Allele frequency dynamics in a pedigreed natural population

To Prosper, Live Long: Understanding the Sources of Reproductive Skew and Extreme Reproductive Success in Structured Populations

AbstractIn many species, a few individuals produce most of the next generation. How much of this reproductive skew is driven by variation among individuals in fixed traits, how much by external factors, and how much by random chance? And what does it take to have truly exceptional lifetime reproductive output (LRO)? In the past, we and others have partitioned the variance of LRO as a proxy for reproductive skew. Here we explain how to partition LRO skewness itself into contributions from fixed trait variation, four forms of "demographic luck" (birth state, fecundity luck, survival trajectory luck, and growth trajectory luck), and two kinds of "environmental luck" (birth environment and environment trajectory). Each of these is further partitioned into contributions at different ages. We also determine what we can infer about individuals with exceptional LRO. We find that reproductive skew is largely driven by random variation in lifespan, and exceptional LRO generally results from exceptional lifespan. Other kinds of luck frequently bring skewness down rather than increasing it. In populations where fecundity varies greatly with environmental conditions, getting a good year at the right time can be an alternate route to exceptional LRO, so that LRO is less predictive of lifespan.

Allele frequency dynamics under sex-biased demography and sex-specific inheritance in a pedigreed jay population

Sex-biased demography, including sex-biased survival or migration, can alter allele frequency changes across the genome. In particular, we can expect different patterns of genetic variation on autosomes and sex chromosomes due to sex-specific differences in life histories, as well as differences in effective population size, transmission modes, and the strength and mode of selection. Here, we demonstrate the role that sex differences in life history played in shaping short-term evolutionary dynamics across the genome. We used a 25-year pedigree and genomic dataset from a long-studied population of Florida Scrub-Jays (Aphelocoma coerulescens) to directly characterize the relative roles of sex-biased demography and inheritance in shaping genome-wide allele frequency trajectories. We used gene dropping simulations to estimate individual genetic contributions to future generations and to model drift and immigration on the known pedigree. We quantified differential expected genetic contributions of males and females over time, showing the impact of sex-biased dispersal in a monogamous system. Due to female-biased dispersal, more autosomal variation is introduced by female immigrants. However, due to male-biased transmission, more Z variation is introduced by male immigrants. Finally, we partitioned the proportion of variance in allele frequency change through time due to male and female contributions. Overall, most allele frequency change is due to variance in survival and births. Males and females make similar contributions to autosomal allele frequency change, but males make higher contributions to allele frequency change on the Z chromosome. Our work shows the importance of understanding sex-specific demographic processes in characterizing genome-wide allele frequency change in wild populations.

Impacts of increasing isolation and environmental variation on Florida Scrub-Jay demography

Isolation caused by anthropogenic habitat fragmentation can destabilize populations. Populations relying on the inflow of immigrants can face reduced fitness due to inbreeding depression as fewer new individuals arrive. Empirical studies of the demographic consequences of isolation are critical to understand how populations persist through changing conditions. We used a 34-year demographic and environmental dataset from a population of cooperatively-breeding Florida Scrub-Jays ( Aphelocoma coerulescens ) to create mechanistic models linking environmental and demographic factors to population growth rates. We found that the population has not declined despite both declining immigration and increasing inbreeding, owing to a coinciding response in breeder survival. We find evidence of density-dependent immigration, breeder survival, and fecundity, indicating that interactions between vital rates and local density play a role in buffering the population against change. Our study elucidates the impacts of isolation on demography and how long-term stability is maintained via demographic responses.

A new approach to geostatistical synthesis of historical records reveals capuchin spatial responses to climate and demographic change

Recent proliferation of GPS technology has transformed animal movement research. Yet, time-series data from this recent technology rarely span beyond a decade, constraining longitudinal research. Long-term field sites hold valuable historic animal location records, including hand-drawn maps and semantic descriptions. Here, we introduce a generalised workflow for converting such records into reliable location data to estimate home ranges, using 30 years of sleep-site data from 11 white-faced capuchin (Cebus imitator) groups in Costa Rica. Our findings illustrate that historic sleep locations can reliably recover home range size and geometry. We showcase the opportunity our approach presents to resolve open questions that can only be addressed with very long-term data, examining how home ranges are affected by climate cycles and demographic change. We urge researchers to translate historical records into usable movement data before this knowledge is lost; it is essential to understanding how animals are responding to our changing world.

Mapping QTL associated with resistance to Pseudomonas syringae pv. actinidiae in kiwifruit (Actinidia chinensis var. chinensis)

Pseudomonas syringae pv. actinidiae (Psa) is a bacterial pathogen of kiwifruit. This pathogen causes leaf-spotting, cane dieback, wilting, cankers (lesions), and in severe cases, plant death. Families of diploid A. chinensis seedlings grown in the field show a range of susceptibilities to the disease with up to 100% of seedlings in some families succumbing to Psa. But the effect of selection for field resistance to Psa on the alleles that remain in surviving seedlings has not been assessed. The objective of this work was to analyse, the effect of plant removal from Psa on the allele frequency of an incomplete-factorial-cross population. This population was founded using a range of genotypically distinct diploid A. chinensis var. chinensis parents to make 28 F1 families. However, because of the diversity of these families, low numbers of surviving individuals, and a lack of samples from dead individuals, standard QTL mapping approaches were unlikely to yield good results. Instead, a modified bulk segregant analysis (BSA) overcame these drawbacks while reducing the costs of sampling and sample processing, and the complexity of data analysis. Because the method was modified, part one of this work was used to determine the signal strength required for a QTL to be detected with BSA. Once QTL detection accuracy was known, part two of this work analysed the 28 families from the incomplete-factorial-cross population that had multiple individuals removed due to Psa infection. Each family was assigned to one of eight bulks based on a single parent that contributed to the families. DNA was extracted in bulk by grinding sampled leaf discs together before DNA extraction. Each sample bulk was compared against a bulk made up of WGS data from the parents contributing to the sample bulk. The deviation in allele frequency from the expected allele frequency within surviving populations using the modified BSA method was able to identify 11 QTLs for Psa that were present in at least two analyses. The identification of these Psa resistance QTL will enable marker development to selectively breed for resistance to Psa in future kiwifruit breeding programs.

Multi-generation genetic contributions of immigrants reveal cryptic elevated and sex-biased effective gene flow within a natural meta-population

Impacts of immigration on micro-evolution and population dynamics fundamentally depend on net rates and forms of resulting gene flow into recipient populations. Yet, the degrees to which observed rates and sex ratios of physical immigration translate into multi-generational genetic legacies have not been explicitly quantified in natural meta-populations, precluding inference on how movements translate into effective gene flow and eco-evolutionary outcomes. Our analyses of three decades of complete song sparrow (Melospiza melodia) pedigree data show that multi-generational genetic contributions from regular natural immigrants substantially exceeded those from contemporary natives, consistent with heterosis-enhanced introgression. However, while contributions from female immigrants exceeded those from female natives by up to three-fold, male immigrants' lineages typically went locally extinct soon after arriving. Both the overall magnitude, and the degree of female bias, of effective gene flow therefore greatly exceeded those which would be inferred from observed physical arrivals, altering multiple eco-evolutionary implications of immigration.

