Dominance and the maintenance of polymorphism in multiallelic migration-selection models with two demes

The maintenance of genetic variation in a spatially heterogeneous environment has been one of the main research themes in theoretical population genetics. Despite considerable progress in understanding the consequences of spatially structured environments on genetic variation, many problems remain unsolved. One of them concerns the relationship between the number of demes, the degree of dominance, and the maximum number of alleles that can be maintained by selection in a subdivided population. In this work, we study the potential of maintaining genetic variation in a two-deme model with deme-independent degree of intermediate dominance, which includes absence of G x E interaction as a special case. We present a thorough numerical analysis of a two-deme three-allele model, which allows us to identify dominance and selection patterns that harbor the potential for stable triallelic equilibria. The information gained by this approach is then used to construct an example in which existence and asymptotic stability of a fully polymorphic equilibrium can be proved analytically. Noteworthy, in this example the parameter range in which three alleles can coexist is maximized for intermediate migration rates. Our results can be interpreted in a specialist-generalist context and (among others) show when two specialists can coexist with a generalist in two demes if the degree of dominance is deme independent and intermediate. The dominance relation between the generalist allele and the specialist alleles play a decisive role. We also discuss linear selection on a quantitative trait and show that G x E interaction is not necessary for the maintenance of more than two alleles in two demes.

Functional correction in mouse models of muscular dystrophy using exon-skipping tricyclo-DNA oligomers

Antisense oligonucleotides (AONs) hold promise for therapeutic correction of many genetic diseases via exon skipping, and the first AON-based drugs have entered clinical trials for neuromuscular disorders1, 2. However, despite advances in AON chemistry and design, systemic use of AONs is limited because of poor tissue uptake, and recent clinical reports confirm that sufficient therapeutic efficacy has not yet been achieved. Here we present a new class of AONs made of tricyclo-DNA (tcDNA), which displays unique pharmacological properties and unprecedented uptake by many tissues after systemic administration. We demonstrate these properties in two mouse models of Duchenne muscular dystrophy (DMD), a neurogenetic disease typically caused by frame-shifting deletions or nonsense mutations in the gene encoding dystrophin3, 4 and characterized by progressive muscle weakness, cardiomyopathy, respiratory failure5 and neurocognitive impairment6. Although current naked AONs do not enter the heart or cross the blood-brain barrier to any substantial extent, we show that systemic delivery of tcDNA-AONs promotes a high degree of rescue of dystrophin expression in skeletal muscles, the heart and, to a lesser extent, the brain. Our results demonstrate for the first time a physiological improvement of cardio-respiratory functions and a correction of behavioral features in DMD model mice. This makes tcDNA-AON chemistry particularly attractive as a potential future therapy for patients with DMD and other neuromuscular disorders or with other diseases that are eligible for exon-skipping approaches requiring whole-body treatment.

Genetic consequences of habitat fragmentation during a range expansion

We investigate the effect of habitat fragmentation on the genetic diversity of a species experiencing a range expansion. These two evolutionary processes have not been studied yet, at the same time, owing to the difficulties of deriving analytic results for non-equilibrium models. Here we provide a description of their interaction by using extensive spatial and temporal coalescent simulations and we suggest guidelines for a proper genetic sampling to detect fragmentation. To model habitat fragmentation, we simulated a two-dimensional lattice of demes partitioned into groups (patches) by adding barriers to dispersal. After letting a population expand on this grid, we sampled lineages from the lattice at several scales and studied their coalescent history. We find that in order to detect fragmentation, one needs to extensively sample at a local level rather than at a landscape level. This is because the gene genealogy of a scattered sample is less sensitive to the presence of genetic barriers. Considering the effect of temporal changes of fragmentation intensities, we find that at least 10, but often >100, generations are needed to affect local genetic diversity and population structure. This result explains why recent habitat fragmentation does not always lead to detectable signatures in the genetic structure of populations. Finally, as expected, long-distance dispersal increases local genetic diversity and decreases levels of population differentiation, efficiently counteracting the effects of fragmentation.

