A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

Integration of socioeconomic and genetic aspects involved in the conservation of animal genetic resources = Integración de aspectos socioeconómicos y genéticos involucrados en la conservación de recursos genéticos animales

El sector ganadero está siendo gradualmente dominado por sistemas intensivos y especializados en los que los factores de producción están controlados y en los que los caracteres productivos son los criterios principales para la selección de especies y razas. Entretanto, muchos de los bienes y servicios que tradicionalmente suministraba el ganado, tales como los fertilizantes, la tracción animal o materias primas para la elaboración vestimenta y calzado están siendo reemplazados por productos industriales. Como consecuencia de ambos cambios, las razas seleccionadas intensivamente, las cuales están estrechamente ligadas a sistemas agrícolas de alta producción y altos insumos, han desplazado a muchas razas autóctonas, en las que la selección prácticamente ha cesado o es muy poco intensa. Actualmente existe una mayor conciencia social sobre la situación de las razas autóctonas y muchas funciones del ganado que previamente habían sido ignoradas están siendo reconocidas. Desde hace algunas décadas, se ha aceptado internacionalmente que las razas de ganado cumplen funciones económicas, socio-culturales, medioambientales y de seguridad alimentaria. Por ello, diferentes organismos internacionales han reconocido que la disminución de los recursos genéticos de animales domésticos (RGADs) es un problema grave y han recomendado su conservación. Aun así, la conservación de RGADs es un tema controvertido por la dificultad de valorar las funciones del ganado. Esta valoración es compleja debido que los RGADs tiene una doble naturaleza privada - pública. Como algunos economistas han subrayado, el ganado es un bien privado, sin embargo debido a algunas de sus funciones, también es un bien público. De esta forma, el aumento del conocimiento sobre valor de cada una de sus funciones facilitaría la toma de decisiones en relación a su conservación y desarrollo. Sin embargo, esta valoración es controvertida puesto que la importancia relativa de las funciones del ganado varía en función del momento, del lugar, de las especies y de las razas. El sector ganadero, debido a sus múltiples funciones, está influenciado por factores técnicos, medioambientales, sociales, culturales y políticos que están interrelacionados y que engloban a una enorme variedad de actores y procesos. Al igual que las funciones del ganado, los factores que afectan a su conservación y desarrollo están fuertemente condicionados por localización geográfica. Asimismo, estos factores pueden ser muy heterogéneos incluso dentro de una misma raza. Por otro lado, es razonable pensar que el ganadero es el actor principal de la conservación de razas locales. Actualmente, las razas locales están siendo Integration of socioeconomic and genetic aspects involved in the conservation of animal genetic resources 5 explotadas por ganaderos muy diversos bajo sistemas de producción también muy diferentes. Por todo ello, es de vital importancia comprender y evaluar el impacto que tienen las motivaciones, y el proceso de toma de decisiones de los ganaderos en la estructura genética de las razas. En esta tesis doctoral exploramos diferentes aspectos sociales, económicos y genéticos involucrados en la conservación de razas locales de ganado vacuno en Europa, como ejemplo de RGADs, esperando contribuir al entendimiento científico de este complejo tema. Nuestro objetivo es conseguir una visión global de los procesos subyacentes en la conservación y desarrollo de estas razas. Pretendemos ilustrar como se pueden utilizar métodos cuantitativos en el diseño y establecimiento de estrategias de conservación y desarrollo de RGADs objetivas y adecuadas. En primer lugar, exploramos el valor económico total (VET) del ganado analizando sus componentes públicos fuera de mercado usando como caso de estudio la raza vacuna Alistana-Sanabresa (AS). El VET de cualquier bien está formado por componentes de uso y de no-uso. Estos últimos incluyen el valor de opción, el valor de herencia y el valor de existencia. En el caso del ganado local, el valor de uso directo proviene de sus productos. Los valores de uso indirecto están relacionados con el papel que cumple las razas en el mantenimiento de los paisajes y cultura rural. El valor de opción se refiere a su futuro uso potencial y el valor de herencia al uso potencial de las generaciones venideras. Finalmente, el valor de existencia está relacionado con el bienestar que produce a la gente saber que existe un recurso específico. Nuestro objetivo fue determinar la importancia relativa que tienen los componentes fuera de mercado sobre el VET de la raza AS. Para ello evaluamos la voluntad de la gente a pagar por la conservación de la AS mediante experimentos de elección (EEs) a través de encuestas. Estos experimentos permiten valorar individualmente los distintos componentes del VET de cualquier bien. Los resultados los analizamos mediante de uso de modelos aleatorios logit. Encontramos que las funciones públicas de la raza AS tienen un valor significativo. Sus valores más importantes son el valor de uso indirecto como elemento cultural Zamorano y el valor de existencia (ambos representaron el 80% de VET). Además observamos que el valor que gente da a las funciones públicas de la razas de ganado dependen de sus características socioeconómicas. Los factores que condicionaron la voluntad a pagar para la conservación de la raza AS fueron el lugar de residencia (ciudad o pueblo), el haber visto animales de la raza o haber consumido sus productos y la actitud de los encuestados ante los conflictos entre el desarrollo económico y el medioambiente. Por otro lado, encontramos que no todo el mundo tiene una visión completa e integrada de todas las funciones públicas de la raza AS. Por este motivo, los programas o actividades de concienciación sobre su estado deberían hacer hincapié en este aspecto. La existencia de valores públicos de la raza AS implica que los ganaderos deberían recibir compensaciones económicas como pago por las funciones públicas que cumple su raza local. Las compensaciones asegurarían un tamaño de población que permitiría que la raza AS siga realizando estas funciones. Un mecanismo para ello podría ser el desarrollo del turismo rural relacionado con la raza. Esto aumentaría el valor de uso privado mientras que supondría un elemento añadido a las estrategias de conservación y desarrollo. No obstante, los ganaderos deben analizar cómo aprovechar los nichos de mercado existentes, así como mejorar la calidad de los productos de la raza prestando especial atención al etiquetado de los mismos. Una vez evaluada la importancia de las funciones públicas de las razas locales de ganado, analizamos la diversidad de factores técnicos, económicos y sociales de la producción de razas locales de ganado vacuno existente en Europa. Con este fin analizamos el caso de quince razas locales de ocho países en el contexto de un proyecto de colaboración