Attention has been focused on the field of genetics and genomics in Iran in recent years and some efforts have been enforced and implemented. However, they are totally not adequate, considering the advances in medical genetics and genomics in the past two decades around the world. Overall, considering the lack of medical genetics residency programs in the Iranian health education system, big demand due to high consanguinity and intraethnic marriages, there is a lag in genetic services and necessity to an immediate response to fill this big gap in Iran. As clarified in the National constitution fundamental law and re‐emphasized in the 6th National Development Plan, the Iranian government authority is in charge of providing the standard level of health including genetic services to all Iranian individuals who are in need. Iran is located in Western Asia with 1,648,195 km2 land, as the second largest country in the Middle East and the 17th in the world. Iran is bordered to the north by the Caspian Sea, to the south by the Persian Gulf and the Gulf of Oman, to the northwest by Turkey and Armenia and the Republic of Azerbaijan, to the west by Iraq, to the northeast by Turkmenistan, and to the east by Afghanistan and Pakistan. Tehran is the country's capital, its largest and the leading economic and cultural city.Iran , is the 18th most populous country  in the world (https://en.wikipedia.org/wiki/Greater_Iran)  Figure . This exIn the fourth century BCE, it fell to Alexander the Great leading to division into some Hellenistic states. An Iranian disobedience developed to the Parthian Empire followed (in the third century CE) by the Sasanian Empire as a leading world power till the seventh century CE when Arab Muslims conquered it and displaced the Zoroastrianism and Manichaeism with Islam . The Canon of Medicine was a five‐volume medical encyclopedia used as the reference medical textbook in Europe up to the 18th century . Also 800 years ago, “the Great Iranian Poet” Ferdowsi of 10th century explains an equal contribution of man and woman in the transmission of characters and fetus formation; it is mentioned in Shahnameh—the world's longest epic poem created by a single poet, and the national epic of Greater Iran  and Keykavus (the emperor of Iran)”  till renaissance happened. In the recent 2–3 centuries tremendous efforts have been made in the field of reproduction biology including the embryo formation via ovum and spermatozoa union (fertilization).Interestingly, prior and consistent with what has been currently proved and accepted as a fact, Persian historically believed in the equal contribution of women and men in formation of a child and its hereditary characteristics since the prophet Zoroaster  who expressed equal right for both sexes to choose how to live life. To store the egg (gametes) from reproductive organs (gonads) for future conception was also mentioned in  Browne, . Regardihttps://en.wikipedia.org/wiki/Ethnicities_in_Iran).From population demography viewpoint, Iran is a big regional multicultural country consisting of numerous ethnic and linguistic groups, including Persians , Azeris (16%), Kurds (10%), Lurs (6%), Balochs (2%), Arabs (2%), Turkmens (1%), Talyshs (1%), Qashqais (1%) , respectively, with 75.1% living in urban areas. The biggest metropolitan areas are the cities of Tehran (13.26 million), Mashad (3.37 million), Isfahan (2.24 million), Shiraz (1.87 million), Karaj (1.85 million), and Tabriz (1.77 million).Consanguineous marriages are allowed in Iran, and are common in most ethnic groups, communities, and religions of Iranians including Azeris, Kurds, Lurs, Balochs, Arabs, Turkmens, Gilaks, Talyshs, Qasqais, and Mazanis. Consanguineous marriage is not only common but also has a positive trend in Iranian community. In a survey in Persian population of Iran, the consanguinity status (rate) for 1,789 marriages showed 8.8% in the generation with marriages before 1949 versus 19% after 1979  and because of prenatal screenings and public education, there is a significant increase in the voluntary termination of pregnancies upon the detection of fetal abnormalities. The frequency of congenital disorders is notably high  in Iran, including congenital malformations , single gene disorders , chromosomal disorders , and congenital infections  . The greatest prevalence and proportion rates belonged to musculoskeletal disorders, skin, and urogenital anomalies, and may be different in different ethnicities due to higher consanguineous marriages, different genetic makeup and SES  in Iran, the mean maternal and paternal ages are 28 and 33 years, respectively; and the total fertility rate is 2.01 children born/woman. The current birth and growth rates are, respectively, 10.6 births per 1,000 inhabitants and 1.24. Changes in socioeconomic status (SES) may contribute to the increasing parental age and low fertility rates. Higher education levels of women and their more exposure to the workforce vacancies from one way, and gender inequality, the consequences of sanctions and economic hardship from another way, play an important role in above‐mentioned facts and rates. All these resulted in a significant increase in the age of marriage and maternal age above 35 years old, which may have a direct increasing effect on congenital and genetic defect in subsequent generations  is an acceptable practice in Iran. There are two main legal grounds for PND in Iran; the main one is the endangerment of a mother's life, and the other one is parents’ severe hardship. The “hard to treat diseases” include chromosomal disorders, major hemoglobinopathies, inborn errors of metabolism, Duchene muscular dystrophy, and spinal muscular dystrophy which are all diagnosed early in embryonic period that medical abortion is possible and advisable in Iran The Iranian law, based on religious authorities (fatwa), allows for termination of pregnancy before the 19th week of embryo (the 120th day of the pregnancy by LMP) on the affected fetus with a severe disease in ultrasonography imaging and/or by a detected disease‐causing mutation/chromosomal aberration including fetuses with Down syndrome. Most of the population of Iran are religious/traditional so the interruptions of pregnancy were relatively rare. However, Despite this, extensive changes in the healthcare system including ethical changes are still necessary to overcome the ethical obstacles including knowledge gap and informed consent, privacy and confidentiality and availability of healthcare services. The approaches to genetic testing are limited but diverse in Iranian, mainly because of the differences in the traditions of different ethnicities. The multi‐ethnic Iranian communities (composed of more than 10 ethnic groups) are homogeneous, and include about 50% of Iranian population.2.3https://shenasname.ir/1391-09-30-20-01-30/tosee/plan6/3579.html), the Ministry of Health and Medical education (MHME) is in charge to recruit cooperative and private sectors to provide accredited genetic laboratories to the couples who are in need. Also MHME and State Welfare Organization of Iran  need to provide the access to genetic counseling to them. There is a possibility to perform genetic tests outside the country if necessary.The purpose of the law is to provide the screening tests, genetic testing, and genetic counseling for early detection of some targeted genetic diseases to all, including women in reproductive ages, and pregnant women. It is defined in section 75 of the 6th National Development Plan (2016) (2.4http://irimc.org/). However, MHME defined the curriculum and professional criteria for Ph.D. in medical genetics in five universities, with the annual acceptance of 15 holders of a master degree . The Ph.D. in medical genetics program includes 24‐month syllabus of cytogenetics, molecular, biochemical, and medical/clinical genetics followed by a comprehensive exam. After passing the comprehensive exam, doing a dissertation and oral (defense) examination is necessary prior to taking the medical genetic national board examination. The board‐certified Ph.D. medical geneticists are recognized as laboratory specialties in the health system by MHME and IRIMC. There is no separate training program for cytogenetics, molecular, and biochemical genetics specialties. A Ph.D. medical geneticist can serve as director of a genetics laboratory, and sign out the results of tests in the fields of cytogenetics, molecular, and biochemical genetics.As mentioned above, despite all other residency programs in different disciplines, medical genetics has not been yet a medical specialty recognized by MHME and the Iranian Medical Council (IRIMC) , and 35delG in conexin26 (deafness). Meanwhile, the tests are mostly affordable for people in need in above‐mentioned cases. The costs of IVF and the genetic services which are necessary because of infertility are also covered by the national health insurance. Otherwise, many genetic tests are not covered by health insurances and therefore are hardly affordable for most of the families in need.Genetic tests for screened cases or the ones whom recommended by a physician because of suspicions of any chromosomal aberration, thalassemia, and/or PKU are covered by insurances. Also the health insurances mostly cover the costs of molecular genetic tests as long as their indications are well‐defined (because of being well‐known disease‐causing mutations) and they are carried out in Iran. Two examples for indicated well‐defined mutations could be p.508del mutation in 2.6By now, there are 49 clinical genetic (diagnostic) laboratories in different provinces of Iran; including 13 in Tehran (Tehran), 5 in Fars (Shiraz), 4 in Isfahan (Isfahan), 2 in Azarbayejan (Tabriz), 4 in Khorasan (Mashad), 4 in Khoozestan (Ahvaz), 1 in Balochestan (Zahedan), 3 in Kerman (Kerman), 1 in Kermanshah (Kermanshah), 3 in Gilan (Rasht), 4 in Mazandaran (3 in Sari & 1 in Babol), 2 in Hormozgan (Bandarabbas), 1 in Hamedan (Hamedan), 1 in Kurdestan (Sanandaj), and 1 in Alborz (Karaj). About half of them are in charge of the national screening program for assigned genetic disorders .Almost all genetic laboratories in Iran have both the cytogenetic and molecular genetics divisions; the set‐up of each genetic laboratory is individual and different from others. The directors of both cytogenetics and molecular genetics divisions are Ph.D. in medical genetics. S/he could be director of both simultaneously. The cytogenetics laboratories provide two types of services: clinical diagnosis and PND. However, the cytogenetics laboratories are independent and found outside of the genetic departments in hospitals, as there is no such clinical department/unit due to the lack of medical genetics program as a clinical discipline.All the genetics laboratories are regulated by the MHME. There are just three active laboratories offering Chromosomal microarray analysis (CMA) for clinical and PND in Tehran. Perhaps there are three more laboratories which offer CMA in three big cities  which are mainly for PGD and PND. Cytogenetic tests of oncology/hematology are also performed in the genetics laboratories or in the oncology/hematology departments . Generally, the genetic