Past, present and future of a huge inversion in the Common Quail

Where did this inversion come from and what will happen to it?

Talking about a massive discovery. In the journal Current Biology, Ines Sanchez-Donoso and her colleagues reported on a massive inversion in the Common Quail (Coturnix coturnix). An inversion is a genomic region that has been flipped around (see this blog post for more details). Think of a piece of text “THIS IS AN INVERSION” that is reversed to “NOISREVNI NA SI SIHT“. In the case of the Common Quail, this flipped text is about 115,000,000 DNA-letters long and contains roughly 7700 putative genes. Detailed analyses of individuals with and without the inversion revealed some interesting patterns:

Birds with the inversion are larger, have darker throat coloration and rounder wings, are inferred to have poorer flight efficiency, and are geographically restricted despite the high mobility of the species.

The exact mechanisms relating the inversion to these traits remain to be unraveled, but we can already contemplate the origin and future of the inverted region. But before we travel backward and forward into time, let’s start from the present-day: How did the researchers find this massive inversion?

Present: Is it really an inversion?

Our story starts with a standard population genomic analysis of 80 Common Quails from Italy, Spain, Portugal, Morocco, and the eastern Atlantic archipelagos of Canary Islands and Madeira. Genetic differentiation between these locations appeared to be concentrated in a large region on chromosome one. A closer look at this region uncovered two main clusters (A and B). Most quails belonged to one of these clusters, but 30 birds showed a 50-50 genetic ancestry. This pattern suggests that we are dealing with two genetic variants that can be arranged as homozygotes (AA or BB) and heterozygotes (AB).

To test whether these three genotypes (AA, BB and AB) can be explained by an inversion, the researchers turned to cytogenetics. They developed two probes that bind with certain sections of chromosome one. In the AA birds, these probes were further apart (23.80 μm) than in the BB birds (11.97 μm). The different locations of the probes are expected if there is a large chromosomal inversion. And indeed, whole genome sequencing of 16 individuals confirmed the presence of a huge inversion.

A differentiated region on chromosome one (top left) turned out to be an inversion. The researchers uncovered three genotypes (AA, BB and AB) using admixture analyses (bottom left). Cytogenetic probes (J-23 and K-19) showed patterns that were in line with an inverted region on chromosome one (right). From: Ines Sanchez-Donoso et al. (2022).

Past: Ancestral variation or introgression?

Now that we are confident that it is an inversion, let’s focus on the past. Using the genetic variants within the inversion, the researchers were able to estimate when this genomic region was flipped around. Based on a range of mutation rates, this inversion probably originated between 0.9 and 3.2 million years ago. An old origin.

However, the exact event that gave rise to the inversion is still uncertain. It could have occurred in an ancestral population and the resulting inversion was maintained until the present-day. Or the inversion could have occurred in another (now extinct) species and was consequently transferred to the Common Quail by introgressive hybridization. This “ghost introgression” scenario seems plausible because “several extinct species of quail have been described for the eastern Atlantic islands.” An exciting idea to explore.

The inversion (AB in blue and BB in red) mainly occurs in the southern part of the distribution range. Whether it originated in the Common Quail itself or was introgressed from an extinct species remains to be determined. From: Ines Sanchez-Donoso et al. (2022).

Future: Speciation or stability?

What will happen to this inversion in the future? It is impossible to know for sure, but the authors offer several possibilities. The inverted and non-inverted regions might continue to accumulate genetic differences, potentially culminating in the origin of two distinct quail species. At the moment, however, heterozygotes – carrying both an inverted and a non-inverted region – do not seem to suffer from any fitness reductions. Perhaps the inversion will be maintained in the quail population for several thousands of years. Indeed, frequency-dependent selection or temporally fluctuating selection can result in a stable polymorphism.

Speciation or stability? Only time will tell.

References

Sanchez-Donoso, I., Ravagni, S., Rodríguez-Teijeiro, J. D., Christmas, M. J., Huang, Y., Maldonado-Linares, A., … & Vilà, C. (2022). Massive genome inversion drives coexistence of divergent morphs in common quails. Current Biology32(2), 462-469.

Featured image: Common Quail (Coturnix coturnix) © Christoph Moning | Wikimedia Commons

What caused the decline of the Green Peafowl?

Did past climatic changes or human actions impact this species?

