Spatial variation in life history reveals insight into connectivity and geographic population structure of a tropical estuarine teleost: king threadfin, Polydactylus macrochir

Understanding the life history of exploited fish species is not only critical in developing stock assessments and productivity models, but has a dual function in the delineation of connectivity and geographical population structure. In this study, patterns in growth and length and age at sex change of Polydactylus macrochir, an ecologically and economically important protandrous estuarine teleost, were examined to provide preliminary information on the species' connectivity and geographic structure across northern Australia. Considerable variation in life history parameters was observed among the 18 locations sampled. Both unconstrained and constrained (t(0) = 0) estimates of von Bertalanffy growth function parameters differed significantly among all neighbouring locations with the exception of two locations in Queensland's east coast and two in Queensland's Gulf of Carpentaria waters, respectively. Comparisons of back-calculated length-at-age 2 provided additional evidence for growth differences among some locations, but were not significantly different among locations in the south-eastern Gulf of Carpentaria or on Queensland's east coast. The length and age at sex change differed markedly among locations, with fish from the east coast of Australia changing sex from males to females at significantly greater lengths and ages than elsewhere. Sex change occurred earliest at locations within Queensland's Gulf of Carpentaria, where a large proportion of small, young females were recorded. The observed differences suggest that P. macrochir likely form a number of geographically and/or reproductively distinct groups in Australian waters and suggest that future studies examining connectivity and geographic population structure of estuarine fishes will likely benefit from the inclusion of comparisons of life history parameters. (C) 2012 Elsevier B.V. All rights reserved.

Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time

Nested association mapping (NAM) offers power to dissect complex, quantitative traits. This study made use of a recently developed sorghum backcross (BC)-NAM population to dissect the genetic architecture of flowering time in sorghum; to compare the QTL identified with other genomic regions identified in previous sorghum and maize flowering time studies and to highlight the implications of our findings for plant breeding. A subset of the sorghum BC-NAM population consisting of over 1,300 individuals from 24 families was evaluated for flowering time across multiple environments. Two QTL analysis methodologies were used to identify 40 QTLs with predominately small, additive effects on flowering time; 24 of these co-located with previously identified QTL for flowering time in sorghum and 16 were novel in sorghum. Significant synteny was also detected with the QTL for flowering time detected in a comparable NAM resource recently developed for maize (Zea mays) by Buckler et al. (Science 325:714-718, 2009). The use of the sorghum BC-NAM population allowed us to catalogue allelic variants at a maximal number of QTL and understand their contribution to the flowering time phenotype and distribution across diverse germplasm. The successful demonstration of the power of the sorghum BC-NAM population is exemplified not only by correspondence of QTL previously identified in sorghum, but also by correspondence of QTL in different taxa, specifically maize in this case. The unification across taxa of the candidate genes influencing complex traits, such as flowering time can further facilitate the detailed dissection of the genetic control and causal genes.

On Systems Thinking, Systems Biology, and the in Silico Plant

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).