Mark Johnson - US grants

9870676 Johnson This Integrative Graduate Education and Research Training (IGERT) award will support the establishment of a broadly- based graduate training program in mathematical, cognitive and computational approaches to understanding how diverse cognitive processes, including language, movement and reasoning, are learned. The basic phenomena to be addressed are of significant commercial as well as scientific importance because, for example, they form the basis for design of speech and pattern recognition software, and for the design of robotic systems. The program is a joint effort of 13 faculty from the Departments of Applied Mathematics, Cognitive and Linguistic Sciences, and Computer Science. In combination with institutional resources, NSF funds will provide stipends for 12 graduate students, 2 postdoctoral students and 9 undergraduate students each year, as well as for related costs of student research training. Graduate students will be required to satisfy existing coursework requirements of their home departments and to take at least three new IGERT advanced topics courses meant to span the three participating disciplines. During the first two years of graduate school, each student will complete an interdisciplinary research project before beginning thesis research. All IGERT graduate trainees and faculty will also participate in a weekly research seminar, biannual retreats, a yearly week-long mini- course lead by a visiting researcher and a national conference to be organized during the second year of the project. Postdoctoral fellows will jointly organize one of the advanced topics courses and will themselves receive additional training to complement that received during their own graduate studies. Undergraduate students will become involved through active involvement in summer research projects in the groups of participating faculty. IGERT is a new, NSF-wide program whose goal is to sponsor the establishment of innovative, researc h-based graduate programs that will train a diverse group of new scientists and engineers to be well-prepared for varied careers in the private and public sectors. IGERT provides an opportunity for the development of new, well-focused multidisciplinary programs that bridge traditional organizational barriers, uniting faculty from several departments or institutions to establish a highly-interactive collaborative environment for both training and research. In its first year, the program will provide support to 17 institutions for new or nascent programs that collectively span all areas of science, engineering and mathematics eligible for support by the NSF.

DESCRIPTION (provided by applicant): The studies outlined in this proposal are based on a unique genetic approach to identify genes that are essential for the function of either the male or female gametes of Arabidopsis thaliana. In particular, the focus of this proposal will be on the critical molecular events that allow the male gamete-bearing structure, the pollen grain, to germinate, invade the ovary and successfully achieve fertilization of an ovule. These experiments take advantage of the quartet mutation, which causes the four products of pollen meiosis to remain fused, without adverse effects on individual pollen grains. T-DNA mutagenesis of quartet using a reporter gene that is expressed only in pollen enables detection of insertions into genes that are essential for either male or female gametes by a rapid and efficient visual screen. Lines carrying these types of insertions can be identified because they will fail to produce individuals that are homozygous for the insertion. This approach offers a unique opportunity to study the function of genes that will not be isolated by traditional genetic screens. In addition, the T-DNA allows direct analysis of mutant pollen phenotypes so that mutations can be isolated that disrupt each of the critical steps in pollen function, allowing a thorough mechanistic study.

Language is one of the most complex aspects of human behavior, and provides the foundation for many kinds of social interaction. The question of how people learn and use language is a subject of extensive research in several behavioral sciences, including cognitive science, psychology, and linguistics. There is a long tradition of using formal approaches to explore answers to this question, and recent work has begun to emphasize the importance of statistical models. With support from the National Science Foundation, Dr. Griffiths at UC Berkeley and Dr. Johnson at Brown University will develop and investigate new methods and models for learning and analyzing natural languages based on Bayesian statistics. In Bayesian statistics, the information about the structure of language provided by linguistic data is combined with a "prior" distribution that constrains the structures under consideration. This approach can make it easier to learn the properties of a language from limited amounts of data, and has a direct connection to theories of human language acquisition that emphasize the role of constraints in learning. This research project aims to integrate the statistical models used for learning and analyzing language with two methods from modern Bayesian statistics: Markov chain Monte Carlo algorithms and nonparametric Bayesian models. These methods make it possible to apply Bayesian inference in complex models of the kind that people typically work with in cognitive science and linguistics. The results of this project will provide new ways of working with traditional models of language, and lead to new models that are potentially of relevance to explaining how people acquire language. By exploring how contemporary statistical methods can be applied to the probabilistic models used in computational linguistics, this project will build closer connections between statistics, linguistics, and cognitive science, and provide opportunities for students to receive training in topics at the intersection of these disciplines.

This award was supported as part of the fiscal year 2006 Mathematical Sciences priority area special competition on Mathematical Social and Behavioral Sciences (MSBS).