Models of hybridization during range expansions and their application to recent human evolution

Several lines of genetic, archeological and paleontological evidence suggest that anatomically modern humans (Homo sapiens) colonized the world in the last 60,000 years by a series of migrations originating from Africa (e.g. Liu et al., 2006; Handley et al., 2007; Prugnolle, Manica, and Balloux, 2005; Ramachandran et al. 2005; Li et al. 2008; Deshpande et al. 2009; Mellars, 2006a, b; Lahr and Foley, 1998; Gravel et al., 2011; Rasmussen et al., 2011). With the progress of ancient DNA analysis, it has been shown that archaic humans hybridized with modern humans outside Africa. Recent direct analyses of fossil nuclear DNA have revealed that 1–4 percent of the genome of Eurasian has been likely introgressed by Neanderthal genes (Green et al., 2010; Reich et al., 2010; Vernot and Akey, 2014; Sankararaman et al., 2014; Prufer et al., 2014; Wall et al., 2013), with Papua New Guineans and Australians showing even larger levels of admixture with Denisovans (Reich et al., 2010; Skoglund and Jakobsson, 2011; Reich et al., 2011; Rasmussen et al., 2011). It thus appears that the past history of our species has been more complex than previously anticipated (Alves et al., 2012), and that modern humans hybridized several times with local hominins during their expansion out of Africa, but the exact mode, time and location of these hybridizations remain to be clarifi ed (Ibid.; Wall et al., 2013). In this context, we review here a general model of admixture during range expansion, which lead to some predictions about expected patterns of introgression that are relevant to modern human evolution.

Long distance dispersal shaped patterns of human genetic diversity in Eurasia

Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account, or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the Last Glacial Maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite dataset genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion, or to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM-contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations.

Expansion load: recessive mutations and the role of standing genetic variation

Expanding populations incur a mutation burden – the so-called expansion load. Previous studies of expansion load have focused on codominant mutations. An important consequence of this assumption is that expansion load stems exclusively from the accumulation of new mutations occurring in individuals living at the wave front. Using individual-based simulations, we study here the dynamics of standing genetic variation at the front of expansions, and its consequences on mean fitness if mutations are recessive. We find that deleterious genetic diversity is quickly lost at the front of the expansion, but the loss of deleterious mutations at some loci is compensated by an increase of their frequencies at other loci. The frequency of deleterious homozygotes therefore increases along the expansion axis, whereas the average number of deleterious mutations per individual remains nearly constant across the species range. This reveals two important differences to codominant models: (i) mean fitness at the front of the expansion drops much faster if mutations are recessive, and (ii) mutation load can increase during the expansion even if the total number of deleterious mutations per individual remains constant. We use our model to make predictions about the shape of the site frequency spectrum at the front of range expansion, and about correlations between heterozygosity and fitness in different parts of the species range. Importantly, these predictions provide opportunities to empirically validate our theoretical results. We discuss our findings in the light of recent results on the distribution of deleterious genetic variation across human populations and link them to empirical results on the correlation of heterozygosity and fitness found in many natural range expansions.

BIOCHEMICAL CHARACTERIZATION AND GENETIC MAPPING OF WILD TYPE AND MUTANT GLYCERALDEHYDE-3-PHOSPHATE DEHYDROGENASE ALLELES IN CHINESE HAMSTER OVARY CELLS

