Estimation Of Population Genetic Parameters Research Articles

Influence of molecular marker type on estimating effective population size and other genetic parameters in a critically endangered parrot

AbstractGenetics is a fast‐moving field, and for conservation practitioners or ecologists, it can be bewildering. The choice of marker used in studies is fundamental; in the literature, preference has recently shifted from microsatellites to single nucleotide polymorphism (SNP) loci. Understanding how marker type affects estimates of population genetic parameters is important in the context of conservation, especially because the accuracy of estimates has a bearing on the actions taken to protect threatened species. We compare parameter estimates between seven microsatellites, 3761 SNP loci, and a random subset of 100 SNPs for the exact same 324 individual swift parrots, Lathamus discolor, and also use 457 additional samples from subsequent years to compare SNP estimates. Both marker types estimated a lower HO than HE. We show that microsatellites and SNPs mainly indicate a lack of spatial genetic structure, except when a priori collection locations were used on the SNP data in a discriminant analysis of principal components (DAPC). The 100‐SNP subset gave comparable results to when the full dataset was used. Estimates of effective population size (Ne) were comparable between markers when the same individuals were considered, but SNPs had narrower confidence intervals. This is reassuring because conservation assessments that rely on population genetic estimates based on a few microsatellites are unlikely to be nullified by the general shift toward SNPs in the literature. However, estimates between markers and datasets varied considerably when only adult samples were considered; hence, including samples of all age groups is recommended to be used when available. The estimated Ne was higher for the full SNP dataset (2010–2019) than the smaller comparison data (2010–2015), which might be a better reflection of the species status. The lower precision of microsatellites may not necessarily be a barrier for most conservation applications; however, SNPs will improve confidence limits, which may be useful for practitioners.

NgsJulia: population genetic analysis of next-generation DNA sequencing data with Julia language

A sound analysis of DNA sequencing data is important to extract meaningful information and infer quantities of interest. Sequencing and mapping errors coupled with low and variable coverage hamper the identification of genotypes and variants and the estimation of population genetic parameters. Methods and implementations to estimate population genetic parameters from sequencing data available nowadays either are suitable for the analysis of genomes from model organisms only, require moderate sequencing coverage, or are not easily adaptable to specific applications. To address these issues, we introduce ngsJulia, a collection of templates and functions in Julia language to process short-read sequencing data for population genetic analysis. We further describe two implementations, ngsPool and ngsPloidy, for the analysis of pooled sequencing data and polyploid genomes, respectively. Through simulations, we illustrate the performance of estimating various population genetic parameters using these implementations, using both established and novel statistical methods. These results inform on optimal experimental design and demonstrate the applicability of methods in ngsJulia to estimate parameters of interest even from low coverage sequencing data. ngsJulia provide users with a flexible and efficient framework for ad hoc analysis of sequencing data.ngsJulia is available from: https://github.com/mfumagalli/ngsJulia.

NgsJulia: population genetic analysis of next-generation DNA sequencing data with Julia language.

A sound analysis of DNA sequencing data is important to extract meaningful information and infer quantities of interest. Sequencing and mapping errors coupled with low and variable coverage hamper the identification of genotypes and variants and the estimation of population genetic parameters. Methods and implementations to estimate population genetic parameters from sequencing data available nowadays either are suitable for the analysis of genomes from model organisms only, require moderate sequencing coverage, or are not easily adaptable to specific applications. To address these issues, we introduce ngsJulia, a collection of templates and functions in Julia language to process short-read sequencing data for population genetic analysis. We further describe two implementations, ngsPool and ngsPloidy, for the analysis of pooled sequencing data and polyploid genomes, respectively. Through simulations, we illustrate the performance of estimating various population genetic parameters using these implementations, using both established and novel statistical methods. These results inform on optimal experimental design and demonstrate the applicability of methods in ngsJulia to estimate parameters of interest even from low coverage sequencing data. ngsJulia provide users with a flexible and efficient framework for ad hoc analysis of sequencing data.ngsJulia is available from: https://github.com/mfumagalli/ngsJulia.

Re-evaluating Coho salmon (Oncorhynchus kisutch) conservation units in Canada using genomic data.

