Genome-wide scans for footprints of natural selection

A positive selection at binding site 501 in the B.1 lineage might have triggered the highly infectious sub-lineages of SARS-CoV-2

The descendants of the B lineage are the most predominant variants among the SARS-CoV-2 virus due to the incorporation of new mutations augmenting the infectivity of the virus. There is a substantial increase in the transition transversion bias, nucleotide diversity and purifying selection on the spike protein in the descendants of the B lineage of the SARS-CoV-2 virus on a temporal scale. A strong bias for C-to-U substitutions is found in the genes encoding spike protein in this lineage. The positive selection has operated on the spike gene of B lineages and its sub-lineages. The B.1 lineage has undergone positive selection on site 501 of the receptor binding domain ultimately reflected in a key substitution N501Y in its three descendant lineages namely B.1.1.7, B.1.351 and P.1. The intensity of purifying selection on the multiple sites of the spike gene has increased substantially in the sub-lineages of B.1 in a timescale. The binding site 501 on the spike protein in B lineage is found to coevolve with other amino acid sites. This study sheds light on the evolutionary trajectory of the B lineage into highly infectious descendants in the recent past under the influence of positive and purifying selection exerted by natural immunity and vaccination of the host.

Population structure and selection signal analysis of indigenous sheep from the southern edge of the Taklamakan Desert

Analyzing the genetic diversity and selection characteristics of sheep (Ovis aries) holds significant value in understanding their environmental adaptability, enhancing breeding efficiency, and achieving effective conservation and rational utilization of genetic resources. In this study, we utilized Illumina Ovine SNP 50 K BeadChip data from four indigenous sheep breeds from the southern margin of the Taklamakan Desert (Duolang sheep: n = 36, Hetian sheep: n = 74, Kunlun sheep: n = 27, Qira black sheep: n = 178) and three foreign meat sheep breeds (Poll Dorset sheep: n = 105, Suffolk sheep: n = 153, Texel sheep: n = 150) to investigate the population structure, genetic diversity, and genomic signals of positive selection within the indigenous sheep. According to the Principal component analysis (PCA), the Neighbor-Joining tree (NJ tree), and Admixture, we revealed distinct clustering patterns of these seven sheep breeds based on their geographical distribution. Then used Cross Population Extended Haplotype Homozygosity (XP-EHH), Fixation Index (FST), and Integrated Haplotype Score (iHS), we identified a collective set of 32 overlapping genes under positive selection across four indigenous sheep breeds. These genes are associated with wool follicle development and wool traits, desert environmental adaptability, disease resistance, reproduction, and high-altitude adaptability. This study reveals the population structure and genomic selection characteristics in the extreme desert environments of native sheep breeds from the southern edge of the Taklimakan Desert, providing new insights into the conservation and sustainable use of indigenous sheep genetic resources in extreme environments. Additionally, these findings offer valuable genetic resources for sheep and other mammals to adapt to global climate change.

Approximate Bayesian Computation applied to time series of population genetic data disentangles rapid genetic changes and demographic variations in a pathogen population

Adaptation can occur at remarkably short timescales in natural populations, leading to drastic changes in phenotypes and genotype frequencies over a few generations only. The inference of demographic parameters can allow understanding how evolutionary forces interact and shape the genetic trajectories of populations during rapid adaptation. Here we propose a new Approximate Bayesian Computation (ABC) framework that couples a forward and individual-based model with temporal genetic data to disentangle genetic changes and demographic variations in a case of rapid adaptation. We test the accuracy of our inferential framework and evaluate the benefit of considering a dense versus sparse sampling. Theoretical investigations demonstrate high accuracy in both model and parameter estimations, even if a strong thinning is applied to time series data. Then, we apply our ABC inferential framework to empirical data describing the population genetic changes of the poplar rust pathogen following a major event of resistance overcoming. We successfully estimate key demographic and genetic parameters, including the proportion of resistant hosts deployed in the landscape and the level of standing genetic variation from which selection occurred. Inferred values are in accordance with our empirical knowledge of this biological system. This new inferential framework, which contrasts with coalescent-based ABC analyses, is promising for a better understanding of evolutionary trajectories of populations subjected to rapid adaptation.

Selection signatures and landscape genomics analysis to reveal climate adaptation of goat breeds

Goats have achieved global prominence as essential livestock since their initial domestication, primarily owing to their remarkable adaptability to diverse environmental and production systems. Differential selection pressures influenced by climate have led to variations in their physical attributes, leaving genetic imprints within the genomes of goat breeds raised in diverse agroecological settings. In light of this, our study pursued a comprehensive analysis, merging environmental data with single nucleotide polymorphism (SNP) variations, to unearth indications of selection shaped by climate-mediated forces in goats. Through the examination of 43,300 SNPs from 51 indigenous goat breeds adapting to different climatic conditions using four analytical methods: latent factor mixed models (LFMM), F-statistics (Fst), Extended haplotype homozygosity across populations (XPEHH), and spatial analysis method (SAM), A total of 74 genes were revealed to display clear signs of selection, which are believed to be influenced by climatic conditions. Among these genes, 32 were consistently identified by at least two of the applied methods, and three genes (DENND1A, PLCB1, and ITPR2) were confirmed by all four approaches. Moreover, our investigation yielded 148 Gene Ontology (GO) terms based on these 74 genes, underlining pivotal biological pathways crucial for environmental adaptation. These pathways encompass functions like vascular smooth muscle contraction, cellular response to heat, GTPase regulator activity, rhythmic processes, and responses to temperature stimuli. Of significance, GO terms about endocrine regulation and energy metabolic responses, key for local adaptation were also uncovered, including biological processes, such as cell differentiation, regulation of peptide hormone secretion, and lipid metabolism. These findings contribute to our knowledge of the genetic structure of climate-triggered adaptation across the goat genome and have practical implications for marker-assisted breeding in goats.

The Potential Impact of MYH9 (rs3752462) and ELMO1 (rs741301) Genetic Variants on the Risk of Nephrotic Syndrome Incidence

The kidney lost a lot of protein in the urine when you have nephrotic syndrome (NS). Clinical manifestations mostly common in NS include massive proteinuria, hypoalbuminemia, hyperlipidemia, and edema. Idiopathic nephrotic syndrome is currently classified into steroid-dependent (SDNS) and steroid-resistant (SRNS) based on the initial response to corticosteroid therapy at presentation. Several reports examined the association of the MYH9 gene (rs3752462, C > T) variant and ELMO1 gene (rs741301 G > A) variant as risk factors for Nephrotic Syndrome. This study aimed to determine the potential effect of the MYH9 gene (rs3752462, C > T) and ELMO1 gene (rs741301) variant on the risk of (NS) among Egyptian Children. This study included two hundred participants involving 100 nephrotic syndrome (NS) cases and 100 healthy controls free from nephrotic syndrome (NS). The MYH9 gene (rs3752462, C > T) variant and ELMO1 gene (rs G > A741301) variant were analyzed by ARMS-PCR technique. Nephrotic syndrome cases include 74% SRNS and 26% SDNS. Higher frequencies of the heterozygous carrier (CT) and homozygous variant (TT) genotypes of the MYH9 (rs3752462, C > T) variant were observed in NS patients compared to the controls with p-value < 0.001. The frequencies of the MYH9 (rs3752462, C > T variant indicated a statistically significant elevated risk of NS under various genetic models, including allelic model (OR 2.85, p < 0.001), dominant (OR 3.97, p < 0.001) models, and the recessive model OR 5.94, p < 0.001). Higher frequencies of the heterozygous carrier (GA) and homozygous variant (AA) genotypes of ELMO1gene (rs G > A741301) variant were observed in NS patients compared to the controls with p-value < 0.001. The frequencies of the ELMO1 (rs G > A741301) variant indicated a statistically significant elevated risk of NS under various genetic models, including allelic model (OR 2.15, p < 0.001), dominant models (OR 2.8, p < 0.001), and the recessive model (OR 4.17, p = 0.001). Both MYH9 and ELMO1 gene variants are significantly different in NS in comparison with the control group (p < 0.001). The MYH9 gene (rs3752462, C > T) and ELMO1gene (rs G > A741301) variants were considered independent risk factors for NS among Egyptian Children.

