The future of prenatal diagnosis and screening lies in developing clinical approaches and laboratory technologies applicable to genetic analyses and therapeutic interventions during embryonic development. In addressing the challenge of predicting the future of prenatal diagnosis and screening, the inimitable quotations attributed to Yogi Berra, New York baseball catcher (1951–1963) and manager (1963–1989), come immediately to mind. He is reportedly to have made the following three paradoxical statements: first, “It’s tough to make predictions, especially about the future”; followed by words of advice, “If you don’t know where you are going, you’ll end up someplace else”; and concluding with a somewhat cautionary note, “The future ain’t what it used to be”. The past half-century has been witness to the application of a series of clinical and laboratory technologies that have provided remarkable insights into the human genome. It is now possible to define the human genotype at distinct biological levels, chromosome, gene, nucleotide, as well as their intrinsic and extrinsic interactions culminating in phenotype. Nowhere have these technologies, and the genetic information generated from them, been more widely applied than in the case of prenatal testing, both screening and diagnosis. Each year hundreds of thousands of women and their partners now undergo genetic testing in the form of carrier screening for single gene mutations, prenatal screening for chromosome abnormalities, and/or diagnostic analysis following an invasive procedure (first trimester chorionic villus sample or midtrimester amniocentesis). The dynamism of the field of prenatal genetic diagnosis and screening is illustrated with the ongoing introduction of new technologies, such as non-invasive prenatal testing (NIPT), array comparative genome hybridization (aCGH), exome sequencing, whole genome amplification, and RNA sequencing. The time has come where testing of a pre-implantation embryo, post-implantation embryo or a fetus has the potential of revealing not simply individual, deleterious mutations but rather a series of genes and gene interactions that impact on different stages of life in both positive and negative manners. If, as anticipated, the technologies associated with single cell analysis of the transcriptome ,3,4,5,6 Premise 1: Whereas the field of reproductive genetics has achieved remarkable success in the diagnosis and screening of chromosome and single gene disorders, the goal of positive therapeutic interventions has yet to be achieved.Premise 2: The etiology and pathogenesis of many genetic/developmental disorders are known and/or are being continuously refined and detailed.Premise 3: There is a categorical imperative for the need to shift focus from late identification of genetic and developmental disorders of the fetus  to the embryonic period . Premise 4: Identification of genetic and developmental disorders in the embryonic period is insufficient; there is a need to develop therapeutic interventions that either correct, alleviate and/or minimize the phenotypic effects of any genetic and developmental disorder at the time of their potential genesis, namely, during embryogenesis.Premise 5: Recognizing that there will be insufficient numbers of medical geneticists and genetic counselors to address the expansive genetic information generated by the multitude of technologies applicable to prenatal diagnosis and screening, the format of genetic counseling will be required to change in philosophy and in practice.The following is a discussion elaborating on each premise.Premise 1: Whereas the field of reproductive genetics has achieved remarkable success in the diagnosis and screening of chromosome and single gene disorders, the goal of positive therapeutic interventions has yet to be achieved.The first premise is that, based on current approaches and practices, essentially there will be no change in the future of prenatal diagnosis and screening. Whereas over the past 50 years prenatal identification of genetic mutations and developmental malformations has become increasingly sophisticated and expansive, the choices following such identification, namely, pregnancy termination or the birth of an affected offspring, have in fact not changed. In opposition to pregnancy termination, it has been proposed that prenatal diagnosis and screening represent a failure of medicine in the classical sense. This failure of current practices of prenatal diagnosis and screening, it is claimed, was first articulated specifically in the Hippocratic Oath:“I will prescribe regimens for the good of my patients according to my ability and my judgment and never do harm to anyone.”“I will give no deadly medicine to any one if asked, nor suggest any such counsel; and similarly I will not give a woman a pessary to cause an abortion.” (Author emphasis.)i.e., 9–11 weeks’ gestation, is also an acknowledgement of a medical failure, since from a developmental perspective, the damage, physical and/or functional, has already taken place many weeks earlier and as a result the best that can be expected from fetal therapy is partial but incomplete amelioration of the phenotypic effects of most genetic mutations and/or developmental anomalies.As part of the argument, it is evident that the distinction between a viable and nonviable fetus as a rationale and justification for termination of pregnancy is artificial on medical grounds alone, with no need for moral or religious considerations. Consequently, as presently conducted, it is argued, prenatal diagnosis and screening represents a violation of the basic tenet of medicine from the perspective of the fetus and ultimately is likely in many instances to be considered a failure on the part of the parents as well, especially those choosing pregnancy termination. The argument further suggests that the diagnosis of a genetic mutation and/or developmental anomaly made in the first trimester, Premise 2: The etiology and pathogenesis of many genetic/developmental disorders are known and/or are being continuously refined and detailed.i.e., non-human in origin [The human genome consists of coding and noncoding DNA sequences. Coded DNA comprise sequences that are transcribed into mRNA and eventually translated into proteins in the course of embryonic development. Whereas these coding sequences comprise less than 2% of the genome, they ultimately lead to the production of all human proteins, recognizing that other biological processes lead to the formation of many more unique proteins than the number of protein-coding genes . In the n origin . In the A number of Mendelian genes can serve as models wherein the complete spectrum of genetic and developmental effects of individual mutations has been defined. Examples would include, but not be limited to, sickle cell disease, Tay Sachs, spinal muscle atrophy, and cystic fibrosis. In the case of sickle cell disease (SCD), for example, every component of the pathogenesis has been defined including specific changes at the nucleotide level, the altered composition of the protein coded by the mutation(s), its effect on red cell morphology, the biochemical and physiological impact on somatic development, and the overall clinical expression as a direct consequence of the mutation(s). Patients with SCD experience multisystem complications comprising recurrent and painful vaso-occlusive crises, acute chest syndrome, splenic sequestration and pulmonary hypertension; organ damage begins at a young age and reduces life expectancy to half of the general population; SCD remains a highly morbid disease caused by chronic and progressive physical damage . DespitePremise 3: There is a categorical imperative for the need to shift focus from late identification of genetic and developmental disorders of the fetus (9 weeks gestation and beyond) to the embryonic period (pre-implantation to day 58 post-conception).It is generally understood that genetic disorders are developmental in nature and as such are formulated during embryogenesis; are already physically and/or functionally defined primarily before the beginning of the fetal stage; and, that developmental disturbances identified post-natally are in reality extensions of biological events occurring between three and eight weeks’ gestation. Consequently, the current practice of genetic testing following first trimester CVS or second trimester amniocentesis is applying prenatal diagnosis weeks far-too-late in pregnancy. Furthermore, as previously stated, when a genetic and/or developmental abnormality is identified using current technologies, the primary choices are usually limited to pregnancy termination or the birth of an affected offspring followed by ameliorative medical/surgical treatment. If this scenario is to be altered with a potentially positive outcome, alternative medical approaches and interventions that are not only realistic and practical but also acceptable to major sectors of any society, must be considered. Pre-implantation genetic diagnosis and screening is an obvious choice but it is proposed that in the future the focus of reproductive geneticists will be interventions during embryogenesis.i.e., polar bodies) or of embryos prior to transfer, easily meets the need of early identification of genetic and developmental disorders. There now is a relatively extensive worldwide body of knowledge and experience defining the field of pre-implantation genetic diagnosis and screening [The initial impression is that pre-implantation evaluation, either of gametes , chromosome banding, aCGH, next generation sequencing and NIPT, but all applied in distinguishing “normal” from “affected”. There have been projects aimed at integrating multiple approaches to