Conservation units (CUs) are important tools for supporting the implementation of standardized management practices for exploited species. Following the adoption of the Wild Salmon Policy in Canada, CUs were defined for Pacific salmon based on characteristics related to ecotype, life history and genetic variation using microsatellite markers as indirect measures of local adaptation. Genomic data sets have the potential to improve the definition of CUs by reducing variance around estimates of population genetic parameters, thereby increasing the power to detect more subtle patterns of population genetic structure and by providing an opportunity to incorporate adaptive information more directly with the identification of variants putatively under selection. We used one of the largest genomic data sets recently published for a nonmodel species, comprising 5662 individual Coho salmon (Oncorhynchus kisutch) from 149 sampling locations and a total of 24,542 high-quality SNPs obtained using genotyping-by-sequencing and mapped to the Coho salmon reference genome to (1) evaluate the current delineation of CUs for Coho in Canada and (2) compare patterns of population structure observed using neutral and outlier loci from genotype-environment association analyses to determine whether separate CUs that capture adaptive diversity are needed. Our results reflected CU boundaries on the whole, with the majority of sampling locations managed in the same CU clustering together within genetic groups. However, additional groups that are not currently represented by CUs were also uncovered. We observed considerable overlap in the genetic clusters identified using neutral or candidate loci, indicating a general congruence in patterns of genetic variation driven by local adaptation and gene flow in this species. Consequently, we suggest that the current CU boundaries for Coho salmon are largely well-suited for meeting the Canadian Wild Salmon Policy's objective of defining biologically distinct groups, but we highlight specific areas where CU boundaries may be refined.

Perspectives in plant evolutionary genetics: A field guide in 15 “easy steps” to modern tools in evolutionary genetics and genomics

Plant genomes contain huge troves of information, and nowadays molecular tools to analyze genomes are less expensive and keep improving. In this review, we aimed to produce a “roadmap” to take advantage of this explosion of molecular methods and opportunities. We explain how to decide which strategies are adequate for a given evolutionary or taxonomic problem by describing 15 possible (and in some cases nonconsecutive) steps to take advantage of all the genomic resources drawing from the ever-increasing studies. We describe how to obtain an adequate genome sequence given our study species and objectives and discuss if we need to also obtain a transcriptome and additional “omic” data ( i.e. , proteome, metabolome, epigenome, microbiome). We analyze what is needed to conduct population genomics studies in terms of genomic methods and sampling strategies and discuss the pangenome concept. In addition, we present some considerations about how to estimate population genetics parameters and how to analyze geographic differentiation, inbreeding and gene flow. We examine ideas and methods on how to estimate natural selection and local adaptation, how to detect candidate genes, how coalescent analyses can help in these studies, the importance of genomic information for conservation studies and to understand adaptability to climate change. We assess the use of these methods in domestication studies and in understanding how form and function can be inferred from genes; likewise, how to use the genomic information for improvement of cultivated plants. We also review how can we use these methods in phylogenomic studies.

Fast and accurate estimation of multidimensional site frequency spectra from low-coverage high-throughput sequencing data.

BackgroundThe site frequency spectrum summarizes the distribution of allele frequencies throughout the genome, and it is widely used as a summary statistic to infer demographic parameters and to detect signals of natural selection. The use of high-throughput low-coverage DNA sequencing data can lead to biased estimates of the site frequency spectrum due to high levels of uncertainty in genotyping.ResultsHere we design and implement a method to efficiently and accurately estimate the multidimensional joint site frequency spectrum for large numbers of haploid or diploid individuals across an arbitrary number of populations, using low-coverage sequencing data. The method maximizes a likelihood function that represents the probability of the sequencing data observed given a multidimensional site frequency spectrum using genotype likelihoods. Notably, it uses an advanced binning heuristic paired with an accelerated expectation-maximization algorithm for a fast and memory-efficient computation, and can generate both unfolded and folded spectra and bootstrapped replicates for haploid and diploid genomes. On the basis of extensive simulations, we show that the new method requires remarkably less storage and is faster than previous implementations whilst retaining the same accuracy. When applied to low-coverage sequencing data from the fungal pathogen Neonectria neomacrospora, results recapitulate the patterns of population differentiation generated using the original high-coverage data.ConclusionThe new implementation allows for accurate estimation of population genetic parameters from arbitrarily large, low-coverage datasets, thus facilitating cost-effective sequencing experiments in model and non-model organisms.

Evaluation of methods for estimating coalescence times using ancestral recombination graphs.

