Luca Ferretti:

Senior Researcher in Statistical Genetics and Pathogen Dynamics

Big Data Institute, University of Oxford

Contacts: ,


  • Ph.D in Theoretical Physics, 2008, SISSA, Trieste
  • M.Sc. in Physics, 2004, University of Pisa and Scuola Normale Superiore, Pisa

Scientific interests:

  • Evolution and molecular biology of viruses
  • Population genetics
  • Genomics
  • Next Generation Sequencing
  • Methods in molecular evolution
  • Complex networks

My research focuses on computational, statistical and modelling approaches to evolutionary questions in genomics. High-Throughput Sequencing technologies are generating an unprecedented amount of data, allowing researchers to study different facets of biological systems at the same time. As an example, genomic analysis of sequences from infected cells may reveal the origin and the evolutionary dynamics of the pathogen, the demographic and selective history of the host species, as well as the genetic pathways and the molecular mechanisms involved in the infection. These experimental approaches have blurred the boundaries between fields like population genetics, evolutionary biology, systems biology, microbiology and epidemiology and call for new and advanced statistical methods. My main interests lie in the analysis of high-throughput data to detect recent natural selection from genomic variability, uncover the determinants of intra- and inter-host evolution of pathogens from sequence analysis of microorganisms and their hosts, and in the integration of multiple genomic datasets.

This century has been called "the century of biology" but at the same time it is witnessing the big data revolution. Hence, bioinformatics represents a key set of skills for the new generation of biologists. In fact, quantitative and computational approaches are required more and more often both in academic research and industry. These methods require a solid understanding of modelling, statistics and algorithms.

My research revolves around the topic of genomic variability, declined along three main directions:

  • Population genetics and analyses of genetic diversity
  • Genomics, transcriptomics and integrative biology
  • Population genetics and evolution of pathogens

Current affiliation:

  • Big Data Institute, Nuffield Department of Medicine, University of Oxford, United Kingdom.

Past affiliations:

  • Integrative Biology group, The Pirbright Institute, Ash Road, Woking, United Kingdom.
  • UMR 7138 (Systématique, Adaptation et Evolution) and Atelier de BioInformatique, Université Pierre et Marie Curie (Paris VI), Paris
  • CIRB, Collège de France, Paris
  • Institute for Genetics, University of Cologne
  • CRAG and Universitàt Autonoma de Barcelona, Bellaterra, Barcelona