identify the functional element encoded in the human genome, e.g., ENCODE [There is general consensus by health professionals that whereas elective abortion following any form of prenatal testing may be expeditious, in reality it still connotes an unsatisfactory medical response and outcome, as does the birth of a developmentally compromised newborn. The focus of the past 30 years has been on refining genetic analyses of the fetus, including the application of fluorescent , ENCODE , however, ENCODE .When genetic testing by amniocentesis was clinically introduced in the 1960s, it was generally recognized and agreed upon that this approach was not the ultimate goal of prenatal diagnosis. While the idea of fetal gene therapy was envisioned as a distant but attainable goal, it was understood that ultimately prenatal diagnostic testing had to be complemented by some form(s) of therapy, be it genetic, medical or surgical. Fetal gene therapy is inherently flawed as the potential detrimental phenotypic effects of any genetic mutation, be it at the chromosomal or molecular level, have already occurred in the embryonic period. Albeit with some minor success, in utero treatment has been applied to fetuses at risk for a number of genetic and congenital anomalies, including congenital diaphragmatic hernia, cystadenomatoid malformation of the lung and saccrococygeal teratoma, shunts for uropathies and thoracic fluids, pharmacological therapies for congenital adrenal hyperplasia and neural tube defect as well as stem cell treatment of severe combined immunodeficiency disorder ,28,29,30(1)Epigenomics would become a reality in which regulatory regions of all known genes in all major cell types and their disease variants would have been analyzed and their influences would be understood during prenatal and early postnatal development when epigenetic mechanisms undergo establishment and maturation;(2)Prevention of chromosome abnormalities by defining the biological processes associated with gamete maturation including chromosome pairing, synapsis and segregation of homologs, thereby ensuring that the euploid state would be obtained at conception and maintained during early embryonic development;(3)Treatment of mendelian, mitochondrial and multifactorial diseases in the pre-implantation and embryonic periods of development, which would involve cost-effective sequencing of the human genome at the single gene level, the development of databases cataloging submicroscopic copy number variants and their role in disease, a complete understanding of the pathogenesis of both single gene mutations and complex diseases, and knowledge derived from the epigenome, all of which have become a reality over the past decade .In the 30th Anniversary Issue of Prenatal Diagnosis published in 2010, three paradigm shifts in pre-implantation and prenatal genetics were projected to occur by 2020, each in turn enhancing one ultimate goal of medical science, namely, “personalized medicine”:i.e., a call to re-examine germline gene therapy as a responsible way to address the consequences of somatic gene therapy [Such related technologies would make possible implementation of targeted molecular interventions and the realization of the full potential of a personalized genome analysis in the prenatal period of human development, a consequence of the synergy of epigenetics, pharmacogenetics, and the ability to physically and chemically manipulate cells, tissues or organ systems . The add therapy .i.e., maternal, paternal and mitochondrial. The potential of manipulating the genetic inheritance of future offspring by modification of spermatozoa, oocytes and embryos prior to implantation can be criticized as being “high tech eugenics” and experimentation on humans. This criticism is a recurring theme consistently sounded following the introduction of new prenatal technology, e.g., when amniocentesis, chorionic villus sampling, in vitro fertilization (IVF) and pre-implantation genetic diagnosis (PGD) were each introduced. In the case of mitochondrial disorders, the combined application of several different technologies provides an opportunity for a carrier parent to ensure an offspring free of the clinical devastation as a consequence of dysfunctional mitochondria.Gene therapy is likely to be first applied in pre-implantation embryos, namely, in the case of mitochondrial disorders, which in turn immediately raises a recurring concern of simultaneously altering the germline. Both in the United Kingdom and United States, governmental approval has been requested for placing a fertilized oocyte at risk for a mitochondrial disorder into the cytoplasm with normal mitochondria, thus resulting in a conception with three genotypes, While the pre-implantation substitution of defective mitochondria represents a heritable change by virtue of the interaction of these organelles with the recipient nuclear genome, this approach does not address nuclear genetic mutations, e.g., the over six thousand single gene mutations, the hundreds of different kinds of chromosome abnormalities, and/or any of the multifactorial traits. It is likely that any attempt at prenatal genetic therapy during embryogenesis will require different types of molecular technologies for different developmental disorder. Targeted gene therapy in metabolic disorders restricted to an organ system, e.g., the liver in phenylketonuria or in maple syrup urine disease, would appear to be an acceptable approach, implemented as early as possibly in gestation in order to minimize any potential negative impact, particularly the development and function of the central nervous system . With the ability to edit DNA at the nucleotide level by virtue of such technologies as CRISPR , the “future is now” in the case of prenatal genetic therapy may no longer be a paradoxical statement . The tecOne consequence of the development and application of individualized gene therapies will likely be challenges to the relative autonomy of parental decision-making. In fact, in societies practicing a public health model, challenges to parental autonomy concerning various aspects of genetic testing have already been accepted. In the case of private health care models, e.g., the United States, individual choice concerning various forms of genetic testing is often considerably modulated by the professional societies, which, in turn, influence another important factor in parental decision-making, namely, insurance coverage. Therefore, although the basic right of reproductive choice, of when, with whom, and how to reproduce, continues to be articulated by Western societies, parental autonomy has been, and will continue to be, moderated by health care providers, particularly as new technologies are applied in prenatal diagnosis. What has been increasingly contentious in Western societies, primarily on ethical and moral grounds, is the granting of broad autonomy to prospective parents when the choice includes abortion. Over the coming decades, it will be the medical consequences and available choices following prenatal diagnosis that will be expanded to include pre-implantation and embryonic gene therapies. And, if practiced in the pre-implantation embryo, it must be understood and accepted that any form of gene therapy will likely involve altering the germ line as well as the soma. in vivo embryonic development at all biological levels, i.e., cell, tissue and organ [How in the foreseeable future is genomic medicine to influence pregnancy management and pregnancy outcome? New genetic technologies as well as new therapeutic strategies must be developed if embryonic care is to include expanded choices of action beyond current means ,4,5,6,7.nd organ , along wnd organ ,40,41,42nd organ ,44. Thisnd organ , spermatnd organ  and fertnd organ . Until n


Tropical tuna fisheries are central to food security and economic development of many regions of the world. Contemporary population assessment and management generally assume these fisheries exploit a single mixed spawning population, within ocean basins. To date population genetics has lacked the required power to conclusively test this assumption. Here we demonstrate heterogeneous population structure among yellowfin tuna sampled at three locations across the Pacific Ocean  via analysis of double digest restriction-site associated DNA using Next Generation Sequencing technology. The differences among locations are such that individuals sampled from one of the three regions examined can be assigned with close to 100% accuracy demonstrating the power of this approach for providing practical markers for fishery independent verification of catch provenance in a way not achieved by previous techniques. Given these results, an extended pan-tropical survey of yellowfin tuna using this approach will not only help combat the largest threat to sustainable fisheries  but will also provide a basis to transform current monitoring, assessment, and management approaches for this globally significant species. International tuna fisheries, managed under the auspices of Regional Fisheries Management Organisations (RFMO), are central to global food security and underpin multi-billion dollar economic activity in the developed and developing world. International law and governance arrangements for these fisheries (i.e. United Nations Convention on the Law of the Sea and UN Fish Stocks Agreement), which straddle international boundaries and large proportions of ocean basins, assume that the areas of competence of each RFMO equate to single panmictic stocks of the major target speciesThunnus albacares) in the Pacific, where it is the second-most important species in the world’s largest tuna fishery2Until recently, whether population