Population Genetic Methods Research Articles

Assessment of drivers of spatial genetic variation of a ground-dwelling bird species and its implications for conservation.

In modern wildlife ecology, spatial population genetic methods are becoming increasingly applied. Especially for animal species in fragmented landscapes, preservation of gene flow becomes a high priority target in order to restore genetic diversity and prevent local extinction. Within Central Europe, the Alps represent the core distribution area of the black grouse, Lyrurus tetrix. At its easternmost Alpine range, events of subpopulation extinction have already been documented in the past decades. Molecular data combined with spatial analyses can help to assess landscape effects on genetic variation and therefore can be informative for conservation management. Here, we addressed whether the genetic pattern of the easternmost Alpine black grouse metapopulation system is driven by isolation by distance or isolation by resistance. Correlative ecological niche modeling was used to assess geographic distances and landscape resistances. We then applied regression‐based approaches combined with population genetic analyses based on microsatellite data to disentangle effects of isolation by distance and isolation by resistance among individuals and subpopulations. Although population genetic analyses revealed overall low levels of genetic differentiation, the ecological niche modeling showed subpopulations to be clearly delimited by habitat structures. Spatial genetic variation could be attributed to effects of isolation by distance among individuals and isolation by resistance among subpopulations, yet unknown effects might factor in. The easternmost subpopulation was the most differentiated, and at the same time, immigration was not detected; hence, its long‐term survival might be threatened. Our study provides valuable insights into the spatial genetic variation of this small‐scale metapopulation system of Alpine black grouse.

Genetic Variability, Population Structure, and Relatedness Analysis of Meagre Stocks as an Informative Basis for New Breeding Schemes

This study evaluates the genetic diversity of different meagre broodstocks sampled in Greece. A multiplex of twelve microsatellite markers was used to genotype 946 fish from eleven stocks and batches used for broodstock selection, and the genetic data was used to calculate genetic population parameters as well as to investigate the genetic differentiation between stocks. The results from a relatedness analysis were used as the guiding lines for a fine-tuned and overall evaluation of the genetic distance between stocks, and the choice of candidate breeders from some of them. The approach implemented in this study uses well-established population genetics methods to evaluate the selection of breeder candidates in aquaculture commercial conditions utilizing a descriptive genetic data set based on microsatellite analyses, and to outline an efficient methodology for establishing the basis of new breeding schemes.

Differential patterns of connectivity in Western Pacific hydrothermal vent metapopulations: A comparison of biophysical and genetic models.

Hydrothermal ecosystems face threats from planned deep-seabed mining activities, despite the fact that patterns of realized connectivity among vent-associated populations and communities are still poorly understood. Since populations of vent endemic species depend on larval dispersal to maintain connectivity and resilience to habitat changes, effective conservation strategies for hydrothermal ecosystems should include assessments of metapopulation dynamics. In this study, we combined population genetic methods with biophysical models to assess strength and direction of gene flow within four species of the genus Alviniconcha (A.boucheti, A.kojimai, A.strummeri and A.hessleri) that are ecologically dominant taxa at Western Pacific hydrothermal vents. In contrast to predictions from dispersal models, among-basin migration in A.boucheti occurred predominantly in an eastward direction, while populations within the North Fiji Basin were clearly structured despite the absence of oceanographic barriers. Dispersal models and genetic data were largely in agreement for the other Alviniconcha species, suggesting limited between-basin migration for A.kojimai, lack of genetic structure in A.strummeri within the Lau Basin and restricted gene flow between northern and southern A.hessleri populations in the Mariana back-arc as a result of oceanic current conditions. Our findings show that gene flow patterns in ecologically similar congeneric species can be remarkably different and surprisingly limited depending on environmental and evolutionary contexts. These results are relevant to regional conservation planning and to considerations of similar integrated analyses for any vent metapopulations under threat from seabed mining.

Comparative Analysis of Genotyping by Sequencing and Whole-Genome Sequencing Methods in Diversity Studies of Olea europaea L.

