection of recombinants. An effective solution to this latter problem is provided biotechnological tools that make use of poison and antidote genes. Several of these tools have been developed in my laboratory in close collaboration with Delphi Genetics SA, a spin-off company founded by Philippe Gabant, C&eacute;dric Szpirer (CS), myself, and the Free University of Brussels. Delphi Genetics commercialises several kits for molecular cloning and protein production that surpass in efficiency all competing technologies. More information is available at <a href="http://www.delphigenetics.com">www.delphigenetics.com</a></p> <p>Automation of DNA engineering technology requires the development of homologous recombination tools and the discovery of new poison/antidote genes. Hence, we have identified new candidate genes through automated comparison of known poison-antidote genes against sequences accumulating in public databases. These genes are then functionally tested in different bacterial and eukaryotic models. Furthermore, we have performed phylogenetic analyses of poison-antidote genes in order to understand the origin and evolution of these very peculiar, and probably selfish, genetic elements.</p> <h4>Selected recent publications:</h4> <ul> <li>Szpirer C. Y. &amp; M. C. Milinkovitch. Separate-Component-Stabilization (SCS) System for protein and DNA production without the use of antibiotics.
Biotechniques 38: 775-781 (2005)<br /></li> <li>Guglielmini J., Szpirer C., &amp; M. C. Milinkovitch. Automated Discovery and Phylogenetic Analysis of New Toxin-Antitoxin Systems.
BMC Microbiology, 8: 104 (2008)</li> </ul> <h3>Evolutionary Developmental Genetics (Evo-Devo)</h3> <p>Molecular developmental biology and evolutionary molecular genetics have proven, these last 20 years, to be highly successful but, strangely enough, remained largely separated despite the obvious conceptual links between the two disciplines. Indeed, on one hand, molecular developmental biologists have focused on the use of a handful of model organisms for deciphering the fascinating processes by which cells differentiate, as well as tissues, organs, and organisms grow and develop. On the other hand, evolutionary molecular geneticists have investigated the modes and tempos of DNA and protein evolution in a multitude of organisms (from viruses to vertebrates), and developed the laboratory techniques and analytical methods allowing today to infer phylogenies, reconstruct population histories, uncover hidden biodiversity, and detect selection and stochastic patterns in laboratory and natural populations.</p> <p><a href="/system/illustrations/0000/0098/slide.jpg"><img src="/system/illustrations/0000/0098/slide_small.jpg" alt="slide.jpg_small" title="slide.jpg_small" width="230" height="271" style="float: left;" /></a></p> <p>Given that a large proportion of evolutionary mechanisms, namely, those pertaining to natural selection, acts on the phenotypes that originate from development (i.e., genetic information and epigenetic parameters are translated into phenotypes during development), it was fully realised only in the 1990&rsquo;s, that our understanding of both evolution and development would greatly benefit from the partial merging of the two above-mentioned disciplines into what is called today Evolutionary Developmental Biology (Evo-Devo). The existence of identical signals for the, supposedly independent, development of structures of similar functions (e.g., the eye) in very different lineages, has shaken concepts as central/major as homology. The most important defining feature of Evo-Devo is that it explicitly addresses the generative mechanisms underlying the evolution of life forms on both short-term and long-term time-scales. Uncovering these mechanisms will require the use of many additional model organisms. Evo-Devo studies are, by essence, highly multidisciplinary and integrative as they require investigation, across lineages, of morphological/ physiological, as well as of the underlying genomic, characters. Currently, my major interests in Evo-Devo revolve around two topics: uncovering the genetic basis of (i) evolutionary novelties and of (ii) phenotypic convergences.</p> <h4>Selected recent publications</h4> <ul> <li>Milinkovitch M.C. &amp; A. C. Tzika. Escaping the Mouse Trap; the Selection of New Evo-Devo Model Species 
Journal of Experimental Zoology (Mol. Dev. Evol.) 308B: 337&ndash;346 (2007)<br /></li> <li>Tzika A. C., Helaers R, Van de Peer Y. &amp; M. C. Milinkovitch. MANTiS: a phylogenetic framework for multi-species genome comparisons
Bioinformatics, 24 (2):151-157 (2008)</li> </ul> 15 LANE: Laboratory of Artificial & Natural Evolution LANE: Laboratory of Artificial & Natural Evolution 327 Artificial & Natural Evolution 2008-08-01T00:00:00+02:00 2009-05-08T15:57:09+02:00 http://www.lanevol.org