Signal transducer and activator of transcription 3 (STAT3) is a signaling molecule and transcription factor that plays important protective roles in the heart. The protection mediated by STAT3 is attributed to its genomic actions as a transcription factor and other non-genomic roles targeting mitochondrial function and autophagy. As a transcription factor, STAT3 upregulates genes that are anti-oxidative, anti-apoptotic, and pro-angiogenic, but suppresses anti-inflammatory and anti-fibrotic genes. Its suppressive effects on gene expression are achieved through competing with other transcription factors or cofactors. STAT3 is also linked to the modification of mRNA expression profiles in cardiac cells by inhibiting or inducing miRNA. In addition to these genomic roles, STAT3 is suggested to function protectively in mitochondria, where it regulates ROS production, in part by regulating the activities of the electron transport chain complexes, although our recent evidence calls this role into question. Nonetheless, STAT3 is a key player known to be activated in the cardioprotective ischemic conditioning protocols. Through these varied roles, STAT3 participates in various mechanisms that contribute to cardioprotection against different heart pathologies, including myocardial infarction, hypertrophy, diabetic cardiomyopathy, and peripartum cardiomyopathy. Understanding how STAT3 is involved in the protective mechanisms against these different cardiac pathologies could lead to novel therapeutic strategies to treat them. Cardiovascular diseases are among the top challenges to global health, constituting a leading cause for morbidity and mortality worldwide. According to the World Health Organization (WHO), these diseases result in 17.5 million deaths globally per year . This reSTAT3 gene. It is 770 amino acids in length and is composed of six functional domains. The NH2-terminal domain participates in higher order complex formation. This is followed by the coiled-coil domain involved in protein-protein interactions with co-regulators and transcription factors. Next is the DNA binding domain with a sequence specificity for an interferon gamma (INFγ) activated sequence (GAS) present in the promoter region of specific genes. Following that is the linker domain located directly before the Src homology-2 (SH2) domain, which mediates receptor recruitment and STAT3 dimerization via intermolecular phosphorylated tyrosine-SH2 interactions. The transcription activation domain (TAD), located in the COOH-terminal region, is where regulatory phosphorylation occurs  and STAT3β. Compared to STAT3α, STAT3β is the truncated form lacking the 55-residue C-terminal transactivation domain. This splice variant can be phosphorylated at the tyrosine 705 (Y705) residue, but unlike STAT3α lacks serine 727 (S727). STAT3β can still bind to DNA as a homo- or heterodimer (with STAT3α or other transcription factors) . The rolThe main function of STAT3 is the regulation of gene transcription. STAT3 is modified at specific residues by a number of post-translational modifications with functional consequences, mainly acetylation and phosphorylation. In addition, methylation, ubiquitination, s-nitrosylation, and glutathionylation occur . In addiSTAT3 is activated through phosphorylation of its tyrosine 705 residue (Y705) by receptor and non-receptor tyrosine kinases. This activation facilitates STAT3's homo/hetero-dimerization and DNA binding . TyrosinIn cardiomyocytes, agonists with pathophysiological importance engage membrane receptors coupled to the activation of JAK1 and JAK2 tyrosine kinases, and consequently lead to STAT3 tyrosine phosphorylation. These agonists include, in addition to IL-6 and leukemia inhibitory factor (LIF), tumor necrosis factor alpha (TNFα), IFNγ, erythropoietin, and granulocyte-colony stimulating factor (G-CSF). The Src family kinases and bone marrow kinase on chromosome X (BMX) also induce tyrosine phosphorylation of STAT3 in cardiac cells .Serine/threonine kinases have been shown to phosphorylate STAT3 on S727 in the cytoplasm or nucleus. The involvement of serine phosphorylation in STAT3 activities was first reported in 1995 by Zhang et al. who studied the importance of such phosphorylation for DNA binding . S727 waMultiple kinases are responsible for S727 phosphorylation, depending on the nature of the activating signal. Mitogen activated protein kinase (MAPK) family members are mainly reported to induce this phosphorylation in response to different extracellular stimuli. The MAPK family is composed of extracellular signal-regulated kinase (ERK), induced by growth factors and cytokines, as well as JNK/stress-activated protein kinase and p38/HOG1 (p38 MAPK), both activated by pro-inflammatory cytokines and environmental stresses , 20. AmoBesides phosphorylation, the function of STAT3 is also regulated by p300-mediated acetylation of lysine residues within its NH2 terminus  and SH2 (K685) domains. Acetylation of K49 and K87 was shown to be important for transcription through strengthening or enhancing the interaction of STAT3 with the histone acetyltransferase p300, which stabilizes the enhanceosome assembly and ensures retention of STAT3 in the nucleus , 25. In It has become clear that nitric oxide (NO) is an endogenous regulator in cardiovascular physiology and cellular respiration. The presence of NO provokes S-nitrosylation, a ubiquitous post-translational modification, by selective addition of nitric oxide (NO) to specific cysteine residue(s) of proteins forming S-nitrosothiol (SNO). This redox-related post-translational modification can inhibit STAT3 activation. STAT3 was observed to be S-nitrosylated on C259, which inhibited JAK2-mediated Y705 phosphorylation. For instance, endogenous NO from iNOS or treatment with s-nitrosoglutathione inhibited STAT3-induced gene expression and proliferation in microglial cells. It has not been reported yet if STAT3 is s-nitrosylated in the heart under conditions where iNOS is upregulated, such as the ischemic and failing myocardium –31.S-sulfhydration is a post-translational modification involved in many physiological and pathological processes. S-sulfhydration yields hydropersulfide (–SSH) in the active cysteine residue of a protein, which mediates most of the cellular functions induced by hydrogen sulfide (H2S). Some preclinical studies have reported that the administration of hydrogen sulfide (H2S) decreases myocardial injury, protects blood vessels, limits inflammation and regulates blood pressure. In the context of STAT3, Wu et al. reported that S-propargyl-cysteine (SPRC), a producing agent of endogenous hydrogen sulfide (H2S), possesses cardioprotective efficacy through the activation of STAT3 phosphorylation downstream of gp130. In another study, Xin et al. reported that H2S ameliorated IL-6-induced STAT3 acetylation, which was accompanied by a decreased inflammatory response in patients with anemia. Although the presence of H2S provokes sulfhydration, it seems that there is no direct sulfhydration of STAT3 reported in the presence of H2S, but rather the presence H2S induces phosphorylation or acetylation  injury is a pathological state caused by an initial low supply of blood to a specific area, followed by the restoration of perfusion and reoxygenation (reperfusion). This injury is associated with a profound inflammatory response , 52. Dur2O2 and different cytokines induced a rapid loss of STAT3 (within few minutes) from mitochondria, and a rapid recovery also, dependent on the phosphorylation of the S727 residue. Although this study was performed on different cell types, it was not assessed in cardiac cells  directly by decreasing ROS generation in mitochondria. On the one hand, STAT3 upregulates expression of ROS scavengers and anti-oxidants: metallothioneins and MnSOD , 69. On In the context of MI-induced fibrosis and hypertrophy, cardiomyocyte-specific ablation of STAT3 exacerbated cardiac fibrosis during the subacute phase of MI, along with an increase in the expression of fibrosis-related genes, most probably due to increased death of cardiomyocytes. Besides, cardiac hypertrophy was enhanced by STAT3 ablation after MI in mouse hearts and consequently, capillary density was perhaps reduced in the border zone .Two main signaling pathways have been identified as contributors to the infarct-reducing effect of ischemic preconditioning . The firThe involvement of STAT3 in the cardioprotective effects of conditioning was proved using different animal models, including mice, rats, rabbits, and pigs. It was shown through knocking out STAT3, inhibiting STAT3 with stattic, or inhibiting the JAK-STAT pathway with AG490. Although few studies focused on S727 STAT3 phosphorylation during conditioning, the primary targeted phosphorylation residue is Y705. Starting with the mouse models, Xuan et al. reported that JAK1/2 phosphorylation was increased within 5 min of preconditioning, while Y705 phosphorylation of STAT3 significantly increased within 30 min. Phosphorylation and cardioprotection were blocked by AG490 . In addiIn rabbit models as well, post-conditioning was shown to induce cardioprotection through the phosphorylation and activation of both JAK and STAT3 proteins, an effect abolished by AG490 . In rat in vivo animal models, some groups used in vitro cellular models of cardiomyocytes and cardiomyoblasts. For instance, Suleman et al.  proteins that were normally expressed in response to delayed preconditioning , 85.in situ pig model, that ischemic post-conditioning induced an increase in Y705 phosphorylation of STAT3 in the mitochondrial compartment. This was accompanied by protection of mitochondrial respiration and an increase in the calcium retention capacity. Again, AG490 and stattic abolished post-conditioning-induced protection of calcium retention capacity and respiration  plays a major role in cellular calcium homeostasis. Various stimuli such as ischemic insult, oxidative stress, and calcium disturbances lead to the accumulation of unfolded proteins, a condition named ER stress . Severalll death . Since tin vivo rat model of IR, the JAK2-STAT3 pathway was shown to be involved in rescuing SERCA expression and activity following 3 and 24 h of reperfusion, and thus reducing ER stress and infarct size . On the other hand, well-preserved SERCA activity attenuates ER stress and protects against myocardial IR injury. In this context, using rct size . Similarrct size . In addirct size . In anotpathways .It seems that the non-canonical activities of STAT3, which were controversially assigned to the maintenance of ETC activity in mitochondria, now include a shift toward activities at the level of ER via IP3R degradation and modulation of calcium flux. Further investigations need to be conducted on cardiomyocytes in this regard, in which it would be interesting to also assess STAT3 in the mitochondrial associated membranes (MAMs) that lie at the interface between mitochondria and ER. This might also help explain why different groups have reported different results regarding the presence of STAT3 in cardiomyocyte mitochondria.STAT3 has been considered a potential anti-cancer target since its description as an oncogene in 1999 . It is iAccumulating evidence indicates that preservation of bioenergetics, including maintenance of fatty acid oxidation, is important for normal cardiac function and prevention of ischemic and non-ischemic heart failure –111. TheIn cardiac myocytes, microtubules (MTs) are cytoskeleton components that consist of αβ-tubulin heterodimers, assembled into microtubule polymers. Besides their well-established physiological roles, evidence suggests that MTs have an important role in disease conditions, such as cardiac hypertrophy and heart failure. Cooper reported that re-organization of MTs accompanied the development of cardiac disease , and an STAT3 has been reported to partially co-localize with microtubules in various types of cells . It contSTAT3 participates in mechanisms contributing to different chronic cardiac pathologies including hypertension-induced hypertrophy, fibrosis, and diabetic cardiomyopathy .in vitro  activation. This displacement, induced by CaMKII-mediated phosphorylation of bIV-spectrin, was implicated in cardiac fibrosis and in the loss of cardiac function since it resulted in the nuclear translocation of STAT3 and induction of pro-fibrotic genes in cardiomyocytes  is a rare heart disease that develops in women during the last month of pregnancy or within 5 months of delivery. Its typical features are apoptosis, inflammation, autoimmune processes, and impaired cardiac microvasculature . ObservaThe absence of STAT3 leads to PPCM development through oxidative stress. Female mice with cardiomyocyte-specific deletion of STAT3 develop PPCM, associated with the abrogation of superoxide dismutase 2 (MnSOD2) upregulation . This coLow levels of ventricular STAT3 contribute to a state of energy depletion and increased ROS generation, which compromises glucose uptake and increases the sensitivity of the heart to the toxic effects of chronic β-adrenergic signaling. This again assures the importance of STAT3 in cardioprotection against PPCM . GeneralDiabetes mellitus (DM) is one of the most prevalent diseases worldwide . DiabetiUnder non-ischemic cardiac conditions, the effect of diabetes on the expression, phosphorylation, and activation of cardiac STAT3 is controversial. On one hand, various papers have reported a decrease in cardiac STAT3 phosphorylation and activation in several diabetic experimental models. In this regard, Wang et al. showed that myocardial pS727-STAT3 activation was decreased in streptozotocin-induced type I diabetes . Using tin vivo studies, STAT3 activation was also reported under high glucose conditions in H9c2 cells  expression in DCM . In addiin vivo studies, the same reduction was reported in different models , a key mediator of neutrophil infiltration, is significantly increased and can be induced by angiotensin II. In a mouse study, angiotensin II infusion lead to a significant increase in G-CSF, along with a neutrophil accumulation, pro-inflammatory cytokine expression, reactive oxygen species production and cardiac fibrosis via activation of STAT3, ERK1/2, and AKT signaling pathways .STAT3 plays a role in the recruitment of macrophages. This process is facilitated by Reg3b secretion from cardiac myocytes in response to the gp130-family cytokine oncostatin M (OSM), and STAT3 was demonstrated to be required for the expression of Reg3b .Macrophages are major effector cells in tissue repair and fibrosis. They can be broadly categorized as M1 and M2. M1 macrophages are pro-inflammatory, expressing inflammatory genes, including iNOS. In contrast, M2 macrophages are involved in the resolution of inflammation and secrete arginase-1 and IL-10 . AccumulIn this context, the IL-10-galectin-3 axis was recently shown to be essential for the M2 macrophage polarization after myocardial infarction in a STAT3-dependent manner, and these macrophages contributed to tissue repair by promoting fibrosis and clearance of apoptotic cells . In anotOverall, STAT3 plays pivotal roles in regulating the cardiac response during myocardial infarction, partly through regulating inflammation. It interferes in the pro-inflammatory and anti-inflammatory responses, whereby STAT3 is first activated downstream of inflammatory cytokines and then regulates the infiltration of immune cells to the injured area.S-propargyl-cysteine (SPRC), a source of endogenous hydrogen sulfide (H2S), possesses cardioprotective efficacy against Dox by stimulating the activation of STAT3 via gp130-mediated signaling in vitro and in vivo. In Dox-stimulated cardiotoxicity, SPRC enhanced cell viability, restored expression of gp130/STAT3-regulated downstream genes, inhibited apoptosis and oxidative stress, and antagonized mitochondrial dysfunction. All of these beneficial effects of SPRC were lost by blocking the gp130/STAT3 signaling (Doxorubicin (Dox) is an important anticancer agents. However, its clinical application is limited by severe cardiotoxicity . Variousignaling .STAT3 represents a crucial molecule for the maintenance of heart function, under physiological and pathological conditions. The pathological conditions in which STAT3 is involved include myocardial infarction, diabetic cardiomyopathy, peripartum cardiomyopathy, fibrosis, and hypertrophy. This involvement of STAT3 is mainly mediated through its functioning as a transcription factor able to regulate a wide array of genes. However, several functions are still controversial and need to be better understood in order to guide future therapeutic strategies against these pathologies. The roles played by STAT3 in autophagy, metabolism, and ER stress need to be better established in the context of the mentioned cardiac pathologies in order to link the abnormalities at the molecular and functional levels , 190. MoThe level of STAT3 activation in the heart likely determines whether its actions are beneficial, harmful, or a combination of the two. For instance, transgenic mice with cardiac-specific overexpression of a constitutively active STAT3, which produces low levels of continuous activation, demonstrated evidence for VEGF induction in the heart .On the oTherapeutically, understanding the mechanisms underlying a pathology represents the first step toward discovering preventive or treatment protocols and medications against this pathology. Since STAT3 is involved in a wide range of physiological and pathological cardiac conditions, understanding the mechanisms of this involvement paves the way toward finding therapeutic strategies involving either the inhibition or activation of STAT3. By describing the different roles of STAT3 as a transcription factor and a signaling molecule, and through explaining its upstream activation, the current review highlights several targets for therapeutic approaches. This may include pharmacological activation or inhibition of STAT3, respectively achieved by inducing the secretion of upstream activators (such as cytokines or growth factors) or developing direct pharmacological inhibitors with non-toxic side effects.All authors have equally contributed to the writing of the manuscript and have approved the final version for submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Plasmodium knowlesi merozoite surface protein 1 (PkMSP1) is a potential asexual blood-stage vaccine candidate, however, only a limited number of clinical isolates have been analysed from Malaysia and no inter-country comparative diversity study has been conducted. In the present study, nucleotide diversity, haplotypes and natural selection levels of pkmsp1 in clinical samples from geographically distinct regions of Malaysia and Thailand were investigated. The overall population structure of the parasite from the region was determined.The C-terminal 42 kDa domain of pkmsp1 sequences obtained from clinical isolates of Malaysia along with the H-strain were downloaded from the database for domain wise characterization of pkmsp1 gene. Additionally, 76 pkmsp-142 sequences from Thailand and Malaysia were downloaded from the database for intra and inter-population analysis. DnaSP 5.10 and MEGA 5.0 software were used to determine genetic diversity, polymorphism, haplotypes and natural selection. Genealogical relationships were determined using haplotype network tree in NETWORK software v5.0. Population genetic differentiation index (FST) of parasites were analysed using Arlequin v3.5.Eleven full-length pkmsp1 sequences along with the H-strain identified 477 (8.4%) polymorphic sites, of which 107 were singleton sites. The overall diversity observed in the full-length genes were high in comparison to its ortholog pvmsp1 and the 4 variable domains showed extensive size variations. The nucleotide diversity was low towards the pkmsp1-42 compared to the conserved domains. The 19 kDa domain was less diverse and completely conserved among isolates from Malaysian Borneo. The nucleotide diversity of isolates from Peninsular Malaysia and Thailand were higher than Malaysian Borneo. Network analysis of pkmsp1-42 haplotypes showed geographical clustering of the isolates from Malaysian Borneo and grouping of isolates from Peninsular Malaysia and Thailand. Population differentiation analysis indicated high FST values between parasite populations originating from Malaysian Borneo, Peninsular Malaysia and Thailand attributing to geographical distance. Moderate genetic differentiation was observed for parasite populations from Thailand and Peninsular Malaysia. Evidence of population expansion and purifying selection were observed in all conserved domains with strongest selection within the pkmsp1-42 domain.Sequence analysis of 11 full-length P. knowlesi based on msp1. Strong evidence of negative selection was observed in the 42 kDa domain, indicating functional constrains. Geographical clustering of P. knowlesi and moderate to high genetic differentiation values between populations identified in this study highlights the importance of further evaluation using larger number of clinical samples from Southeast Asian countries.This study is the first to report on inter country genetic diversity and population structure of The online version of this article (10.1186/s12936-018-2583-z) contains supplementary material, which is available to authorized users. Plasmodium knowlesi is now considered as the fifth Plasmodium species infecting humans and high number of cases has been reported from most Southeast Asian countries  and Others [T] refers to observed sequential variations within Malaysian or Thailand isolates, respectively.Additional file 5. Graphical representation of nucleotide diversity of PkMSP1 at the 33 kDa and 19 kDa domains.