Taking identity-by-descent analysis into the wild: Estimating realized relatedness in free-ranging macaques

Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of DNA segments that are identical-by-descent (IBD) yield the most precise estimates of relatedness. Here, we leverage novel methods for estimating locus-specific IBD from low coverage whole genome resequencing data to demonstrate the feasibility and value of resolving fine-scaled gradients of relatedness in free-living animals. Using primarily 4-6× coverage data from a rhesus macaque (Macaca mulatta) population with available long-term pedigree data, we show that we can call the number and length of IBD segments across the genome with high accuracy even at 0.5× coverage. The resulting estimates demonstrate substantial variation in genetic relatedness within kin classes, leading to overlapping distributions between kin classes. They identify cryptic genetic relatives that are not represented in the pedigree and reveal elevated recombination rates in females relative to males, which allows us to discriminate maternal and paternal kin using genotype data alone. Our findings represent a breakthrough in the ability to understand the predictors and consequences of genetic relatedness in natural populations, contributing to our understanding of a fundamental component of population structure in the wild.

The era of the ARG: An introduction to ancestral recombination graphs and their significance in empirical evolutionary genomics

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

Effective fitness under fluctuating selection with genetic drift

The natural environment fluctuates for virtually every population of organisms. As a result, the fitness of a mutant may vary temporally. While commonly used for summarizing the effect of fluctuating selection on the mutant, geometric mean fitness can be misleading under some circumstances due to the influence of genetic drift. Here, we show by mathematical proof and computer simulation that, with genetic drift, the geometric mean fitness does not accurately reflect the overall effect of fluctuating selection. We propose an alternative measure based on the average expected allele frequency change caused by selection and demonstrate that this measure-effective fitness-better captures the overall effect of fluctuating selection in the presence of drift.

Temporal collections to study invasion biology

Biological invasions represent an extraordinary opportunity to study evolution. This is because accidental or deliberate species introductions have taken place for centuries across large geographical scales, frequently prompting rapid evolutionary transitions in invasive populations. Until recently, however, the utility of invasions as evolutionary experiments has been hampered by limited information on the makeup of populations that were part of earlier invasion stages. Now, developments in ancient and historical DNA technologies, as well as the quickening pace of digitization for millions of specimens that are housed in herbaria and museums globally, promise to help overcome this obstacle. In this review, we first introduce the types of temporal data that can be used to study invasions, highlighting the timescale captured by each approach and their respective limitations. We then discuss how ancient and historical specimens as well as data available from prior invasion studies can be used to answer questions on mechanisms of (mal)adaptation, rates of evolution, or community-level changes during invasions. By bridging the gap between contemporary and historical invasive populations, temporal data can help us connect pattern to process in invasion science. These data will become increasingly important if invasions are to achieve their full potential as experiments of evolution in nature.

The era of the ARG: an empiricist's guide to ancestral recombination graphs

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in empirical evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

The estimation of reproductive values from pedigrees

Quantifying fitness is important to understand adaptive evolution. Reproductive values are useful for making fitness comparisons involving different categories of individuals, like males and females. By definition, the reproductive value of a category is the expected per capita contribution of the members of that category to the gene pool of future generations. Life history theory reveals how reproductive values can be determined via the estimation of life-history parameters, but this requires an adequate life-history model and intricate algebraic calculations. Recently, an alternative pedigree-based method has become popular, which estimates the expected genetic contribution of individuals to future generations by tracking their descendants down the pedigree. This method is versatile and intuitively appealing, but it is unknown if the method produces estimates of reproductive values that are accurate and precise. To investigate this, we implement various life-history scenarios (for which the "true" reproductive values can be calculated) in individual-based simulations, use the simulation data to estimate reproductive values with the pedigree method, and compare the results with the true target values. We show that the pedigree-based estimation of reproductive values is either biased (in the short term) or imprecise (in the long term). This holds even for simple life histories and under idealized conditions. We conclude that the pedigree method is not a good substitute for the traditional method to quantify reproductive values.

Beyond simple adaptation: Incorporating other evolutionary processes and concepts into eco-evolutionary dynamics

Studies of eco-evolutionary dynamics have integrated evolution with ecological processes at multiple scales (populations, communities and ecosystems) and with multiple interspecific interactions (antagonistic, mutualistic and competitive). However, evolution has often been conceptualised as a simple process: short-term directional adaptation that increases population growth. Here we argue that diverse other evolutionary processes, well studied in population genetics and evolutionary ecology, should also be considered to explore the full spectrum of feedback between ecological and evolutionary processes. Relevant but underappreciated processes include (1) drift and mutation, (2) disruptive selection causing lineage diversification or speciation reversal and (3) evolution driven by relative fitness differences that may decrease population growth. Because eco-evolutionary dynamics have often been studied by population and community ecologists, it will be important to incorporate a variety of concepts in population genetics and evolutionary ecology to better understand and predict eco-evolutionary dynamics in nature.

The long-lasting legacy of reproduction: lifetime reproductive success shapes expected genetic contributions of humans after 10 generations

An individual's lifetime reproductive success (LRS) measures its realized genetic contributions to the next generation, but how well does it predict this over longer periods? Here we use human genealogical data to estimate expected individual genetic contributions (IGC) and quantify the degree to which LRS, relative to other fitness proxies, predicts IGC over longer periods. This allows an identification of the life-history stages that are most important in shaping variation in IGC. We use historical genealogical data from two non-isolated local populations in Switzerland to estimate the stabilized IGC for 2230 individuals approximately 10 generations after they were born. We find that LRS explains 30% less variation in IGC than the best predictor of IGC, the number of grandoffspring. However, albeit less precise than the number of grandoffspring, we show that LRS does provide an unbiased prediction of IGC. Furthermore, it predicts IGC better than lifespan, and accounting for offspring survival to adulthood does not improve the explanatory power. Overall, our findings demonstrate the value of human genealogical data to evolutionary biology and suggest that reproduction-more than lifespan or offspring survival-impacts the long-term genetic contributions of historic humans, even in a population with appreciable migration.

Genetic and demographic consequences of range contraction patterns during biological annihilation

Species range contractions both contribute to, and result from, biological annihilation, yet do not receive the same attention as extinctions. Range contractions can lead to marked impacts on populations but are usually characterized only by reduction in extent of range. For effective conservation, it is critical to recognize that not all range contractions are the same. We propose three distinct patterns of range contraction: shrinkage, amputation, and fragmentation. We tested the impact of these patterns on populations of a generalist species using forward-time simulations. All three patterns caused 86-88% reduction in population abundance and significantly increased average relatedness, with differing patterns in declines of nucleotide diversity relative to the contraction pattern. The fragmentation pattern resulted in the strongest effects on post-contraction genetic diversity and structure. Defining and quantifying range contraction patterns and their consequences for Earth's biodiversity would provide useful and necessary information to combat biological annihilation.