Ascertaining the genetic background of the Celtic-Iberian pig strain: A signatures of selection approach

Celtic-Iberian pig breeds were majority in Spain and Portugal until the first half of the 20th century. In the 1990s, they were nearly extinct as a result of the introduction of foreign improved pig breeds. Despite its historical importance, the genetic background of the Celtic-Iberian pig strain is poorly documented. In this study, we have identified genomic regions that might contain signatures of selection peculiar of the Celtic-Iberian genetic lineage. A total of 153 DNA samples of Celtic-Iberian pigs (Spanish Gochu Asturcelta and Portuguese Bísara breeds), Iberian pigs (Spanish Iberian and Portuguese Alentejano breeds), Cinta Senese pig, Korean local pig and Cosmopolitan pig (Hampshire, Landrace and Large White individuals) were analysed. A pairwise-comparison approach was applied: the Gochu Asturcelta and the Bísara samples as test populations and the five other pig populations as reference populations. Three different statistics (XP-EHH, FST and ΔDAF) were computed on each comparison. Strict criteria were used to identify selection sweeps in order to reduce the noise brought on by the Gochu Asturcelta and Bísara breeds' severe population bottlenecks. Within test population, SNPs used to construct potential candidate genomic areas under selection were only considered if they were identified in four of ten two-by-two pairwise comparisons and in at least two of three statistics. Genomic regions under selection constructed within test population were subsequently overlapped to construct candidate regions under selection putatively unique to the Celtic-Iberian pig strain. These genomic regions were finally used for enrichment analyses. A total of 39 candidate regions, mainly located on SSC5 and SSC9 and covering 3130.5 kb, were identified and could be considered representative of the ancient genomic background of the Celtic-Iberian strain. Enrichment analysis allowed to identify a total of seven candidate genes (NOL12, LGALS1, PDXP, SH3BP1, GGA1, WIF1, and LYPD6). Other studies reported that the WIF1 gene is associated with ear size, one of the characteristic traits of the Celtic-Iberian pig strain. The function of the other candidate genes could be related to reproduction, adaptation and immunity traits, indirectly fitting with the rusticity of a non-improved pig strain traditionally exploited under semi-extensive conditions.

The impact of paramutations on the invasion dynamics of transposable elements

According to the prevailing view, the trap model, the activity of invading transposable elements (TEs) is greatly reduced when a TE copy jumps into a piRNA cluster, which triggers the emergence of piRNAs that silence the TE. One crucial component in the host defence are paramutations. Mediated by maternally deposited piRNAs, paramutations convert TE insertions into piRNA producing loci, thereby transforming selfish TEs into agents of the host defence. Despite this significant effect, the impact of paramutations on the dynamics of TE invasions remains unknown. To address this issue, we performed extensive forward simulations of TE invasions with piRNA clusters and paramutations. We found that paramutations significantly affect TE dynamics, by accelerating the silencing of TE invasions, reducing the number of insertions accumulating during the invasions and mitigating the fitness cost of TEs. We also demonstrate that piRNA production induced by paramutations, an epigenetically inherited trait, may be positively selected. Finally, we show that paramutations may account for three important open problems with the trap model. Firstly, paramutated TE insertions may compensate for the insufficient number of insertions in piRNA clusters observed in previous studies. Secondly, paramutations may explain the discrepancy between the observed and the expected abundance of different TE families in Drosophila melanogaster. Thirdly, piRNA clusters may be crucial to trigger the host defence, but paramutations render the clusters dispensable once the defence has been established. This could account for the lack of TE activation when three major piRNA clusters were deleted in a previous study.

Candidate signatures of positive selection for environmental adaptation in indigenous African cattle: A review

Environmental adaptation traits of indigenous African cattle are increasingly being investigated to respond to the need for sustainable livestock production in the context of unpredictable climatic changes. Several studies have highlighted genomic regions under positive selection probably associated with adaptation to environmental challenges (e.g. heat stress, trypanosomiasis, tick and tick-borne diseases). However, little attention has focused on pinpointing the candidate causative variant(s) controlling the traits. This review compiled information from 22 studies on signatures of positive selection in indigenous African cattle breeds to identify regions under positive selection. We highlight some key candidate genome regions and genes of relevance to the challenges of living in extreme environments (high temperature, high altitude, high infectious disease prevalence). They include candidate genes involved in biological pathways relating to innate and adaptive immunity (e.g. BoLAs, SPAG11, IL1RL2 and GFI1B), heat stress (e.g. HSPs, SOD1 and PRLH) and hypoxia responses (e.g. BDNF and INPP4A). Notably, the highest numbers of candidate regions are found on BTA3, BTA5 and BTA7. They overlap with genes playing roles in several biological functions and pathways. These include but are not limited to growth and feed intake, cell stability, protein stability and sweat gland development. This review may further guide targeted genome studies aiming to assess the importance of candidate causative mutations, within regulatory and protein-coding genome regions, to further understand the biological mechanisms underlying African cattle's unique adaption.

Genetic Diversity and Signatures of Selection in the Roughskin Sculpin (Trachidermus fasciatus) Revealed by Whole Genome Sequencing

The roughskin sculpin (Trachidermus fasciatus) is an endangered fish species in China. In recent years, artificial breeding technology has made significant progress, and the population of roughskin sculpin has recovered in the natural environment through enhancement programs and the release of juveniles. However, the effects of released roughskin sculpin on the genetic structure and diversity of wild populations remain unclear. Studies on genetic diversity analysis based on different types and numbers of molecular markers have yielded inconsistent results. In this study, we obtained 2,610,157 high-quality SNPs and 494,698 InDels through whole-genome resequencing of two farmed populations and one wild population. Both farmed populations showed consistent levels of genomic polymorphism and a slight increase in linkage compared with wild populations. The population structure of the two farmed populations was distinct from that of the wild population, but the degree of genetic differentiation was low (overall average Fst = 0.015). Selective sweep analysis showed that 523,529 genes were selected in the two farmed populations, and KEGG enrichment analysis showed that the selected genes were related to amino acid metabolism, which might be caused by artificial feeding. The findings of this study provide valuable additions to the existing genomic resources to help conserve roughskin sculpin populations.

Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under nonconvex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data although preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx, which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

Urbanization drives adaptive evolution in a Neotropical bird

Urbanization has dramatic impacts on natural habitats and such changes may potentially drive local adaptation of urban populations. Behavioral change has been specifically shown to facilitate the fast adaptation of birds to changing environments, but few studies have investigated the genetic mechanisms of this process. Such investigations could provide insights into questions about both evolutionary theory and management of urban populations. In this study, we investigated whether local adaptation has occurred in urban populations of a Neotropical bird species, Coereba flaveola, specifically addressing whether observed behavioral adaptations are correlated to genetic signatures of natural selection. To answer this question, we sampled 24 individuals in urban and rural environments, and searched for selected loci through a genome-scan approach based on RADseq genomic data, generated and assembled using a reference genome for the species. We recovered 46 loci as putative selection outliers, and 30 of them were identified as associated with biological processes possibly related to urban adaptation, such as the regulation of energetic metabolism, regulation of genetic expression, and changes in the immunological system. Moreover, genes involved in the development of the nervous system showed signatures of selection, suggesting a link between behavioral and genetic adaptations. Our findings, in conjunction with similar results in previous studies, support the idea that cities provide a similar selective pressure on urban populations and that behavioral plasticity may be enhanced through genetic changes in urban populations.