Breeding schemes that utilize modern breeding methods like genomic selection (GS) and speed breeding (SB) have the potential to accelerate genetic gain for different crops. We investigated through stochastic computer simulation the advantages and disadvantages of adopting both GS and SB (SpeedGS) into commercial breeding programs for allogamous crops. In addition, we studied the effect of omitting one or two selection stages from the conventional phenotypic scheme on GS accuracy, genetic gain, and inbreeding. As an example, we simulated GS and SB for five traits  with different genetic architectures and heritabilities  for a tall fescue breeding program. We developed a new method to simulate correlated traits with complex architectures of which effects can be sampled from multiple distributions, e.g. to simulate the presence of both minor and major genes. The phenotypic selection scheme required 11 years, while the proposed SpeedGS schemes required four to nine years per cycle. Generally, SpeedGS schemes resulted in higher genetic gain per year for all traits especially for traits with low heritability such as persistency. Our results showed that running more SB rounds resulted in higher genetic gain per cycle when compared to phenotypic or GS only schemes and this increase was more pronounced per year when cycle time was shortened by omitting cycle stages. While GS accuracy declined with additional SB rounds, the decline was less in round three than in round two, and it stabilized after the fourth SB round. However, more SB rounds resulted in higher inbreeding rate, which could limit long-term genetic gain. The inbreeding rate was reduced by approximately 30% when generating the initial population for each cycle through random crosses instead of generating half-sib families. Our study demonstrated a large potential for additional genetic gain from combining GS and SB. Nevertheless, methods to mitigate inbreeding should be considered for optimal utilization of these highly accelerated breeding programs. Allogamous species are obligate outbreeding, or cross-pollinated, due to the presence of self-incompatibility mechanisms that cause dissonant pollen-stigma interactions . AllogamThe development of cost-effective and high-throughput genotyping methods have made it possible to improve selection efficiency through genomic selection (GS) . GS, firCombining GS with other modern breeding strategies may further enhance its efficiency on improving genetic gain. For instance, Brassica species, bread wheat, durum wheat, barley, chickpea, pea, grass pea, quinoa, oat, Brachypodium distachyon, and peanut; and at least four generations have been achieved in a single year using SB (The recent development of “speed breeding” (SB) protocols has the potential to significantly accelerate breeding programs for different crops by reducing the generation time . In SB, using SB . Thus, cusing SB , such noWhile breeding strategies such as GS and SB show considerable promise, their efficient implementation requires optimization as implementation could be achieved in many ways. Large scale empirical testing of many scenarios is costly and slow. Alternatively, computer simulation can be a time- and cost-effective tool to predict the outcome of multiple breeding designs and strategies. Simulation can facilitate the assessment of optimal population sizes, selection intensities or other breeding program parameters ending with a small number of recommended schemes for the industry. Planning a simulation study for a breeding program requires 1) information about the genomic characteristics of the empirical breeding population for the target species; 2) understanding the genetic architecture and variance components of the traits under investigation; 3) knowledge about current breeding practices; and 4) designing and integrating new strategies into the current breeding practices e.g. . Once seA previous study simulated a simple breeding program which combined both SB and GS (SpeedGS) in wheat . HoweverFescue arundinacea; 2n = 6x = 42; G1G1G2G2PP) was simulated. Tall fescue is a hexaploid pasture crop that evolved from the hybridization of three diploid genomes, G1, G2, and P. To the best of our knowledge, this is the first simulation study to investigate the potential of breeding programs for allogamous crops that combine GS and SB and its effect on inbreeding.In this study, through stochastic computer simulation, the potential of incorporating both GS and SB strategies into allogamous crop breeding programs was investigated to improve multiple traits with different genetic architectures. The main strategy involved selecting parents for crosses based on their genomic estimated breeding values (GEBVs), generating their progeny through SB, and repeating the process multiple times in a single year. Multiple designs were tested omitting some of the conventional phenotypic selection (PS) stages to study their effects on the genetic gain, GS accuracy, and inbreeding rate. We aimed to compare the genetic gain per breeding cycle, genetic gain per year, accuracy of GS, and inbreeding levels for each proposed scheme. In each scheme, we simulated one, two, or three SB rounds and we also aimed to study the effect of reducing the number of full-sib plants in the initial population. As a case study, the commercial breeding program for the pasture crop tall fescue  at generation 16,000. The hexaploid tall fescue was evolved at generation 25,000 by hybridizing the tetraploid and the third diploid . We stopped the simulation at generation 105 to ensure that the hexaploid populations reached mutation-drift equilibrium. For all newly evolved taxa, populations were expanded exponentially within 100 generations to reach the final population size. The number of generations in each stage was selected to run the analysis long enough to reach mutation-drift equilibrium  h2 = 0.3, persistency (Per) h2 = 0.1, seed yield (SY) h2 = 0.4, and quality (Q) h2 = 0.3 (We simulated five different traits to be subject to selection which were heading date (HD) with narrow sense heritability 2 = 0.3  and know2 = 0.3 . To simum) in which:QTL effects for FY, Per. and SY were simulated from the normal distribution N ∼ , while QTL effects of Q and HD were simulated from two different normal distributions. It is known that HD has some QTL of large effect  and thisl is the number of large effect QTL.Where e is the total genetic variance explained by large effect QTL (ranged between 0 and 1); n is the total number of simulated QTL and R (n × p) of random QTL effects with the Cholesky decomposition of the targeted (p × p) correlation matrix C (n QTL for p traits); assuming C is a Hermitian, positive definite matrix. This works because Var(R) = I; in which I is the identity matrix. However, if the QTL effects for multiple traits were sampled from multiple normal distributions with different variances (such as our case), the variance of R will not be equal to that of the identity matrix. For this reason, we proposed the below method to solve this problem.Simulating correlated traits is usually done by multiplying a matrix n × p) matrix (R) in which random QTL effects for each trait were drawn from different normal distributions, i.e. Var(R) ≠ I. Second, rescale R to keep its variance equal to the identity matrix variance by multiplying it with the inverse of a matrix L, the Cholesky decomposition of the variance of R (Var(R) = L × LT); where LT is the transpose of L.First, simulate an ; where DT is the transpose of D; to get the final correlated QTL effects, where 20 QTL explain 50% of the genetic variance and 980 QTL explain the other 50% for HD.h2 for each trait by adding random environmental error terms to TBVs as Pheno=TBV+e; where e is a random normal deviate sampled from h2 during the breeding program.True breeding values (TBVs) for individuals were calculated as the sum of all QTL effects multiplied by their allelic dosage . Phenotypes were simulated considering the We ran eight cycles of the following PS program. The PS program required a total of 11 years to release new cultivars with six major stages of which four containing a selection step  and these small plots were phenotyped for FY and Per for selection. Equal selection pressure was applied, and phenotypes were standardized. The top 40 small plots were selected based on FY and Per and 25 plants from the top 80% plants for FY and Per within each small plot were cloned to be planted in a single row trial. This resulted in 1,000 plants  being grown in single rows and phenotyped for HD and Q, which is stage four . In stage five , the top 500 rows for Q were selected and were grouped into 50 synthetic populations where each involved 10 rows with similar HD phenotypes. In the final stage , the 50 synthetic populations were planted in large plots and the top 20 large plots were selected as cultivars for the next breeding cycle based on their FY and