Genomic technology can now deliver cost effective, targeted diagnosis and treatment for patients. Genetic counselling is a communication process empowering patients and families to make autonomous decisions and effectively use new genetic information. The skills of genetic counselling and expertise of genetic counsellors are integral to the effective implementation of genomic medicine.Original papers, reviews, guidelines, policy papers and web-resources.An international consensus on the definition of genetic counselling. Genetic counselling is necessary for implementation of genomic medicine.Models of genetic counselling.Genomic medicine is a growing and strategic priority for many health care systems. Genetic counselling is part of this.An evidence base is necessary, incorporating implementation and outcome research, to enable health care systems, practitioners, patients and families to maximize the utility  of the new genomic possibilities. There are many challenges ahead, to name but a few, these include: controversies around data use and sharing across international borders, the need for standardized methods for interpretation of genomic data, the streamlining of reliable quality-assured results delivery within a clinical setting, maximized clinical utility of results while minimizing the uncertainty of the information and managing uncertainty about which data to return in the clinical setting. However, learning from existing clinical services, the UK 100,000 Genomes Project and other similar projects are already enabling genomic diagnoses to be delivered within health care settings.4The drive towards the vision of genomic medicine is informed by various large-scale sequencing projects across the world. One of the UK 100,000 Genome Project’s aims is to transform the National Health Service by integrating genomics into mainstream clinical care.8Traditionally, genetic testing and genetic counselling within the UK has taken place within NHS regional genetics centres in tertiary care. The focus has been predominantly on rare syndromes and disorders showing Mendelian inheritance patterns. Genetic counsellors work as part of the multidisciplinary health care team providing expertise both in the science of genetics as well as facilitating the inevitable inter-generational  conversations from the psychological impact of the science. There is an ongoing debate as to the tasks of genetic counselling in this traditional domain and the developing roles in relation to genomic medicine.10 In England, as part of the workforce development initiated through the investment in the development of genomic medicine, the NHS scientist training programme offers a genomic counselling branch to equip practitioners to work under the current professional title of genetic counsellor. This is a new addition to existing routes into practice in the UK which have been provided through master’s level training followed by a competency based assessment and registration with the Genetic Counsellor Registration Board. The ongoing demand for a skilled and competent workforce will require a variety of routes for health care practitioners to develop relevant skills.‘Genetic counsellor’ is an internationally recognized professional title with practitioners having specialist education, assessed competencies in genetics (and now genomics) combined with counselling skills.6It is probable that all health care practitioners will be engaging with genomic medicine in time and as it is ‘mainstreamed’ at scale, health professionals will increasingly be asked to communicate and manage the results from genomic testing. The question is how much of what they will be doing is simply ‘having a conversation based on genomic data’ versus applying some aspects of genetic counselling skills and practice, i.e. will all health professionals be ‘doing’ genetic counselling to some degree? The professional bodies representing genetic counsellors are in a strong position to guide this to resolution. As yet it is unknown what, of genetic counselling skills and theory, will and should be translated into mainstream practice.11 and will not form the focus of this review.There is a growing market in genetic tests available directly to the consumer and both the American College of Medical Genetics and the European Society for Human Genetics have recommended that genetic counselling is made available to online customers. This is further discussed in a recent position paperIn this review the developments in and challenges for genetic counselling, both as an activity and a profession, will be discussed in relation to genomic medicine, but focussed on practice within health care settings.A structured search of Web of Science, PubMed, Embase and CINAHL was conducted using the search terms ‘genetic counselling’ and ‘genomic medicine’. Articles were included if they presented empiric data or detailed discussion on the practice of genetic counselling in health care settings. They were excluded if they referred solely to healthy population genome sequencing studies, sequencing in a research setting or direct to consumer or commercial genetic testing. Bibliographies were scanned to retrieve additional relevant articles and policy documents. The websites from Professional Societies relevant to genetic counselling practice in Europe, North America and Australasia were reviewed for applicable policy documents. The summaries below offer an overview of the issues represented in published material. However, this is not a systematic review, and the topics selected for presentation are guided by the experience of the two authors. Our aim is to reflect on the climate of genomic medicine, view this through a genetic counsellor lens and articulate the issues of importance to genetic counselling practise.12 Definitions of genetic counselling have evolved over time, however professionals trained in genetic counselling traditionally have assessed an individual’s risk of a genetic disorder, prepared individuals for genetic testing, communicated the results and assisted the management of the patients’ genetic disease as well as preparing and supporting the individual to contact their relatives also at risk of the same disease. Patients would attend genetic services either to obtain a diagnosis of a genetic condition or because they knew of a condition in their family and wanted to understand their own options and choices for managing the consequences of the condition.There is consensus among professional bodies around the world that the act of genetic counselling is a client-centred communication process with the aim of helping patients understand, adapt and adjust to the medical or psychosocial consequences of genetic contributions to disease.13 In the era of genomic medicine the debate as to where to focus expertise continues.There is long history of conceptualizing genetic counselling as teaching and counselling or more recently a very circumscribed form of psychotherapy.an emerging medical discipline that involves using genomic information about an individual as part of their clinical care (e.g. for diagnostic or therapeutic decision-making) and the health outcomes and policy implications of that clinical use.In discussions of the implications of genomic medicine, the term ‘genomic counselling’ has started to be used. It is unclear how this is differentiated from the act of genetic counselling but it is related to the developments in technology and the desire to create genomic medicine defined by the National Human Genome Research Institute as:14 We now know that much of the relevance, across clinical specialities, will be using molecular testing for screening, diagnosis and to guide treatment15 and thus genomic medicine will eventually become simply ‘medicine’. The focus on technology and data in definitions of genomic medicine is important but there should also be a recognition of how the information generated is incorporated into the lives, experiences and health care decisions of individuals.The earliest use of the term ‘genomic medicine’ was in the title of a Commentary paper, in 2009. Here the argument was made that information from a whole genome should be part of an integrated electronic health record. The implication being that genomic data would be available for use across health services in all medical specialities. The whole clinical team would be involved in using this data in the management of patients.17 How to communicate and make decisions about ‘secondary’, ‘incidental’ or ‘additional findings’ are also an active area of discussion.18 The terminology around these findings is used inconsistently but broadly they relate to results within the sequence that are found or searched for deliberately, that are secondary to the reason for doing the sequence to start with. There is also a confusion between issues relating to sequencing technologies used in: (a) a clinical setting as a technology to answer a clinical question with return of results related to that clinical question, (b) sequencing used in a healthy population with the intention of returning clinically actionable results and (c) sequencing used for research cohorts with the possibility of returning ‘results’ to participants (including raw sequence data). The response to these challenges will depend on the context within which the technology is being used.The challenges relating to storing, interpreting and using data generated from genome sequencing are well rehearsed and remain.Genetic counsellors have skills enabling them to be involved in all stages of the patient’s pathway through genomic medicine, however there is uncertainty, as genetic technologies become more routinely used in health care, what aspects of their practice is necessary and at which time points. It is probable that as genomic medicine becomes mainstream, certain roles that are currently considered as an integral part of genetic counselling practice, may become part of other clinicians’ roles Fig. .19 The two pre-testing counselling sessions focused on information giving about the disease and the genetic risks and exploration of how the patient would incorporate their potential new genetic status into their lives, once they had the results. The aim was to facilitate an informed decision about whether to have the test, who should be tested and when the test should be performed and also to address the emotional context of the test decision. This took into account the presence of a highly penetrant single gene disorder, concerns about the history of genetics and incorporated the values of autonomy and non-directiveness into the genetic counselling approach.Historically clinical genetics services were the only healthcare setting where genetic testing could be accessed. Now, genomic technologies can be accessed across the entire healthcare service. Given the extensive experience in working with genetic technologies, clinical genetics services have developed systems for patient management that may be applicable within non-genetics specialisms. One of these systems relates to the process of consent. The ability to offer presymptomatic testing for inherited diseases such as Huntington’s Disease in the 1990s resulted in the recommendation for multi-session counselling prior to taking blood for analysis, thus giving the patient time to psychologically adapt and prepare for a possible future condition where there was no effective treatment or cure.21 As genetic technologies become incorporated into more routine health care decision-making about treatment and management they will become a routine part of diagnostics. It may be that in this context, less focus is placed on the decision about whether to have the test, with a shift to more exploration, post-test as to what the results mean. The consent conversation then moves – where the main body of information about the genetic test result occurs post-test as opposed to pre-test. Once a genetic result is known there becomes a need to have a conversation about the relevance of this to treatment and clinical decision making within the pathway of resolving a medical issue, rather than a personal decision about the desirability and consequences of obtaining genetic information. However, the pre-test information for at-risk relatives, who do not currently have genetic disease, is still as relevant as it ever was and would likely fall within the domain of existing genetic counselling practice. Thus, the care of ‘at risk relatives’, who are not yet unwell, but who are potentially pre-disposed to developing disease, should be referred by primary and secondary care, into tertiary genetics services.As more presymptomatic/predictive testing has been possible for conditions where prevention or management strategies can be recommended, such as cancer predisposition genes, genetic counselling protocols have been shortened. However there is still an emphasis on provision of information and decision making about the test exploring the emotional and psychosocial implications.Genetic counsellors have specific