genetic approaches  had sufficient discriminating power to adequately test this assumption has been constantly debated2346789108Yellowfin tuna is distributed in a continuous pan-tropical band 45 degrees north and south of the equator, from the Gulf of Mexico in the western Atlantic eastward to the coast of the Americas in the Pacific Ocean. It is now recognized as a single species, although it was originally classified into seven sub-species based primarily on morphological variation151618Genetic studies of yellowfin tuna stock structure in the Pacific using mitochondrial DNA (mtDNA), allozyme, and nuclear DNA (nDNA) microsatellite markers have been inconclusive5205The current study investigated the population structure of yellowfin tuna among three distantly separated locations across the Pacific Ocean . We demoThe DArTsoft14 pipeline delivered a total of 14,412 SNPs . This nuGlobal measures of genetic differentiation G, as computed with Genepop, were highly significant for both the NL and LUPS datasets. Pairwise G statistics for all population pairs were highly significant for the LUPS-dataset, but not for the NL-dataset. The contrast between global and pairwise measures of genetic differentiation suggests the existence of a relatively weak genetic structure as inferred from neutral markers.Neither the PCA nor the STRUCTURE analysis of the NL-dataset revealed any pattern or presence of genetic heterogeneity . In contAn analysis to determine the minimal SNP panel required for discriminating among the three populations estimated a panel of ~18 SNPs would provide a probability of 99.9% of correctly assigning provenance of an individual to the correct population . This leHere, we provide the first unequivocal evidence of genetically distinct populations of yellowfin tuna at ocean basin-scale using SNP markers. Importantly, we have demonstrated that, with a small sub-set of these markers, provenance of individuals can be assigned with a high degree of confidence. This provides the foundation for practical, cost-effective approaches for analysis of population structure, provenance, and chain-of-custody systems for these multi-billion dollar common resources.Katsuwonus pelamis), yellowfin , and bigeye (T. obesus) tunas221The implications of these findings for assessment and management of global tropical tuna populations are substantial and wide ranging. Contemporary assessment and management is based on the assumption that the management unit being assessed is a single reproductive population with mixing of spawning populations , mixed gear (purse-seine and longline), equatorial band, and the Coral Sea, low catch , higher latitude, longline only fishery. To assess these fisheries independently would require a more comprehensive, systematic genetic survey across the range of yellowfin tuna within the Pacific to determine number of populations and define the appropriate units for assessment and, if appropriate, management. Depending on the degree of mixing on feeding/fishing grounds, such a multi-population system may require catch-sampling programs to provide estimates of the proportion of different populations in catches from each area. Given the high probability of assignment of provenance using the markers under selection, this (assigning probabilistic sources of catches) is now feasible, and cost-effective, and could be implemented through at-sea or port sub-sampling of catches.et al.18Results from tagging data and genetic markers from previous studies provided evidence indicative of east-west population structure of yellowfin tuna across the Pacific Ocean, which was temporally stable over several decades51921242720262920313233The definitive nature of the population structure revealed here and capacity to define provenance with a small number of markers (<20) clearly demonstrates the power and efficiency of this new approach, even with the modest number of fish available to this study. Determining the specific implications for assessment and management of yellowfin tuna in the Pacific, and other oceans, requires a systematic global survey to provide a comprehensive description of population structure and associated estimates of connectivity. The (relatively) low cost and rapid rate of processing of this approach mean that such a survey could be completed within a matter of years, given sufficient international collaboration. Furthermore, the very high probability of assignment, combined with low unit cost, high through-put, inter-laboratory repeatability, and speed of processing associated with the genotyping-by-sequencing approaches suggest it is also well suited to large-scale, forensic screening required for chain of custody schemes and detecting and deterring activities associated with IUU fishing, such as catch substitutions. These results clearly demonstrate the need to define and incorporate this finer scale population structure of yellowfin tuna, and other “highly migratory species” in both their assessment and management and, potentially, allocation of access rights for these globally important resources.Individual yellowfin tuna tissue biopsies were obtained from dead animals from commercial catches on board vessels fishing in areas located in the western , central , and eastern  Pacific Ocean . Fish raet al.SphI-compatible overhang sequence.DArTseq™ represents a combination of DArT complexity reduction methods and next generation sequencing platforms12363740Only “mixed fragments” (PstI-SphI) were effectively amplified by PCR. PCR conditions consisted of an initial denaturation at 94 °C for 1 min followed by 30 cycles of 94 °C for 20 sec, 58 °C for 30 sec and 72 °C for 45 sec, with a final extension step at 72 °C for 7 min.After PCR equimolar amounts of amplification products from each sample of the 96-well microtiter plate were bulked and applied to cBot (Illumina) bridge PCR followed by sequencing on an Illumina Hiseq2000. The sequencing (single read) was run for 77 cycles.Sequences generated from each lane were processed using proprietary DArTseq analytical pipelines. In the primary pipeline, the FASTQ files were first processed to filter away poor quality sequences, applying more stringent selection criteria to the barcode region compared to the rest of the sequence. In that way the assignments of the sequences to specific samples carried in the “barcode split” step were very reliable. Approximately 2,000,000 sequences per barcode/sample were identified and used in marker calling. Finally, identical sequences were collapsed into “fastqcoll files”. The fastqcoll files were “groomed” using DArT PLD’s proprietary algorithm that corrects low quality base from singleton tag into a correct base using collapsed tags with multiple members as a template. The “groome” fastqcoll files were used in the secondary pipeline for DArT PLD’s proprietary SNP and SilicoDArT (presence/absence of restriction fragments in representation) calling algorithms (DArTsoft14). For SNP calling all tags from all libraries included in theDArTsoft14 analysis are clustered using DArT PL’s C++ algorithm at the threshold distance of 3, followed by parsing of the clusters into separate SNP loci using a range of technical parameters, especially the balance of read counts for the allelic pairs. Additional selection criteria were added to the algorithm based on analysis of approximately 1,000 controlled cross populations. Testing for Mendelian distribution of alleles in these populations facilitated selection of technical parameters discriminating well true allelic variants from paralogous sequences, In addition multiple samples were processed from DNA to allelic calls as technical replicates and scoring consistency was used as the main selection criteria for high quality/low error rate markers. Calling quality was assured by high average read depth per locus . As tuna reference genome is not yet available DArT has not performed alignment of tags/markers identified, hence mapping efficiency of reads against such reference could not be evaluated. For the current study only co-dominant SNP-DArT markers were used for population analysis.The data set used for population analysis from the DArTsoft14 pipeline consisted of 75 bp fragments containing one or more SNPs. When multiple polymorphisms were found on the same 75 bp fragment (RAD contig), a single SNP was randomly chosen to represent that locus to avoid linkage disequilibrium between close loci. Loci were further eliminated from population analysis by excluding loci with call rate  was lower than 90% and/or minor allele frequencies (MAF) lower than 5%. Departure from Hardy-Weinberg equilibrium (HWE) was tested for each locus within each sampling location using the “HWE.test.genind” function in the Adegenet R packageMeasures of genetic diversity, including observed and expected heterozygosities and allelic richness, were calculated for all SNPs that passed the quality filtering steps using the diveRsity R package 53.st outlier approach developed by Beaumont & Nicholsst. This Fst value was then used in a second LOSITAN analysis including all SNPs. The ‘Force mean Fst′ option was selected in order to approximate a desired mean Fst, by running a bisection algorithm over repeated simulationsTo identify putatively neutral loci and loci potentially located in genomic regions subject to positive selection, we used the Fet al.Global and pairwise exact G tests of genetic differentiation were calculated using GENEPOP (v. 4.2 with default parameters)The minimum number of SNPs required to distinguish the three populations was determined for the LUPS-dataset using forward selection  populations demands rethink of management for this globally important resource. Sci. Rep.5, 16916; doi: 10.1038/srep16916 (2015).