internacional. Investigamos las diferencias entre los países para determinar los factores comunes clave que afectan a la viabilidad de las razas locales. Para ello entrevistamos mediante cuestionarios a un total de 355 ganaderos en las quince razas. Como indicador de viabilidad usamos los planes de los ganaderos de variación del tamaño de las ganaderías. Los cuestionarios incluían diferentes aspectos económicos, técnicos y sociales con potencial influencia en las dinámicas demográficas de las razas locales. Los datos recogidos los analizamos mediante distintas técnicas estadísticas multivariantes como el análisis discriminante y la regresión logística. Encontramos que los factores que afectan a la viabilidad de las razas locales en Europa son muy heterogéneos. Un resultado reseñable fue que los ganaderos de algunos países no consideran que la explotación de su raza tenga un alto valor social. Este hecho vuelve a poner de manifiesto la importancia de desarrollar programas Europeos de concienciación sobre la importancia de las funciones que cumplen las razas locales. Además los países analizados presentaron una alta variabilidad en cuanto a la importancia de los mercados locales en la distribución de los productos y en cuanto al porcentaje en propiedad del total de los pastos usados en las explotaciones. Este estudio reflejó la variabilidad de los sistemas y medios de producción (en el sentido socioeconómico, técnico y ecológico) que existe en Europa. Por ello hay que ser cautos en la implementación de las políticas comunes en los diferentes países. También encontramos que la variabilidad dentro de los países puede ser elevada debido a las diferencias entre razas, lo que implica que las políticas nacionales deber ser suficientemente flexibles para adaptarse a las peculiaridades de cada una de las razas. Por otro lado, encontramos una serie de factores comunes a la viabilidad de las razas en los distintos países; la edad de los ganaderos, la colaboración entre ellos y la apreciación social de las funciones culturales, medioambientales y sociales del ganado local. El envejecimiento de los ganaderos de razas locales no es solo un problema de falta de transferencia generacional, sino que también puede suponer una actitud más negativa hacia la inversión en las actividades ganaderas y en una menor capacidad de adaptación a los cambios del sector. La capacidad de adaptación de los ganaderos es un factor crucial en la viabilidad de las razas locales. Las estrategias y políticas de conservación comunes deben incluir las variables comunes a la viabilidad de las razas manteniendo flexibilidad suficiente para adaptarse a las especificidades nacionales. Estas estrategias y políticas deberían ir más allá de compensación económica a los ganaderos de razas locales por la menor productividad de sus razas. Las herramientas para la toma de decisiones ayudan a generar una visión amplia de la conservación y desarrollo de las razas locales. Estas herramientas abordan el diseño de estrategias de conservación y desarrollo de forma sistemática y estructurada. En la tercera parte de la tesis usamos una de estas herramientas, el análisis DAFO (Debilidades, Amenazas, Fortalezas y Oportunidades), con este propósito, reconociendo que la conservación de RGADs depende de los ganaderos. Desarrollamos un análisis DAFO cuantitativo y lo aplicamos a trece razas locales de ganado vacuno de seis países europeos en el contexto del proyecto de colaboración mencionado anteriormente. El método tiene cuatro pasos: 1) la definición del sistema; 2) la identificación y agrupación de los factores influyentes; 3) la cuantificación de la importancia de dichos factores y 4) la identificación y priorización de estrategias. Identificamos los factores utilizando multitud de agentes (multi-stakeholder appproach). Una vez determinados los factores se agruparon en una estructura de tres niveles. La importancia relativa de los cada uno de los factores para cada raza fue determinada por grupos de expertos en RGADs de los países integrados en el citado proyecto. Finalmente, desarrollamos un proceso de cuantificación para identificar y priorizar estrategias. La estructura de agrupación de factores permitió analizar el problema de la conservación desde el nivel general hasta el concreto. La unión de análisis específicos de cada una de las razas en un análisis DAFO común permitió evaluar la adecuación de las estrategias a cada caso concreto. Identificamos un total de 99 factores. El análisis reveló que mientras los factores menos importantes son muy consistentes entre razas, los factores y estrategias más relevantes son muy heterogéneos. La idoneidad de las estrategias fue mayor a medida que estas se hacían más generales. A pesar de dicha heterogeneidad, los factores influyentes y estrategias más importantes estaban ligados a aspectos positivos (fortalezas y oportunidades) lo que implica que el futuro de estas razas es prometedor. Los resultados de nuestro análisis también confirmaron la gran relevancia del valor cultural de estas razas. Las factores internos (fortalezas y debilidades) más importantes estaban relacionadas con los sistemas de producción y los ganaderos. Las oportunidades más relevantes estaban relacionadas con el desarrollo y marketing de nuevos productos mientras que las amenazas más importantes se encontraron a la hora de vender los productos actuales. Este resultado implica que sería fructífero trabajar en la motivación y colaboración entre ganaderos así como, en la mejora de sus capacidades. Concluimos que las políticas comunes europeas deberían centrarse en aspectos generales y ser los suficientemente flexibles para adaptarse a las singularidades de los países y las razas. Como ya se ha mencionado, los ganaderos juegan un papel esencial en la conservación y desarrollo de las razas autóctonas. Por ello es relevante entender que implicación puede tener la heterogeneidad de los mismos en la viabilidad de una raza. En la cuarta parte de la tesis hemos identificado tipos de ganaderos con el fin de entender cómo la relación entre la variabilidad de sus características socioeconómicas, los perfiles de las ganaderías y las dinámicas de las mismas. El análisis se ha realizado en un contexto sociológico, aplicando los conceptos de capital cultural y económico. Las tipologías se han determinado en función de factores socioeconómicos y culturales indicadores del capital cultural y capital económico de un individuo. Nuestro objetivo era estudiar si la tipología socioeconómica de los ganaderos afecta al perfil de su ganadería y a las decisiones que toman. Entrevistamos a 85 ganaderos de la raza Avileña-Negra Ibérica (ANI) y utilizamos los resultados de dichas entrevistas para ilustrar y testar el proceso. Definimos los tipos de ganaderos utilizando un análisis de clúster jerarquizado con un grupo de variables canónicas que se obtuvieron en función de cinco factores socioeconómicos: el nivel de educación del ganadero, el año en que empezó a ser ganadero de ANI, el porcentaje de los ingresos familiares que aporta la ganadería, el porcentaje de propiedad de la tierra de la explotación y la edad del ganadero. La tipología de los