A UV-induced mutation of the enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPD) was characterized in the CHO clone A24. The asymmetric 4-banded zymogram and an in vitro GAPD activity equal to that of wild type cells were not consistent with models of a mutant heterozygote producing equal amounts of wild type and either catalytically active or inactive mutant subunits that interacted randomly. Cumulative evidence indicated that the site of the mutation was the GAPD structural locus expressed in CHO wild type cells, and that the mutant allele coded for a subunit that differed from the wild type subunit in stability and kinetics. The evidence included the appearance of a fifth band, the putative mutant homotetramer, after addition of the substrate glyceraldehyde-3-phosphate (GAP) to the gel matrix; dilution experiments indicating stability differences between the subunits; experiments with subsaturating levels of GAP indicating differences in affinity for the substrate; GAPD zymograms of A24 x mouse hybrids that were consistent with the presence of two distinct A24 subunits; independent segregation of A24 wild type and mutant electrophoretic bands from the hybrids, which was inconsistent with models of mutation of a locus involved in posttranslational modification; the mapping of both wild type and mutant forms of GAPD to chromosome 8; and the failure to detect any evidence of posttranslational modification (of other A24 isozymes, or through mixing of homogenates of A24 and mouse).^ The extent of skewing of the zymogram toward the wild type band, and the unreduced in vitro activity were inconsistent with models based solely on differences in activity of the two subunits. Comparison of wild type homotetramer bands in wild type cells and A24 suggested the latter had a preponderance of wild type subunits over mutant subunits, and had more GAPD tetramers than did CHO controls.^ Two CHO linkages, GAPD-triose phosphate isomerase, and acid phosphatase 2-adenosine deaminase were reported provisionally, and several others were confirmed. ^

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. ^

Molecular genetic analyses of extracellular signaling pathways during murine retinal development

Extracellular signaling pathways initiated by secreted proteins are important in the co-ordination of tissue interactions in multi-cellular organisms, particularly during embryonic development. These signaling cascades direct diverse cellular events, including proliferation, differentiation and migration, in both autocrine and paracrine modes. In adult animals, abnormal function of these proteins often results in degenerative and tumourigenic syndromes. In this study, I have focused on elucidating the role of Bone Morphogenetic Protein (Bmp) signal transduction during neuronal specification and differentiation in the vertebrate embryo, using the mouse retina as a model. Using tissue-specific conditional knock-out approaches, the consequences of genetic loss-of-function of this signaling pathway on retinal physiology were examined. Mutant mice lacking Bmp type I receptor function displayed a range of retinal phenotypes, each of which appeared to be regulated at a different threshold of Bmp receptor activity. Novel essential functions for Bmp signaling were uncovered for retinal neurogenesis, cell survival, and axonal pathfinding at the optic disc. Further, BmprIa and BmprIa exhibited genetic interactions suggestive of functional redundancy. To further characterize the underlying molecular bases for the pleiotropic effects of Bmp receptors, retina-specific loss-of-function mutants of the obligate Bmp-activated transcriptional mediator Smad4 were generated. A comparison of the retina-specific Smad4 mutant phenotypes with those of the Bmp receptor mutant retina revealed that only a subset of retinal phenotypes, namely optic disc axon pathfinding and axial patterning were common for both classes of mutant animals. Thus, these results suggest that, contrary to the classic scheme of Bmp signal transduction, Smad4-independent pathways may be operative downstream of the type I receptors. Indeed, such alternative intracellular signaling cascades may constitute a molecular basis for the multiple cellular responses elicited by Bmp signaling. Finally, I tested whether the potential Bmp pathway targets, the extracellular ligands Fgf9 and Fgf15, mediate essential cellular processes in the retina. The analyses of Fgf9 −/−; Fgf15−/− mutant mice posit a novel shared role for these genes in intra-retinal axon pathfinding. Collectively, these studies have elucidated part of the molecular machinery directing mammalian neuro-retinal development, and provided useful in vivo models to study visual function. ^

DNA incisions stimulate genetic instability of triplet repeat sequences related to human hereditary neurological diseases

