Detection of the footprint of natural selection in the genome Genomics Noelia Pérez Pereira Advanced Genetics 2015-2016

Contents Introduction Natural selection Modes of selection Detecting natural selection Detecting natural selection at macroevolutionary level Gene-based methods Other rate-based methods

INTRODUCTION

Mechanisms that explain adaptation of populations to their environment Natural selection Mechanisms that explain adaptation of populations to their environment Beneficial traits (those that improve an individual’s chances to survive and reproduce) tend to become more frequent in populations over time. Vitti et al. (2013)

Mechanisms that explain adaptation of populations to their environment Natural selection Mechanisms that explain adaptation of populations to their environment Beneficial traits (those that improve an individual’s chances to survive and reproduce) tend to become more frequent in populations over time. Vitti et al. (2013)

Mechanisms that explain adaptation of populations to their environment Natural selection Mechanisms that explain adaptation of populations to their environment Beneficial traits (those that improve an individual’s chances to survive and reproduce) tend to become more frequent in populations over time. Vitti et al. (2013)

Modes of selection Modified from Quintana-Murci & Clark (2013)

Detecting natural selection Microevolution Polymorphism data Divergence data Macroevolution

Detecting selection at the MACROEVOLUTIONARY level

Methods for macroevolution Vitti et al. (2013)

Gene-based methods 1. Ka/Ks ratio Synonymous changes are assumed to be neutral non-synonymous changes synonymous changes Ka = Ks = non-synonymous sites synonymous sites Vitti et al. (2013)

Gene-based methods 1. Ka/Ks ratio λ > μ λ = μ λ < μ Synonymous changes are assumed to be neutral non-synonymous changes synonymous changes Ka = Ks = non-synonymous sites synonymous sites Ka / Ks > 1 Ka / Ks = 1 Ka / Ks < 1 Positive selection Genetic drift Purifying selection λ > μ λ = μ λ < μ

Gene-based methods > 2. McDonald-Kreitman test (MKT) < = Pn Dn Fixed difference Polymorphic site Positive selection Null hypothesis Purifying selection Pn Dn Ps Ds Pn Dn Ps Ds Pn Dn Ps Ds > < = Egea et al. (2008)

Gene-based methods 2. McDonald-Kreitman test (MKT) Single-locus MKT http://mkt.uab.cat/mkt/ Single-locus MKT Standard MKT: coding regions Advanced MKT: closely linked regions Multi-locus MKT 2x2 contingency table

Other rate-based methods 1. Hudson-Kreitman Aguadé (HKA) Levels of polymorphism and divergence should be correlated (because both are primarily functions of the mutation rate) unless selection causes one to exceed the other Change contributing to speciation was accelerated D P Value ratio Diversity within the species is reduced D: fixed interspecific differences P: within-species polymorphisms across loci Value Balancing selection between species Vitti et al. (2013)

Other rate-based methods 2. Comparative genomic data Regions that undergo accelerated change in one lineage but are conserved in related lineages are probable candidates for selection Comparative analysis of 29 mammalian genomes 5.5% of the human genome: purifying selection (∼1,2% exons) 3.6 millions of conserved elements

References Vitti, J. J., Grossman, S. R., & Sabeti, P. C. (2013). Detecting natural selection in genomic data. Annual review of genetics. 47:97-120. Quintana-Murci, L., & Clark, A. G. (2013). Population genetic tools for dissecting innate immunity in humans. Nature Reviews Immunology.13(4):280-293. Hurst LD. (2002). The Ka/Ks ratio: diagnosing the form of sequence evolution. Trends Genet. 18(9):486. Egea R, Casillas S, Barbadilla A. (2008). Standard and generalized McDonald-Kreitman test: a website to detect selection by comparing different classes of DNA sites. Nucleic Acids Res. 36:W157–62. Lindblad-Toh, K., Garber, M., Zuk, O., Lin, M. F., Parker, B. J., Washietl, S., ... & Ward, L. D. (2011). A high-resolution map of human evolutionary constraint using 29 mammals. Nature. 478(7370):476-482.

Thank you for your attention Genomics Noelia Pérez Pereira Advanced Genetics 2015-2016