Per performance. Again, both FY and Per were selected for simultaneously using an index with an equal 50% weight for each trait.Index = Σ biXi, where bi is the index weight and Xi is the plant GEBV for trait i. The cultivars released after the fourth PS program were used to commence the first SpeedGS cycle, while the small plots from the first four phenotypic cycles  were genotyped and used as a reference population to train the GS prediction equation for all five traits. The genotyping for small plots were recoded as the allelic dosage of SNPs  calculated using 20 randomly selected plants per plot  involved the same stages as the phenotypic program except for replacing the first two conventional stages with the 1-year SpeedGS stageScenario two (6 years) omitted the single row stageScenario three (7 years) left out the small plots stageScenario four (4 years) omitted both the small plots and the single row stages so it had the shortest cycle.The initial population  developing the synthetic cultivars from five plants instead of ten; and 2) developing the initial population starting from cycle 5 from 100, 200 or 1,000 crosses instead of 50 crosses × 100 plants. We kept the same pairwise crossing scheme but involved more plants per cultivar to be crossed. In other words, we aimed to study the effect of reducing the number of full-sib plants in the initial population.He) of the hexaploid population after its first appearance every 5,000 generations to ensure that the population reached equilibrium between mutation and drift and to be compared with empirical values and expected values given the simulation parameters. However, given the limited information available on tall fescue, we compared it with ryegrass as it is expected to have similar LD with tall fescue (Ne) considering the mutation rate as [E(r2) = 1/(2+4NeC) + 1/n]; in which C is the genetic distance in Morgan and n is the sample size. The expected He was calculated following He) = 4Neµ/(8Neµ+1)]; in which µis the mutation rate. Two-sample student’s t tests were performed to investigate the level of significant differences between scenarios or different analyses, where required. Throughout the manuscript, comparisons with p<0.01 were declared to have significant differences.We tracked the linkage disequilibrium (LD) and heterozygosity  method implemented in the R package Bayesian Generalized Linear Regression, BGLR . BRR assc5) and av.(TBVci) are the average TBVs of the initial population in cycle five and cycle i (i ranged from six to nine), and std.(TBVc5) is the TBV standard deviation in the fifth cycle initial population. In cycle nine, we only generated the initial population to track genetic gain.where av. (TBVF). The genomic relatedness matrices (GRM) for initial populations were generated following the first method described in ΔF) between neighboring cycles (cycle c and c-1) was calculated according to The initial populations of breeding cycles five to nine were also used to track the increase in the inbreeding coefficient  higher genetic gain per cycle Table S1The genetic gain of all four SpeedGS scenarios were comparable after each SB round for HD. PS performed significantly better than all four scenarios for HD when considering SB1, but was comparable to SB2 (PS slightly higher) and SB3 (PS slightly lower). For FY, scenario one performed better than all other scenarios followed by scenarios two and three. Scenarios one and two consistently showed significantly higher genetic gain compared to scenario four, while their differences from scenario three were not significant except between scenario one and three for SB3. The PS exhibited significantly higher genetic gain than scenario four for SB1 and significantly lower genetic gain than scenario one for SB2 as well as scenarios one and two for SB3. Scenarios one and three showed significantly higher genetic gain for SY compared to scenarios two and four as well as the PS for all SB rounds. SY genetic gain for scenario two was significantly higher than the PS only for SB3.All SpeedGS scenarios, regardless of the number of SB rounds or the crossing scheme, resulted in significantly higher genetic gain compared to PS for Per, which had the lowest heritability. Scenarios one and two steadily showed significantly higher genetic gain compared to scenarios three and four. For the trait Q, PS always showed higher genetic gain than scenarios two and four but resulted in no significant differences between scenarios one and three, involving the single row planting stage. Scenarios one and three were not significantlydifferent, regardless of the number of SB rounds, and this was also the case for scenarios two and four. However, scenarios one and three showed significantly higher genetic gain compared to scenarios two and four.Similar to the genetic gain per cycle, having 100 or 1,000 crosses during the SpeedGS stage resulted in no significant differences in genetic gain per unit of time (year), regardless of the scenario or the number of SB rounds. As SpeedGS schemes had a shorter cycle, the general trend showed that they performed better than the PS in most cases especially after three SB rounds Figure 4For HD, shorter scenarios (two and four) always exhibited significantly higher genetic gain except for scenario two with one SB round compared to PS. The genetic gain of the longer scenarios (one and three) was always comparable to PS, although they were slightly higher with three SB rounds. The shortest scenario (four), resulted in significantly higher genetic gain compared to all other SpeedGS scenarios Figure 4The accuracy of GEBVs varied considerably among different SpeedGS scenarios, SB rounds within the SpeedGS stage, and different breeding cycles Table S2All SpeedGS scenarios resulted in larger increases in inbreeding per cycle and reductions in genetic diversity compared to PS even when only one SB round was applied. Extra SB rounds resulted in higher inbreeding rate Table S3As SpeedGS schemes resulted in higher inbreeding rates, we tried to investigate possible modifications to the proposed SpeedGS programs that can limit this sharp increase , while the remaining scenarios were reduced forms omitting steps. The selection for HD happened only during the SpeedGS stage, which is a common feature in all scenarios explaining its comparable gain per cycle across scenarios with the same number of SB rounds Figure 3PS outperformed all scenarios per cycle when considering GS only (SB rounds = 1) for both HD and Q Table S5In concordance with previous reports e.g. , shortenWe also tested whether omitting the small plots and/or the single row stages resulted in any tradeoffs regarding to genetic gain. The small plots stage takes two years but it adds an extra selection step for FY and Per. Comparing scenario two with scenario four or scenarios one with scenario three, which differ only with the small plots stage, showed that there was similar genetic gain between reducing cycle time and increasing selection intensity Figure 4Generally, the accuracies of GS achieved in our study were low for all traits. The reasons could be due to a small size of reference population  and infeThe first SpeedGS cycle had exactly the same starting reference population resulting in non-significant differences in prediction accuracy across the four scenarios. After each breeding cycle, the reference population was updated with 150 new plots  in scenario one and two or 100 large plots for scenario three and four. For this reason, the accuracy of the first two scenarios was generally higher than the other scenarios for later cycles except for HD, but, on the other hand, it requires more labor resources. The accuracy for HD prediction in scenario four was slightly higher than other scenarios mainly due to the lower number of random recombination rounds (generations) during meiosis around HD QTL, while it received no selection emphasis in any of the omitted stages. In the first three scenarios, extra selection steps happen on traits other than HD which will just randomly break the linkage disequilibrium between the genotyped SNPs and HD QTL without contributing to any sort of selective sweep around them . Thus, hThe accuracy of GS is expected to decrease when implementing more SB rounds in one cycle due to the extra crossing step shifting the population away from the reference population. Interestingly, the decrease in accuracy was not linearly correlated to the increase of the number of SB rounds. A larger decrease was observed in the scenarios with two SB rounds compared to the further decrease in the scenarios with three SB rounds for all traits across cycles. Accuracy stabilized after four SB rounds for all traits . Habier Previous GS studies on perennial ryegrass resulted in comparable or higher prediction accuracies in comparison with our simulation. Increasing the selection rounds and intensities through SB increases the risk of running out of