The molecular mechanisms responsible for the expansion and deletion of trinucleotide repeat sequences (TRS) are the focus of our studies. Several hereditary neurological diseases including Huntington's disease, myotonic dystrophy, and fragile X syndrome are associated with the instability of TRS. Using the well defined and controllable model system of Escherichia coli, the influences of three types of DNA incisions on genetic instability of CTG•CAG repeats were studied: DNA double-strand breaks (DSB), single-strand nicks, and single-strand gaps. The DNA incisions were generated in pUC19 derivatives by in vitro cleavage with restriction endonucleases. The cleaved DNA was then transformed into E. coli parental and mutant strains. Double-strand breaks induced deletions throughout the TRS region in an orientation dependent manner relative to the origin of replication. The extent of instability was enhanced by the repeat length and sequence (CTG•CAG vs. CGG•CCG). Mutations in recA and recBC increased deletions, mutations in recF stabilized the TRS, whereas mutations in ruvA had no effect. DSB were repaired by intramolecular recombination, versus an intermolecular gene conversion or crossover mechanism. 30 nt gaps formed a distinct 30 nt deletion product, whereas single strand nicks and gaps of 15 nts did not induce expansions or deletions. Formation of this deletion product required the CTG•CAG repeats to be present in the single-stranded region and was stimulated by E. coli DNA ligase, but was not dependent upon the RecFOR pathway. Models are presented to explain the DSB induced instabilities and formation of the 30 nucleotide deletion product. In addition to the in vitro creation of DSBs, several attempts to generate this incision in vivo with the use of EcoR I restriction modification systems were conducted. ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network

An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included.

Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Aerodynamic optimization of the ICE2 high-speed train nose using a genetic algorithm and metamodels

An aerodynamic optimization of the ICE 2 high-speed train nose in term of front wind action sensitivity is carried out in this paper. The nose is parametrically defined by Be?zier Curves, and a three-dimensional representation of the nose is obtained using thirty one design variables. This implies a more complete parametrization, allowing the representation of a real model. In order to perform this study a genetic algorithm (GA) is used. Using a GA involves a large number of evaluations before finding such optimal. Hence it is proposed the use of metamodels or surrogate models to replace Navier-Stokes solver and speed up the optimization process. Adaptive sampling is considered to optimize surrogate model fitting and minimize computational cost when dealing with a very large number of design parameters. The paper introduces the feasi- bility of using GA in combination with metamodels for real high-speed train geometry optimization.

Improving the management of water and nitrogen resources in cropping systems by using simulation models