tests for diseases which are specific to a hospital and/or department  are set up in a very limited number of genetic laboratories within the hospitals.The number of genetic laboratories which are licensed and regulated by the MHME are growing rapidly in the recent years. However, there are (for maximum) just 4–5 big and mother private genetic laboratories in capital Tehran providing cytogenetics and molecular genetic testing.The performance of next‐generation sequencing (NGS) was literally announced in 2016 in Iran. However, the samples for different diagnostic panels (WES and GWAS) are still shipped outside the country, rather than being performed as a clinical service in any of the Iranian accredited laboratories. In turn, it is due to lack of the NGS platforms hardware maintenance and support (by the main company providers) for the analysis of genetic variation secondary to Iranian Transactions and Sanctions Regulations (ITSR).33.1Iran with its very diverse population in terms of ethnicity, is among the most underrepresented populations in currently available human genomic variation databases; this is important because many genomic variations are ethnicity‐specific.http://www.genomicsengland.co.uk), the Iranian MHME with its partner—Genetics Research Center (GRC) at the University of Social Welfare & Rehabilitation Sciences, Tehran, Iran and Dalla Lana School of Public Health at University of Toronto, Toronto, Ontario, Canada—have recently (2017) decided to launch the Iranome database (available at www.iranome.com). It has been launched by performing whole‐exome sequencing on 800 individuals from eight major ethnic groups in Iran. The groups included 100 healthy individuals from each of the following ethnic groups: Arabs, Azeris, Balochs, Kurds, Lurs, Persians, Persian Gulf Islanders, and Turkmen. They represent over 80 million Iranians, and perhaps over half a billion populations in Middle East with a rapid population growth expectations for the future .No work was reported on genetics in Iran until 1936 when a genetic course was added to the curriculum of biology in the universities. The Iranian Genetics Society was founded in 1966. The first‐genetic counseling clinic opened, and the first department of Human Genetics and Anthropology was founded in 1972 at the School of Public Health, University of Tehran by DD Farhud. In 1986, he reported some genetic information on the Persian population including higher rates of chromosomal, external genital, and thorax and abdominal anomalies, and other syndromes; similar rates of cleft lip and palate, joint dislocation, and finger anomalies in Iranian infants compared to other populations were found . The above‐mentioned genetic services and tests in the medical genetics laboratories of the university hospitals are offered to the public and covered by the medical insurances. In all these university hospital medical genetic laboratories, there is at least one PhD (or rarely MD/PhD) in medical genetics graduated from a foreign university . Otherwise, they should have graduated from a PhD program in Medical Genetics from a local university (within Iran). There are just 2–3 MHME‐accredited programs of PhD in Medical Genetics. The genetic counseling is mainly done by the physicians who participated in the short courses or workshops certified by MHME.3.3https://financialtribune.com/articles/people/50834/tehran-s-first-genetic-center-launched). The first one was established by the Shiraz University of Medical Sciences. The genetic counseling services include maternal and pediatric medicine and laboratories of molecular genetics, cytogenetic, and prebirth tests.There are two recently established comprehensive centers for genetic counseling services in Iran; the second was launched with an academic affiliation in Tehran in 2016 (http://www.royaninstitute.org/)—a leader of stem cell research and also one of the most advanced clinics for infertility treatment in Iran—was established in 1991 as a public nonprofitable organization affiliated to Academic Center for Education, Culture and Research for Reproductive Biomedicine and infertility treatments. Then it this institute was approved by MHME as a cell‐based research center in 1998.Genetic counseling in the area of infertility and abortion has been more highlighted in Iran, and is well established in some special centers which were founded for this specific purpose. Now, there are 2–8 such centers in the capitals/big cities in each province of Iran. The most prominent ones in Tehran  are the infertility clinics at Royan and Avicenna Research Institutes which function as semi‐private and accept the national health insurances. Royan Institute (https://iscc-charity.org/mahak-charity/) for the malignancies in children.In Tehran, there are some other private clinics of infertility and abortion which are mainly affiliated with the OB/G hospitals or departments. A reason of this progress in terms of quantity and quality of the genetic services in the area of infertility and reproduction could be the government special policies on population growth. Most of these clinics and laboratories are doing PND and PGD (each is part of the IVF division and genetic department) offering molecular and cytogenetic diagnosis mainly for the cases of infertility, recurrent abortion, chromosomal aberration, and sex selection. Prenatal clinics are found in most of them; though a big highly specific center—Hope Generation—for the prenatal clinic including genetics and metabolic genetics exists in Tehran. However, cancer genetics clinics rarely exist; perhaps mainly in MAHAK  to be mandatory for all couples in Iran but not approved yet. Upon its approval by the parliament of Iran, the establishment of the genetics comprehensive centers is essential. The mandatory tests include first and second trimester combined screening . Although premarital genetic tests are now mandatory, these limited number of genetic centers may not meet the needs and coverage of the millions of people. There is certainly a real need to expand genetic services in the public health sector in Iran. Financial constraint is currently a serious obstacle for the health sector as well as for the people. On the other hand, Iran still needs the required technologies for some genetic tests; so the samples have to be sent to other countries for standard lab testing.Screening of congenital hypothyroidism and thalassemia has been successfully performed across the country by the MHME. Apart from thalassemia, a national pilot newborn screening program for other congenital and some frequent genetic diseases/disorders  autosomal recessive genetic disease are predicted to be more frequent in Iranian population versus European and American populations. This might be due to high rate of consanguinity, and close/common origin with Caucasians (as some Caucasian countries were) separated from Iran by Russian Empire in the 19th century.In the past decades, some reports have been published on ethnic‐specific differential pattern and frequencies of mutations in several rare Mendelian diseases in the Iranian population and ethnic groups:Iranian Jews in Israel had a high frequency of inbreeding with very unique and ancient Jewish community and a novel genotype in blood markers , estimating a carrier frequency of 5% in the Iranian population. It is higher than in the European population  in normal individuals were within the carrier range of 0.31–0.57 for A high prevalence (39.3%) of subjects  among Iranians; therefore, the harmful effects of drugs are relatively common  was identified in 35 affected individuals (out of 96 pedigree members) among an expanded pedigree among Lurs. Therefore, the prevalence of X‐ALD is expected to be higher among consanguineous Lurs ethnicity CTNS  mutations is highlighted in Iranian children with distal renal tubular acidosis (dRTA); moreover a novel mutation pattern of AE) has been reported in patients with distal renal tubular acidosis in Iran  , Familial Mediterranean Fever (FMF), phenylketonuria (PKU), and maple syrup urine disease (MSUD). FMF caused by mutations in the The genetic diseases with a higher referral rate to the author's genetics laboratory at a university hospital in Iran are listed in Table Congenital defects registries have been recently implemented in Iran; thus there is still no big cohort study for the rates and numbers of Mendelian disorders. However, there is an estimate of significantly higher frequencies for autosomal recessive disorders due to high rate of consanguinity and intraethnic marriages, and close ethnicity with Caucasians in north, northwest, and northeast of Iran , Iran, Iraq, and eastern Turkey .The Rare Diseases Foundation of Iran (RADOIR) (with an affiliation to “Rare Diseases Patients without Borders”) was established in 2008 to create a patient registry and to help individuals with rate genetic diseases in Iran (3) of the ITSR] (https://www.treasury.gov/resource-center/faqs/Sanctions/Pages/faq_iran.aspx#lic_agmed_amend). This includes the NGS equipment and tools; however, the sanctions have a significant negative impact on it indirectly. A considerable part of the delay and lagging in genetic services in Iran, in particular in the recent two decades, has been due to the conflict of interests. Although it was due to the shortage in qualified professional human resources in the field of clinical diagnostic genetic laboratories, a number of the private genetic laboratory directors had been the members of the Iranian Board of Medical Genetics at MHME, while simultaneously serving as advisor/counselor to MHME policy maker(s) in the field of genetics. Synchronously, some of them had also been the members of a team who approved the permission and licenses of other private genetic laboratories, and also in charge of reviewing the complaint files against a laboratory geneticist colleague (as referees). All above‐mentioned parameters and factors resulted in a delay and restriction/constriction in the expansion of services in genetics and genomic medicine in Iran, despite a highly consanguineous population, and despite the big efforts which have been done by a number of medical laboratory geneticists.The role which NGS technologies play in practicing medical/clinical genetics, disease diagnosis and thus patient management, is prominent and significant. It can also be cost‐effective for a National Health System. However, NGS and the highest quality services in genetics and genomic medicine have not been practically implemented at the clinical level in Iran yet. This pitfall is multifactorial including underestimating the medical/clinical genetics discipline as a clinical residency program by MHME and IRIMC, the recent economic decline in addition to the international and US sanctions against Iran, and some defects in national regulations and administrations. Although as clarified in the National constitution fundamental law and re‐emphasized in the 6th National Development Plan, the Iranian government authority is in charge of providing the standard level of health including genetic services to all Iranian individuals who are in need. The Office of Foreign Assets Control (OFAC) None declared.