A genome-wide comparison between selected and unselected Valle del Belice sheep reveals differences in population structure and footprints of recent selection

About three decades of breeding and selection in the Valle del Belìce sheep are expected to have left several genomic footprints related to milk production traits. In this study, we have assembled a dataset with 451 individuals of the Valle del Belìce sheep breed: 184 animals that underwent directional selection for milk production and 267 unselected animals, genotyped for 40,660 single-nucleotide polymorphisms (SNPs). Three different statistical approaches, both within (iHS and ROH) and between (Rsb) groups, were used to identify genomic regions potentially under selection. Population structure analyses separated all individuals according to their belonging to the two groups. A total of four genomic regions on two chromosomes were jointly identified by at least two statistical approaches. Several candidate genes for milk production were identified, corroborating the polygenic nature of this trait and which may provide clues to potential new selection targets. We also found candidate genes for growth and reproductive traits. Overall, the identified genes may explain the effect of selection to improve the performances related to milk production traits in the breed. Further studies using high-density array data, would be particularly relevant to refine and validate these results.

Spatial and temporal diversity of positive selection on shared haplotypes at the PSCA locus among worldwide human populations

Selection on standing genetic variation is important for rapid local genetic adaptation when the environment changes. We report that, for the prostate stem cell antigen (PSCA) gene, different populations have different target haplotypes, even though haplotypes are shared among populations. The C-C-A haplotype, whereby the first C is located at rs2294008 of PSCA and is a low risk allele for gastric cancer, has become a target of positive selection in Asia. Conversely, the C-A-G haplotype carrying the same C allele has become a selection target mainly in Africa. However, Asian and African share both haplotypes, consistent with the haplotype divergence time (170 kya) prior to the out-of-Africa dispersal. The frequency of C-C-A/C-A-G is 0.344/0.278 in Asia and 0.209/0.416 in Africa. Two-dimensional site frequency spectrum analysis revealed that the extent of intra-allelic variability of the target haplotype is extremely small in each local population, suggesting that C-C-A or C-A-G is under ongoing hard sweeps in local populations. From the time to the most recent common ancestor (TMRCA) of selected haplotypes, the onset times of positive selection were recent (3-55 kya), concurrently with population subdivision from a common ancestor. Additionally, estimated selection coefficients from ABC analysis were up to ~3%, similar to those at other loci under recent positive selection. Phylogeny of local populations and TMRCA of selected haplotypes revealed that spatial and temporal switching of positive selection targets is a unique and novel feature of ongoing selection at PSCA. This switching may reflect the potential of rapid adaptability to distinct environments.

Tensor decomposition based feature extraction and classification to detect natural selection from genomic data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under non-convex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data while preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx , which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

Population Genomic Analysis of Diploid-Autopolyploid Species

This chapter outlines an empirical analysis of genome-wide single-nucleotide polymorphism (SNP) variation and its underlying drivers among multiple natural populations within a diploid-autopolyploid species. The aim is to reconstruct the genetic structure among natural populations of varying ploidy and infer footprints of selection in these populations, framed around specific questions that are typically encountered when analyzing a mixed-ploidy data set,e.g., addressing the relevance of natural whole-genome duplication for speciation and adaptation. We briefly review the options for the analysis of polyploid population genomic data involving variant calling, population structure, demographic history inference, and selection scanning approaches. Further, we provide suggestions for methods and associated software, possible caveats, and examples of their application to mixed-ploidy and autopolyploid data sets.

Selection signatures for fiber production in commercial species: A review

Natural fibers derived from diverse animal species have gained increased attention in recent years due to their favorable environmental effects, long-term sustainability benefits, and remarkable physical and mechanical properties that make them valuable raw materials used for textile and non-textile production. Domestication and selective breeding for the economically significant fiber traits play an imperative role in shaping the genomes and, thus, positively impact the overall productivity of the various fiber-producing species. These selection pressures leave unique footprints on the genome due to alteration in the allelic frequencies at specific loci, characterizing selective sweeps. Recent advances in genomics have enabled the discovery of selection signatures across the genome using a variety of methods. The increased demand for 'green products' manufactured from natural fibers necessitates a detailed investigation of the genomes of the various fiber-producing plant and animal species to identify the candidate genes associated with important fiber attributes such as fiber diameter/fineness, color, length, and strength, among others. The objective of this review is to present a comprehensive overview of the concept of selection signature and selective sweeps, discuss the main methods used for its detection, and address the selection signature studies conducted so far in the diverse fiber-producing animal species.

Wide distribution of D-xylose dehydrogenase in yeasts reveals a new element in the D-xylose metabolism for bioethanol production

D-xylose utilization by yeasts is an essential feature for improving second-generation ethanol production. However, industrial yeast strains are incapable of consuming D-xylose. Previous analyzes of D-xylose-consuming or fermenting yeast species reveal that the genomic features associated with this phenotype are complex and still not fully understood. Here we present a previously neglected yeast enzyme related to D-xylose metabolism, D-xylose dehydrogenase (XylDH), which is found in at least 105 yeast genomes. By analyzing the XylDH gene family, we brought evidence of gene evolution marked by purifying selection on codons and positive selection evidence in D-xylose-consuming and fermenting species, suggesting the importance of XylDH for D-xylose-related phenotypes in yeasts. Furthermore, although we found no putative metabolic pathway for XylDH in yeast genomes, namely the absence of three bacterial known pathways for this enzyme, we also provide its expression profile on D-xylose media following D-xylose reductase for two yeasts with publicly available transcriptomes. Based on these results, we suggest that XylDH plays an important role in D-xylose usage by yeasts, likely being involved in a cofactor regeneration system by reducing cofactor imbalance in the D-xylose reductase pathway.

Climate-Driven Adaptive Differentiation in Melia azedarach: Evidence from a Common Garden Experiment

Studies of local adaptation in populations of chinaberry (Melia azedarach L.) are important for clarifying patterns in the population differentiation of this species across its natural range. M. azedarach is an economically important timber species, and its phenotype is highly variable across its range in China. Here, we collected M. azedarach seeds from 31 populations across its range and conducted a common garden experiment. We studied patterns of genetic differentiation among populations using molecular markers (simple sequence repeats) and data on phenotypic variation in six traits collected over five years. Our sampled populations could be subdivided into two groups based on genetic analyses, as well as patterns of isolation by distance and isolation by environment. Significant differentiation in growth traits was observed among provenances and families within provenances. Geographic distance was significantly correlated with the quantitative genetic differentiation (QST) in height (HEIT) and crown breadth. Climate factors were significantly correlated with the QST for each trait. A total of 23 climatic factors were examined. There was a significant effect of temperature on all traits, and minimum relative humidity had a significant effect on the survival rate over four years. By comparing the neutral genetic differentiation (FST) with the QST, the mode of selection acting on survival rate varied, whereas HEIT and the straightness of the main trunk were subject to the same mode of selection. The variation in survival rate was consistent with the variation in genetic differentiation among populations, which was indicative of local adaptation. Overall, our findings provide new insights into the responses of the phenological traits of M. azedarach to changes in the climate conditions of China.

Prospects for genomic surveillance for selection in schistosome parasites

Schistosomiasis is a neglected tropical disease caused by multiple parasitic Schistosoma species, and which impacts over 200 million people globally, mainly in low- and middle-income countries. Genomic surveillance to detect evidence for natural selection in schistosome populations represents an emerging and promising approach to identify and interpret schistosome responses to ongoing control efforts or other environmental factors. Here we review how genomic variation is used to detect selection, how these approaches have been applied to schistosomes, and how future studies to detect selection may be improved. We discuss the theory of genomic analyses to detect selection, identify experimental designs for such analyses, and review studies that have applied these approaches to schistosomes. We then consider the biological characteristics of schistosomes that are expected to respond to selection, particularly those that may be impacted by control programs. Examples include drug resistance, host specificity, and life history traits, and we review our current understanding of specific genes that underlie them in schistosomes. We also discuss how inherent features of schistosome reproduction and demography pose substantial challenges for effective identification of these traits and their genomic bases. We conclude by discussing how genomic surveillance for selection should be designed to improve understanding of schistosome biology, and how the parasite changes in response to selection.

