Predicting Carriers of Ongoing Selective Sweeps without Knowledge of the Favored Allele

A Novel Approach Utilizing Domain Adversarial Neural Networks for the Detection and Classification of Selective Sweeps

The identification and classification of selective sweeps are of great significance for improving the understanding of biological evolution and exploring opportunities for precision medicine and genetic improvement. Here, a domain adaptation sweep detection and classification (DASDC) method is presented to balance the alignment of two domains and the classification performance through a domain-adversarial neural network and its adversarial learning modules. DASDC effectively addresses the issue of mismatch between training data and real genomic data in deep learning models, leading to a significant improvement in its generalization capability, prediction robustness, and accuracy. The DASDC method demonstrates improved identification performance compared to existing methods and excels in classification performance, particularly in scenarios where there is a mismatch between application data and training data. The successful implementation of DASDC in real data of three distinct species highlights its potential as a useful tool for identifying crucial functional genes and investigating adaptive evolutionary mechanisms, particularly with the increasing availability of genomic data.

Landmarks in the history of selective sweeps

Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.

Admixture has obscured signals of historical hard sweeps in humans

The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.

Selection on the gametophyte: Modeling alternation of generations in plants

PREMISE

The degree of gametophyte dependence on the sporophyte life stage is a major feature that differentiates the life cycles of land plants, yet the evolutionary consequences of this difference remain poorly understood. Most evolutionary models assume organisms are either haploid or diploid for their entire lifespan, which is not appropriate for simulating plant life cycles. Here, we introduce shadie (Simulating Haploid-Diploid Evolution), a new, simple Python program for implementing simulations with biphasic life cycles and analyzing their results, using SLiM 3 as a simulation back end.

METHODS

We implemented evolutionary simulations under three realistic plant life cycle models supported in shadie, using either standardized or biologically realistic parameter settings to test how variation in plant life cycles and sexual systems affects patterns of genome diversity.

RESULTS

The dynamics of single beneficial mutation fixation did not vary dramatically between different models, but the patterns of spatial variation did differ, demonstrating that different life histories and model parameters affect both genetic diversity and linkage disequilibrium. The rate of linkage disequilibrium decay away from selected sites varied depending on model parameters such as cloning and selfing rates, through their impact on effective population sizes.

DISCUSSION

Evolutionary simulations are an exciting, underutilized approach in evolutionary research and education. shadie can aid plant researchers in developing null hypotheses, examining theory, and designing empirical studies, in order to investigate the role of the gametophyte life stage, and the effects of variation in plant life cycles, on plant genome evolution.

Assessing Bos taurus introgression in the UOA Bos indicus assembly

Background

Reference genomes are essential in the analysis of genomic data. As the cost of sequencing decreases, multiple reference genomes are being produced within species to alleviate problems such as low mapping accuracy and reference allele bias in variant calling that can be associated with the alignment of divergent samples to a single reference individual. The latest reference sequence adopted by the scientific community for the analysis of cattle data is ARS_UCD1.2, built from the DNA of a Hereford cow (Bos taurus taurus—B. taurus). A complementary genome assembly, UOA_Brahman_1, was recently built to represent the other cattle subspecies (Bos taurus indicus—B. indicus) from a Brahman cow haplotype to further support analysis of B. indicus data. In this study, we aligned the sequence data of 15 B. taurus and B. indicus breeds to each of these references.

Results

The alignment of B. taurus individuals against UOA_Brahman_1 detected up to five million more single-nucleotide variants (SNVs) compared to that against ARS_UCD1.2. Similarly, the alignment of B. indicus individuals against ARS_UCD1.2 resulted in one and a half million more SNVs than that against UOA_Brahman_1. The number of SNVs with nearly fixed alternative alleles also increased in the alignments with cross-subspecies. Interestingly, the alignment of B. taurus cattle against UOA_Brahman_1 revealed regions with a smaller than expected number of counts of SNVs with nearly fixed alternative alleles. Since B. taurus introgression represents on average 10% of the genome of Brahman cattle, we suggest that these regions comprise taurine DNA as opposed to indicine DNA in the UOA_Brahman_1 reference genome. Principal component and admixture analyses using genotypes inferred from this region support these taurine-introgressed loci. Overall, the flagged taurine segments represent 13.7% of the UOA_Brahman_1 assembly. The genes located within these segments were previously reported to be under positive selection in Brahman cattle, and include functional candidate genes implicated in feed efficiency, development and immunity.

Conclusions

We report a list of taurine segments that are in the UOA_Brahman_1 assembly, which will be useful for the interpretation of interesting genomic features (e.g., signatures of selection, runs of homozygosity, increased mutation rate, etc.) that could appear in future re-sequencing analysis of indicine cattle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00688-1.

