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The genetics of Mexico recapitulates Native American substructure and affects biomedical traits

Sun, 04 Jan 2015 00:16:01 +0000

Mexico, hosted many cultures such as the Olmec, the Toltec, the Maya and the Aztec, conquered and colonized by the Spanish Empire in 1521. The country harbors a large source of pre-Columbian diversity and their genetic contributions to today’s population.

In a recent paper, Moreno-Estrada et al. 2014 performed a detailed genetic study of Mexican genetic diversity. The results showed the genetic stratification among indigenous populations and an association between subcontinental ancestry and lung function.

In the first part of the study, to estimate the genetic diversity, researchers examined autosomal single-nucleotide polymorphisms for more than 500 Native Mexican individuals from all around Mexico. Statistical analysis of genomic data showed that some populations within Mexico are more differentiated than European and East Asian populations. This extreme differentiation thought to be a result of isolation followed by a bottleneck and small effective population sizes.

The data was analyzed in various ways (ROH and IBD analysis, PCA etc.) and revealed the population substructure of Mexico. In all of the analysis, the results confirmed that Seri (northernmost) and Lacandon (southernmost) have the highest level of differentiation. Also, the differentiation between Seri and Lacandon was greater than average differentiation between human populations. The relationships between other populations were accordance with geography, migration and language history. When African and European genetic data were included in the analysis of native Mexicans, it had been shown that most individuals have the genetic composition of Native and European ancestry. Further analysis indicated the ancient Native American substructure was recapitulated even after postcolonial admixture.

In the second part of the study, Moreno-Estrada et al. 2014 investigated the potential biomedical applications of genetic substructure information. Previous studies indicated the relationship between forced expiratory volume in 1 second (FEV₁) could be an indicative of pulmonary disease and another study suggested that the proportion of European ancestry was associated with FEV₁ in Mexicans. Researchers measured the lung function in Mexican and Mexican-American children with asthma and correlated these findings with native ancestry. Results showed 7.3% change in FEV₁ moving from Sonora to Yucatan and researchers proposed that native ancestry could alone have effects on lung function in admixed individuals within Mexico.

Personal Comments

This paper provides novel insights to Mexican genetic diversity and proposes the biomedical applications of genetic data. The sampling locations cover most of the country and the analysis of the data in various methods gives confidence to reader. The paper is easy to follow and the figures are quite helpful.

However, I think there is a critical point that needs to be discussed from a medical point of view. As far as I know, asthma is a complex disease and thought to be caused by both genetic and environmental factors. In this study, I could not find any information about the developmental and medical history of patients. I think this is a critical point because of heterogeneous geography of the county. Where were they raised – in volcano towns, Pacific shores, Sumidero Canyon, Laguna Salada (-10m) or piedmont plains of Pico de Orizaba (5636m)? Did their mothers smoke during pregnancy? Were they born in Mexico City – the city named as “the most polluted city on the planet” by United Nations in 1992? I hope the researchers have already checked for this type information and found them unnecessary to include.

Nevertheless, this is an interesting paper and shows the genetic history of Mexico – before and after 16^th century. I recommend reading this paper and discussing with a medical doctor

Moreno-Estrada, A., Gignoux, C., Fernandez-Lopez, J., Zakharia, F., Sikora, M., Contreras, A., Acuna-Alonzo, V., Sandoval, K., Eng, C., Romero-Hidalgo, S., Ortiz-Tello, P., Robles, V., Kenny, E., Nuno-Arana, I., Barquera-Lozano, R., Macin-Perez, G., Granados-Arriola, J., Huntsman, S., Galanter, J., Via, M., Ford, J., Chapela, R., Rodriguez-Cintron, W., Rodriguez-Santana, J., Romieu, I., Sienra-Monge, J., Navarro, B., London, S., Ruiz-Linares, A., Garcia-Herrera, R., Estrada, K., Hidalgo-Miranda, A., Jimenez-Sanchez, G., Carnevale, A., Soberon, X., Canizales-Quinteros, S., Rangel-Villalobos, H., Silva-Zolezzi, I., Burchard, E., & Bustamante, C. (2014). The genetics of Mexico recapitulates Native American substructure and affects biomedical traits Science, 344 (6189), 1280-1285 DOI: 10.1126/science.1251688

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Electrogenic fish – what’s in charge of the charge?

Mon, 15 Dec 2014 09:11:39 +0000

Electric organs – organs that are capable of creating and discharging electricity – have evolved independently in at least six different lineages of fish (Torpediniformes, Rajiformes, Mormyroidea, Euteleostei, Siluriformes, Gymnotiformes) and play an important role in communication, navigation, defense and predation.

To investigate whether the convergent evolution of these organs has a common genetic basis, Jason Gallant and his coworkers studied the transcriptome of five species of electrogenic fish in three different lineages: Electrophorus electricus, Sternopygus macrurus, Eigenmannia virescens (Gymnotiforme), Malapterurus electricus (Siluriforme) and Brienomyrus brachyistius (Mormyroidea).