Identification of Signatures of Selection for Litter Size and Pubertal Initiation in Two Sheep Populations

Fecundity is an important economic trait in sheep that directly affects their economic and productive efficiency. Our study aimed to identify SNP loci associated with sheep puberty or litter size which could be used in future breeding programs to improve fertility. Genomic DNA was obtained from Hetian and Cele Black sheep breeds and used for reduced-representation genome sequencing to identify SNP loci associated with pubertal initiation and litter size. Selective signatures analysis was performed based on the fixation index and nucleotide diversity, followed by pathway analysis of the genes contained in the selected regions. The selected SNP loci in the genes associated with pubertal initiation and litter size were validated using both sheep breeds. In total, 384,718 high quality SNPs were obtained and 376 genes were selected. Functional annotation of genes and enrichment analysis identified 12 genes associated with pubertal initiation and 11 genes associated with litter size. SNP locus validation showed that two SNP on PAK1 and four on ADCY1 may be associated with pubertal initiation, and one SNP on GNAQ gene (NC_040253.1: g.62677376G > A) was associated with litter size in Cele Black sheep. Our results provide new theoretical support for sheep breeding.

Identifying signatures of natural selection in Indian populations

In this study, we present the results of a genome-wide scan for signatures of positive selection using data from four tribal groups (Kokana, Warli, Bhil, and Pawara) and two caste groups (Deshastha Brahmin and Kunbi Maratha) from West of the Maharashtra State In India, as well as two samples of South Asian ancestry from the 1KG project (Gujarati Indian from Houston, Texas and Indian Telugu from UK). We used an outlier approach based on different statistics, including PBS, xpEHH, iHS, CLR, Tajima’s D, as well as two recently developed methods: Graph-aware Retrieval of Selective Sweeps (GRoSS) and Ascertained Sequentially Markovian Coalescent (ASMC). In order to minimize the risk of false positives, we selected regions that are outliers in all the samples included in the study using more than one method. We identified putative selection signals in 107 regions encompassing 434 genes. Many of the regions overlap with only one gene. The signals observed using microarray-based data are very consistent with our analyses using high-coverage sequencing data, as well as those identified with a novel coalescence-based method (ASMC). Importantly, at least 24 of these genomic regions have been identified in previous selection scans in South Asian populations or in other population groups. Our study highlights genomic regions that may have played a role in the adaptation of anatomically modern humans to novel environmental conditions after the out of Africa migration.

The evolutionary history and mechanistic basis of female ornamentation in a tropical songbird

Ornamentation, such as the showy plumage of birds, is widespread among female vertebrates, yet the evolutionary pressures shaping female ornamentation remain uncertain. In part this is due to a poor understanding of the mechanistic route to ornamentation in females. To address this issue, we evaluated the evolutionary history of ornament expression in a tropical passerine bird, the White-shouldered Fairywren, whose females, but not males, strongly vary between populations in occurrence of ornamented black-and-white plumage. We first use phylogenomic analysis to demonstrate that female ornamentation is derived and that female ornamentation evolves independently of changes in male plumage. We then use exogenous testosterone in a field experiment to induce partial ornamentation in naturally unornamented females. By sequencing the transcriptome of experimentally induced ornamented and natural feathers, we identify genes expressed during ornament production and evaluate the degree to which female ornamentation in this system is associated with elevated testosterone, as is common in males. We reveal that some ornamentation in females is linked to testosterone and that sexes differ in ornament-linked gene expression. Lastly, using genomic outlier analysis we identify a candidate melanogenesis gene that lies in a region of high genomic divergence among populations that is also differentially expressed in feather follicles of different female plumages. Taken together, these findings are consistent with sex-specific selection favoring the evolution of female ornaments and demonstrate a key role for testosterone in generating population divergence in female ornamentation through gene regulation. More broadly, our work highlights similarities and differences in how ornamentation evolves in the sexes.

Genomic signatures for drylands adaptation at gene-rich regions in African zebu cattle

Background

Indigenous Sudanese cattle are mainly indicine/zebu (humped) type. They thrive in the harshest dryland environments characterised by high temperatures, long seasonal dry periods, nutritional shortages, and vector disease challenges. Here, we sequenced 60 indigenous Sudanese cattle from six indigenous breeds and analysed the data using three genomic scan approaches to unravel cattle adaptation to the African dryland region.

Results

We identified a set of gene-rich selective sweep regions, detected mostly on chromosomes 5, 7 and 19, shared across African and Gir zebu. These include genes involved in immune response, body size and conformation, and heat stress response. We also identified selective sweep regions unique to Sudanese zebu. Of these, a 250 kb selective sweep on chromosome 16 spans seven genes, including PLCH2, PEX10, PRKCZ, and SKI, which are involved in alternative adaptive metabolic strategies of insulin signalling, glucose homeostasis, and fat metabolism.

Conclusions

Our results suggest that environmental adaptation may involve recent and ancient selection at gene-rich regions, which might be under a common regulatory genetic control, in zebu cattle.

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Sudanese cattle thrive in the harshest environments of the African drylands.

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Bos indicus shared selected genes are involved in immune response, conformation, and heat stress response.

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Sudanese zebu-specific sweep includes genes involved in alternative adaptive metabolic strategies of insulin signalling, glucose homeostasis, and fat metabolism.

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Environmental adaptation in zebu cattle may involve recent and ancient selection at gene-rich regions, which might be under a common regulatory genetic control.

Detecting Local Adaptation between North and South European Atlantic Salmon Populations

Pollution and other anthropogenic effects have driven a decrease in Atlantic salmon (Salmo salar) in the Iberian Peninsula. The restocking effort carried out in the 1980s, with salmon from northern latitudes with the aim of mitigating the decline of native populations, failed, probably due to the deficiency in adaptation of foreign salmon from northern Europe to the warm waters of the Iberian Peninsula. This result would imply that the Iberian populations of Atlantic salmon have experienced local adaptation in their past evolutionary history, as has been described for other populations of this species and other salmonids. Local adaptation can occur by divergent selections between environments, favoring the fixation of alleles that increase the fitness of a population in the environment it inhabits relative to other alleles favored in another population. In this work, we compared the genomes of different populations from the Iberian Peninsula (Atlantic and Cantabric basins) and Scotland in order to provide tentative evidence of candidate SNPs responsible for the adaptive differences between populations, which may explain the failures of restocking carried out during the 1980s. For this purpose, the samples were genotyped with a 220,000 high-density SNP array (Affymetrix) specific to Atlantic salmon. Our results revealed potential evidence of local adaptation for North Spanish and Scottish populations. As expected, most differences concerned the comparison of the Iberian Peninsula with Scotland, although there were also differences between Atlantic and Cantabric populations. A high proportion of the genes identified are related to development and cellular metabolism, DNA transcription and anatomical structure. A particular SNP was identified within the NADP-dependent malic enzyme-2 (_mMEP-2*), previously reported by independent studies as a candidate for local adaptation in salmon from the Iberian Peninsula. Interestingly, the corresponding SNP within the _mMEP-2* region was consistent with a genomic pattern of divergent selection.

Clotting factor genes are associated with preeclampsia in high-altitude pregnant women in the Peruvian Andes

Preeclampsia is a multi-organ complication of pregnancy characterized by sudden hypertension and proteinuria that is among the leading causes of preterm delivery and maternal morbidity and mortality worldwide. The heterogeneity of preeclampsia poses a challenge for understanding its etiology and molecular basis. Intriguingly, risk for the condition increases in high-altitude regions such as the Peruvian Andes. To investigate the genetic basis of preeclampsia in a population living at high altitude, we characterized genome-wide variation in a cohort of preeclamptic and healthy Andean families (n = 883) from Puno, Peru, a city located above 3,800 meters of altitude. Our study collected genomic DNA and medical records from case-control trios and duos in local hospital settings. We generated genotype data for 439,314 SNPs, determined global ancestry patterns, and mapped associations between genetic variants and preeclampsia phenotypes. A transmission disequilibrium test (TDT) revealed variants near genes of biological importance for placental and blood vessel function. The top candidate region was found on chromosome 13 of the fetal genome and contains clotting factor genes PROZ, F7, and F10. These findings provide supporting evidence that common genetic variants within coagulation genes play an important role in preeclampsia. A selection scan revealed a potential adaptive signal around the ADAM12 locus on chromosome 10, implicated in pregnancy disorders. Our discovery of an association in a functional pathway relevant to pregnancy physiology in an understudied population of Native American origin demonstrates the increased power of family-based study design and underscores the importance of conducting genetic research in diverse populations.