Olive, Olea europaea L., is a tree of great economic and cultural importance in the Mediterranean basin. Thousands of cultivars have been described, of which around 1200 are conserved in the different olive germplasm banks. The genetic characterisation of these cultivars can be performed in different ways. Whole-genome sequencing (WGS) provides more information than the reduced representation methods such as genotype by sequencing (GBS), but at a much higher cost. This may change as the cost of sequencing continues to drop, but, currently, genotyping hundreds of cultivars using WGS is not a realistic goal for most research groups. Our aim is to systematically compare both methodologies applied to olive genotyping and summarise any possible recommendations for the geneticists and molecular breeders of the olive scientific community. In this work, we used a selection of 24 cultivars from an olive core collection from the World Olive Germplasm Collection of the Andalusian Institute of Agricultural and Fisheries Research and Training (WOGBC), which represent the most of the cultivars present in cultivated fields over the world. Our results show that both methodologies deliver similar results in the context of phylogenetic analysis and popular population genetic analysis methods such as clustering. Furthermore, WGS and GBS datasets from different experiments can be merged in a single dataset to perform these analytical methodologies with proper filtering. We also tested the influence of the different olive reference genomes in this type of analysis, finding that they have almost no effect when estimating genetic relationships. This work represents the first comparative study between both sequencing techniques in olive. Our results demonstrate that the use of GBS is a perfectly viable option for replacing WGS and reducing research costs when the goal of the experiment is to characterise the genetic relationship between different accessions. Besides this, we show that it is possible to combine variants from GBS and WGS datasets, allowing the reuse of publicly available data.

The Complex History of Genome Duplication and Hybridization in North American Gray Treefrogs.

Polyploid speciation has played an important role in evolutionary history across the tree of life, yet there remain large gaps in our understanding of how polyploid species form and persist. Although systematic studies have been conducted in numerous polyploid complexes, recent advances in sequencing technology have demonstrated that conclusions from data-limited studies may be spurious and misleading. The North American gray treefrog complex, consisting of the diploid Hyla chrysoscelis and the tetraploid H. versicolor, has long been used as a model system in a variety of biological fields, yet all taxonomic studies to date were conducted with only a few loci from nuclear and mitochondrial genomes. Here, we utilized anchored hybrid enrichment and high-throughput sequencing to capture hundreds of loci along with whole mitochondrial genomes to investigate the evolutionary history of this complex. We used several phylogenetic and population genetic methods, including coalescent simulations and testing of polyploid speciation models with approximate Bayesian computation, to determine that H. versicolor was most likely formed via autopolyploidization from a now extinct lineage of H. chrysoscelis. We also uncovered evidence of significant hybridization between diploids and tetraploids where they co-occur, and show that historical hybridization between these groups led to the re-formation of distinct polyploid lineages following the initial whole-genome duplication event. Our study indicates that a wide variety of methods and explicit model testing of polyploid histories can greatly facilitate efforts to uncover the evolutionary history of polyploid complexes.

Revisiting the demographic history of Central African populations from a genetic perspective

