Publications by authors named "Norbert Bokros"

Stalk lodging (structural failure crops prior to harvest) significantly reduces annual yields of vital grain crops. The lack of standardized, high throughput phenotyping methods capable of quantifying biomechanical plant traits prevents comprehensive understanding of the genetic architecture of stalk lodging resistance. A phenotyping pipeline developed to enable higher throughput biomechanical measurements of plant traits related to stalk lodging is presented.

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This study presents a methodology for a high-throughput digitization and quantification process of plant cell walls characterization, including the automated development of two-dimensional finite element models. Custom algorithms based on machine learning can also analyze the cellular microstructure for phenotypes such as cell size, cell wall curvature, and cell wall orientation. To demonstrate the utility of these models, a series of compound microscope images of both herbaceous and woody representatives were observed and processed.

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The cell wall compositional (lignin and polysaccharides) variation of two sweet sorghum varieties, Della (D) and its variant (RG), was evaluated at internodes (IN) and nodes (N) using high-performance liquid chromatography (HPLC), pyrolysis-gas chromatography-mass spectrometry (Py-GCMS), X-ray diffraction (XRD), and two-dimensional (2D) H-C nuclear magnetic resonance (NMR). The stalks were grown in 2018 (D1 and RG1) and 2019 (D2 and RG2) seasons. In RG1, Klason lignin reductions by 16-44 and 2-26% were detected in IN and N, respectively.

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We report here the genome sequence of sp. RRD69, a plant-growth-promoting bacterial endophyte isolated from switchgrass plants grown on a reclaimed coal-mining site in Kentucky. RRD69 is predicted to contain 3,758 protein-coding genes, with a genome size of 3.

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The complexity in chemical composition alongside the genomic complexity of crop plants poses significant challenges for the characterization of their proteomes. This chapter provides specific methods that can be used for the extraction and identification of proteins from sweet potato, and a proteogenomic method for the subsequent peptide mapping on the haplotype-derived sweet potato genome assembly. We outline two basic methods for extracting proteins expressed in root and leaf tissues for the label-free quantitative proteomics-one phenol-based procedure and one polyethylene glycol (PEG) 4000-based fractionation method-and discuss strategies for the organ-specific protein extraction and increased recovery of low-abundance proteins.

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We report here the genome assembly and analysis of strain sp. LKL04, a Gram-positive bacterial endophyte isolated from switchgrass plants () grown on a reclaimed coal-mining site. The 2.

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Article Synopsis
  • Two methods for extracting proteins were used alongside an automated system to examine the specific proteins found in sweetpotato tissues, discovering 74,255 peptides that relate to 4,321 distinct proteins.
  • Different extraction methods yielded varying numbers and types of unique proteins, with leaves showing more proteins related to primary metabolism and protein translation, while roots had proteins connected to folding and carbohydrate metabolism.
  • The analysis revealed 90.4% of peptides matched the sweetpotato genome, led to the prediction of 741 new protein-coding genes, and highlighted 2,056 areas for possible gene annotation improvements; data from this study can be found on ProteomeXchange using the identifier PXD012999.
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Background: Gene families are sets of structurally and evolutionarily related genes - in one or multiple species - that typically share a conserved biological function. As such, the identification and subsequent analyses of entire gene families are widely employed in the fields of evolutionary and functional genomics of both well established and newly sequenced plant genomes. Currently, plant gene families are typically identified using one of two major ways: 1) HMM-profile based searches using models built on Arabidopsis thaliana genes or 2) coding sequence homology searches using curated databases.

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