training and skills in communication and genetic science but are a scarce resource. There is a tension developing in where to focus this resource and a need for an evidence base to determine what is best practice and what competencies and skills are required for the health professionals who are responsible for the delivery of genomic health care.23 Questions have arisen as to how information about these possible outcomes should be incorporated into the consent process and how to ensure that consent is appropriate.24 In 2013 the American College of Medical Genetics created some controversy by suggesting that all patients receiving genome sequencing should have an analyses performed to identify actionable genetic variants in a specific list of genes linked to serious, life-threatening disease. These guidelines have recently been updated with a process for nominating new genes.25 The recommendation is that the patient can choose to opt-out of receiving these secondary findings. Other policy statements concerning the clinical use of whole genome technologies, recommend minimizing the chance of generating secondary findings by performing clinically directed tests.26 In the UK 100,000 Genomes Project the decision has been made to limit the possible additional findings that will be analysed.2The availability of increasingly extensive genetic analyses has raised the possibility of more uncertain findings and findings unrelated to the reason for requesting the test. Concern is expressed as to how to ensure appropriate consent for sequencing analysis in various contexts, how to manage the uncertainty of the interpretation of the data and how to communicate that uncertainty back to patients.29 Such research offers helpful exploration for the mechanisms that could be applied to clinical pathways. Recent empirical work interviewing health care professionals consenting patients for genomic testing has reiterated that being informed about all possible outcomes of genetic testing is not possible and moreover may not always reflect appropriate consent.30 The time taken for this detailed consenting process has also been identified as a problematic issue.31 Given the extensive experience that genetic counsellors have developed over the years in consenting patients for genetic testing, their insight offers a valuable contribution to new practitioners of genomic medicine. The consent conversation for a genomic test is multi-faceted. It should cover: the implications of the result, both for the individual patient and also their family (with a recognition that patients are expected to inform their relatives about their result so that they can seek out their own testing where relevant); the types of result that may come back from the laboratory  and what each of these will mean in terms of future risk and disease management and plans for genomic data storage, protection and sharing.The complexities of decisions about testing and informational requirements have focused genetic counselling activity at the beginning of the patient pathway through the genetic testing process. The provision of more detailed information and more choices regarding results has been explored in the context of research studies, where results from sequencing have been returned in the healthy populations and in participants recruited from health care services. Various studies have also explored different ways of presenting information and eliciting preferences for the return of additional findings and results.32 A survey in Europe, prior to setting up the genetic counselling European Registration system, did not identify practitioners working is this role yet.33 In Europe and the UK, as discussed previously, most genetic counsellors work in multidisciplinary teams within the setting of specialist genetic health care. The teams include medically qualified clinical geneticist and laboratory scientists. Emerging models of genomic medicine emphasize the iterative nature of variant interpretation with input from the bioinformatician, the laboratory scientist and the clinician.18 These multidisciplinary teams will often now include a genetic counsellor.35As the technologies used for genetic testing have increased in complexity, genetic counsellors have become involved in new roles. The global number of genetic counsellors is estimated at only 7000, practising in at least 28 countries with over 60% in North America. In North America, Canada and South Africa genetic counsellors are increasingly employed by laboratories. A recent survey identified the main roles as customer liaison/case coordination and variant interpretation/result reporting.36 It is probable that these bioinformatics tools will become more sophisticated over time and remove the need for as much human intervention as there is today.Understanding of genome sequencing technologies and variant interpretation is identified as an important part of the knowledge of genetic counsellors and other health professionals. With increasing volumes of sequencing data there are a plethora of bioinformatics tools being developed which curate and synthesize evidence for variant classification in line with professional guidelines.5In addition to having roles within laboratories, as well as multidisciplinary genetics teams, genetic counsellors are now moving further afield. Genetic counsellors, will often practise autonomously within non-genetics specialisms, for example, joining the specialist ophthalmology, cancer, endocrine, ENT or dermatology clinic. With the mainstreaming of genomic medicine they are now being called upon to train and educate their non-genetics colleagues in genomics. Increasingly genetic counsellors also offer their own independent private practice, in the UK this is happening already within the cancer and pre-implantation genetic diagnosis field. They also may practice full time as academics in education or research as well as policy and industry.Increasingly these roles are being developed independently of the tertiary genetic services in a similar way to the autonomous roles that have developed in other countries for example in North America. As noted above although numbers are small, genetic counsellors practice across both developed and developing countries. How models of care will be implemented is unclear and the mainstreaming conversation includes all members of the health care team. International networks and opportunities for sharing expertise, learning and good practice are growing in genetic counselling, nursing and midwifery and medicine. How this impacts on the development of services in these different health care systems is beyond the scope of this review but is an important question.should have a conversation about the impact of these for relatives. Given that non-genetics clinicians would not routinely care for at-risk, healthy relatives, the future management of such ‘patients in waiting’ will be enabled by a referral into tertiary genetic counselling services. Workforce planning and the need for more skilled staff is recognized as an issue that needs addressing both in the UK and internationally. The genetic counselling work force is integral to this.The implementation of genomic medicine across the whole healthcare service has the potential to significantly increase the demand for clinically practising genetic counsellors. If, as predicted, hundreds of thousands more patients have a genomic test as part of their diagnostic pathway, any complications from this will result in a post-results referral back into clinical genetics. It will be genetic counsellors who will likely pick up these referrals (having expertise in explaining the significance of genomic results and help the patient make sense of these) and also sort out the cascade family testing. For every new genetic diagnosis made in a non-genetics healthcare setting, the clinician who orders the test and delivers the results, 22The large amount of data generated by genomic technologies and the potential for uncertainty is a feature of genetic testing in the genomic era. It has been suggested that genomic medicine will feature heavily on enabling patients to manage and adapt to uncertainty.12 It has been noted however that the ‘teaching model’ within genetic counselling practice, has become predominant with less time being given to eliciting client concerns or providing psychological care.37 There is a debate in the literature as to whether the psychotherapeutic aspect of managing genetic information should be made more prominent13 partly in response to acknowledging that all health care professionals in the future will be having conversations with their patients about genomic results. Such conversation, whilst it might draw on good medical communication skills, is not genetic counselling and while health care professionals may need support in delivering the genomic information they will not be providing genetic counselling per se. Genetic counselling attends to both the educational component and the psychosocial and emotional component of the genomic information and incorporates discussion with relatives.8In the past, genetic services focussed on rare syndromes and inherited genetic disorders. Families with these types of conditions will still be a significant part of genomic medicine practice. The majority of genomic testing used clinically to date is in the diagnosis of single gene disorders. As discussed previously, definitions of genetic counselling as a client-centred communication process incorporate an aim of adjustment and adaptation to the medical or psychosocial consequences of genetic contributions to disease.38 Genetic counsellors have been engaged in research to develop their practice and interventions to assist patients and their families in managing the genetic information.40 However it is recognized that there is a need for greater evidence base for genetic counselling in order that services may continue to evolve to meet the changing needs of patients and families with genetic conditions.10There is evidence that genetic counselling can lead to a range of positive outcomes including increased knowledge, perceived personal control; positive risk behaviours and improved risk perception.In the same way that developing roles in laboratories and variant interpretation are amenable to technology solutions that assist in test selection or interpretation of variants, the educational and information provision aspect of genetic counselling may also lend itself to innovative ways of delivery. For example in August 2017 a genetic testing company announced the formation of a start-up company to develop an internet algorithm (chatbot) to guide patients through their genetic tests. However the provision of information about tests and their potential results cannot ever replace the psychosocial conversation, based on a two-way, patient-led conversation that addresses the needs of patients to adapt and adjust and incorporate this new knowledge into their lives.Examination of the literature and discussions with experts has demonstrated that genetic counsellors are involved at all stages in the pathway of the patient journey through genomic medicine. At the beginning, with genetic risk estimation, decision-making about testing and conversations about consent; in the management and interpretation of results; at the point at which the result enters into the health care system and is returned to the clinician and the patient, at the follow up of patients in mainstream and in helping the patient to seek out and communicate the results within their family. Genetic counsellors are also involved in supporting the patient to adapt to the genetic information and manage the psychosocial consequences of this as it is relevant to the wider family and future generations.As genomic medicine develops it will become clearer as to what aspects of genetic counselling will become part of mainstreamed health services and what aspects will remain within the domain of the specialist genetics workforce. The current focus on information provision prior to the test and managing information generated by the genomic analysis may change as solutions are developed that make this more routine. However, the consequences of the genetic information, particularly as it relates to conditions with implications for future health and familial implications, may need more specialist genetic counselling skills in order that patients and families can adjust and adapt to the information and use it effectively to maximize the health gains from genomic medicine and minimize potential harms.In order to increase the evidence base for practice there is an urgent need for funding and research resources to be focussed on implementation and outcome research. This needs to explore how to enable health care systems, practitioners, patients and families to maximize the utility of the new knowledge. Genetic counsellors with their experience of implementing genetic medicine should be at the heart of effective and responsible implementation of genomic medicine.