Electric organs are comprised of arrays of electrocytes – asymmetric cells that are enriched in cation-specific ion channels on one and sodium pumps on the opposing side. The resulting ion flux slowly charges the electrocyte membrane and upon activation by a neuronal stimulus, the voltage is discharged, generating an electrical pulse from the fish.

Although the morphology of electric organs and electrocytes varies substantially amongst these species, they are all muscle-derived tissue and originate developmentally from muscle progenitor cells.

Since this evolution of muscular to electrogenic tissue has occurred several times independently, the authors investigated, whether the underlying genetic mechanisms are shared.

To address this question, Gallant et al. first sequenced and assembled the genome of the electric eel, E. electricus. The authors further performed transcriptome analysis on multiple tissues of E. electricus as well as on pairs of skeletal muscle and electric organ tissue of two species within the same lineage (S. macrurus and E. virescens) and two species of distinct lineages (B. brachyistius, M. electricus).

Main findings

Across the species they observed common patterns of differential gene expression between electric organs versus skeletal muscles, which they attributed to the following five key mechanisms for the evolution of electrogenic tissue:

Alteration of the expression of myogenic transcription factors
Increased excitability by upregulation of transporters and ion channels
Enhanced isolation and direction of electrical currents by the upregulation of proteins in the connective tissue
Decrease in contractility by down-regulation of sarcomere associated genes
Increase of cell size by up-regulation of factors in the Insulin-like growth factor signaling pathway

Gallant et al. propose a convincing set of changes in gene expression to explain the functional differences between electric organ and muscle tissue. The fact that these mechanisms seem to be conserved in five species of electrogenic fish is an intriguing, yet not entirely surprising observation: presumably there are strong constraints on keeping muscle function intact while opening the potential for specialization to electric tissue – it would be interesting to inquire if – and to what extent – these shared expression differences are reflected on the genetic level.

Given the ambitious goal of uncovering the basis of electric organ evolution, I think the sampling of only one individual per species is problematic, despite the authors´ main interest in inter-species similarities. For an evolutionary approach the importance of intra-species variations should not be neglected and certainly requires a larger number of individuals. Including specimens from the other electrogenic lineages (e.g. Torpediniformes, Rajiformes) or (genetic) comparisons between electrogenic and non-electrogenic descendants within a lineage would have further strengthened the evolutionary aspect.

Lastly one could suspect that phylogenetically “older” electric organs have undergone a more advanced tissue specialization, resulting in a reduced “muscle profile” but the authors do neither raise this question, nor provide any information on this aspect.

Nevertheless I can highly recommend reading and discussing the paper – the ideas and methodology are presented in a clear language, the figures are appealing and – apart from the histological pictures – informative and well explained.

Although the results on what is in charge of the evolution of electric organs holds no shocking surprise yet, the research is still electrifying.

Gallant, J., Traeger, L., Volkening, J., Moffett, H., Chen, P., Novina, C., Phillips, G., Anand, R., Wells, G., Pinch, M., Guth, R., Unguez, G., Albert, J., Zakon, H., Samanta, M., & Sussman, M. (2014). Genomic basis for the convergent evolution of electric organs Science, 344 (6191), 1522-1525 DOI: 10.1126/science.1254432

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Genomic basis of the convergent evolution of electric organs

Sun, 30 Nov 2014 23:46:30 +0000

Electric organs in fish have evolved independently in six lineages and are an interesting example of convergent evolution. However, the genetic basis underlying the convergence of this trait is poorly understood. By sequencing and assembling the transcriptomes from the electric organ (EO) and skeletal muscle of three of those lineages of electric fish, Galant et al. showed the presence of shared patters of gene expression in pathways related to differentiation from muscle cell, increased cell size, reduced contractility and increased excitability.

Paper summary

Electric organs allow fish to communicate, navigate and cope with predators and preys. They have evolved rather recently: less than 100 million years ago in the Cenozoic (as shown in Figure 1A). Importantly they have evolved independently in at least six taxonomically diverse lineages, constituting a clear example of convergent evolution.

Electrocytes are thought to be developmentally derived from myogenic precursors and are morphologically very different among fish lineages. This is illustrated in Figure 1B, where the authors show micrographs of electrocytes in two lineages of electric fish: gymnotiformes, such as Electrophorus electricus and Sternopygus macrurus, present electrocytes devoid of sarcomere, the contractile unit of muscle cells. In contrast, in mormiroids like Paramormyrops kingsleyae a disorganized and non-functional sarcomere can be found in electrocytes.

In order to understand the genetic programme that led to the common function of electrocytes in such morphologically different cells among lineages, Gallant et al. assembled the genome of the gymnotiform E. electricus and use RNA-seq reads from eight tissues for gene prediction, giving rise to 29,363 gene models. Genes co-expressed between tissues in E. electricus were subjected to k-means clustering analysis to reveal groups of genes that are either up-regulated (211 genes) or down-regulated (186 genes) in the EO as compared to skeletal muscle (Figure S1).