Los modelos de simulación de cultivos permiten analizar varias combinaciones de laboreo-rotación y explorar escenarios de manejo. El modelo DSSAT fue evaluado bajo condiciones de secano en un experimento de campo de 16 años en la semiárida España central. Se evaluó el efecto del sistema de laboreo y las rotaciones basadas en cereales de invierno, en el rendimiento del cultivo y la calidad del suelo. Los modelos CERES y CROPGRO se utilizaron para simular el crecimiento y rendimiento del cultivo, mientras que el modelo DSSAT CENTURY se utilizó en las simulaciones de SOC y SN. Tanto las observaciones de campo como las simulaciones con CERES-Barley, mostraron que el rendimiento en grano de la cebada era mas bajo para el cereal continuo (BB) que para las rotaciones de veza (VB) y barbecho (FB) en ambos sistemas de laboreo. El modelo predijo más nitrógeno disponible en el laboreo convencional (CT) que en el no laboreo (NT) conduciendo a un mayor rendimiento en el CT. El SOC y el SN en la capa superficial del suelo, fueron mayores en NT que en CT, y disminuyeron con la profundidad en los valores tanto observados como simulados. Las mejores combinaciones para las condiciones de secano estudiadas fueron CT-VB y CT-FB, pero CT presentó menor contenido en SN y SOC que NT. El efecto beneficioso del NT en SOC y SN bajo condiciones Mediterráneas semiáridas puede ser identificado por observaciones de campo y por simulaciones de modelos de cultivos. La simulación del balance de agua en sistemas de cultivo es una herramienta útil para estudiar como el agua puede ser utilizado eficientemente. La comparación del balance de agua de DSSAT , con una simple aproximación “tipping bucket”, con el modelo WAVE más mecanicista, el cual integra la ecuación de Richard , es un potente método para valorar el funcionamiento del modelo. Los parámetros de suelo fueron calibrados usando el método de optimización global Simulated Annealing (SA). Un lisímetro continuo de pesada en suelo desnudo suministró los valores observados de drenaje y evapotranspiración (ET) mientras que el contenido de agua en el suelo (SW) fue suministrado por sensores de capacitancia. Ambos modelos funcionaron bien después de la optimización de los parámetros de suelo con SA, simulando el balance de agua en el suelo para el período de calibración. Para el período de validación, los modelos optimizados predijeron bien el contenido de agua en el suelo y la evaporación del suelo a lo largo del tiempo. Sin embargo, el drenaje fue predicho mejor con WAVE que con DSSAT, el cual presentó mayores errores en los valores acumulados. Esto podría ser debido a la naturaleza mecanicista de WAVE frente a la naturaleza más funcional de DSSAT. Los buenos resultados de WAVE indican que, después de la calibración, este puede ser utilizado como "benchmark" para otros modelos para periodos en los que no haya medidas de campo del drenaje. El funcionamiento de DSSAT-CENTURY en la simulación de SOC y N depende fuertemente del proceso de inicialización. Se propuso como método alternativo (Met.2) la inicialización de las fracciones de SOC a partir de medidas de mineralización aparente del suelo (Napmin). El Met.2 se comparó con el método de inicialización de Basso et al. (2011) (Met.1), aplicando ambos métodos a un experimento de campo de 4 años en un área en regadío de España central. Nmin y Napmin fueron sobreestimados con el Met.1, ya que la fracción estable obtenida (SOC3) en las capas superficiales del suelo fue más baja que con Met.2. El N lixiviado simulado fue similar en los dos métodos, con buenos resultados en los tratamientos de barbecho y cebada. El Met.1 subestimó el SOC en la capa superficial del suelo cuando se comparó con una serie observada de 12 años. El crecimiento y rendimiento del cultivo fueron adecuadamente simulados con ambos métodos, pero el N en la parte aérea de la planta y en el grano fueron sobreestimados con el Met.1. Los resultados variaron significativamente con las fracciones iniciales de SOC, resaltando la importancia del método de inicialización. El Met.2 ofrece una alternativa para la inicialización del modelo CENTURY, mejorando la simulación de procesos de N en el suelo. La continua emergencia de nuevas variedades de híbridos modernos de maíz limita la aplicación de modelos de simulación de cultivos, ya que estos nuevos híbridos necesitan ser calibrados en el campo para ser adecuados para su uso en los modelos. El desarrollo de relaciones basadas en la duración del ciclo, simplificaría los requerimientos de calibración facilitando la rápida incorporación de nuevos cultivares en DSSAT. Seis híbridos de maiz (FAO 300 hasta FAO 700) fueron cultivados en un experimento de campo de dos años en un área semiárida de regadío en España central. Los coeficientes genéticos fueron obtenidos secuencialmente, comenzando con los parámetros de desarrollo fenológico (P1, P2, P5 and PHINT), seguido de los parámetros de crecimiento del cultivo (G2 and G3). Se continuó el procedimiento hasta que la salida de las simulaciones estuvo en concordancia con las observaciones fenológicas de campo. Después de la calibración, los parámetros simulados se ajustaron bien a los parámetros observados, con bajos RMSE en todos los casos. Los P1 y P5 calibrados, incrementaron con la duración del ciclo. P1 fue una función lineal del tiempo térmico (TT) desde emergencia hasta floración y P5 estuvo