Life as we see it in our planet today has been shaped by many different biological processes, particularly natural selection, during billions of years. These processes leave a signature in our genomes in the form of differences between species, or between individuals of the same species. Interrogating these patterns of genome diversity we can infer what are the forces that affect living organisms, how and when they act and how do they affect such various things as biodiversity, human emotions or the differential susceptibility of different persons to certain diseases. All this knowledge empowers us to control our future but, above all, it is very fun to obtain.

Currently, the main research goals of the group focus on to elucidating how evolution, and particularly natural selection, has shaped genome and phenotype diversity in our lineage. To this end, we combine experiments, models and data analysis. Some specific research lines are as follows:


Chromosomal evolution and speciation 

We study how large chromosomal rearrangements affect many aspects of genome structure and evolution, including how they may drive the generation of new species.


Segmental duplications and copy-number variation in primates 

The genomes of humans and other primates show an enrichment in Segmental Duplications (SDs) with high sequence identity, plus they present may Copy-Number Variants (CNVs), large genome fragments of which different individuals present different copies. SDs and CNVs are fundamental for the creation of novel genes and may have been key in the evolution of our lineage. We study not only the frequencies and genome locations of these variants, but also the molecular evolution of their sequence content.


Detecting the genomic signature of natural selection 

We try to detect the signature of adaptive changes out of single-copy protein-coding regions. We focus in how natural selection may have shaped variability patterns in introns and regulatory regions of genes.


Human disease and its evolutionary implications 

We study world-wide patterns of disease susceptibility distribution to ascertain how these may have been influenced by recent human evolution. In addition, we investigate the possible origins of Multiple Sclerosis and its possible relationship with very recent natural selection events in humans.



Complex human traits that are exclusive of our lineage are the basis of our societies and have huge socio-economic impact. We deploy the latest tools of genomics for the dissection of human economic traits.


Lab website: Evolutionary Genomics Lab

Investigador principal Investigador principal

Membres del grup Membres del grup

Projectes en curs Projectes en curs

Publicacions Publicacions

Serres-Armero, Aitor; Povolotskaya, Inna S.; Quilez, Javier ; Ramírez, Óscar ; Santpere, Gabriel ; Kuderna, Lukas F.K.; Hernández-Rodríguez, Jessica; Fernández-Callejo, Marcos; Góme-Sánchez, Daniel; Freedman, Adam H.; Fan, Zhenxin; Novembre, John; Navarro, Arcadi ; Boyko, Adam; Wayne, Robert; Vilà, Carles ; Lorente-Galdós, Belén ; Marques-Bonet, Tomás 2017. Similar genomic proportions of copy number variation within gray wolves and modern dog breeds inferred from whole genome sequencing. BMC Genomics. 18(1):977

Rodríguez, J.A.; Marigorta, U.M.; Hughes, D.A.; Spataro, N.; Bosch, E.; Navarro, A. 2017. Antagonistic pleiotropy and mutation accumulation influence human senescence and disease. Nature Ecology & Evolution 1:0055

Ravinet, M.; Faria, R.; Butlin, R.K.; Galindo, J.; Bierne, N.; Rafajlovi¿, M.; Noor, M.A.F.; Mehlig, B.; Westram, A.M. 2017. Interpreting the genomic landscape of speciation: a road map for finding barriers to gene flow. Journal of Evolutionary Biology. 30(8):1450-1477

Muntané G.; Santpere G.; Verendeev A.; Seeley W.W.; Jacobs B.; Hopkins W.D.; Navarro A.; Sherwood C.C. 2017. Erratum to: Interhemispheric gene expression differences in the cerebral cortex of humans and macaque monkeys (Brain Structure and Function, (2017), 222, 7, (3241-3254), 10.1007/s00429-017-1401-7). Brain Structure and Function. 227(7):3367-3368

Martínez H.; Barrachina S.; Castillo M.; Quintana-Ortí E.S.; De Argila J.R.; Farré X.; Navarro A. 2017. Accelerating FaST-LMM for epistasis tests. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10393:548-557