To develop and evaluate serological methods for chikungunya diagnosis and research in Nicaragua.Two IgM ELISA capture systems (MAC-ELISA) for diagnosis of acute chikungunya virus (CHIKV) infections, and two Inhibition ELISA Methods (IEM) to measure total antibodies against CHIKV were developed using monoclonal antibodies (mAbs) and hyperimmune serum at the National Virology Laboratory of Nicaragua in 2014–2015. The sensitivity, specificity, predictive values, and agreement of the MAC-ELISAs were obtained by comparing the results of 198 samples  with the Centers for Disease Control and Prevention’s IgM ELISA . For clinical evaluation of the four serological techniques, 260 paired acute and convalescent phase serum samples of suspected chikungunya cases were used.All four assays were standardized by determining the optimal concentrations of the different reagents. Processing times were substantially reduced compared to the CDC-MAC-ELISA. For the MAC-ELISA systems, a sensitivity of 96.6% and 97.4%, and a specificity of 98.8% and 91.5% were obtained using mAb and hyperimmune serum, respectively, compared with the CDC method. Clinical evaluation of the four serological techniques versus the CDC real-time RT-PCR assay resulted in a sensitivity of 95.7% and a specificity of 88.8%–95.9%.Two MAC-ELISA and two IEM systems were standardized, demonstrating very good quality for chikungunya diagnosis and research demands. This will achieve more efficient epidemiological surveillance in Nicaragua, the first country in Central America to produce its own reagents for serological diagnosis of CHIKV. The methods evaluated here can be applied in other countries and will contribute to sustainable diagnostic systems to combat the disease. Alphavirus genus of the Togaviridae family. The 60 nm – 70 nm diameter virion has a phospholipid envelope and a singlestranded positive-sense ribonucleic acid (RNA) genome that encodes three structural and seven nonstructural proteins  is a reemerging arbovirus that belongs to the proteins , 2. It hproteins . CHIKV imosquito . The dismosquito  – 3. ChiIn December 2013, the Pan American Health Organization (PAHO) reported the first case of CHIKV transmission in the Americas. The virus quickly spread from St. Martin to other countries in the Caribbean, as well as to Central and South America  – 10. ThIn Nicaragua, epidemiological surveillance of chikungunya was based on Immunoglobulin M (IgM) detection in suspected cases after the 4th day of illness . InitialAdditionally, a goal was set to implement a surveillance system similar to the one in place for dengue surveillance, where most of the reagents for dengue-specific IgM antibody detection are produced at the National Virology Laboratory  and distributed to 12 laboratories throughout the country. Therefore, the researchers produced a rabbit hyperimmune serum in order to establish a sustainable chikungunya diagnostic and surveillance system through the development of an additional MAC-ELISA. Furthermore, to help predict epidemiological behavior in the coming years, it was necessary to perform focal and national seroprevalence studies to determine the extent of the current epidemic.To this end, two Inhibition ELISA methods (IEM), using the mAbs or hyperimmune serum, were developed to determine total anti-CHIKV antibodies. The IEMs were based on the methods described by Vazquez and Fernandez for dengue , 16. AllTo determine the cutoff (or positivity threshold) values of both MAC-ELISA methods, 137 samples  were processed. The sensitivity, specificity, predictive values, and agreement of both MAC-ELISA systems in comparison with the CDC-MAC-ELISA were determined using 198 additional samples (116 positive and 82 negative), collected an average of 5.9 days after symptom onset (interquartile range [IQR]: 1). All samples consisted of sera from suspected chikungunya cases collected through the national surveillance programs of Nicaragua. The detailed protocol of the CDC-MAC-ELISA is described elsewhere , 18.These studies were approved by the Institutional Review Boards of the Centro Nacional de Diagnóstico y Referencia (CNDR) of the Ministry of Health of Nicaragua and the University of California–Berkeley . The reference method for the clinical evaluation was the CHIKV real-time Reverse-Transcription-Polymerase Chain Reaction (rRT-PCR) recommended by the CDC.In order to obtain hyperimmune serum (HIS), the vaccine strain CHIKV 181/25 , 14 was Anti-CHIKV gamma globulin was precipitated from the HIS using saturated ammonium sulfate, and then conjugated to horseradish peroxidase (HRP) using the periodate oxidation method . An antiAedes albopictus C6/36 HT cells at 33°C in 175-cm2 flasks for 5 days under Biosafety Level (BSL) 2 conditions since 181/25 is a vaccine strain. Three freeze-thaw cycles were performed, then the flask content was centrifuged at 3 500 rpm for 30 minutes (min), and the supernatant was concentrated by osmosis with refined sugar for 24 hours (hr). The presence of the virus was confirmed by rRT-PCR. The antigen was inactivated with formaldehyde (1 : 2 000) and stored at –80° C until further use.CHIKV antigen was obtained by inoculating the vaccine strain CHIKV 181/25 , 14 intoStrips of polystyrene microwells  were coated overnight at room temperature with 100 µl per well of anti-human IgM immunoglobulin at a concentration of 5 µg/ml and 2.5 µg/ml in carbonate buffer  for the IgM capture ELISA using hyperimmune serum (MAC-ELISA-HIS) and monoclonal antibody (MAC-ELISA-mAb), respectively. Wells were washed three times with phosphate-buffered saline (PBS) containing 0.05% Tween20 (PBS-T) and blocked with 1% bovine serum albumin (BSA) in PBS-T for 30 min at 37°C. Then 50 µl of serum diluted 1 : 20 in PBS-T was added and incubated for 1 hour at 37°C. After four washes with PBS-T, 50 µl of CHIKV antigen (1:25 dilution for MAC-ELISA-HIS and 1:50 for the MAC-ELISA-mAb) was added and incubated for 1 hr at 37°C, then washed four times with PBS-T. HRP-conjugated anti-CHIKV antibodies were then added as follows: for the MAC-ELISA-HIS, 50 µl of a 1 : 10 000 dilution of HRP-conjugated anti-CHIKV HIS for 30 min at 37°C; and for the MAC-ELISA-mAb, 50 µl of a 1:10 000 dilution of HRP-conjugated CHIKV mAb 152 for 1 h at 37°C. After five washes with PBS-T, 50 µl of substrate tetramethylbenzidine  was added for 10 min at room temperature, and the reaction was terminated by the addition of 50 µl of 12.5% sulfuric acid. The optical density (OD) at 450 nm was measured in an ELISA reader . Samples with an OD higher than the average of the negative controls plus 3 standard deviations for MAC-ELISA-HIS and greater than the average of the negative controls plus 4 standard deviations for MAC-ELISA- mAb were considered positive. Positive and negative controls consisted of serum samples with known anti-CHIKV IgM responses, as determined using the CDC-MAC-ELISA, that tested negative for Hepatitis B, C, and human immunodeficiency virus (HIV).In all, 96 well-polystyrene plates (Nunc Immuno MaxiSorp) were coated overnight at room temperature with 100 µl per well of 10 µg/ml anti-CHIKV HIS (IEM-HIS) or with 5 µg/ml of CHIKV mAb 187  in carbonate buffer. The plates were washed three times with PBS-T and blocked with 1% BSA in PBS-T for 30 min at 37°C. Then, 100 µl of antigen (1 : 100 dilution for both IEM) was added for 1 hr at 37°C. After four washes with PBS-T, 100 µl of serum , positive control (1:5 120 dilution), and negative control (PBS-T) was added. The plates were then incubated for 2 hr at 37°C. After four washes with PBS-T, 100 µl of HRP-conjugated anti-CHIKV HIS or mAb 152 diluted 1:10 000 in PBS-T with 2.5% of normal bovine serum was added. The plates were incubated for 1 hr at 37°C and washed five times with PBS-T. The HRP-catalyzed reaction was carried out as described for the MAC-ELISA methods. The percentage inhibition (%I) was calculated using the following formula: %I = (1-[sample OD/mean OD of negative controls]) x 100%. Sample titer was then calculated using the Reed and Muench method , accordiTiter = exponential [(%I of the lowest sample dilution with a %I ? 50% inhibition - %I of the highest sample dilution with a %I < 50%) / (%I of the lowest sample dilution with a %≥ 50% inhibition – 50) + log of the lowest sample dilution with a %I ? 50% inhibition]Sample size was calculated using Epidat® software version 4.1  and the following parameters: precision of the sensitivity and specificity estimates, 5%; expected sensitivity and specificity, 95%; and confidence level, 95%. The calculated sample size was at least 193 samples. The sensitivity, specificity, positive and negative predictive values, and their 95% Confidence Intervals (95% CI), as well as kappa indices, were calculated using the statistical package Stata®/MP13.1 .First, the optimal concentrations of the major components of the four serological tests were established. Optimal concentrations of MAC-ELISA-HIS and MAC-ELISA-mAb were determined using a saturation curve . OptimalA summary of the protocols for the two newly developed, in-house MAC-ELISA systems compared to the CDC-MAC-ELISA  is shownA total of 198 serum samples collected from suspected chikungunya cases with known CDC-MAC-ELISA results were processed using the two in-house MAC- ELISA systems and compared to the CDC method. Both in-house systems yielded sensitivity, specificity, and predictive values above 90%  when usiA total of 260 paired acuteand convalescent-phase serum samples from suspected chikungunya cases enrolled in one of two ongoing studies of dengue and chikungunya conducted in Managua, Nicaragua , 18, werSensitivity, specificity, and positive and negative predictive values for all four serological methods were calculated . The fouThis study reports the development, standardization, and clinical evaluation of two MAC-ELISAs and two IEMs for the diagnosis and surveillance of chikungunya. In order to evaluate our MAC-ELISA systems, 198 serum samples collected via the national surveillance system were processed using both (MAC-ELISA-HIS and the MAC-ELISA-mAb) ELISA and compared to the CDC-MAC-ELISA as the reference method. A sensitivity of 97.4% and 96.6% and a specificity of 98.8% and 91.5% were obtained for the MAC-ELISA-HIS and MAC-ELISA-mAb, respectively. These results are consistent with results reported for similar assays. For instance, the MAC-ELISA developed by Wasonga and colleagues had a sensitivity of 97.6% and a specificity of 81.3% compared to the CDC-MAC-ELISA. Blacksel and colleagues  evaluateA substantial achievement of the present study was to reduce the processing time from 48 