They sequenced and assembled the transcriptomes from EO and skeletal muscle of two other gymnotiforms (S. macrurus and E. virescens) and two species with an independently-evolved electric organ: M. electricus and the mormyroid B. brachyistius. In this four species they looked for the orthologs of those transcripts found up/donw-regulated in the cluster analysis of E. electricus to detect shared patterns of gene expression. Finally they focused on genes that might explain the convergent features of electrocytes versus muscle cells by selecting pathways related to down-regulation of muscle differentiation, increased excitability and insulation, decreased contractility and larger cell size.

A summary of the results is presented in figure 2A. Consistent with their idea that electrocytes derived from muscle cells, they found that transcription factors typically down-regulated in mature muscle cells are highly expressed in electrocytes (e.g. six2a, hey1), together with the down-regulation of transcription factors specifically involved in muscle cell differentiation (e.g. six4b, myogenin), except in S. macrurus.

They also showed that the increased excitability of electrocytes compared to muscle cells could be explained by the enhanced expression of certain genes involved in ion pumps and transporters (e.g. atp1a2a, scn4aa), with the notable exception of atp1a3a in E.electricus.

Similarly, they found a general down-regulation of genes related to the assembly of sarcomeres (e.g. smyd1a. cacna1sa), again with milder results in the EO of S. macrurus., that would account for the lack of functional sarcomeres and thus reduced contractility of these cells as opposed to muscle cells.

Finally, they found a general enhancement of the insulin-like growth factor (IGF) signalling pathway (e.g. igf2b, net-37, further illustrated in figure 2B), which would contribute to the larger cell size of electrocytes. An overview of the combined contribution of the studied pathways to the characteristic phenotype of electrocytes is proposed in figure 2C.

Personal comment

In the present study, Gallant et al. use transcriptome sequencing to elucidate the genetic basis of the convergent function of independently-evolved and morphologically diverse EO. However, in spite of this transcription-wide approach, the authors focused on a very selected and relatively small number of genes and transcription factors, potentially ignoring other genetic contributions that could be provided with the rich and large dataset generated.

Based on the notion that electrocytes are derived from muscle cells, they first selected genes that are up/down-regulated in the EO compared to skeletal muscle solely in E. electricus, disregarding the implications of genes that do not show differential expression, or genes up/down-regulated in EO of the other species but not in E. electricus.

Secondly, they selected certain pathways that they considered a priori to be likely responsible for the distinct phenotype of electrocytes, and for each of those pathway they presented in the main text results for only 5 genes that strongly supports their hypothesis. However in the supplementary figures S2-4 they extended their findings with other genes within the selected pathways that show more variable and unconserved patterns among species and that are nor further discussed. One particular case, atp1a3a shown in figure 2A, do not follow the pattern of enhanced expression in EO of E. electricus as they claim in the text for ion transporters responsible for increased excitability, but the unexpected result is not justified.

The presence of vestiges of disarrayed and non-functional sarcomeres in the electrocytes of the mormiroid S. macrurus that nevertheless might be energetically expensive to keep could suggest a more recent evolution of electric organs in this species. Consistent with this idea would be the milder up/down-regulation reported for some of the studied genes in S. macrurus compared to the other electric fish.

However it is important to notice the lack of biological and/or technical replicates in the study, a caveat that weakens its conclusions and questions its presence in a high-impact journal like Science. Given that the used animals were not wild but commercially obtained, increasing the sample size to a minimum of 3 animals per lineage studied could be feasible and would eliminate potential undesired technical or biological variability and provide more robust and conclusive results.

Reference

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The Amborella Genome and the Evolution of Flowering Plants

Wed, 14 May 2014 09:25:21 +0000

Amborella trichopoda, an endemic species to New Caledonia, is the most early-diverging taxa of flowering plants (angiosperms, Figure 1). As such, the sequencing of its genome was of considerable interest for the investigation of the emergence and evolution of this highly diverse lineage presenting at least 350’00 species.
In this work, the Amborella genome project (http://www.amborella.org/) reports the draft genome sequence for A. trichopoda. Notably, it was used as reference for the reconstruction of genomic features and architecture of the most recent common ancestor of living angiosperms, the investigation of gene families specific to flowering plants, and the investigation of the Amborella population structure.

Figure 1: Overview of the land plant phylogeny. Major hypothetical polyploidy events are indicated with stars. Additional ones are indicated with ellipses. Events supported by synteny analysis are filled, other events are only supported by phylogenetic analysis of paralogous gene pairs.