These literatures support the contention that mental control of musical imagery is multi-faceted. Future research should investigate these two components of mental control and better integrate the diverse literatures on musical imagery.Hearing music in your head is a ubiquitous experience, but the role mental control plays in these experiences has not been deeply addressed. In this conceptual analysis, a dual-component model of mental control in musical imagery experiences is developed and discussed. The first component, initiation, refers to whether the musical imagery experience began voluntarily or involuntarily. The second component, management, refers to instances of control that occur after the experience has begun . Given the complex nature of this inner experience, we propose a new model combining and integrating four literatures: lab-based auditory imagery research using musical stimuli; involuntary musical imagery; mental rehearsal and composition in musicians; and  Engagement with music is pervasive—we subscribe to music-listening services, star in mini-concerts during our showers and commutes, and are bombarded by upbeat, bopping tunes when shopping. Our musical experiences are not limited to our external environment, however—we also hear music in our “mind’s ear.” Musical imagery can broadly be described as hearing music in one’s head not simultaneously present in the environment . People These common internal experiences also vary in their complexity. In some experiences, people only imagine select components of the music  but in others report experiencing more subtle components of the music, such as harmonic lines or different timbres of instruments . FurtherOne multi-dimensional model of musical imagery  identifiBy discussing mental control of musical imagery this way, we can reflect on what the field has already examined and where we have yet to go. When re-examining the research traditions in musical imagery, it’s evident this framework provides new ways of organizing and interpreting what we know about mental control of musical imagery and demonstrates that seemingly different musical imagery experiences have more in common than they first appear to. Additionally, by having a common language with which to describe these mental control processes, we can better articulate what we already know, develop research questions that become obvious once operating within this framework, and refine our assessment of mental control.1In this conceptual analysis, I focus on only the dimension of mental control and examine what is known about the mental control of musical imagery in psychology and musicology. I demonstrate that mental control of musical imagery can be broken down into two distinct components—initiation and management. I analyze lab-based auditory imagery work using musical stimuli and explore how the principles of mental control established through auditory imagery research can be applied to musical imagery experiences in daily life. Because musical imagery in the lab and in daily life are related experiences, these principles can be further refined to address the greater complexity inherent in musical imagery in everyday life. This conceptual analysis also applies the dual component model to three everyday musical imagery approaches: involuntary musical imagery, mental rehearsal and composition, and ecological musical imagery .Musical imagery is one example of auditory imagery. Auditory imagery research, rooted in cognitive psychology, has often used tonal and musical stimuli in its lab-based paradigms to investigate principles of people’s auditory imagery experiences—this section focuses only on studies using musical stimuli. These music-based auditory imagery studies assess a range of people’s auditory imagery capabilities, from simple imagery-assisted pitch discrimination to complex mental transformations of melodies. Although this literature does not formally discuss mental control, the natures of the tasks provide support for the two proposed components of mental control—initiation and management. Inherent in any auditory imagery task is the need to construct a mental image. In early work, the imagery tasks were relatively simple—imagining the pitch of a presented tone and completing a signal detection task . These rSeveral studies also assess people’s ability to manage their established images, such as deliberately sustaining the image—Other sustention work uses Temporal Accuracy tasks see , which aResearchers have also used more complicated sustention tasks that involve continuous monitoring of an image. A more complex Pitch Discrimination task involved listening to a melody and judging whether the subsequently presented notation matched the heard melody . To evalIn Loudness Profile studies see , particiOther studies using Tempo Judgment paradigms see  ask partAlthough sustaining musical imagery is one example of management, the more intuitive sense of management is the ability to manipulate and alter aspects of an image. In one Pitch Manipulation study see , particiResearchers have also examined people’s ability to perform complex mental manipulations using a Melody Transformation task see . MusiciaAdditionally, a survey measure—the Bucknell Auditory Imagery Scale BAIS; —has beenPerformance on the BAIS-Control subscale suggests there are individual differences in the self-reported ability to control auditory images and, in some cases, predicts performance on auditory imagery tasks. In several cases, higher self-reported imagery control predicted better accuracy  on auditThis work, however, has not explored the complexity of these experiences outside of the lab. In classic auditory imagery studies, the stimuli are single tones or chords or simple melodic lines e.g.,  and moreWhen applying this mental control framework to daily life, it is necessary to recognize that initiation and management of musical imagery in daily life will not look identical to these components when examined in a lab. First, in lab studies participants initiate and manipulate musical imagery as specified by researchers. Although possible, it is unlikely that in daily life someone is playing the first few notes of the Bb major scale and requests that another person imagines the rest of that scale or for someone to be told to imagine a single tone and be asked, “Is this your note?” People have a variety of motives for deliberately initiating and managing musical imagery that are not captured in lab experiments. Additionally, the nature of lab-based auditory imagery tasks is predicated on people willfully initiating and managing specific musical images, making it difficult to study involuntary or uncontrolled instances of musical imagery see ; howeverEveryday musical imagery research can be grouped into three approaches: (1) the involuntary musical imagery approach; (2) the mental rehearsal and composition approach; and (3) the ecological musical imagery approach. Although each approach focuses on a different slice of musical imagery, all three provide support for the dual-component model.2Recent everyday musical imagery research has focused on involuntary musical imagery—experiences defined as being “spontaneous” and “uncontrolled” e.g., . AlthougHearing earworms is a nearly universal experience , but theBut what exactly is meant by “involuntary” is inconsistent in the literature. In a few definitions, the involuntariness refers to initiation—the music appeared spontaneously and without intention. For example, involuntary musical imagery has been described as a “short musical piece, which comes to the mind unintended” , p. 2189The same term is used, but how mental control is discussed lacks consistency. Although management is not explicitly referenced as a separate aspect of mental control, the involuntary musical imagery literature does provide evidence for its existence. This literature often asks about people’s ability to either change the content of their musical imagery or to end the experience. For example, in two separate studies participants were asked what activities they engaged in to get rid of their involuntary musical imagery —people rOne study has directly compared involuntary and voluntary musical imagery experiences using a Tempo Judgment paradigm see . They coUnsurprisingly, musicians also report using imagery techniques to enhance their performances. To bolster their confidence, some performers report picturing themselves having won a role and performing on stage prior to an audition ; others Most work has focused on people’s use of mental imagery as a rehearsal tool and the efficacy of imagery compared to other rehearsal techniques. In qualitative studies, musicians described the ways musical imagery factors into their rehearsal and performance practices. Musical imagery can be used to achieve several goals—a survey of music students and musicians revealed musical imagery is often used to achieve mastery of a piece, assess technical aspects of music, and rehearse whole pieces . AdditioMusicians allude to both initiating and managing their musical imagery experiences. Most frequently, musicians reported running through the piece of music and constructing an image of how a performance should sound . For somThese studies examining mental rehearsal provide a limited amount of support for the use of initiation and management and any conclusions are largely speculative. These descriptions do, however, identify starting points for work emphasizing when and how musicians employ involuntary and voluntary musical imagery.There are also quantitative studies examining similar questions that are largely concerned with the effectiveness of using musical imagery as a rehearsal technique as compared to other methods. Multiple studies manipulate the kind of feedback available to participants when they perform and assess impacts on performance quality. In one project, the efficacy of purely mental or physical practice of novel music was compared . ParticiAn early study assessed when using mental rehearsal is beneficial . While lIn more complex paradigms, musicians perform pieces under a variety of feedback conditions. In one study, pianists were asked to perform memorized music under four different conditions: (1) normal playing conditions (baseline); (2) without auditory feedback ; (3) without auditory or visual feedback ; and (4) tapping a single key to the beat without auditory or visual feedback . PerformIn a related design, participants were presented with a musical score that had a well-known melody from classical music embedded within it, but this melody could not be identified through visual inspection of the score but could using musical imagery . ParticiThese quantitative mental rehearsal studies are comparable to those from the lab-based auditory imagery approach—they use behavioral methods to assess imagery ability in the lab—so they can be interpreted similarly. In all tasks, people are instructed to imagine specific passages of music. Their ability to do so indicates people can initiate musical imagery. Likewise, these tasks require people to imagine an extended passage, not just a single tone. This means that to complete the task, people are sustaining their image, one form of management. These principles easily transfer from the lab-based auditory imagery research, but these studies differ in their aims. By using richer musical stimuli that more closely approximate music that may be mentally rehearsed , these studies demonstrate the ability to control forms of complex musical imagery and that such techniques can be used to accomplish musical goals.A smaller literature has discussed the role of musical imagery in composition. Mental imagery has often been thought to be connected to the generation of creative ideas see , and musI carry my thoughts about with me for a long time, often for a very long time before writing them down. I can…be sure that…I shall not forget [a theme] even years later. I change many things, discard others, and try again and again until I am satisfied; then, in my head, I begin to elaborate the work…the underlying idea never deserts me. It rises, it grows. I hear and see the image in front of me from every angle , p. 194.Examination of documentation of other eminent composers’ references to the use of musical imagery echoes the sentiments expressed by Beethoven—imagery is an important aspect of the composition process . BeethovWithin the contemporary scientific literature, there has been very little discussion of musical imagery’s role in the composition process, and what does exist relies on theoretical musings, anecdotes, or interviews with a few composers e.g., . These rThe final approach uses ecological momentary assessment techniques to measure everyday musical imagery experiences. Researchers tend to take a descriptive, exploratory approach: they seek to describe people’s everyday musical imagery experiences. Experience sampling, the most frequently used technique, collects probe-caught musical imagery experiences as they are happening via completion of multiple surveys per day across several days at random time intervals. This method provides researchers with a measure of control over data collection in people’s everyday environments . All studies discussed used experience sampling methods. This approach preserves differences between episodes that can be obscured when using retrospective survey or interview measures that require respondents to pool their musical imagery experiences  that can be used to better divide and understand this