Machine-Learning Prospects for Detecting Selection Signatures Using Population Genomics Data

Natural selection has been given a lot of attention because it relates to the adaptation of populations to their environments, both biotic and abiotic. An allele is selected when it is favored by natural selection. Consequently, the favored allele increases in frequency in the population and neighboring linked variation diminishes, causing so-called selective sweeps. A high-throughput genomic sequence allows one to disentangle the evolutionary forces at play in populations. With the development of high-throughput genome sequencing technologies, it has become easier to detect these selective sweeps/selection signatures. Various methods can be used to detect selective sweeps, from simple implementations using summary statistics to complex statistical approaches. One of the important problems of these statistical models is the potential to provide inaccurate results when their assumptions are violated. The use of machine learning (ML) in population genetics has been introduced as an alternative method of detecting selection by treating the problem of detecting selection signatures as a classification problem. Since the availability of population genomics data is increasing, researchers may incorporate ML into these statistical models to infer signatures of selection with higher predictive accuracy and better resolution. This article describes how ML can be used to aid in detecting and studying natural selection patterns using population genomic data.

Detecting selection using extended haplotype homozygosity (EHH)-based statistics in unphased or unpolarized data

Analysis of population genetic data often includes a search for genomic regions with signs of recent positive selection. One of such approaches involves the concept of extended haplotype homozygosity (EHH) and its associated statistics. These statistics typically require phased haplotypes, and some of them necessitate polarized variants. Here, we unify and extend previously proposed modifications to loosen these requirements. We compare the modified versions with the original ones by measuring the false discovery rate in simulated whole-genome scans and by quantifying the overlap of inferred candidate regions in empirical data. We find that phasing information is indispensable for accurate estimation of within-population statistics (for all but very large samples) and of cross-population statistics for small samples. Ancestry information, in contrast, is of lesser importance for both types of statistic. Our publicly available R package rehh incorporates the modified statistics presented here.

Genetic diversity and selection in Puerto Rican horses

Since the first Spanish settlers brought horses to America centuries ago, several local varieties and breeds have been established in the New World. These were generally a consequence of the admixture of the different breeds arriving from Europe. In some instances, local horses have been selectively bred for specific traits, such as appearance, endurance, strength, and gait. We looked at the genetics of two breeds, the Puerto Rican Non-Purebred (PRNPB) (also known as the "Criollo") horses and the Puerto Rican Paso Fino (PRPF), from the Caribbean Island of Puerto Rico. While it is reasonable to assume that there was a historic connection between the two, the genetic link between them has never been established. In our study, we started by looking at the genetic ancestry and diversity of current Puerto Rican horse populations using a 668 bp fragment of the mitochondrial DNA D-loop (HVR1) in 200 horses from 27 locations on the island. We then genotyped all 200 horses in our sample for the "gait-keeper" DMRT3 mutant allele previously associated with the paso gait especially cherished in this island breed. We also genotyped a subset of 24 samples with the Illumina Neogen Equine Community genome-wide array (65,000 SNPs). This data was further combined with the publicly available PRPF genomes from other studies. Our analysis show an undeniable genetic connection between the two varieties in Puerto Rico, consistent with the hypothesis that PRNPB horses represent the descendants of the original genetic pool, a mix of horses imported from the Iberian Peninsula and elsewhere in Europe. Some of the original founders of PRNRB population must have carried the "gait-keeper" DMRT3 allele upon arrival to the island. From this admixture, the desired traits were selected by the local people over the span of centuries. We propose that the frequency of the mutant "gait-keeper" allele originally increased in the local horses due to the selection for the smooth ride and other characters, long before the PRPF breed was established. To support this hypothesis, we demonstrate that PRNPB horses, and not the purebred PRPF, carry a signature of selection in the genomic region containing the DMRT3 locus to this day. The lack of the detectable signature of selection associated with the DMRT3 in the PRPF would be expected if this native breed was originally derived from the genetic pool of PRNPB horses established earlier and most of the founders already had the mutant allele. Consequently, selection specific to PRPF later focused on allels in other genes (including CHRM5, CYP2E1, MYH7, SRSF1, PAM, PRN and others) that have not been previously associated with the prized paso gait phenotype in Puerto Rico or anywhere else.

Contrasting gene-level signatures of selection with reproductive fitness

Selection leaves signatures in the DNA sequence of genes, with many test statistics devised to detect its action. While these statistics are frequently used to support hypotheses about the adaptive significance of particular genes, the effect these genes have on reproductive fitness is rarely quantified experimentally. Consequently, it is unclear how gene-level signatures of selection are associated with empirical estimates of gene effect on fitness. Eukaryotic datasets that permit this comparison are very limited. Using the model plant Arabidopsis thaliana, for which these resources are available, we calculated seven gene-level substitution and polymorphism-based statistics commonly used to infer selection (dN/dS, NI, DOS, Tajima's D, Fu and Li's D*, Fay and Wu's H, and Zeng's E) and, using knockout lines, compared these to gene-level estimates of effect on fitness. We found that consistent with expectations, essential genes were more likely to be classified as negatively selected. By contrast, using 379 Arabidopsis genes for which data was available, we found no evidence that genes predicted to be positively selected had a significantly different effect on fitness than genes evolving more neutrally. We discuss these results in the context of the analytic challenges posed by Arabidopsis, one of the only systems in which this study could be conducted, and advocate for examination in additional systems. These results are relevant to the evaluation of genome-wide studies across species where experimental fitness data is unavailable, as well as highlighting an increasing need for the latter.

Identifying loci under selection via explicit demographic models

Adaptive genetic variation is a function of both selective and neutral forces. To accurately identify adaptive loci, it is thus critical to account for demographic history. Theory suggests that signatures of selection can be inferred using the coalescent, following the premise that genealogies of selected loci deviate from neutral expectations. Here, we build on this theory to develop an analytical framework to identify loci under selection via explicit demographic models (LSD). Under this framework, signatures of selection are inferred through deviations in demographic parameters, rather than through summary statistics directly, and demographic history is accounted for explicitly. Leveraging the property of demographic models to incorporate directionality, we show that LSD can provide information on the environment in which selection acts on a population. This can prove useful in elucidating the selective processes underlying local adaptation, by characterizing genetic trade-offs and extending the concepts of antagonistic pleiotropy and conditional neutrality from ecological theory to practical application in genomic data. We implement LSD via approximate Bayesian computation and demonstrate, via simulations, that LSD (a) has high power to identify selected loci across a large range of demographic-selection regimes, (b) outperforms commonly applied genome-scan methods under complex demographies and (c) accurately infers the directionality of selection for identified candidates. Using the same simulations, we further characterize the behaviour of isolation-with-migration models conducive to the study of local adaptation under regimes of selection. Finally, we demonstrate an application of LSD by detecting loci and characterizing genetic trade-offs underlying flower colour in Antirrhinum majus.

Taxonomy, Evolutionary and Dispersal Events of Pig-Tailed Macaque, Macaca nemestrina (Linnaeus, 1766) in Southeast Asia with Description of a New Subspecies, Macaca nemestrina perakensis in Malaysia

The pig-tailed macaque, Macaca nemestrina, which is distributed in Peninsular Malaysia, Thailand, Borneo, and Sumatra, has been the subject of unstable and changing taxonomic entity in the M. nemestrina group. This species is involved with a human-macaque conflict in Malaysia and at the same time played an important role in the ethnozoological culture of Malaysian. Even so, comprehensive phylogenetic, population genetics and biogeographical analysis of M. nemestrina in Malaysia are non-existent after decades of intensive research on the genus itself. Thus, we conducted the first comprehensive genetic study of M. nemestrina in Malaysia, based on three mitochondrial loci-Cytochrome b (567 bp), D-loop (398 bp), and COI (577 bp)-from 27 individuals representing Malaysia, plus an additional 26 sequences of Southeast Asian macaques from Genbank. Comparative biogeographical analysis in this study supports the positions of M. nemestrina in M. nemestrina groups as opposed to the silenus or Sulawesi groups. Results from this study also indicate that Bornean populations are the first extant lineages to separate from the other examined lineages of M. nemestrina, M. leonina, M. pagensis, and M. siberu in Southeast Asia. Molecular clock analysis suggested that M. nemestrina arrived in the Malay Peninsula about 0.32 million years ago (MYA). Our results indicate that the population of pig-tailed macaque from Perak (west Peninsular Malaysia) differs genetically based on all phylogenetic and population genetic analyses. Morphologically, Perak's pig-tailed macaque shows brighter coloration than M. n. nemestrina. Thus, we proposed a new subspecies for Perak's pig-tailed macaque as Macaca nemestrina perakensis distributed in the state of Perak, Peninsular Malaysia. This research helps resolve the taxonomic position and population genetics of pig-tailed macaque in Malaysia, which contribute directly to conservation and management of the species in Malaysia.