heterozygosity due to extensive inbreeding. This can increase the opportunity for deleterious recessive genes to become prevalent after a few cycles of breeding program and can lead to inbreeding depression . PreviouVarious mathematical methods have been tested for controlling inbreeding in animal/plant breeding . Lin et The present study has investigated the potential of utilizing both speed breeding and genomic selection (SpeedGS) in the breeding programs of allogamous crops using stochastic computer simulation. Although low prediction accuracy for different traits was reported, all proposed SpeedGS schemes outperformed the conventional phenotypic selection scheme and the higher the number of speed breeding rounds, the higher the genetic gain obtained. Persistency, which had the lowest heritability, showed the highest improvement in SpeedGS schemes over the conventional phenotypic selection program. The reference population for the first SpeedGS cycle started with 400 plots which were updated with 100/150 plots every cycle. This small number was chosen to investigate genetic gain with the minimal possible prediction accuracy when resources are limiting. The optimal utilization of SpeedGS would require plant breeders to carefully consider its impact on inbreeding. The present study showed that increasing the diversity of parents used in multiple stages of the breeding programs can significantly reduce the inbreeding gain. Other mathematical models should also be used to further reduce the inbreeding rate and ensure long-term genetic gain. Moreover, similar comprehensive studies should also be done to simulate the potential of SpeedGS in self-pollinated crops.The datasets generated for this study are available on request to the corresponding author.AJ: planned the study, ran the simulation and data analysis, developed the new QTL simulation model, and drafted the manuscript. ZL: assisted with the phenotypic selection simulation. LP, NC: provided information of tall fescue breeding program parameters. HD: planned the study, supervised the work. ZL, LP, NC, GS, BH, HD: revised the manuscript. All authors read and approved the final copy of the manuscript.The authors acknowledge financial support from DairyBio, a joint venture between Agriculture Victorian and Dairy Australia, and the Royal Barenbrug Group, Netherlands.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The production of most farmed molluscs, including mussels, oysters, scallops, abalone, and clams, is heavily dependent on natural seed from the plankton. Closing the lifecycle of species in hatcheries can secure independence from wild stocks and enables long-term genetic improvement of broodstock through selective breeding. Genomic techniques have the potential to revolutionize hatchery-based selective breeding by improving our understanding of the characteristics of mollusc genetics that can pose a challenge for intensive aquaculture and by providing a new suite of tools for genetic improvement. Here we review characteristics of the life history and genetics of molluscs including high fecundity, self-fertilization, high genetic diversity, genetic load, high incidence of deleterious mutations and segregation distortion, and critically assess their impact on the design and effectiveness of selective breeding strategies. A survey of the results of current breeding programs in the literature show that selective breeding with inbreeding control is likely the best strategy for genetic improvement of most molluscs, and on average growth rate can be improved by 10% per generation and disease resistance by 15% per generation across the major farmed species by implementing individual or family-based selection. Rapid advances in sequencing technology have resulted in a wealth of genomic resources for key species with the potential to greatly improve hatchery-based selective breeding of molluscs. In this review, we catalog the range of genomic resources currently available for molluscs of aquaculture interest and discuss the bottlenecks, including lack of high-quality reference genomes and the relatively high cost of genotyping, as well as opportunities for applying genomics-based selection. Molluscs comprise a diverse Phylum comprising ten classes and some 85,000-extant species. The majority of the 80-individual species farmed come from the Classes Bivalvia, Cephlapoda, and Gastropoda. Bivalves, namely clam, oyster, scallop and mussel species, dominate in terms of tonnage and economic value Figure . In totaAdvances in sequencing technology have provided a powerful set of genetic tools which can facilitate the establishment of hatchery-based breeding programs  and mutation rate  and deviation from expected Mendelian ratios (segregation distortion) in pair crosses. These phenomena have been observed across the major groups of cultured molluscs and with a variety of marker types, including allozymes  spawned and reared in common conditions to be 0.015 and 0.511 (more than a 30-fold difference), presumably due to very different levels of genetic diversity in the two stocks. Drawing general conclusions from heritability estimates is also confounded by the fact that heritability for the same trait can change dramatically depending on the life stage at which the trait is measured. For example, heritability for shell length was shown to increase with age in red abalone  selection, in which selection is performed solely based on the phenotypes of individuals  in Australia and a family-based program for greenlip (GreenShell™) mussel  in New Zealand. The breeding program for blue mussel was initiated in Victoria, Australia in 2008 with a founder population of 74 full-sib families  for key production traits.https://www.ncbi.nlm.nih.gov/assembly/GCF_002022765.2/).Declining costs of next-generation DNA sequencing has made it possible to sequence the entire genome of nearly any species in a cost-effective manner. Genome sequences allow genetic markers to be mapped to a specific location in the genome, and when genetic markers associated with particular traits are identified, a genome sequence provides the opportunity to investigate nearby genes or genetic elements to potentially identify causative mutations. As of 2017, there were 22 published, scaffold-level genome sequences for finfish  for traits of commercial interest and for the development of marker assisted selection (MAS) programs  just 10 were found to provide consistent PCR amplification across 74 full-sibling families. Only 62.5% of 2,536 offspring tested could be assigned to single parent pairs using the remaining 10 microsatellites  reached 97% accuracy . QTL mapping is the process of identifying genetic marker alleles that segregate non-randomly with QTL and positioning those loci in the genome  has traditionally relied on linkage-based methods of identifying QTL, in which one or more families are genotyped and scored for a trait of interest, and the co-segregation of markers and trait values are observed for each family  has become an important aspect of genetic improvement in livestock and plant breeding , is the extension of MAS to a genome-wide scale. Rather than targeting specific QTL, GS assumes that genetic markers  are genotyped at sufficient density such that all QTL are in linkage disequilibrium with at least one marker (Meuwissen et al., Patinopectin yessoensis; Dou et al., MAS and GS have yet to be applied in breeding programs for molluscs, although several studies in other aquaculture species have demonstrated increases in accuracy of breeding value predictions for traits such as growth (Tsai et al., Challenges for incorporating genomic approaches in breeding of molluscs include high rates of larval mortality, high incidence of marker segregation distortion, and self-fertilization. A better theoretical understanding of these processes in molluscs will lead to the development of strategies for more optimally balancing control of inbreeding and genetic gain. In addition, the transition from low to high-throughput genotyping technologies will alleviate marker-specific issues such as local segregation distortion, because these markers can be removed from a large dataset with minimal impact on the results. The lack of high quality annotated reference genomes and studies to understand the genetic architecture of important production traits for key species is also a bottleneck for the adoption of genomics-based breeding. Only three of the top ten cultivated molluscan species Table  have hadProviding these bottlenecks can be overcome, the gains in accuracy of breeding value predictions that can be obtained using genomic data, along with optimized control of inbreeding, should enable more rapid rates of genetic improvement in cultured molluscs compared to traditional selection schemes.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.IJ is Chief Executive Officer of Xelect Ltd. and CH is a consultant for Xelect Ltd.