Research topics

Population genetics, genomics and evolution

  • Intra-host genetic diversity and evolution
    • We found that FMDV infections in buffaloes often present a peculiar pattern of genetic diversity, corresponding to a multi-swarm/quasi-species structure. This unusual diversity structure allowed us to detect within-host selection, pervasive recombination and epistasis at the intra-host level [1,2]. Our results suggest that the evolutionary dynamics of FMDV is considerably more complex than previously thought, with intra-host evolutionary forces playing a major role in it.
    1. Ferretti L, Di Nardo A, Singer B, Lasecka-Dykes L, Logan G, Wright CF, Pérez-Martín E, King DP, Tuthill TJ and Ribeca P, “Within-host recombination in the Foot-and-Mouth Disease Virus genome”, Viruses, 10(5)221 (2018).
    2. Ferretti L, Pérez-Martín E, Zhang F, Maree F, Charleston B and Ribeca P, "Pervasive within-host recombination and epistasis as major determinants of the molecular evolution of the Foot-and-Mouth Disease Virus capsid", in preparation.
  • Population genetics of selected variants
    • We developed a null framework to test selection on specific variants based on the patterns of linked mutations [1,2]. These methods are being applied to an evolutionary classification of chromosomal inversions detected as polymorphic in human populations [3].
    1. Ferretti L, Klassmann A, Raineri E, Ramos-Onsins SE, Wiehe T and Achaz G, “The neutral frequency spectrum of linked sites”, accepted in Theoretical Population Biology (2018).
    2. Klassmann A and Ferretti L, “The third moments of the site frequency spectrum”, Theoretical Population Biology, 120:16-28 (2018).
    3. Giner-Delgado C, Villatoro S, Lerga-Jaso J, Gayà-Vidal M, Oliva M, Castellano D, Izquierdo D, Noguera I, Bitarello B, Olalde I, Delprat A, Blancher A, Lalueza C, Esko T, O’Reilly P, Andrés A, Ferretti L, Pantano L, Puig M and Cáceres M, “Functional and evolutionary impact of polymorphic inversions in the human genome”, in preparation.
  • Epistasis and evolution in fitness landscapes
    • Try out MaGelLan, the Maps of Genetical Landscapes, our new website to analyse and visualise fitness landscapes!
    • We have several ongoing project on measures of epistasis in fitness landscapes [3], divergence of ortholog sequences and long-term evolution in the protein universe with multidimensional epistasis [4,5], characterization of models of fitness landscapes [2] and analysis of evolutionary constraints imposed by landscape features [1,6].
    1. Ferretti L, Weinreich D and Achaz G, “Evolutionary constraints in fitness landscapes”, accepted in Heredity (2018).
    2. Hwang S, Schmiegelt B, Ferretti L and Krug J, “Universality classes of interaction structures for NK fitness landscapes”, accepted in Journal of Statistical Physics (2018).
    3. Ferretti L, Schmiegelt B, Weinreich D, Yamauchi A, Kobayashi Y, Tajima F and Achaz G, “Measuring epistasis in fitness landscapes: the correlation of fitness effects of mutations”, Journal of Theoretical Biology, 396:132-143 (2016).
    4. Usmanova DR, Ferretti L, Povolotskaya IS, Vlasov PK, Kondrashov FA, A model of substitution trajectories in sequence space and long-term protein evolution, Mol. Biol. Evol. 32(2):542- 54 (2015).
    5. Ledda A, Achaz G, Kondrashov FA and Ferretti L, Long-term evolution in epistatic fitness landscapes, in preparation.
    6. Ferretti L, Ledda A and Achaz G, Heterogeneities in the distribution of fitness effects, in preparation.
  • Methods for population genetics from Next Generation Sequencing data
      • We developed several methods for NGS data. We extended neutrality tests like Tajima's D and Fay and Wu's H to NGS data, both using called sequences with missing data and correcting for missing information [3]. We presented a general framework for Watterson estimators of variability from all kinds of NGS data, including haploid and diploid individuals, trios, pools and polyploids [2] as well as a general analysis of the frequency spectrum in autopolyploids [7]. For pooled data, we developed a Bayesian SNP caller using the neutral frequency spectrum as a prior [4] and proposed a Maximum Composite Likelihood estimator of variability and a complete set of tests: Tajima's D, Fay and Wu's H, HKA etc, specific for pooled NGS samples [1]. We also wrote a recent review on population genomics methods for neglected genomes, focused on arthropods [5] and a (slightly outdated) review on the methods and applications of NGS for animal genetics, containing some material on pool sequencing [6].
    1. Ferretti L, Ramos-Onsins SE and Perez-Enciso M, Population genomics from pool sequencing, Molecular Ecology (2013), 22: 5561-5576.
    2. Ferretti L and Ramos-Onsins SE, Watterson estimators for Next Generation Sequencing: from trios to autopolyploids, Theor Popul Biol. 100C:79-87 (2015). arXiv.
    3. Ferretti L*, Raineri E* and Ramos-Onsins SE, Neutrality tests for sequences with missing data, Genetics 191(4):1397-401 (2012).
    4. Raineri E, Ferretti L, Esteve-Codina A, Nevado B, Heath S and Perez-Enciso M, SNP calling by sequencing pooled samples, BMC Bioinformatics 13:239 (2012).
    5. Hasselmann M, Ferretti L and Zayed A, “Beyond fruit-flies: Population genomic advances in non-dipteran arthropods”, Briefings in Functional Genomics, 14 (6): 424-431 (2015).
    6. Perez-Enciso M and Ferretti L, Massive parallel sequencing in animal genetics: wherefroms and wheretos, Anim Genet. 41(6):561-9 (2010).