In the current climate of rapid biodiversity loss, it is easy to blame human activities. Land use changes, overexploitation or other anthropogenic factors can certainly contribute to population declines, but in some cases past climatic changes have left their mark. Humans just provided the final push over the edge, hurling the population towards extinction. Disentangling the impact of past climate change and recent human-induced impact is a challenging exercise. Luckily, the methodological toolbox keeps expanding. And these tools are even more powerful when they are combined in an efficient way.

In a recent study, a team of Chinese scientists applied several approaches to understand the downfall of the Green Peafowl (Pavo muticus), an endangered bird species from Southeast Asia. They published their findings in the Proceedings of the Royal Society B.

Demographic Patterns

First, the researchers used genomic data to reconstruct the fluctuations in the population size of the Green Peafowl (you can check out this blog post for more details on the specific method they used, namely a PSMC analysis). This demographic analysis revealed an early population decline between 800,000 and 210,000 years ago, followed by a recovery during the Last Interglacial Period (about 70,000 years ago). After this period, the population started declining again. Unfortunately, it is not possible to determine whether this decline continued into the present day. The results of a PSMC analysis become unreliable in more recent times.

That is why the researchers turned to another approach and sequenced the genomes of five museum samples (from 1956 to 1976). Comparing the genetic make-up of these older specimens with present-day birds pointed to a significant reduction in genetic diversity. It thus seems that the decline in population size from the glacial periods can be extended to the present day.

The demographic PSMC analysis indicated a steady population decline until about 10,000 years ago (left). A comparison between museum specimens and modern samples revealed a significant decrease in genetic diversity, suggesting that the population decline has continued until the present day. From: Dong et al. (2021).

Niche Models

Using genomic data, we have now established that the Green Peafowl has been declining since the last ice age. But we still don’t know whether humans were involved. To answer this question, the researchers took another look at their toolbox. They reconstructed the amount of suitable habitat during the Holocene (less than 10,000 years ago) with Ecological Niche Modelling (ENM). This approach “predicted stationary general range during these periods and imply little impact of climate change.” If we can rule out these climatic changes, it had to be anthropogenic factors. Right?

Not so fast. This type of reasoning would be a black-and-white fallacy (i.e. pretending that there are only two options). To confidently blame human actions, we need more direct evidence. Here, the researchers provided two lines of evidence. First, they reported a negative correlation between human disturbance statistics, such as intensified land use for buildings and agriculture, and the population size of the Green Peafowl. In addition, they referred to written records in Chinese history that described the use of meat and feathers from this bird species.

Several indices of human impact increased over time, such as population size (blue line), area with buildings (orange), cropland (yellow) and grazing land (purple). These variables negative correlate with Green Peafowl population sizes over time. From: Dong et al. (2021).

Shades of Grey

Taken together, it seems reasonable that human factors have played a central role in the decline of the Green Peafowl. Nonetheless, I would argue that the reductions in population size during the Pleistocene might have rendered this species more vulnerable for population decline in more recent times. As mentioned in the previous paragraph, we should not fall victim to a black-and-white fallacy. The world is often comprised of different shades of grey. Safeguarding the future of the Green Peafowl will add some much-needed color.

References

Dong, F., Kuo, H. C., Chen, G. L., Wu, F., Shan, P. F., Wang, J., … & Yang, X. J. (2021). Population genomic, climatic and anthropogenic evidence suggest the role of human forces in endangerment of green peafowl (Pavo muticus). Proceedings of the Royal Society B288(1948), 20210073.

Featured image: Green Peafowl (Pavo muticus) © Scaup | Wikimedia Commons

Is the Altai Snowcock a hybrid species?

Re-analysis of genetic data questions the hybrid origin of this species.

Hybrid bird species are rare. In my review of hybrid speciation in birds, I listed only seven putative cases with variable levels of supporting evidence. Since the publication of that paper, a few other bird species have been proposed to be of hybrid origin, namely the Salvin’s Prion (Pachyptila salvini) and the Steller’s Eider (Polysticta stelleri). It is, however, difficult to discriminate between hybrid speciation and other evolutionary scenarios, such as incomplete lineage sorting and repeated bouts of introgressive hybridization. Several lines of evidence are needed to confidently conclude that a bird species has a hybrid origin (see for example, the Italian Sparrow [Passer italiae]). That is why I am always very skeptical when someone announces the discovery of a hybrid bird species. As Carl Sagan nicely put it: “extraordinary claims require extraordinary evidence.”