Africa is the continent of our species’ origin and the deep history of humans is represented by African genetic variation. Through genetic studies, it has become evident that deep African population history is captured by relationships among African hunter-gatherers and that the world’s deepest population divergences occur among these groups. In this review, we look back at a study published by Cavalli-Sforza and colleagues in 1969 entitled “Studies on African Pygmies. I. A pilot investigation of Babinga Pygmies in the Central African Republic (with an analysis of genetic distances)”. The study analyzed 19 classical polymorphisms and found that the deepest divergences in African populations were represented by hunter-gatherer groups such as the southern African San and the central African rainforest hunter-gatherers. We repeated the original analyses from Cavalli-Sforza et al. [1] with about 22 thousand times more genome-wide genetic markers in populations similar to those included in the original study. Our high-resolution analyses gave similar results regarding the relationships of early-diverging African populations compared to the classical polymorphism analyses. This finding, however, does not imply that research has stagnated and that developments in technology and genetic methods over the last fifty years delivered no additional information regarding African history and adaptation. We review how technology and population genetic methods have advanced to give more detailed inferences about population structure, migrations, admixture patterns, timing of admixture, sex-biased admixture, and inferences of selection and adaptive introgression in rainforest hunter-gatherers and other African populations. We also comment on how sequencing of ancient DNA has influenced findings and deliberate on the progress and development of more complex models of African history, including alternatives to tree-models and the inference of possible archaic admixture in African populations. We review the growing complexity of our picture of population history in central Africa and Africa as a whole, emerging from genomic studies and other disciplines investigating human population history and adaptation. While data and knowledge are accumulating, certain populations and areas remain underrepresented in genomic research. Their inclusion, possibly also through ancient DNA studies, together with new methods of analysis and the testing of representative models of deep population history in Africa, will help to build a more complete picture of past population history in Africa. Based on “Cavalli-Sforza LL, Zonta LA, Nuzzo F, Bernini L, de Jong WW, Meera Khan P, Ray AK, Went LN, Siniscalco M, Nijenhuis LE, van Loghem E, Modiano G. Studies on African Pygmies. I. A pilot investigation of Babinga Pygmies in the Central African Republic (with an analysis of genetic distances). Am J Hum Genet. 1969 May;21(3):252-274”.

Genomic Insight Into the Population Structure and Admixture History of Tai-Kadai-Speaking Sui People in Southwest China.

Sui people, which belong to the Tai-Kadai-speaking family, remain poorly characterized due to a lack of genome-wide data. To infer the fine-scale population genetic structure and putative genetic sources of the Sui people, we genotyped 498,655 genome-wide single-nucleotide polymorphisms (SNPs) using SNP arrays in 68 Sui individuals from seven indigenous populations in Guizhou province and Guangxi Zhuang Autonomous Region in Southwest China and co-analyzed with available East Asians via a series of population genetic methods including principal component analysis (PCA), ADMIXTURE, pairwise Fst genetic distance, f-statistics, qpWave, and qpAdm. Our results revealed that Guangxi and Guizhou Sui people showed a strong genetic affinity with populations from southern China and Southeast Asia, especially Tai-Kadai- and Hmong-Mien-speaking populations as well as ancient Iron Age Taiwan Hanben, Gongguan individuals supporting the hypothesis that Sui people came from southern China originally. The indigenous Tai-Kadai-related ancestry (represented by Li), Northern East Asian-related ancestry, and Hmong-Mien-related lineage contributed to the formation processes of the Sui people. We identified the genetic substructure within Sui groups: Guizhou Sui people were relatively homogeneous and possessed similar genetic profiles with neighboring Tai-Kadai-related populations, such as Maonan. While Sui people in Yizhou and Huanjiang of Guangxi might receive unique, additional gene flow from Hmong-Mien-speaking populations and Northern East Asians, respectively, after the divergence within other Sui populations. Sui people could be modeled as the admixture of ancient Yellow River Basin farmer-related ancestry (36.2–54.7%) and ancient coastal Southeast Asian-related ancestry (45.3–63.8%). We also identified the potential positive selection signals related to the disease susceptibility in Sui people via integrated haplotype score (iHS) and number of segregating sites by length (nSL) scores. These genomic findings provided new insights into the demographic history of Tai-Kadai-speaking Sui people and their interaction with neighboring populations in Southern China.

Species Delimitation of Asteropyrum (Ranunculaceae) Based on Morphological, Molecular, and Ecological Variation.