Chromosome-Level Genome Assemblies Expand Capabilities of Genomics for Conservation Biology

Genome assemblies are in the process of becoming an increasingly important tool for understanding genetic diversity in threatened species. Unfortunately, due to limited budgets typical for the area of conservation biology, genome assemblies of threatened species, when available, tend to be highly fragmented, represented by tens of thousands of scaffolds not assigned to chromosomal locations. The recent advent of high-throughput chromosome conformation capture (Hi-C) enables more contiguous assemblies containing scaffolds spanning the length of entire chromosomes for little additional cost. These inexpensive contiguous assemblies can be generated using Hi-C scaffolding of existing short-read draft assemblies, where N50 of the draft contigs is larger than 0.1% of the estimated genome size and can greatly improve analyses and facilitate visualization of genome-wide features including distribution of genetic diversity in markers along chromosomes or chromosome-length scaffolds. We compared distribution of genetic diversity along chromosomes of eight mammalian species, including six listed as threatened by IUCN, where both draft genome assemblies and newer chromosome-level assemblies were available. The chromosome-level assemblies showed marked improvement in localization and visualization of genetic diversity, especially where the distribution of low heterozygosity across the genomes of threatened species was not uniform.

Genetic composition and evolution of the prevalent Mycobacterium tuberculosis lineages 2 and 4 in the Chinese and Zhejiang Province populations

Background

There are seven human-adaptation lineages of Mycobacterium tuberculosis (Mtb). Tuberculosis (TB) dissemination is strongly influenced by human movements and host genetics. The detailed lineage distribution evolution of Mtb in Zhejiang Province is unknown. We aim to determine how different sub-lineages are transmitted and distributed within China and Zhejiang Province.

Methods

We analysed whole-genome sequencing data for a worldwide collection of 1154 isolates and a provincial collection of 1296 isolates, constructed the best-scoring maximum likelihood phylogenetic tree. Bayesian evolutionary analysis was used to calculate the latest common ancestor of lineages 2 and 4. The antigenic diversity of human T cell epitopes was evaluated by calculating the pairwise dN/dS ratios.

Results

Of the Zhejiang isolates, 964 (74.38%) belonged to lineage 2 and 332 (25.62%) belonged to lineage 4. The distributions of the sub-lineages varied across the geographic regions of Zhejiang Province. L2.2 is the most ancient sub-lineage in Zhejiang, first appearing approximately 6897 years ago (95% highest posterior density interval (HDI): 6513–7298). L4.4 is the most modern sub-lineage, first appearing approximately 2217 years ago (95% HDI: 1864–2581). The dN/dS ratios showed that the epitope and non-epitope regions of lineage 2 strains were significantly (P < 0.001) more conserved than those of lineage 4.

Conclusions

An increase in the frequency of lineage 4 may reflect its successful transmission over the last 20 years. The recent common ancestors of the sub-lineages and their transmission routes are relevant to the entry of humans into China and Zhejiang Province. Diversity in T cell epitopes may prevent Mycobacterium tuberculosis from being recognized by the immune system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-021-00673-7.

De Novo Mutation and Rapid Protein (Co-)evolution during Meiotic Adaptation in Arabidopsis arenosa

A sudden shift in environment or cellular context necessitates rapid adaptation. A dramatic example is genome duplication, which leads to polyploidy. In such situations, the waiting time for new mutations might be prohibitive; theoretical and empirical studies suggest that rapid adaptation will largely rely on standing variation already present in source populations. Here, we investigate the evolution of meiosis proteins in Arabidopsis arenosa, some of which were previously implicated in adaptation to polyploidy, and in a diploid, habitat. A striking and unexplained feature of prior results was the large number of amino acid changes in multiple interacting proteins, especially in the relatively young tetraploid. Here, we investigate whether selection on meiosis genes is found in other lineages, how the polyploid may have accumulated so many differences, and whether derived variants were selected from standing variation. We use a range-wide sample of 145 resequenced genomes of diploid and tetraploid A. arenosa, with new genome assemblies. We confirmed signals of positive selection in the polyploid and diploid lineages they were previously reported in and find additional meiosis genes with evidence of selection. We show that the polyploid lineage stands out both qualitatively and quantitatively. Compared with diploids, meiosis proteins in the polyploid have more amino acid changes and a higher proportion affecting more strongly conserved sites. We find evidence that in tetraploids, positive selection may have commonly acted on de novo mutations. Several tests provide hints that coevolution, and in some cases, multinucleotide mutations, might contribute to rapid accumulation of changes in meiotic proteins.

Genome-Wide Scanning for Signatures of Selection Revealed the Putative Genomic Regions and Candidate Genes Controlling Milk Composition and Coat Color Traits in Sahiwal Cattle

Background

In the evolutionary time scale, selection shapes the genetic variation and alters the architecture of genome in the organisms. Selection leaves detectable signatures at the genomic coordinates that provide clues about the protein-coding regions. Sahiwal is a valuable indicine cattle adapted to tropical environments with desirable milk attributes. Insights into the genomic regions under putative selection may reveal the molecular mechanisms affecting the quantitative and other important traits. To understand this, the present investigation was undertaken to explore signatures of selection in the genome of Sahiwal cattle using a medium-density genotyping INDUS chip.

Result

De-correlated composite of multiple selection signals (DCMS), which combines five different univariate statistics, was computed in the dataset to detect the signatures of selection in the Sahiwal genome. Gene annotations, Quantitative Trait Loci (QTL) enrichment, and functional analyses were carried out for the identification of significant genomic regions. A total of 117 genes were identified, which affect a number of important economic traits. The QTL enrichment analysis highlighted 14 significant [False Discovery Rate (FDR)-corrected p-value ≤ 0.05] regions on chromosomes BTA 1, 3, 6, 11, 20, and 21. The top three enriched QTLs were found on BTA 6, 20, and 23, which are associated with exterior, health, milk production, and reproduction traits. The present study on selection signatures revealed some key genes related with coat color (PDGFRA, KIT, and KDR), facial pigmentation (LEF), milk fat percent (MAP3K1, HADH, CYP2U1, and SGMS2), sperm membrane integrity (OSTC), lactation persistency (MRPS30, NNT, CCL28, HMGCS1, NIM1K, ZNF131, and CCDC152), milk yield (GHR and ZNF469), reproduction (NKX2-1 and DENND1A), and bovine tuberculosis susceptibility (RNF144B and PAPSS1). Further analysis of candidate gene prioritization identified four hub genes, viz., KIT, KDR, MAP3K1, and LEF, which play a role in coat color, facial pigmentation, and milk fat percentage in cattle. Gene enrichment analysis revealed significant Gene ontology (GO) terms related to breed-specific coat color and milk fat percent.

Conclusion

The key candidate genes and putative genomic regions associated with economic traits were identified in Sahiwal using single nucleotide polymorphism data and the DCMS method. It revealed selection for milk production, coat color, and adaptability to tropical climate. The knowledge about signatures of selection and candidate genes affecting phenotypes have provided a background information that can be further utilized to understand the underlying mechanism involved in these traits in Sahiwal cattle.