Genetic Signature of Pinctada fucata Inferred from Population Genomics: Source Tracking of the Invasion in Mischief Reef of Nansha Islands

Among the anthropogenic stresses that marine ecosystems face, biological invasions are one of the major threats. Recently, as a result of increasingly intense anthropogenic disturbance, numerous marine species have been introduced to their non-native ranges. However, many introduced species have uncertain original sources. This prevents the design and establishment of methods for controlling or preventing these introduced species. In the present study, genomic sequencing and population genetic analysis were performed to detect the geographic origin of the introduced Pinctada fucata population in the Mischief Reef of the South China Sea. The results of population genetic structure analysis showed a close relationship between the Mischief Reef introduced population and the Lingshui population, indicating that Lingshui may be the potential geographical origin. Furthermore, lower heterozygosity and nucleotide diversity were observed in the introduced population in Mischief Reef, indicating lower genetic diversity than in other native populations. We also identified some selected genomic regions and genes of the introduced population, including genes related to temperature and salinity tolerance. These genes may play important roles in the adaptation of the introduced population. Our study will improve our understanding of the invasion history of the P. fucata population. Furthermore, the results of the present study will also facilitate further control and prevention of invasion in Mischief Reef, South China Sea.

Impact of Helicobacter pylori virulence markers on clinical outcomes in adult populations

BACKGROUND

In recent years, associations between specific virulence markers of Helicobacter pylori (H. pylori) and gastrointestinal disorders have been suggested.

AIM

To investigate the presence of virulence factors including vacuolating cytotoxin A genotypes (s1m1, s1m2, s2m1, and s2m2), cytotoxin-associated gene A (CagA), and urease activity in H. pylori strains isolated from Arab and Jewish populations in northern Israel and to assess associations between these factors and patients’ demographics and clinical outcomes.

METHODS

Patients (n = 108) who underwent gastroscopy at the Baruch Padeh Medical Center, Poriya due to symptomatic gastroduodenal pathologies as part of H. pylori diagnosis were enrolled in the study. Gastric biopsy specimens were collected from the antrum of the stomach. Clinical condition was assessed by clinical pathology tests. Bacteria were isolated on modified BD Helicobacter Agar (BD Diagnostics, Sparks, MD, United States). Bacterial DNA was extracted, and PCR was performed to detect CagA and vacuolating cytotoxin A genes. Urease activity was assessed using a rapid urease test.

RESULTS

A significant correlation was found between disease severity and patient ethnicity (P = 0.002). A significant correlation was found between CagA presence and the s1m1 genotype (P = 0.02), which is considered the most virulent genotype. Further, a higher level of urease activity was associated with isolates originating from the Jewish population. Moreover, higher urease activity levels were measured among CagA-/s1m1 and CagA-/s2m2 isolates.

CONCLUSION

Our study highlights the importance of incorporating molecular methods for detection of virulence markers of H. pylori in order to tailor optimal treatments for each patient. Further investigation should be performed regarding associations between H. pylori virulence factors and ethnicity.

Semantic and Population Analysis of the Genetic Targets Related to COVID-19 and Its Association with Genes and Diseases

SARS-CoV-2 is a coronavirus responsible for one of the most serious, modern worldwide pandemics, with lasting and multifaceted effects. By late 2021, SARS-CoV-2 has infected more than 180 million people and has killed more than 3 million. The virus gains entrance to human cells through binding to ACE2 via its surface spike protein and causes a complex disease of the respiratory system, termed COVID-19. Vaccination efforts are being made to hinder the viral spread, and therapeutics are currently under development. Toward this goal, scientific attention is shifting toward variants and SNPs that affect factors of the disease such as susceptibility and severity. This genomic grammar, tightly related to the dark part of our genome, can be explored through the use of modern methods such as natural language processing. We present a semantic analysis of SARS-CoV-2-related publications, which yielded a repertoire of SNPs, genes, and disease ontologies. Population data from the 1000 Genomes Project were subsequently integrated into the pipeline. Data mining approaches of this scale have the potential to elucidate the complex interaction between COVID-19 pathogenesis and host genetic variation; the resulting knowledge can facilitate the management of high-risk groups and aid the efforts toward precision medicine.

Taking quantitative genomics into the wild

We organized this special issue to highlight new work and review recent advances at the cutting edge of 'wild quantitative genomics'. In this editorial, we will present some history of wild quantitative genetic and genomic studies, before discussing the main themes in the papers published in this special issue and highlighting the future outlook of this dynamic field.

The genomic scale of fluctuating selection in a natural plant population

This study characterizes evolution at ≈1.86 million Single Nucleotide Polymorphisms (SNPs) within a natural population of yellow monkeyflower (Mimulus guttatus). Most SNPs exhibit minimal change over a span of 23 generations (less than 1% per year), consistent with neutral evolution in a large population. However, several thousand SNPs display strong fluctuations in frequency. Multiple lines of evidence indicate that these 'Fluctuating SNPs' are driven by temporally varying selection. Unlinked loci exhibit synchronous changes with the same allele increasing consistently in certain time intervals but declining in others. This synchrony is sufficiently pronounced that we can roughly classify intervals into two categories, "green" and "yellow," corresponding to conflicting selection regimes. Alleles increasing in green intervals are associated with early life investment in vegetative tissue and delayed flowering. The alternative alleles that increase in yellow intervals are associated with rapid progression to flowering. Selection on the Fluctuating SNPs produces a strong ripple effect on variation across the genome. Accounting for estimation error, we estimate the distribution of allele frequency change per generation in this population. While change is minimal for most SNPs, diffuse hitchhiking effects generated by selected loci may be driving neutral SNPs to a much greater extent than classic genetic drift.

Screening of Candidate Genes Associated with Brown Stripe Resistance in Sugarcane via BSR-seq Analysis

Sugarcane brown stripe (SBS), caused by the fungal pathogen Helminthosporium stenospilum, is one of the most serious threats to sugarcane production. However, its outbreaks and epidemics require suitable climatic conditions, resulting in the inefficient improvement of the SBS resistance by phenotype selection. The sugarcane F₁ population of SBS-resistant YT93-159 × SBS-susceptible ROC22 was used for constructing the bulks. Bulked segregant RNA-seq (BSR-seq) was then performed on the parents YT93-159 (T01) and ROC22 (T02), and the opposite bulks of 30 SBS-susceptible individuals mixed bulk (T03) and 30 SBS-resistant individuals mixed bulk (T04) collected from 287 F₁ individuals. A total of 170.00 Gb of clean data containing 297,921 SNPs and 70,426 genes were obtained. Differentially expressed genes (DEGs) analysis suggested that 7787 and 5911 DEGs were identified in the parents (T01 vs. T02) and two mixed bulks (T03 vs. T04), respectively. In addition, 25,363 high-quality and credible SNPs were obtained using the genome analysis toolkit GATK for SNP calling. Subsequently, six candidate regions with a total length of 8.72 Mb, which were located in the chromosomes 4B and 7C of sugarcane wild species Saccharum spontaneum, were identified, and 279 genes associated with SBS-resistance were annotated by ED algorithm and ΔSNP-index. Furthermore, the expression profiles of candidate genes were verified by quantitative real-time PCR (qRT-PCR) analysis, and the results showed that eight genes (LRR-RLK, DHAR1, WRKY7, RLK1, BLH4, AK3, CRK34, and NDA2) and seven genes (WRKY31, CIPK2, CKA1, CDPK6, PFK4, CBL2, and PR2) of the 20 tested genes were significantly up-regulated in YT93-159 and ROC22, respectively. Finally, a potential molecular mechanism of sugarcane response to H. stenospilum infection is illustrate that the activations of ROS signaling, MAPK cascade signaling, Ca²⁺ signaling, ABA signaling, and the ASA-GSH cycle jointly promote the SBS resistance in sugarcane. This study provides abundant gene resources for the SBS resistance breeding in sugarcane.