Genome structure

The identification of frequent duplicated collinear genes (Figure 2a) within A. trichopoda genome provides evidence of an a ancient whole genome duplication (WGD). WGD is known to be a pervasive feature in the evolution of plants, with modern plants frequently presenting traces of multiple past duplication events. Thus, a comparison with Vitis vinifera (grape) showed that the genome of A. trichopoda is almost entirely covered by three syntenic grape regions (Figure 2b and 2c). This 1:3 relationship between those two genomes indicates that the WGD detected in A. trichopoda occurred in the common ancestor of the two species (an event referred as Epsilon, Figure 1), and confirms that the divergence of A. trichopoda at least 160 Ma ago predates the observed genome triplication of Vitis vinifera (referred as Gamma, Figure 1). In addition, the A. trichopoda genome shows no evidence of more recent duplication event.
A phylogenomic approach was then used to confirm results based on synteny analysis. First, with the reconstruction of the phylogeny of 11,519 gene families supporting the fact that duplicated genes specific to A. trichopoda are unfrequent. Inference of the duplication time significantly supported two divergence times of respectively 244 and 341 mya, corresponding to the previously identified Zeta and Epsilon WGD (Figure1). The fact that the Zeta duplication was not supported by syntenic analysis is probably due to extensive gene loss and rearrangements that occurred since this ancient event. A second phylogenetic analysis of 155 syntenic genes pairs from six manually curated duplicated blocks supports as well that Epsilon WGD predates the divergence of A. trichopoda.

Figure 2: Synteny analysis: a) Syntenic region of scaffolds 24 and 48 of the A. trichopoda draft genome. b) Top: Synteny pattern between Grape and Amborella: each A. trichopoda region match to up to three Grape regions, as a result of the Gamma hexaploidization, and A. trichopoda present signal of the Zeta WGD, with numerous blocks of intragenomic synteny. Bottom: Detailed view of A. trichopoda scaffold 9. Coloured blocks present genes with orientation on the same strand (blue) or reverse strand (green). c) Bottom: Alignments of the seven reconstructed ancestral eudicot chromosomes (blue) and the A. trichopoda scaffolds (green). Top: Alignment of the reconstructed ancestral eudicot chromosomes with the three copies present in Peach, Cacao and Grape genomes.

The ancestral gene order of the eudicot ancestor was reconstructed based on three eudicot genomes presenting structurally similar genomes and clear patterns of paralogy among gene copies: grape (V. vinifera), peach (Prunus persica), and cacao (Theobroma cacao). A. trichopoda was used as an outgroup. Seven hypothetical ancestral chromosomes were reconstructed. This reconstruction will help to understand the evolution of eudicot lineages after the Gamma hexaploidy event. Figure 2c presents the alignment of one ancestral chromosome and triplicates blocks of genes in the three rosid genomes.

Ancestral gene family content, origin and history of angiosperm genes

To investigate the ancestral gene content and evolution of genes families in the different lineages of the land plant phylogeny, protein coding genes from 22 sequenced land-plants were clustered into 53,136 orthogroups. Subsequent clustering merged those orthogroups into 6054 super-orthogroups. Changes in genes families are more important for terminal branches, and the branch leading to all angiosperms. Additional analysis including spruce genome, gymnosperm and basal angiosperm transcript assemblies led to the identification of 1179 orthogroups which seems to be specific to angiosperms.
We discussed the fact that this clustering method is based on BLASTp analyses. Amino acid sequences are not necessarily well conserved between distantly related proteins, and cutoffs used for clustering influence the number of inferred unique gene families. Most genes lineages (70%) with function linked to flowering were present in the most recent common ancestor of all seed plants, highlighting the fact that novelty is generally not linked with the emergence of drastically new gene families.
They further detailed gene family expansions linked with flowering, such as the MADS-box transcription factors, seed storage globulins and cell wall and lignin genes.

Transposable elements

One striking feature of the A. trichopoda genome is that average age of identifiable transposable elements (TEs) in A. trichopoda is considerably older than that of other angiosperm genomes. Terminal repeats of LTR retrotransposons presented extensive degree of divergence. Endogenous pararetroviruses (EPRVs) and TEs still account for 57.2% of the nonambiguous nucleotides in the A. trichopoda genome (668 Mb), but only few TEs families presented signal of recent activity, with an estimated insertion date of more than 10Ma for most of the TEs. The lack of recent transposon activity in the A. trichopoda genome may be due to very effective silencing or the loss of active transposases.

Population genomics and conservation

They finally investigated population history and structure of Amborella. Twelve genomes of 12 individuals sampled from nearly all known populations from New Caledionia were resequenced. The Pairwise Sequentially Markovian Coalescent (PSMC) method, which uses Single Nucleotide Polymorphism (SNP) data to infer past changes in effective population size, was used to investigate population history of the 12 Amborella populations (Figure 3). The coalescent time of the 12 genomes was estimated to be 9.0-2Ma. They discussed evidences suggesting population bottlenecks, sub-lineages admixture and reduction in effective population size in recent past. Nevertheless, given the boostrap clouds visible on Figure 2, those results are not strongly supported by the data. The number of identified SNP varied importantly depending the parameters used for the SNP calling: from 1,903,437 SNP with stringent parameters to 5,131,595 SNP with less stringent parameters. As the median read depth was quite low for some samples (6X for several samples), the less stringent analysis was retained to perform the subsequent PSMC and population structure analysis, casting doubt on the value of those results.

