The Genomic Signature of Population Reconnection Following Isolation: From Theory to HIV

Genetic signatures of lineage fusion closely resemble population decline

Accurate interpretation of the genetic signatures of past demographic events is crucial for reconstructing evolutionary history. Lineage fusion (complete merging, resulting in a single panmictic population) is a special case of secondary contact that is seldom considered. Here, the circumstances under which lineage fusion can be distinguished from population size constancy, growth, bottleneck, and decline were investigated. Multi-locus haplotype data were simulated under models of lineage fusion with different divergence versus sampling lag times (D:L ratios). These pseudo-observed datasets also differed in their allocation of a fixed amount of sequencing resources (number of sampled alleles, haplotype length, number of loci). Distinguishability of lineage fusion versus each of 10 untrue non-fusion scenarios was quantified based on six summary statistics (neutrality tests). Some datasets were also analyzed using extended Bayesian skyline plots. Results showed that signatures of lineage fusion very closely resemble those of decline-high distinguishability was generally limited to the most favorable scenario (D:L = 9), using the most sensitive summary statistics (F S and Z nS), coupled with the optimal sequencing resource allocation (maximizing number of loci). Also, extended Bayesian skyline plots often erroneously inferred population decline. Awareness of the potential for lineage fusion to carry the hallmarks of population decline is critical.

Inferring the Demographic History and Inheritance Mode of Tetraploid Species Using ABC

Genomic patterns of diversity and divergence are impacted by certain life history traits, reproductive systems, and demographic history. The latter is characterized by fluctuations in population sizes over time, as well as by temporal patterns of introgression. For a given organism, identifying a demographic history that deviates from the standard neutral model allows a better understanding of its evolution but also helps to reduce the risk of false positives when screening for molecular targets of natural selection. Tetraploid organisms and beyond have demographic histories that are complicated by the mode of polyploidization, the mode of inheritance, and different scenarios of gene flow between sub-genomes and diploid parental species. Here we provide guidelines for experimenters wishing to address these issues through a flexible statistical framework: approximate Bayesian computation (ABC). The emphasis is on the general philosophy of the approach to encourage future users to exploit the enormous flexibility of ABC beyond the limitations imposed by generalist data analysis pipelines.

Genomic signatures of protease and reverse transcriptase genes from HIV-1 subtype C isolated from first-line ART patients in India

Genomic signatures of the protease and reverse transcriptase gene of HIV-1 from HIV infected North Indian patients who were under ART from 1 to ≤ 7 years were analyzed. The DNA from plasma samples of 9 patients and RNA from 57 patients were isolated and subjected to amplification for the protease and reverse transcriptase gene of HIV-1 subtype C. Then sequencing was carried out following the WHO dried blood spot protocol. The drug resistance mutation patterns were analyzed using the HIV Drug Resistance Database, Stanford University, USA. Lamivudine-associated drug-resistance mutations such as M184V/M184I, nevirapine-associated drug resistance mutations Y181C and H221Y, and efavirenz-associated drug resistance mutations M230I were observed in reverse transcriptase gene of archived DNA of two HIV-1 infected patients. No mutation was observed in the remaining 7 patients. Various computational tools and websites like viral epidemiological signature pattern analysis (VESPA), hyper mutation, SNAP version 2.1.1, and entropy were utilized for the analysis of the signature pattern of amino acids, hyper mutation, selection pressure, and Shannon entropy in the protease and reverse transcriptase gene sequences of the 9 archived DNA, 56 protease gene and 51 reverse transcriptase gene from the HIV-1 DNA amplified sequences of RNA. The HIV-1 Subtype-C (Gene bank accession number: AB023804) and first isolate HXB2 (Gene bank accession number: K03455.1) was taken as reference sequence. The signature amino acid sequences were identified in the protease and reverse transcriptase gene, no hyper mutation, highest entropy was marked in the amino acid positions and synonymous to non-synonymous nucleotide ratio was calculated in the protease and reverse transcriptase gene of 9 archived DNA sequences, 56 protease and 51 reverse transcriptase gene sequences of HIV-1 Subtype C isolates.