On the hidden temporal dynamics of plant adaptation

Adaptation to a wide range of environments is a major driver of plant diversity. It is now possible to catalog millions of potential adaptive genomic differences segregating between environments within a plant species in a single experiment. Understanding which of these changes contributes to adaptive phenotypic divergence between plant populations is a major goal of evolutionary biologists and crop breeders. In this review, we briefly highlight the approaches frequently used to understand the genetic basis of adaptive phenotypes in plants, and we discuss some of the limitations of these methods. We propose that direct observation of the process of adaptation using multigenerational studies and whole genome sequencing is a crucial missing component of recent studies of plant adaptation because it complements several shortcomings of sampling-based techniques.

Parent-offspring inference in inbred populations

Genealogical relationships are fundamental components of genetic studies. However, it is often challenging to infer correct and complete pedigrees even when genome-wide information is available. For example, inbreeding can obscure genetic differences between individuals, making it difficult to even distinguish first-degree relatives such as parent-offspring from full siblings. Similarly, genotyping errors can interfere with the detection of genetic similarity between parents and their offspring. Inbreeding is common in natural, domesticated, and experimental populations and genotyping of these populations often has more errors than in human data sets, so efficient methods for building pedigrees under these conditions are necessary. Here, we present a new method for parent-offspring inference in inbred pedigrees called specific parent-offspring relationship estimation (spore). spore is vastly superior to existing pedigree-inference methods at detecting parent-offspring relationships, in particular when inbreeding is high or in the presence of genotyping errors, or both. spore therefore fills an important void in the arsenal of pedigree inference tools.

Design and validation of a 63K genome-wide SNP-genotyping platform for caribou/reindeer (Rangifer tarandus)

BACKGROUND

Development of large single nucleotide polymorphism (SNP) arrays can make genomic data promptly available for conservation problematic. Medium and high-density panels can be designed with sufficient coverage to offer a genome-wide perspective and the generated genotypes can be used to assess different genetic metrics related to population structure, relatedness, or inbreeding. SNP genotyping could also permit sexing samples with unknown associated metadata as it is often the case when using non-invasive sampling methods favored for endangered species. Genome sequencing of wild species provides the necessary information to design such SNP arrays. We report here the development of a SNP-array for endangered Rangifer tarandus using a multi-platform sequencing approach from animals found in diverse populations representing the entire circumpolar distribution of the species.

RESULTS

From a very large comprehensive catalog of SNPs detected over the entire sample set (N = 894), a total of 63,336 SNPs were selected. SNP selection accounted for SNPs evenly distributed across the entire genome (~ every 50Kb) with known minor alleles across populations world-wide. In addition, a subset of SNPs was selected to represent rare and local alleles found in Eastern Canada which could be used for ecotype and population assignments - information urgently needed for conservation planning. In addition, heterozygosity from SNPs located in the X-chromosome and genotyping call-rate of SNPs located into the SRY gene of the Y-chromosome yielded an accurate and robust sexing assessment. All SNPs were validated using a high-throughput SNP-genotyping chip.

CONCLUSION

This design is now integrated into the first genome-wide commercially available genotyping platform for Rangifer tarandus. This platform would pave the way to future genomic investigation of populations for this endangered species, including estimation of genetic diversity parameters, population assignments, as well as animal sexing from genetic SNP data for non-invasive samples.

Reproductive isolation via polygenic local adaptation in sub-divided populations: Effect of linkage disequilibria and drift

This paper considers how polygenic local adaptation and reproductive isolation between hybridizing populations is influenced by linkage disequilibria (LD) between loci, in scenarios where both gene flow and genetic drift counteract selection. It shows that the combined effects of multi-locus LD and genetic drift on allele frequencies at selected loci and on heterozygosity at neutral loci are predicted accurately by incorporating (deterministic) effective migration rates into the diffusion approximation (for selected loci) and into the structured coalescent (for neutral loci). Theoretical approximations are tested against individual-based simulations and used to investigate conditions for the maintenance of local adaptation on an island subject to one-way migration from a differently adapted mainland, and in an infinite-island population with two habitats under divergent selection. The analysis clarifies the conditions under which LD between sets of locally deleterious alleles allows these to be collectively eliminated despite drift, causing sharper and (under certain conditions) shifted migration thresholds for loss of adaptation. Local adaptation also has counter-intuitive effects on neutral (relative) divergence: F_ST is highest for a pair of subpopulations belonging to the same (rare) habitat, despite the lack of reproductive isolation between them.

Environmental adaptation often involves spatially heterogeneous selection at many genetic loci. Thus, the evolutionary consequences of hybridisation between populations adapted to different environments depend on the coupled dynamics of multiple loci under selection, migration and genetic drift, making them challenging to predict. Here, I introduce theoretical approximations that accurately capture the effect of such coupling on allele frequencies at individual loci, while also accounting for the stochastic effects of genetic drift. I then use these approximations to study hybridisation in a metapopulation consisting of many interconnected subpopulations, where each subpopulation belongs to one of two habitats under divergent selection. The analysis clarifies how subpopulations belonging to a rare habitat can maintain local adaptation despite high levels of migration if net selection against multi-locus genotypes is stronger than a threshold which depends on the relative abundances of the two habitats. Further, local adaptation in a metapopulation can significantly elevate F_ST between subpopulations belonging to the same habitat, even though these are not reproductively isolated. These findings highlight the importance of carefully considering the genetic architecture and spatial context of divergence when interpreting patterns of genomic differentiation between speciating populations.

Quantitative evaluation of nonlinear methods for population structure visualization and inference

Population structure (also called genetic structure and population stratification) is the presence of a systematic difference in allele frequencies between subpopulations in a population as a result of nonrandom mating between individuals. It can be informative of genetic ancestry, and in the context of medical genetics, it is an important confounding variable in genome-wide association studies. Recently, many nonlinear dimensionality reduction techniques have been proposed for the population structure visualization task. However, an objective comparison of these techniques has so far been missing from the literature. In this article, we discuss the previously proposed nonlinear techniques and some of their potential weaknesses. We then propose a novel quantitative evaluation methodology for comparing these nonlinear techniques, based on populations for which pedigree is known a priori either through artificial selection or simulation. Based on this evaluation metric, we find graph-based algorithms such as t-SNE and UMAP to be superior to principal component analysis, while neural network-based methods fall behind.