ganaderos de ANI resultó ser más compleja que en el pasado. Los resultados indicaron que los tipos de ganaderos variaban en muchos aspectos socioeconómicos y en los perfiles de sus Integration of socioeconomic and genetic aspects involved in the conservation of animal genetic resources 9 ganaderías. Los tipos de ganaderos determinados toman diferentes decisiones en relación a la modificación del tamaño de su ganadería y a sus objetivos de selección. Por otro lado, reaccionaron de forma diferente ante un hipotético escenario de reducción de las compensaciones económicas que les planteamos. En este estudio hemos visto que el capital cultural y el económico interactúan y hemos explicado como lo hacen en los distintos tipos de ganaderos. Por ejemplo, los ganaderos que poseían un mayor capital económico, capital cultural formal y capital cultural adquirido sobre la raza, eran los ganaderos cuyos animales tenían una mayor demanda por parte de otros ganaderos, lo cual podría responder a su mayor prestigio social dentro de la raza. Uno de los elementos claves para el futuro de la raza es si este prestigio responde a una superioridad genética de las animales. Esto ocurriría si los ganaderos utilizaran las herramientas que tienen a su disposición a la hora de seleccionar animales. Los tipos de ganaderos identificados mostraron también claras diferencias en sus formas de colaboración y en su reacción a una hipotética variación de las compensaciones económicas. Aunque algunos tipos de ganaderos mostraron un bajo nivel de dependencia a estas compensaciones, la mayoría se manifestaron altamente dependientes. Por ello cualquier cambio drástico en la política de ayudas puede comprometer el desarrollo de las razas autóctonas. La adaptación las políticas de compensaciones económicas a la heterogeneidad de los ganaderos podría aumentar la eficacia de las mismas por lo que sería interesante explorar posibilidades a este respecto. Concluimos destacando la necesidad de desarrollar políticas que tengan en cuenta la heterogeneidad de los ganaderos. Finalmente abordamos el estudio de la estructura genética de poblaciones ganaderas. Las decisiones de los ganaderos en relación a la selección de sementales y su número de descendientes configuran la estructura demográfica y genética de las razas. En la actualidad existe un interés renovado por estudiar las estructuras poblacionales debido a la influencia potencial de su estratificación sobre la predicción de valores genómicos y/o los análisis de asociación a genoma completo. Utilizamos dos métodos distintos, un algoritmo de clústeres basados en teoría de grafos (GCA) y un algoritmo de clustering bayesiano (STRUCTURE) para estudiar la estructura genética de la raza ANI. Prestamos especial atención al efecto de la presencia de parientes cercanos en la población y de la diferenciación genética entre subpoblaciones sobre el análisis de la estructura de la población. En primer lugar evaluamos el comportamiento de los dos algoritmos en poblaciones simuladas para posteriormente analizar los genotipos para 17 microsatélites de 13343 animales de 57 ganaderías distintas de raza ANI. La ANI es un ejemplo de raza con relaciones complejas. Por otro lado, utilizamos el archivo de pedigrí de la raza para estudiar el flujo de genes, calculando, entre otras cosas, la contribución de cada ganadería a la constitución genética de la raza. En el caso de las poblaciones simuladas, cuando el FST entre subpoblaciones fue suficientemente alto, ambos algoritmos, GCA y STRUCTURE, identificaron la misma estructura genética independientemente de que existieran o no relaciones familiares. Por el contrario, cuando el grado de diferenciación entre poblaciones fue bajo, el STRUCTURE identificó la estructura familiar mientras que GCA no permitió obtener ningún resultado concluyente. El GCA resultó ser un algoritmo más rápido y eficiente para de inferir la estructura genética en poblaciones con relaciones complejas. Este algoritmo también puede ser usado para reducir el número de clústeres a testar con el STRUTURE. En cuanto al análisis de la población de ANI, ambos algoritmos describieron la misma estructura, lo cual sugiere que los resultados son robustos. Se identificaron tres subpoblaciones diferenciadas que pudieran corresponderse con tres linajes distintos. Estos linajes estarían directamente relacionados con las ganaderías que han tenido una mayor contribución a la constitución genética de la raza. Por otro lado, hay un conjunto muy numeroso de individuos con una mezcla de orígenes. La información molecular describe una estructura estratificada de la población que se corresponde con la evolución demográfica de la raza. Es esencial analizar en mayor profundidad la composición de este último grupo de animales para determinar cómo afecta a la variabilidad genética de la población de ANI. SUMMARY Summary Livestock sector is gradually dominated by intensive and specialized systems where the production environment is controlled and the production traits are the main criteria for the selection of species and breeds. In the meantime, the traditional use of domestic animals for draught work, clothes and manure has been replaced by industrial products. As a consequence of both these changes, the intensively selected breeds closely linked with high-input highoutput production systems have displaced many native breeds where the selection has practically ceased or been very mild. People are now more aware of the state of endangerment among the native breeds and the previously ignored values of livestock are gaining recognition. For some decades now, the economic, socio-cultural, environmental and food security function of livestock breeds have been accepted worldwide and their loss has been recognized as a major problem. Therefore, the conservation of farm animal genetic resources (FAnGR) has been recommended. The conservation of FAnGR is controversial due to the complexity of the evaluation of its functions. This evaluation is difficult due to the nature of FAnGR both as private and public good. As some economists have highlighted, livestock animals are private goods, however, they are also public goods by their functions. Therefore, there is a need to increase the knowledge about the value of all livestock functions since to support the decision-making for the sustainable conservation and breeding of livestock. This is not straightforward since the relative importance of livestock functions depends on time, place, species and breed. Since livestock play a variety of roles, their production is driven by interrelated and everchanging economic, technical, environmental, social, cultural and political elements involving an enormous range of stakeholders. Not only FAnGR functions but also the importance of factors affecting the development and conservation of FAnGR can be very different across geographical areas. Furthermore, heterogeneity can be found even within breeds. Local breeds are nowadays raised by highly diverse farmers in equally diverse farms. It is quite reasonable to think that farmer is the major actor in the in situ conservation of livestock breeds. Thus, there is a need