Osteoglossum) are emblematic species widely distributed in the Amazon and surrounding basins. Arowana species are under strong anthropogenic pressure as they are extensively exploited for ornamental and food purposes. Until now, limited genetic and cytogenetic information has been available, with only a few studies reporting to their genetic diversity and population structure. In the present study, cytogenetic and DArTseq-derived single nucleotide polymorphism (SNP) data were used to investigate the genetic diversity of the two Osteoglossum species, the silver arowana O. bicirrhosum, and the black arowana O. ferreirai. Both species differ in their 2n  and in the composition and distribution of their repetitive DNA content, consistent with their taxonomic status as different species. Our genetic dataset was coupled with contemporary and paleogeographic niche modeling, to develop concurrent demographic models that were tested against each other with a deep learning approach in O. bicirrhosum. Our genetic results reveal that O. bicirrhosum colonized the Tocantins-Araguaia basin from the Amazon basin about one million years ago. In addition, we highlighted a higher genetic diversity of O. bicirrhosum in the Amazon populations in comparison to those from the Tocantins-Araguaia basin.The South American arowanas (Osteoglossiformes, Osteoglossidae,  Amazonia is the ecosystem hosting the highest amount of biodiversity in the world . Such anOsteoglossum (Osteoglossidae), are widely distributed in the AMb, as well as in some of its neighboring basins [Osteoglossum ferreirai and the silver arowana, Osteoglossum bicirrhosum. However, cryptic diversity is potentially present in the genus, as suggested by substantial differences among populations of both species, particularly at reproductive strategies and growth patterns [Osteoglossum ferreirai occurs in Negro and Orinoco river basins, living mainly in acidic blackwaters, like in the Negro, Bita, and Tomo rivers [O. bicirrhosum lives in clean and alkaline waters of the Amazon, Tocantins-Araguaia (TAb), and Essequibo basins [The ichthyofauna of the Amazon basin is the richest worldwide with representatives of many taxonomic groups ,8. One og basins . Two aropatterns ,11, and patterns . Osteoglo rivers ,14. Meano basins . It is po basins . Both aro basins .O. ferreirai, assigned with a LC (least concern) status, but suggest that this classification needs updating [Osteoglossum bicirrhosum is only included in the Red Book of the Colombian freshwater fishes [O. ferreirai is considered as an En (endangered) species. Because of the significant strength of anthropogenic threat affecting these two species, and the few genetic studies available [Both species are under anthropogenic pressures, where the silver arowana is highly exploited as a food source and the black arowana used as ornamental purposes ,16,17,18updating . Osteoglr fishes , classifvailable ,22, compThe advent of new technologies involving high-throughput sequencing to obtain large genetic datasets in non-model organisms allows investigating genetic variation from markers scattered along the species’ genome, resulting in more accurate inferences . SeveralThe recent combined use of cytogenetic and refined molecular studies has allowed a better understanding of both intra- and interspecific cytogenomic organization and differentiation . RecentlIn this study, we characterized the cytogenetic and genomic patterns of natural populations from both black and silver arowanas to evaluate the genetic differentiation between and within species and to contribute to better strategies for their conservation. The genomic information was coupled with geographic climatic models to design possible demographic events that led to the current distribution of the species. For this purpose, we assessed data from several parts of the specimens’ genome isolated with DArTseq, and also retrieved information about conserved genomic regions as revealed by cytogenetics techniques, which provides a wider overview of their genetic organization.The number, sampling sites and sex of the individuals are presented in Mitotic chromosomes were obtained following the protocol by Bertollo et al. . The expO. ferreirai and O. bicirrhosum from the AMb localities were labeled with Aminoallyl-dUTP - ATTO-550 (red) and Aminoallyl-dUTP - ATTO-488 (green) using Nick-translation labeling kit , respectively, and hybridized against the chromosomal background of O. ferreirai. The final hybridization mixture for each slide contained 500 ng of each labeled gDNA and 25 μg of unlabeled C0t-1 DNA from both species , while the gDNA of individuals from AMb was labeled with Aminoallyl-dUTP - ATTO-488 (green), both using Nick-translation labeling kit . The final probe cocktail was composed by 500 ng of gDNA of individuals from TAb + 500 ng of gDNA of individuals from AMb + 15 μg of derived C0t-1 DNA of specimens from both populations. The probes were ethanol-precipitated, and the dry pellets were dissolved in hybridization buffer containing 50% formamide, 2 × SSC, 10% SDS, 10% dextran sulfate and Denhardt´s buffer, pH 7.0. The CGH experiments were performed according to Symonová et al. [Two different experimental designs of comparative genomic hybridization (CGH) were used. The first one focused on interspecific genomic comparisons and, in this case, gDNAs of k et al. ), dissolá et al. .At least 30 metaphase spreads per individual were analyzed to confirm the diploid chromosome number (2n) and CGH results. The images were captured using an Olympus BX50 microscope  with Cool SNAP, and processed using Image-Pro Plus 4.1 software .Tissue samples  were senO. ferreirai only (O. ferreirai dataset) and the other for O. bicirrhosum only (O. bicirrhosum dataset). This approach was adopted to maximize the number of markers for subsequent analyzes. Only one aleatory SNP per locus was maintained from the selected loci.Demultiplexed raw data, provided by the sequencing facility, was processed with ipyrad v.0.7.28 . SequencO. bicirrhosum datasets. Runs were executed with a prior odd value of 100, 5000 MCMC chains, and thinning of 10. A total of 20 pilot runs of 5000 iterations were done, burn-in was set to 50,000. Loci with a False Discovery Rate (FDR) value lower than 0.01 were considered as outliers.In order to search for markers that are possibly under selection, a BayeScan  analysisHO—observed heterozygosity; HE—expected heterozygosity; GIS—inbreeding coefficient) were generated for O. bicirrhosum and O. ferreirai separately. Pairwise STF between all O. bicirrhosum sampling locations was also recovered.Genetic diversity was assessed with Genodive ; summaryO. bicirrhosum across the two basins, using the O. bicirrhosum dataset.The genetic diversity distribution between the two species was assessed with a principal coordinate (PCoA) analysis carried in the R package dartR . A subseO. ferreirai dataset with K from 1 to 2, and O. bicirrhosum dataset with K from 1 to 4.Population structure was also assessed using the Bayesian approach implemented in fastSTRUCTURE v.1.0 , a methoO. bicirrhosum dataset, as it contains multiple localities. Spatial methods are usually less prone to artificial cluster detection in the presence of isolation by distance (IBD) and are advised for studies with focal groups more prone to IBD, as freshwater fishes [Because of the small number of localities, isolation by distance (IBD) tests would not have statistical power to give reliable results. Therefore, the spatial analysis implemented in GENELAND  was alsor fishes . The runr fishes , for prer fishes  input fir fishes .O. bicirrhosum, genetic data were simulated in ms [−9 mutations per site per year was used, according to suggested by Oliveira et al. [Arapaima . Effective population size (Ne) was sampled from a uniform distribution ranging from 10,000 to 1,000,000 individuals. Four different scenarios were selected to simulate 50,000 datasets in each of them with a Python script modified from Perez et al. [Ne* μ formula. The divergence time between the basins (DT) was set to 0 on model 1 and sampled from a uniform distribution between 0 and 2 million years ago (MYA) for the subsequent models. The coalescent divergence time (CT), which is the required parameter in ms, was calculated from each sampled DT value based on the DT/4*Ne*G formula. The intensity of the population reduction during colonization (θrF-A) was estimated as a ratio of the θ value during colonization over the θ in the ancient population. Values were sampled from a uniform distribution ranging from 0.01 to 0.1. For the magnitude of population expansion after colonization (θrC-A), the ratio between θ values in the contemporary and in the ancient population (sampled from 0.1 to 1) were used. Only models 3 and 4 considered the priors for founder effect intensity and growth ratio.To compare demographic models in ed in ms  based oned in ms . A mutata et al.  for the z et al. . The fir6 simulations was generated under this model, for further parameter estimation using the same neural network architecture. To infer the estimation capacity of the CNN, a Root Mean Squared Error (RMSE) and Spearman’s ρ were calculated for each parameterThe simulated scenarios were then compared with a convolutional neural network (CNN). CNN is an artificial intelligence method that can be used to learn to identify patterns and then predict those patterns on new data, not seen before by the network. The architecture of the CNN consists of a set of layers that apply mathematical functions to the data that passes through it, generating outputs for subsequent layers. Convolutional layers are followed by pooling layers that summarize the results from previous layers. CNNs can be applied to genetic data because of its high capacity to detect patterns on images and matrices . Our genO. bicirrhosum and O. ferreirai were estimated for both species based on occurrence data for O. bicirrhosum  and O. ferreirai , mixturis , multivs , surfacop , classiis , generals , generals , random forests , and max. Calibr has 2n = 56 for all populations analyzed, the black arowana (O. ferreirai) differs by presenting 2n = 54 as previously described in Suzuki et al. [Osteoglossum species showed a high diversity level emphasizing their repetitive DNA content. In fact, only a limited number of overlapping hybridization signals were observed, restricted to the heterochromatic blocks, which were widely present in the centromeric regions of some chromosomes. Several chromosome pairs of O. ferreirai showed species-specific sequences with abundant hybridization signals on their centromeric region  even with fewer samples (E) was slightly higher than the observed (HO) for all tested populations. Inbreeding levels were smaller for Tocantins-Araguaia locations and higher in Amazon locations as suggested by GIS values (ST estimates reinforced the similarity of the TAb specimens (0.059), with a high differentiation from samples of AMb . The individuals of O. ferreirai presented an HE value higher than that of the individuals of O. bicirhossum from TAb but lower than that of the individuals of O. bicirhossum in AMb. A higher GIS was also observed in O. ferreirai when compared to all other localities, suggesting higher levels of inbreeding.Higher genetic diversity was observed in  samples . ExpecteS values . PairwisOsteoglossum  was the easiest to predict with 99% accuracy. The scenario 2 (vicariance) had an accuracy of 84%, while the third (TAb colonization) and the fourth (AMb colonization) scenarios had 87.1% and 79.3% of accuracy, respectively  and divergence time  were the two parameters that CNN had the highest capability to infer. Conversely, founder effect ratio  and growth ratio  were predicted with less efficiency. Effective population size estimate had a median of 468,195 . Separation time between basins was estimated at Pleistocene, with a median of 1,049,955 . Founder size ratio was estimated with a median of 0.0551 . The estimated growth rate has a median of 0.6454 .A parameter estimation step was then carried under the TAb colonization scenario . EffectiO. bicirrhosum. The analysis generated a distribution in the present that is highly concordant with registered occurrences . The present distribution was also congruent with the occurrences  for urrences A,B. The urrences B. On theurrences C. The laurrences D. For O.urrences E,F, thouurrences G. Duringurrences H.O. bicirrhosum, 2n = 56, and the black arowana, O. ferreirai, 2n = 54. These results corroborate their distinct species status and thus indicate that they already substantially diverge from one another. Accordingly, these species are also associated to different water characteristics in the environments they live  [The two analyzed species have different 2n: the silver arowana, ference) ,70, and ference) . In addiference) ,71.O. bicirrhosum from the AMb is higher than O. ferreirai. DaSilva [O. bicirrhosum has higher diversity levels analyzing microsatellite markers. This can be related to the restricted distribution and the conservation status of O. ferreirai. Our results suggest that interference of past climatic and demographic events, along with contemporary habitat degradation might be factors that influenced this loss of diversity. In addition, economic features may have had also some additional implication. It is known, for example, that when Scleropages formosus fishing was restricted in the 1970s [Osteoglossum increased, but O. ferreirai reached higher selling prices compared to O. bicirrhosum [Overall, the genetic diversity of  DaSilva  also evihe 1970s  not onlyO. bicirrhosum populations was observed by CGH experiments , at ~21,000 years ago, the distribution is even more restricted. At that time, the Amazon region had several suitable areas that could have served as a shelter for O. bicirrhosum populations. Otherwise, the TAb region had a very small area that could have supported such populations. Climatic niche modeling in O. ferreirai evidenced LIG as the harsher period, with the smallest projected suitable area. In such conditions, the species may have suffered a decrease in the population size, with the presence of small populations in Colombia and, maybe, in other Brazilian regions. The simulation suggests that during the LGM, O. ferreirai experienced more marginally suitable regions, mainly in central Amazon basin, where some populations may have persisted. Comparisons between species indicate that O. ferreirai niche was smaller at all periods, which could be related to the habitat preference of this species for dark acid waters. The population reduction in both species should have concomitantly decreased their genetic diversity due to genetic drift. Besides such factors, the hydrological dynamics that occur in the TAb may also directly impact the species diversity levels. This is the case of the flooding events that connect some rivers allowing gene flow and thus making populations more homogenous. In addition, the species behavior cannot be omitted either, as O. bicirrhosum is characterized as a non-migratory species [Based on the current niche projections for both species in the present conditions, we recovered a potential distribution that was similar, but larger than their natural occurrence. Our modeling approach used only bioclimatic variables, an approach similar to other authors when analyzing freshwater fishes e.g., ,75,76). ,76. 75,7 species , that teArapaima species [A. gigas is a very large species, while O. bicirrhosum is much smaller and usually much more abundant where both species occur in sympatry . The other parameters estimated showed low Spearman’s ρ and higher RMSE, evidencing lower capacity of CNN to predict these values. It is important to note that several results obtained here are congruent with recent populational assessments of A. gigas [O. bicirrhosum and A. gigas, mediated by the separation of the TAb and AMb, which can be also responsible for promoting genetic structuring and differentiation in other fish species. Otherwise, distinct events might have promoted the divergence between O. ferreirai and O. bicirrhosum, as both species occur in the Amazon basin, mostly in allopatry, and estimated divergence age is much older. In this sense, as indicated previously, water characteristics associated with different chemical properties may be related to ecological speciation in fishes as found in some other freshwater fishes , and this result agrees with the suggestion of Rossetti and Valeriano  about th species , anotherA. gigas ,78,79, cA. gigas ). This cs .O. bicirrhosum during Pleistocene. When comparing both species, O. ferreirai probably requires a more elevated conservation status than that of O. bicirrhosum, because of its restricted distribution and its association to a specific water type.In summary, our results provided evidence of an overall higher genetic diversity in arowanas from the Amazon basin compared to those from the TAb, suggesting that the latter may be more likely to reach a vulnerable conservation status. It also pointed out that populations from the same basin are more similar genetically and that the species divergence is more ancient than the separation of populations in different basins. For both black and silver arowanas, paleomodeling suggested a larger distribution nowadays than in the past, and our demographic model approach pointed to the colonization of the TAb from an ancient Amazon population in


Aspergillus fumigatus is a potentially deadly opportunistic fungal pathogen. Molecular studies have shaped our understanding of the genes, proteins, and molecules that contribute to A. fumigatus pathogenicity, but few studies have characterized genome-wide patterns of genetic variation at the population level. Of A. fumigatus genomic studies to-date, most focus mainly on single nucleotide polymorphisms and large structural variants, while overlooking the contribution of copy number variation (CNV). CNV is a class of small structural variation defined as loci that vary in their number of copies between individuals due to duplication, gain, or deletion. CNV can influence phenotype, including fungal virulence. In the present study, we characterized the population genomic patterns of CNV in a diverse collection of 71 A. fumigatus isolates using publicly available sequencing data. We used genome-wide single nucleotide polymorphisms to infer the population structure of these isolates and identified three populations consisting of at least 8 isolates. We then computationally predicted genome-wide CNV profiles for each isolate and conducted analyses at the species-, population-, and individual levels. Our results suggest that CNV contributes to genetic variation in A. fumigatus, with ~10% of the genome being CN variable. Our analysis indicates that CNV is non-randomly distributed across the A. fumigatus genome, and is overrepresented in subtelomeric regions. Analysis of gene ontology categories in genes that overlapped CN variants revealed an enrichment of genes related to transposable element and secondary metabolism functions. We further identified 72 loci containing 33 genes that showed divergent copy number profiles between the three A. fumigatus populations. Many of these genes encode proteins that interact with the cell surface or are involved in pathogenicity. Our results suggest that CNV is an important source of genetic variation that could account for some of the phenotypic differences between A. fumigatus populations and isolates. Aspergillus fumigatus is a ubiquitous, saprophytic mold found in soil, compost, and other organic matter, and plays an important ecological role as a decomposer . Taclusters , and sugfhk3 (Afu8g06140) encodes a histidine kinase and is predominantly present at a CN of 1 in population 1, while entirely absent in populations 2 and 3  that displayed divergent CN patterns  functions as a transcription factor that regulates sexual and asexual development [osaA in the A. nidulans genome leads to proliferation of vegetative cells while deletion of osaA results in heightened sexual fruiting and reduces asexual development [Fusarium oxysporum the otholog Sge1 is also confirmed as a transcription factor and is essential for pathogenicity in tomato [Alvoelar macrophages kill swollen conidia with reactive oxygen species (ROS) . To survpatterns . Both geelopment . This geelopment . Multiplelopment . In Fusan tomato .A. fumigatus CNV to better understand their abundance, localization, and potential functional associations. Further molecular and experimental studies are warranted to assess the functional role of CNVs in A. fumigatus. More broadly, to fully grasp the influence of genetic variation on phenotype, there is a need for the A. fumigatus community to combine comparative, population, and quantitative genomics [CNV is an often overlooked source of genetic variation . We havegenomics , 23, 54 genomics –78, protgenomics –82, highgenomics –86, and genomics , 88 and genomics .S1 FigThe scale bar represents the proportion of nucleotide sites at which two sequences that were being compared were different. Isolates colored with red, blue, and yellow correspond to structure populations 1, 2, and 3.(PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S1 File(CSV)Click here for additional data file.