The ancestral recombination graph is a structure that describes the joint genealogies of sampled DNA sequences along the genome. Recent computational methods have made impressive progress toward scalably estimating whole-genome genealogies. In addition to inferring the ancestral recombination graph, some of these methods can also provide ancestral recombination graphs sampled from a defined posterior distribution. Obtaining good samples of ancestral recombination graphs is crucial for quantifying statistical uncertainty and for estimating population genetic parameters such as effective population size, mutation rate, and allele age. Here, we use standard neutral coalescent simulations to benchmark the estimates of pairwise coalescence times from 3 popular ancestral recombination graph inference programs: ARGweaver, Relate, and tsinfer+tsdate. We compare (1) the true coalescence times to the inferred times at each locus; (2) the distribution of coalescence times across all loci to the expected exponential distribution; (3) whether the sampled coalescence times have the properties expected of a valid posterior distribution. We find that inferred coalescence times at each locus are most accurate in ARGweaver, and often more accurate in Relate than in tsinfer+tsdate. However, all 3 methods tend to overestimate small coalescence times and underestimate large ones. Lastly, the posterior distribution of ARGweaver is closer to the expected posterior distribution than Relate's, but this higher accuracy comes at a substantial trade-off in scalability. The best choice of method will depend on the number and length of input sequences and on the goal of downstream analyses, and we provide guidelines for the best practices.

NgsJulia: population genetic analysis of next-generation DNA sequencing data with Julia language

A sound analysis of DNA sequencing data is important to extract meaningful information and infer quantities of interest. Sequencing and mapping errors coupled with low and variable coverage hamper the identification of genotypes and variants and the estimation of population genetic parameters. Methods and implementations to estimate population genetic parameters from sequencing data available nowadays either are suitable for the analysis of genomes from model organisms only, require moderate sequencing coverage, or are not easily adaptable to specific applications. To address these issues, we introduce ngsJulia, a collection of templates and functions in Julia language to process short-read sequencing data for population genetic analysis. We further describe two implementations, ngsPool and ngsPloidy, for the analysis of pooled sequencing data and polyploid genomes, respectively. Through simulations, we illustrate the performance of estimating various population genetic parameters using these implementations, using both established and novel statistical methods. These results inform on optimal experimental design and demonstrate the applicabil- ity of methods in ngsJulia to estimate parameters of interest even from low coverage sequencing data. ngsJulia provide users with a flexible and efficient framework for ad hoc analysis of sequencing data.ngsJulia is available from: https://github.com/mfumagalli/ngsJulia

Sporophyte Stage Genes Exhibit Stronger Selection Than Gametophyte Stage Genes in Haplodiplontic Giant Kelp

Macrocystis pyrifera (giant kelp), a haplodiplontic brown macroalga that alternates between a macroscopic diploid (sporophyte) and a microscopic haploid (gametophyte) phase, provides an ideal system to investigate how ploidy background affects the evolutionary history of a gene. In M. pyrifera, the same genome is subjected to different selective pressures and environments as it alternates between haploid and diploid life stages. We assembled M. pyrifera gene models using available expression data and validated 8,292 genes models using the model alga Ectocarpus siliculosus. Differential expression analysis identified gene models expressed in either or both the haploid and diploid life stages while functional annotation identified processes enriched in each stage. Genes expressed preferentially or exclusively in the gametophyte stage were found to have higher nucleotide diversity (π = 2.3 × 10–3 and 2.8 × 10–3, respectively) than those for sporophytes (π = 1.1 × 10–3 and 1 × 10–3, respectively). While gametophyte-biased genes show faster sequence evolution, the sequence evolution exhibits less signatures of adaptations when compared to sporophyte-biased genes. Our findings contrast the standing masking hypothesis, which predicts higher standing genetic variation at the sporophyte stage, and support the strength of expression theory, which posits that genes expressed more strongly are expected to evolve slower. We argue that the sporophyte stage undergoes more stringent selection compared with the gametophyte stage, which carries a heavy genetic load associated with broadcast spawning. Furthermore, using whole-genome sequencing, we confirm the strong population structure in wild M. pyrifera populations previously established using microsatellite markers, and estimate population genetic parameters, such as pairwise genetic diversity and Tajima’s D, important for conservation and domestication of M. pyrifera.

Select and Sequence of a Segregating Sugar Beet Population Provides Genomic Perspective of Host Resistance to Seedling Rhizoctonia solani Infection.

