Convergent evolution of immune proteins in tits, chickadees, and titmice

These small passerines use similar molecular tricks to detect pathogens.

Convergent evolution is a fascinating phenomenon. It concerns the evolution of similar traits in distantly related organisms. Think of the streamlined bodies of fish-eating penguins and auks, birds that diverged more than 60 million years ago. But such similarities are not only limited to morphological traits, evolution can also converge on the same solutions at the molecular level. For example, whales and bats use the same genes for echolocation.

Convergent evolution on the molecular level can be especially important for proteins involved in immunity. These molecular machines need to detect and fight a wide range of pathogens. It is easy to imagine that organisms exposed to the same bacterial or viral species will converge upon similar defense mechanisms. A recent study in the journal Molecular Ecology tested this idea with the bird family Paridae (tits, chickadees, and titmice).

Convergent evolution of body shape in the extinct Great Auk (left) and the Emperor Penguin (right). Credits: Great Auk © Mike Pennington | Emperor Penguin © Samuel Blanc.


Toll-like Receptors

Martin Těšický and his colleagues focused on toll-like receptors (TLRs), proteins that recognize signals derived from pathogens and trigger a signaling cascade that starts the innate immune response (first line of defense against all pathogens) and regulates the consequent adaptive immune response (learned response, specific to a particular pathogen). Toll-like receptors have specific structures (called ectodomains, ECD) that contain a ligand-binding region (LBR) which interacts with pathogenic molecules. Because these protein regions have to recognize a wide range of bacteria and viruses, you can expect strong positive selection for successful toll-like receptors.

The study focused on two receptors that are specialized to recognize different signals: TLR4 binds with lipopolysaccharides from gram-negative bacteria, while TLR5 is specific to flagellin (a protein in the bacterial flagellum). The researchers scanned the protein sequences from 29 tit species for sites under positive selection. Next, they investigated whether these positively selected sites altered the structure and binding capacity of the receptors. For instance, a different amino acid in a certain location might have different molecular properties that affect the functioning of the protein. This approach resulted in four positive selected sites in TLR4 and fourteen in TLR5.

Positively selected sites and functionally important sites of the extracellular ectodomain on the great tit TLR4 (a) and TLR5 (b). Positively selected sites are highlighted in blue or orange, and sites under convergent evolution are indicated with red arrows. From: Těšický et al. (2020) Molecular Ecology.


Comparing Trees

Now that we have a list of positively selected sites, we can investigate whether they experienced convergent evolution. This can be done by comparing the phylogeny of the Paridae with the evolutionary trajectories of the different sites. These analyses revealed that three positions in
TLR4 and six positions in TLR5 showed signals of molecular convergence. Hence, different tit species independently evolved similar protein structures to fend off invading pathogens. This finding indicates that these species might have experienced similar ecological conditions with shared bacteria or viruses. However, the researchers reported that “the observed evolutionary convergence was not explained by the selected ecological traits, suggesting that more direct evidence on the composition of the microbial communities interacting with TLRs is needed.” Another evolutionary puzzle to solve.

Convergent evolution in Toll‐like receptor 4 (TLR4) in the Paridae family. The species tree on the left does not match the evolutionary history of a particular protein location on the right. Different tit species converged on the same solution independently. From: Těšický et al. (2020) Molecular Ecology.



Těšický, M., Velová, H., Novotný, M., Kreisinger, J., Beneš, V., & Vinkler, M. (2020). Positive selection and convergent evolution shape molecular phenotypic traits of innate immunity receptors in tits (Paridae). Molecular Ecology29(16), 3056-3070.

Featured image: Black-capped Chickadee (Poecile atricapillus) © USFWS | Wikimedia Commons

The genomics of local adaptation in Blue Tits

Understanding the evolutionary history of the populations helps to pinpoint locally adapted genes.

“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change.” This quote is often attributed to Charles Darwin, but it turns this sentence does not appear in any of his writings. Instead these words can be traced back to a 1963 speech by Louisiana State University business professor Leon C. Megginson who presented his interpretation of Darwin’s work at the convention of the Southwestern Social Science Association (see here for the whole story). Whoever said it, this quote captures an important aspect of the evolutionary process, namely adaptation to local environments. We already have a good idea of how this works on an individual level, but can we also identify signatures of local adaption in the genome? A recent paper in the journal Evolutionary Applications tried to do this by studying several Blue Tit (Cyanistes caeruleus) populations in France.


Genome Scans

Before we travel to southern France (not easy in these Covid-times), we first have to understand how we can detect local adaption in the genome. A common method concerns Fst genome scans, where you calculate the population genetic statistic Fst for different genomic regions (usually referred to as windows). Fst is a measure of genetic differentiation and ranges from 0 to 1. Populations with an Fst = 0 are genetically indistinguishable, while an Fst = 1 points to completely differentiated populations. By calculating this statistic for different genomic regions, you can pinpoint sections of the genome that are significantly differentiated and might contain genes involved in adaptation to particular environments.

