A framework for the study of genetic variation in migratory behaviour

Evolutionary change results from selection acting on genetic variation. For migration to be successful, many different aspects of an animal's physiology and behaviour need to function in a co-coordinated way. Changes in one migratory trait are therefore likely to be accompanied by changes in other migratory and life-history traits. At present, we have some knowledge of the pressures that operate at the various stages of migration, but we know very little about the extent of genetic variation in various aspects of the migratory syndrome. As a consequence, our ability to predict which species is capable of what kind of evolutionary change, and at which rate, is limited. Here, we review how our evolutionary understanding of migration may benefit from taking a quantitative-genetic approach and present a framework for studying the causes of phenotypic variation. We review past research, that has mainly studied single migratory traits in captive birds, and discuss how this work could be extended to study genetic variation in the wild and to account for genetic correlations and correlated selection. In the future, reaction-norm approaches may become very important, as they allow the study of genetic and environmental effects on phenotypic expression within a single framework, as well as of their interactions. We advocate making more use of repeated measurements on single individuals to study the causes of among-individual variation in the wild, as they are easier to obtain than data on relatives and can provide valuable information for identifying and selecting traits. This approach will be particularly informative if it involves systematic testing of individuals under different environmental conditions. We propose extending this research agenda by using optimality models to predict levels of variation and covariation among traits and constraints. This may help us to select traits in which we might expect genetic variation, and to identify the most informative environmental axes. We also recommend an expansion of the passerine model, as this model does not apply to birds, like geese, where cultural transmission of spatio-temporal information is an important determinant of migration patterns and their variation.

Challenging the dogma: the hidden layer of non-protein-coding RNAs in complex organisms

The central dogma of biology holds that genetic information normally flows from DNA to RNA to protein. As a consequence it has been generally assumed that genes generally code for proteins, and that proteins fulfil not only most structural and catalytic but also most regulatory functions, in all cells, from microbes to mammals. However, the latter may not be the case in complex organisms. A number of startling observations about the extent of non-protein-coding RNA (ncRNA) transcription in the higher eukaryotes and the range of genetic and epigenetic phenomena that are RNA-directed suggests that the traditional view of the structure of genetic regulatory systems in animals and plants may be incorrect. ncRNA dominates the genomic output of the higher organisms and has been shown to control chromosome architecture, mRNA turnover and the developmental timing of protein expression, and may also regulate transcription and alternative splicing. This paper re-examines the available evidence and suggests a new framework for considering and understanding the genomic programming of biological complexity, autopoletic development and phenotypic variation. BioEssays 25:930-939,2003. (C) 2003 Wiley Periodicals, Inc.

A genetic linkage map in autotetraploid lucerne adapted to northern Australia, and use of the map to identify DNA markers linked to resistance to Phytophthora medicaginis

Phytophthora root rot, caused by Phytophthora medicaginis, is a major limitation to lucerne ( Medicago sativa L.) production in Australia and North America. Quantitative trait loci (QTLs) involved in resistance to P. medicaginis were identified in a lucerne backcross population of 120 individuals. A genetic linkage map was constructed for tetraploid lucerne using 50 RAPD ( randomly amplified polymorphic DNA), 104 AFLP (amplified fragment length polymorphism) markers, and one SSR ( simple sequence repeat or microsatellite) marker, which originated from the resistant parent (W116); 13 markers remain unlinked. The linkage map contains 18 linkage groups covering 2136.5 cM, with an average distance of 15.0 cM between markers. Four of the linkage groups contained only either 2 or 3 markers. Using duplex markers and repulsion phase linkages the map condensed to 7 homology groups and 2 unassigned linkage groups. Three regions located on linkage groups 2, 14, and 18, were identified as associated with root reaction and the QTLs explained 6 - 15% of the phenotypic variation. The research also indicates that different resistance QTLs are involved in conferring resistance in different organs. Two QTLs were identified as associated with disease resistance expressed after inoculation of detached leaves. The marker, W11-2 on group 18, identified as associated with root reaction, contributed 7% of the phenotypic variation in leaf response in our population. This marker appears to be linked to a QTL encoding a resistance factor contributing to both root and leaf reaction. One other QTL, not identified as associated with root reaction, was positioned on group 1 and contributed to 6% of the variation. This genetic linkage map provides an entry point for future molecular-based improvement of lucerne in Australia, and markers linked to the QTLs we have reported should be useful for marker-assisted selection for partial resistance to P. medicaginis in lucerne.