Hybrid Snowcocks

Recently, Li Ding and colleagues proposed that the Altai Snowcock (Tetraogallus altaicus) evolved through ancient hybridization between Tibetan Snowcock (T. tibetanus) and Himalayan Snowcock (T. himalayensis). This conclusion was largely based on a phylogenetic analysis of the mitochondrial D-loop which clustered three hybrid individuals next to the Tibetan Snowcock. Molecular dating analyses suggested that these hybrids shared a common ancestor with the Tibetan Snowcock about 1.8 million years ago. The researchers summarized their conclusions at the end of the paper:

The hybridization between T. tibetanus and T. himalayensis reproduced fertile hybrids during the Quaternary glacial period and repeatedly backcrosses with T. himalayensis during the interglacial period as a result of inheriting many characteristics from T. himalayensis, and glacial dispersal and isolation finally promoted the speciation of T. altaicus.

That is quite a bold statement from a single evolutionary tree. As mentioned above, I am always skeptical about claims of hybrid bird species. And I am not the only one: Martin Päckert was not convinced by the presented evidence and decided to re-analyze the genetic data. His results appeared in the journal Ecology and Evolution.

Phylogenetic Analyses

The hybrid species hypothesis of the Altai Snowcock relies heavily on the phylogenetic position of two mitochondrial haplotypes: H35 and H36. In the original analyses, these haplotypes formed a separate cluster next to the Tibetan Snowcock. However, Päckert could not recover this result. He ran several phylogenetic analyses with different datasets and approaches (I will not bother you with all the phylogenetic details. Interested readers can check the methods section of the paper). Interestingly, only one out of six phylogenetic analyses showed a sister species relationship between haplotypes H35/H36 and the Tibetan Snowcock. All the other analyses indicated that these haplotypes are more closely related to the Himalayan Snowcock. Based on these patterns, Päckert concluded that “Ding et al. (2020) did not discover previously unknown hybrid snowcocks, because haplotypes H35 and H36 just represent another deeply split mitochondrial lineage of the genetically diverse Himalayan Snowcock, T. himalayensis.”

Phylogenetic positions of the haplotypes H35/H36 based on different alignment strategies (with ClustalW on the left and with manual editing on the right) and different analyses (a = Bayesian inference and b = Maximum Likelihood). Most analyses pointed to H35/H36 as most closely related to the Himalayan Snowcock. From: Päckert (2021).

Hypervariable Regions

But what could have caused the faulty position of these haplotypes in the original study? A more detailed analysis of the mitochondrial D-loop identified the culprit, namely the hypervariable region. This section of the gene is – as the name suggests – extremely variable and can lead to errors in the alignment of genetic sequences. When Päckert removed the hypervariable region from the dataset, he uncovered a clear cluster containing the two haplotypes, the Himalayan Snowcock and the Altai Snowcock (confirming the phylogenetic results). There is thus no convincing evidence for a hybrid origin of the Altai Snowcock.

Päckert nicely summarized the lesson from this case study, namely that “results inferred from mitochondrial markers (in particular from those including hypervariable regions) require a thorough quality check.” Moreover, this example illustrates the importance of re-analyzing data and checking bold claims. That is how science progresses.

Phylogenetic networks with and without the hypervariable region clearly show the impact on the position of the haplotypes H35 and H36. From: Päckert (2021).

References

Ding, L., Liao, J., & Liu, N. (2020). The uplift of the Qinghai–Tibet Plateau and glacial oscillations triggered the diversification of Tetraogallus (Galliformes, Phasianidae). Ecology and Evolution, 10(3), 1722-1736.

Päckert, M. (2021). No hybrid snowcocks in the Altai—Hyper‐variable markers can be problematic for phylogenetic inference. Ecology and Evolution11(22), 16354-16364.

Featured image: Tibetan Snowcock © Donald Macauley | Wikimedia Commons

The ebb and flow of the Taiwan Strait shaped patterns of gene flow between two partridge species

Genetic analyses point to several bouts of gene flow.

The Strait of Taiwan separates the Chinese Bamboo Partridge (Bambusicola thoracicus) from the Taiwan Bamboo Partridge (B. sonorivox). It is easy to imagine that these bird species have been in contact during periods of low sea levels. And indeed, a taxonomic study from 2014 provided evidence for gene flow after their divergence, roughly 1.8 million years ago. However, these genetic analyses – using an isolation-with-migration model – only indicated that gene flow occurred, but not when. A recent paper in the journal Avian Research addressed this knowledge gap using a set of 31 nuclear loci. When did the Chinese and Taiwan Bamboo Partridge exchange genetic material?