hours for the CDC-MAC-ELISA to 2.5 – 3 hours for the in-house MAC-ELISA systems. In addition, the in-house MAC-ELISA assays enabled savings in supplies and reagents because they do not use a non-viral antigen control for each sample. Thus, 90 samples can be processed in one plate without affecting the assay specificity, whereas the CDC technique only allows 45 samples per plate. The decision to use more concentrated samples (1 : 20 instead of 1 : 400 as recommended in the CDC protocol) was made to facilitate the work-flow. The lower dilution allows the samples to be diluted directly into the plate, instead of having to predilute the samples prior to adding them to the plate.In addition to the assays for detecting CHIKV-specific IgM antibodies, we developed two Inhibition ELISA methods that measure total anti-CHIKV antibodies. These assays can be used for diagnosis of chikungunya in paired acute and convalescent samples. In addition, they can be used to conduct seroprevalence studies that enable determination of current chikungunya epidemic’s magnitude, and therefore, help predict the potential of future epidemics. A similar method for the detection of total anti-dengue virus antibodies has been used in Nicaragua for 17 years by a clinical study of dengue at the National Pediatric Reference Hospital  and for 12 years in the Pediatric Dengue Cohort Study , 28. BasA total of 260 paired acute and convalescent samples collected through both Nicaraguan research studies were processed using all four new serological methods. Results were compared to those from a CHIKV rRT–PCR assay performed on the acute sample. As expected, the sensitivity of the MAC-ELISA was low for samples collected in the acute phase (average of 2.0 days after symptoms onset), but high for samples collected in the convalescent phase (average of 21.6 days after symptom onset). This result was consistent with the fact that detection of IgM is not useful in the first days of illness  – 32. ThOne limitation of the study was the lack of a gold standard method for the standardization of the IEM. However, the clinical evaluation of the IEM with the 260 paired samples demonstrated the utility of this technique, with ~95% sensitivity and specificity when compared with testing of acute samples by rRT-PCR. These results are similar to those obtained by Balmaseda and colleagues  when theSince the standardization and evaluation of these different serological methods was accomplished, the chikungunya MAC-ELISA-HIS assay has been decentralized to 12 regional laboratories in the country, a significant improvement for national epidemiological surveillance. Currently, all of these laboratories are able to identify and differentiate dengue and chikungunya cases using MAC-ELISA. Also, two studies, one local and one national, of chikungunya seroprevalence were conducted using the IEM assays to determine the attack rate of CHIKV infection in Nicaragua .Two MAC-ELISAs and two IEMs for chikungunya diagnosis and research were developed, standardized, and evaluated by this study. These assays currently support epidemiological surveillance of chikungunya at the national level in Nicaragua, as well as more focused research studies in Managua. Nicaragua has thus become the first country in Central America with the capacity to produce its own reagents for serological diagnosis of chikungunya. Nicaragua’s experience can be extended to other countries, and thus contribute to the sustainability of chikungunya diagnosis and to the fight against the dengue and chikungunya epidemics that are currently affecting the Region of the Americas.We are grateful to Michael S. Diamond at Washington University  for providing the CHIKV mAbs and 181/25 vaccine strain. We also thank José Luis Soto for his significant contribution in the production of hyperimmune serum; María José Vargas, Stephania Ramírez, and Damaris Collado for their help in processing the samples; Andrea Núñez for her invaluable help in the selection of samples and Douglas Elizondo for his significant help on formatting and editing the text. This work was supported by a supplement to R01 AI099631 (AB) from the United States National Institutes of Health .RPSP/ PAJPH and/or PAHO.Authors hold sole responsibility for the views expressed in the manuscript, which may not necessarily reflect the opinion or policy of the


Solanum tuberosum L.) is the fourth most important crop food in the world and Colombia has one of the most important collections of potato germplasm in the world . Little is known about its potential as a source of genetic diversity for molecular breeding programs. In this study, we analyzed 809 Andigenum group accessions from the CCC using 5968 SNPs to determine: 1) the genetic diversity and population structure of the Andigenum germplasm and 2) the usefulness of this collection to map qualitative traits across the potato genome. The genetic structure analysis based on principal components, cluster analyses, and Bayesian inference revealed that the CCC can be subdivided into two main groups associated with their ploidy level: Phureja (diploid) and Andigena (tetraploid). The Andigena population was more genetically diverse but less genetically substructured than the Phureja population . The association mapping analysis of qualitative morphological data using 4666 SNPs showed 23 markers significantly associated with nine morphological traits. The present study showed that the CCC is a highly diverse germplasm collection genetically and phenotypically, useful to implement association mapping in order to identify genes related to traits of interest and to assist future potato genetic breeding programs.The potato ( Solanum tuberosum L. is a herbaceous species that reproduces mainly vegetatively by tubers, distributed from the Southwestern United States to South-central Chile, with centers of diversity located in Central Mexico and in the high Andes from Peru to Northwestern Argentina [Solanum tuberosum contains two cultivar groups, the Chilotanum group comprising lowland tetraploid Chilean landraces [S. tuberosum subsp. andigena and S. stenotonum, and they are cultivated in Peru, with lower frequency in Bolivia, Ecuador and Colombia [rgentina . Potato rgentina . It is crgentina . Solanumandraces  and the andraces . Within andraces , 6. In Aandraces , 7. Theyandraces . AnotherColombia .The conservation of cultivated potato species and their wild relatives in germplasm banks provides long-term availability of crop genetic diversity. The characterization of these collections are essential to identify alleles/genes associated with traits of interest for plant breeding such as resistance to pathogens and insect pests, tolerance of abiotic stresses  and tuber quality , 10. In Genetic diversity could be analyzed from agronomic traits data, but the results obtained are not always robust because the environment often affects phenotypic traits . In addiSolanum section Petota [Currently, two beadchips with SNP array technology for genotyping potato at high-density genome-wide level are available, the Infinium 8K potato SNP array  and the n Petota  and to in Petota , 24, 25 n Petota –28.By combining molecular and morphological data from the potato germplasm of CCC is possible to map simple or complex traits and subsequently to identify candidate genes through Genome-Wide Association Studies (GWAS) or Association mapping (AM). Such studies provide an efficient way to map quantitative trait loci (QTL) in natural populations or germplasm collections because they can detect historical recombination events and provide high mapping resolution –31. The S. tuberosum Andigenum group was conducted based on SNPs markers in order to evaluate its population structure and genetic diversity. Also, the extent of the linkage disequilibrium between pairs of SNPs markers was estimated in order to determine the utility of this germplasm and the molecular markers used to implement association-mapping studies. Accordingly, association mapping in tetraploid potatoes was conducted using morphological traits related with stem, berry, tuber and flower variables.In the present study, a genetic analysis of the CCC of S. tuberosum group Andigenum conserved under field conditions in Zipaquira, Cundinamarca, Colombia  were characterized. Six hundred seventy-five accessions are classified from passport data as Andigena (83.5%), 85 as Phureja (10.5%) and 49 as Chaucha (6.0%). Six hundred and sixteen accessions were collected from different Colombia regions (76.1%), 75 accessions from other countries (9.3%) and 118 accessions do not have passport data (14.6%)  of the CCC-CORPOICA of  (14.6%) , Table 1Fresh young leaves were collected from one plant randomly selected per accession. The material was lyophilized during two days at -50°C and 0.20 mBar. The genomic DNA was extracted using the DNeasy Plant Mini Kit . DNA concentration and quality were checked by visualization in a 1% (w/v) agarose gel and a NanoDrop 2000 Spectrophotometer . Genotyping was performed using the array available in 2013, the Infinium 8303 potato SNP array , 21. Thea priori population information using a tetraploid model . The analyses were conducted by varying the number of possible subpopulations (K) from 1 to 10, with five independent repetitions, assuming an admixture model with correlated allele frequencies and a burn-in of 50.000 and 150.000 iterations. The optimal number of subpopulations was established using the Evanno method [ST) and population inbreeding (FIS) within subpopulations were estimated by an analysis of molecular variance (AMOVA) with 1023 permutations in the Arlequin software [Nm) was estimated through the equation: Nm = (1-FST)/4FST.The population structure analysis was performed using a Bayesian model implemented in the software Structure  without o method  in Struco method . The numo method  conducteo method  in the Ro method  and a Pro method . Coefficsoftware . The genThe genetic indexes, Observed Heterozygosity (Ho) and Expected Heterozygosity (He) were calculated using Genalex software . The Polhttp://biodiversityinformatics.amnh.org). The correlation between geographical, morphological and genetic distances was estimated by a Mantel test [Phenotypic data from fifteen qualitative characteristics of stem, berry, tuber, and flower were used for the morphological analysis . The Platel test  with 100tel test . The corp < 0.001) with a threshold of r2 that corresponded to 90th percentile [The linkage disequilibrium (LD) was calculated in each inferred population. The SNPs used presented the physical position (mapped) on the potato