Objectively evaluating different lines of evidence within a formalized framework is the most efficient and theoretically grounded approach for defining robust species hypotheses. Asteropyrum Drumm. et Hutch. is a small genus of perennial herb containing two species, A. cavaleriei and A. peltatum. The distinction of these two species mainly lies in the shape and size of leaf blades. However, these characters have been considered labile and could not differentiate the two species reliably. In this study, we investigated the variation of the leaf blades of 28 populations across the whole range of Asteropyrum using the landmark-based geometric morphometrics (GMM), sought genetic gaps within this genus using DNA barcoding, phylogenetic reconstruction and population genetic methods, and compared the predicted ecological niches of the two species. The results showed that the leaf form (shape and size) was overlapped between the two species; barcode gap was not detected within the genus Asteropyrum; and little ecological and geographical differentiation was found between the two taxa. Two genetic clusters detected by population genetic analysis did not match the two morphospecies. The results suggest that there are no distinct boundaries between the two species of Asteropyrum in terms of morphology, genetics and ecology and this present classification should be abandoned. We anticipate that range-wide population genomic studies would properly delineate the species boundaries and help to understand the evolution and speciation within Asteropyrum.

HLA haplotype frequency estimation for heterogeneous populations using a graph-based imputation algorithm

HLA haplotype frequencies are estimated from ambiguous unphased HLA genotyping data using Expectation-Maximization (EM) algorithms. Current population genetics methods require independent EM frequency estimates for each population, and assume that each population is in Hardy-Weinberg Equilibrium (HWE). The HWE assumption of EM has thus far resulted in the exclusion of individuals from mixed or unknown ethnic backgrounds from reference datasets. Multi-region populations are currently poorly served by stem cell donor registry HLA imputation and matching implementations due to the inability of such algorithms to incorporate admixture into their population genetics models. To address this unmet need, we have expanded the imputation component of our GRaph IMputation and Matching (GRIMM) framework, where imputation becomes the expectation step in an iterative EM algorithm. Our novel multi-region EM implementation considers region as a Bayesian prior, enabling integration of HLA information from multiple single-region population groups, and for the first time including individuals with ambiguous or mixed ethnic backgrounds. We show that our multi-region EM produces much higher likelihood values and better haplotype recovery as measured by Kullback-Leibler divergence than all evaluated EM implementations when tested on real datasets of US donor registry HLA typings as well as simulated multi-region datasets of ambiguous HLA typings.

Inferring the population structure and admixture history of three Hmong-Mien-speaking Miao tribes from southwest China based on genome-wide SNP genotyping

Background Hmong-Mien speaking Miao, also called Hmong, is the sixth largest ethnic group in mainland China. However, the fine-scale genetic profiles and population history of Miao populations in southwest China, especially in Guizhou province, remain uncharacterised due to a scarcity of samples of genome-wide data from different tribes. Aim To further investigate the population substructure and admixture history of the Guizhou Miao minority. Subjects and methods We collected 29 samples from three Miao tribes of Guizhou province in southwest China and genotyped about 700,000 genome-wide SNPs of each sample. We analysed newly generated data in together with published modern/ancient East Asian populations datasets via a series of population genetic methods, including principal component analysis (PCA), ADMIXTURE, Fst, TreeMix, f-statistics, qpWave, and qpAdm. Results PCA and ADMIXTURE results showed that the three studied Guizhou Miao groups consistently fell on the Hmong-Mien-related genetic cline and were relatively genetically homogeneous, displaying a genetic affinity with neighbouring Tai-Kadai speaking populations such as Dong. These results were further confirmed by the observed genetic clade in Fst, TreeMix, outgroup-f3 -statistics, and f4 -statistics. Furthermore, f4 -based allele sharing patterns illustrated that compared with Hunan Miao in central China, Guizhou Miao shared more alleles with Hmong-Mien-speaking Vietnam Hmong and Tai-Kadai-speaking CoLao, Dong, while exhibiting less northeast Asian-related ancestry. Admixture-f3 and f4 -statistics revealed the North-South admixture pattern for the studied Guizhou Miao. A qpAdm-based two-way admixture model further revealed that the studied Guizhou Miao harboured 44%–55.4% indigenous Austronesian-speaking Atayal-related ancestry and 44.6%–56% Late Neolithic Yellow River farmer-related ancestry. Conclusions The population structure within Hmong-Mien-related populations showed a geographic correlation. Hmong-Mien speaking Hunan Miao, Guizhou Miao, and Vietnam Hmong presented close genetic relationships although they dwelt in different regions, suggesting the preservation of the original Hmong-related genetic diversity. The results based on genome-wide SNPs data generally matched the migration history for the Miao population. Our study contributes to a better knowledge of Miao populations and the population structure in southwest China.