to understand the farmers’ motivations, decision making processes and the impact of their decisions on the genetic structure of breeds. In this PhD thesis we explore different social, economic and genetic aspects involved in the conservation of local cattle breeds, i.e. FAnGR, in Europe seeking to contribute to the scientific understanding of this complex issue. We aim to achieve a comprehensive view of the processes involved in the conservation and development of local cattle breeds and have made special efforts in discussing the implications of the research results in this respect. The final outcome of the thesis is to illustrate how quantitative methods can be exploited in designing and establishing sound strategies and programmes for the conservation and development of local livestock breeds. Firstly we explored the public non-market attributes of the total economic value (TEV) of livestock, using the Spanish Alistana-Sanabresa (AS) cattle breed as a case study. Total economic value of any good comprises both use and non-use components, where the latter include option, bequest and existence values. For livestock, the direct use values are mainly stemming from production outputs. Indirect use values relate to the role of livestock as a maintainer of rural culture and landscape. The option value is related to the potential use of livestock, the bequest values relate to the value associated with the inheritance of the resources to future generation and the existence values relate to the utility perceived by people from knowing that specific resources exist. We aimed to determine the relative importance of the non-market components of the TEV of the AS breed, the socio-economic variables that influence how people value the different components of TEV and to assess the implications of the Spanish national conservation strategy for the AS breed. To do so, we used a choice experiment (CE) approach and applied the technique to assess people’s willingness to pay (WTP) for the conservation of AS breed. The use of CE allows the valuation of the individual components of TEV for a given good. We analysed the choice data using a random parameter logit (RPL) model. AS breed was found to have a significant public good value. Its most important values were related to the indirect use value due to the maintenance of Zamorian culture and the existence value (both represent over 80% of its TEV). There were several socioeconomic variables influencing people’s valuation of the public service of the breed. In the case of AS breed, the place of living (city or rural area), having seen animals of the breed, having eaten breed products and the respondents’ attitude towards economic development – environment conflicts do influence people’s WTP for AS conservation. We also found that people do not have a complete picture of all the functions and roles that AS breed as AnGR. Therefore, the actions for increasing awareness of AS should go to that direction. The farmers will need incentives to exploit some of the public goods values and maintain the breed population size at socially desirable levels. One such mechanism could be related to the development of agritourism, which would enhance the private good value and provide an important addition to the conservation and utilisation strategy. However, the farmers need a serious evaluation on how to invest in niche product development or how to improve product quality and brand recognition. Using the understanding on the importance of the public function of local cattle we tried to depict the current diversity regarding technical, economic and social factors found in local cattle farming across Europe. To do so we focused in an international collaborative project on the case of fifteen local cattle breeds in eight European countries. We investigated the variation among the countries to detect the common key elements, which affect the viability of local breeds. We surveyed with interviews a total of 355 farms across the fifteen breeds. We used the planned herd size changes by the farmer as an indicator of breed viability. The questionnaire included several economic, technical and social aspects with potential influence on breeds’ demographic trends. We analysed the data using multivariate statistical techniques, such as discriminat analysis and logistic regression. The factors affecting a local breed’s viability were highly heterogeneous across Europe. In some countries, farmers did not recognise any high social value attached to keeping a local cattle breed. Hence there is a need to develop communication programmes across EU countries making people aware about the diversity and importance of values associated to raising local breeds. The countries were also very variable regarding the importance of local markets and the percentage of farm land owned by the farmers. Despite the country specificities, there were also common factors affecting the breed viability across Europe. The factors were from different grounds, from social, such as the age of the farmer and the social appreciation of their work, to technicalorganizational, such as the farmers’ attitude to collaborating with each other. The heterogeneity found reflects the variation in breeding systems and production environment (in the socioeconomic, technical and ecological sense) present in Europe. Therefore, caution should be taken in implementing common policies at the country level. Variability could also be rather high within countries due to breed specificities. Therefore, the national policies should be flexible to adapt to the specificities. The variables significantly associated with breed viability should be positively incorporated in the conservation strategies, and considered in developing common and/or national policies. The strategy preparation and policy planning should go beyond the provision of a general economic support to compensate farmers for the lower profitability of local breeds. Of particular interest is the observation that the opportunity for farmer collaboration and the appreciation by the society of the cultural, environmental and social role of local cattle farming were positively associated with the breed survival. In addition, farmer's high age is not only a problem of poor generation transfer but it is also a problem because it might lead to a lower attitude to investing in farming activities and to a lower ability to adapt to environment changes. The farmers’ adaptation capability may be a key point for the viability of local breeds. Decision making tools can help to get a comprehensive view on the conservation and development of local breeds. It allows us to use a systematic and structured approach for identifying and prioritizing conservation and development strategies. We used SWOT (Strengths, Weaknesses Opportunities and Threats) analysis for this purpose and recognized that many conservation and development projects rely on farmers. We developed a quantified SWOT method and applied it in the aforementioned collaborative research to a set of thirteen cattle breeds in six European countries. The method has four steps: definition of the system, identification