Understanding the genetic basis of polygenic traits is a major challenge in agricultural species, especially in non-model systems. Select and sequence (SnS) experiments carried out within existing breeding programs provide a means to simultaneously identify the genomic background of a trait while improving the mean phenotype for a population. Using pooled whole genome sequencing (WGS) of selected and unselected bulks derived from a synthetic outcrossing sugar beet population EL57 (PI 663212), which segregates for seedling rhizoctonia resistance, we identified a putative genomic background involved in conditioning a resistance phenotype. Population genomic parameters were estimated to measure fixation (He), genome divergence (FST), and allele frequency changes between bulks (DeltaAF). We report on the genome wide patterns of variation resulting from selection and highlight specific genomic features associated with resistance. Expected heterozygosity (He) showed an increased level of fixation in the resistant bulk, indicating a greater selection pressure was applied. In total, 1,311 biallelic loci were detected as significant FST outliers (p < 0.01) in comparisons between the resistant and susceptible bulks. These loci were detected in 206 regions along the chromosomes and contained 275 genes. We estimated changes in allele frequency between bulks resulting from selection for resistance by leveraging the allele frequencies of an unselected bulk. DeltaAF was a more stringent test of selection and recovered 186 significant loci, representing 32 genes, all of which were also detected using FST. Estimates of population genetic parameters and statistical significance were visualized with respect to the EL10.2 physical map and produced a candidate gene list that was enriched for function in cell wall metabolism and plant disease resistance, including pathogen perception, signal transduction, and pathogen response. Specific variation associated with these genes was also reported and represents genetic markers for validation and prediction of resistance to Rhizoctonia. Select and sequence experiments offer a means to characterize the genetic base of sugar beet, inform selection within breeding programs, and prioritize candidate variation for functional studies.

Genetic characterization of F0 outbred and F1 inbred Swiss albino mice using microsatellite markers and their performance evaluation

Swiss albino mice have been widely utilized in various biological researches worldwide. Phenotypic and fitness related traits of F0 and F1 inbred mice were estimated on 918 and 707 individual offsprings, respectively. The influence of fixed effects (litter size and sex) on birth weight (BW), weaning weight (WW) and adult body weight (ABW) in both the generations were found to be statistically significant. Genetic characterization of F0 outbred and the F1 inbred strain of Swiss albino mice were evaluated by using 10 microsatellites markers. The results indicated that total number of alleles per locus ranged from 3 (D2Mit61, D3Mit55, D8Mit14, D9Mit27, D10Mit180, D11Mit167) to 4 (D1Mit15, D2Mit51, D5Mit18, D7Mit323) in F0 and F1 inbred population, with a mean value of 3.4 indicating polymorphism in all 10 loci. The mean of effective number of alleles was 2.935 and 2.733 in F0 and F1 population, respectively. Estimates of the FIS ranged from 0.139 (D10Mit180) to 0.999 (D9Mit27); and from 0.109 (D3Mit55) to 0.679 (D2Mit51) in F0 and F1 inbred population, respectively. The estimated mean markerbased FIS was 0.294 and 0.372 in F0 and F1 populations, respectively. The mean values of observed heterozygosity (Ho) and expected heterozygosity (He) were 0.460 and 0.654, respectively for F0 and 0.390 and 0.627, respectively for F1 inbred mice population. Slight reduction in heterozygosity and 7.8% increase in inbreeding coefficient were observed in F1 inbred in comparison to F0 population. The results suggested that genome wide microsatellite genotyping might be more useful for accurate measuring and reliable estimation of population genetic parameters and inbreeding coefficient.

Genome-scale data resolves the timing of divergence in Joshua trees.

Joshua trees (Yucca brevifolia and Y. jaegeriana) and their yucca moth pollinators (Tegeticula synthetica and T. antithetica) are a model system for studies of plant-pollinator coevolution and, they are thought to be one of the only cases in which there is compelling evidence for cospeciation driven by coevolution. Previous work attempted to evaluate whether divergence between the plant and their pollinators was contemporaneous. That work concluded that the trees diverged more than 5 million years ago-well before the pollinators. However, clear inferences were hampered by a lack of data from the nuclear genome and low genetic variation in chloroplast genes. As a result, divergence times in the trees could not be confidently estimated. We present an analysis of whole chloroplast genome sequence data and RADseq data from >5000 loci in the nuclear genome. We developed a molecular clock for the Asparagales and the Agavoideae using multiple fossil calibration points. Using Bayesian inference, we produced new estimates for the age of the genus Yucca and for Joshua trees. We used calculated summary statistics describing genetic variation and used coalescent-based methods to estimate population genetic parameters. We find that the Joshua trees are moderately genetically differentiated, but that they diverged quite recently (~100-200 kya), and much more recently than their pollinators. The results argue against the notion that coevolution directly contributed to speciation in this system, suggesting instead that coevolution with pollinators may have reinforced reproductive isolation following initial divergence in allopatry.