Genomic signatures of selection for resistance to stripe rust in Austrian winter wheat

Key messageWe combined quantitative and population genetic methods to identify loci under selection for adult plant resistance to stripe rust in an Austrian winter wheat breeding population from 2008 to 2018.Resistance to stripe rust, a foliar disease caused by the fungus P. striiformis f. sp. tritici, in wheat (Triticum aestivum L.) is both qualitatively and quantitatively controlled. Resistance genes confer complete, race-specific resistance but are easily overcome by evolving pathogen populations, while quantitative resistance is controlled by many small- to medium-effect loci that provide incomplete yet more durable protection. Data on resistance loci can be applied in marker-assisted selection and genomic prediction frameworks. We employed genome-wide association to detect loci associated with stripe rust and selection testing to identify regions of the genome that underwent selection for stripe rust resistance in an Austrian winter wheat breeding program from 2008 to 2018. Genome-wide association mapping identified 150 resistance loci, 62 of which showed significant evidence of selection over time. The breeding population also demonstrated selection for resistance at the genome-wide level.

Effects of single nucleotide polymorphism ascertainment on population structure inferences.

Single nucleotide polymorphism (SNP) data are widely used in research on natural populations. Although they are useful, SNP genotyping data are known to contain bias, normally referred to as ascertainment bias, because they are conditioned by already confirmed variants. This bias is introduced during the genotyping process, including the selection of populations for novel SNP discovery and the number of individuals involved in the discovery panel and selection of SNP markers. It is widely recognized that ascertainment bias can cause inaccurate inferences in population genetics and several methods to address these bias issues have been proposed. However, especially in natural populations, it is not always possible to apply an ideal ascertainment scheme because natural populations tend to have complex structures and histories. In addition, it was not fully assessed if ascertainment bias has the same effect on different types of population structure. Here, we examine the effects of bias produced during the selection of population for SNP discovery and consequent SNP marker selection processes under three demographic models: the island, stepping-stone, and population split models. Results show that site frequency spectra and summary statistics contain biases that depend on the joint effect of population structure and ascertainment schemes. Additionally, population structure inferences are also affected by ascertainment bias. Based on these results, it is recommended to evaluate the validity of the ascertainment strategy prior to the actual typing process because the direction and extent of ascertainment bias vary depending on several factors.

Maternal Lineages from 10-11th Century Commoner Cemeteries of the Carpathian Basin.

Nomadic groups of conquering Hungarians played a predominant role in Hungarian prehistory, but genetic data are available only from the immigrant elite strata. Most of the 10–11th century remains in the Carpathian Basin belong to common people, whose origin and relation to the immigrant elite have been widely debated. Mitogenome sequences were obtained from 202 individuals with next generation sequencing combined with hybridization capture. Median joining networks were used for phylogenetic analysis. The commoner population was compared to 87 ancient Eurasian populations with sequence-based (Fst) and haplogroup-based population genetic methods. The haplogroup composition of the commoner population markedly differs from that of the elite, and, in contrast to the elite, commoners cluster with European populations. Alongside this, detectable sub-haplogroup sharing indicates admixture between the elite and the commoners. The majority of the 10–11th century commoners most likely represent local populations of the Carpathian Basin, which admixed with the eastern immigrant groups (which included conquering Hungarians).

Temporal and spatial variation in population structure among brooding sea stars in the genus Leptasterias.