Figure 3: PSCM results for the 12 Amborella populations (one color/population, right panel), and the boostrap clouds in green. The vertical bar at about 325,000 years indicates the estimated timing of species wide decline of effective population size.

In conclusion, the analysis of the draft genome sequence of this basal Angiosperm gave first hints of the genome architecture and gene content of ancestral flowering plants, and promises to be a valuable tool for the investigation of the evolution of flowering plants.

., Albert, V., Barbazuk, W., dePamphilis, C., Der, J., Leebens-Mack, J., Ma, H., Palmer, J., Rounsley, S., Sankoff, D., Schuster, S., Soltis, D., Soltis, P., Wessler, S., Wing, R., Albert, V., Ammiraju, J., Barbazuk, W., Chamala, S., Chanderbali, A., dePamphilis, C., Der, J., Determann, R., Leebens-Mack, J., Ma, H., Ralph, P., Rounsley, S., Schuster, S., Soltis, D., Soltis, P., Talag, J., Tomsho, L., Walts, B., Wanke, S., Wing, R., Albert, V., Barbazuk, W., Chamala, S., Chanderbali, A., Chang, T., Determann, R., Lan, T., Soltis, D., Soltis, P., Arikit, S., Axtell, M., Ayyampalayam, S., Barbazuk, W., Burnette, J., Chamala, S., De Paoli, E., dePamphilis, C., Der, J., Estill, J., Farrell, N., Harkess, A., Jiao, Y., Leebens-Mack, J., Liu, K., Mei, W., Meyers, B., Shahid, S., Wafula, E., Walts, B., Wessler, S., Zhai, J., Zhang, X., Albert, V., Carretero-Paulet, L., dePamphilis, C., Der, J., Jiao, Y., Leebens-Mack, J., Lyons, E., Sankoff, D., Tang, H., Wafula, E., Zheng, C., Albert, V., Altman, N., Barbazuk, W., Carretero-Paulet, L., dePamphilis, C., Der, J., Estill, J., Jiao, Y., Leebens-Mack, J., Liu, K., Mei, W., Wafula, E., Altman, N., Arikit, S., Axtell, M., Chamala, S., Chanderbali, A., Chen, F., Chen, J., Chiang, V., De Paoli, E., dePamphilis, C., Der, J., Determann, R., Fogliani, B., Guo, C., Harholt, J., Harkess, A., Job, C., Job, D., Kim, S., Kong, H., Leebens-Mack, J., Li, G., Li, L., Liu, J., Ma, H., Meyers, B., Park, J., Qi, X., Rajjou, L., Burtet-Sarramegna, V., Sederoff, R., Shahid, S., Soltis, D., Soltis, P., Sun, Y., Ulvskov, P., Villegente, M., Xue, J., Yeh, T., Yu, X., Zhai, J., Acosta, J., Albert, V., Barbazuk, W., Bruenn, R., Chamala, S., de Kochko, A., dePamphilis, C., Der, J., Herrera-Estrella, L., Ibarra-Laclette, E., Kirst, M., Leebens-Mack, J., Pissis, S., Poncet, V., Schuster, S., Soltis, D., Soltis, P., & Tomsho, L. (2013). The Amborella Genome and the Evolution of Flowering Plants Science, 342 (6165), 1241089-1241089 DOI: 10.1126/science.1241089

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The evolutionary history of polar bears

Tue, 18 Sep 2012 17:55:00 +0000

The study of the Ursus lineage, including brown bear (Ursus arctos), black bear (Ursus americanus) and polar bear (Ursus maritimus), provides the ability of addressing the subject of adaptation to extreme (salty and glacial) environments in mammals. Moreover, in last few decades, polar bears won public and media attention, being one of the most charismatic species endangered by global warming and Arctic ice melting. To trace history of innovations and determine response to environmental changes in populations of polar bears, two articles published in Science and Proceedings of the National Academy of Sciences in April and June 2012 provide new data and insights to resolve this question.

The absence of fossil of polar bears dating before the late Pleistocene (circa 126 000 years ago) and mitochondrial data, suggesting that polar bear were very closely related to a group of brown bear living in Admiralty, Baranof and Chichagof (ABC) islands in Alaska, previously led to believe that polar bears recently emerged from brown bears. The consequences of this hypotheses would be :

Polar bear underwent a very rapid and recent (less than 200 ky ago) adaptation to extreme environment (previously not seen in mammals)
Brown bear is a paraphyletic taxon, as polar bear is the sister specie of the ABC bears (see Fig. 1)


Fig. 1: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

Phylogeny of bear lineage with mitochondrial DNA and Bayesian maximum clade credibility model

The blue box contains polar individuals coming from Svalbard and Alaska and an ancient sample 130ky to 110 ky old, the yellow box ABC individuals and the pink box other brown bear individuals. The outgroup is made of black bears individuals.