Evaluating the genetic diversity in two tropical leguminous trees, Dalbergia cochinchinensis and D. nigrescens, in lowland forests in Cambodia and Thailand using MIG-seq.

It is vital to measure the levels of genetic diversity and differentiation between populations in a species to understand the current genetic structure and evolution of the species. Here, MIG-seq (multiplexed inter-simple sequence repeat genotyping by sequencing) was employed to assess the genetic variation in two tropical leguminous tree species, Dalbergia cochinchinensis and D. nigrescens, in Cambodia and Thailand. Sequence data for 255-618 loci, each with an approximate length of 100 bp, were obtained, and the nucleotide diversity, Tajima's D and FST were computed. The estimates calculated from the data obtained by MIG-seq were compared to those obtained by Sanger sequencing of nine nuclear coding genes in D. cochinchinensis in our previous study. The nucleotide diversity at the MIG-seq loci was slightly higher than that at silent sites in the coding loci, whereas the FST values at the MIG-seq loci were generally lower than those at the coding loci, although the differences were not significant. Moreover, nucleotide diversities within populations of the two species were similar to each other, at approximately 0.005. Three and four population clusters were genetically recognized in D. cochinchinensis and D. nigrescens, respectively. Although the populations were differentiated from each other, the levels of differentiation among them, as measured by FST, were higher in D. cochinchinensis than in D. nigrescens. This indicates higher levels of gene flow between the populations in the latter species. We recommend using MIG-seq for quick surveys of genetic variation because it is cost-effective and results in smaller variance in the estimates of population genetic parameters.

Populációgenetikai paraméterek, tenyészértékek, fenotípusos és genetikai trendek limousin tehenek első ellési életkorára

Some environmental effects, population genetic parameters, breeding value of Limousin breeding bulls, also phenotypic and genetic trends in the age at first calving (AFC) of cows between 1992 and 2013 were estimated. Data were served by the Limousin and Blonde d’Aquitaine Breeders Association, in Hungary. The study was extended to three herds and 1157 cows. GLM method was used for the study of different effects, the BLUP animal model for estimation of population genetic parameters and breeding values (BV), and one-way linear regression analysis for trend calculations. The overall mean value of the AFC was estimated to be 34.7±0.4 months. The contribution of the evaluated factors to the phenotype was as follows: herd 73.51%, birth year of cow 13.02%, sire 6.74%, birth season of cow 1.62%. The heritability of AFC proved to be low (h2 = 0.08±0.07 and h2 = 0.01±0.04). There were relatively small differences in the estimated BV of the studied sires for the AFC. Based on the phenotypic trend calculation, the AFC of cows decreased by an average of 0.33 months per year, however no significant change was found in the genetic trend during the study period.

Detecting and Quantifying Natural Selection at Two Linked Loci from Time Series Data of Allele Frequencies with Forward-in-Time Simulations.

Recent advances in DNA sequencing techniques have made it possible to monitor genomes in great detail over time. This improvement provides an opportunity for us to study natural selection based on time serial samples of genomes while accounting for genetic recombination effect and local linkage information. Such time series genomic data allow for more accurate estimation of population genetic parameters and hypothesis testing on the recent action of natural selection. In this work, we develop a novel Bayesian statistical framework for inferring natural selection at a pair of linked loci by capitalising on the temporal aspect of DNA data with the additional flexibility of modeling the sampled chromosomes that contain unknown alleles. Our approach is built on a hidden Markov model where the underlying process is a two-locus Wright-Fisher diffusion with selection, which enables us to explicitly model genetic recombination and local linkage. The posterior probability distribution for selection coefficients is computed by applying the particle marginal Metropolis-Hastings algorithm, which allows us to efficiently calculate the likelihood. We evaluate the performance of our Bayesian inference procedure through extensive simulations, showing that our approach can deliver accurate estimates of selection coefficients, and the addition of genetic recombination and local linkage brings about significant improvement in the inference of natural selection. We also illustrate the utility of our method on real data with an application to ancient DNA data associated with white spotting patterns in horses.