Comparing models

The researchers compared several demographic models with different timing of gene flow. The most likely model (with a posterior probability of 0.53) pointed to early gene flow during the first 20 percent of divergence. However, a second model with late gene flow could not be rejected (posterior probability of 0.30). Together, these patterns suggest that the partridges experienced multiple bouts of gene flow. The researchers speculate that “fluctuations in the sea level of the Taiwan Strait during the early late Pleistocene may have led to changes in their distribution alternating between sympatry and allopatry.” This scenario was supported by ecological niche modelling, showing that the ranges of ancestral populations overlapped during the Last Glacial Maximum.

Three different demographic models that could explain the evolutionary history of these partridges. From: Wang et al. (2021).

Merging and diverging

The evolutionary history of the Chinese and the Taiwan Bamboo Partridge was thus shaped by multiple bouts of gene flow. As methods to detect and date gene flow events improve, we can expect to find similar scenarios in other bird species. The glacial cycles of the Pleistocene impacted the distribution of numerous species, regularly giving rise to zones of secondary contact. Many species pairs were probably subjected to cycles of merging and diverging.

These insights can help us to assess the consequences of current climate change. As species distributions change, some previously isolated populations might establish secondary contact and enter a phase of merging. These human-induced hybridization events are both a curse and a blessing. As I wrote in my review on hybridization the Anthropocene: “As humans continue to change the environment and alter species distributions, more anthropogenic hybridization events will definitely occur. This will pose challenges for the conservation of endangered species, but also provide unique opportunities for evolutionary biologists.”

Ecological niche modelling indicated overlap between both partridge species (in green) during the Last Glacial Maximum. From: Wang et al. (2021).

References

Hung, C. M., Hung, H. Y., Yeh, C. F., Fu, Y. Q., Chen, D., Lei, F., … & Li, S. H. (2014). Species delimitation in the Chinese bamboo partridge Bambusicola thoracica (Phasianidae; Aves). Zoologica Scripta43(6), 562-575.

Wang, P., Yeh, C., Chang, J., Yao, H., Fu, Y., Yao, C., … & Zhang, Z. (2021). Multilocus phylogeography and ecological niche modeling suggest speciation with gene flow between the two Bamboo Partridges. Avian Research12(1), 1-10.

Featured image: Chinese Bamboo Partridge (Bambusicola thoracicus) © Sun Jiao | Wikimedia Commons

The danger of few genetic markers: Revisiting introgression between Chukar and Red-legged Partridge

In contrast to previous studies, genomic analyses point to little gene flow between these species.

For decades, people have been releasing the non-native Chukar Partridge (Alectoris chukar) and farm-reared hybrids into the range of the native Red-legged Partridge (A. rufa). Conservationists feared that these practices would impact the genetic integrity of European Red-legged Partridge populations. And indeed, several genetic studies reported extensive introgression from the Chukar into the Red-legged Partridge (see the Galliformes page for an overview). However, the introgression patterns were based on a limited set of genetic markers, such as microsatellites. These markers only capture a fraction of the genetic variation. Genomic data will tell a more complete story that might be very different. The possible discrepancy between microsatellites and genomic data was nicely illustrated by Mallards (Anas platyrhynchos) and American Black Ducks (A. rubripes). Analyses of microsatellites suggested that hybridization between these duck species might lead to the genetic extinction of the latter species. However, genomic studies of this system revealed little gene flow between the species, indicating that hybridization is not threatening the genetic integrity of the American Black Duck. A recent study in the Proceedings of the Royal Society B investigated whether a similar scenario applies to the Chukar and Red-legged Partridge situation.

Limited Introgression

Giovanni Forcina and his colleagues sequenced the genomes of 81 birds (75 Red-legged Partridges and 6 Chukar Partridges) and obtained almost 170,000 molecular markers. Analyses of this large dataset indicated that introgression from the non-native Chukar into the native Red-legged Partridge was quite limited. Specifically, the authors reported the following patterns for several subspecies (rufa, intercedens and hispanica) of the Red-legged Partridge:

While most populations within the ranges of A. r. rufa and A. r. intercedens showed a low yet detectable level of A. chukar introgression, those of A. r. rufa from Corsica and A. r. hispanica turned out to be probably unaffected.

All in all, the genetic impact of restocking practices appears to be relatively minor. Although there are clear signs of introgression from the Chukar Partridge, the genetic integrity of the Red-legged Partridge is not in serious jeopardy. It is possible that lower fitness of hybrids prevents most of them from mating and contributing to the next generation.