The effective family size of immigrant founders predicts their long-term demographic outcome: From Québec settlers to their 20th-century descendants

Population history reconstruction, using extant genetic diversity data, routinely relies on simple demographic models to project the past through ascending genealogical-tree branches. Because genealogy and genetics are intimately related, we traced descending genealogies of the Québec founders to pursue their fate and to assess their contribution to the present-day population. Focusing on the female and male founder lines, we observed important sex-biased immigration in the early colony years and documented a remarkable impact of these early immigrants on the genetic make-up of 20th-century Québec. We estimated the immigrants’ survival ratio as a proportion of lineages found in the 1931–60 Québec to their number introduced within the immigration period. We assessed the effective family size, EFS, of all immigrant parents and their Québec-born descendants. The survival ratio of the earliest immigrants was the highest and declined over centuries in association with the immigrants’ EFS. Parents with high EFS left plentiful married descendants, putting EFS as the most important variable determining the parental demographic success throughout time for generations ahead. EFS of immigrant founders appears to predict their long-term demographic and, consequently, their genetic outcome. Genealogically inferred immigrants’ "autosomal" genetic contribution to 1931–60 Québec from consecutive immigration periods follow the same yearly pattern as the corresponding maternal and paternal lines. Québec genealogical data offer much broader information on the ancestral diversity distribution than genetic scrutiny of a limited population sample. Genealogically inferred population history could assist studies of evolutionary factors shaping population structure and provide tools to target specific health interventions.

What is the best fitness measure in wild populations? A case study on the power of short-term fitness proxies to predict reproductive value

Fitness is at the core of evolutionary theory, but it is difficult to measure accurately. One way to measure long-term fitness is by calculating the individual’s reproductive value, which represents the expected number of allele copies an individual passes on to distant future generations. However, this metric of fitness is scarcely used because the estimation of individual’s reproductive value requires long-term pedigree data, which is rarely available in wild populations where following individuals from birth to death is often impossible. Wild study systems therefore use short-term fitness metrics as proxies, such as the number of offspring produced. This study compared two frequently used short-term metrics for fitness obtained at different offspring life stages (eggs, hatchlings, fledglings and recruits), and compared their ability to predict reproductive values derived from the genetic pedigree of a wild passerine bird population. We used twenty years of precise field observations and a near-complete genetic pedigree to calculate reproductive success, individual growth rate and de-lifed fitness as lifetime fitness measures, and as annual de-lifed fitness. We compared the power of these metrics to predict reproductive values and lineage survival to the end of the study period. The three short-term fitness proxies predict the reproductive values and lineage survival only when measured at the recruit stage. There were no significant differences between the different fitness proxies at the same offspring stages in predicting the reproductive values and lineage survival. Annual fitness at one year old predicted reproductive values equally well as lifetime de-lifed fitness. However, none of the short-term fitness proxies were strongly associated with the reproductive values. The commonly used short-term fitness proxies best predict long-term fitness when measured at recruitment stage. Thus, because lifetime fitness measured at recruit stage and annual fitness in the first year of life were the best proxies of long-term fitness in short-lived birds, we encourage their future use.

Evolutionary and Ecological Drivers of Local Adaptation and Speciation in a North American Avian Species Complex

Throughout the speciation process, genomic divergence can be differentially impacted by selective pressures, as well as gene flow and genetic drift. Disentangling the effects of these evolutionary mechanisms remains challenging, especially for non-model organisms. Accounting for complex evolutionary histories and contemporary population structure often requires sufficient sample sizes, for which the expense of full genomes remains prohibitive. Here, we demonstrate the utility of partial-genome sequence data for range-wide samples to shed light into the divergence process of two closely related ducks, the Mexican duck (Anas diazi) and mallard (A. platyrhynchos). We determine the role of selective and neutral processes during speciation of Mexican ducks by integrating evolutionary and demographic modelling with genotype-environment and genotype-phenotype association testing. First, evolutionary models and demographic analyses support the hypothesis that Mexican ducks originally diverged ~300,000 years ago in a climate refugia arising during a glacial period in in a southwestern North America, and that subsequent environmental selective pressures played a key role in divergence. Mexican ducks then showed cyclical demographic patterns that likely reflected repeated range expansions and contractions, along with bouts of gene flow with mallards during glacial cycles. Finally, we provide evidence that sexual selection acted on several phenotypic traits as a co-evolutionary process, facilitating the development of reproductive barriers that initially arose due to strong ecological selection. More broadly, this work reveals that the genomic and phenotypic patterns observed across species complexes are the result of myriad factors that contribute in dynamic ways to the evolutionary trajectories of a lineage.

A Population Genomic Assessment of Three Decades of Evolution in a Natural Drosophila Population

Population genetics seeks to illuminate the forces shaping genetic variation, often based on a single snapshot of genomic variation. However, utilizing multiple sampling times to study changes in allele frequencies can help clarify the relative roles of neutral and non-neutral forces on short time scales. This study compares whole-genome sequence variation of recently collected natural population samples of Drosophila melanogaster against a collection made approximately 35 years prior from the same locality—encompassing roughly 500 generations of evolution. The allele frequency changes between these time points would suggest a relatively small local effective population size on the order of 10,000, significantly smaller than the global effective population size of the species. Some loci display stronger allele frequency changes than would be expected anywhere in the genome under neutrality—most notably the tandem paralogs Cyp6a17 and Cyp6a23, which are impacted by structural variation associated with resistance to pyrethroid insecticides. We find a genome-wide excess of outliers for high genetic differentiation between old and new samples, but a larger number of adaptation targets may have affected SNP-level differentiation versus window differentiation. We also find evidence for strengthening latitudinal allele frequency clines: northern-associated alleles have increased in frequency by an average of nearly 2.5% at SNPs previously identified as clinal outliers, but no such pattern is observed at random SNPs. This project underscores the scientific potential of using multiple sampling time points to investigate how evolution operates in natural populations, by quantifying how genetic variation has changed over ecologically relevant timescales.

Gene Flow and Genetic Structure Reveal Reduced Diversity between Generations of a Tropical Tree, Manilkara multifida Penn., in Atlantic Forest Fragments

The Atlantic Forest remnants in southern Bahia, Brazil, contain large tree species that have suffered disturbances in recent decades. Anthropogenic activities have led to a decrease in the population of many tree species and a loss of alleles that can maintain the evolutionary fitness of their populations. This study assessed patterns of genetic diversity, spatial genetic structure, and genetic structure among Manilkara multifida Penn. populations, comparing the genetic parameters of adult and juvenile trees. In particular, we collected leaves from adults and juveniles of M. multifida in two protected areas, the Veracel Station (EVC) and the Una Biological Reserve (UBR), located in threatened Atlantic Forest fragments. We observed a substantial decay in genetic variability between generations in both areas i.e., adults’ H_O values were higher (EVC = 0.720, UBR = 0.736) than juveniles’ (EVC = 0.463 and UBR = 0.560). Both juveniles and adults showed genetic structure between the two areas (θ = 0.017 for adults and θ = 0.109 for juveniles). Additionally, forest fragments indicated an unexpectedly short gene flow. Our results, therefore, highlight the pervasive effects of historical deforestation and other human disturbances on the genetic diversity of M. multifida populations within a key conservation region of the Atlantic Forest biodiversity hotspot.