genome version 4.03 . To inclrcentile  of pairwp values were corrected with the Bonferroni method [p values of 0.05, 0.01 and 0.001.Phenotypic data corresponding to 15 qualitative variables  of 466 ti method  at p valThe 809 accessions of the CCC were genotyped with 8303 SNPs using the Infinium SolCAP, 1584 markers were removed from the dataset since 1174 were monomorphic (14.1%), 405 SNPs could not be called (4.9%), and five presented more than 20% of missing data (0.1%). Genotype calling inferred 6719 high confidence SNPs (81%), from which 751 SNPs presenting a MAF less than 0.05, were also excluded, giving a total of 5968 useful markers (72%) . Of thesThe population structure analysis of the CCC using the software Structure discriminated two main populations (K = 2) , S1A FigST = 0.203, p = 0.000), and the percentage of genetic variation was higher within populations (81%) than among populations (19%)  and a low gene flow (Nm = 0.98) , where the genetic diversity was higher in Andigena  than Phureja  (The genetic differentiation between Phureja and Andigena populations was high (Fns (19%) . High va = 0.98) . High ge= 0.167) . ObserveST = 0.225, p = 0.000), and were characterized by presenting an excess of heterozygotes  and low gene flow (Nm = 0.86)  observed among the subpopulations that ranged from 0.161 (Phureja_1 vs. Phureja_2) to 0.435 (Phureja_2 vs. Phureja_3)   , S1B Fig = 0.86) . The genureja_3) . The disureja_3) . The popureja_3) .ST = 0.06, p = 0.000), excess of heterozygosity  and high gene flow (Nm = 3.91)  of Andigena_2 to Andigena_5 subpopulations were low, ranging from 0.031 (Andigena_3 vs. Andigena_5) to 0.080 (Andigena_2 vs. Andigena_3), and high among these subpopulations with Andigena_1 that ranged from 0.122 (Andigena_1 vs. Andigena_5) to 0.216 (Andigena_1 vs. Andigena_3)  were polymorphic in Andigena population and the analyses conducted on these data subdivided the Andigena population in five groups (K = 5) (Andigena_1—Andigena_5) . The inf = 3.91) . The FSTigena_3) . The Andigena_3) .The MCA based on morphological traits among 624 Andigena accessions showed that the total morphological variation was distributed in 73 dimensions, from which the three first dimensions explained the 12.3% of the variation . The firThe cluster analysis discriminated six morphological groups within the Andigena population . Althougp = 0.311), and geographical distribution and genetic data . However, a low but significant correlation  was identified between all morphological variables analyzed and the genetic data (p > 0.05), three  were negatively correlated (p < 0.05) and the remaining nine were positively correlated (p < 0.05). The variables with higher correlation were those related with flower variables , general tuber shape (GTS: 9.4%) and primary  and secondary color of skin tuber  (p = 0.001)  . The glo= 0.001) . AlthougThe linkage disequilibrium between pairwise SNPs was estimated for Phureja and Andigena populations; the analysis showed that the amount of SNPs in LD and the extent of LD differed among these.r2 values for the 133 Phureja accessions were 0.463 for linked markers with 49.8% of the markers in significant LD. The r2 values ranged from 0.440 (Chr. 1) to 0.496 (Chr. 12) (p < 0.001) were used to assess the extension of LD decay. The threshold for r2 was 0.45 representing the 90th percentile of all pairwise correlations in the Phureja population. Using this threshold, the LD declined to 3.5 Mb for linked markers in the population Phureja. For each chromosome of the potato genome the LD decay was estimated and ranged from 2 Mb  to up to 9 Mb  (The LD in Phureja was estimated using data from the entire population (133 accessions) and separately for the subpopulation Phureja_1. The analysis was not conducted in the subpopulations Phureja_2 and 3, because they presented a low number of samples. In this analysis the 2555 markers used, mapped on the 12 chromosomes of the genome, with a mean distance between markers of 22.7 Mb, ranging from 11.5 Mb (Chr. 2) to 34.2 Mb (Chr. 1). The Pearson Chr. 12) . The pai. 3, 12) .r2 values obtained was 0.256 for linked markers with 50.1% combinations of markers in significant LD. The mean r2 value in the 12 chromosomes ranged from 0.234 (Chr. 4) to 0.283 (Chr. 8). To estimate the LD decay in the Andigena population, the r2 threshold was 0.25 representing the 90th percentile of the all pairwise Pearson correlations. The extent of LD was 0.8 Mb in linked markers and every chromosome ranged from 0.3 Mb in chromosome 4 to 8 Mb in chromosome 8  to 31.6 Mb (Chr. 1). The LD was not estimated for each subpopulation independently, because these groups did not differ genetically. The subpopulation Andigena_1 was excluded of the analyses because it presented a high genetic differentiation from the others. In addition, the LD in this subpopulation was not independently assessed because it was represented by a low number of samples. The average Pearson mosome 8 .10  ranging between 4.6 for STFC (solcap_snp_c1_12945) and 9.36 for PFC and PFIC (solcap_snp_c2_43970), were significantly associated with 9 of the 15 evaluated variables  were associated with PFC and PFIC and one (solcap_snp_c2_45235) with STFC , a high gene flow (Nm = 1.61) and only 9.64% of the variation among populations in diploid accessions of CCC-Universidad Nacional de Colombia. These two studies differed in the molecular markers (number and type) and samples (number and origin) evaluated. Samples analyzed in the two works were not exactly the same. Although the CCC-Phureja from the Universidad Nacional de Colombia conserves part of the accessions of the CCC-CORPOICA, the ID numbers did not match. In addition, some accessions of the CCC-Universidad Nacional were recently collected. Juyó et al. [The two inferred populations of CCC present high genetic diversity and were genetically differentiated with low gene flow among them, probably due to the difference in ploidy level . The Solulations . Human sulations , who ideó et al.  used SSRó et al. –79. Howeó et al. , 81. In ó et al. –84.S. tuberosum group tuberosum of CCC were probably originated from landraces and breeding material from United States and Europe [Andigena population presents a genetic admixture supported by a high gene flow among populations . The lacd Europe . Tuberosd Europe , 90.Phytophthora infestans [High genetic diversity was found in both populations according with other studies , 68, 89.nfestans , sugar cnfestans .The accessions of Andigena population showed wide phenotypic diversity based on fifteen morphological traits, in which shape, skin color and color intensity of tuber and flower attributes were the most informative variables to discriminate the six groups of Andigena. Previous works reported that the same variables were useful to differentiate potato accessions –99. VariIn this work, geographic distance was not correlated between genetic and morphological distances. Similar results were obtained in previous studies using potato collections for morphological data , 103 andr2 and SNP pairs with significant LD in Phureja and Andigena were identified. These results contrasted with the study of Juyó et al. [The linkage between molecular markers and phenotypic polymorphisms is required for the association mapping of genes or QTLs underlying traits of interest . The extó et al.  in diploó et al. .r2 threshold of 0.45 (Phureja) and of 0.25 (Andigena) were used. Those values corresponded to the 90th percentile of the distribution of all pairwise Pearson correlation in each population. Vos et al. [r2 = 0.1) did not allow the comparison among studies [r2 values and extent of LD through the genome differ among studies because of differences in population size, number and type of markers [To estimate the LD decay in Phureja and Andigena populations, a s et al.  found th studies , 35, 95. studies . The r2  markers  and the  markers . The pol markers . In cont markers . Based o markers –35, 118. markers , 10 cM [ markers . It is n markers , 120.p values less than 0.001. Of these four markers, three were associated with flower primary color and one with secondary color distribution in tuber skin. The marker solcap_snp_c2_45235  was associated to secondary color and was mapped to the gene Sotub10g021050.1.1 (PGSC0003DMG400008137) which has a glucosyltransferase function. Some glucosyltransferase enzymes are implicated in the production of anthocyanin, pigment compound of skin and flesh tubers [The LD decay value is useful to design future GWAS studies; it makes possible to estimate the minimum number of SNPs required to have a successful GWAS . Since Ph tubers . In addih tubers .The SNP dataset produced in this study and the germplasm analyzed would allow the implementation of association-mapping studies and to detect markers or genes associated to traits of interest useful for potato breeding such as resistance to pathogens and insect pests, tolerance of abiotic stresses and tuber quality. The function of the associated markers should be validated through genetic transformation. Additionally, conventional potato plant breeding programs could be supported using the genetic information through marker-assisted selection (MAS) and genomic selection (GS), and thus to accelerate the selection of potato materials and reduce the cost and time to develop new potato varieties.Solanum tuberosum using morphological and SNP molecular markers. The study identified high levels of genetic diversity and genetic differentiation in diploid and tetraploid potatoes. CCC constitutes a potential source of variable traits useful for a genetic breeding program. Additionally, the linkage disequilibrium study of the CCC indicated that the genomes of Phureja and Andigena presented an elevated number of SNP pairs in significant LD and a slow LD decay, suggesting that with a modest number of molecular markers, a marker-phenotype association could be detected. The information obtained in this work allowed to conclude that the CCC is a germplasm with a broad genetic base and is useful to conduct association mapping studies suitable for the identification of QTLs/genes associated to quality traits and biotic and abiotic stress tolerance traits.The present study is the first report of phenotypic and genotypic evaluations of the Colombian Central Collection of S1 Fig(A) Overall Colombian Central Collection. (B) Phureja population. (C) Andigena Population.(TIF)Click here for additional data file.S1 Table(DOC)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(DOC)Click here for additional data file.S5 Table(DOC)Click here for additional data file.