Nevertheless, both fossil data, as it can be incomplete, and mitochondrial data, as it sensitive to hybridization, are not sufficient to confirm this hypothesis. Thus the two publishing groups led in parallel projects aiming to collect nuclear data and test its agreement with mitochondrial data.

Hailer et al., in their work Nuclear Genomic Sequences Reveal that Polar Bears Are an Old and Distinct Bear Lineage published in Science, sequenced 9116 nucleotides from 14 independent introns in 45 individuals of black, brown and polar bears. Introns were sequenced to provide more variation between individuals: given the low amount of time since the divergence of the last common ancestor of bears (estimated between 559 to 1 429 ky ago in their study), choosing exons, whose evolution being more likely bounded by selection, would have yielded less information.

Using this data and various phylogenetic reconstructions (bayesian multilocus coalescent approach, bayesian inference for the concatenated data and neighbour-joining of the differentiation estimates between species) that all led to the same conclusion, they recovered the three species of bears as being monophyletic and observed in the species tree the polar bear clade being sister to the brown bear clade. They estimated the divergence time of the two species around 603 ky ago (338 to 934 ky being the 99% highest credibility range) and clearly revealed a discrepancy with the mitochondrial data.

The authors resolved this incongruence by stating that the most probable scenario was a divergence between polar and brown species 600 ky ago and an hybridization event between 111 to 166 ky ago between polar bears and ABC bears leading to the complete replacement of the former mtDNA by the latter. The opposite phenomenon (several and severe introgression events of polar bears mtDNA into brown bears leading to all extant mtDNA being of polar origin) is judged very unlikely by the authors given the extended range of distribution of the brown bear. The lack of finding of older fossil from polar bears was explained by their constantly changing living environment.

Despite the recent hybridization event, Hailer et al. found very few common nuclear haplotypes between polar and brown bears: out of the 35 polar and 79 brown haplotypes, only 6 of them were shared across both species. Nevertheless, we must bear in mind that given the relatively low amount of nuclear data analysed, those findings might not reflect the entire picture of polar and brown bears nuclear DNA ancestry.

In Polar and brown bear genomes reveal ancient admixture and demographics footprints of past climate change, published in PNAS by Miller et al., a genome-wide sequencing project was adopted to unravel the same problem. In this extensive study, the authors assembled a reference genome of a polar bear individual, deeply sequenced the genome of two ABC, one black and one non-ABC brown bear (GRZ). Finally, they produced low coverage data from 23 other polar bear individuals, one of them being an ancient specimen 110 to 130 ky old found in Svalbard.

Having aligned all reads from every samples to the polar bear genome reference, they identified 12 millions of what they called “SNPs” (even though they are dealing with three different species) and constructed the following phylogeny (Fig. 2).

Fig. 2: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

Phylogeny based on the matrix of distances of the 12 millions SNP and using a neighbour-joining algorithm (probably given the amount of data and computational time needed with more sophisticated algorithms)

We observe that, as in the previous paper, the nuclear data is not in agreement with the mitochondrial data. A scenario where polar bears emerged as a sister species of the brown species and later experienced a massive and unique event of mtDNA introgression from ABC bears (as the polar bear individuals form only one group in Fig. 1) is again strongly favoured. Regarding the ancient polar bear specimen, both trees inform us that it dates after the mtDNA introgression event and that the modern individuals living in Svalbard are actually more closely related to the modern individuals in Alaska than to the ancient one.

Though up to this point both articles seem consistent, following findings radically differ with the previous study. Indeed, Miller et al., used a coalescence hidden Markov model for four of their deeply-covered genomes (one ABC, one polar bear, one brown bear, one black bear) to assess the history of the lineage. They estimated both the splits of polar bears with brown bears and the common ancestor of those two species with black bears to have occurred around 4 to 5 My ago, as shown in Fig. 3.


Fig. 3: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

Reconstructed evolutionnary history of polar, brown and black bears

The black solid line represent the specie tree and the brown dashed lines the mtDNA tree

The X represents the introgression event, the shortened branch of the specie tree the disappearance of the ancient Svalbard lineage

It is however true that Hailer et al. reported on their article (that pre-dates the PNAS one) that other studies hint that the 600 ky-value is an underestimate of the splitting time of the two lineages under consideration, without it weakening their own conclusion.