Sex differences in deleterious mutational effects in Drosophila melanogaster: combining quantitative and population genetic insights

Fitness effects of deleterious mutations can differ between females and males due to: (i) sex differences in the strength of purifying selection; and (ii) sex differences in ploidy. Although sex differences in fitness effects have important broader implications (e.g., for the evolution of sex and lifespan), few studies have quantified their scope. Those that have belong to one of two distinct empirical traditions: (i) quantitative genetics, which focusses on multi-locus genetic variances in each sex, but is largely agnostic about their genetic basis; and (ii) molecular population genetics, which focusses on comparing autosomal and X-linked polymorphism, but is poorly suited for inferring contemporary sex differences. Here, we combine both traditions to present a comprehensive analysis of female and male adult reproductive fitness among 202 outbred, laboratory-adapted, hemiclonal genomes of Drosophila melanogaster. While we find no clear evidence for sex differences in the strength of purifying selection, sex differences in ploidy generate multiple signals of enhanced purifying selection for X-linked loci. These signals are present in quantitative genetic metrics-i.e., a disproportionate contribution of the X to male (but not female) fitness variation-and population genetic metrics-i.e., steeper regressions of an allele's average fitness effect on its frequency, and proportionally less nonsynonymous polymorphism on the X than autosomes. Fitting our data to models for both sets of metrics, we infer that deleterious alleles are partially recessive. Given the often-large gap between quantitative and population genetic estimates of evolutionary parameters, our study showcases the benefits of combining genomic and fitness data when estimating such parameters.

The promise and deceit of genomic selection component analyses

Selection component analyses (SCA) relate individual genotype to fitness components such as viability, fecundity and mating success. SCA are based on population genetic models and yield selection estimates directly in terms of predicted allele frequency change. This paper explores the statistical properties of gSCA: experiments that apply SCA to genome-wide scoring of SNPs in field sampled individuals. Computer simulations indicate that gSCA involving a few thousand genotyped samples can detect allele frequency changes of the magnitude that has been documented in field experiments on diverse taxa. To detect selection, imprecise genotyping from low-level sequencing of large samples of individuals provides much greater power than precise genotyping of smaller samples. The simulations also demonstrate the efficacy of 'haplotype matching', a method to combine information from a limited collection of whole genome sequence (the reference panel) with the much larger sample of field individuals that are measured for fitness. Pooled sequencing is demonstrated as another way to increase statistical power. Finally, I discuss the interpretation of selection estimates in relation to the Beavis effect, the overestimation of selection intensities at significant loci.

The relevance of pedigrees in the conservation genomics era

Over the past 50 years conservation genetics has developed a substantive toolbox to inform species management. One of the most long‐standing tools available to manage genetics—the pedigree—has been widely used to characterize diversity and maximize evolutionary potential in threatened populations. Now, with the ability to use high throughput sequencing to estimate relatedness, inbreeding, and genome‐wide functional diversity, some have asked whether it is warranted for conservation biologists to continue collecting and collating pedigrees for species management. In this perspective, we argue that pedigrees remain a relevant tool, and when combined with genomic data, create an invaluable resource for conservation genomic management. Genomic data can address pedigree pitfalls (e.g., founder relatedness, missing data, uncertainty), and in return robust pedigrees allow for more nuanced research design, including well‐informed sampling strategies and quantitative analyses (e.g., heritability, linkage) to better inform genomic inquiry. We further contend that building and maintaining pedigrees provides an opportunity to strengthen trusted relationships among conservation researchers, practitioners, Indigenous Peoples, and Local Communities.

The genomic consequences of hybridization

In the past decade, advances in genome sequencing have allowed researchers to uncover the history of hybridization in diverse groups of species, including our own. Although the field has made impressive progress in documenting the extent of natural hybridization, both historical and recent, there are still many unanswered questions about its genetic and evolutionary consequences. Recent work has suggested that the outcomes of hybridization in the genome may be in part predictable, but many open questions about the nature of selection on hybrids and the biological variables that shape such selection have hampered progress in this area. We synthesize what is known about the mechanisms that drive changes in ancestry in the genome after hybridization, highlight major unresolved questions, and discuss their implications for the predictability of genome evolution after hybridization.

Annual climatic fluctuations and short-term genetic variation in the eastern spadefoot toad

In addition to variations on the spatial scale, short- and long-term temporal variations, too, can impose intense selection on the overall genetic diversity and composition of a population. We hypothesized that the allelic composition in populations of the eastern spadefoot toad (Pelobates syriacus) would change among successive years in accordance with the short-term changes in environmental conditions. Surprisingly, the effect of short-term climate fluctuations on genetic composition have rarely been addressed in the literature, and to our knowledge the effect of annual climatic fluctuations have not been considered meaningful. Our findings show that climatic variation among successive years, primarily the amount of rainfall and rainy days, can significantly alter both microsatellite allelic composition and diversity. We suggest that environmental (i.e. fluctuating) selection is differential across the globe, and that its intensity is expected to be greatest in regions where short-term climatic conditions are least stable.

Demographic History, Not Mating System, Explains Signatures of Inbreeding and Inbreeding Depression in a Large Outbred Population

AbstractInbreeding depression is often found in small, inbred populations, but whether it can be detected in and have evolutionary consequences for large, wide-ranging populations is poorly known. Here, we investigate the possibility of inbreeding in a large population to determine whether mild levels of inbreeding can still have genetic and phenotypic consequences and how genomically widespread these effects can be. We apply genome-wide methods to investigate whether individual and parental heterozygosity is related to morphological, growth, or life-history traits in a pelagic seabird, Leach's storm-petrel (Oceanodroma leucorhoa). Examining 560 individuals as part of a multiyear study, we found a substantial effect of maternal heterozygosity on chick traits: chicks from less heterozygous (relatively inbred) mothers were significantly smaller than chicks from more heterozygous (noninbred) mothers. We show that these heterozygosity-fitness correlations were due to general genome-wide effects and demonstrate a correlation between heterozygosity and inbreeding, suggesting inbreeding depression. We used population genetic models to further show that the variance in inbreeding was probably due to past demographic events rather than the current mating system and ongoing mate choice. Our findings demonstrate that inbreeding depression can be observed in large populations and illustrate how the integration of genomic techniques and fieldwork can elucidate its underlying causes.