An empirical comparison of population genetic analyses using microsatellite and SNP data for a species of conservation concern

BackgroundUse of genomic tools to characterize wildlife populations has increased in recent years. In the past, genetic characterization has been accomplished with more traditional genetic tools (e.g., microsatellites). The explosion of genomic methods and the subsequent creation of large SNP datasets has led to the promise of increased precision in population genetic parameter estimates and identification of demographically and evolutionarily independent groups, as well as questions about the future usefulness of the more traditional genetic tools. At present, few empirical comparisons of population genetic parameters and clustering analyses performed with microsatellites and SNPs have been conducted.ResultsHere we used microsatellite and SNP data generated from Gunnison sage-grouse (Centrocercus minimus) samples to evaluate concordance of the results obtained from each dataset for common metrics of genetic diversity (HO, HE, FIS, AR) and differentiation (FST, GST, DJost). Additionally, we evaluated clustering of individuals using putatively neutral (SNPs and microsatellites), putatively adaptive, and a combined dataset of putatively neutral and adaptive loci. We took particular interest in the conservation implications of any differences. Generally, we found high concordance between microsatellites and SNPs for HE, FIS, AR, and all differentiation estimates. Although there was strong correlation between metrics from SNPs and microsatellites, the magnitude of the diversity and differentiation metrics were quite different in some cases. Clustering analyses also showed similar patterns, though SNP data was able to cluster individuals into more distinct groups. Importantly, clustering analyses with SNP data suggest strong demographic independence among the six distinct populations of Gunnison sage-grouse with some indication of evolutionary independence in two or three populations; a finding that was not revealed by microsatellite data.ConclusionWe demonstrate that SNPs have three main advantages over microsatellites: more precise estimates of population-level diversity, higher power to identify groups in clustering methods, and the ability to consider local adaptation. This study adds to a growing body of work comparing the use of SNPs and microsatellites to evaluate genetic diversity and differentiation for a species of conservation concern with relatively high population structure and using the most common method of obtaining SNP genotypes for non-model organisms.

The Early Peopling of the Philippines based on mtDNA

Despite the efforts made to reconstruct the history of modern humans, there are still poorly explored regions that are key for understanding the phylogeography of our species. One of them is the Philippines, which is crucial to unravel the colonization of Southeast Asia and Oceania but where little is known about when and how the first humans arrived. In order to shed light into this settlement, we collected samples from 157 individuals of the Philippines with the four grandparents belonging to the same region and mitochondrial variants older than 20,000 years. Next, we analyzed the hypervariable I mtDNA region by approximate Bayesian computation based on extensive spatially explicit computer simulations to select among several migration routes towards the Philippines and to estimate population genetic parameters of this colonization. We found that the colonization of the Philippines occurred more than 60,000 years ago, with long-distance dispersal and from both north and south migration routes. Our results also suggest an environmental scenario especially optimal for humans, with large carrying capacity and population growth, in comparison to other regions of Asia. In all, our study suggests a rapid expansion of modern humans towards the Philippines that could be associated with the establisment of maritime technologies and favorable environmental conditions.

DEVELOPMENT OF MICROSATELLITE MARKERS FOR Balfourodendron riedelianum (Engl.) Engl. (PAU MARFIM - IVORY TREE): AN ENDANGERED HIGH VALUE TROPICAL TREE (SCIENTIFIC NOTE)

Pressure on tropical forests by agriculture and livestock expansion, frequently leads to highly fragmented and isolated populations. Limited gene fow drives increased drift and genetic differentiation among populations, ultimately reducing the overall genetic diversity of forest tree species. Balforoudendron riedelianum (Engl.) Engl., commonly known as pau marfm (ivory tree), a valuable Brazilian hardwood tree used in carpentry and building, is currently endangered due to logging and forest fragmentation. Information on genetic diversity and structure of remnants populations is necessary to support its conservation and sustainable management. Microsatellite markers are an effective tool for understanding and quantifying the effects of fragmentation on genetic diversity. Seven microsatellite markers were developed and validated using a sample of 98 individuals. The number of alleles per locus ranged from 3 to 25, the observed and expected heterozygosities from 0.051 to 0.909 and 0.050 to 0.930, respectively, the fxation index corrected for null alleles from 0.036 to 1.0 and all markers were found in linkage equilibrium. This microsatellite marker set is suitable to estimate population genetic parameters in support of sustainable management and conservation, and to assess relatedness and parentage in breeding populations.