Finding locally adapted genes thus boils down to finding peaks in Fst across the genome. Sounds simple, but there is a catch. Other evolutionary processes can also give rise to an increase in Fst. Genetic drift, for example, can lead to genetic differentiation between populations through random fluctuations in the frequency of certain gene variants (or alleles). Recombination – the shuffling of chromosomal segments during meiosis – can also affect Fst. In regions of low recombination, several genes will be linked together (i.e. they reside on the same segment) and selection for one deleterious gene variant will thus affect the frequency of all linked genes. If different deleterious alleles unrelated to local conditions are selected against in different populations, the genomic regions in which they reside will diverge genetically, resulting in higher Fst-values. This process – background selection – can complicate the search for locally adapted genes.

A final process to keep in mind is gene flow: the exchange of genetic material between populations. Similar to mixing two paint cans, gene flow results in homogenization of the genome and can erase the genetic signatures of local adaptation. Several studies – both empirical work and simulations – have shown that a few immigrants can strongly decrease the genetic distance between two populations.

The relationship between genetic differentiation (Fst) and recombination rate in Ficedula Flycatchers. Notice the increase in Fst (top) coincides with a decrease in recombination rate. Adapted from Burri et al. (2015) Genome Research


Countless Comparisons

After this quick course in population genetics, we can finally turn to the Blue Tits. Charles Perrier and his colleagues focused on two particular pairs of populations. The first comparison concerns birds living in deciduous and evergreen forests. Previous work revealed differences in morphology and behavior between these populations. Specifically, birds breeding in deciduous forest habitats are taller, more aggressive, and lay larger and earlier broods than birds in evergreen forests. The second comparison comprised mainland versus island populations of Blue Tits. The island birds are smaller and more colorful than their mainland relatives and have been classified as a different subspecies (caeruleus on the mainland and ogliastrae on Corsica and Sardinia).

Let’s start with the deciduous vs. evergreen populations. The researchers sampled and compared four population pairs. Genome scans revealed a few Fst-outliers, but these genomic regions were unique for each comparison. This lack of repeatability is probably due to high levels of gene flow between these populations. And indeed, demographic analyses indicated ongoing gene flow between the deciduous and evergreen populations. As explained above, the mixing of a few migrations can erase genetic differences, including signatures of local adaptation. In addition, these results suggest that the traits involved in adaptation might be encoded by many alleles of small effect (i.e. polygenic architecture). These small effects are extremely difficult to pick up with genome scans and require a different approach, such as quantitative genomics.

Several comparisons of deciduous vs. evergreen forest populations revealed several Fst-outliers that were unique to each comparison. From: Perrier et al. (2020) Evolutionary Applications


Recombination Rate

The situation for mainland vs. island birds was slightly different. The demographic analyses showed that gene flow between these populations stopped about 10,000 years ago, most likely due to the isolation of Corsica after a rise in sea level. This abrupt termination in gene flow could have set the scene for local adaption to build-up in the genome. And indeed, the researchers found several outlier regions that could be involved in adaptation to the local conditions. But before we open the champagne (we are in France after all) to celebrate the discovery of several locally adapted genes, we should have a look at recombination rate. The researchers report a correlation between genetic differentiation and recombination rate: high levels of Fst coincide with low recombination rates. Hence, they have to admit that “increased differentiation in regions with low recombination is not necessarily due to positive selection, or at least not alone, and [can be] largely influenced by the effect of recombination in interaction with background selection.” More analyses are needed to disentangle these effects. The search continues.

The correlation between genetic differentiation (Fst) and recombination rate shows that regions of high Fst tend to exhibit low recombination rates. From: Perrier et al. (2020) Evolutionary Applications


An Extra Oddity

Apart from the search for locally adapted genes, the researchers uncovered an inversion on chromosome 3. Inversions are essentially regions in the DNA that has been flipped around (see this blog post for more on these peculiar segments) and they can link several genes together that consequently evolve as a single “super-gene”. If the linked genes affect the same traits, they can significantly speed up adaptation. The origin and evolutionary dynamics of this inversion – which is unique to the mainland population – remain to be investigated but the researchers can already speculate:

While the putative genomic inversion on chromosome 3 was absent from Corsica and detected in mainland individuals, its level of divergence from the noninverted sequence indicated that it was likely twice older than the beginning of divergence between blue tit populations from mainland and Corsica. This could first suggest that this polymorphism emerged in mainland blue tit populations and then did not introgress the Corsican populations, maybe due to a local disadvantage and/or genetic incompatibilities or simply due to drift coupled to little gene flow. A second hypothesis could be that this inversion was present in Corsican populations but had been purged out due to a local disadvantage.

More exciting questions to explore in these Blue Tit populations.