Schistometopum thomense. Variation in pigmentation, morphology and size of this taxon over its c. 45 km island range is extreme, motivating a number of taxonomic, ecological, and evolutionary hypotheses to explain the observed diversity. We conducted a population genetic study of S. thomense using partial sequences of two mitochondrial DNA genes (ND4 and 16S), together with morphological examination, to address competing hypotheses of taxonomic or clinal variation. Using Bayesian phylogenetic analysis and Spatial Analysis of Molecular Variance, we found evidence of four geographic clades, whose range and approximated age (c. 253 Kya – 27 Kya) are consistent with the spread and age of recent volcanic flows. These clades explained 90% of variation in ND4 (CTφ = 0.892), and diverged by 4.3% minimum pairwise distance at the deepest node. Most notably, using Mismatch Distributions and Mantel Tests, we identified a zone of population admixture that dissected the island. In the northern clade, we found evidence of recent population expansion (Fu's sF = −13.08 and Tajima's D = −1.80) and limited dispersal . Color assignment to clades was not absolute. Paired with multinomial regression of chromatic data, our analyses suggested that the genetic groups and a latitudinal gradient together describe variation in color of S. thomense. We propose that volcanism and limited dispersal ability are the likely proximal causes of the observed genetic structure. This is the first population genetic study of any caecilian and demonstrates that these animals have deep genetic divisions over very small areas in accordance with previous speculations of low dispersal abilities.Islands provide exciting opportunities for exploring ecological and evolutionary mechanisms. The oceanic island of São Tomé in the Gulf of Guinea exhibits high diversity of fauna including the endemic caecilian amphibian,  Islands are self-contained natural laboratories and provide the backdrop to many of Darwin's and Wallace's observations that culminated in the theory of evolution pers. obs. 1 Aug 2012) – São Tomé is one of three oceanic islands in the Gulf of Guinea that rose along the Cameroon Line roughly 13 Mya 2, with the highest peak at 2024 m. Over the course of its existence, volcanic activity has reshaped topography Notable for its high endemism in both flora and fauna – including approximately 80 plants a.k.a., caecilians – for which very little intraspecific information exists The presence of salt-intolerant taxa on truly oceanic islands has garnered particular interest because mechanisms accounting for presence imply dispersal across marine environments, but direct dispersal is assumed to be limited by physiology. However, recent phylogenetic studies have suggested the existence of delivery mechanisms, in particular oceanic currents, which carry flotsam Schistometopum thomense (Barboza du Bocage) Schistometopum gregorii, occurs on the far eastern coast of continental Africa (Kenya and Tanzania) Schistometopum ephele Taylor S. thomense  S. thomense, recognizing that criteria used to designate S. ephele Taylor were expressions of sexual dimorphism and of possible clinal variation from north to south on the island, and confirming that the third taxon – S. brevirostre – had been described without knowledge of the initial description S. thomense may have limited dispersal ability receives further support from the finding that this species exhibits Bergmann's rule; Measey and Van Dongen S. thomense, examining genetic variation at the species level offers indirect means to understand microevolutionary processes acting within this fossorial species.The caecilian amphibian S. thomense, we investigated the distribution of genetic diversity using mitochondrial DNA (mtDNA). In particular, we were interested in whether previously proposed taxonomic  or clinal variation  hypotheses could better explain the high phenotypic variation exhibited by caecilians on São Tomé In order to assess population structuring of Schistometopum thomense on the island of São Tomé was was granted by Hon. Arlindo Carvalho, Director General, Ministry of Environment, Republic of São Tomé and Príncipe. Ethics clearance for this study was granted by the Office for the Protection of Human and Animal Subjects, San Francisco State University (Protocol # A3-014).Permission to collect, sample and export Schistometopum thomense (Barboza du Bocage) is an elongate, limbless, burrowing amphibian of the Order Gymnophiona  on the island of São Tomé (Schistometopum gregorii (MW 03231) was used as an outgroup in phylogenetic analyses.In order to assess genetic and chromatic variation within the range of São Tomé . SpecimeSão Tomé . Specime2, 0.033 U Bioline Taq, 10 µL template DNA), and used the temperature profile: 94°C for 7 min., 40 cycles of 94°C for 30 sec., 46°C–50°C for 30 sec., 72°C for 1 min., followed by 72°C for 7 min. Non-hot-start reactions were conducted in 10 µL volumes  and used the temperature profile: 94°C for 7 min., 25 cycles of 94°C for 30 sec., 50°C for 30 sec.-1 min., 72°C for 1 min., followed by 72°C for 7 min. In addition to ND4, approximately 600 base pairs of the small ribosomal subunit 16S were amplified using the primers 16sar and 16sbr Whole genomic DNA was extracted from liver tissue, using either phenol-chloroform μL volumes , incubating at 37°C for 15 min., 80°C for 15 min., then cooling to 4°C. Based on visual strength of bands in an agarose gel, 0.5–1.0 μL Wizard Prep product or 1.0–4.5 μL of ExoSAP-IT reaction product were then used in cycle sequencing reactions.PCR product was cleaned using the Promega Wizard PCR Preps DNA Purification System  following manufacturer's protocol, or with ExoSAP-IT , using the following reaction conditions: 7.5 http://www.ncbi.nlm.nih.gov/BLAST/) in GenBank Cycle Sequencing was performed on either a Perkin Elmer 9600, Perkin Elmer 9700 or BioRad thermocycler, following ABI prism instructions for either Big Dye version 2.0  or Big Dye version 3.1  , depending on which reagent was used. For all samples, amplified products were sequenced in both the 3′ and 5′ directions, using the original PCR primers. Nucleotide order was read by an ABI-PRISM 3100 Genetic Analyzer . Base calls and editing were resolved by eye using Sequencher versions 3.1 and 4.2 . Confirmation of ND4 as the amplified product was made with BLAST searches . Because SAMOVA performs poorly with datasets populated by low sample-size locations, disjunct sampling localities represented by one individual only were excluded and neighboring and/or remaining low sample size locales (n≤2) were grouped with proximate larger populations, creating a dataset of 136 individuals from 16 sample sites (SAMOVA sample sites represented in green and blue and lumped populations circled by dashed red lines in hπsF and Tajima's D) to determine whether any group might be out of mutation drift equilibrium FS and Tajima's D tests are sensitive to frequencies of alleles within a sample and will generate significantly negative values when an excess of rare frequency alleles exists, a condition that is expected after recent population expansion. In the instance that a group returned significant values of either of these tests, mismatch distribution analyses were run t = τ/(2u), in which t is generation time, τ is the age of the expansion in mutational units (estimated in the model of demographic expansion) and u is the sum of the per nucleotide mutation rate for the region sequenced S. thomense, generation time was set at two years based on reported ages at first reproduction for captive females u was estimated from mutation rates of ND4 in amphibians that were available in the literature .To further examine relationships among groups, the full ND4 dataset , the geometric mean of the mutation rate (U) for the markers sequenced was used: T = t/Uμ) per nucleotide site per million years were estimated from amphibian rates for ND4 and 16S in the literature  light yellow, no brown flecks, 2) dark yellow, no brown flecks, 3) dark yellow, light to moderate brown flecking, 4) dark yellow, heavy brown flecking. Colors were scored by two of us (RES and GJM) from live animals or from images of animals (after anesthesia). Any disagreements in scores were resolved by reviewing images of specimens concerned.We followed Nussbaum and Pfrender S. thomense (n = 138) as a nominal response variable (category 4 serving as the reference) in a multinomial logistic model implemented in PROC GLIMMIX of SAS v 9.2 c scores To test whether color variation was best explained by genetic lineages and/or clinal variation, we treated color coding of ND4-sequenced Schistometopum thomense, respectively, collected at 24 sample locations across the island of São Tomé  and 538 additional base pairs of mitochondrial 16S rRNA from 138 and 26 individual nhaplo = 57) revealed two deeply divergent and geographically-concordant evolutionary lineages on the island  of the ND4 haplotype dataset  – within population variance explained only 6.34% of the total island variance. Likewise, variance among populations within groups – described by φSC, which was lower (0.412) – explained only 4.45% of total island variance . We found φCT for this SAMOVA continued to rise marginally (<0.01) when the number of possible groups was increased, but adding groups did not significantly change φCT , but not for the Central+Eastern group.In order to