Areal specialization of pyramidal cell structure in the visual cortex of the tree shrew: a new twist revealed in the evolution of cortical circuitry

Cortical pyramidal cells, while having a characteristic morphology, show marked phenotypic variation in primates. Differences have been reported in their size, branching structure and spine density between cortical areas. In particular, there is a systematic increase in the complexity of the structure of pyramidal cells with anterior progression through occipito-temporal cortical visual areas. These differences reflect area-specific specializations in cortical circuitry, which are believed to be important for visual processing. However, it remains unknown as to whether these regional specializations in pyramidal cell structure are restricted to primates. Here we investigated pyramidal cell structure in the visual cortex of the tree shrew, including the primary (V1), second (V2) and temporal dorsal (TD) areas. As in primates, there was a trend for more complex branching structure with anterior progression through visual areas in the tree shrew. However, contrary to the trend reported in primates, cells in the tree shrew tended to become smaller with anterior progression through V1, V2 and TD. In addition, pyramidal cells in V1 of the tree shrew are more than twice as spinous as those in primates. These data suggest that variables that shape the structure of adult cortical pyramidal cells differ among species.

Small regulatory RNAs in mammals

Mammalian cells harbor numerous small non-protein-coding RNAs, including small nucleolar RNAs (snoRNAs), microRNAs (miRNAs), short interfering RNAs (siRNAs) and small double-stranded RNAs, which regulate gene expression at many levels including chromatin architecture, RNA editing, RNA stability, translation, and quite possibly transcription and splicing. These RNAs are processed by multistep pathways from the introns and exons of longer primary transcripts, including protein-coding transcripts. Most show distinctive temporal- and tissue-specific expression patterns in different tissues, including embryonal stem cells and the brain, and some are imprinted. Small RNAs control a wide range of developmental and physiological pathways in animals, including hematopoietic differentiation, adipocyte differentiation and insulin secretion in mammals, and have been shown to be perturbed in cancer and other diseases. The extent of transcription of non-coding sequences and the abundance of small RNAs suggests the existence of an extensive regulatory network on the basis of RNA signaling which may underpin the development and much of the phenotypic variation in mammals and other complex organisms and which may have different genetic signatures from sequences encoding proteins.

Congruence in QTL for adventitious rooting in Pinus elliottii X Pinus caribaea hybrids resolves between and within-species effects

Targeting between-species effects for improvement in synthetic hybrid populations derived from outcrossing parental tree species may be one way to increase the efficacy and predictability of hybrid breeding. We present a comparative analysis of the quantitative trait loci (QTL) which resolved between from within-species effects for adventitious rooting in two populations of hybrids between Pinus elliottii and P. caribaea, an outbred F-1 (n=287) and an inbred-like F-2 family (n=357). Most small to moderate effect QTL (each explaining 2-5% of phenotypic variation, PV) were congruent (3 out of 4 QTL in each family) and therefore considered within-species effects as they segregated in both families. A single large effect QTL (40% PV) was detected uniquely in the F-2 family and assumed to be due to a between-species effect, resulting from a genetic locus with contrasting alleles in each parental species. Oligogenic as opposed to polygenic architecture was supported in both families (60% and 20% PV explained by 4 QTL in the F-2 and F-1 respectively). The importance of adventitious rooting for adaptation to survive water-logged environments was thought in part to explain oligogenic architecture of what is believed to be a complex trait controlled by many hundreds of genes.

DNA markers linked to yield, yield components, and morphological traits in autotetraploid lucerne (Medicago sativa L.)