A principal component analysis clearly separated the Chukar Partridges (white squares) from the Red-legged Partridges (colored dots). More detailed analyses pointed to limited introgression between these species. From: Forcina et al. (2021).

Genomic Landscape

The observation of limited introgression between these partridges is certainly good news, but why did previous genetic studies point to high levels of gene flow? In a recent review, I warned about the use of a few markers (such as microsatellites) in conservation because of the so-called genomic landscape of differentiation. When comparing the genomes of closely related species, we generally observe that genetic differences are heterogeneously distributed across the genome. Some genomic regions will be drastically different, while others are largely undifferentiated. The random selection of a few genetic markers might result in a marker set that only captures the undifferentiated section of the genome, giving the impression that the studied species are genetically similar. When the species interbreed, researchers can be quick to conclude that this similarity is due to introgressive hybridization. However, a genomic perspective might lead to very different conclusions, as we have seen with the partridges. Do not underestimate the power of genomic data.

References

Forcina, G., Tang, Q., Cros, E., Guerrini, M., Rheindt, F. E., & Barbanera, F. (2021). Genome-wide markers redeem the lost identity of a heavily managed gamebird. Proceedings of the Royal Society B288(1947), 20210285.

Featured image: Red-legged Partridge (Alectoris rufa) © Juan Lacruz | Wikimedia Commons

A chicken and egg situation: did the Red or the Green Junglefowl evolve first?

Two genomic studies tried to solve this mystery.

Although the domestic chicken is one of the most studied birds ever, the evolutionary history of its genus (Gallus) is still a mystery. The four species in this genus – Sri Lanka Junglefowl (G. lafayetti), Grey Junglefowl (G. sonneratii), Green Junglefowl (G. varius) and Red Junglefowl (G. gallus, the ancestor of the domestic chicken) – can be arranged in no less than 15 different topologies. Early genetic studies, using mitochondrial DNA or a few nuclear markers, reported evidence for six of these topologies. And a recent analysis of ultraconserved elements (UCEs) added a seventh possibility to the list. You can see an overview of these seven evolutionary arrangements in the figure below.

The discordant results among previous genetic studies can be explained by several factors. First, introgression can lead to patterns that deviate from the main evolutionary history (i.e. the species tree). Extensive gene flow from one species into another can pull distantly related species together in an evolutionary tree. Second, the random sampling of gene trees can cause issues. It is known that different genes tell different evolutionary stories. If you happen to sample a set of molecular markers that do not follow the species tree, you will draw the wrong conclusions. Third, some genetic markers might have too little phylogenetic information to confidently resolve phylogenetic relationships. These three issues can be addressed with whole genome sequences: there is plenty of data available and detailed analyses of gene trees can detect signatures of introgression and random sampling biases.

An overview of different topologies for the genus Gallus. The abbreviations corresponds to Sri Lanka Junglefowl (laf), Grey Junglefowl (son), Green Junglefowl (var) and Red Junglefowl (gal). From: Tiley et al. (2020) Avian Research.

Different Datatypes

Recently, two genomic studies appeared that tried to resolve the Gallus phylogeny. The first study – published in the journal Avian Research – focused on the effects of different datatypes. George Tiley and his colleagues performed phylogenetic analyses on different molecular markers, namely protein-coding exons, introns, UCEs and conserved non-exonic elements (CNEEs). Interestingly, all markers converged upon the same topology in which the Green Junglefowl diverged first, followed by the Red Junglefowl. The remaining two species – Sri Lanka Junglefowl and Grey Junglefowl – are sister species.

Moreover, the researchers took a closer look at the distribution of the gene trees. As expected, the most common gene tree (36%) reflected the topology described above. The remaining topologies can provide important insights into introgression dynamics. If there has been no introgression, two minor gene trees are expected to occur in roughly equal frequencies (similar to flipping a coin). Introgression, however, leads to a bias towards one minor gene tree. Additional analyses on gene tree distributions revealed several of such biases that pointed to introgression between Red Junglefowl and Green Junglefowl, and between Red Junglefowl and Grey Junglefowl.

Phylogenetic analyses of different genetic markers all converged on the same topology. From: Tiley et al. (2020) Avian Research.