Perrier, C., Rougemont, Q., & Charmantier, A. (2020). Demographic history and genomics of local adaptation in blue tit populations. Evolutionary Applications, 13(6), 1145.

Feature image © Pierre Dalous | Wikimedia Commons

A common species with a complex history: The evolutionary story of the Great Tit

Genetic study uncovers five distinct groups within this widely distributed songbird.

One of most studied bird species is a taxonomic mess. The widely distributed Great Tit complex (Parus major) has been divided into 43 subspecies and ornithologists are still debating where to draw species limits between all these subspecies. In the Handbook of Birds of the World, you will find only one species, while the IOC World Bird List recognizes three distinct species: Great Tit (P. major), Japanese Tit (P. minor) and Cinereous Tit (P. cinereus). These taxonomic disputes are interesting to follow, but I prefer to focus on the evolutionary history of these birds (as I have explained in previous blog posts, such as here and here). However, an unstable taxonomy often indicates that something interesting is going on. A recent study in the Journal of Biogeography took a closer look at the Great Tit species complex and uncovered some peculiar patterns.

A Great Tit in Italy © Banellino | Wikmedia Commons


Five Groups

The researchers collected no less than 340 samples from 67 geographic populations. They sequences several genes: the mitochondrial cytochrome b (Cytb) and NADH dehydrogenase subunit 2 (ND2) genes, as well as the nuclear β-fibrinogen intron 5 (Fib5) and the transforming growth factor beta 2 intron 5 (TGFB2).

Analyses of the mitochondrial genes revealed five main groups. The Northern and Western Eurasia group contains individuals from western Europe, the Iberian Peninsula and North Africa, as well as populations from across the north part of Eurasia all the way to the Russian Far East. Taxonomically, this large group corresponds to the nominate major. The remaining four groups are scattered across Asia. The Central Asia group consists of individuals from Uzbekistan, Tajikistan and western China. The Eastern Asia group includes birds from East Asia and Southeast Asia, including China, South Korea, Japan, the Indochinese Peninsula, Malaysia and Java. The Eastern Himalaya group spans the eastern portion of the Himalayas and corresponds to the subspecies tibetanus and subtibetanus. Finally; the Southern Asia group houses individuals from Sri Lanka, the Indian Subcontinent, and parts of Afghanistan. The contrast between Western Europe (one group) and Asia (four groups) probably reflects the topographic complexity around the Himalayas with a diverse selection of habitats, providing ample opportunity for populations to diversify.

Distribution of the five main mitochondrial groups within the Great Tit species complex. From: Song et al. (2020) Journal of Biogeography


Taxonomic Grey Zone

Interestingly, analyses of the nuclear genes could not resolve the phylogenetic relationships between the populations. This suggests that the mitochondrial groups diverged recently – about 1.5 million years ago according to their calculations – and that the nuclear variation has not been divided over these groups yet (a phenomenon known as incomplete lineage sorting). Moreover, some populations might still be connected by occasional gene flow. For example, birds of the major and minor groups are known to hybridize in the Amur River area in the Russian Far East and China.

This pattern of clear mitochondrial groups and lack of nuclear population structure is common in Eurasian bird species that originated in the last few million years. In my own work, I have found similar patterns in the Bean Goose complex, where Taiga (Anser fabalis fabalis) and Tundra Bean Goose (A. f. serrirostris) started diverging about 2.5 million years ago and occasionally interbreed. These cases provide evolutionary biologists with the exciting opportunity to study speciation in action, but complicate taxonomic decisions. Because speciation is still ongoing, these populations end up in a taxonomic grey zone, often resulting in subjective decisions and a proliferation of subspecies.

A Japanese Tit in Osaka © Laitche | Wikimedia Commons


An Afterthought

While reading this paper, I realized that the authors used four very common genetic markers (the mitochondrial Cytb and ND2, and the nuclear Fib5 and TGFB2). If you browse through the ornithological literature on phylogenetics and taxonomy, you will often come across these markers. This suggests that a large part of our knowledge of avian evolutionary history is based on a tiny fraction of their genomes. Although these findings are sound and insightful, who knows how much we are missing?

My feeling that there is still much to discover with genomic data was strengthened when I read the book “Who We Are and How We Got Here” by David Reich. This book provides an overview of the recent progress in research on human evolution using genomics and ancient DNA. The findings are mind-blowing, especially the discovery of so many ghost populations that went extinct but left their genetic signatures in present-day populations (a fascinating concept that I recently covered in this BioEssays paper). It makes you wonder how many Great Tit ghost populations have wandered across Eurasia.



Song, G. et al. (2020). Great journey of Great Tits (Parus major group): Origin, diversification and historical demographics of a broadly distributed bird lineage. Journal of Biogeography.

Featured image © Francis C. Franklin | CC-BY-SA-3.0 Wikimedia Commons


This paper has been added to the Paridae page.