class of experience. Based on existing data, it is possible to further differentiate cases of involuntary musical imagery that persist in being uncontrolled from cases in which people manage the experience. This additional specificity allows for more refined examination of whether these experiences differ on other dimensions of musical imagery. But this also suggests that current work on involuntary musical imagery is limited because it obscures potential differences between involuntarily initiated musical imagery that remains involuntary and episodes that are deliberately managed. Further, the proposed model describes multiple ways in which a single episode of musical imagery can be involuntary, showing that the label of “involuntary musical imagery” does not convey the same specificity it once did when the field of musical imagery research was less mature.Additionally, the four literatures have evolved independently with few bridges between them. Researchers commonly review work within their own approach and provide limited, if any, consideration of findings from the other approaches. This is especially true of the mental rehearsal and composition approach, rooted in music education, which is almost completely isolated from the others. But in providing a common language regarding mental control, this model can illuminate how this literature fits alongside the other three. Although this conceptual analysis focuses on one piece of musical imagery experiences, it demonstrates these approaches have similarities.For instance, musicians reference having music pop into their heads that is then applied to compositions  or havinSince both initiation and management are evident in the four approaches, a natural step is to apply the lessons from one approach to the others. For example, the strengths of the lab-based auditory imagery approach include its behavioral measurement and emphasis on the cognitive processes underlying imagery. But it often lacks the complexity of musical imagery in everyday life and has limited ecological validity. The ecological approach has the opposite character—research assesses musical imagery in people’s daily lives, but its descriptive and self-report nature does not provide the same clarity and validity as the lab-based studies see ; Table 2Borrowing techniques would benefit both literatures without compromising their respective focuses. Future auditory imagery work could use more complex stimuli, such as music similar to what is heard in everyday life  most closely relate to attempts to control musical imagery? Do these factors differ for initiation and management? These are a few examples of research that can emerge through differentiating between the initiation and management.Importantly, future research must also investigate these components of mental control of musical imagery concurrently across all approaches to further substantiate the distinction between initiation and management. Since research has yet to examine initiation and management within the same study, the association between these two components and any differential relations with related concepts . To date, no research has examined sustention, manipulation, and termination of musical imagery episodes individually and thus a parsimonious approach to mental control of musical imagery was adopted. Further work is necessary to better understand how these dimensions of management relate to one another and whether there are additional components of mental control of musical imagery.People have rich internal worlds. Musical imagery is one complex, idiosyncratic internal experience the vast majority of people report regularly having in their everyday lives e.g., . We exhiMental control, an important element of musical imagery experiences, is a complex, multi-faceted process that has not been a focal point of past research. Examining four diverse approaches to musical imagery—lab-based auditory imagery, involuntary musical imagery, mental rehearsal and composition, and ecological musical imagery—demonstrates that mental control is not a singular, unitary construct and can be broken down into two overarching components: initiation and management.Recognizing a dual-component model of mental control advocates for a thoughtful re-examination of past work and generates new directions for future research. By re-examining the literature, we can identify its limitations and what prior research already can tell us about initiation and management and where there are paths for growth. But more importantly, this dual-component model can spark new lines of research to develop our understanding of the underlying processes of musical imagery.KC is the sole author and is responsible for all manuscript contents.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Zelandoperla fenestrata species group  contains populations ranging from fully winged (macropterous) to vestigial-winged (micropterous), with the latter phenotype typically associated with high altitudes. The presence of flightless forms on numerous mountain ranges, separated by lowland fully winged populations, suggests wing reduction has occurred multiple times. We use Genotyping by Sequencing (GBS) to test for genetic differentiation between fully winged (n = 62) and vestigial-winged (n = 34) individuals, sampled from a sympatric population of distinct wing morphotypes, to test for a genetic basis for wing morphology. While we found no population genetic differentiation between these two morphotypes across 6,843 SNP loci, we did detect several outlier loci that strongly differentiated morphotypes across independent tests. These findings indicate that small regions of the genome are likely to be highly differentiated between morphotypes, suggesting a genetic basis for wing reduction. Our results provide a clear basis for ongoing genomic analysis to elucidate critical regulatory pathways for wing development in Pterygota.Wing polymorphism is a prominent feature of numerous insect groups, but the genomic basis for this diversity remains poorly understood. Wing reduction is a commonly observed trait in many species of stoneflies, particularly in cold or alpine environments. The widespread New Zealand stonefly  Within these groups, flightless taxa are particularly common on islands, at high altitudes and high latitudes1. In some cases, however, the degree of wing development may vary between closely related species or even within a species. While referred to as “wing polymorphism”, such variation often consists of morphs that differ in all major aspects of flight capability , as well as many other aspects of physiology and reproduction. These polymorphisms may result from a variety of causes: alternate morphologies may be encoded by different genotypes (genetic polymorphism), induced by different environments , or produced by variation in both genetic and environmental factors5. The degree of wing development can either be dimorphic with two alternative forms, or variation can exist along a spectrum.Understanding the genetic basis of phenotypic variability not only illuminates active evolutionary processes occurring within species, but may also shed light on the evolution of different morphologies among species. Wing polymorphism has arisen in many insect orders, with variability in wing morphology particularly prominent in Hemiptera (true bugs), Coleoptera (beetles), Orthoptera (crickets and grasshoppers), and Plecoptera (stoneflies)8). Wing reduction may confer an adaptive advantage when habitat stability is high, and when habitat complexity is low9. Habitat isolation may also promote flight loss, as the removal of flighted emigrants from habitat patches selects against this dispersal ability12. Specifically, in alpine environments high winds may sweep away fully winged individuals capable of flight15. Wing reduction has also been attributed to the high energy expenditure required in the production and maintenance of flight apparatus, with dispersal apparently traded off for life history traits such as fecundity21.There are many factors that influence the relative costs and benefits of flight in insects , brachypterism (short-winged), micropterism  and apterism (wingless)27. Even most fully winged stonefly taxa are typically considered to be weak flyers with limited dispersal ability33. There have been several studies of wing reduction in stoneflies e.g.38, with some suggesting a possible genetic basis for short wingedness e.g.39 but this hypothesis remains to be tested.Stoneflies are of particular interest relating to the evolution of insect flight due to their early divergence within winged insects (Pterygota) and also because they exhibit multiple wing-powered locomotive behaviors, including sailing and surface skimming40 have enabled the low-cost discovery and genotyping of thousands of genetic markers for non-model organisms, revolutionizing ecological, evolutionary and conservation genetics43. In particular, these advances have enabled the discovery of many candidate loci involved in specific phenotypic traits46. Such advances have been made either with quantitative trait loci (QTL) mapping using pedigree information, or through genome-wide association studies (GWAS) that identify non-random associations of alleles between loci and adaptive traits as a consequence of natural selection49.Over the last decade, high-throughput genetic sequencing, along with reduced representation genomic libraries50. For instance, the proximate endocrine processes that control wing development have been investigated in wing-polymorphic crickets (Gryllus sp.), showing Juvenile Hormone (JH) may regulate wing development in this species51, while in a planthopper (Nilaparvata lugensor), genes in the insulin-signaling pathway may regulate wing development53. The genes responsible for wing polymorphism have also recently been investigated in ants (Pheidole morrisi)54, salt marsh beetles 56 and pea aphids (Acyrthosiphon pisum)58. There are also known genes responsible for wing patterning and development in model organisms such as Drosophila melanogaster, which may be relevant to intra-specific wing polymorphism59. While genetic changes often underlie wing polymorphism, epigenetic changes have also been demonstrated between wing morphs in a planthopper (Sogatella furcifera)61.The underlying bases for wing polymorphism have now been studied in several species of insects, revealing various environmental, developmental, and genetic controls, often with multiple developmental pathways and regulators e.g.Zelandoperla fenestrata species group  contains populations that range from fully winged to vestigial-winged, with wing-reduced populations more prevalent in southern South Island, particularly at higher altitudes63. Under current taxonomy, micropterous individuals are classified as Zelandoperla pennulata (McLellan 1999), dark-colored individuals, including those implicated in the mimicry of another stonefly (Austroperla cyrene), are classified as Zelandoperla tillyardi (McLellan 1999), while the remaining light-colored fully winged individuals are classified as Zelandoperla fenestrata (Tillyard 1923). The three described species, however, appear to represent co-distributed color and wing-length polymorphisms rather than discrete evolutionary units, with the species group actually comprising five geographically discrete, deeply divergent clades (from 2–9% average divergence at COI)32. These five regional clades exhibit differing propensities to exhibit wing reduced populations   wing loss is genetically determined, or (2) wing loss is mediated by environmentally determined gene expression (i.e. polyphenism). Both of these hypotheses have received support from studies of other wing-dimorphic insects. Examples of taxa showing genetically determined wing dimorphism (Hypothesis 1) include several species of carabids and weevils66 where wing dimorphism is controlled by a single gene operating in a Mendelian fashion. Similarly, in field crickets67 maize leaf hoppers (Cicadulina sp.)68 and salt marsh beetles 69, wing polymorphism is genetically controlled but related to a complex interplay between many genes. However, in a situation more consistent with Hypothesis 2 (polyphenism), while wing morphology in Gryllus crickets can be controlled either by a single gene locus or a polygene complex, both can be regulated by the level of juvenile hormone (JH) – whereby if JH exceeds a threshold value during a critical developmental stage of the insect, wing development is suppressed70. Other environmental factors that can influence wing development include abiotic factors such as temperature66 and photoperiod71 as well as biotic factors such as food resources66 and population density72. Many of these environmental regulators of wing development also have a genetic component, for instance the fully winged morphotype of the red fire bug (Pyrrhocoris apterus) is determined by a recessive allele, whose penetrance depends on photoperiod and temperature73. Environmentally induced wing polyphenism in insects can also be transgenerational, with the level of the hormone ecdysone in the mother (regulated by population density) altering the expression of wing development in the offspring of the pea aphid (Acyrthosiphon pisum)74.There are two (non-exclusive) hypotheses as to how Z. fenestrata Clade 1, and test for loci specifically associated with wing reduction. GBS analyzes a subset of the genome next to specific restriction sites, providing a near-random sample of SNP loci across the genome, some of which may