    7. Ferretti L, Ribeca P and Ramos-Onsins SE, "The Site Frequency/Dosage Spectrum of autopolyploid populations", submitted.
  • Genetic mechanisms of sex determination and dosage balance in insects
  • We studied the allelic variability in the hypervariable complementary sex determination (csd) locus in Apis mellifera [1]. We found conditions for functional heterozygotes, based on minimum aminoacid and length diversity, and we showed that negative-frequency selection generated a large number of functionally different alleles (about 150 worldwide and 100 in Kenya only). We also studied the mechanisms of dosage compensation of sexual chromosomes during the development of Anopheles gambiae [2]. The expression of the X chromosome is (fully or partially) dosage compensated in larvae and pupae.
    • Lechner S, Ferretti L, Schöning C, Kinuthia W, Willemsen D and Hasselmann M, Nucleotide variability at its limit? Insights into the number and evolutionary dynamics of the sex-determining specificities of the honeybee Apis mellifera, Mol. Biol. Evol. 31 (2) 272-287 (2013).
    • Rose G, Krzywinska E, Kim J, Revuelta L, Ferretti L and Krzywinski J, “Dosage compensation in the African malaria mosquito Anopheles gambiae”, Genome Biology and Evolution, 8 (2): 411-425 (2016).
  • Population genetics estimators and neutrality tests
  • We proposed a class of ''optimal'' neutrality tests similar to Tajima's D but optimized for a given alternative model of evolution [1] and we described a method to build them from the expected frequency spectrum of the alternative model. These tests belong to the general class of tests proposed by Achaz (Genetics, 2009). Moreover, we studied some of their properties and extensions [2]. We also discuss the relation between neutrality tests and their interpretation in terms of genealogical trees [3].
    1. Ferretti L, Perez-Enciso M, Ramos-Onsins SE, Optimal neutrality tests based on the frequency spectrum, Genetics 186(1):353-65 (2010).
    2. Ferretti L, Marmorini G, Ramos-Onsins SE, Properties of neutrality tests based on allele frequency spectrum, arXiv.
    3. Ferretti L, Ledda A, Achaz G, Wiehe T and Ramos-Onsins SE, “Decomposing the site frequency spectrum: the impact of tree topology on neutrality tests”, Genetics, 207(1):229-240 (2017).
  • Tree balance in the coalescent
  • We derived the probabilities of recombination events that change tree height in the neutral model and we derived first-order transition probabilities for the root inbalance (which is a simple measure of tree balance) after a single recombination event [1]. These results are a first step towards a theoretical basis for haplotype tests of selection.
    1. Ferretti L, Disanto F, Wiehe T, The effect of single recombination events on coalescent tree height and shape, PLoS One. 2013 Apr 8;8(4):e60123. PLoS One.
  • Evolution of recombination in mammals
  • We studied the evolution of the recombination rate, number of crossovers etc. in several species of mammals [1]. Recombination rates increase over time and their evolution appears to be punctuated and subject to selection. Another interesting observation is the high recombination rate and the strangely weak crossover interference in the tiger.
    • Segura J, Ferretti L, Ramos-Onsins S, Capilla L, Farre M, Reis F, Oliver-Bonet M, Fernandez-Bellon H, Garcia F, Garcia-Caldes M, Robinson T, Ruiz-Herrera A, Evolution of recombination in eutherian mammals: insights into mechanisms that affect recombination rates and crossover interference, Proceedings of the Royal Society B, 280 1771 1471-2954 (2013).
  • Swine evolution and domestication
  • We applied the methods developed for pooled NGS data to variability and differentiation in wild boar and international pig breeds, in order to infer which genes and functions were targets of artificial selection during domestication [3]. We studied the patterns of variability in a single Iberian pig [2] and in pooled data from an Iberian pig population [1].
    1. Esteve-Codina A, Paudel Y, Ferretti L, Raineri E, Megens HJ, Silio L, Rodriguez MC, Groenen MA, Ramos-Onsins SE, Perez-Enciso M, Dissecting structural and nucleotide genome-wide variation in inbred Iberian pigs, BMC Genomics. 2013 Mar 5;14:148.
    2. Esteve-Codina A, Kofler R, Himmelbauer H, Ferretti L, Vivancos AP, Groenen MA, Folch JM, Rodriguez MC, Perez-Enciso M, Partial short-read sequencing of a highly inbred Iberian pig and genomics inference thereof, Heredity 107(3):256-64 (2011).
    3. Amaral AJ, Ferretti L, Megens HJ, Crooijmans RP, Nie H, Ramos-Onsins SE, Perez-Enciso M, Schook LB, Groenen MA, Genome-wide footprints of pig domestication and selection revealed through massive parallel sequencing of pooled DNA, PLoS One 6(4):e14782 (2011). PLoS One.
  • Inference of spatial relations along the genome
  • We developed a technique to infer relations between motifs and other genomic features from their distribution along the genome [1], showing that under general assumptions these features can be described by a log-linear Poisson model, and estimating its parameters by maximum likelihood and EM.
    1. Pirino D, Rigosa J, Ledda A and Ferretti L, Detecting Correlations among Functional Sequence Motifs, Phys. Rev. E 85, 066124 (2012).
  • Theoretical ecology
  • We presented a non-neutral version of Hubbard's neutral model of biodiversity [1].
    1. G. Bianconi, L. Ferretti and S. Franz, Non-neutral theory of biodiversity, Eur. Phys. Lett. 87 28001 (2009). arXiv.