and grouping of the driving factors, quantification of the importance of driving factors and identification and prioritization of the strategies. The factors were determined following a multi-stakeholder approach and grouped with a three level structure. FAnGR expert groups ranked the factors and a quantification process was implemented to identify and prioritize strategies. The structure of the SWOT analysis allowed analyzing the conservation problem from general down to specific perspectives. Joining breed specific analyses into a common SWOT analysis permitted comparison of breed cases across countries. We identified 99 driving factors across breeds. The across breed analysis revealed that irrelevant factors were consistent. There was high heterogeneity among the most relevant factors and strategies. The strategies increased eligibility as they lost specificity. Although the situation was very heterogeneous, the most promising factors and strategies were linked to the positive aspects (Strengths and Opportunities). Therefore, the future of the studied local breed is promising. The results of our analysis also confirmed the high relevance of the cultural value of the breeds. The most important internal factors (strengths and weaknesses) were related farmers and production systems. The most important opportunities were found in developing and marketing new products, while the most relevant threats were found in selling the current conventional products. In this regard, it should be fruitful to work on farmers’ motivation, collaboration, and capacity building. We conclude that European policies should focus on general aspects and be flexible enough to be adapted to the country and breed specificities. As mentioned, farmers have a key role in the conservation and development of a local cattle breed. Therefore, it is very relevant to understand the implications of farmer heterogeneity within a breed for its viability. In the fourth part of the thesis, we developed a general farmer typology to help analyzing the relations between farmer features and farm profiles, herd dynamics and farmers’ decision making. In the analysis we applied and used the sociological framework of economic and cultural capital and studied how the determined farmer types were linked to farm profiles and breeding decisions, among others. The typology was based on measurable socioeconomic factors indicating the economic and cultural capital of farmers. A group of 85 farmers raising the Spanish Avileña-Negra Ibérica (ANI) local cattle breed was used to illustrate and test the procedure. The farmer types were defined by a hierarchical cluster analysis with a set of canonical variables derived from the following five the socioeconomic factors: the formal educational level of the farmer, the year the farmer started keeping the ANI breed, the percentage of the total family income covered by the farm, the percentage of the total farm land owned by the farmer and the farmer’s age. The present ANI farmer types were much more complex than what they were in the past. We found that the farmer types differed in many socioeconomic aspects and in the farms profile. Furthermore, the types also differentiate farmers with respect to decisions about changing the farm size, breeding aims and stated reactions towards hypothetical subsidy variation. We have verified that economic and cultural capitals are not independent and further showed how they are interacting in the different farmer types. The farmers related to the types with high economic, institutionalized and embodied cultural capitals had a higher demand of breeding animals from others farmers of the breed, which may be related to the higher social prestige within the breed. One of the key implications of this finding for the future of the breed is whether or not the prestige of farmers is related to genetic superiority of their animals, what is to say, that it is related with a sound use of tools that farmers have available to make selection decisions. The farmer types differed in the form of collaboration and in the reactions to the hypothetical variation in subsidies. There were farmers with low dependency on subsidies, while most of them are highly dependent on subsidies. Therefore, any drastic change in the subsidy programme might have influence on the development of local breeds. The adaptation of these programme to the farmers’ heterogeneity might increase its efficacy, thus it would be interesting to explore ways of doing it. We conclude highlighting the need to have a variety of policies, which take into account the heterogeneity among the farmers. To finish we dealt with the genetic structure of livestock populations. Farmers’ decisions on the breeding animals and their progeny numbers shape the demographic and genetic structure of the breeds. Nowadays there is a renovated interest in studying the population structure since it can bias the prediction of genomic breeding values and genome wide association studies. We determined the genetic structure of ANI breed using two different methods, a graphical clustering algorithm (GCA) and a Bayesian clustering algorithm (STRUCTURE) were used. We paid particular attention to the influence that the presence of closely related individuals and the genetic differentiation of subpopulations may have on the inferences about the population structure. We first evaluated the performance of the algorithms in simulated populations. Then we inferred the genetic structure of the Spanish cattle breed ANI analysing a data set of 13343 animals (genotyped for 17 microsatellites) from 57 herds. ANI breed is an example of a population with complex relationships. We used the herdbook to study the gene flow, estimation among other things, the contribution of different herds to the genetic composition of the ANI breed. For the simulated scenarios, when FST among subpopulations was sufficiently high, both algorithms consistently inferred the correct structure regardless of the presence of related individuals. However, when the genetic differentiation among subpopulations was low, STRUCTURE identified the family based structure while GCA did not provide any consistent picture. The GCA was a fast and efficient method to infer genetic structure to determine the hidden core structure of a population with complex history and relationships. GCA could also be used to narrow down the number of clusters to be tested by STRUCTURE. Both, STRUCTURE and GCA describe a similar structure for the ANI breed suggesting that the results are robust. ANI population was found to have three genetically differentiated clusters that could correspond to three genetic lineages. These are directly related to the herds with a major contribution to the breed. In addition, ANI breed has also a large pool made of individuals with an admixture of origins. The genetic structure of ANI, assessed by molecular information, shows a stratification that corresponds to the demographic evolution of the breed. It will be of great importance to learn more about the composition of the pool and study how it is related to the existing genetic variability of the breed.