provide a more historical interpretation of matrilineal populations, a second SAMOVA was run, for which the four admixed populations were split into their component Northern and Central+Eastern subsets. As expected, this analysis identified the Northern, Western, Central+Eastern, and Southern groups, generating a nge φCT . As illuh) and nucleotide diversity (π) – was highest in the Western and Northern lineages, slightly less variable in the Central+Eastern lineage, and least variable in the Southern lineage  allowed greater insight into lineage ages. Two distinct divergence periods were identified: one between 200–250 Kya and the other between 20–30 Kya. The first divergence between Northern and other lineages produced the highest point for divergence (HPD) at 253 Kya (95% HPD = 136–435 Kya), and the lineage on the west coast appears to have split very close to this time (average HPD = 215 Kya: 95% HPD = 101–354 Kya). Most recently, the lineage in the extreme south diverged from the lineage in the central and eastern areas around 27 Kya (95% HPD = 2–242 Kya). Although 95% HPDs were overlapping for all of these events, the highest point for the HPD for each of the divergence events was used as an indication of the most likely divergence scenario.IMa2 analysis of a composite ND4 and 16S dataset , allowing an additional calculation of time since the inferred demographic expansion in the North of São Tomé: ca. 167.5 Kya . The Central+Eastern and Western groups also showed conformity to a pattern of recent population expansion based on mismatch distribution tests, but for neither of these groups were Tajima's D or Fu's Fs significantly negative. The Bayesian phylogram shows the same relative ‘ages’ of the lineages and the haplotypes within: apparent ancestral haplotypes were collected from the west of the island . Our AICc ordering of multinomial logistic regressions selected the global model – retaining the explanatory variables of genetic group, geology, latitude and altitude – as the best model , ranking more than 21 AICc units above the next best model and accounting for virtually all the weight among our candidate model set. Despite retaining all explanatory variables, the best model only produced significant Type III effects for genetic group  and latitude . Examination of 95% confidence limits surrounding β estimates indicated that most support for these covariates came from the comparison between dark yellow, unflecked morphs (category 2) to dark yellow, flecked morphs  and number of individuals in each response category (ncolor = ∼35) relative to total model parameters (k = 27), our ability to detect significant effects may have been restricted. For the geology covariate, sample size may have limited the power to detect an effect in some levels, e.g., only one specimen resided on older basaltic lava flows 3–8 Mya , coupled with genetic data, show that S. thomense, as currently recognized, is highly structured for mtDNA and that this structure is concordant with northern, western, eastern+central and southern geographic groupings on the island. Although, a north-south cline is not rejected by our morphological analyses , our mitochondrial genetic results show that this species exhibits a narrow zone of admixture between the two most divergent clades (∼4% minimum uncorrected pairwise distance between ND4 lineages) and ages this split at approximately 0.25 Mya. We require nDNA sequencing to ascertain whether the admixed area contains hybrids between the two mtDNA lineages. However, the mixed nature of color forms in these areas suggests that this is the case. Admixed zones have been found for other amphibians which have arrived on islands Our results suggest that both genetic clades and clinal variation contribute to the strikingly high differences in coloration that led Taylor S. thomense arrived on São Tomé by a single or multiple colonization events remains inconclusive, given the relatively recent estimates of population divergence (relative to island age) and of volcanic flows. Multiple independent colonization events have been suggested for geckos Zosterops spp. and Speirops spp., respectively) Whether The most recent eruptions have been placed at 36 Kya, in geologic samples collected from the islet of Rolas  Ichthyophis sp. from the Western Ghats of India) suggests that caecilians are not necessarily philopatric pers. obs.). An explanation for these two very different results for caecilian taxa may stem from the Indian study being based on a very small sample (n = 18) using relatively undifferentiated mtDNA markers (12S and 16S) in a phylogeographic context Amphibians have been classically described as highly philopatric S. thomense on São Tomé given the neutral behavior of the mutations observed, the geographic congruence of haplotype pattern, and the generalized concordance with morphological data.We emphasize provisional acceptance of our results given potential bias posed by use of a two-gene mtDNA dataset. Because (1) natural selection influences mutations in functional genes, (2) the coalescence of gene lineages to cladogenic events may be slow to reflect organismal phylogeny or gene lineages may diverge within a taxonomic line and insinuate a taxonomic division when one does not exist, and (3) – for most taxa – mitochondrial phylogenies track only the evolutionary history of matriarchal lines, we highlight the fact that cladogenic results reported here require substantiation with nDNA. However, we note that single-gene mtDNA histories have proven informative in many studies Schistometopum thomense on São Tomé has a strongly differentiated population structure shown by mtDNA, something that was hitherto unknown for any species in this amphibian Order. Our study confirms previous hypotheses concerning clinal latitudinal variation S. thomense and S. ephele), although applying genetic barcoding standards to 16S Abstract S1Resumo. Abstract in Portuguese.(DOCX)Click here for additional data file.Table S1Specimen Data.(DOCX)Click here for additional data file.


Exploring interactions between ecological disturbance, species’ abundances and community composition provides critical insights for ecological dynamics. While disturbance is also potentially an important driver of landscape genetic patterns, the mechanisms by which these patterns may arise by selective and neutral processes are not well‐understood. We used simulation to evaluate the relative importance of disturbance regime components, and their interaction with demographic and dispersal processes, on the distribution of genetic diversity across landscapes. We investigated genetic impacts of variation in key components of disturbance regimes and spatial patterns that are likely to respond to climate change and land management, including disturbance size, frequency, and severity. The influence of disturbance was mediated by dispersal distance and, to a limited extent, by birth rate. Nevertheless, all three disturbance regime components strongly influenced spatial and temporal patterns of genetic diversity within subpopulations, and were associated with changes in genetic structure. Furthermore, disturbance‐induced changes in temporal population dynamics and the spatial distribution of populations across the landscape resulted in disrupted isolation by distance patterns among populations. Our results show that forecast changes in disturbance regimes have the potential to cause major changes to the distribution of genetic diversity within and among populations. We highlight likely scenarios under which future changes to disturbance size, severity, or frequency will have the strongest impacts on population genetic patterns. In addition, our results have implications for the inference of biological processes from genetic data, because the effects of dispersal on genetic patterns were strongly mediated by disturbance regimes. The importance of ecological disturbance as a driver of biodiversity patterns is being increasingly recognized as disturbance regimes change globally Turner . Global Disturbance regimes are classically considered as the history of disturbance at a point Gill . This hiUlex parvoflorus , diversity within demes (HS) and differentiation among demes (FST). Slatkin  provides a starting point for developing expectations about the impacts of disturbance regimes Slatkin . Much of Slatkin  identifiTo understand the potentially complex relationships that may exist between landscape patterns of genetic diversity and disturbance, we focus on modelling space, time, demography, disturbance, and genetics in a simple and neutral form  by varying the degree of in situ survival. Extinction of entire populations within a disturbance footprint represents one extreme scenario of disturbance intensity  influence the interaction between disturbance regimes and genetic patterns? We expect that these parameters will not only influence the patterns of recovery from specific disturbance events, but influence the pre‐existing spatial genetic context in which recovery occurs.The novelty of this study was to use simulation to understand the relative importance of variation in key components of disturbance regimes and demographic processes, in driving landscape patterns of genetic diversity. Insights of this nature address a key gap in understanding disturbance‐driven ecological genetics , after noting that preliminary simulations on a 204 × 204 cell