be associated with differentially adaptive genes or regulatory regions49. As mentioned, Z. fenestrata Clade 1 represents a genetically distinctive lineage of the species group, with a propensity for alpine related wing-reduction, and it may be divergent enough from other clades to warrant reclassification to species or sub-species level. Surveys of Z. fenestrata Clade 1 morphotype distributions identified one stream (Black Jacks Creek) that exhibited an unusual pattern of substantial overlap between wing morphotype populations at a low altitude. By focusing our study on a single stream population that exhibits co-distributed extreme wing morphologies, we aim to examine genomic differentiation between morphotypes without the confounding factor of neutral genetic population structure or other environmental differences.In this study, we use Genotyping By Sequencing (GBS) to test for genetic differentiation between wing morphotypes in Z. fenestrata Clade 1 were collected from under stones in rapids or in the moss or vegetation next to the stream and immediately stored in absolute ethanol. Large nymphs were also collected from under stones in rapids and returned to the laboratory in a cooler, where they were reared in Styrofoam cups at 11 °C in water from their natal stream with small amounts of stream vegetation. Upon emerging as adults (within 30 days of sampling), individuals were immediately transferred to ethanol and stored at 4 °C. While the exact location was not identified for each sample, the approximate altitude was recorded within 20 m altitude. Samples were obtained from numerous different rocks across each sampling location.Sampling was conducted along Black Jacks Creek  on the Old Man Range, South Island, New Zealand, at three sampling zones   or vestigial-winged (micropterous) groups  according to the manufacturer’s protocol using dissected head and femur tissue. Genotyping by sequencing library preparation followed the protocols of Elshire et al. (2011) with modifications as follows. DNA extractions were first dried using a vacuum centrifuge at 45 °C, then resuspended in 15 μL dH2O. To each sample, a uniquely barcoded PstI adapter was added . DNA digestion was performed using 4UPstI-HF  in 1X CutSmart BufferTM130 with incubation at 37 °C for 2 h. Adapters were ligated with T4 DNA ligase in 1X ligation buffer (New England Biolabs), followed by incubation at 16 °C for 90 min and 80 °C for 30 min. Purification was performed using a Qiagen MinElute PCR purification kit, with elution in 25 mL 1X TE. PCRs were carried out in 50 mL volumes containing 10 mL purified DNA, 1X MyTaqTM HS Master Mix (Bioline), and 1 mM each of PCR primers 5_AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATC∗T and 5_ CAAGCAGAAGACGGCATACGAGATCGGTCTCGGCATTCCTGCTGAACCGCTCTTCCGATC∗T (where ∗ indicates phosphorothioation) as per Dussex et al.64. PCRs were run in a Mastercycler ep Gradient S  under the following conditions: 72 °C for 5 min, 95 °C for 60 s, and 24 cycles of 95 °C for 30 s, 65 °C for 30 s, and 72 °C for 30 s, with a final extension step at 72 °C for 5 min. Sample concentrations were assessed using a NanoDrop spectrophotometer (Thermo Scientific) and all samples were pooled (20 ng DNA per sample). Size fractionation of the pooled library was achieved via electrophoresis on a 1.5% agarose gel, with a 300 bp size range from 200 to 500 bp selected for sequencing. A total of 96 samples were sequenced on one lane of an Illumina HiSeq 2500 using paired-end 75 bp reads.DNA extractions and GBS library prep were carried out for 96 individuals  using the same methodology as Dussex, 76 in order to create catalogues of comparable SNP loci. We optimized the pipeline according to the recommendations of Paris, et al.77. Initially, the PROCESS_RADTAGS module was used to separate reads by their barcode, remove low-quality reads (any read with an average Phred score <10 in any sliding window of 11 bp), trim all reads to 70 base pairs in length, and remove any reads that did not contain the enzyme recognition sequence. Next, the USTACKS module was used for the de novo assembly of raw reads into RAD tags. The minimum number of reads to create a stack was set at 3 (-m parameter in USTACKS), and the maximum number of pairwise differences between stacks was 2 (-M parameter in USTACKS). A catalogue of RAD tags was then generated using the 25 highest coverage individuals from each morphotype in CSTACKS. The distance allowed between catalogue loci (-n in CSTACKS) was increased to 2, after different trials were run to ensure loci were not inaccurately called as separate stacks. The execution of these components was accomplished using the STACKS denovo_map.pl script; in running this script, the optional -t flag was used to remove highly repetitive RAD tags during the USTACKS component of the pipeline. Following assembly and genotyping, the data were further filtered to maximize data quality. Using the POPULATIONS module, we retained only those loci that were genotyped in ≥50% of individuals and had a minor allele frequency ≥0.05 and a minimum stack depth of 10 (-m in POPULATIONS) for each individual. Genotypic data were exported from STACKS in GENEPOP format78 and converted for subsequent analyses using PGD SPIDER v. 279.All reads were trimmed, filtered and analyzed using the STACKS pipeline80 displaying this as a neighbor-joining relatedness tree. We investigated the number of populations (or clusters) represented in our data using FASTSTRUCTURE81 and the putatively neutral SNP dataset, default parameters, a logistic prior, and K from 1 to 6. The appropriate number of model components that explained structure in the dataset was determined using the chooseK.py function81. Results for the identified optimal values of K were visualized using DISTRUCT82. We also estimated the number of clusters using the find.clusters command in ADEGENET, with optimization based on the Bayesian Information Criterion (BIC). Finally, we also calculated expected and observed heterozygosity using Arlequin 3.583.We calculated an adjusted Genomic Relatedness Matrix (GRM)85, we utilized two distinct approaches: 1) an FST based outlier approach between a priori morphotype-pairs implemented in BAYESCAN86 and 2) a hierarchical Bayesian modeling approach implemented in PCADAPT87.Due to the limitations of differentiation-based methods and the potentially high false positive rates when looking for outlier loci under divergent selection88. Due to the sample size of vestigial-winged specimens being approximately twice that of fully winged specimens, we performed two independent BAYESCAN runs, both including all fully winged individuals, but each with a different half of the vestigial-winged group. These two comparisons therefore each had a balanced design, and can be used to evaluate the generality of outlier loci detected across partially independent comparisons (given that one comparison group remains the same while the other changes). For each analysis, BAYESCAN was run using 10,000 output iterations, a thinning interval of 10, 20 pilot runs of length 10,000, and a burn-in period of 10,000, with prior odds of the neutral model of 10. We recorded all loci with a q-value of 0.2 or less, which equates to a false discovery rate of 20%. Q-values are far more stringent than p-values in classical statistics as they are adjusted for the false discovery rate given multiple comparisons, rather than the individual false positive rates in each comparison89. To better understand the rates of false positive identification for outlier loci in this dataset, we also undertook 20 runs of BAYESCAN using identical parameters but comparing randomized groups of individuals .BAYESCAN analyses can give spurious results when there is significant over-representation of one of the groups being compared87. The number of Principal Components retained (K) for each analysis was determined by the graphical approach based on the scree-plot90, as recommended by Luu, et al.87.We also conducted outlier detection as implemented in PCADAPTAll experiments were performed in accordance with University of Otago ethics committee regulations and guidelines.Z. fenestrata Clade 1 population, we found clear wing dimorphism for both males and females, with an approximately even number of each sex sampled  with an average depth per tag of 3.1× . Following GBS, processing and filtering, we collected genotypic data at 6,843 SNPs across 96 of the measured 127 find.clusters function in ADEGENET, the optimal number of clusters was 1, and no trend in differential clustering was visible for higher values of K. Third, no structure was evident in the principal component analyses of genetic differentiation . Given this apparent panmixia, genetic differences associated with morphotype differentiation, if present, must therefore be limited to small regions of the genome, likely indicating loci under divergent selection.Given that no principal components correlated to morphotype differentiation, PCADAPT was unable to detect outliers associated with morphotypes, instead only identifying loci associated with the differentiation of a handful of slightly divergent individuals Fig. .88. These analyses also provided an opportunity to identify any loci significantly differentiated across both of these largely independent comparisons.Given that the data set included 34 fully winged individuals compared with 62 vestigial-winged individuals, we conducted two separate BAYESCAN analyses, dividing the vestigial-winged population sample in two. This approach was adopted to avoid the effects of uneven sample sizes, which can disproportionately skew outlier detection results2.The two BAYESCAN runs detected 17 and 14 outlier loci with q-values < 0.2, 9 and 8 with q-values < 0.1, and 7 and 5 with q-values < 0.05  are highly differentiated, contrasting with lower differentiation across the rest of the genome93. These results strongly support the hypothesis that wing reduction in Z. fenestrata Clade 1 is at least partially genetically determined, and not solely an environmentally determined polyphenism. Under such as scenario it is unsurprising we were unable to detect differentiation between morphotypes using analyses such as FASTSTRUCTURE and ADEGENET, as the proportion of SNPs differentiating morphotypes is small. In a similar system where a few SNPs are linked to the causal mechanisms behind ecotype divergence in sockeye salmon, no population differentiation was detectable among a complete marker set in several lake systems, despite almost fixed differences between ecotypes at these outlier SNPs95.In this study, we tested for a genetic basis for wing reduction in the New Zealand stonefly all of these loci are necessarily true outliers in this population. Indeed, outlier loci should only ever be treated as hypotheses that require further lines of evidence for validation, ideally using independent datasets. In this study, we considered outlier loci from individual runs to be ‘hypotheses’, and then tested these hypotheses on the other independent dataset, under the assumption that loci genuinely linked to wing phenotypic divergence would be detected in both tests. Our comparisons of winged versus wing-reduced samples revealed four highly significant outlier loci, each with q-values substantially lower than any values obtained from randomised runs. Additionally, the fact that three of these outliers were detected across multiple independent runs increases confidence that they represent real genetic differences strongly associated with Z. fenestrata wing variation.The current study used a relatively low threshold (<0.2) for reporting q-values for outlier loci, although this does not mean that Zelandoperla phenotypic variation, although we do not infer that these SNPs themselves have any direct causal relationship with the distinct wing morphotypes. Rather, these SNPs are likely to be in linkage with changes in nearby regions of the genome that influence morphotype96. As regions linked to the genetic changes underlying phenotypic differences can be very large98, we would require a well-annotated and near-complete genomic sequence before we could speculate as to the specific changes responsible for wing polymorphism. Currently, the genomic resources for Z. fenestrata  are too incomplete to allow us to assess if the outlier loci identified in our analyses are adjacent to each other, or more generally, if they are in islands of divergence. Without these genomic resources, it is also impossible to speculate as to the potential underlying genes that may be responsible for these two phenotypes. With further work creating a genome assembly for this species, we will be able to look at the specific genomic regions linked to the outlier SNPs defined in this study.Our study has identified several SNPs potentially associated with 64, this system is potentially an example of early ecological divergence with gene flow, similar to recent examples of ecological speciation e.g.100. While reproductive barriers do not apparently exist between these two sympatric morphotypes in Clade 1, the broad system we describe demonstrates the effects of divergent selection at different altitudes, with ongoing gene flow where the two forms meet. A similar system of repeated phenotypic divergence between high and low altitude insect morphotypes (with some wing-reduced forms) has been seen in hunter beetles in the Galapagos Islands101. From both the present study and previous work, there appears to be minimal neutral divergence (beyond possible isolation by