Towards the automatic generation of card games through Grammar-Guided Genetic Programming

We demonstrate generating complete and playable card games using evolutionary algorithms. Card games are represented in a previously devised card game description language, a context-free grammar. The syntax of this language allows us to use grammar-guided genetic programming. Candidate card games are evaluated through a cascading evaluation function, a multi-step process where games with undesired properties are progressively weeded out. Three representa- tive examples of generated games are analysed. We observed that these games are reasonably balanced and have skill ele- ments, they are not yet entertaining for human players. The particular shortcomings of the examples are discussed in re- gard to the generative process to be able to generate quality games

Grouping genetic operators for the delineation of functional areas based on spatial interaction

The delineation of functional economic areas, or market areas, is a problem of high practical relevance, since the delineation of functional sets such as economic areas in the US, Travel-to-Work Areas in the United Kingdom, and their counterparts in other OECD countries are the basis of many statistical operations and policy making decisions at local level. This is a combinatorial optimisation problem defined as the partition of a given set of indivisible spatial units (covering a territory) into regions characterised by being (a) self-contained and (b) cohesive, in terms of spatial interaction data (flows, relationships). Usually, each region must reach a minimum size and self-containment level, and must be continuous. Although these optimisation problems have been typically solved through greedy methods, a recent strand of the literature in this field has been concerned with the use of evolutionary algorithms with ad hoc operators. Although these algorithms have proved to be successful in improving the results of some of the more widely applied official procedures, they are so time consuming that cannot be applied directly to solve real-world problems. In this paper we propose a new set of group-based mutation operators, featuring general operations over disjoint groups, tailored to ensure that all the constraints are respected during the operation to improve efficiency. A comparative analysis of our results with those from previous approaches shows that the proposed algorithm systematically improves them in terms of both quality and processing time, something of crucial relevance since it allows dealing with most large, real-world problems in reasonable time.