landscape yielded similar final results (Appendix S1). To ensure a sufficiently large sample size for analysis, the 102 × 102 cell landscape was divided into 1156 sample populations, each comprising a square of nine grid cells. A sample population, therefore, has a carrying capacity of 9 × 20 . Preliminary simulations with larger values of K did not substantially change the final results but did require simulating a greater number of generations (Appendix S1). All spatial processes  were isotropic, as heterogeneous cost‐surfaces for mate selection and dispersal were not invoked. This provides the opportunity to employ a topologically infinite landscape; a torus topology  of size 0 to K exists at any time in each cell, with K set to 20 (see Appendix S1 for discussion of model sensitivity to K). We initialized the simulations with N = K new‐born individuals per cell with a 50:50 sex ratio. Mating and demographic structure parameters were set to represent a population that was dioecious. Both females and males mate with replacement, and generations were nonoverlapping. We assumed the population growth rate was female‐limited (eq. A variable population (ited eq. : (1)N(t+Nt + 1), a value between 0–1, around a specified mean (m)  eq. . Equatiomean dispersal distance rather than dispersal rates but provide the equivalent values above.For our simulation experiments, we considered three levels of mean dispersal distance . This parameterization constrained dispersal to a stepping‐stone model in two dimensions where mean distance can be directly converted to dispersal rates as has been common in earlier studies Slatkin . For exak‐allele model (k = 10) (see Appendix S1 for discussion of the sensitivity of model results to k). Each individual had a diploid genotype with ten unlinked loci to approximate the number of loci and degree of polymorphism observed in many empirical microsatellite‐based studies. Mutation rate was constant at 10−4 per generation for each allele selection, which is near the mid‐range of mammalian microsatellite mutation rates  disturbance size, (2) disturbance interval; and (3) minimum disturbance severity . Disturbances were arbitrarily square in shape with three levels of size . The place and time of each disturbance was uniformly random. Sufficient events of the specified size were generated to produce a mean interdisturbance interval (at each cell) of either 30, 60, or 120 generations for the three treatment levels. No constraint was imposed on the minimum interval between disturbances. The severity of disturbance effects can vary randomly between cells from 100% down to a prescribed minimum . For any single simulation, disturbance size is held constant. We acknowledge that disturbances commonly occur with intensities or sizes that have a log distribution Cumming . FurtherThe simulations proceeded according to Fig. K. Conversely, the same process took only 12 generations under our scenario with highest dispersal and birth rate . Viable populations might also occur if disturbance size is traded against frequency, and this may be important when considering the generality of our results. However, increasing birth rate beyond 12 will have no effect because: (1) the diversity of source populations does not change in a stepping‐stone model (as used here); and (2) birth rates beyond those used here, even when source populations are very small, will result in a population at carrying capacity at the first generation. Therefore, when considering scale and the application of this general study to particular cases, it is the relativity between carrying capacity and disturbance size that should be kept in mind. To confirm that the disturbance parameters are within a long‐term equilibrium we examined our parameter space using two metrics (T and S) used to define degrees of landscape equilibrium  mediates the sensitivity of population persistence to disturbance size and frequency , howeveHT=(1−(1/2N))tH0. Thus, our underlying demographic‐genetic model “delivers” the expectations of population genetic theory, and the dispersal scenarios that we simulate are sufficiently simple and general that they can be representative of, or relevant to, many real scenarios.While there are no relevant analytical disturbance models for comparison, the basic demographic model used here, when simulated under panmixia, results in patterns of genetic drift expected under Wright's formulation of HT, HS¯, and FST were relatively stable after 4000 generations. Therefore, each simulation was preceded by a 4000 generation burn‐in with a further 1000 generations executed to provide data for analysis. We ran 12 replicates for each simulation resulting in 2916 runs. Replicates differ only in their random number seeds which affect: (1) initial allele assignment; (2) Mendelian genetics and mutation; (3) disturbance time and location; (4) distance and direction of individual dispersal events; and (5) random post‐disturbance survival. We used only 12 replicates per scenario because the large landscapes  resulted in little variation among replicates within treatments. Indeed, the coefficient of variation in FST between replicates (averaged over the last 1000 generations) was, at most, 18% for simulations with large, frequent and severe disturbances with low dispersal distance and low growth rates .Preliminary simulations of 10,000 generations , indicated that l for frequency p of allele i of k. For a given population, heterozygosity was averaged over the number of loci HS¯) was the sum of Hi, weighted by the population size (Ni): The average heterozygosity of populations  were randomly selected for pairwise FST analysis at the end of each simulation, to quantify spatial genetic structure arising from the experiments. Pairwise FST for populations A and B is given by FST(FST/(1–FST) and log‐transformed geographic distance between populations, as suggested by Rousset  or FST , predominantly disturbance size (56% of variance explained)   Fig. C. BecausS¯) Fig. A. For thlts Fig. D.FST, with only mean dispersal distance (MD) explaining greater variation (37%), while disturbance interval (DI) and severity explained 7% and 6% respectively  explained around 9% of variation in simulated ely Fig. D. There ely Fig. D. The efariation 7%, whileFST in recovering populations, and therefore on genetic structure in the presence of disturbance.The least important parameter in our simulations was birth rate (BR) Fig. D. While Increasing in situ survival rates after disturbance (SV) markedly reduced any effect of disturbance on genetic structure, with disturbance having little effect on genetic structure under low severity (SV = 0.85) Fig. E,F. IncrFST/(1–FST) by ln‐distance  DFST/(1–FST (CVFST), measured over the last 1000 generations of the simulation, was strongly affected by disturbance size, which explained around 56% of the variance in this response variable , and the most severe and frequent disturbance (severity of 1 and mean interdisturbance frequency of 30 years), the spatial coefficient of variation in HS increased from 2% where disturbance size was zero, to 54% when disturbance size was 24 cells in width. At the same time, mean HS decreased by 84% from 0.82 to 0.13.Informally, for regimes incorporating large, frequent, and severe disturbances, our model produced a clumped patterns of high and low heterozygosity meditated by dispersal distance Fig. . These pape Fig. , This leDisturbance regimes are critical attributes of ecosystems and can have large effects on community composition Lake . Here, wFST under the propagule pool model  and dispersal capacity is restricted relative to the scale of disturbance. This finding has parallels with ecological research on the scale‐dependence of postdisturbance recovery processes, where the spatial dispersion of survivors and the scaling of colonization ability relative to disturbance area mediate the sensitivity of population distribution to disturbance size and return interval , higher dispersal scenarios imply that founders are drawn from larger, and therefore a more heterogeneous set of source populations, corresponding to the distinction between the HS and FST resulting from disturbance regimes has some important implications for the measurement of neutral genetic patterns and the inference of biological processes. For instance, impacts of dispersal distance on FST were greater under scenarios of large and/or severe disturbance compared to undisturbed populations , but by: (1) changes to overall FST, Mantel r correlations within distance classes   was apparent for undisturbed populations. However, even in IBD models of undisturbed populations, genetic drift will counter spatial patterns generated by gene flow at a certain distance threshold  have been observed empirically in response to fire history in several species of Florida sand skink populations  Fig. D, and , highlThere is considerable scope for greater complexity in representation of key mechanisms in future studies, including representation of ecological, disturbance and genetic processes.Successional dynamics are a well‐documented consequence of disturbance  of the model used in this article following the suggested protocol by (Grimm et al. Click here for additional data file.Appendix S3. Java source code, parameter and input files together with installation instructions for the model used in article.Click here for additional data file.