NJ vs. ML

To answer the question in the title: the Green Junglefowl evolved first. Well, not so fast. Because a second genomic study in the journal Molecular Phylogenetics and Evolution suggests otherwise. Phylogenetic analyses of more than 20,000 gene sequences resulted in two main topologies depending on the applied method. A Neighbor-Joining (NJ) approach indicated that the Green Junglefowl evolved first, whereas a Maximum Likelihood (ML) approach pointed to Red Junglefowl as the first species to diverge. Introgression analyses on the NJ-tree – using the popular D-statistic – revealed extensive gene flow from the Green Junglefowl into the ancestor of the Sri Lanka Junglefowl and Grey Junglefowl: no less than 27.6%. The researchers consider this amount of introgression unlikely, which invalidates the NJ-topology. Hence, the ML-tree with more realistic levels of introgression – and where Red Junglefowl evolved first – represents a more likely scenario.

Introgression patterns across the two main topologies, based on (a) Maximum Likelihood and (b) Neighbour-Joining. The extremely high level of introgression (27.6%) in the NJ-tree makes this an unlikely scenario. From: Mariadassou et al. (2021) Molecular Phylogenetics and Evolution.

Species Tree?

So, now what? The two genomic studies report contrasting results and we still don’t know which species evolved first. Personally, I find the first study more convincing because it took different datatypes into account and provided a detailed overview of the gene trees. The second study, on the other hand, analyzed all autosomal gene trees in one go and did not report the distribution of these gene trees (I am very curious to see it). My bet would thus be on the Green-Junglefowl-first-scenario.

However, until now we assumed that the evolutionary history of the genus Gallus can be captured in a bifurcating tree. This is not necessarily the case. The high levels of ancient and recent introgression between these species might be better depicted in a phylogenetic network (see for example here). Trying to find the “true” species tree could be seen as a wild goose (or chicken) chase. And the question which junglefowl species evolved first becomes a bit nonsensical.

References

Mariadassou, M., Suez, M., Sathyakumar, S., Vignal, A., Arca, M., Nicolas, P., … & Tixier-Boichard, M. (2021). Unraveling the history of the genus Gallus through whole genome sequencing. Molecular Phylogenetics and Evolution158, 107044.

Tiley, G. P., Pandey, A., Kimball, R. T., Braun, E. L., & Burleigh, J. G. (2020). Whole genome phylogeny of Gallus: introgression and data-type effects. Avian Research11(1), 1-15.

Featured image: Green Junglefowl (Gallus varius) © Panji Gusti Akbar | Wikimedia Commons

Across Asia and beyond: The evolutionary story of the Common Pheasant

Genetic study reconstructs the Asian diversification of the Common Pheasant.

When I visit my family in Belgium, we often go for walks with our dog Mira (a Hungarian vizsla). While strolling through the local nature reserves, we sometimes disturb a Common Pheasant (Phasianus colchicus) hiding in the tall grass. Females mostly fly off with a loud alarm call, whereas males tend to run away in a seemingly random direction. These colorful birds – the males anyway – are not native to this part of Europe, but were introduced for hunting purposes. Common Pheasants originated in Asia where they display an amazing diversity of male plumage, resulting in a proliferation of more than 30 subspecies.

A recent study in the Journal of Biogeography focused on the native range of the Common Pheasant and reconstructed its evolutionary history based on a handful of genetic markers. The researchers found that this species diversified into eight distinct lineages during the Late Pleistocene. Let’s explore the Asian expansion of the Common Pheasant.

Spreading across Asia

Simin Liu and colleages sampled more than 200 individuals across the range of the Common Pheasant, which extends from the Black Sea to Korea. Analyses of seven nuclear and two mitochondrial genes revealed that the diversification within this species started at the end of the Pleistocene, between 700,000 and 200,000 years ago. Our evolutionary story starts at the eastern edge of the Qinghai-Tibetan Plateau from where several lineages spread in different directions.

One population expanded to the Chinese mountain ranges in the south-east, giving rise to the elegans-lineage. Because the climate remained relatively stable in this region, this lineage shows a stable population size of time and did not diversify into more sub-lineages. A second expansion to the east brought pheasants into a more unstable area where periods of drought promoted diversification into multiple lineages. Here, we currently find the torquatus and strauchi–vlangallii lineages that were occasionally connected by gene flow. One population traveled further east and became isolated on the island of Taiwan (the formosanus-lineage). Finally, a third movement to the west resulted in the evolution of several Central Asian lineages: tarimensis,, mongolicus, principalis–chrysomelas and colchicus. The exact evolutionary relationships between these lineages remain to be disentangled.

The genetic analyses pointed to eight distinct lineages (see phylogeny on top) that spread across Asia from the Qinghai-Tibetan Plateau (map below). From: Liu et al. (2020) Journal of Biogeography.