An extended catalogue of tandem alternative splice sites in human tissue transcriptomes

Tandem alternative splice sites (TASS) is a special class of alternative splicing events that are characterized by a close tandem arrangement of splice sites. Most TASS lack functional characterization and are believed to arise from splicing noise. Based on the RNA-seq data from the Genotype Tissue Expression project, we present an extended catalogue of TASS in healthy human tissues and analyze their tissue-specific expression. The expression of TASS is usually dominated by one major splice site (maSS), while the expression of minor splice sites (miSS) is at least an order of magnitude lower. Among 46k miSS with sufficient read support, 9k (20%) are significantly expressed above the expected noise level, and among them 2.5k are expressed tissue-specifically. We found significant correlations between tissue-specific expression of RNA-binding proteins (RBP), tissue-specific expression of miSS, and miSS response to RBP inactivation by shRNA. In combination with RBP profiling by eCLIP, this allowed prediction of novel cases of tissue-specific splicing regulation including a miSS in QKI mRNA that is likely regulated by PTBP1. The analysis of human primary cell transcriptomes suggested that both tissue-specific and cell-type-specific factors contribute to the regulation of miSS expression. More than 20% of tissue-specific miSS affect structured protein regions and may adjust protein-protein interactions or modify the stability of the protein core. The significantly expressed miSS evolve under the same selection pressure as maSS, while other miSS lack signatures of evolutionary selection and conservation. Using mixture models, we estimated that not more than 15% of maSS and not more than 54% of tissue-specific miSS are noisy, while the proportion of noisy splice sites among non-significantly expressed miSS is above 63%.

Pre-mRNA splicing is an important step in the processing of the genomic information during gene expression. During splicing, introns are excised from a gene transcript, and the remaining exons are ligated. Our work concerns one its particular subtype, which involves the so-called tandem alternative splice sites, a group of closely located exon borders that are used alternatively. We analyzed RNA-seq measurements of gene expression provided by the Genotype-Tissue Expression (GTEx) project, the largest to-date collection of such measurements in healthy human tissues, and constructed a detailed catalogue of tandem alternative splice sites. Within this catalogue, we characterized patterns of tissue-specific expression, regulation, impact on protein structure, and evolutionary selection acting on tandem alternative splice sites. In a number of genes, we predicted regulatory mechanisms that could be responsible for choosing one of many tandem alternative splice sites. The results of this study provide an invaluable resource for molecular biologists studying alternative splicing.

Polymorphism of fecundity genes (BMP15 and GDF9) and their association with litter size in Bangladeshi prolific Black Bengal goat

Goat farming in Bangladesh is primarily centred on indigenous Black Bengal goat, a highly prolific breed. Searching for genetic markers associated with prolificacy in this breed is vital for the country's goat breeding industry. However, there are no reports on polymorphisms associated with the fertility of Bangladeshi Black Bengal goats. This study investigated two major fecundity genes-bone morphogenetic protein 15 (BMP15) and growth differentiation factor 9 (GDF9) to detect any possible mutations in these two genes associated with litter size in Black Bengal goats. Blood samples were collected from 40 raised goats in Hathazari Government Goat Farm, Bangladesh. Genomic DNA was extracted; PCR amplification was performed; and sequencing of PCR products was performed to detect polymorphism loci in the target genes. Five SNPs viz. C735A, C743A, G754T, C781A and C808G were detected in exon 2 of BMP15 gene. A SNP (T1173A) was detected in GDF9 exon 2. Association results show that SNPs at the 735, 754 and 781 nucleotide positions of BMP15 exon 2 had a significant association with litter size in Black Bengal goat. The effect of parity was also highly significant (P < 0.001) on litter size. For the first time, this study explored SNP loci in fecundity genes in Bangladeshi prolific Black Bengal goats. Further studies with many genetically unrelated animals for assessing the association of these loci and others in the fecundity genes with litter size may be useful.

The Genome-Wide EMS Mutagenesis Bias Correlates With Sequence Context and Chromatin Structure in Rice

Ethyl methanesulfonate (EMS) is a chemical mutagen believed to mainly induce G/C to A/T transitions randomly in plant genomes. However, mutant screening for phenotypes often gets multiple alleles for one gene but no mutant for other genes. We investigated the potential EMS mutagenesis bias and the possible correlations with sequence context and chromatin structure using the whole genome resequencing data collected from 52 rice EMS mutants. We defined the EMS-induced single nucleotide polymorphic sites (SNPs) and explored the genomic factors associated with EMS mutagenesis bias. Compared with natural SNPs presented in the Rice3K project, EMS showed a preference on G/C sites with flanking sequences also higher in GC contents. The composition of local dinucleotides and trinucleotides was also associated with the efficiency of EMS mutagenesis. The biased distribution of EMS-induced SNPs was positively correlated with CpG numbers, transposable element contents, and repressive epigenetic markers but negatively with gene expression, the euchromatin marker DNase I hypersensitive sites, and active epigenetic markers, suggesting that sequence context and chromatin structure might correlate with the efficiency of EMS mutagenesis. Exploring the genome-wide features of EMS mutagenesis and correlations with epigenetic modifications will help in the understanding of DNA repair mechanism.

Using natural variation to understand plant responses to iron availability

Iron bioavailability varies dramatically between soil types across the globe. This has given rise to high levels of natural variation in plant iron responses, allowing members of even a single species to thrive across a wide range of soil types. In recent years we have seen the use of genome-wide association analysis to identify natural variants underlying plant responses to changes in iron availability in both Arabidopsis and important crop species. These studies have provided insights into which genes have been important in shaping local adaptation to iron availability in different plant species and have allowed the discovery of novel regulators and mechanisms, not previously identified using mutagenesis approaches. Furthermore, these studies have allowed the identification of markers that can be used to accelerate breeding of future elite varieties with increased resilience to iron stress and improved nutritional quality. The studies highlighted here show that, in addition to studying plant responses to iron alone, it is important to consider these responses within the context of plant nutrition more broadly and to also consider iron regulation in relation to additional traits of agronomic importance such as yield and disease resistance.

Ancestral haplotype reconstruction in endogamous populations using identity-by-descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs.

We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to North America from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 12 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct—we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.

When analyzing complex heritable traits, genomic data from many generations of an extended family increases the amount of information available for statistical inference. However, typically only genomic data from the recent generations of a pedigree are available, as ancestral individuals are deceased. In this work we present an algorithm, called thread, for reconstructing the genomes of ancestral individuals, given a complex pedigree and genomic data from the recent generations. Previous approaches have not been able to accommodate large datasets (both in terms of sites and individuals), made simplifying assumptions about pedigree structure, or did not tie reconstructed sequences back to specific individuals. We apply thread to a complex Old Order Amish pedigree of 1338 individuals, 394 with genotype data.

Time and Chance: Using Age Partitioning to Understand How Luck Drives Variation in Reproductive Success

AbstractOver the course of individual lifetimes, luck usually explains a large fraction of the between-individual variation in life span or lifetime reproductive output (LRO) within a population, while variation in individual traits or "quality" explains much less. To understand how, where in the life cycle, and through which demographic processes luck trumps trait variation, we show how to partition by age the contributions of luck and trait variation to LRO variance and how to quantify three distinct components of luck. We apply these tools to several empirical case studies. We find that luck swamps effects of trait variation at all ages, primarily because of randomness in individual state dynamics ("state trajectory luck"). Luck early in life is most important. Very early state trajectory luck generally determines whether an individual ever breeds, likely by ensuring that they are not dead or doomed quickly. Less early luck drives variation in success among those breeding at least once. Consequently, the importance of luck often has a sharp peak early in life or it has two peaks. We suggest that ages or stages where the importance of luck peaks are potential targets for interventions to benefit a population of concern, different from those identified by eigenvalue elasticity analysis.