Using computer simulation we explore the consequences of linkage on the inbreeding load of an equilibrium population, and on the efficiency of purging and the loss of genetic diversity after a reduction in population size. We find that linkage tends to cause increased inbreeding load due to the build up of coupling groups of  recessive deleterious alleles. It also induces associative overdominance at neutral sites but rarely causes increased neutral genetic diversity in equilibrium populations. After a reduction in population size, linkage can cause some delay both for the expression of the inbreeding load and the corresponding purging. However, reasonable predictions can be obtained for the evolution of fitness under inbreeding and purging by using empirical estimates of the inbreeding depression rate. Purging selection against homozygotes for deleterious alleles affects the population’s pedigree. Furthermore, it can slow the loss of genetic diversity compared to that expected from the variance of gametic contributions to the breeding group and even from pedigree inbreeding. Under some conditions, this can lead to a smaller loss of genetic diversity, even below that expected from population size in the absence of selection. The consequences of inbreeding on fitness are increasingly being recognized as a main factor potentially determining the extinction risk of endangered populations and, therefore, as a target to be controlled in conservation programs , but alsConsiderable progress has been attained in the comprehension and prediction of the consequences of genetic purging on average fitness through theoretical analysis  but, so However, selection against recessive alleles induces some positive correlation between individual fitness and heterozygosity at neutral sites, known as associative overdominance  and, undi.e., the neutral prediction for Wright’s inbreeding coefficient fN). Furthermore, we compute the inbreeding expected from pedigrees (fp), and the inbreeding expected taking into account the variance of the number of gametes (Vk) contributed by the individuals of the population to the next generation breeding pool (fVk). Our results allow us to explore the inbreeding load concealed in the populations, its relationship with the population’s genetic diversity, and the mechanisms governing the evolution of both fitness and genetic diversity through generations after the reduction of census size.In this work, we investigate the consequences of linkage on inbreeding depression and purging, and on their impact upon genetic diversity. To achieve this, we use computer simulations to generate populations at the mutation-selection-drift balance for different values of the deleterious effect and dominance coefficient of mutations as well as for different genome lengths. Then, we derive lines that are maintained with reduced census size, and we analyze the consequences of inbreeding on the evolution of fitness and neutral genetic diversity. To disentangle the mechanisms responsible for the consequences of purging on genetic diversity, we track different measures of inbreeding. First, as a reference, we compute the inbreeding expected from the population size in the absence of selection under the classical ideal conditions  balance were obtained by simulating a life cycle consisting of mutation, selection, recombination and reproduction steps for 10,000 generations. Reproduction was panmictic, with selfing allowed. Each simulated haploid genome consisted of consecutive batches of 20 selective sites, followed by a marker neutral site, all along a single conceptual chromosome with length L Morgans. The numbers of neutral and selective sites simulated were nn = 1000 and ns = 20,000, respectively. The overall number of neutral or selective new mutations per generation was Poisson distributed with a mean of 0.1 deleterious mutations per haploid genome and generation, and 0.005 neutral mutations at neutral sites per haploid genome and generation. This implies the same average mutation rate per simulated site for markers and selective sites (5 × 10−6). New mutations were randomly assigned to the individuals and then to random nonsegregating sites. The segregating neutral sites should be interpreted as a sample of neutral marker segregating sites. The simulated selective sites can be interpreted as a small proportion of the actual number of sites where deleterious alleles might occur. However, the number of simulated selective sites was large enough to warrant that there were always nonsegregating sites to locate new deleterious mutations.Base populations of m) with selection coefficient s and coefficient of dominance h, so that the three genotypes  had fitness 1, 1 – hs, and 1 – s, respectively. Individual fitness (wi) was computed as the product of fitness values for all the ns selective sites. To obtain each individual of the next generation, two parents were randomly sampled with replacement from the Nb individuals. The probability of each individual i of being sampled was proportional to its fitness wi. Then, a gamete was produced where the gene copy at the first site was chosen at random out of the two copies in the parent. For each consecutive site, the gene copy contributed to the gamete was sampled from the same chromosome or from the alternative one with probability (1 – c) or c, respectively, where c = 0.5 {1 – exp[−2L/(ns + nn − 1)]} represents the recombination fraction  and genome length (L).At selective sites, wild type alleles (+) mutated to deleterious alleles . In each line, 100 individuals were produced each generation. New mutations were assigned to them and they were used to compute average fitness, as well as gene frequencies. Then, i.e., all individuals had the same probability of being sampled as parents: mutation-drift (MD) scenario]. Pedigrees were saved, and the number of gametes k contributed by each potential breeder to the next generation was recorded to compute its corresponding variance (Vk) each generation.Lines were maintained following the same mutation-selection-recombination-reproduction life cycle as for the base population (MSD scenario), or by avoiding natural selection .Both at the base populations and for the derived reduced size lines, we computed the average fitness and the additive and dominance components of fitness genetic variance . For thet using different approaches:fp) using the tabular procedure  expected on the basis of the variance (Vk) of the number of gametes actually contributed by each individual to the next generation, and computed aspredicted from Wright’s equations using the effective size (where Ne = (4N − 2) / (2 + Vk) (The average inbreeding coefficient of the lines was computed for each generation (2 + Vk) .t relative to that at the base population , equals 1 – ft (where ft stands for Wright’s inbreeding coefficient), we plot Ht/H0 through generations of reduced size against different estimates of the inbreeding coefficient in order to dissect the consequences of selection on genetic diversity.Since, in the absence of natural selection, the expected value of genetic diversity at generation i.e., using the classical neutral equationw0 and wt are the average fitness value at the base population and at t generations with reduced size N, and fN is the corresponding inbreeding coefficient computed from Equation 2. In the above expression, δ is the inbreeding depression rate . For a single site model, or for a multisite model with no linkage disequilibrium, δ equals the inbreeding load B. Therefore, predictions from Equation 4 were obtained by replacing δ with the inbreeding load B of the base population. However, due to the multiplicative nature of fitness across different sites, the inbreeding depression rate in the early generations immediately after the reduction in population size is expected to be smaller (larger) than B when there is positive (negative) linkage disequilibrium between deleterious alleles at the base population. Therefore, predictions were also computed using an estimate of the inbreeding depression rate obtained by solving Equation 4 for δ using the fitness average obtained for t = 3 in the N = 2 lines maintained under the MSD scenario. This estimate of δ, analogous to the estimates that could be experimentally obtained in actual populations, was used to compute additional predictions of the evolution of fitness for N = 10 or N = 50 lines with Equation 4.The evolution of fitness after the reduction of population size was first predicted assuming relaxed selection, fN with the purged inbreeding coefficient tg  approach, by replacing cient gt  at generL = 1) are shown. Intermediate genome lengths gave intermediate results that are shown in Supporting Information, Table S1.B) is very close to the theoretical prediction. Likewise, average fitness (w) and neutral genetic diversity (H) are very close to their corresponding expectations, and linkage disequilibrium is always nonsignificantly different from zero.In the absence of linkage (FR), the observed inbreeding load (L = 5 and L = 10 or for h = 0.2 (results not shown), but is more important for h = 0 and L = 1, particularly for the larger deleterious effect (s = 0.5). This increase of B is accompanied by an increase of coupling linkage disequilibrium (LD) between selective sites (r > 0) that also becomes relevant for h = 0, implying the presence of coupling groups of recessive deleterious alleles.With reduced genome length, however, inbreeding load increases. This increase is only slight for r], which measures associative overdominance, is always positive for h < 0.5 and increases as deleterious effects become more recessive and linkage becomes tighter. It is remarkable that, for small recessive deleterious effects (s = 0.1 and h = 0), this correlation becomes significantly positive even under free recombination. However, a shorter genome leads, in all cases, to reduced genetic diversity (H) in the base population, despite the increase in associative overdominance.The correlation of neutral individual heterozygosity with individual fitness , is plotted in i.e., this figure plots (1 – fVk) vs. fN]. It shows that the expected neutral genetic diversity computed taking into account the variance of gametic contributions (Vk) caused by purging, can be much smaller than under nonpurging . In contrast, the four right-hand panels of Ht/H0vs. fN is not too different from that expected in the absence of purging, given by the diagonal. In fact, although Ht/H0 