We have mapped and identifed DNA markers linked to morphology, yield, and yield components of lucerne, using a backcross population derived from winter-active parents. The high-yielding and recurrent parent, D, produced individual markers that accounted for up to 18% of total yield over 6 harvests, at Gatton, south-eastern Queensland. The same marker, AC/TT8, was consistently identified at each individual harvest, and in individual harvests accounted for up to 26% of the phenotypic variation for yield. This marker was located in linkage group 2 of the D map, and several other markers positively associated with yield were consistently identified in this linkage group. Similarly, markers negatively associated with yield were consistently identified in the W116 map, W116 being the low-yielding parent. Highly significant positive correlations were observed between total yield and yield for harvests 1-6, and between total yield and stem length, tiller number, leaf yield/plant, leaf yield/5 stems, stem yield/plant, and stem yield/5 stems. Highly significant QTL were located for all these characters as well as for leaf shape and pubescence.

Specialization of pyramidal cell structure in the visual areas V1, V2 and V3 of the South American rodent, Dasyprocta primnolopha

Marked phenotypic variation has been reported in pyramidal cells in the primate cerebral cortex. These extent and systematic nature of these specializations suggest that they are important for specialized aspects of cortical processing. However, it remains unknown as to whether regional variations in the pyramidal cell phenotype are unique to primates or if they are widespread amongst mammalian species. In the present study we determined the receptive fields of neurons in striate and extrastriate visual cortex, and quantified pyramidal cell structure in these cortical regions, in the diurnal, large-brained, South American rodent Dasyprocta primnolopha. We found evidence for a first, second and third visual area (V1, V2 and V3, respectively) forming a lateral progression from the occipital pole to the temporal pole. Pyramidal cell structure became increasingly more complex through these areas, suggesting that regional specialization in pyramidal cell phenotype is not restricted to primates. However, cells in V1, V2 and V3 of the agouti were considerably more spinous than their counterparts in primates, suggesting different evolutionary and developmental influences may act on cortical microcircuitry in rodents and primates. (c) 2006 Elsevier B.V. All rights reserved.

How lifetimes shape epigenotype within and across generations

Despite our detailed characterization of the human genome at the level of the primary DNA sequence, we are still far from understanding the molecular events underlying phenotypic variation. Epigenetic modifications to the DNA sequence and associated chromatin are known to regulate gene expression and, as such, are a significant contributor to phenotype. Studies of inbred mice and monozygotic twins show that variation in the epigenotype can be seen even between genetically identical individuals and that this, in some cases at least, is associated with phenotypic differences. Moreover, recent evidence suggests that the epigenome can be influenced by the environment and these changes can last a lifetime. However, we also know that epigenetic states in real-time are in continual flux and, as a result, the epigenome exhibits instability both within and across generations. We still do not understand the rules governing the establishment and maintenance of the epigenotype at any particular locus. The underlying DNA sequence itself and the sequence at unlinked loci (modifier loci) are certainly involved. Recent support for the existence of transgenerational epigenetic inheritance in mammals suggests that the epigenetic state of the locus in the previous generation may also play a role. Over the next decade, many of these processes will be better understood, heralding a greater capacity for us to correlate measurable molecular marks with phenotype and providing the opportunity for improved diagnosis and presymptomatic healthcare.

The stability of P in coral reef fishes

The constancy of phenotypic variation and covariation is an assumption that underlies most recent investigations of past selective regimes and attempts to predict future responses to selection. Few studies have tested this assumption of constancy despite good reasons to expect that the pattern of phenotypic variation and covariation may vary in space and time. We compared phenotypic variance-covariance matrices (P) estimated for Populations of six species of distantly related coral reef fishes sampled at two locations on Australia's Great Barrier Reef separated by more than 1000 km. The intraspecific similarity between these matrices was estimated using two methods: matrix correlation and common principal component analysis. Although there was no evidence of equality between pairs of P, both statistical approaches indicated a high degree of similarity in morphology between the two populations for each species. In general, the hierarchical decomposition of the variance-covariance structure of these populations indicated that all principal components of phenotypic variance-covariance were shared but that they differed in the degree of variation associated with each of these components. The consistency of this pattern is remarkable given the diversity of morphologies and life histories encompassed by these species. Although some phenotypic instability was indicated, these results were consistent with a generally conserved pattern of multivariate selection between populations.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Genetic population structure and call variation in a passerine bird, the satin bowerbird, Ptilonorhynchus violaceus

