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: 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.
Most activities in Milinkovitch’s laboratory revolves now around Evolutionary Developmental Genetics (EvoDevo) and the physics of biology although we continue working on a selected number of issues in Conservation Genetics, Molecular Phylogenetics, and Bioinformatics.
Please, find below a short and general description of our research projects. Much additional information is available on the LANE web site.
Evolutionary Developmental Genetics (Evo-Devo)
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.
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’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 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 characters, as well as of the underlying molecular determinism. Currently, our major interests in Evo-Devo revolve around two topics: (i) uncovering the molecular genetic basis of evolutionary novelties and of phenotypic convergences, and (ii) the physics of developmental processes. Much additional information is available on Milinkovitch’s lab web site.
Conservation Genetics, population genetics, and phylogeography
It is indisputable that environmental changes, including human disturbances, have a striking impact on the biodiversity of ecosystems. Using exceptional sample archives, multiple molecular markers (including microsatellites and SNPs), and latest analytical methods, we describe the variations in stratification and levels of genetic diversity 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 are investigated through phylogenetic and network methods and their diversity correlated to their geographic distribution (= phylogeography). Given their predictive value, the results of this work can significantly contribute, among others, to environment policy decisions. Several of our analyses have lead to practical recommendations for natural or captive population management (e.g., South-American dolphins, Giant Galápagos tortoises, Jamaican Boas).
Experimental and computational phylogenetics
Our contribution to the field of molecular phylogenetics primarily consisted into inferring historical information from DNA and protein sequences, as well as SINE (“Short Interspersed Nuclear Elements”) 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), leaf beetles, amphibians, and cetaceans.
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 . Given the tremendous number of new questions in evolutionary biology that could be investigated through the use of larger taxon samplings, most researchers have given 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 here) provides an efficient solution by combining a Hidden Markov model (HMM), a progressive alignment algorithm, and a probabilistic character substitution model. We do not intend to continue developing alignment methods in the near future. On the other hand, we continue developing methods for phylogeny inference such as the “Meta-population Genetic Algorithm” [MetaGA; PNAS, 99: 10516-10521 (2002)] that we recently implemented in the version 2 of the MetaPIGA software (BMC Bioinformatics 2010, 11: 379).
Selected recent publications
- Brykczynska U., Tzika A.C., Rodriguez I. & M. C. Milinkovitch.
Contrasted evolution of the vomeronasal receptor repertoires in Mammals and Squamate reptiles.
Genome Biol Evol. 5(2):389-401 (2013)
- Milinkovitch M.C., Manukyan L., Debry A., Di-Poï N., Martin S., Singh D., Lambert D., Zwicker M.
Crocodile Head Scales Are Not Developmental Units But Emerge from Physical Cracking.
Science 339, 78-81 (2013)
- Milinkovitch et al.
Recovery of a nearly extinct Galápagos tortoise despite minimal genetic variation.
Evolutionary Applications 6, 377–383 (2013)
- Tzika A.C., Helaers R., Schramm G. & M. C. Milinkovitch.
Reptilian-transcriptome v1.0, a glimpse in the brain transcriptome of five divergent Sauropsida lineages and the phylogenetic position of turtles.
EvoDevo 2011, 2: 19
- Tiedemann R., Paulus K.B., Havenstein K., Thorstensen S., Petersen A., Lyngs P. & M. C. Milinkovitch.
Alien eggs in duck nests: brood parasitism or a help from Grandma?
Molecular Ecology 20, 3237–3250 (2011)
- Milinkovitch, Helaers, Depiereux, Tzika & Gabaldon.
2X genomes - depth does matter .
Genome Biology, 11 (2): R16 (2010)
- Helaers & Milinkovitch
MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics.
BMC Bioinformatics, 11:379 (2010)
- Di-Poï, Montoya-Burgos, Miller, Pourquié, Milinkovitch & Duboule
Changes in Hox genes’ structure and function during the evolution of the squamate body plan.
Nature, 464: 99-103 (2010)
- Tzika, Helaers, Van de Peer & Milinkovitch.
MANTiS: a phylogenetic framework for multi-species genome comparisons.
Bioinformatics, 24 (2):151-157 (2008)
- Milinkovitch & Tzika.
Escaping the Mouse Trap; the Selection of New Evo-Devo Model Species.
Journal of Experimental Zoology (Mol. Dev. Evol.) 308B: 337–346 (2007)
- Bossuyt, Meegaskumbura, Beenaerts, Gower, Pethiyagoda, Roelants, Mannaert, Wilkinson, Bahir, Manamendra-Arachchi, Ng, Schneider, Oommen & Milinkovitch.
Local Endemism Within the Western Ghats-Sri Lanka Biodiversity Hotspot .
Science, 306: 479-481 (2004)
- Löytynoja & Milinkovitch.
A hidden Markov model for progressive multiple alignment.
Bioinformatics, 19: 1505–1513 (2003)
- Lemmon & Milinkovitch.
The metapopulation genetic algorithm: an efficient solution for the problem of large phylogeny estimation.
PNAS, 99: 10516-10521 (2002)
- Bossuyt & Milinkovitch.
Amphibians as Indicators of Early Tertiary 'Out-of-India' Dispersal of Vertebrates.
Science 292: 93-95 (2001)
- Cassens, Vicario, Waddell, Balchowsky, Van Belle, Wang Ding, Chen Fan, Lal Mohan, Simões-Lopes, Bastida, Meyer, Stanhope & Milinkovitch.
Independent Adaptation to Riverine Habitats Allowed Survival of Ancient Cetacean Lineages.
PNAS (Proc. National Academy of Sciences, USA), 97: 11343-11347 (2000)