Although natural selection is expected to reduce variability, polymorphism is common in nature even under strong selective regimes. Discrete polymorphisms in mating strategies are widespread and offer a good opportunity to understand the genetic processes that allow the maintenance of polymorphism in relatively simple systems. Here we explored the genetic mechanism underlying the expression of discrete mating strategies in the rock-paper-scissors (RPS) game. Heterozygotes carry the genetic information for two different strategies, yet little attention has been devoted to the mechanisms underpinning heterozygote phenotype and its consequences for allele frequency dynamics. We explored the maintenance of polymorphism under 1) genetic dominance or 2) plasticity, as mechanisms driving the expression of alternative strategies in males. We developed an alternative mating strategy model and analysed allele frequency dynamics using time series analyses. Our results show that both genetic mechanisms can maintain polymorphism depending on population demographic characteristics but that plasticity can enhance the likelihood that polymorphism is maintained relative to dominance. Time series analysis on simulation outcomes show that the RPS game is mostly driven by a single strategy, but the importance of this strategy on long term dynamics is stronger when gene expression shows dominance rather than plasticity. Game theory suggests that multiple players competing for a resource  can be maintained by negative FDS in a system as long as no single player or strategy is an evolutionarily stable strategy8. In this context, allele frequencies can be stable or show frequency oscillations over time9. However, Trotter and Spencer10 showed that oscillations will be hardly detectable in natural conditions for more than three alleles. Discrete polymorphism such as trimorphism in mating strategies, which have been reported over the last two decades reviewed in11 are particularly interesting in this respect since they offer the opportunity to study the maintenance of polymorphism in a very simple and detectable context (i.e. control of mates and three discrete strategies). Indeed, in the discrete trimorphism context, the strategy pay-off matrix can form a rock-paper-scissors game (RPS game) between the three strategies with minor differences between empirical systems reviewed in11. In a RPS-type game, each strategy beats another one but is beaten by a third one. Theoretically, such a game can lead to monomorphic or polymorphic populations (stable equilibrium of strategy frequencies or oscillations over time)12. Empirical evidence for alternative mating strategies have been found in a variety of organisms including birds, lizards, damselflies, isopods, bacteria and loose-leaf flowers18, but the genetics underlying such polymorphism have received limited attention.Evolutionary mechanisms such as natural selection and genetic drift are expected to reduce genetic variation within populations. Yet polymorphism is surprisingly widespread in animal and plant populations. To explain this paradox, a number of mechanisms have been proposed such as heterosis23. However, only a few studies have attempted to explore the genetic mechanisms underlying the expression of alternative mating strategy games, usually assuming that a dominance relationship exists between alleles26. The assumption of genetic dominance is supported by several empirical examples advocating for dominance as a mechanism underpinning RPS games28 and is very common in genetic studies of morphological traits. On the other hand, empirical evidence for plasticity as a mechanism underpinning RPS games is relatively scarce either because this mechanism is rare or because it is more difficult to detect and therefore less often studied. However, plasticity is certainly possible and would translate into specific morph expression in heterozygotes or switches in individual reproductive strategies31 which could have important implications for fitness payoffs of each allele. Plasticity could be advantageous if the alleles coding for the different strategies are either neutral or synergetic in their respective expression24. However, this genetic information could be antagonistic and reduce a heterozygote’s performance compared to homozygotes. Such a cost would have an important impact the stability of the RPS game7 especially since a low cost to heterozygotes could induce a strong allele frequency disequilibrium which could explain why plasticity in alternative mating strategies has rarely been documented in nature to date. Regardless, very little theoretical attention has been devoted to the viability of phenotypic plasticity as a mechanism underpinning the expression of reproductive strategies in heterozygotes; especially in a context where the number of alleles is above two as in the RPS game context26.Heterozygotes carry genetic information for two strategies. An extensive literature exists on the genetic models for polymorphism34 and game stability35 but is neglected by most studies of the maintenance of polymorphism36. In this regard, we performed population dynamic simulations of a virtual species playing a generic RPS game using an individual-based-model. The individual-based-model allows us to simulate the effects of individual genetic information , social environment and demographic stochasticity on the maintenance of alternative reproductive strategies. In this framework, we explore the maintenance of polymorphism under two hypotheses on the mechanisms leading to individual phenotype:31. Past diploid models explicitly ignored over-dominance and only considered co-dominance or dominance34.Genetic dominance: we assess genetic dominance of alleles coding for the mating strategyPlasticity: heterozygotes are plastic and able to apply the best strategy given the current social context of that individual. Note that this could mean that an individual expresses a poor strategy that is the best available given its genes and the current social context or in a different context may mean the individual can express the best strategy overall relative to its neighbours.The first goal of this study is to explore how different genetic mechanisms leading to the expression of alternative reproductive strategies and demographic stochasticity could influence the maintenance of trimorphism in RPS games under a range of initial conditions concerning species lifespan (short-lived to long-lived species) and allele frequencies . Indeed, demographic stochasticity occurs in most biological systems and has an important impact on population dynamicsThe second goal is to explore the impact of the genetic structure and life history traits under each genetic hypothesis, on the maintenance of polymorphism given different assumptions about the strategies: (1) genetic expression basis of alternative reproductive strategies (2) costs linked to being a heterozygote.11), we have chosen to implement the RPS game as a male alternative strategy game because it illustrates a simple game observed in natural populations of a few well studied species with a direct impact on individual reproductive performance and thus phenotype fitness16. The game assumes that M players are monogamous with a small home range, P are polygynous with medium home ranges and S are polygynous sneakers in P harems with large home ranges. Thus, M beats S and is beaten by P; P beats M and is beaten by S and finally, S beats P and is beaten by M ensuring the RPS game. Such a game is similar to the game extensively documented in Uta stansburiana and Paracerceis sculpta where M players resemble mate guarder males in U. stansburiana and the β female mimicking males in P. sculpta, P players would correspond to aggressive polygynous males in U. stansburiana and α mate guarder males in P. sculpta and S players to the female mimicking males in U. stansburiana and the γ criptic dwarf males in P. sculpta. We chose to implement the simplest possible genetic structure underlying our 3 phenotypes in the RPS game by using a single locus with three alleles corresponding to the genetic structure found in damselflies (Ischnura elegans) and the marine isopod (P. sculpta)  leading to six genotypes 28. Hence, male reproductive strategies are determined as M, P or S depending on the genetic rule underlying the social strategy which we modelled in two ways:p > s > m) assumes that all genotypes containing a p  allele lead to a P strategy, the M strategy exists when individuals have mm genotypes and all other genotypes  lead to a S strategy.Allelic dominance . The strategy expressed will depend in this case on the frequency of each strategy in the population. New adults will adopt the apparently most optimal strategy in the population given their alleles and carry that strategy for the rest of their life . Thus, in a population where P and S are rare, an individual of genotype To reach these goals, we built a stochastic individual-based model and used realistic assumptions that may generate cyclical structures in population dynamics (i.e. density dependence and RPS game). Even though the RPS game occurs in various ways  which allowed us to 1) detect cyclical structures, 2) distinguish between cycles coming from population dynamics and cycles coming from the RPS game, and 3) identify causal relationships between phenotypes to understand how the genetic mechanisms underlying the expression of mating strategies affects the maintenance of polymorphismSimulations with populations initially composed by individuals presenting only two of the three alleles leads to the fixation of the strongest strategy in the RPS game . However, the time necessary for allele extinction depends on the genetic mechanism underlying the strategies. Indeed, the monogamous allele disappears faster than the polygynous and sneaker alleles under the genetic dominance hypothesis. In contrast, this same allele disappears more slowly under the plasticity hypothesis (see Supplementary Results).p allele when P plays against S.Under the genetic dominance mechanism, a cost to heterozygote genotypes does not significantly change the probability or time before extinction of alleles. In contrast, under the plasticity hypothesis, the cost of being a heterozygote strongly influences the extinction speed of the Whilst all simulations lead to mono-strategic populations, the speed at which this occurs presents high variation among strategies and is closely linked to population carrying capacity and demographic traits . Indeed, regardless of the losing strategy the global pattern is the same for a given set of parameters for carrying capacity and fecundity. The time to monomorphism increases with carrying capacity and decreases with fecundity  , the interpretable emerging structures are situated between 4 and 32 time steps  between frequencies of pairs of strategies show that the P strategy has a negative effect on the M strategy and a positive effect on the S strategy. The frequency of the M strategy does not influence the S strategy frequency suggesting that the game is largely driven by the P strategy Fig. .Figure 238 between the number of individuals applying a strategy and total population size show that cyclical structures emerging from the alternative mating strategies are attenuated by demographic stochasticity . The attenuation is more important under the plasticity hypothesis suggesting that the global demography is less constrained by the alternative mating strategies demographic outcome when strategies are plastic.The gain functionsp allele is initially rare, the P strategy can invade and the probability of maintenance of the trimorphism converges to the same pattern as if all alleles would have been equally represented initially.When rare, strategies differ in their probability of extinction. Indeed, under the genetic dominance hypothesis, S and M are unable to persist when rare, heterozygosity costs, carrying capacity or lifespan. In contrast, when the p or m alleles are initially rare are similar to the pattern observed when the three alleles are equally represented. In this case, trimorphism maintenance probabilities are lower than in the case of equal frequency of all alleles (respectively reduced by 0.1 ± 0.01 and 0.3 ± 0.02) due to the enhancement of stochastic extinction of invading alleles.Under the plasticity hypothesis, both M and P strategies are able to reach high enough frequencies to allow for the maintenance of trimorphism while S cannot be maintained when initially rare. As under the genetic dominance mechanism, the pattern observed when 41. However, our results suggest that the underlying genetic control of the mating strategy phenotype strongly affects the probability that polymorphism is maintained. Previous genetic models, based on empirical work studying the properties of alternative mating strategies assumed that a dominance relationship existed in alleles coding for the three strategies42. However, even though trimorphism can be maintained under the allelic