Integration of population and functional genomics to understand mechanisms of artemisinin resistance in Plasmodium falciparum

Resistance to antimalarial drugs, and in particular to the artemisinin derivatives and their partner drugs, threatens recent progress toward regional malaria elimination and eventual global malaria eradication. Population-level studies utilizing whole-genome sequencing approaches have facilitated the identification of regions of the parasite genome associated with both clinical and in vitro drug-resistance phenotypes. However, the biological relevance of genes identified in these analyses and the establishment of a causal relationship between genotype and phenotype requires functional characterization. Here we examined data from population genomic and transcriptomic studies in the context of data generated from recent functional studies, using a new population genetic approach designed to identify potential favored mutations within the region of a selective sweep (iSAFE). We identified several genes functioning in pathways now known to be associated with artemisinin resistance that were supported in early population genomic studies, as well as potential new drug targets/pathways for further validation and consideration for treatment of artemisinin-resistant Plasmodium falciparum. In addition, we establish the utility of iSAFE in identifying positively-selected mutations in population genomic studies, potentially accelerating the time to functional validation of candidate genes.

Contrasting signatures of genomic divergence during sympatric speciation

The transition from 'well-marked varieties' of a single species into 'well-defined species'-especially in the absence of geographic barriers to gene flow (sympatric speciation)-has puzzled evolutionary biologists ever since Darwin1,2. Gene flow counteracts the buildup of genome-wide differentiation, which is a hallmark of speciation and increases the likelihood of the evolution of irreversible reproductive barriers (incompatibilities) that complete the speciation process3. Theory predicts that the genetic architecture of divergently selected traits can influence whether sympatric speciation occurs4, but empirical tests of this theory are scant because comprehensive data are difficult to collect and synthesize across species, owing to their unique biologies and evolutionary histories5. Here, within a young species complex of neotropical cichlid fishes (Amphilophus spp.), we analysed genomic divergence among populations and species. By generating a new genome assembly and re-sequencing 453 genomes, we uncovered the genetic architecture of traits that have been suggested to be important for divergence. Species that differ in monogenic or oligogenic traits that affect ecological performance and/or mate choice show remarkably localized genomic differentiation. By contrast, differentiation among species that have diverged in polygenic traits is genomically widespread and much higher overall, consistent with the evolution of effective and stable genome-wide barriers to gene flow. Thus, we conclude that simple trait architectures are not always as conducive to speciation with gene flow as previously suggested, whereas polygenic architectures can promote rapid and stable speciation in sympatry.

TRPV6 as a Putative Genomic Susceptibility Locus Influencing Racial Disparities in Cancer

It is well established that African Americans exhibit higher incidence, higher mortality, and more aggressive forms of some cancers, including those of breast, prostate, colon, stomach, and cervix. Here we examine the ancestral haplotype of the TRPV6 calcium channel as a putative genomic factor in this racial divide. The minor (ancestral) allele frequency is 60% in people of African ancestry, but between 1% and 11% in all other populations. Research on TRPV6 structure/function, its association with specific cancers, and the evolutionary-ecological conditions that impacted selection of its haplotypes are synthesized to provide evidence for TRPV6 as a germline susceptibility locus in cancer. Recently elucidated mechanisms of TRPV6 channel deactivation are discussed in relation to the location of the allele favored in selection, suggesting a reduced capacity to inactivate the channel in those who have the ancestral haplotype. This could result in an excessively high cellular Ca²⁺, which has been implicated in cancer, for those in settings where calcium intake is far higher than in their ancestral environment. A recent report associating increasing calcium intake with a pattern of increase in aggressive prostate cancer in African-American but not European-American men may be related. If TRPV6 is found to be associated with cancer, further research would be warranted to improve risk assessment and examine interventions with the aim of improving cancer outcomes for people of African ancestry.

Detection and Classification of Hard and Soft Sweeps from Unphased Genotypes by Multilocus Genotype Identity

Positive natural selection can lead to a decrease in genomic diversity at the selected site and at linked sites, producing a characteristic signature of elevated expected haplotype homozygosity. These selective sweeps can be hard or soft. In the case of a hard selective sweep, a single adaptive haplotype rises to high population frequency, whereas multiple adaptive haplotypes sweep through the population simultaneously in a soft sweep, producing distinct patterns of genetic variation in the vicinity of the selected site. Measures of expected haplotype homozygosity have previously been used to detect sweeps in multiple study systems. However, these methods are formulated for phased haplotype data, typically unavailable for nonmodel organisms, and some may have reduced power to detect soft sweeps due to their increased genetic diversity relative to hard sweeps. To address these limitations, we applied the H12 and H2/H1 statistics proposed in 2015 by Garud et al., which have power to detect both hard and soft sweeps, to unphased multilocus genotypes, denoting them as G12 and G2/G1. G12 (and the more direct expected homozygosity analog to H12, denoted G123) has comparable power to H12 for detecting both hard and soft sweeps. G2/G1 can be used to classify hard and soft sweeps analogously to H2/H1, conditional on a genomic region having high G12 or G123 values. The reason for this power is that, under random mating, the most frequent haplotypes will yield the most frequent multilocus genotypes. Simulations based on parameters compatible with our recent understanding of human demographic history suggest that expected homozygosity methods are best suited for detecting recent sweeps, and increase in power under recent population expansions. Finally, we find candidates for selective sweeps within the 1000 Genomes CEU, YRI, GIH, and CHB populations, which corroborate and complement existing studies.