distance)64 between fully winged and vestigial-winged morphotypes within the same stream. This pattern may indicate that the underlying genetic basis for wing loss is simple, comparable to the mechanisms underlying melanism in various insects104. If this is the case, then instead of a ‘divergence with gene flow’ scenario105, we may simply be observing the effects of two alleles that lead to different phenotypes, with differential selection across distinct environments, similar to industrial melanism in the peppered moth104.Given a probable genetic basis for wing morphotype, and evidence for divergent selection for different morphotypes at different altitudes as indicated by the broader altitudinal distribution of the two morphotypes106), and conversely, gene flow between divergent populations acts as a homogenizing force, eroding population differentiation107. In the majority of Z. fenestrata Clade 1 populations, vestigial-winged populations occupy higher altitudes and are largely allopatric to the lower altitude fully winged populations. It appears that gene flow over any distance is extremely low for Z. fenestrata, as evidenced by the fine-scale genetic structure between nearby streams64. This poor flighted dispersal ability may contribute towards maintaining the spatial divergence between morphotypes often observed, despite the observed homogenization across the majority of the genome in geographic regions of population overlap.When populations occupy different habitats, divergent natural selection can cause differentiation in ecologically important characters  behind wing loss. Z. fenestrata can have a long generation time (perhaps involving years as a wingless nymph), making breeding experiments and QTL studies challenging. Furthermore, their habitat is fast flowing rapids in highly oxygenated streams with cold water, making them difficult to raise in laboratory settings for a full life cycle, and hindering reciprocal translocation experiments in the wild. Studies of gene expression in the developing notums of Z. fenestrata nymphs of different morphotypes should provide more information to the regulatory mechanisms and pathways underlying wing development in this species.Untangling the precise mechanisms of wing reduction in the Z. fenestrata Clade 1 into the separate taxon Z. pennulata. Along with there being no neutral genetic differentiation between co-occurring morphotypes of this species, we found no temporal or spatial segregation of the two morphotypes: recently-emerged fully winged and vestigial-winged individuals were collected simultaneously, and in immediate sympatry. These results are consistent with the completely overlapping temporal patterns of emergence documented by McLellan63. While fully winged and vestigial-winged morphotypes within Z. fenestrata Clade 1 appear to have minimal genetic differentiation between them, suggesting they are conspecific, the species status of this clade has not been formally reviewed. The remaining clades of the Z. fenestrata species group appear to have different propensities for wing reduction , future studies will aim to assess genetic variation at potential wing-loss loci across the entire group.Our results reinforce the need for taxonomic revision for this species group, as there is no genetic evidence for the separation of vestigial-winged morphotypes of Zelandoperla fenestrata Clade 1 presents an ideal taxon to examine this phenomenon, potentially revealing the generalized mechanisms behind wing reduction in this order. Our results for this spatially overlapping population of fully winged and vestigial-winged Z. fenestrata Clade 1 morphotypes support the hypothesis that wing development has a genetic mechanism rather than being solely environmentally determined. While there was no neutral genetic structure between wing morphotypes, outlier loci were identified between these two groups. While it is possible that these outlier loci are not themselves linked with the specific causative changes associated with wing development, any genetic differences linked to wing morphotype differentiation in an otherwise sympatric population must indicate that there is some genetic differentiation between morphotypes. Further examination of these outlier loci may reveal the underlying genes linked to wing reduction in this species.Wing dimorphism is a common trait across many species of stoneflies, but the mechanisms behind this phenotypic diversity have yet to be investigated. Supplementary Figure 1Supplementary Table 1Supplementary Table 2Supplementary Information


The olive tree is a typical crop of the Mediterranean basin where it shows a wide diversity, accounting for more than 2,600 cultivars. The ability to discriminate olive cultivars and determine their genetic variability is pivotal for an optimal exploitation of olive genetic resources.We investigated the genetic diversity within 128 olive accessions belonging to four countries in the Mediterranean Basin , with the purpose of better understanding the origin and spread of the olive genotypes across Mediterranean Basin countries. Eleven highly polymorphic simple sequence repeat (SSR) markers were used and proved to be very informative, producing a total of 179 alleles.x/y-axes of principal coordinate analysis (PCoA). Model-based and neighbor clustering, PCoA, and migration analysis suggested the existence of two different gene pools (Algerian and Syrian) and that the genetic exchange occurred between the Syrian, Italian and Maltese populations.Cluster analysis distinguished three main groups according to their geographical origin, with the current sample of Maltese accessions included in the Italian group. Phylogenetic analysis further differentiated Italian and Maltese olive accessions, clarifying the intermediate position of Maltese accessions along the The close relationship between Syrian and Italian and Maltese olives was consistent with the historical domestication and migration of olive tree from the North Levant to eastern Mediterranean basin. This study lays the foundations for a better understanding of olive genetic diversity in the Mediterranean basin and represents a step toward an optimal conservation and exploitation of olive genetic resources. Olea europaea L. subsp. europaea, 2n = 2x = 46) is a primary crop in all the countries of the Mediterranean basin where most of the global production comes from Southern Europe, North Africa, and the Near East (FAOSTAT). The olive germplasm consists of a large number of varieties mainly used for oil or table olive production and each country has a wide panorama of autochthonous cultivated varieties and wild relatives that represents an enormous reservoir of biodiversity and a valuable economic resource  spread from the temperate-hot climate coasts to the inner areas at up to 600 m a.s.l., and accounts for more than 50 different varieties, most of which are minor varieties . Algerialtivated . In the ltivated  in additltivated . The Bidltivated . “Bajda”ltivated . In factltivated .The recently renewed interest, also economical, in the Maltese olive oil sector contrasts with the scarcity of genetic studies carried out on local cultivars . Basic qA total of 128 olive accessions, both cultivated and wild, were collected from Algeria, Syria, Italy, and Malta . The 25 Young leaves were collected and immediately frozen. For DNA extraction, 70 mg of lyophilized leaf samples were processed according to TM Thermal Cycler  following the protocol described in TM 500 ROX dye Size Standard .A set of 11 microsatellite markers [simple sequence repeat (SSR)] was selected as the most effective in differentiating the olive accessions  Bouchef. PCR reao) and expected (He) heterozygosity, and fixation index (F), using the GENALEX software v.6.5 (http://biology-assets.anu.edu.au/GenAlEx/Welcome.html) (p), which considers the number of polymorphic alleles and the informativeness of a single amplified peak according to A total of 11 SSR markers provided clear and unambiguous molecular patterns used to estimate: number of alleles (Na), effective number of alleles (Ne), Shannon’s information index (I), observed (Hme.html) . The effF-statistic  was performed using GenAlex 6.1 in order to estimate the partitioning of the total molecular variance among and within populations. To test the significance of partitioned variance components, tatistic  values (tatistic . GenAlexhttp://darwin.cirad.fr)  . The resirad.fr)  and viewhttps://web.stanford.edu/group/pritchardlab/structure.html) (Genetic population structure was assessed by using the Bayesian clustering method implemented in the STRUCTURE software version 2.3.4 (re.html) , which aK test , ten independent runs for each K (from 1 to 10) were performed, using 100,000 MCMC repetitions and 10,000 burn-in periods. Resulting data were analyzed by the Structure Harvester software , which iK test . AccessiM) and the M value that reached an asymptote and simultaneously provided the smallest residual variance was selected as the most predictive model.In order to infer the phylogenetic relationships and historical admixture events amongst populations, we adopted tree-based approach implemented in TREEMIX . Firstlylocus and 25 at DCA16 locus. The number of effective alleles (Ne) per SSR ranged from 3.03 (DCA15) to 13.58 (DCA09), with a mean of 7.4. For the same markers, Shannon’s information index (I) ranged from 1.51 (DCA15) to 2.74 (DCA09). The Ho ranged between 0.42 for DCA15 and 0.89 for UDO43, whereas the He, which corresponds to heterozygosity at a single locus in a theoric panmictic population, ranged between 0.67 (DCA15) and 0.92 (DCA09). In all the accessions under investigation, the mean observed heterozygosity (Ho = 0.697) was lower than the mean expected heterozygosity (He = 0.830), determining a significant positive value for the fixation indices (mean F = 0.142) at all loci with the exception of UDO43 that showed a negative value . Null allele frequency greater than 0.20 can be considered as a threshold over which a significant underestimation of He can be found  to 3.06 (DCA15) (loci were highly informative (PIC > 0.50).The number of allele combinations ranged from 16 at the us DCA09 . The eff (DCA15) . PIC valF-statistic test, that relates the diversity within-population to the total genetic diversity, confirmed the significance of the partitioned variance components, with values of Fst = 0.152, Fit = 0.268, and Fis = 0.137.The genetic relationships between the Mediterranean olive accessions were investigated by using PCoA performed on Nei’s unbiased genetic distance matrix . A totalK at K = 3 and as result all accessions were grouped into three different populations, with four accessions assigned to the admixed group  and population 3 , Fst was 0.122 between population 1 (Algeria) and population 2 (Syria), and Fst was 0.079 between population 2 (Syria) and population 3 . Ho, He, and the fixation index (F) were also calculated within each group , 0.779 (He), and −0.037 (F); for population 2: 0.772 (Ho), 0.801 (He), 0.038 (F); for population 3: 0.771 (Ho), 0.713 (He), and −0.075 (F).For population 1, the mean values were 0.805  were classified into two molecular profiles and were different at eight SSR alleles; “Ogliarola_68” and “Ogliarola Garganica_71” (Apulia region) were differentiated by 10 SSR alleles; “Ogliarola_68” and “Ogliarola Salentina_89” were differentiated by three SSR alleles, whereas “Ogliarola Garganica_71” and “Ogliarola Salentina_89” were differentiated by nine SSR alleles. “Coratina_60” and “Coratina_simile_88” (Apulia region) were differentiated by 11 SSR alleles.The rare white cv. Oliva Bianca IT and Leucocarpa IT clustered together and were clearly separate from the other Italian accessions such as LeucoarpaPal, indicating that the probability of the same mutation affecting anthocyanin synthesis, responsible for the white color of ripened olives, occurred in different accessions . MoreoveBased on log-likelihood and residual variance values, the most predictive model suggested the presence of two migration events . The sigMediterranean landscape and culture has in the olive tree its distinctive element, and olive oil production is among the sectors of high economic significance in the area. Indeed, olive tree cultivation and marketing of olive oil and table olives are major sources of employment and income in the Mediterranean Basin. For these reasons, many projects addressing the characterization, conservation and utilization of olive genetic resources have been recently funded by local administrations in several Mediterranean countries . Geneticlocus UDO43), indicating a defect of heterozygosity in the collection. o over He and other authors have reported a defect of heterozygosity in olive, ascribing it to differences in plant samples and in the set of genetic markers  and Italian (cluster III) accessions, but not in the Syrian (cluster II) accessions. This result could be due to the limited area of origin of the Syrian accessions, and to the selection operated on some alleles , bibliographic reference, repeat motif, primer sequence and annealing temperature (Ta) is reported.Click here for additional data file.10.7717/peerj.5260/supp-2Supplemental Information 2For each cluster, the observed heterozygosity (Ho), the expected heterozygosity (He), and the fixation index (F) are reported. Cluster I (Algerian accessions), Cluster II (Syrian accessions), Cluster III .Click here for additional data file.10.7717/peerj.5260/supp-3Supplemental Information 3Click here for additional data file.