Sexual Dimorphism through the Lens of Genome Manipulation, Forward Genetics, and Spatiotemporal Sequencing

Sexual reproduction often leads to selection that favors the evolution of sex-limited traits or sex-specific variation for shared traits. These sexual dimorphisms manifest due to sex-specific genetic architectures and sex-biased gene expression across development, yet the molecular mechanisms underlying these patterns are largely unknown. The first step is to understand how sexual dimorphisms arise across the genotype-phenotype-fitness map. The emergence of "4D genome technologies" allows for efficient, high-throughput, and cost-effective manipulation and observations of this process. Studies of sexual dimorphism will benefit from combining these technological advances (e.g., precision genome editing, inducible transgenic systems, and single-cell RNA sequencing) with clever experiments inspired by classic designs (e.g., bulked segregant analysis, experimental evolution, and pedigree tracing). This perspective poses a synthetic view of how manipulative approaches coupled with cutting-edge observational methods and evolutionary theory are poised to uncover the molecular genetic basis of sexual dimorphism with unprecedented resolution. We outline hypothesis-driven experimental paradigms for identifying genetic mechanisms of sexual dimorphism among tissues, across development, and over evolutionary time.

Predicting evolutionary change at the DNA level in a natural Mimulus population

Evolution by natural selection occurs when the frequencies of genetic variants change because individuals differ in Darwinian fitness components such as survival or reproductive success. Differential fitness has been demonstrated in field studies of many organisms, but it remains unclear how well we can quantitatively predict allele frequency changes from fitness measurements. Here, we characterize natural selection on millions of Single Nucleotide Polymorphisms (SNPs) across the genome of the annual plant Mimulus guttatus. We use fitness estimates to calibrate population genetic models that effectively predict allele frequency changes into the next generation. Hundreds of SNPs experienced "male selection" in 2013 with one allele at each SNP elevated in frequency among successful male gametes relative to the entire population of adults. In the following generation, allele frequencies at these SNPs consistently shifted in the predicted direction. A second year of study revealed that SNPs had effects on both viability and reproductive success with pervasive trade-offs between fitness components. SNPs favored by male selection were, on average, detrimental to survival. These trade-offs (antagonistic pleiotropy and temporal fluctuations in fitness) may be essential to the long-term maintenance of alleles. Despite the challenges of measuring selection in the wild, the strong correlation between predicted and observed allele frequency changes suggests that population genetic models have a much greater role to play in forward-time prediction of evolutionary change.

The search for sexually antagonistic genes: Practical insights from studies of local adaptation and statistical genomics

Sexually antagonistic (SA) genetic variation-in which alleles favored in one sex are disfavored in the other-is predicted to be common and has been documented in several animal and plant populations, yet we currently know little about its pervasiveness among species or its population genetic basis. Recent applications of genomics in studies of SA genetic variation have highlighted considerable methodological challenges to the identification and characterization of SA genes, raising questions about the feasibility of genomic approaches for inferring SA selection. The related fields of local adaptation and statistical genomics have previously dealt with similar challenges, and lessons from these disciplines can therefore help overcome current difficulties in applying genomics to study SA genetic variation. Here, we integrate theoretical and analytical concepts from local adaptation and statistical genomics research-including F ST and F IS statistics, genome-wide association studies, pedigree analyses, reciprocal transplant studies, and evolve-and-resequence experiments-to evaluate methods for identifying SA genes and genome-wide signals of SA genetic variation. We begin by developing theoretical models for between-sex F ST and F IS, including explicit null distributions for each statistic, and using them to critically evaluate putative multilocus signals of sex-specific selection in previously published datasets. We then highlight new statistics that address some of the limitations of F ST and F IS, along with applications of more direct approaches for characterizing SA genetic variation, which incorporate explicit fitness measurements. We finish by presenting practical guidelines for the validation and evolutionary analysis of candidate SA genes and discussing promising empirical systems for future work.

Autosomal STR Profiling and Databanking in Malaysia: Current Status and Future Prospects

Science and technology are extensively used in criminal investigation. From the mid- to late-1980s, one of the scientific discoveries that has had a particularly remarkable impact on this field has been the use of highly variable DNA sequence regions (minisatellites) in the human genome for individual identification. The technique was initially referred to as DNA fingerprinting, but is now more widely referred to as DNA profiling. Since then, many new developments have occurred within this area of science. These include the introduction of new genetic markers (microsatellites also known as short tandem repeats/STRs), the use of the polymerase chain reaction for target amplification, the development of DNA databases (databanking), and the advancement and/or improvement of genotyping protocols and technologies. In 2019, we described the progress of DNA profiling and DNA databanking in Malaysia for the first time. This report included information on DNA analysis regulations and legislation, STR genotyping protocols, database management, and accreditation status. Here, we provide an update on the performance of our DNA databank (numbers of DNA profiles and hits) plus the technical issues associated with correctly assigning the weight of evidence for DNA profiles in an ethnically diverse population, and the potential application of rapid DNA testing in the country. A total of 116,534 DNA profiles were obtained and stored in the Forensic DNA Databank of Malaysia (FDDM) by 2019, having increased from 70,570 in 2017. The number of hits increased by more than three-fold in just two years, where 17 and 69 hits between the DNA profiles stored in the FDDM and those from crime scenes, suspects, detainees, drug users, convicts, missing persons, or volunteers were recorded in 2017 and 2019, respectively. Forensic DNA analysis and databanking are thus progressing well in Malaysia and have already contributed to many criminal investigations. However, several other issues are discussed here, including the need for STR population data for uncharacterized population groups, and pilot trials for adopting rapid DNA profiling technology. These aspects should be considered by policy makers and law enforcement agencies in order to increase the reliability and efficiency of DNA profiling in criminal cases and in kinship analysis in Malaysia.

Pedigree-Based Estimation of Reproductive Value

How successful an individual or cohort is, in terms of their genetic contribution to the future population, is encapsulated in the concept of reproductive value, and is crucial for understanding selection and evolution. Long-term studies of pedigreed populations offer the opportunity to estimate reproductive values directly. However, the degree to which genetic contributions, as defined by a pedigree, may converge on their long-run values within the time frames of available data sets, such that they may be interpreted as estimates of reproductive value, is unclear. We develop a system for pedigree-based calculation of the expected genetic representation that both individuals and cohorts make to the population in the years following their birth. We apply this system to inference of individual and cohort reproductive values in Soay sheep (Ovis aries) from St Kilda, Outer Hebrides. We observe that these genetic contributions appear to become relatively stable within modest time frames. As such, it may be reasonable to consider pedigree-based calculations of genetic contributions to future generations as estimates of reproductive value. This approach and the knowledge that the estimates can stabilize within decades should offer new opportunities to analyze data from pedigreed wild populations, which will be of value to many fields within evolutionary biology and demography.