linealmente relacionada con el TT desde floración a madurez. No hubo diferencias significativas en PHINT entre híbridos de FAO-500 a 700 , ya que tuvieron un número de hojas similar. Como los coeficientes fenológicos estuvieron directamente relacionados con la duración del ciclo, sería posible desarrollar rangos y correlaciones que permitan estimar dichos coeficientes a partir de la clasificación del ciclo. ABSTRACT Crop simulation models allow analyzing various tillage-rotation combinations and exploring management scenarios. DSSAT model was tested under rainfed conditions in a 16-year field experiment in semiarid central Spain. The effect of tillage system and winter cereal-based rotations on the crop yield and soil quality was evaluated. The CERES and CROPGRO models were used to simulate crop growth and yield, while the DSSAT CENTURY was used in the SOC and SN simulations. Both field observations and CERES-Barley simulations, showed that barley grain yield was lower for continuous cereal (BB) than for vetch (VB) and fallow (FB) rotations for both tillage systems. The model predicted higher nitrogen availability in the conventional tillage (CT) than in the no tillage (NT) leading to a higher yield in the CT. The SOC and SN in the top layer, were higher in NT than in CT, and decreased with depth in both simulated and observed values. The best combinations for the dry land conditions studied were CT-VB and CT-FB, but CT presented lower SN and SOC content than NT. The beneficial effect of NT on SOC and SN under semiarid Mediterranean conditions can be identified by field observations and by crop model simulations. The simulation of the water balance in cropping systems is a useful tool to study how water can be used efficiently. The comparison of DSSAT soil water balance, with a simpler “tipping bucket” approach, with the more mechanistic WAVE model, which integrates Richard’s equation, is a powerful method to assess model performance. The soil parameters were calibrated by using the Simulated Annealing (SA) global optimizing method. A continuous weighing lysimeter in a bare fallow provided the observed values of drainage and evapotranspiration (ET) while soil water content (SW) was supplied by capacitance sensors. Both models performed well after optimizing soil parameters with SA, simulating the soil water balance components for the calibrated period. For the validation period, the optimized models predicted well soil water content and soil evaporation over time. However, drainage was predicted better by WAVE than by DSSAT, which presented larger errors in the cumulative values. That could be due to the mechanistic nature of WAVE against the more functional nature of DSSAT. The good results from WAVE indicate that, after calibration, it could be used as benchmark for other models for periods when no drainage field measurements are available. The performance of DSSAT-CENTURY when simulating SOC and N strongly depends on the initialization process. Initialization of the SOC pools from apparent soil N mineralization (Napmin) measurements was proposed as alternative method (Met.2). Method 2 was compared to the Basso et al. (2011) initialization method (Met.1), by applying both methods to a 4-year field experiment in a irrigated area of central Spain. Nmin and Napmin were overestimated by Met.1, since the obtained stable pool (SOC3) in the upper layers was lower than from Met.2. Simulated N leaching was similar for both methods, with good results in fallow and barley treatments. Method 1 underestimated topsoil SOC when compared with a 12-year observed serial. Crop growth and yield were properly simulated by both methods, but N in shoots and grain were overestimated by Met.1. Results varied significantly with the initial SOC pools, highlighting the importance of the initialization procedure. Method 2 offers an alternative to initialize the CENTURY model, enhancing the simulation of soil N processes. The continuous emergence of new varieties of modern maize hybrids limits the application of crop simulation models, since these new hybrids should be calibrated in the field to be suitable for model use. The development of relationships based on the cycle duration, would simplify the calibration requirements facilitating the rapid incorporation of new cultivars into DSSAT. Six maize hybrids (FAO 300 through FAO 700) were grown in a 2-year field experiment in a semiarid irrigated area of central Spain. Genetic coefficients were obtained sequentially, starting with the phenological development parameters (P1, P2, P5 and PHINT), followed by the crop growth parameters (G2 and G3). The procedure was continued until the simulated outputs were in good agreement with the field phenological observations. After calibration, simulated parameters matched observed parameters well, with low RMSE in most cases. The calibrated P1 and P5 increased with the duration of the cycle. P1 was a linear function of the thermal time (TT) from emergence to silking and P5 was linearly related with the TT from silking to maturity . There were no significant differences in PHINT between hybrids from FAO-500 to 700 , as they had similar leaf number. Since phenological coefficients were directly related with the cycle duration, it would be possible to develop ranges and correlations which allow to estimate such coefficients from the cycle classification.