Melipona rufiventris Lepeletier, 1836 is a Brazilian native stingless bee that is part of a species complex known as the ‘rufiventris group’, making it difficult to distinguish between the different species. Populations in this group are facing a severe decline, leading to the risk of local extinction, and therefore, their conservation should be treated as a major concern. This study describes the first set of tri- and tetranucleotide microsatellite markers, using next-generation sequencing technology for use in the identification of genetic diversity and population structure in the ‘rufiventris group’. A total of 16 microsatellite loci displayed polymorphism. Analysis of the whole data set (n = 50) detected 63 alleles in all loci, ranging from 2 to 7 with a mean of 3.9 alleles/locus. A genetic diversity analysis revealed high values for population differentiation estimates  between the Atlantic Forest, Cerrado, and Caatinga biomes. An additional evidence for genetic divergence among populations was also found in the ’rufiventris group’; these should be treated as separate conservation units or even as separate species. These microsatellite markers have demonstrated a strong potential for assessing population discrimination in this threatened stingless bee group.The species  Bees are considered the main pollinators in natural and agricultural environments. This ecosystem service is essential to sustaining species diversity and production of crops. Meliponines belong to this group of eusocial insects and are characterized by atrophied stingers in both workers and queens, and are found in most tropical or subtropical regions of the world .Melipona rufiventris Lepeletier, 1836 is a native stingless bee distributed mainly in the Atlantic Forest, Caatinga, and Cerrado biomes in Brazil [rufiventris group’ because of their similar morphology, which makes it difficult to distinguish between the different species [M. rufiventris is a complex of two or three species with a distinct distribution [Apis mellifera [M. rufiventris occurs with a single male, and as a result, considerably low intracolonial genetic variability can be generated [The species n Brazil . It is a species ,5. Additribution ,6,7. Thiellifera , and wheenerated .Melipona rufiventris is one of these bees that are becoming rare, and are listed as Endangered (EN), due to the adverse effects of deforestation, habitat loss, and predatory collection of honey [Some of the Brazilian endemic stingless bees are on the official national list of fauna species threatened with extinction . The speof honey ,12. TherMicrosatellite markers, or simple sequence repeats (SSR), have emerged as one of the most popular and effective tools for determining the genetic divergence among populations and the estimation of population structure and genetic diversity in different taxa ,13,14, wM. rufiventris , and momarkers; ,16. Moremarkers; .loci from primers developed from other species in the same genus  might ociculata . Thus, iciculata  in improMelipona species [Next generation sequencing has been recently used for the isolation and development of microsatellite loci in the  species ,23. The  species .Melipona rufiventris group’ in three Brazilian biomes.Therefore, this study describes the first set of tri- and tetranucleotide microsatellite markers, using low coverage whole genome sequencing data from the Illumina platform, and their application to assess genetic diversity and population structure of the existing forms in the ‘DNA-Gdansk), following the manufacturer’s protocol for animal tissue. DNA samples were electrophoresed on 1.0% agarose gel to test for overall quantity and quality of the DNA yield.A total of 50 worker bees, one from each colony, were randomly collected in the states of Minas Gerais (n = 20), Goiás (n = 15), and Piauí (n = 15), Brazil , Table 1A single individual DNA sample of approximately 1 µg was used to prepare the genomic library for sequencing, following the standard protocol of the Illumina Nextera XT Library Preparation kit . The DNA library was sequenced using a MiSeq Benchtop Sequencer , targeting 500-bp fragments with 2 × 250-bp reads in a paired-end sequencing configuration. The paired-end Illumina reads were first combined to produce contigs with CLC Genomics Workbench 7.0.4 .http://bioinfo.ut.ee/primer3-0.4.0/).Contigs were added directly into Msatcommander 0.8.2  for dete2, 1.0 mM dNTP mix, 0.25 mM of each primer and 0.75 units of Taq DNA polymerase . All reactions were run on a Veriti 96-well Thermal Cycler  using the PCR temperature profile indicated in Genomic DNA from the 50 individuals described above  were useHO), expected heterozygosity (HE), and allele richness (AR) were calculated using the Fstat v2.9.3.2 software [RST, a measure of genetic differentiation analogous to FST, and DEST estimator of actual differentiation, as implemented in GenAlEx v.6.5 [The software Micro-Checker 2.2.3  was usedsoftware . The polsoftware . Deviatisoftware . A Bayessoftware , was usesoftware . The proEx v.6.5 .Illumina MiSeq sequencing resulted in 54,555,929 reads, which were assembled into a total of 137,313 contig sequences. Minimum and maximum contigs were 200 and 13,505 bases, respectively, with an average size of 397 bases. The Msatcommander 0.8.2 program identified 9745 (7.1%) contigs with microsatellite loci consisting of di- to hexa-nucleotide SSRs with at least six repetitions.Melipona rufiventris. All microsatellite sequences isolated and validated in this study were deposited in the NCBI in the GenBank database under accession numbers MK133898–MK133922.For ease of imaging and scoring, only tri- and tetranucleotides were examined. From these potential microsatellite markers, 25 loci were randomly selected for primer designing and validation in Among all 25 designed primer pairs, 16 loci (64%) were amplified successfully, producing consistent and specific PCR bands of expected size. Possible assembling errors or mutations in both primer-annealing sites at each locus could have resulted in the failed amplifications.Mruf 6, 13, 19, 20, 21, 22) to 7 (Mruf 9) with a mean of 3.9 alleles/locus (Melipona seminigra merrillae [NA = 3.7), Melipona interrupta manaosensis [NA = 2.8), Melipona mondury [NA = 3.0), Melipona yucatanica [NA = 2.6 to 3.6), and Melipona fasciculata [NA = 3.9). Furthermore, these novel microsatellite loci were more polymorphic than the SSR markers developed from an earlier study by traditional cloning methods on the same species (NA = 2.6) [Analysis of the whole data set (n = 50) revealed 63 alleles in all 16 loci, ranging from 2 (es/locus . This reciculata  (NA = 3.A = 2.6) .p > 0.05). The polymorphism of microsatellite loci was also separately evaluated in terms of allelic richness (AR), heterozygosities (H), and the polymorphic information content (PIC) in the samples collected from the three distinct biomes , and PIC were low to moderate, respectively, 2.4, 0.514/0.425, 0.345 for Minas Gerais in the Cerrado biome, 2.7, 0.547/0.479, 0.400 for Goiás in the Atlantic Forest, and 2.7, 0.563/0.502, 0.412 for Piauí in the Caatinga. Despite the fact that the low levels of genetic diversity might occur in social Hymenoptera compared to other insects [rufiventris group’ [Melipona fasciculata [M. subnitida [All loci were observed to segregate independent of each other, showing no evidence of linkage disequilibrium  were detected, mostly towards an excess of heterozygotes. This could be attributed to a reduction in population size, probably associated with extensive deforestation for new land use and urban expansion, which leads to a disproportionate loss of rare alleles, such that predicting heterozygosity from allele numbers alone creates an underestimated value [Mruf1 in Goiás and Piauí, at estimated frequencies of 0.216 and 0.218, respectively, and for loci Mruf9 (0.234) and Mruf18 (0.261) in Minas Gerais.From the 48 combinations (16 loci and 3 populations) of the overall samples, 10 significant deviations from HWE after sequential Bonferroni correction , RST (0.317), and DEST (0.284) estimates obtained from the microsatellite loci suggest the existence of genetic differentiation among populations/colonies in the ’rufiventris group’  and in M. beecheii [FST = 0.280). Such high differentiation might reflect partial isolation with reduced gene flow between the colonies located in different biomes, resulting in high inbreeding within localities [M. rufiventris, 0.055 bees per generation, was detected from microsatellite data collected in Minas Gerais [In our study, s group’ . Even thulations . Our resiventris   recognized three distinct genetic populations. The ad hoc statistic ∆K, used to infer the true number of clusters (K) that capture the major structure of the dataset, revealed the best K at the second level of sub-population separation (K = 3), with a strong signal (∆K > 400), as seen in rufiventris group’. The analysis corroborated the population assignments inferred by Structure and the pairwise STF calculations  should be called M. mondury Smith 1863 [rufiventris group’, with a distribution that goes from the northwest of Minas Gerais to Maranhão, including the state of Piauí.Principal coordinate analysis (PCoA) of codominant genotypic distance was conducted to obtain further insights into the relationships among populations of the ‘ulations c. Coloniith 1863 ,6. Our sith 1863  that indrufiventris group’—using NGS technology, have a strong potential for population-level genetic studies, and consequently, will add valuable information to aid in the conservation and management of the species. The information obtained by this set of markers could be used in conjunction with ecological data to genetically monitor the ‘rufiventris group’, in order to help detect populations at risk of decline and improve population viability for ensuring appropriate conservation and management decisions.In summary, our findings showed that the set of molecular markers described here—which are the first microsatellite loci for the ‘rufiventris group’, representing colonies from three distinct biomes, and that these should be treated as separate conservation units, each managed accordingly. However, further investigation should be conducted to confirm the extent of this genetic delimitation.Further support is also given to the presence of high degree of genetic differentiation in the ‘