usually declines at a rate somewhat larger than in the neutral nonpurging model, there is even one tight linkage case  where the decline of neutral genetic diversity is considerably slower than expected under drift alone. This is not observed for the analogous case with larger deleterious effects , probably because there are fewer segregating deleterious alleles and linkage between them is therefore weaker.We have computed the proportion of the genetic diversity of the base population that is expected to persist through the period of maintenance with reduced size taking into account the observed values for fp. Occasionally, purging can cause even slower decline of genetic diversity than expected from population size in the absence of purging , although this was only detected for tight linkage. It should be noted that these observations hold even when drift is so intense that purging is unable to hold back inbreeding depression, as occurs for N = 2. Thus, purging can slow the loss of genetic diversity even in situations in which it is not able to slow the rate of fitness decline.In summary, the loss of genetic diversity due to genetic purging is smaller than expected from i.e., the average fitness of the panmictic base populations shows no appreciable reduction).Our simulation results show that panmictic populations at the MSD balance can conceal larger inbreeding load in the presence of linkage than under free recombination. This is due to the build up of coupling groups of deleterious alleles, and requires the presence of linked segregating sites with deleterious alleles that are substantially recessive. In principle, natural selection against linked additive deleterious alleles is expected to induce negative linkage disequilibrium in finite populations . Howeverh < 0.5). Therefore, it induces a genetic excess for the variance of the gametic contributions to the next generations (Vk), compared to an ideal situation where all individuals have identical fitness. This excess determines the intensity of purging selection, while purging efficiency could be quantified by the reduction it causes of the fitness decline induced by inbreeding. Thus, the per-generation efficiency of purging could be defined as the difference between the per-generation decline expected just from inbreeding and that realized under inbreeding and purging . Therefore, according to Fisher’s theorem of natural selection, in the absence of drift, the efficiency of purging per generation should equal the additive component of the increase in Vk caused by inbreeding .After a reduction in population size, inbreeding exposes the recessive component of deleterious effects . In our multiplicative fitness model, the average fitness at generation t (with inbreeding ft) is:wA stands for the fitness of individuals al locus A, and Cov stands for covariance. When A and C are associated in a coupling group, the covariance term is positive, so that the expected fitness at generation t is larger than in the absence of linkage disequilibrium, and the realized rate in inbreeding depression is therefore smaller. This explains why the larger value of B maintained in the presence of linkage, does not translate into a higher rate of fitness decline in the short–medium term, since the full expression of the inbreeding load requires the progressive destruction of the initial linkage disequilibrium due to recombination. Nevertheless, purging can become less efficient in small genomes for values of Nd close to 1, due to background selection  to selected sites with Nhs ≤ 4, although inspection of their figure 1f reveals that increased neutral genetic diversity also requires that Nhs is much smaller than Ns  and, of course, it requires Ns > 1. Our h = 0 cases fulfill these conditions regarding Nhs and Ns, but, even for L = 1, each neutral mutation had one recessive deleterious allele to each side at an average distance about 5 × 10−4 M, i.e., about 50 times larger than in the case analyzed by Selection against partially recessive deleterious alleles also affects the neutral genetic diversity expected at the MSD balance. In principle, in the absence of dominance, a reduction of neutral diversity is expected from natural selection, due to a reduction in the effective size . Howeveri.e., associative overdominance. To understand the reasons for this association, it is convenient to consider individual inbreeding at the base MSD balance population, as it could be defined by reference to any arbitrary generation in the recent past. Then it is obvious that individuals with larger inbreeding are expected to have both smaller fitness (due to inbreeding depression) and smaller neutral genetic diversity, which prompts a positive correlation between the two latter variables . Thus, the fact that associative overdominance is observed even in the absence of linkage, should be ascribed to the association between individual heterozygosity on neutral and selected sites caused by mating of related individuals in finite populations. Furthermore, we observe that r increases for reduced genome length, because linkage implies an association for the heterozygosity at different sites in the offspring of each single mating. Note, however, that associative overdominance does not imply increased neutral genetic diversity. These observations are in agreement with It is possible that the associative overdominance is ineffective as a mechanism for the maintenance of genetic variabilities, except for some special cases such as inversion chromosome and semi-isolated local populations. Its real importance lies in the fact that it is probably responsible for most of the observed superiority of heterozygotes. In fact, it could be more illuminating to consider associative overdominance not as a mechanism at all, but just as a side effect created by selection when it is constrained to operate mostly against homozygotes: an illusion of advantage for heterozygotes that, occasionally, concurs with some increase of neutral diversity. The dependence of natural selection against recessive alleles on inbreeding is known to be able to induce some increase in neutral genetic diversity at equilibrium populations, as it imposes restrictions on the evolution of genealogical relationships between individuals and of the probability of identity by descent at neutral sites closely linked to selected ones. Nevertheless, the conditions for this phenomenon, including close linkage and largely recessive deleterious effects, are so restrictive that they were never met in our panmictic base populations at the MSD balance, where neutral genetic diversity was never larger than that expected in the neutral model and did not increase with associative overdominance.Despite this, we found that natural selection against  recessive deleterious alleles produces in the base populations a positive association between average fitness and heterozygosity at neutral sites, h = 0. In fact, the delay of fp compared to fVk (fVk, considering long-term contributions rather than one generation contributions, would be larger than that given by Equation 3 due to the heritable component of the variance of gametic contributions.However, as a drastic reduction of population size induces a high inbreeding rate, it also increases the magnitude of the negative covariance between identity by descent and fitness. Therefore, as purging acts upon fitness, it can slow the progress of pedigree inbreeding below that expected from the variance of gametic contributions, as observed for d to fVk  should bfp compared to fVk implies that purging against recessive deleterious alleles produces an advantage for individuals showing smaller average coancestry, and, therefore, tends to equalize the contributions of the different founding individuals to future generations in a way that is, to some extent, analogous to the minimum coancestry strategy proposed in conservation programs to reduce the loss of genetic diversity in endangered populations (This delay of ulations .fp, this additional mechanism should involve some equalization of the contribution to future generations of the two haploid sets of neutral alleles for each founder individual. Again, to visualize this mechanism, we can think of a situation where the two haploid sets of each single founder individual carry different recessive deleterious alleles. Then purging, when preventing the overrepresentation in future generations for each ancestral deleterious allele, will favor equal representation of both haploid sets for selected sites, preserving genetic diversity for neutral sites linked to them.Furthermore, for neutral sites closely linked to selected ones , the losThe more common consequence of the two equalization processes described above is a loss of genetic diversity smaller than would be expected from standard selection of similar intensity but, usually, around that expected from genetic drift in the absence of selection. As this loss of genetic diversity can be smaller than that expected from pedigree inbreeding, this process could be responsible for the slowed loss of genetic diversity that has often been observed experimentally (In fact, the genetic diversity at the neutral sites can occasionally decline during purging even more slowly than expected from the population size in the absence of selection, although this occurred under restrictive conditions, involving tight linkage . Thus, tThus, two main lessons should be drawn from the above analysis that can be useful to conservation practices. The first concerns fitness inbreeding depression. Although, for small genome lengths, the large ancestral population can conceal larger inbreeding load than under free recombination, this does not imply increased rates of inbreeding depression in the short term, so that the inbreeding depression rate can be empirically estimated from short-term inbreeding depression, and the evolution of fitness after a reduction in population size can still be reasonably predicted from IP theory. Obviously, this depends on the availability of a reliable estimate of the purging coefficient . NeverthThe second lesson has to do with the decision about whether or not managing the gametic contributions. This management can be as simple as the equalization of the number of offspring contributed by each parent to the next generation breeding pool, or can be intended to minimize the average coancestry in the offspring in order to equalize the contributions of the founder individuals , and als