Biases in Demographic Modeling Affect Our Understanding of Recent Divergence

Testing among competing demographic models of divergence has become an important component of evolutionary research in model and non-model organisms. However, the effect of unaccounted demographic events on model choice and parameter estimation remains largely unexplored. Using extensive simulations, we demonstrate that under realistic divergence scenarios, failure to account for population size (N_e) changes in daughter and ancestral populations leads to strong biases in divergence time estimates as well as model choice. We illustrate these issues reconstructing the recent demographic history of North Sea and Baltic Sea turbots (Scophthalmus maximus) by testing 16 isolation with migration (IM) and 16 secondary contact (SC) scenarios, modeling changes in N_e as well as the effects of linked selection and barrier loci. Failure to account for changes in N_e resulted in selecting SC models with long periods of strict isolation and divergence times preceding the formation of the Baltic Sea. In contrast, models accounting for N_e changes suggest recent (<6 kya) divergence with constant gene flow. We further show how interpreting genomic landscapes of differentiation can help discerning among competing models. For example, in the turbot data, islands of differentiation show signatures of recent selective sweeps, rather than old divergence resisting secondary introgression. The results have broad implications for the study of population divergence by highlighting the potential effects of unmodeled changes in N_e on demographic inference. Tested models should aim at representing realistic divergence scenarios for the target taxa, and extreme caution should always be exercised when interpreting results of demographic modeling.

Gene flow as a simple cause for an excess of high-frequency-derived alleles

Most human populations exhibit an excess of high-frequency variants, leading to a U-shaped site-frequency spectrum (uSFS). This pattern has been generally interpreted as a signature of ongoing episodes of positive selection, or as evidence for a mis-assignment of ancestral/derived allelic states, but uSFS has also been observed in populations receiving gene flow from a ghost population, in structured populations, or after range expansions. In order to better explain the prevalence of high-frequency variants in humans and other populations, we describe here which patterns of gene flow and population demography can lead to uSFS by using extensive coalescent simulations. We find that uSFS can often be observed in a population if gene flow brings a few ancestral alleles from a well-differentiated population. Gene flow can either consist in single pulses of admixture or continuous immigration, but different demographic conditions are necessary to observe uSFS in these two scenarios. Indeed, an extremely low and recent gene flow is required in the case of single admixture events, while with continuous immigration, uSFS occurs only if gene flow started recently at a high rate or if it lasted for a long time at a low rate. Overall, we find that a neutral uSFS occurs under more restrictive conditions in populations having received single pulses of gene flow than in populations exposed to continuous gene flow. We also show that the uSFS observed in human populations from the 1000 Genomes Project can easily be explained by gene flow from surrounding populations without requiring past episodes of positive selection. These results imply that uSFS should be common in non-isolated populations, such as most wild or domesticated plants and animals.

Model-based demographic inference of introgression history in European whitefish species pairs'

Parallel phenotypic differentiation is generally attributed to parallel adaptive divergence as an evolutionary response to similar environmental contrasts. Such parallelism may actually originate from several evolutionary scenarios ranging from repeated parallel divergence caused by divergent selection to a unique divergence event followed by gene flow. Reconstructing the evolutionary history underlying parallel phenotypic differentiation is thus fundamental to understand the relative contribution of demography and selection on genomic divergence during speciation. In this study, we investigate the divergence history of replicate European whitefish (Coregonus lavaretus), limnetic and benthic species pairs from two lakes in Norway and two lakes in Switzerland. Demographic models accounting for semi-permeability and linked selection were fitted to the unfolded joint allele frequency spectrum built from genome-wide SNPs and compared to each other in each species pair. We found strong support for a model of asymmetrical post-glacial secondary contact between glacial lineages in all four lakes. Moreover, our results suggest that heterogeneous genomic differentiation has been shaped by the joint action of linked selection accelerating lineage sorting during allopatry, and heterogeneous migration eroding divergence at different rates along the genome following secondary contact. Our analyses reveal how the interplay between demography, selection and historical contingency has influenced the levels of diversity observed in previous whitefish phylogeographic studies. This study thus provides new insights into the historical demographic and selective processes that shaped the divergence associated with ecological speciation in European whitefish.

Analysis of Genome-Wide Differentiation between Native and Introduced Populations of the Cupped Oysters Crassostrea gigas and Crassostrea angulata