Taxonomic Decisions

This study nicely shows how different environmental conditions affect the evolutionary trajectory of a population. The relatively stable climate of the Chinese mountains resulted in a stable population of Common Pheasants, making further diversification of this lineage (elegans) unlikely. Other populations ended up in regions with more pronounced climatic cycles that led to diversification into several separate lineages. Ultimately, the researchers could discriminate between eight distinct lineages.

Taxonomic-minded readers might be wondering if all these lineages should be elevated to species rank. At the moment, the researchers argue that the diversity within the Common Pheasant can be captured in three species: the Yunnan Pheasant (P. elegans), the Chinese Pheasant (P. vlangallii which includes the torquatus, strauchi–vlangallii and formosanus lineages) and the Turkestan Pheasant (P. colchicus which includes the tarimensis, principalis–chrysomelas, mongolicus and colchicus lineages). However, more research is needed to justify this classification.

References

Liu et al. (2020) Regional drivers of diversification in the late Quaternary in a widely distributed generalist species, the common pheasant Phasianus colchicus. Journal of Biogeography47(12), 2714-2727.

Featured image: Common Pheasant (Phasianus colchicus) © David Croad | Wikimedia Commons

You only need one genome to unravel the demographic history of the Chinese Grouse

Genomic analyses reveal population fluctuations during the Pleistocene.

A few weeks ago, scientists announced that they almost completed a sequence of the human genome. This might come as a surprise: did we not sequence the human genome in 2003 when the results from the Human Genome Project were published? That genome sequence was actually incomplete, about 15% was missing (especially stretches of repetitive DNA are difficult to assemble). Similarly, many avian genome assemblies contain significant gaps (see this blog post for more details). However, scientists can still extract a lot of information from incomplete genome assemblies. For instance, you can reconstruct the demographic history of a species from one genome using a pairwise sequentially Markovian coalescent (PSMC) analysis. This technique – developed by Heng Li and Richard Durbin – is nicely explained by David Reich in his book Who We Are and How We Got Here:

A 2011 paper by Heng Li and Richard Durbin showed that the idea that a single person’s genome contains information about a multitude of ancestors was not just a theoretical possibility, but a reality. To decipher the deep history of a population from a single person’s DNA, Li and Durbin leveraged the fact that any single person actually carries not one but two genomes: one from his or her father and one from his or her mother. Thus it is possible to count the number of mutations separating the genome a person receives from his or her mother and the genome the person receives from his or her father to determine when they shared a common ancestor at each location. By examining the range of dates when these ancestors lived—plotting the ages of one hundred thousand Adams and Eves—Li and Durbin established the size of the ancestral population at different times. In a small population, there is a substantial chance that two randomly chosen genome sequences derive from the same parent genome sequence, because the individuals who carry them share a parent. However, in a large population the chance is far lower. Thus, the times in the past when the population size was low can be identified based on the periods in the past when a disproportionate fraction of lineages have evidence of sharing common ancestors.

Population Fluctuations

A recent study in the journal BMC Genomics applied this PSMC analysis to the genome of a Chinese Grouse (Tetrastes sewerzowi). This forest-dwelling species can be found in the mountains east of the Qinghai-Tibet Plateau. It is currently considered “Near Threatened” because of population declines due to ongoing deforestation and fragmentation of its habitat.

The genomic analyses revealed that the population size of the Chinese Grouse has fluctuated over time. Populations decreased during early to middle Pleistocene but showed an expansion during late Pleistocene (between 30,000 and 40,000 years ago), followed by a sharp decline during the last glacial maximum (about 20,000 years ago). Similar patterns have been found in other bird species, highlighting the influence of the climatic cycles during the Pleistocene (see for example this study by Krystyna Nadachowska-Brzyska and her colleagues).

The PSMC analysis showed population fluctuations of the Chinese Grouse during the Pleistocene. From: Song et al. (2020) BMC Biology.

Coniferous Forests

Next, the researchers focused on the underlying mechanisms of these population fluctuations. Why did the number of Chinese Grouse wax and wane during the Pleistocene? To answer this question, the researchers turned to Ecological Niche Modelling and reconstructed the distribution of the Chinese Grouse throughout the Pleistocene. This exercise showed that the population expansion during the late Pleistocene (30,000–40,000 years ago, also known as the Greatest Lake Period) can be explained by the warmer weather which allowed conifer forests, the primary habitat for Chinese Grouse, to reach their greatest extent. Later on, during colder periods, the coniferous habitat shrunk and the Chinese Grouse populations moved westwards into higher altitudes.