dominance hypothesis, the conditions for its maintenance are restrictive when compared to the plasticity hypothesis. Indeed, inclusion of demographic stochasticity under the genetic dominance hypothesis will likely lead to a loss of one of the three alleles underlying the alternative mating strategies phenotypes, especially when compared to the plasticity hypothesis. This would be especially important since evolution of a third strategy will most likely require some length of time where the two other strategies are stable8.As in previous studies, we find that discrete polymorphism can be maintained by negative FDS11, or in small populations of a metapopulation as suggested by Corl et al.12. However, the expression of a phenotype may affect individual survival. Polygynous males of the side blotched lizards and highly harassed females of I. elegans have reduced survival43. Thus we may expect that the difference in survival rate depending on the expressed strategy will change the observed pattern of phenotype frequencies in the field in different ways. First, the oscillation frequencies of the affected phenotype may increase with the reduction of survival. Second, the phase function between strategies may be affected, thus modulating the sequence of high frequencies of each phenotype from a highly structured sequence to chaotic sequences. These two last changes of the observed pattern linked to differences in survival rates of the expressed phenotype would be closely linked to the payoff matrix and to the interaction between demographic processes  and the game between strategies (payoff matrix). In these two cases, oscillations due to frequency dependent competition between strategies may be undetectable in the field and the use of wavelet analysis would allow disentangling the demographic components from the game component and their interaction in the maintenance of the alternative strategies. A third possible consequence of survivorship tied to strategy expression is that the oscillation in strategy frequencies may disappear and tend towards stable frequency equilibrium of the three strategies where the frequency of each strategy will depend on the payoff matrix design. Indeed, this result has also found in other theoretical studies10 where oscillation of the phenotype frequencies can disappear and tend to stasis depending on the payoff matrix design, especially with a genetic dominance mechanism. By contrast, our results show that phenotypic plasticity can help maintain strategy cyclicity over longer time scales relative to genetic dominance . Together, our results suggest that cyclicity among phenotypes of polymorphic species in natural populations might be maintained by 1) strategy plasticity in heterozygotes, 2) demographic stochasticity when genetic dominance occurs, or 3) some external factor such as predation that shifts strategy frequencies off their stable equilibrium.From our results, we should expect that the trimorphism will be maintained by dominance and negative frequency dependent selection only in large populations or in long-lived species with high dispersal rates, although these are precisely the cases where trimorphisms are apparently rare47. However, in contrast of the dominance hypothesis which benefits from experimental evidence in damselflies28, our plasticity hypothesis is only suggested by indirect evidence from one specific case. Indeed, in the U. stansburiana, there is evidence that ms color genotype, sp color genotypes and ss color genotypes exhibit plasticity as modulated by components of the endocrine system  seems to allow the maintenance of polymorphism for a wider range of species life strategies and environments; and accordingly we might expect the plasticity mechanism to be more wide-spread in trimorphic species and by extension to more complex systems with more than three alleles and more continuous and less detectable polymorphisms. In this respect, previous empirical as well as theoretical studies have shown that heterozygote advantage often underpins the maintenance of polymorphism of reproductive strategies in natural populationsp > m > s which is just one of the 6 possible combinations of dominance relationships that could exist with 3 alleles. However, additional simulations (not shown) with different combinations of dominance relationships (p > s > m and s > p > m) led to similar general results in terms of the conditions for the maintenance of polymorphism. Furthermore, these additional explorations tend to suggest that the maintenance of polymorphism relies more on the payoff matrix design than the dominance relationship within alleles. Additional simulations using different genetic mechanisms such as codominance, heterozygote advantage, or different forms of plasticity (e.g. pleiotropy) would help determine if the genetic structure or payoff matrix play a bigger role in determining the maintenance of polymorphism in general.Numerous ways of modelling the genetic mechanisms underlying the reproductive strategies are possible, we restricted this study to just 2 of those possible mechanisms. Indeed, the genetic dominance mechanism we implemented assumed that Further, our modeling approach assumed a simple case where plasticity was generated by the differential expression of two alleles at a single loci, rather than by the differential expression of alleles at different loci (as is the case in plastic homozygotes for instance), warranting further and more complex modeling on the topic.42. This would imply that the maintenance of the cyclical structures generated by the RPS game may be equally sensitive to frequency variation of the three strategies. Our time series analyses have shown that, in the general case, the genetic dynamic emerging from the RPS game is driven by a single strategy, the P strategy. This suggests that even though all the strategies have equivalent global fitness, the system will be more sensitive to perturbation of the P strategy and that trimorphism is closely linked to the frequency dynamic of the P strategy. Whether this result holds for empirical systems and if different systems have the same strategy as the driver of cyclical dynamics remains to be seen when the methods we outline here are applied to empirical data.Theory says that in the RPS game, all strategies must have equivalent global fitness over long time scales to constitute an ESSIn conclusion, the model we developed allowed us to test the possibility that two mechanisms of genic expression (genetic dominance or phenotypic plasticity) may maintain polymorphism. We found that, plasticity more easily maintained strategy polymorphism and was more likely to maintain frequency oscillations in a negative FDS system. Hence, both mechanisms are able to maintain polymorphism but, in the wild, phenotypic plasticity may be more widespread due to a less restrictive set of conditions leading to polymorphism maintenance. The coupled use of simulation and time series analysis enlightened the causal relationships which may drive simple negative FDS processes and by extension probably more complex genetic structures and associated polymorphisms. This approach also highlighted that in a specific case, discrepancies between empirical observations and theoretical models may not be only attributed to model simplification. Indeed, the lengths of field time series are too short in most of the cases to permit the disentangling between the social game cyclical structures and demographic ones. As a consequence, while the studies of most empirical systems do not provide sufficiently long time series to investigate the influence of each strategy on population frequency dynamics, the time series analysis techniques used here suggest that social game pay-off structure may not reflect the current importance of each social strategy when demographic stochasticity and density dependence are present.Population dynamic model description: The model is a basic stochastic demographic model of two sexes and two age classes  which can model the population dynamics of any species (fauna or flora) with multiple reproductive status classes and sexual reproduction. The demographic process is divided in four main phases .Juvenile recruitment: juveniles are randomly recruited into the adult population depending on population density. The non-recruited juveniles survive depending on the juvenile survival probability , we modelled the negative FDS by designing a 3 × 3 pay-off matrix i playing against k where f are the frequencies of strategies i and k and i strategy playing in a world of only k strategy, Table The home range size reflects the number of neighbours each male has and thus, the number of competitors for mates. To estimate at each time step the relative average fitness of each strategy playing against the beaten strategy (i.e. P mentclass2pt{minimc) to heterozygotes. We considered that a game between heterozygotes is equivalent to a game between pure strategists but that pure strategist had an advantage playing against heterozygotes which was implemented as an increased probability to win by a factor c. We also assumed that the initial heterozygote mean harem size was reduced by a factor c as was the probability of winning in the RPS game against a pure strategist.To determine the impact of a putative cost in heterozygotes expressing their phenotype on the maintenance of trimorphism we implemented a cost (pwin = 0.5) while a player expressing a different strategy from its opponent has an additional gain or loss to the chance of winning the contest depending on the relative strategy frequencies in the current population and determined using equation 1. For example, a P strategiest in a population where M is common will have an increased chance of winning. Then each female won from a neighbour is added to the winner’s harem and removed from the loser’s harem. So while males can usurp females from another male, no mixed paternity of a single female’s reproductive output exists since reproduction occurs after final harems are composed.During phase 2 of the demographic model, the mating process is implemented in three steps Fig. : First, We performed runs with only two alleles in the population to determine how long it took for each strategy to outcompete the other.We aim to determine if the genetic mechanism allows maintenance of reproductive strategy trimorphism. Consequently, we assumed that all alleles are initially equally represented in the population.p’ and ‘m’ alleles, we removed 20 ‘pm’ individuals and replaced them by 20 ‘ms’.We simulated the “appearance” of a third allele (and therefore a third strategy) in a two allele population. Appearance of the new allele is implemented by exchanging 20 heterozygote individuals  into 20 heterozygotes who carry the new allele and the allele coding the strategy that is currently losing. For example, in a population with only ‘Under each genetic mechanism, we examine a range of possible life history trait values provided in Table Simulations are run 300 time steps which are usually long enough to reach stability of the population dynamics and genetic structure. All runs are repeated 200 times. To perform time series analysis, simulations leading to a dynamic equilibrium of the 3 strategies are run again on 2050 time steps to provide sufficiently long time series to ensure time series analysis robustness.11. To identify and characterize the temporal structure emerging from the RPS game, we perform a wavelet analysis using “Morlet” wavelet49. Wavelet analysis has multiple applications in ecology such as studying, interactions between climate change and phenology50, switches in biological cycles due to anthropogenic pressures51, spatial behaviour and distribution of species54, and various other applications reviewed in48. Wavelet analysis detects when information sensu Shannon55 is present and how this information “travels” across temporal scales57. The technical benefits of such analysis in ecology more generally are reviewed by48 but in our study, wavelet analysis allows us to identify if a cyclical structure exists in the time series and when it occurs. The method allows us to determine the periodicity of a cyclical structure in a continuous space even if the process is non-stationary (i.e. the periodicity changes). Thus, wavelet analysis allows for the characterization of slowing or accelerating cycles or punctual structures48 in contrast to discrete methods such as Fourier analysis that focus on stationary cyclical structures. We then perform multi-resolution analysis to identify the time scale of patterns emerging from the RPS game38. Multi-resolution analysis assumes that the global signal is the result of the addition of multiple signals at different temporal scales and thus separates the global signal into its different components39. Multi-resolution analysis allows us to analyse interactions between different time series signals and we used this analysis to identify interactions between time series emerging from the RPS game due to different strategies. Finally we use cross-correlational analysis between strategies to identify the causal nature of changes in allelic frequency59. In this statistical context , cross-correlational analysis between the time series frequencies of two different phenotypes is a measure of similarity of two series as a function of different time lags of one cycle relative to another cycle. The cross-correlation is similar in nature to the convolution of two functions . In other words, this last analysis answers the following question: can some strategies drive the cycles of others or are cycles due to some other effect?No time series analyses are performed for simulations exploring costs of plasticity for the heterozygote phenotypes due to the impossibility of maintaining trimorphism during enough time steps. RPS games are likely to show cyclical dynamics due to the interactions between strategies reviewed in® environment using the Wavelab toolbox60.Modelling and time series analyses are performed under the MATLABSupplementary information