Temporal genetic studies of low‐dispersing organisms are rare. Marine invertebrates lacking a planktonic larval stage are expected to have lower dispersal, low gene flow, and a higher potential for local adaptation than organisms with planktonic dispersal. Leptasterias is a genus of brooding sea stars containing several cryptic species complexes. Population genetic methods were used to resolve patterns of fine‐scale population structure in central California Leptasterias species using three loci from nuclear and mitochondrial genomes. Historic samples (collected between 1897 and 1998) were compared to contemporary samples (collected between 2008 and 2014) to delineate changes in species distributions in space and time. Phylogenetic analysis of contemporary samples confirmed the presence of a bay‐localized clade and revealed the presence of an additional bay‐localized and previously undescribed clade of Leptasterias. Analysis of contemporary and historic samples indicates two clades are experiencing a constriction in their southern range limit and suggests a decrease in clade‐specific abundance at sites at which they were once prevalent. Historic sampling revealed a dramatically different distribution of diversity along the California coastline compared to contemporary sampling and illustrates the importance of temporal genetic sampling in phylogeographic studies. These samples were collected prior to significant impacts of Sea Star Wasting Disease (SSWD) and represent an in‐depth analysis of genetic structure over 117 years prior to the SSWD‐associated mass die‐off of Leptasterias.

New approaches for ecological adaptation study: from population genetics to landscape genomics

Ecological adaptation or local adaptation is one of the most important responses of species to the changing environment. Understanding the molecular mechanism of local adaptation provides a theoretical foundation for the protection and utilization of the species. Landscape genomics studies the interaction between the genetic variation of species and landscape characteristics on the genomic level which quantify the response of genetic variation caused by environmental changes at the genomic level, and can provide new insights for local adaptation research as compared with the classic population genetics methods. In this review, we first summarized series methods for local adaptation research, with particular emphasis on the introduction of generalized linear mixed models, multivariate statistical analysis, non-linear models, and calculation tools involved in genotype-environment associations (GEAs), and we also compared the advantages and disadvantages of these methods. Next, we introduced the newly developed method “risk of non-adaptedness (RONA)”, which evaluates the current and predicts future adaptability of species by combining the allele frequency and the changes in environmental factors. Finally, using case studies of tree local adaptation, we provided suggestions for the future study directions on tree local adaptation.

Systematics of a Neotropical clade of dead-leaf-foraging antwrens (Aves: Thamnophilidae; Epinecrophylla)

The stipple-throated antwrens of the genus Epinecrophylla (Aves: Thamnophilidae) are represented by eight species primarily found in the lowlands of the Amazon Basin and the Guiana Shield. The genus has a long and convoluted taxonomic history, with many attempts made to address the taxonomy and systematics of the group. Here we employ massively parallel sequencing of thousands of ultraconserved elements (UCEs) to provide both the most comprehensive subspecies-level phylogeny of Epinecrophylla antwrens and the first population-level genetic analyses for most species in the genus. Most of our results are robust to a diversity of phylogenetic and population genetic methods, but we show that even with thousands of loci we are unable to fully resolve the relationships between some western Amazonian species in the haematonota group. We uncovered phylogenetic relationships between taxa and patterns of population structure that are discordant with both morphology and current taxonomy. For example, we found deep genetic breaks between taxa in the ornata group that are currently regarded as species, and in the haematonota and leucophthalma groups we found paraphyly at the species and subspecies levels, respectively. As has been found in many Amazonian taxa, our phylogenetic results show that the major river systems of the Amazon Basin appear to have an effect on the genetic structure and range limits within Epinecrophylla. Our population genetics analyses showed extensive admixture between some taxa despite their deep genetic divergence. We present a revised taxonomy for the group and suggest areas for further study.

Global incursion pathways of Thaumastocoris peregrinus, an invasive Australian pest of eucalypts

The bronze bug, Thaumastocoris peregrinus, is an endemic Australian eucalypt pest that has become a serious threat to the global forestry industry. Following a large outbreak within its native range in 2002, introduced populations of the bronze bug appeared in South Africa and Argentina. Since then, T. peregrinus has spread rapidly around the world, with the number of reported incursions increasing steadily. Despite the problems posed by the bronze bug, little is known about its global invasion pathways. In this study, we used multiple different population genetic methods to (1) gain new insight into aspects of bronze bug population history within Australia, and (2) characterise the spread of the bronze bug throughout South America, South Africa, New Zealand and the Mediterranean Basin. Taken together, the genetic data and the outbreak records suggest that, across the international regions surveyed, at least three separate introductions of T. peregrinus from Australia have occurred over the decade 2003–2012—one into South Africa, another into Argentina and a third into New Zealand—each of which is likely to have originated in Sydney. Populations in Europe and Israel appear to have become established from individuals introduced from South America, rather than from within the native Australian range, suggesting the existence of a bridgehead effect. These findings provide an important framework for understanding the global spread of invasive bronze bug populations. They may be used to inform management decisions and improve the effectiveness of control strategies.