Mark A. Johnson
IOS-1021917
HAP2(GCS1): Mechanisms of double fertilization

The molecular mechanisms that allow gamete cells (sperm and egg) to fuse are unknown. Overcoming this gap in our knowledge is an important goal because gamete fusion is central to the life cycle of all sexually reproducing organisms. Flowering plants (including major crops like corn, rice, and soybean) undergo double fertilization: one sperm fuses with the egg cell to form an embryo and another sperm fuses with the central cell to produce endosperm, a specialized tissue that supports the embryo. These cell fusion events lead to formation of seeds, the basis of the human food system. Gaining greater understanding of gamete fusion in flowering plants will lead to technologies that can improve seed crop production and control reproduction of crop plants. The hap2-1 mutant was identified using genetic analysis in the model plant species Arabidopsis thaliana. hap2-1 mutant sperm appear normal, but fail to fuse with either the egg or the central cell. These mutants lack a protein, HAP2(GCS1), that is normally on the surface of sperm cells. The hypothesis that will be tested in this project is that the HAP2(GCS1) protein is directly involved in a process that allows the male and female gametes to fuse. The goals of this project are 1) to identify new proteins that participate with HAP2(GCS1) to mediate gamete fusion, 2) to identify proteins that regulate the function of HAP2(GCS1), and 3) to determine how HAP2(GCS1) and other proteins allow gamete cells to fuse. The results of this project will have broad scientific impacts because HAP2(GCS1) is found in many eukaryotic species and is likely part of a gamete fusion mechanism employed by many plants and animals. This project will provide cutting-edge research training for both female and male undergraduate, graduate, and post-doctoral researchers of diverse backgrounds. This project also includes an outreach component to local elementary and high school students and teachers.

PI: Mark A. Johnson (Brown University)

ERA-CAPS Collaborators: Jörg Becker (Instituto Gulbenkian de Ciência, Oeiras, Portugal), Frederic Berger (Gregor Mendel Institute, Vienna, Austria), Thomas Dresselhaus and Stefanie Sprunck (University of Regensburg, Regensburg, Germany), David Twell (University of Leicester, Leicester, United Kingdom), Marek Mutwil (Max Plank Institute of Molecular Plant Physiology, Potsdam, Germany), and Jose Gutierrez-Marcos (University of Warwick, Warwick, United Kingdom)

The key agricultural products derived from corn, rice, wheat, and tomato all require successful reproduction by fertilization. The ability to increase crop production in the coming years will depend on developing a better understanding of reproductive mechanisms. The goal of this project is to take what has been learned about the molecules that mediate fertilization in a model plant species (Arabidopsis) and extend this knowledge using a comparative genomic approach in seven plant species including corn, rice, and tomato. The expected findings will allow for the identification of specific mechanisms that are targeted by environmental stresses during sexual reproduction in crops and will assist in the selection of stress-resistant cultivars. The outputs of this project will provide a deeper understanding of the evolution of sexual reproduction of economically important plant species. In addition this project will provide cutting edge training in biological imaging, genetics and genomics in the context of a critical crop plant (tomato) for a diverse team of researchers that will include a post-doctoral fellow and an undergraduate researcher. Importantly, this research team will be benefit from participation in this large, multidisciplinary and international effort comprising eight laboratories from five nations.

Research during the past five years has delivered tremendous new insights into gamete physiology and the mechanisms involved in fertilization in Arabidopsis. This progress has established the view that gametes are hyper-differentiated cell types with highly specific transcriptional profiles. Advances in microscopy based on fluorescent reporters and live cell imaging have also transformed research capability and provided insights into the mechanisms involved in gamete delivery, interaction and activation of seed development. Yet, the understanding of the complexity of double fertilization that characterizes flowering plants is far from complete and lacks any knowledge about the origin of mechanisms that predate double fertilization. In this project, emerging models representing key stages in plant evolution will be used to provide insight into the ancestral mechanisms of gamete differentiation and fertilization. Gene co-function networks will be identified from expression atlases for several plant species that include the liverwort Marchantia, the moss Physcomitrella and the extant basal flowering plant Amborella. These will be complemented with co-function networks from Arabidopsis and the economically important crops maize, tomato and rice and used to study the conservation of gene co-function networks governing male and female gametogenesis, pollen tube growth and fertilization mechanisms in flowering plants. Moreover, these investigations will provide novel molecular markers of fertility in crops. It is expected that this project will result in identification of fertilization factors that were lost from ancient angiosperms during the evolution of monocots (grasses) and eudicots and those which have evolved de novo in the angiosperm lineage. All data produced will be freely and continuously shared within the consortium. Specifically, RNAseq datasets will be accessible through a consortium database as well as through publicly available data repositories.