Adaptive evolution of Moniliophthora PR-1 proteins towards its pathogenic lifestyle

BACKGROUND

Plant pathogenesis related-1 (PR-1) proteins belong to the CAP superfamily and have been characterized as markers of induced defense against pathogens. Moniliophthora perniciosa and Moniliophthora roreri are hemibiotrophic fungi that respectively cause the witches' broom disease and frosty pod rot in Theobroma cacao. Interestingly, a large number of plant PR-1-like genes are present in the genomes of both species and many are up-regulated during the biotrophic interaction. In this study, we investigated the evolution of PR-1 proteins from 22 genomes of Moniliophthora isolates and 16 other Agaricales species, performing genomic investigation, phylogenetic reconstruction, positive selection search and gene expression analysis.

RESULTS

Phylogenetic analysis revealed conserved PR-1 genes (PR-1a, b, d, j), shared by many Agaricales saprotrophic species, that have diversified in new PR-1 genes putatively related to pathogenicity in Moniliophthora (PR-1f, g, h, i), as well as in recent specialization cases within M. perniciosa biotypes (PR-1c, k, l) and M. roreri (PR-1n). PR-1 families in Moniliophthora with higher evolutionary rates exhibit induced expression in the biotrophic interaction and positive selection clues, supporting the hypothesis that these proteins accumulated adaptive changes in response to host-pathogen arms race. Furthermore, although previous work showed that MpPR-1 can detoxify plant antifungal compounds in yeast, we found that in the presence of eugenol M. perniciosa differentially expresses only MpPR-1e, k, d, of which two are not linked to pathogenicity, suggesting that detoxification might not be the main function of most MpPR-1.

CONCLUSIONS

Based on analyses of genomic and expression data, we provided evidence that the evolution of PR-1 in Moniliophthora was adaptive and potentially related to the emergence of the parasitic lifestyle in this genus. Additionally, we also discuss how fungal PR-1 proteins could have adapted from basal conserved functions to possible roles in fungal pathogenesis.

Detection of selection signatures in farmed coho salmon (Oncorhynchus kisutch) using dense genome-wide information

Animal domestication and artificial selection give rise to gradual changes at the genomic level in populations. Subsequent footprints of selection, known as selection signatures or selective sweeps, have been traced in the genomes of many animal livestock species by exploiting variation in linkage disequilibrium patterns and/or reduction of genetic diversity. Domestication of most aquatic species is recent in comparison with land animals, and salmonids are one of the most important fish species in aquaculture. Coho salmon (Oncorhynchus kisutch), cultivated primarily in Chile, has been subjected to breeding programs to improve growth, disease resistance traits, and flesh color. This study aimed to identify selection signatures that may be involved in adaptation to culture conditions and traits of productive interest. To do so, individuals of two domestic populations cultured in Chile were genotyped with 200 thousand SNPs, and analyses were conducted using iHS, XP-EHH and CLR. Several signatures of selection on different chromosomal regions were detected across both populations. Some of the identified regions under selection contained genes such anapc2, alad, chp2 and myn, which have been previously associated with body weight in Atlantic salmon, or sec24d and robo1, which have been associated with resistance to Piscirickettsia salmonis in coho salmon. Findings in our study can contribute to an integrated genome-wide map of selection signatures, to help identify the genetic mechanisms of phenotypic diversity in coho salmon.

Molecular Phylogeny and Evolution of Amazon Parrots in the Greater Antilles

Amazon parrots (Amazona spp.) colonized the islands of the Greater Antilles from the Central American mainland, but there has not been a consensus as to how and when this happened. Today, most of the five remaining island species are listed as endangered, threatened, or vulnerable as a consequence of human activity. We sequenced and annotated full mitochondrial genomes of all the extant Amazon parrot species from the Greater Antillean (A. leucocephala (Cuba), A. agilis, A. collaria (both from Jamaica), A. ventralis (Hispaniola), and A. vittata (Puerto Rico)), A. albifrons from mainland Central America, and A. rhodocorytha from the Atlantic Forest in Brazil. The assembled and annotated mitogenome maps provide information on sequence organization, variation, population diversity, and evolutionary history for the Caribbean species including the critically endangered A. vittata. Despite the larger number of available samples from the Puerto Rican Parrot Recovery Program, the sequence diversity of the A. vittata population in Puerto Rico was the lowest among all parrot species analyzed. Our data support the stepping-stone dispersal and speciation hypothesis that has started approximately 3.47 MYA when the ancestral population arrived from mainland Central America and led to diversification across the Greater Antilles, ultimately reaching the island of Puerto Rico 0.67 MYA. The results are presented and discussed in light of the geological history of the Caribbean and in the context of recent parrot evolution, island biogeography, and conservation. This analysis contributes to understating evolutionary history and empowers subsequent assessments of sequence variation and helps design future conservation efforts in the Caribbean.

Detecting genetic signals of selection in heavily bottlenecked reindeer populations by comparing parallel founder events

Founder populations are of special interest to both evolutionary and conservation biologists, but the detection of genetic signals of selection in these populations is challenging due to their demographic history. Geographically separated founder populations likely to have been subjected to similar selection pressures provide an ideal but rare opportunity to overcome these challenges. Here we take advantage of such a situation generated when small, isolated founder populations of reindeer were established on the island of South Georgia, and using this system we look for empirical evidence of selection overcoming strong genetic drift. We generated a 70 k ddRADseq single nucleotide polymorphism database for the two parallel reindeer founder populations and screened for signatures of soft sweeps. We find evidence for a genomic region under selection shared among the two populations, and support our findings with Wright-Fisher model simulations to assess the power and specificity of interpopulation selection scans-namely Bayescan, OutFLANK, PCadapt and a newly developed scan called Genome Wide Differentiation Scan (GWDS)-in the context of pairwise source-founder comparisons. Our simulations indicate that loci under selection in small founder populations are most probably detected by GWDS, and strengthen the hypothesis that the outlier region represents a true locus under selection. We explore possible, relevant functional roles for genes in linkage with the detected outlier loci.

Genetic Diversity and Signatures of Selection for Thermal Stress in Cattle and Other Two Bos Species Adapted to Divergent Climatic Conditions

Understanding the biological mechanisms of climatic adaptation is of paramount importance for the optimization of breeding programs and conservation of genetic resources. The aim of this study was to investigate genetic diversity and unravel genomic regions potentially under selection for heat and/or cold tolerance in thirty-two worldwide cattle breeds, with a focus on Chinese local cattle breeds adapted to divergent climatic conditions, Datong yak (Bos grunniens; YAK), and Bali (Bos javanicus) based on dense SNP data. In general, moderate genetic diversity levels were observed in most cattle populations. The proportion of polymorphic SNP ranged from 0.197 (YAK) to 0.992 (Mongolian cattle). Observed and expected heterozygosity ranged from 0.023 (YAK) to 0.366 (Sanhe cattle; SH), and from 0.021 (YAK) to 0.358 (SH), respectively. The overall average inbreeding (±SD) was: 0.118 ± 0.028, 0.228 ± 0.059, 0.194 ± 0.041, and 0.021 ± 0.004 based on the observed versus expected number of homozygous genotypes, excess of homozygosity, correlation between uniting gametes, and runs of homozygosity (ROH), respectively. Signatures of selection based on multiple scenarios and methods (F ST, HapFLK, and ROH) revealed important genomic regions and candidate genes. The candidate genes identified are related to various biological processes and pathways such as heat-shock proteins, oxygen transport, anatomical traits, mitochondrial DNA maintenance, metabolic activity, feed intake, carcass conformation, fertility, and reproduction. This highlights the large number of biological processes involved in thermal tolerance and thus, the polygenic nature of climatic resilience. A comprehensive description of genetic diversity measures in Chinese cattle and YAK was carried out and compared to 24 worldwide cattle breeds to avoid potential biases. Numerous genomic regions under positive selection were detected using three signature of selection methods and candidate genes potentially under positive selection were identified. Enriched function analyses pinpointed important biological pathways, molecular function and cellular components, which contribute to a better understanding of the biological mechanisms underlying thermal tolerance in cattle. Based on the large number of genomic regions identified, thermal tolerance has a complex polygenic inheritance nature, which was expected considering the various mechanisms involved in thermal stress response.