Nevertheless, other discrepancies arise : Hailer et al. stated that no evidence of on going gene flow was found between polar bears and brown bears, whereas the coalescent model used by Miller et al. yielded that the time when this gene flow stopped was not significantly different from zero. Following the Science article, a comment arose relating two very recent cases of documented hybridization of polar/brown bears in the wild, among them a second generation hybrid. Interestingly, both crosses involved a polar bear female with a brown bear male: thus no cross leading to the introgression of brown bear mtDNA onto polar bear populations has yet been described.

Besides, where Hailer et al. found relatively few shared nuclear data between polar and brown bears, a PCA analysis of the SNPs identified in the ABC, non-ABC and polar bear genomes yielded that 5.5% of one of the ABC genome and 9.4% of the other one are related to the polar bear genome (Fig. 4).


Fig. 4: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

PCA plot of SNP data for ABC1 & 2, polar and non-ABC brown bear (GRZ)

Following this PCA analysis, it is interesting to focus more precisely on the differentiation of populations of polar and brown bears, as the ABC and GRZ seem pretty much apart on the second component axis. Thus Miller et al. arbitrarily chose a subset of 100 SNPs identified from the genomes of all polar bear individuals and resequenced them for 118 individuals (58 polar bears, 9 ABC bears, 51 non-ABC brown bears). The PCA analysis yielded the following plot (Fig. 5).

Fig. 5: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

On the one hand, ABC and brown bears cluster together even if we can still discriminate them into two groups. On the other hand, polar bear populations seem much more genetically heterogenous than their sister species counterparts. However one must always remain careful when drawing conclusion on such a low amount of data (100 SNPs). Focusing on the polar populations, the authors performed a structured analysis upon this data (Fig. 6).


Fig. 5: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

Structure analysis of 58 polar bear individuals grouped into 4 population

The number of genetic population was set to 3

Here again lies a very striking difference between the two papers. Whereas Miller et al. clearly identified genetic structuring between the populations of polar bears, Hailer et al. used the same type of analysis upon the nuclear variation of their 45 individuals and it led them to conclude that the polar bears were much more genetically homogeneous than the brown bears.

Given the respective data set of both papers, only Miller et al. were able to address the point of adaptation to extreme environment. To do so, they aligned their deeply sequenced genome to the dog genome, choice resulting from a compromise between evolutionary distance and quality of the annotation (as the panda genome has been fully sequenced but being of less good quality). Having thus preserved sinteny accross the bear genomes, they were able to carry admixture analysis for the two ABC genomes (Fig. 6).

Fig. 6: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

Admixture map of the ABC 1 & 2 diploid genomes region homologous to dog chromosome 11

Blue: polar bear origin, red: brown bear origin

In this particular example, based on the annotation of the dog genome, the authors focus on a gene (ALDH7A1) involved in salt resistance. It appears that copies of this gene in the two ABC bears come from the polar bear. As ABC bears live in a marine environment, the idea hinted behind this plot is that during the hybridization event between polar bear and ABC bears, polar bear (being already adapted to salty environment) copies of this gene introgressed into the ABC population and were subsequently selected for, thus appearing in modern ABC individuals.

Then, using Fst values, they were able to identify a few other genes that might have been selected for during the evolution of polar bears, such as DAG1 (involved in the muscular dystrophy) or BTN1A1 (involved in milk producing).

I think that to address the subject of adaptation in polar bear, a study of positive selection in protein-coding gene is lacking. As authors already conducted transcriptome sequencing of polar and brown bears, annotating gene in their genome, selecting orthologous genes together with other copies from completely sequenced genomes, as dog, panda and other mammals, and then using a model to test for positive selection such as implemented in PAML would be an efficient way to identify genes of interest in the polar (or ABC) bears. Nevertheless, I am very well aware of the tremendous amount of work already performed in this PNAS paper.

Regarding the evolution of the population size in bears, Miller et al. used a pairwise sequentially markovian coalescent model (that uses the length of homozygoteous regions of a diploid genome) to reconstruct the effective population size (number of individual in a perfectly panmictic population leading to the same genetic diversity as our observed population) from the four bear genomes (Fig. 7).

Fig. 6: Miller et al., Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change, PNAS 2012

We observe the very closely related trends of both brown bear genomes and the continuous decline of non polar bears during the Early Pleistocene cooling. Conversly, the population of polar bears increased during this period but seemed very sensitive to the following warming period. Two points were raised when discussing this graph:

The bump in the polar bear curve signified as the “Post Eemian increase” was not significant when looking at the 95% interval range in the supplementary material
Knowing from the previous part of the article the extended hybridization between ABC and polar bears, would not the diversity introduced during those event affect the effective population size reconstruction ?

Putting those two papers in parallel allowed us to realize the difficulties of putting in agreement data from various origin, as in this case nuclear, mitochondrial, palaeontological and ecological. The amount of data needed to reconstruct the whole evolutionary history of such a complicated case becomes striking in the light of the work already performed here.