Complex networks

  • Complex networks with preferential attachment and node features
    • Nodes in a network are sometimes homogeneous, but they often have different features: spatial position, quality or fitness, functional modules (e.g. in genetic networks) etc. We studied how the presence of spatial constraints [4] or more general features of the nodes [3] affects the properties of scale-free networks generated by preferential attachment mechanisms. We showed that the degree distribution of these models is scale-free and robust and that these models present a complex pattern of assortativity. We also proved that some models with preferential attachment on the sphere are dual to static networks on hyperbolic spaces [2]. More complex models with negative fitness, rewiring and topological constraints result in new phase transitions with condensation of paths and a complex phase space [1]. We also studied the dynamics of condensation and the turnover of condensate nodes in the fitness models [5].
      1. Ferretti L*, Mamino M*, Bianconi G, Condensation and topological phase transitions in a dynamical network model with rewiring of the links, Phys. Rev E 89 042810 (2014). arXiv.
      2. Ferretti L, Cortelezzi M, Mamino M, Duality between preferential attachment and hyperbolic networks, Eur. Phys. Lett. 105 38001 (2014). arXiv.
      3. Ferretti L*, Cortelezzi M*, Bin Y, Marmorini G and Bianconi G, Features and heterogeneities in growing network models, Phys. Rev. E 85, 066110 (2012). arXiv.
      4. Ferretti L and Cortelezzi M, Preferential attachment in growing spatial networks, Phys. Rev. E. 84,016103 (2011). arXiv.
      5. Ferretti L and Bianconi G, Dynamics of condensation in growing complex networks, Phys. Rev. E 78,056102 (2008). arXiv.
  • Dynamics on complex networks
    • We analyzed the dynamics of a phase transition on complex networks.
      1. Halu A, Ferretti L, Vezzani A and Bianconi G, Phase diagram of the Bose-Hubbard Model on Complex Networks, Eur. Phys. Lett. 99 18001 (2012). arXiv.

Theoretical and high energy physics

  • Models of flavour
    1. L. Calibbi*, L. Ferretti*, A. Romanino* and R. Ziegler*, Consequences of a unified, anarchical model of fermion masses and mixings, JHEP 0903 (2009) 031. arXiv.
    2. L. Ferretti, S.F. King and A. Romanino, Flavour from accidental symmetries, JHEP 0611 (2006) 078. arXiv.
  • Supersymmetry and supersymmetry breaking
    1. L. Calibbi*, L. Ferretti*, A. Romanino* and R. Ziegler*, Gauge coupling unification, the GUT scale, and magic fields, Phys. Lett. B 672 (2009) 152. arXiv.
    2. L. Ferretti, R-symmetry breaking, runaway directions and global symmetries in O'Raifeartaigh models, JHEP 0712 (2007) 064. arXiv.
  • Solitons in gauge theories
    1. L. Ferretti, S.B. Gudnason and K. Konishi, Non-Abelian vortices and monopoles in SO(N) theories, Nucl.Phys.B 789 (2008) 84. arXiv.
    2. M. Eto*, L. Ferretti*, K. Konishi*, G. Marmorini*, M. Nitta*, K. Ohashi*, W. Vinci*, N. Yokoi*, Nonabelian duality from vortex moduli: a dual model of color confinement, Nucl.Phys.B 780 (2007) 161. arXiv.