Rht-B1b and Rht-D1b are associated with Type I susceptibility to Fusarium head blight (FHB) in wheat; but the underlying mechanism has not been well delineated. Anther extrusion (AE) has also been related to Type I resistance for initial FHB infection, where high AE renders FHB resistance. In this study, two doubled haploid populations were used to investigate the impact of the two dwarfing genes on FHB resistance and AE, and to elucidate the role of AE in Rht-mediated FHB susceptibility. Both populations were derived by crossing the FHB susceptible cultivar ‘Ocoroni F86’ (Rht-B1a/Rht-D1b) with an FHB resistant variety (Rht-B1b/Rht-D1a), which was ‘TRAP#1/BOW//Taigu derivative’ in one population (the TO population) and ‘Ivan/Soru#2’ in the other (the IO population). Field experiments were carried out from 2010 to 2012 in El Batán, Mexico, where spray inoculation was adopted and FHB index, plant height (PH), and AE were evaluated, with the latter two traits showing always significantly negative correlations with FHB severity. The populations were genotyped with the DArTseq GBS platform, the two dwarfing genes and a few SSRs for QTL analysis, and the results indicated that Rht-B1b and Rht-D1b collectively accounted for 0–41% of FHB susceptibility and 13–23% of reduced AE. It was also observed that three out of the four AE QTL in the TO population and four out of the five AE QTL in the IO population were associated with FHB resistance. Collectively, our results demonstrated the effects of Rht-B1b and Rht-D1b on Type I FHB susceptibility and reducing AE, and proposed that their impacts on Type I FHB susceptibility may partly be explained by their effects on reducing AE. The implication of the relationship between the two dwarfing genes and AE for hybrid wheat breeding was also discussed.It has been well documented that dwarfing genes  Fusarium species, the causal agents of FHB [Fusarium head blight (FHB) is a notorious wheat disease prevailing in warm and humid environments, exerting global impact on food and feed safety due to the presence of mycotoxins produced by s of FHB , 2. Deoxs of FHB .Host resistance to FHB is of quantitative inheritance and influenced significantly by environment , making Rht) genes, and tight linkage [Rht-B1, Rht-D1 and Rht8 [Rht-B1b and Rht-D1b  were derived from the Japanese cultivar ‘Norin 10’ and contributed greatly to the Green Revolution [Rht-D1b and Type I FHB susceptibility in European varieties [Rht-D1b increased FHB severity by 52% in a ‘Mercia’ background and 38% in a ‘Maris Huntsman’ background [Rht-D1b. In an association mapping study on European winter wheat materials, Miedaner et al. [Rht-D1b with increased FHB susceptibility, but to a lesser degree than reported previously; the authors concluded that the negative effects of Rht-D1b in bi-parental populations may have been overestimated. In the case of Rht-B1b, Srinivasachary et al. [Rht-D1b under severe infection. Miedaner and Voss [Rht-B1b under different genetic backgrounds. In the three mapping populations tested by Buerstmayr et al. [Rht-B1b was associated with increased FHB susceptibility, with phenotypic effects ranging from 3–18%. The negative effects of the two dwarfing genes on field FHB resistance have also been reported in Chinese and US wheat materials [Rht-B1b exhibited significant effects on Type II resistance, whereas Rht-D1b showed little or no effects on this type of FHB resistance [Rht-B1b and Rht-D1b near-isogenic lines were physically raised to the same heights as their tall counterparts.The negative association between PH and FHB susceptibility in wheat has long been observed, and it happened also in barley and oat –14. Thre linkage . In the and Rht8 . Dwarfinvolution . Strong arieties –20. For ckground  demonstrr et al.  also repy et al.  found thr et al. , Rht-B1baterials , 26. In sistance , 26–28. sistance , 19, 24;The importance of anthers in FHB infection has long been observed. Pugh et al.  observedRht-B1 explained 10% of the phenotypic variation of AE [Rht-B1b or Rht-D1b showed reduced AE and double dwarfs (Rht-B1b/Rht-D1b) had a high degree of anther retention (+99%) compared to tall lines with Rht-B1a/Rht-D1a [Rht-B1b and Rht-D1b on field FHB resistance and AE in two mapping populations.Considering the associations of Type I FHB resistance with both PH and AE, it is tempting to investigate the association between the latter two traits, and clues do exist in literature. In the Shanghai-3/Catbird x Naxos population, on of AE , and in /Rht-D1a . It was /Rht-D1a . The objRht-B1b/Rht-D1a whereas the susceptible parent had the Rht-B1a/Rht-D1b genotype, resulting in both dwarfing genes segregating in the two populations.Two doubled haploid populations were used in this study. The first one was developed from a cross between ‘TRAP#1/BOW//Taigu derivative’ and ‘Ocoroni F86’ with 135 progenies (referred to as the TO population hereafter), while the second was from ‘Ivan/Soru#2’ and ‘Ocoroni F86’ with 92 progenies (the IO population). Both the two female parents were FHB resistant lines bred at CIMMYT, while ‘Ocoroni F86’ (pedigree JUPATECO-73/(SIB)EMU//(SIB)GRAJO) is a CIMMYT breeding line moderately susceptible to FHB . Both ofF. graminearum isolates were collected, characterized, and used for field inoculation, following the protocols described by He et al. [The field FHB experiments were conducted at the El Batán experimental station  of CIMMYT, Mexico, during the summer season (May to September) when rainfall is concentrated. The two populations were evaluated from 2010 to 2012, sown in 1 m double rows with randomized complete block design with three replications. Each year, a mixture of 5 aggressive e et al. . Spray iFHB index = Severity x Incidence [Severity stands for the averaged percentage of diseased spikelets, and Incidence for the percentage of symptomatic spikes. Plots were sickle harvested and threshed with a belt thresher set at low wind speed to retain scabby kernels. Fusarium damaged kernels (FDK) was estimated only in 2012 for the two populations through visually evaluating a random sample in a petri dish, where both scabby and shrivelled kernels were regarded as FDK. DON content was quantified in 2010 and 2012 for the TO population and in 2011 and 2012 for the IO population, based on 2 g flour sampled from 20 g ground grain of each accession, using the Ridascreen Fast DON ELISA kit  following the manufacturer’s instructions. AE and PH were scored in 2011 and 2012 for the IO population and in 2012 for the TO population. In 2015, the TO population was planted in 40x15 cm hill plots with two replications for an additional evaluation of AE and PH. AE was rated with a linear scale from 0 (no extrusion) to 9 (full extrusion) according to Skinnes et al. [FHB symptoms were evaluated at 25 days post inoculation (dpi) on the 10 spikes that had been tagged at anthesis. Numbers of infected spikes and symptomatic spikelets of each spike were counted for calculating FHB index with the formula: ncidence , where Ss et al. , and PH y for the number of years, and r for the number of replications [The phenotypic data was analysed by the SAS program ver. 9.2. Analysis of variance (ANOVA) was carried out with the PROC GLM module, and Pearson correlation coefficients were calculated using the PROC CORR function. The results of ANOVA were used for calculating the heritability estimates, using the formula ications .Rht-B1 and Rht-D1 were also genotyped, using the KASPar technology (KBioscience) based SNP markers developed at CIMMYT [The two populations were genotyped with the DArTseq genotyping-by-sequencing (GBS) platform at the Genetic Analysis Service for Agriculture (SAGA) in Guadalajara, Mexico. This genotyping method is a combination of complexity reduction methods developed for array-based DArT and sequencing of resulting representations on next-generation sequencing platforms, for detailed information please check Li et al. . Additiot CIMMYT . A few St CIMMYT  were alsLinkage groups (LGs) were constructed using the JoinMap v.4 software , where gr values were low , and the corresponding correlations were also significant in the IO population but with lower r values .AE and PH showed wide segregation in both populations . High heRht-B1, Rht-D1 and four SSRs were used for linkage mapping and 35 LGs were obtained. Total length of the LGs was 4,430cM with a very similar density as that of the TO population. In this case, only chromosome 6D was not represented and six LGs were not assigned to chromosomes.In the TO population, 1,858 GBSs together with seven SSRs and the two dwarfing genes were used for LG construction. Thirty three LGs were generated, covering 4,053cM with an average density of 2.2 cM/marker. All but 1D chromosome were represented in this map and three LGs were not assigned to a chromosome due to a lack of anchored markers. Regarding the IO population, 1,986 GBSs, Rht-B1 on 4BS, Rht-D1 on 4DS and a QTL on 5AL  and 7B in the TO population and on 5BS in the IO population ; despite the utilization of spray inoculation in this study, huge quantity of Fusarium inoculum was present on soil surface due to the adoption of wheat/maize rotation and conservation agricultural practices, supporting the escape mechanism. With the accumulation of molecular evidences in the last decade, more researchers took pleiotropy as the main mechanism for this association. Being DELLA protein producers, Rht-B1b and Rht-D1b have shown association with reduced resistance to biotrophic diseases including Type I FHB resistance  but increased resistance to necrotrophic diseases like Type II FHB resistance [Rht alleles, the correlation between PH and FHB disappeared or was significantly reduced [Rht-D1 locus. Similarly in our previous research, a QTL for FHB in close linkage with Rht-D1 appeared when PH was used as covariate [The association between the two dwarfing genes and FHB susceptibility has been reported in many studies, and three possible mechanisms including disease escape, pleiotropy and tight linkage have been proposed; but a conclusion has not been drawn as to which mechanism was actually taking place. Intuitionally, this could be ascribed to PH per se or escape since tall plants were farther from soil surface where the inoculum was present  and ventilation was reduced that lead to high humidity favourable to FHB development , 49. Thisistance . Another reduced , 21, 50, reduced  found thovariate . So it aThe importance of AE in FHB resistance has long been recognized , 32, butRht-1 gene products [Rht-B1b and Rht-D1b in wheat have similar function in repressing anther elongation through over expression of DELLA proteins, resulting in the phenotype of anther retention or low AE. This finding partly explained the pleiotropic effects of Rht-B1b and Rht-D1b on Type I FHB susceptibility, i.e. the two dwarfing genes lead to low AE, which in turn caused increased Type I FHB susceptibility. The results have also implications for hybrid wheat breeding, in which the selection of male parent, the pollen provider, is very important. A good male parent is expected to have high AE and high pollen production, and these two traits were reported to be significantly positively associated with r = 0.82 by Joppa et al. [Rht alleles Rht-B1a and Rht-D1a will improve both traits. Still more, the tall stature of such lines is favourable for efficient pollination, since it was suggested that the male parent be taller than the female parent in hybrid seed production [The two dwarfing genes showed consistent effects on reducing AE in both populations across environments, collectively contributing about 20% of AE variation. The association may have its physiological basis. In Arabidopsis, the elongation of anther filament is stimulated by GA and repressed by DELLA proteins which are orthologous to wheat products . Thus ita et al.  and was a et al.  and Atasa et al. . Thus thoduction .S1 Table(TXT)Click here for additional data file.S2 Table(TXT)Click here for additional data file.