The Pacific cupped oyster is genetically subdivided into two sister taxa, Crassostrea gigas and Crassostrea angulata, which are in contact in the north-western Pacific. The nature and origin of their genetic and taxonomic differentiation remains controversial due the lack of known reproductive barriers and the high degree of morphologic similarity. In particular, whether the presence of ecological and/or intrinsic isolating mechanisms contributes to species divergence is unknown. The recent co-introduction of both taxa into Europe offers a unique opportunity to test how genetic differentiation is maintained under new environmental and demographic conditions. We generated a pseudochromosome assembly of the Pacific oyster genome using a combination of BAC-end sequencing and scaffold anchoring to a new high-density linkage map. We characterized genome-wide differentiation between C. angulata and C. gigas in both their native and introduced ranges, and showed that gene flow between species has been facilitated by their recent co-introductions in Europe. Nevertheless, patterns of genomic divergence between species remain highly similar in Asia and Europe, suggesting that the environmental transition caused by the co-introduction of the two species did not affect the genomic architecture of their partial reproductive isolation. Increased genetic differentiation was preferentially found in regions of low recombination. Using historical demographic inference, we show that the heterogeneity of differentiation across the genome is well explained by a scenario whereby recent gene flow has eroded past differentiation at different rates across the genome after a period of geographical isolation. Our results thus support the view that low-recombining regions help in maintaining intrinsic genetic differences between the two species.

The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies

Genome-scale diversity data are increasingly available in a variety of biological systems, and can be used to reconstruct the past evolutionary history of species divergence. However, extracting the full demographic information from these data is not trivial, and requires inferential methods that account for the diversity of coalescent histories throughout the genome. Here, we evaluate the potential and limitations of one such approach. We reexamine a well-known system of mussel sister species, using the joint site frequency spectrum (jSFS) of synonymous mutations computed either from exome capture or RNA-seq, in an Approximate Bayesian Computation (ABC) framework. We first assess the best sampling strategy (number of: individuals, loci, and bins in the jSFS), and show that model selection is robust to variation in the number of individuals and loci. In contrast, different binning choices when summarizing the jSFS, strongly affect the results: including classes of low and high frequency shared polymorphisms can more effectively reveal recent migration events. We then take advantage of the flexibility of ABC to compare more realistic models of speciation, including variation in migration rates through time (i.e., periodic connectivity) and across genes (i.e., genome-wide heterogeneity in migration rates). We show that these models were consistently selected as the most probable, suggesting that mussels have experienced a complex history of gene flow during divergence and that the species boundary is semi-permeable. Our work provides a comprehensive evaluation of ABC demographic inference in mussels based on the coding jSFS, and supplies guidelines for employing different sequencing techniques and sampling strategies. We emphasize, perhaps surprisingly, that inferences are less limited by the volume of data, than by the way in which they are analyzed.

The neutral frequency spectrum of linked sites

We introduce the conditional Site Frequency Spectrum (SFS) for a genomic region linked to a focal mutation of known frequency. An exact expression for its expected value is provided for the neutral model without recombination. Its relation with the expected SFS for two sites, 2-SFS, is discussed. These spectra derive from the coalescent approach of Fu (1995) for finite samples, which is reviewed. Remarkably simple expressions are obtained for the linked SFS of a large population, which are also solutions of the multi-allelic Kolmogorov equations. These formulae are the immediate extensions of the well known single site θ∕f neutral SFS. Besides the general interest in these spectra, they relate to relevant biological cases, such as structural variants and introgressions. As an application, a recipe to adapt Tajima's D and other SFS-based neutrality tests to a non-recombining region containing a neutral marker is presented.

Modeling the Multiple Facets of Speciation-with-Gene-Flow toward Inferring the Divergence History of Lake Whitefish Species Pairs (Coregonus clupeaformis)

Parallel divergence across replicated species pairs occurring in similar environmental contrasts may arise through distinct evolutionary scenarios. Deciphering whether such parallelism actually reflects repeated parallel divergence driven by divergent selection or a single divergence event with subsequent gene flow needs to be ascertained. Reconstructing historical gene flow is therefore of fundamental interest to understand how demography and selection jointly shaped genomic divergence during speciation. Here, we use an extended modeling framework to explore the multiple facets of speciation-with-gene-flow with demo-genetic divergence models that capture both temporal and genomic variation in effective population size and migration rate. We investigate the divergence history of replicate sympatric species pairs of Lake Whitefish (normal benthic and dwarf limnetic) characterized by variable degrees of ecological divergence and reproductive isolation. Genome-wide SNPs were used to document the extent of genetic differentiation in each species pair, and 26 divergence models were fitted and compared with the unfolded joint allele frequency spectrum of each pair. We found evidence that a recent (circa 3,000–4,000 generations) asymmetrical secondary contact between expanding postglacial populations has accompanied Whitefish diversification. Our results suggest that heterogeneous genomic differentiation has emerged through the combined effects of linked selection generating variable rates of lineage sorting across the genome during geographical isolation, and heterogeneous introgression eroding divergence at different rates across the genome upon secondary contact. This study thus provides a new retrospective insight into the historical demographic and selective processes that shaped a continuum of divergence associated with ecological speciation.