Geographic variation in vocalizations is widespread in passerine birds, but its origins and maintenance remain unclear. One hypothesis to explain this variation is that it is associated with geographic isolation among populations and therefore should follow a vicariant pattern similar to that typically found in neutral genetic markers. Alternatively, if environmental selection strongly influences vocalizations, then genetic divergence and vocal divergence may be disassociated. This study compared genetic divergence derived from 11 microsatellite markers with a metric of phenotypic divergence derived from male bower advertisement calls. Data were obtained from 16 populations throughout the entire distribution of the satin bowerbird, an Australian wet-forest-restricted passerine. There was no relationship between call divergence and genetic divergence, similar to most other studies on birds with learned vocalizations. Genetic divergence followed a vicariant model of evolution, with the differentiation of isolated populations and isolation-by-distance among continuous populations. Previous work on Ptilonorhynchus violaceus has shown that advertisement call structure is strongly influenced by the acoustic environment of different habitats. Divergence in vocalizations among genetically related populations in different habitats indicates that satin bowerbirds match their vocalizations to the environment in which they live, despite the homogenizing influence of gene flow. In combination with convergence of vocalizations among genetically divergent populations occurring in the same habitat, this shows the overriding importance that habitat-related selection can have on the establishment and maintenance of variation in vocalizations.

Short- and long-term consequences of thermal variation in the larval environment of anurans

To survive adverse or unpredictable conditions in the ontogenetic environment, many organisms retain a level of phenotypic plasticity that allows them to meet the challenges of rapidly changing conditions. Larval anurans are widely known for their ability to modify behaviour, morphology and physiological processes during development, making them an ideal model system for studies of environmental effects on phenotypic traits. Although temperature is one of the most important factors influencing the growth, development and metamorphic condition of larval anurans, many studies have failed to include ecologically relevant thermal fluctuations among their treatments. We compared the growth and age at metamorphosis of striped marsh frogs Limnodynastes peronii raised in a diurnally fluctuating thermal regime and a stable regime of the same mean temperature. We then assessed the long-term effects of the larval environment on the morphology and performance of post-metamorphic frogs. Larval L. peronii from the fluctuating treatment were significantly longer throughout development and metamorphosed about 5 days earlier. Frogs from the fluctuating group metamorphosed at a smaller mass and in poorer condition compared with the stable group, and had proportionally shorter legs. Frogs from the fluctuating group showed greater jumping performance at metamorphosis and less degradation in performance during a 10-week dormancy. Treatment differences in performance could not be explained by whole-animal morphological variation, suggesting improved contractile properties of the muscles in the fluctuating group.

Studying phenotypic evolution using multivariate quantitative genetics

Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.

Trait physiology and crop modelling to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. We explore whether a crop growth and development modelling framework can link phenotype complexity to underlying genetic systems in a way that strengthens molecular breeding strategies. We use gene-to-phenotype simulation studies on sorghum to consider the value to marker-assisted selection of intrinsically stable QTLs that might be generated by physiological dissection of complex traits. The consequences on grain yield of genetic variation in four key adaptive traits – phenology, osmotic adjustment, transpiration efficiency, and staygreen – were simulated for a diverse set of environments by placing the known extent of genetic variation in the context of the physiological determinants framework of a crop growth and development model. It was assumed that the three to five genes associated with each trait, had two alleles per locus acting in an additive manner. The effects on average simulated yield, generated by differing combinations of positive alleles for the traits incorporated, varied with environment type. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages with gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies. We simulated a marker-assisted selection (MAS) breeding strategy based on the analyses of gene effects. When marker scores were allocated based on the contribution of gene effects to yield in a single environment, there was a wide divergence in rate of yield gain over all environments with breeding cycle depending on the environment chosen for the QTL analysis. It was suggested that knowledge resulting from trait physiology and modelling would overcome this dependency by identifying stable QTLs. The improved predictive power would increase the utility of the QTLs in MAS. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate QTLs.