Genomic scans for selective sweeps through haplotype homozygosity and allelic fixation in 14 indigenous sheep breeds from Middle East and South Asia

The performance and productivity of livestock have consistently improved by natural and artificial selection over the centuries. Both these selections are expected to leave patterns on the genome and lead to changes in allele frequencies, but natural selection has played the major role among indigenous populations. Detecting selective sweeps in livestock may assist in understanding the processes involved in domestication, genome evolution and discovery of genomic regions associated with economically important traits. We investigated population genetic diversity and selection signals in this study using SNP genotype data of 14 indigenous sheep breeds from Middle East and South Asia, including six breeds from Iran, namely Iranian Balochi, Afshari, Moghani, Qezel, Zel, and Lori-Bakhtiari, three breeds from Afghanistan, namely Afghan Balochi, Arabi, and Gadik, three breeds from India, namely Indian Garole, Changthangi, and Deccani, and two breeds from Bangladesh, namely Bangladeshi Garole and Bangladesh East. The SNP genotype data were generated by the Illumina OvineSNP50 Genotyping BeadChip array. To detect genetic diversity and population structure, we used principal component analysis (PCA), admixture, phylogenetic analyses, and Runs of homozygosity. We applied four complementary statistical tests, FST (fixation index), xp-EHH (cross-population extended haplotype homozygosity), Rsb (extended haplotype homozygosity between-populations), and FLK (the extension of the Lewontin and Krakauer) to detect selective sweeps. Our results not only confirm the previous studies but also provide a suite of novel candidate genes involved in different traits in sheep. On average, FST, xp-EHH, Rsb, and FLK detected 128, 207, 222, and 252 genomic regions as candidates for selective sweeps, respectively. Furthermore, nine overlapping candidate genes were detected by these four tests, especially TNIK, DOCK1, USH2A, and TYW1B which associate with resistance to diseases and climate adaptation. Knowledge of candidate genomic regions in sheep populations may facilitate the identification and potential exploitation of the underlying genes in sheep breeding.

Breed Ancestry, Divergence, Admixture, and Selection Patterns of the Simbra Crossbreed

In this study, we evaluated an admixed South African Simbra crossbred population, as well as the Brahman (Indicine) and Simmental (Taurine) ancestor populations to understand their genetic architecture and detect genomic regions showing signatures of selection. Animals were genotyped using the Illumina BovineLD v2 BeadChip (7K). Genomic structure analysis confirmed that the South African Simbra cattle have an admixed genome, composed of 5/8 Taurine and 3/8 Indicine, ensuring that the Simbra genome maintains favorable traits from both breeds. Genomic regions that have been targeted by selection were detected using the linkage disequilibrium-based methods iHS and Rsb. These analyses identified 10 candidate regions that are potentially under strong positive selection, containing genes implicated in cattle health and production (e.g., TRIM63, KCNA10, NCAM1, SMIM5, MIER3, and SLC24A4). These adaptive alleles likely contribute to the biological and cellular functions determining phenotype in the Simbra hybrid cattle breed. Our data suggested that these alleles were introgressed from the breed's original indicine and taurine ancestors. The Simbra breed thus possesses derived parental alleles that combine the superior traits of the founder Brahman and Simmental breeds. These regions and genes might represent good targets for ad-hoc physiological studies, selection of breeding material and eventually even gene editing, for improved traits in modern cattle breeds. This study represents an important step toward developing and improving strategies for selection and population breeding to ultimately contribute meaningfully to the beef production industry.

Genetic Structure and Evolutionary History of Rhinopithecus roxellana in Qinling Mountains, Central China

The Qinling mountainous region is one of the world's biodiversity hotspots and provides refuges for many endangered endemic animals. The golden snub-nosed monkeys (Rhinopithecus roxellana) are considered as a flagship species in this area. Here, we depicted the genetic structure and evolutionary history via microsatellite markers and combination with the ecological niche models (ENMs) to elucidate the intraspecific divergent and the impacts of the population demography on our focal species. Our results revealed three distinct subpopulations of R. roxellana and also uncovered asymmetric historical and symmetric contemporary gene flow that existed. Our evolutionary dynamics analyses based on diyabc suggested that the intraspecific divergence accompanied with effective population sizes changes. The ENM result implied that the distribution range of this species experienced expansion during the last glacial maximum (LGM). Our results highlighted that geological factors could contribute to the high genetic differentiation within the R. roxellana in the Qinling Mountains. We also provided a new insight into conservation management plans with endangered species in this region.

A selection signatures study among Middle Eastern and European sheep breeds

Selection, both natural and artificial, leaves patterns on the genome during domestication of animals and leads to changes in allele frequencies among populations. Detecting genomic regions influenced by selection in livestock may assist in understanding the processes involved in genome evolution and discovering genomic regions related to traits of economic and ecological interests. In the current study, genetic diversity analyses were conducted on 34,206 quality-filtered SNP positions from 450 individuals in 15 sheep breeds, including six indigenous breeds from the Middle East, namely Iranian Balouchi, Afshari, Moghani, Qezel, Karakas and Norduz, and nine breeds from Europe, namely East Friesian Sheep, Ile de France, Mourerous, Romane, Swiss Mirror, Spaelsau, Suffolk, Comisana and Engadine Red Sheep. The SNP genotype data generated by the Illumina OvineSNP50 Genotyping BeadChip array were used in this analysis. We applied two complementary statistical analyses, F_ST (fixation index) and xp-EHH (cross-population extended haplotype homozygosity), to detect selection signatures in Middle Eastern and European sheep populations. F_ST and xp-EHH detected 629 and 256 genes indicating signatures of selection, respectively. Genomic regions identified using F_ST and xp-EHH contained the CIDEA, HHATL, MGST1, FADS1, RTL1 and DGKG genes, which were reported earlier to influence a number of economic traits. Both F_ST and xp-EHH approaches identified 60 shared genes as the signatures of selection, including four candidate genes (NT5E, ADA2, C8A and C8B) that were enriched for two significant Gene Ontology (GO) terms associated with the adenosine metabolic procedure. Knowledge about the candidate genomic regions under selective pressure in sheep breeds may facilitate identification of the underlying genes and enhance our understanding on these genes role in local adaptation.

Whose trait is it anyways? Coevolution of joint phenotypes and genetic architecture in mutualisms

Evolutionary biologists typically envision a trait's genetic basis and fitness effects occurring within a single species. However, traits can be determined by and have fitness consequences for interacting species, thus evolving in multiple genomes. This is especially likely in mutualisms, where species exchange fitness benefits and can associate over long periods of time. Partners may experience evolutionary conflict over the value of a multi-genomic trait, but such conflicts may be ameliorated by mutualism's positive fitness feedbacks. Here, we develop a simulation model of a host-microbe mutualism to explore the evolution of a multi-genomic trait. Coevolutionary outcomes depend on whether hosts and microbes have similar or different optimal trait values, strengths of selection and fitness feedbacks. We show that genome-wide association studies can map joint traits to loci in multiple genomes and describe how fitness conflict and fitness feedback generate different multi-genomic architectures with distinct signals around segregating loci. Partner fitnesses can be positively correlated even when partners are in conflict over the value of a multi-genomic trait, and conflict can generate strong mutualistic dependency. While fitness alignment facilitates rapid adaptation to a new optimum, conflict maintains genetic variation and evolvability, with implications for applied microbiome science.

Genome diversity in Ukraine

Background

The main goal of this collaborative effort is to provide genome-wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for public data release. BGISEQ-500 sequence data and genotypes by an Illumina GWAS chip were cross-validated on multiple samples and additionally referenced to 1 sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage.

Results

The genome data have been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, copy number variations, single-nucletide polymorphisms, and microsatellites. To our knowledge, this study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for medical research in a large understudied population.

Conclusions

Our results indicate that the genetic diversity of the Ukrainian population is uniquely shaped by evolutionary and demographic forces and cannot be ignored in future genetic and biomedical studies. These data will contribute a wealth of new information bringing forth a wealth of novel, endemic and medically related alleles.