Next-generation sequencing of iron-metabolism related genes in Portuguese patients with iron overload: novel pathogenic genetic variants

Objective: In Southern European countries up to one-third of the patients with hereditary hemochromatosis (HH) do not present the common HFE risk genotype. In order to investigate the molecular basis of these cases we have designed a gene panel for rapid and simultaneous analysis of 6 HH-related genes (HFE, TFR2, HJV, HAMP, SLC40A1 and FTL) by next-generation sequencing (NGS). Materials and Methods: Eighty-eight iron overload Portuguese patients, negative for the common HFE mutations, were analysed. A TruSeq Custom Amplicon kit (TSCA, by Illumina) was designed in order to generate 97 amplicons covering exons, intron/exon junctions and UTRs of the mentioned genes with a cumulative target sequence of 12115bp. Amplicons were sequenced in the MiSeq instrument (IIlumina) using 250bp paired-end reads. Sequences were aligned against human genome reference hg19 using alignment and variant caller algorithms in the MiSeq reporter software. Novel variants were validated by Sanger sequencing and their pathogenic significance were assessed by in silico studies. Results: We found a total of 55 different genetic variants. These include novel pathogenic missense and splicing variants (in HFE and TFR2), a very rare variant in IRE of FTL, a variant that originates a novel translation initiation codon in the HAMP gene, among others. Conclusion: The merging of TSCA methodology and NGS technology appears to be an appropriate tool for simultaneous and fast analysis of HH-related genes in a large number of samples. However, establishing the clinical relevance of NGS-detected variants for HH development remains a hard-working task, requiring further functional studies.

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence-and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN ( available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

Morphology of breast cancer as a means of triage of patients for BRCA1 genetic testing

Background: Women who have germline mutations in the BRCA1 gene are at substantially increased lifetime risk of developing breast and ovarian cancer but are otherwise normal. Currently. early age of onset of cancer and a strong family history are relied upon as the chief clues as to who should be offered genetic testing. Certain morphologic and immunohistochemical features are overrepresented in BRCA1-associated breast cancers but these differences have not been incorporated into the current selection criteria for genetic testing. Design: Each of the 4 pathologists studied 30 known cases of BRCA1- and BRCA2-associated breast cancer from kConFab families. After reviewing the literature, we agreed on a semiquantitative scoring system for estimating the chances of presence of an underlying BRCA1 mutation, based on the number of the reported prototypic features present. After a time lag of 12 months, we each examined a series of 62 deidentified cases of breast cancer, inclusive of cases of BRCA1-associated breast cancer and controls. The controls included cases of BRCA2-associated breast cancer and sporadic cases. Results: Our predictions had a sensitivity of 92%, specificity of 86%, positive predictive value of 61%, and negative predictive value of 98%. For comparison the sensitivity of currently used selection criteria are in the range of 25% to 30%. Conclusion: The inclusion of morphologic and immunohistochemical features of breast cancers in algorithms to predict the likelihood of presence of germline mutations in the BRCA1 gene improves the accuracy of the selection process.

A class of self-stabilizing MCA learning algorithms

In this letter, we propose a class of self-stabilizing learning algorithms for minor component analysis (MCA), which includes a few well-known MCA learning algorithms. Self-stabilizing means that the sign of the weight vector length change is independent of the presented input vector. For these algorithms, rigorous global convergence proof is given and the convergence rate is also discussed. By combining the positive properties of these algorithms, a new learning algorithm is proposed which can improve the performance. Simulations are employed to confirm our theoretical results.

Statistical racing techniques for improved empirical evaluation of evolutionary algorithms

In empirical studies of Evolutionary Algorithms, it is usually desirable to evaluate and compare algorithms using as many different parameter settings and test problems as possible, in border to have a clear and detailed picture of their performance. Unfortunately, the total number of experiments required may be very large, which often makes such research work computationally prohibitive. In this paper, the application of a statistical method called racing is proposed as a general-purpose tool to reduce the computational requirements of large-scale experimental studies in evolutionary algorithms. Experimental results are presented that show that racing typically requires only a small fraction of the cost of an exhaustive experimental study.

On building a principled framework for evaluating and testing evolutionary algorithms: A continuous landscape generator

In this paper, we address some issue related to evaluating and testing evolutionary algorithms. A landscape generator based on Gaussian functions is proposed for generating a variety of continuous landscapes as fitness functions. Through some initial experiments, we illustrate the usefulness of this landscape generator in testing evolutionary algorithms.

A genetic algorithm for the generalised transportation problem

The generalised transportation problem (GTP) is an extension of the linear Hitchcock transportation problem. However, it does not have the unimodularity property, which means the linear programming solution (like the simplex method) cannot guarantee to be integer. This is a major difference between the GTP and the Hitchcock transportation problem. Although some special algorithms, such as the generalised stepping-stone method, have been developed, but they are based on the linear programming model and the integer solution requirement of the GTP is relaxed. This paper proposes a genetic algorithm (GA) to solve the GTP and a numerical example is presented to show the algorithm and its efficiency.

An application of evolutionary algorithms for WAG optimisation in the Norne Field