Applying f4‐statistics and admixture graphs: Theory and examples

A popular approach to learning about admixture from population genetic data is by computing the allele-sharing summary statistics known as f-statistics. Compared to some methods in population genetics, f-statistics are relatively simple, but interpreting them can still be complicated at times. In addition, f-statistics can be used to build admixture graphs (multi-population trees allowing for admixture events), which provide more explicit and thorough modelling capabilities but are correspondingly more complex to work with. Here, I discuss some of these issues to provide users of these tools with a basic guide for protocols and procedures. My focus is on the kinds of conclusions that can or cannot be drawn from the results of f4 -statistics and admixture graphs, illustrated with real-world examples involving human populations.

The role of population and quantitative genetics and modern sequencing technologies to understand evolved herbicide resistance and weed fitness.

Evolution of resistance to multiple herbicides with different sites of action and of nontarget site resistance (NTSR) often involves multiple genes. Thus, single‐gene analyses, typical in studies of target site resistance, are not sufficient for understanding the genetic architecture and dynamics of NTSR and multiple resistance. The genetics of weed adaptation to varied agricultural environments is also generally expected to be polygenic. Recent advances in whole‐genome sequencing as well as bioinformatic and statistical tools have made it possible to use population and quantitative genetics methods to expand our understanding of how resistance and other traits important for weed adaptation are genetically controlled at the individual and population levels, and to predict responses to selection pressure by herbicides and other environmental factors. The use of tools such as quantitative trait loci mapping, genome‐wide association studies, and genomic prediction will allow pest management scientists to better explain how pests adapt to control tools and how specific genotypes thrive and spread across agroecosystems and other human‐disturbed systems. The challenge will be to use this knowledge in developing integrated weed management systems that inhibit broad resistance to current and future weed‐control methods. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Short Communication: Genetic structure of Longtail Tuna Thunnus tonggol (Bleeker, 1851) in Java Sea, Indonesia

Abstract. Al Malik MD, Pertiwi NPD, Sembiring A, Yusmalinda NLA, Ningsing EY, Astarini IA. 2020. Short Communication: Genetic structure of Longtail Tuna Thunnus tonggol (Bleeker, 1851) in Java Sea, Indonesia. Biodiversitas 21: 3637-3643. Thunnus tonggol (Longtail Tuna) is an economically important fish found in Indonesia waters, however, the information regarding this fish is lacking. Known to be a neritic fish and found in shallow water, Java Sea is one of the ideal habitats for T. tonggol species. Due to high fishing rates activities in Java Sea, a better management plan to ensure the conservation and fisheries sustainability around this area is needed, especially to protect T. tonggol population. In order to complete the Indonesian tuna data, we aim to study the diversity and genetic structure of T. tonggol in Java Sea at three different locations; i.e. Semarang, Banjarmasin, and Jakarta. In this study, population genetic methods with the marker of mitochondrial DNA (mtDNA) control region were used in population structure analysis. A total of 115 specimens were collected from the fish market around the area of study locations and amplified using polymerase chain reaction (PCR) and sequenced using Sanger methods. The result showed genetic diversity (Hd) value of 0.99366, and nucleotide diversity (π) value of 0.01906. Both of these values indicated high genetic diversity. Population analyses using Analysis of Molecular Variance (AMOVA) showed nonsignificant differences between the three populations of study (mixing population), with the ΦST value of 0,00375 (p-value > 0.05). Based on this result, the fisheries management for T. tonggol in Java Sea needs to be managed as one single population management.