These findings indicate that the distribution of the Chinese Grouse is strongly dependent on the coniferous forest cover. It is thus essential to protect these fragmented forests and safeguard the future of this beautiful bird.

Ecological Niche Modelling showed how the suitable habitat for Chinese Grouse increased during the late Pleistocene (figure a), followed by extensive loss of habitat later on (figure b). The current distribution is depicted in figure c. From: Song et al. (2020) BMC Genomics.

References

Song, K., Gao, B., Halvarsson, P., Fang, Y., Jiang, Y. X., Sun, Y. H., & Höglund, J. (2020). Genomic analysis of demographic history and ecological niche modeling in the endangered Chinese Grouse Tetrastes sewerzowiBMC genomics21(1), 1-9.

Featured image: A drawing of Chinese Grouse (Tetrastes sewerzowi) © Ornithological Miscellany. Volume 2 | Wikimedia Commons

Bad news for the Brown Eared Pheasant?

Genomic study finds low genetic diversity and high levels of inbreeding in this vulnerable species.

Small populations are often at risk. They can get sucked in a negative feedback loop of genetic and demographic decline that culminates in their extinction (the so-called extinction vortex, which I covered in this blog post). In general, small populations are more vulnerable to genetic drift and inbreeding, leading to a loss of genetic diversity. This lower level of genetic diversity might prevent small populations from adapting to changing environments. However, it is not all misery and mayhem for small populations. One potential benefit of a small population size is genetic purging, the process in which deleterious variants appear more often due to inbreeding and get purged from the population because individuals carrying these variants fail to survive or reproduce. The result is a genetically healthier population, despite low levels of genetic diversity.

A recent study in the journal Molecular Biology and Evolution examined the situation of the brown eared pheasant (Crossoptilon mantchuricum), a vulnerable bird species that is declining across its range in China due to human activities, such as deforestation and hunting. Is this species heading for extinction or does it reap the benefits of genetic purging?

Genetic Purging?

Based on the genomes of 40 individuals, the researchers identified three distinct populations corresponding to locations in Shaanxi (Western), Shanxi (Central), and Hebei & Beijing (Eastern). The genetic diversity across these three populations was extremely low. In fact, it was the lowest genome-wide estimate for any bird species to date. But, as explained above, this low level of genetic diversity might result in genetic purging when deleterious alleles are filtered out by purifying selection.

The action of genetic purging can be tested with the population genetic statistic Tajima’s D. I have explained the rationale behind the statistic in another blog post, but for this story you only need to understand the main interpretation. In general, a negative Tajima’s D points to a selective sweep (and thus genetic purging), while a positive Tajima’s D suggests balancing selection. In the three brown eared pheasant populations, Tajima’s D was highly positive. There is thus no evidence for genetic purging. And that is bad news…

The brown eared pheasant shows very low levels of genetic diversity (left figure). The positive values of Tajima’s D suggest that there is little purifying selection across the genome of this species (right figure). Blue refers to the blue eared pheasant, Brown-W, Brown-C and Brown-E refer to three populations of the brown eared pheasant. Adapted from Wang et al. (2021) Molecular Biology and Evolution.

Genetic Load

Low genetic diversity is often the outcome of inbreeding. When related individuals mate, their offspring will mostly receive the same genetic variants from both parents. This results in large genomic regions with little genetic variation, also known as runs of homozygosity (ROHs). The brown eared pheasant did indeed show more ROHs compared to its sister species, the blue eared pheasant (C. auritum), that is of little conservation concern.

A closer look at these genomic regions revealed that some brown eared pheasant populations have accumulated missense and loss-of-function mutations. Missense mutations occur when a change in the DNA results in the wrong amino acid being incorporated into a protein. And loss-of-function mutations lead to functional problems in the activity of a protein. Clearly, the brown eared pheasant is suffering from inbreeding depression. Moreover, because natural selection seems unable to eliminate deleterious mutations, this species is accumulating a high genetic load. Unless conservation actions are implemented – such as a genetic rescue program – the brown eared pheasant might be heading for extinction.

The brown eared pheasant populations show more runs of homozygosity (ROHs) compared to the blue eared pheasant, suggesting high levels of inbreeding. From: Wang et al. (2021) Molecular Biology and Evolution.

References

Wang et al. (2021). Genomic Consequences of Long-Term Population Decline in Brown Eared Pheasant. Molecular Biology and Evolution38(1), 263-273.

Featured image: Brown eared pheasant (Crossoptilon mantchuricum) © Josh More | Flickr