Water-alternating-gas (WAG) is an enhanced oil recovery method combining the improved macroscopic sweep of water flooding with the improved microscopic displacement of gas injection. The optimal design of the WAG parameters is usually based on numerical reservoir simulation via trial and error, limited by the reservoir engineer’s availability. Employing optimisation techniques can guide the simulation runs and reduce the number of function evaluations. In this study, robust evolutionary algorithms are utilized to optimise hydrocarbon WAG performance in the E-segment of the Norne field. The first objective function is selected to be the net present value (NPV) and two global semi-random search strategies, a genetic algorithm (GA) and particle swarm optimisation (PSO) are tested on different case studies with different numbers of controlling variables which are sampled from the set of water and gas injection rates, bottom-hole pressures of the oil production wells, cycle ratio, cycle time, the composition of the injected hydrocarbon gas (miscible/immiscible WAG) and the total WAG period. In progressive experiments, the number of decision-making variables is increased, increasing the problem complexity while potentially improving the efficacy of the WAG process. The second objective function is selected to be the incremental recovery factor (IRF) within a fixed total WAG simulation time and it is optimised using the same optimisation algorithms. The results from the two optimisation techniques are analyzed and their performance, convergence speed and the quality of the optimal solutions found by the algorithms in multiple trials are compared for each experiment. The distinctions between the optimal WAG parameters resulting from NPV and oil recovery optimisation are also examined. This is the first known work optimising over this complete set of WAG variables. The first use of PSO to optimise a WAG project at the field scale is also illustrated. Compared to the reference cases, the best overall values of the objective functions found by GA and PSO were 13.8% and 14.2% higher, respectively, if NPV is optimised over all the above variables, and 14.2% and 16.2% higher, respectively, if IRF is optimised.

Interpreting Human Genetic Variation through Genomics and In Vivo Models

Improvements in genomic technology, both in the increased speed and reduced cost of sequencing, have expanded the appreciation of the abundance of human genetic variation. However the sheer amount of variation, as well as the varying type and genomic content of variation, poses a challenge in understanding the clinical consequence of a single mutation. This work uses several methodologies to interpret the observed variation in the human genome, and presents novel strategies for the prediction of allele pathogenicity.

Using the zebrafish model system as an in vivo assay of allele function, we identified a novel driver of Bardet-Biedl Syndrome (BBS) in CEP76. A combination of targeted sequencing of 785 cilia-associated genes in a cohort of BBS patients and subsequent in vivo functional assays recapitulating the human phenotype gave strong evidence for the role of CEP76 mutations in the pathology of an affected family. This portion of the work demonstrated the necessity of functional testing in validating disease-associated mutations, and added to the catalogue of known BBS disease genes.

Further study into the role of copy-number variations (CNVs) in a cohort of BBS patients showed the significant contribution of CNVs to disease pathology. Using high-density array comparative genomic hybridization (aCGH) we were able to identify pathogenic CNVs as small as several hundred bp. Dissection of constituent gene and in vivo experiments investigating epistatic interactions between affected genes allowed for an appreciation of several paradigms by which CNVs can contribute to disease. This study revealed that the contribution of CNVs to disease in BBS patients is much higher than previously expected, and demonstrated the necessity of consideration of CNV contribution in future (and retrospective) investigations of human genetic disease.

Finally, we used a combination of comparative genomics and in vivo complementation assays to identify second-site compensatory modification of pathogenic alleles. These pathogenic alleles, which are found compensated in other species (termed compensated pathogenic deviations [CPDs]), represent a significant fraction (from 3 – 10%) of human disease-associated alleles. In silico pathogenicity prediction algorithms, a valuable method of allele prioritization, often misrepresent these alleles as benign, leading to omission of possibly informative variants in studies of human genetic disease. We created a mathematical model that was able to predict CPDs and putative compensatory sites, and functionally showed in vivo that second-site mutation can mitigate the pathogenicity of disease alleles. Additionally, we made publically available an in silico module for the prediction of CPDs and modifier sites.

These studies have advanced the ability to interpret the pathogenicity of multiple types of human variation, as well as made available tools for others to do so as well.

Forward-in-Time, Spatially Explicit Modeling Software to Simulate Genetic Lineages Under Selection

SELECTOR is a software package for studying the evolution of multiallelic genes under balancing or positive selection while simulating complex evolutionary scenarios that integrate demographic growth and migration in a spatially explicit population framework. Parameters can be varied both in space and time to account for geographical, environmental, and cultural heterogeneity. SELECTOR can be used within an approximate Bayesian computation estimation framework. We first describe the principles of SELECTOR and validate the algorithms by comparing its outputs for simple models with theoretical expectations. Then, we show how it can be used to investigate genetic differentiation of loci under balancing selection in interconnected demes with spatially heterogeneous gene flow. We identify situations in which balancing selection reduces genetic differentiation between population groups compared with neutrality and explain conflicting outcomes observed for human leukocyte antigen loci. These results and three previously published applications demonstrate that SELECTOR is efficient and robust for building insight into human settlement history and evolution.

Automatically Evolving Rotation-invariant Texture Image Descriptors by Genetic Programming

In computer vision, training a model that performs classification effectively is highly dependent on the extracted features, and the number of training instances. Conventionally, feature detection and extraction are performed by a domain-expert who, in many cases, is expensive to employ and hard to find. Therefore, image descriptors have emerged to automate these tasks. However, designing an image descriptor still requires domain-expert intervention. Moreover, the majority of machine learning algorithms require a large number of training examples to perform well. However, labelled data is not always available or easy to acquire, and dealing with a large dataset can dramatically slow down the training process. In this paper, we propose a novel Genetic Programming based method that automatically synthesises a descriptor using only two training instances per class. The proposed method combines arithmetic operators to evolve a model that takes an image and generates a feature vector. The performance of the proposed method is assessed using six datasets for texture classification with different degrees of rotation, and is compared with seven domain-expert designed descriptors. The results show that the proposed method is robust to rotation, and has significantly outperformed, or achieved a comparable performance to, the baseline methods.