Phylogeography of sand‐burrowing amphipods (Haustoriidae) supports an ancient suture zone in the Gulf of Mexico

AbstractAimTo evaluate the impact of a proposed ancient suture zone in the Gulf of Mexico on the distribution and molecular diversity of dispersal‐limited, sand‐burrowing amphipods of the genera Haustorius and Lepidactylus (Haustoriidae: Amphipoda).LocationGulf of Mexico, USA and Mexico.MethodsPhylogenetic and population genetic analyses were performed using mitochondrial (COI and 16S) and nuclear (18S and 28S) data from 93 amphipod individuals from 16 sites across the Gulf of Mexico. Bayesian and ML phylogenies were constructed for all genes, divergence times were estimated using a molecular clock for COI (0.007–0.013 subs./site per Myr), and four species delimitation methods were used to identify operational taxonomic units (OTUs) within each amphipod species. The mitochondrial COI gene was used to construct haplotype networks and estimate population genetic parameters to evaluate historical changes in effective population sizes.ResultsDeep divergences (most estimated to be &gt;4 Ma) were uncovered between sister clades of both amphipod genera on either side of the Mississippi River as well as within Lepidactylus triarticulatus where each sample site was found to harbour a unique genetic lineage. Two cryptic OTUs of L. triarticulatus were identified living sympatrically at Pass Christian, Mississippi. Two distinct OTUs representing western and eastern Haustorius galvezi clades were identified along the Texas and Mexico coastlines with abutting ranges. Population genetic results show some support for recent population expansions for western Gulf OTUs, while eastern Gulf OTUs may have suffered population bottlenecks in the past.Main conclusionsDivergences between sister species of sand‐burrowing amphipods exceeds the timing of previous vicariant hypotheses. The split appears to be consistent with Miocene sedimentation levels from the Mississippi River acting as an east–west barrier to gene flow in the Gulf of Mexico. Given their strong population structure and cryptic diversity, haustoriid amphipods are ideal model organisms for studying open coast biogeography.

Selection for improved white spot syndrome virus resistance increased larval survival and growth rate of Pacific Whiteleg shrimp, Liptopenaeus vannamei

Outbreaks of contagious diseases, including White spot syndrome virus (WSSV), occur more frequently due to environment changes and as commercial shrimp production becomes intensified. The over-arching aim of this study was to examine new traits to improve disease resistance of Whiteleg shrimp, Liptopenaeus vannamei, to WSSV. Specifically, we made a compressive evaluation of the breeding population to determine a suitable selection criterion for improved WSSV resistance. To achieve this objective, we analysed five traits (viral titre, WSSV resistance, larval survival, body weight and standard length) recorded for 120,000 individual shrimps that were offspring of 228 sires and 300 dams produced over two generations of selection in 2017 and 2018. Our restricted maximum likelihood mixed model analysis showed that there is additive genetic variation in viral copy number (or viral titre, viral load) with the heritability that equals 0.18 ± 0.02. Viral titre displayed a moderate and negative genetic correlation with WSSV resistance (rg = −0.55). These results suggest that viral titre can be used as a selection criterion to improve WSSV resistance, but selection for decreased viral titre (i.e., increased resistance) may not capture all genetic expression in WSSV resistance. In addition to the estimation of population genetic parameters, we evaluated direct response to selection for increased WSSV resistance, which was measured as differences in estimated breeding values between the high and low resistant lines. The direct genetic gain achieved for WSSV resistance averaged 12.9% after one generation of selection in this Whiteleg shrimp population. The selection program also resulted in positive impacts on growth and larval survival by 7% and 17%, respectively. There is abundant genetic variation in WSSV resistance (h2 = 0.19–0.27), suggesting that the tested Whiteleg shrimp population will continue to respond to future selection. Collectively, the results obtained in our study provide important information to assist the design and implementation of genetic improvement programs for disease traits in aquaculture species, including L. vannamei.