Hailer F, Kutschera VE, Hallström BM, Klassert D, Fain SR, Leonard JA, Arnason U, & Janke A (2012). Nuclear genomic sequences reveal that polar bears are an old and distinct bear lineage. Science (New York, N.Y.), 336 (6079), 344-347 PMID: 22517859

Miller W, Schuster SC, Welch AJ, Ratan A, Bedoya-Reina OC, Zhao F, Kim HL, Burhans RC, Drautz DI, Wittekindt NE, Tomsho LP, Ibarra-Laclette E, Herrera-Estrella L, Peacock E, Farley S, Sage GK, Rode K, Obbard M, Montiel R, Bachmann L, Ingólfsson O, Aars J, Mailund T, Wiig O, Talbot SL, & Lindqvist C (2012). Polar and brown bear genomes reveal ancient admixture and demographic footprints of past climate change. Proceedings of the National Academy of Sciences of the United States of America, 109 (36) PMID: 22826254

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Classic Selective Sweeps Were Rare in Recent Human Evolution

Wed, 30 Nov 2011 08:07:00 +0000

With the rise of genomics and the availability of whole genome sequences, geneticists hope to be able to understand the recent adaptations humans underwent. Classic selective sweeps, where a beneficial allele arises in a population and subsequently goes to fixation, leave a specific pattern. Indeed, all variation is erased as the selected allele invades the population, and the neighboring neutral variation is also partially swept, with an intensity depending on the linkage with the selected region.

An example of classic selective sweep pattern. As the distance from the selected nucleotide increases, diversity increases. Fig. 2 from Hernandez et al. 2011.

The selective sweep pattern was used to find evidence for recent adaptation in humans. Many candidate genes for recent adaptation in humans were found. Nevertheless, the preeminence of classic selective sweeps compared with other modes of adaptation (like background selection or recurrent a.k.a. “soft” sweeps) is still unknown.

In this paper, the authors claim that classic selective sweeps are in fact a rare event in human recent evolution. They argue that the overall pattern found in genome scan studies can be explained with only nearly neutral mechanisms (neutral evolution plus some purifying selection), without any positive selection going on. This casts a doubt on our ability to detect regions under selection from molecular data with currently available techniques.

Their evidence is based on polymorphism data from 179 human genomes from the 1000 genome project (see Durbin et al. 2010). The authors identified single nucleotide polymorphism. They pooled together all exons in order to see the overall sweep pattern around each substitution. The first blow to the preeminence of classic selective sweeps comes from the fact that synonymous and non-synonymous sites show the exact same sweep pattern. We would expect that non-synonymous sites, as they should be the targets of adaptation, show a stronger sweep pattern. Another concern comes from the comparison of genetic data with the expectation under neutral evolution. They show (see fig. 3) that if classic selective sweeps are frequent (more than 10% of human specific substitutions), we have the statistical power to detect a difference with a purely neutral evolution scenario. Nevertheless, we do not observe any difference between the genomic data and the neutral simulations.

Comparison of simulations under a neutral model with a model with selection, and the actual human genomes data. What is interesting in panel A is that the power is strong for all fractions of the genome under selection the authors tested (alpha parameter). Therefore the authors claim that if classic selective sweeps are frequent in the population, we should be able to detect a significant departure from neutrality. Panel B completes the argument as we can see that all curves (neutral model and human genome data) are merged. Considering that we should have the power to detect a departure from neutrality, the authors claim that the neutral scenario cannot be rejected. Fig. 3 from Hernandez et al. 2011.

They conclude that classic selective sweeps should not have been the major mode of adaptation in recent human evolution.

I personally was not convinced by the relevance of using a mean pattern, over all coding regions, to attest that classic sweeps were rare in human evolution. Indeed, most coding regions have not experienced a selective sweep in the past, and thus the mean pattern should indeed not differ from a neutral or background selection model. Nevertheless, the authors anticipated this argument, as they run simulations where only a fraction of the genome is under positive selection. And as I wrote above, they show that we should be able to discriminate between selection and background mutation, even if the proportion of loci under selection are as low as 10% of human specific substitutions.

We raised during our discussion another concern, regarding the parameter range covered in their simulations. Indeed, the authors tested the power to distinguish selection and neutrality with several fractions of the genome under positive selection, but did not test a wide range of selection coefficient. A selection coefficient of 0.01 already seems very large, and the question remains to see if with weaker selection, we do expect to see a difference in the mean pattern of diversity over all exon SNPs.

In conclusion, I believe that the authors showed that so far we can only detect classic AND very strong selective sweeps from molecular data. In my opinion, this means that we can rarely detect classic selective sweeps. The question remains whether classic but weaker selective sweeps were rare in recent human evolution.

Hernandez, R., Kelley, J., Elyashiv, E., Melton, S., Auton, A., McVean, G., , ., Sella, G., & Przeworski, M. (2011). Classic Selective Sweeps Were Rare in Recent Human Evolution Science, 331 (6019), 920-924 DOI: 10.1126/science.1198878

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