Halyomorpha halys (Hemiptera: Pentatomidae), is an invasive species in North America and Europe that damages many different host plants. Substantial work has been conducted on the genetic diversity and invasion pathways of H. halys in some of the countries where it has been found, based on mitochondrial sequences. The main objective of the present study was to further explore the genetic diversity of invasive populations of H. halys exploiting both mitochondrial and nuclear markers. We used two molecular markers: the mitochondrial Cytochrome Oxidase I (COI) gene, an ideal standardized molecular marker for distinguishing closely related species, and the ribosomal Internal Transcribed Spacer 1 (ITS1), because only a few sequences of H. halys exist to this point in global databases. We used specimens from eight populations from Greece, Italy, Canada, and the US. Among the 14 haplotypes retrieved based on the mtCOI gene, two of them (H162–H163) were detected for the first time. These two haplotypes were found in specimens from Canada, Italy, and the US. Concerning the ITS1 region, 24 haplotypes were identified, with 15 being unique for a sampled population. In Greece and the US, 14 and 12 haplotypes were found, respectively, with 7 and 6 of them being unique for Greece and the US, respectively. Our analysis of the nuclear genes of H. halys indicates high genetic diversity of the invading populations in North America and Europe.The brown marmorated stink bug,  Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), is native to China, Japan, Korea, and Taiwan, and has recently become a global invasive species [Halyomorpha halys is an extremely polyphagous species, with more than 170 documented host plants, including many important agricultural crops [The brown marmorated stink bug,  species ,2,3. It  species , and con species  and subs species , Europe  species ,17,18,19 species , and Sou species . Based o species ,23,24. I species . Halyomoal crops .H. halys outside of its native range has elicited considerable efforts to identify the invasion pathways based on haplotype identification through sequencing. In North America, a single introduction from Beijing, China is most likely to have been the source of invasion of H. halys in the United States, which later spread to Canada. However, in Europe, multiple introductions have occurred, both from H. halys in its native range and possibly also from North America [The introduction and rapid spread of  America ,26,27,28H. halys in North America and Europe have focused mainly on the use of the mitochondrial Cytochrome Oxidase I (COI) gene, coupled with the Cytochrome Oxidase II (COII) gene [rRNA) [cytb) gene [H. halys in Europe, whereas the genetic variability in populations from North America is limited [COI gene has been extensively studied to elucidate the source and genetic variability of H. halys populations, other genetic markers, such as nuclear ones, have been neglected. To our knowledge, two studies based on sequences of the 28S [The genetic studies that have been conducted to elucidate the invasion history of II) gene ,27,28, ttb) gene . These s limited ,26,28. F the 28S  and the  the 28S  have beeH. halys exploiting both mitochondrial and nuclear markers. Therefore, in the present study, we used two molecular markers. Firstly, the COI mitochondrial gene is an ideal standardized molecular marker for distinguishing closely related species, because it is characterized by a fast mutation rate and its sequence is conserved among conspecifics [H. halys exist in global databases  [The ITS1 has been used for population genetic studies ,31, and pecifics . Secondl., NCBI) .H. halys coming from Europe  and North America   . The pop Canada) . CollectCOI mitochondrial gene and a partial fragment of the ITS1 nuclear region. The primer pairs LCO—1490 (5′-GGTCAACAAATCATAAAGATATTGG-3′) and HCO—2198 (5′-TAAACTTCAGGGTGACCAAAAAATCA-3′) [COI gene and the universal invertebrate primers, BD1 (5′-GTGTCCCATTTAATTAGTAGAGA-3′) and 4S (5′-TCTAGATGCGTTCGAAGTGTCGATG-3′) [The genomic DNA (gDNA) was isolated from a single leg from each specimen using a cetyltrimethyl ammonium bromide (CTAB)-based protocol, as described by Milligan . The purATCA-3′)  were useGATG-3′) ,38,39 foCOI gene were performed using the following profile: initial denaturation at 95 °C for 3 min, followed by five cycles of 95 °C for 1 min, 45 °C for 1 min, and 72 °C for 1 min, and by 35 cycles at 95 °C for 1 min, 50 °C for 1 min, and 72 °C for 1 min, and a final step of extension at 72 °C for 2 min. Reactions for the ITS1 region were performed using the following conditions: denaturating at 95 °C for 3 min, followed by 35 cycles of 95 °C for 30 s, 53 °C for 1 min, 72 °C for 1 min, and a final extension at 72 °C for 2 min. All reactions were run on a Verity 96-well Thermal Cycler .Two microliters of the genomic DNA extract were used in 20 μL reactions consisting of 0.2 mM dNTPs, 1.0 μM of each primer, 1 μL Kapa Taq DNA polymerase , and 1× enzyme buffer (KapaBiosystems). Reactions for the Resulting PCR products were purified using the Nucleovac 96 Vacuum Manifold Kit  according to the manufacturer’s instructions, and sequenced in both directions  using the same primers as in the PCR amplification.COI and ITS1 sequences were obtained from a total of 59 and 100 specimens, respectively . Single sequences of each new haplotype were deposited in GenBank under the Accession Numbers MK779996 to MK779997 for COI and MK779975 to MK779995 for ITS1.Both forward and reverse partial ectively . Consens in NCBI . Compari in NCBI ,27,28,34G, parameter = 0.3004 and 0.7690 for COI and ITS1, respectively). Published sequences for both genes available in the database were included as references in the phylogenetic analysis.Aligned sequences were used for determining the phylogenetic relationships between specimens with the MEGA X version 10.0  by usingH. halys, were grouped according to the geographic collection area  because amplification of ITS1 was successful only for a few individuals for the population from North Carolina, US. Diversity measures of the datasets for each country, namely the number of specimens (N), the number of sequences (n), the number of haplotypes (h) and unique haplotypes (H), haplotype diversity (Hd), nucleotide diversity per site (Pi), the number of variable polymorphic sites (S), the average number of nucleotide differences (k), the singleton variable (SVS) and parsimony informative sites (PIS), as well as the population genetic test, Tajima’s D, were calculated using the DNaSP v.6.12.01 package [To produce diversity measures, the different sequences from the amplified fragment of the ITS1, generated from the 100 specimens of  package .COI gene fragment were analysed for a total of 59 specimens of H. halys that were collected from Greece, Italy, Canada, and the US. Among the 14 different haplotypes retrieved, two of them (H162–H163) were detected for the first time, and had not been previously described  (A phylogenetic tree was constructed from sequences of the ih.gov/) . Based oH. halys into two large clusters, both of which consisted of specimens collected from all four countries, without clustering specimens sampled from a single country into the same cluster. The first cluster was dominated by specimens from the US, and the second one by specimens from Greece. In addition, high divergence was observed in the US and Greece, since most of the variants in both countries were clustered into private lineages.In total, 100 individuals were sequenced for the ITS1 region, and 24 variants (denoted as VAR1-VAR24) were identified. The occurrence and frequency of each variant in each sampling site are shown in Genetic diversity data for ITS1, based on haplotype and nucleotide diversity are shown in H. halys in the US based on COI was considered very low [H. halys in the US is not as low as was initially found [H. halys. However, we cannot exclude the possibility that the initial introduced population was dominated by the H1 haplotype, hampering the sampling and detection of other haplotypes.Until recently, the genetic variation of very low . Approxivery low  and Lee very low  reportedly found . It is lH. halys haplotype diversity in Europe , H. halys based on the ITS1 region in countries outside its native range. The introduction and spread of H. halys in North America and Europe have triggered research efforts to identify the pathways of introduction based on the underlying genetics of populations originating from native and introduced areas [COI gene. A few studies were performed on the genetic variability of H. halys by analyzing the COII gene [rRNA) [cytb) gene [H. halys based on sequences of the ITS1 region from 100 specimens. Only three sequences for ITS1 have been reported up to now in the literature [n = 53) likely permits a larger resolution of genetic diversity compared to the other countries examined, where sample sizes were much lower. Interestingly, the US was the second most diverse country.This is the first study to report detailed genetic variability of ed areas ,26,27,46OII gene , the 12Se [rRNA) , and thetb) gene ,29. On ttb) gene . Here, wterature . In the COI haplotypes historically found in the US was considered an indication of a single introduction, at least in the eastern part of the US, our combined analysis of COI and ITS has demonstrated a much higher genetic diversity from specimens in the US. This suggests multiple introductions of H. halys in the US, as also suggested for Europe. Although invasive species initially experience a decrease in genetic diversity, it has been suggested that high genetic diversity due to multiple introductions might allow a species to become invasive, and subsequently to establish, persist, and disperse into new habitats [H. halys occurring both in Europe and North America indicates that the invasions are not affected by genetic bottlenecks or founder effects; two of the most dominant processes influencing the genetic diversity of a species in its new range [While the low number of habitats . Genetichabitats . The higew range .COI gene presents an interesting wrinkle in unraveling the population genetics of this important and devastating invasive species.In summary, our results demonstrate that by exploiting both mitochondrial and nuclear markers, we were able to identify substantial genetic diversity from specimens in the US. Detection of the source area of an invasion is more accurate when multiple molecular markers are combined. The greater diversity of the ITS1 region relative to the mitochondrial