AbstractAtlapetesalbinucha) comprises up to eight allopatric subspecies mainly identified by the color of the underparts (gray vs. yellow belly). Yellow and gray bellied forms were long considered two different species , but they are presently considered as one polytypic species. Previous studies in the genus Atlapetes have shown that the phylogeny, based on molecular data, is not congruent with characters such as coloration, ecology, or distributional patterns. The phylogeography of A.albinucha was analyzed using two mitochondrial DNA regions from samples including 24 different localities throughout montane areas from eastern Mexico to Colombia. Phylogeographic analyses using Bayesian inference, maximum likelihood and haplotype network revealed incomplete geographic structure. The genetic diversity pattern is congruent with a recent process of expansion, which is also supported by Ecological Niche Models (ENM) constructed for the species and projected into three past scenarios. Overall, the results revealed an incomplete genetic divergence among populations of A.albinucha in spite of the species’ ample range, which contrasts with previous results of phylogeographic patterns in other Neotropical montane forest bird species, suggesting idiosyncratic evolutionary histories for different taxa throughout the region.The White-naped Brushfinch (PageBreak This phenotypically-based arrangement suggested that similarly plumaged species may have shared a common ancestor. However, The genus rgentina , 1978, argentina . Diversirgentina . Atlapetge color . Most Athe Andes . Paynterhe Andes , 1978 inAtlapetesalbinucha (White-naped Brushfinch) is a widely distributed species found in montane regions from eastern Mexico to Colombia , we tested: a) if yellow- and gray-plumaged groups are reciprocally monophyletic, b) if there is phylogeographic structure in this widespread taxon across their range, and c) if past reconstructions of the environmental conditions were A.albinucha ranges at present indicate distributional changes that may be related with their genetic-geographic variation. These questions were approached using a mtDNA assessment of populations included within this complex, as well as environmental niche modelling analyses based on records of voucher specimens in biological collections.Here, using an extensive sampling for A.albinucha were obtained from different museum collections in Mexico, USA, and Colombia, spanning the whole distribution of the species (Table brunnescens and azuerensis). We also supplemented our study with two published sequences of Atlapetespileatus, and two from Arremonbrunneinucha to be used as outgroups  and Cytochrome b (Cyt b), which have been shown to successfully assess phylogenetic relationships due to its high probability for tracking recent diversification events (PageBreak1% agarose gel stained with Ethidium Bromide (EtBr) or EZ-Vision. DNA sequencing was performed at the High Throughput Genomics Center of the University of Washington (USA), Macrogen Inc., Korea, and at the Servicio de Secuenciación y Análisis Molecular Universidad Nacional . Sequences were edited and aligned by eye using SEQUENCHER 5.4.6 . Mitochondrial origin for all of our sequences was corroborated in BLAST, through the NCBI server (https://blast.ncbi.nlm.nih.gov/Blast.cgi). Afterwards sequences were aligned using CLUSTALX 2.1  following manufacturer’s protocols. We amplified two n events . We usedn events  and H106n events  for ND2.n events  and H156n events . PCR ampTALX 2.1  and inspmtDNA loci (ND2 and Cyt B) concatenated. Nucleotide substitution model parameters and partition schemes were estimated for each gene in PARTITIONFINDER (BIC) for model selection. Resultant partition schemes and model parameters were used for conducting a phylogenetic reconstruction using the Bayesian inference approach (BI) implemented in MR. BAYES 3.2  the examination of the standard deviation of split frequencies ; and II) by verification of parameter estimates in TRACER v1.6 (ML) criteria as implemented in RAXMLGUI 1.5b1 (ML) or when posterior probability values were > 90 % (BI).We conducted analyses using an alignment with both ONFINDER , using tAYES 3.2  using twCER v1.6 , based oUI 1.5b1 , using tMCCT) using a Yule speciation process .Divergence times were estimated through calculation of a maximum clade credibility tree , through a Median-joining method, assigning equal weights to all variable sites and an epsilon parameter with default values (Ɛ = 0). This method estimates evolutionary relationships among sequences when divergences are recent , (II) Southern Chiapas , (III) El Salvador , Honduras , and (IV) Colombia . For each group, genetic diversity was assessed through the estimation of haplotype diversity (Hd), and nucleotide diversity (π) in ARLEQUIN 3.1  NorQUIN 3.1 .AMOVA) using pairwise differences. In addition, to test if phenotypic divergence is related to genetic structure we also performed an AMOVA between gray-plumaged subspecies and yellow-plumaged subspecies. Genetic divergence between groups was also measured using STF fixation index values  was calculated by developing 1000 simulations using ARLEQUIN 3.1. Evidence of historical signatures of fluctuations in population size was also examined through a Bayesian skyline plot model on the Maximum Clade Credibility Tree (MCCT), as implemented in BEAST v1.8.4  using ecological niche models (ENM). We compiled a total of 475 geographical records, representing 176 localities, of the species through the Global Biodiversity Information Facility  and museum vouchers (see Acknowledgements). GBIF records were filtered for elimination of both duplicates and records lacking geographic data. ENMs were obtained using 19 bioclimatic variables with a cell resolution of 2.5 arc-minutes (ca. 4.5 km2) generated by the Community Climate System Model (CCSM) downloaded through WorldClim , Mid-Holocene , and LGM . CCSM scenarios were preferred over other models as it has been proposed that global cooling conditions are not overestimated (AUC), which can be used as a measure of the model's overall performance; for a second model validation we used PARTIAL-ROC (P-ROC) analysis  rendered similar topologies. The Bayesian tree topology  by both differences among populations (50.7%), as well as by variation within groups , but lower differentiation was among El Salvador and southern Chiapas (STF = 0.04556); the remaining STF values indicated moderate genetic differentiation (STF between 0.4 and 0.7). AMOVA between gray- and yellow-plumaged morphs showed that most of the variance occurs within groups (64.5%), paralleling the results of the phylogenetic analysis that showed that both phenotypes are not reciprocally monophyletic.Overall, genetic diversity values for the geographic groups showed a low nucleotide diversity (π < 0.008), but high haplotype diversity ; a second one where most samples from northern Chiapas  are located; and a third high frequency haplotype that was shared by most samples corresponding to northern Central America, which includes subspecies griseipectus and fuscipygius , whereas differentiation between major clades of A.albinucha apparently occurred around 1.5 Mya (HDP range 1.01–1.61 Mya), during the Early Pleistocene  than a random non-predictive model (AUC = 0.5), indicating that the models obtained may reflect, relatively well, the past distribution of environmental conditions where A.albinucha inhabits at present. ENMs suggested a scenario of geographically fragmented environmental conditions for populations in Mexico, Central America, and Colombia during three of the modeled timeframes: LIG  suggested these same lowland areas as corridors, which may have served for the dispersal between previously isolated populations , suggesting a scenario in which two groups (South America and Mesoamerica) have been diverging in isolation followed by range expansion, allowing the mixture of the genetic variation in periods favoring habitat connectivity during the LIG. Signatures for this vicariant scenario of genetic differentiation may be found in the phylogeographic topology, in which two groups including mainly South American and mainly Mesoamerican individuals were recovered, and in the significant variation among geographic groups determined by the AMOVA analyses  as responPageBreaksible for similar plumage changes in birds (reviewed in mtDNA variation does not correspond to plumage pattern differentiation in this species (A.albinucha may be taxonomically misleading because it doesn’t reflect population history. In addition, it has been shown that vocal repertories are very similar and calls between color morphs cannot be reliably differentiated (Causes of differentiation in plumage coloration in  islands , shorebi islands , and Aus islands . In the evations , thus suevations . Similarevations , however species , suggestentiated .A.albinucha. Genetic divergence as a result of allotypy is apparent, suggesting that these taxa are likely at allotypy (A.albinucha would support a subspecific status for all populations analyzed, thus maintaining the current taxonomic treatment (A.albinucha, as well as emphasize the role of idiosyncratic events in the recent evolution of bird taxa in this region, as it has been suggested for lowland bird taxa (Results in this paper are not conclusive in terms of the currently accepted taxonomy for allotypy . Resultsallotypy , whereasallotypy , lendingreatment . Howeverird taxa .A.albinucha were unexpected given previous findings in birds and other taxa codistributed in montane forests throughout the region (see Genetic patterns found in gion see , which igion see .A.albinucha is consistent with allotypy, which has been suggested to represent an intermediate stage in the path to reciprocal monophyly (The phylogeography of onophyly . Most caonophyly  as well onophyly , as wellonophyly .mtDNA.Environmental factors may have played a major role in shaping the evolution of morphological traits by natural selection that have been considered taxonomically relevant , such asPageBreak