ORCID Profile
0000-0002-8458-7691
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Publisher: Wiley
Date: 02-2012
DOI: 10.3732/AJB.1100313
Abstract: Weeds cause considerable environmental and economic damage. However, genomic characterization of weeds has lagged behind that of model plants and crop species. Here we describe the development of genomic tools and resources for 11 weeds from the Compositae family that will serve as a basis for subsequent population and comparative genomic analyses. Because hybridization has been suggested as a stimulus for the evolution of invasiveness, we also analyze these genomic data for evidence of hybridization. We generated 22 expressed sequence tag (EST) libraries for the 11 targeted weeds using Sanger, 454, and Illumina sequencing, compared the coverage and quality of sequence assemblies, and developed NimbleGen microarrays for expression analyses in five taxa. When possible, we also compared the distributions of Ks values between orthologs of congeneric taxa to detect and quantify hybridization and introgression. Gene discovery was enhanced by sequencing from multiple tissues, normalization of cDNA libraries, and especially greater sequencing depth. However, assemblies from short sequence reads sometimes failed to resolve close paralogs. Substantial introgression was detected in Centaurea and Helianthus, but not in Ambrosia and Lactuca. Transcriptome sequencing using next-generation platforms has greatly reduced the cost of genomic studies of nonmodel organisms, and the ESTs and microarrays reported here will accelerate evolutionary and molecular investigations of Compositae weeds. Our study also shows how ortholog comparisons can be used to approximately estimate the genome-wide extent of introgression and to identify genes that have been exchanged between hybridizing taxa.
Publisher: Cambridge University Press (CUP)
Date: 12-2007
DOI: 10.1614/WS-07-008.1
Abstract: Microarray analysis was used to identify changes in gene expression in velvetleaf that result from competition with corn. The plants were grown in field plots under adequate N (addition of 220 kg N ha −1 ) to minimize stress and s led at the V6 growth stage of corn (late June). Leaf area, dry weight, and N and P concentration were similar in velvetleaf plants grown alone or with corn. Competition, however, did influence velvetleaf gene expression. Genes involved in carbon utilization, photosynthesis, red light signaling, and cell ision were preferentially expressed when velvetleaf was grown in competition with corn. A less clear picture of the physiological impact of growth in monoculture was provided by the data. However, several genes involved in secondary metabolism and a gene preferentially expressed in response to phosphate availability were induced. No differences were observed in genes responsive to water stress or sequestering/transporting micronutrients.
Publisher: Cambridge University Press (CUP)
Date: 30-08-2018
DOI: 10.1017/WSC.2018.33
Abstract: Modern high-throughput molecular and analytical tools offer exciting opportunities to gain a mechanistic understanding of unique traits of weeds. During the past decade, tremendous progress has been made within the weed science discipline using genomic techniques to gain deeper insights into weedy traits such as invasiveness, hybridization, and herbicide resistance. Though the adoption of newer “omics” techniques such as proteomics, metabolomics, and physionomics has been slow, applications of these omics platforms to study plants, especially agriculturally important crops and weeds, have been increasing over the years. In weed science, these platforms are now used more frequently to understand mechanisms of herbicide resistance, weed resistance evolution, and crop–weed interactions. Use of these techniques could help weed scientists to further reduce the knowledge gaps in understanding weedy traits. Although these techniques can provide robust insights about the molecular functioning of plants, employing a single omics platform can rarely elucidate the gene-level regulation and the associated real-time expression of weedy traits due to the complex and overlapping nature of biological interactions. Therefore, it is desirable to integrate the different omics technologies to give a better understanding of molecular functioning of biological systems. This multidimensional integrated approach can therefore offer new avenues for better understanding of questions of interest to weed scientists. This review offers a retrospective and prospective examination of omics platforms employed to investigate weed physiology and novel approaches and new technologies that can provide holistic and knowledge-based weed management strategies for future.
Location: United States of America
No related grants have been discovered for David Horvath.