New Insights into the Genetic Basis of Monge's Disease and Adaptation to High-Altitude

Human high-altitude (HA) adaptation or mal-adaptation is explored to understand the physiology, pathophysiology, and molecular mechanisms that underlie long-term exposure to hypoxia. Here, we report the results of an analysis of the largest whole-genome-sequencing of Chronic Mountain Sickness (CMS) and nonCMS individuals, identified candidate genes and functionally validated these candidates in a genetic model system (Drosophila). We used PreCIOSS algorithm that uses Haplotype Allele Frequency score to separate haplotypes carrying the favored allele from the noncarriers and accordingly, prioritize genes associated with the CMS or nonCMS phenotype. Haplotypes in eleven candidate regions, with SNPs mostly in nonexonic regions, were significantly different between CMS and nonCMS subjects. Closer examination of individual genes in these regions revealed the involvement of previously identified candidates (e.g., SENP1) and also unreported ones SGK3, COPS5, PRDM1, and IFT122 in CMS. Remarkably, in addition to genes like SENP1, SGK3, and COPS5 which are HIF-dependent, our study reveals for the first time HIF-independent gene PRDM1, indicating an involvement of wider, nonHIF pathways in HA adaptation. Finally, we observed that down-regulating orthologs of these genes in Drosophila significantly enhanced their hypoxia tolerance. Taken together, the PreCIOSS algorithm, applied on a large number of genomes, identifies the involvement of both new and previously reported genes in selection sweeps, highlighting the involvement of multiple hypoxia response systems. Since the overwhelming majority of SNPs are in nonexonic (and possibly regulatory) regions, we speculate that adaptation to HA necessitates greater genetic flexibility allowing for transcript variability in response to graded levels of hypoxia.

Identifying the favored mutation in a positive selective sweep

Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations.

Detecting Recent Positive Selection with a Single Locus Test Bipartitioning the Coalescent Tree

Many population genomic studies have been conducted in the past to search for traces of recent events of positive selection. These traces, however, can be obscured by temporal variation of population size or other demographic factors. To reduce the confounding impact of demography, the coalescent tree topology has been used as an additional source of information for detecting recent positive selection in a population or a species. Based on the branching pattern at the root, we partition the hypothetical coalescent tree, inferred from a sequence sample, into two subtrees. The reasoning is that positive selection could impose a strong impact on branch length in one of the two subtrees while demography has the same effect on average on both subtrees. Thus, positive selection should be detectable by comparing statistics calculated for the two subtrees. Simulations demonstrate that the proposed test based on these principles has high power to detect recent positive selection even when DNA polymorphism data from only one locus is available, and that it is robust to the confounding effect of demography. One feature is that all components in the summary statistics ([Formula: see text]) can be computed analytically. Moreover, misinference of derived and ancestral alleles is seen to have only a limited effect on the test, and it therefore avoids a notorious problem when searching for traces of recent positive selection.

Senp1 drives hypoxia-induced polycythemia via GATA1 and Bcl-xL in subjects with Monge's disease

Azad and collaborators propose that Senp1 drives excessive erythropoiesis in high-altitude Andean dwellers suffering from chronic mountain sickness.

In this study, because excessive polycythemia is a predominant trait in some high-altitude dwellers (chronic mountain sickness [CMS] or Monge’s disease) but not others living at the same altitude in the Andes, we took advantage of this human experiment of nature and used a combination of induced pluripotent stem cell technology, genomics, and molecular biology in this unique population to understand the molecular basis for hypoxia-induced excessive polycythemia. As compared with sea-level controls and non-CMS subjects who responded to hypoxia by increasing their RBCs modestly or not at all, respectively, CMS cells increased theirs remarkably (up to 60-fold). Although there was a switch from fetal to adult HgbA0 in all populations and a concomitant shift in oxygen binding, we found that CMS cells matured faster and had a higher efficiency and proliferative potential than non-CMS cells. We also established that SENP1 plays a critical role in the differential erythropoietic response of CMS and non-CMS subjects: we can convert the CMS phenotype into that of non-CMS and vice versa by altering SENP1 levels. We also demonstrated that GATA1 is an essential downstream target of SENP1 and that the differential expression and response of GATA1 and Bcl-xL are a key mechanism underlying CMS pathology.