skip to main content


Title: A deep learning approach to track Arabidopsis seedlings’ circumnutation from time-lapse videos
Abstract Background

Circumnutation (Darwin et al., Sci Rep 10(1):1–13, 2000) is the side-to-side movement common among growing plant appendages but the purpose of circumnutation is not always clear. Accurately tracking and quantifying circumnutation can help researchers to better study its underlying purpose.

Results

In this paper, a deep learning-based model is proposed to track the circumnutating flowering apices in the plant Arabidopsis thaliana from time-lapse videos. By utilizing U-Net to segment the apex, and combining it with the model update mechanism, pre- and post- processing steps, the proposed model significantly improves the tracking time and accuracy over other baseline tracking methods. Additionally, we evaluate the computational complexity of the proposed model and further develop a method to accelerate the inference speed of the model. The fast algorithm can track the apices in real-time on a computer without a dedicated GPU.

Conclusion

We demonstrate that the accuracy of tracking the flowering apices in the plant Arabidopsis thaliana can be improved with our proposed deep learning-based model in terms of both the racking success rate and the tracking error. We also show that the improvement in the tracking accuracy is statistically significant. The time-lapse video dataset of Arabidopsis is also provided which can be used for future studies on Arabidopsis in various takes.

 
more » « less
NSF-PAR ID:
10399159
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Springer Science + Business Media
Date Published:
Journal Name:
Plant Methods
Volume:
19
Issue:
1
ISSN:
1746-4811
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Summary Lay Description

    Particles are widely used as probes in life sciences through their motions. In single molecule techniques such as optical tweezers and magnetic tweezers, microbeads are used to study intermolecular or intramolecular interactions via beads tracking. Also tracking multiple beads’ motions could study cell–cell or cell–ECM interactions in traction force microscopy. Therefore, particle tracking is of key important during these researches. However, parallel 3D multiple particle tracking in real‐time with high resolution is a challenge either due to the algorithm or the program. Here, we combine the performance of CPU and CUDA‐based GPU to make a hybrid implementation for particle tracking. In this way, a speedup of 137 is obtained compared the program before only with CPU without loss of accuracy. Moreover, we improve and build a new centrifugal force microscope for multiple single molecule force spectroscopy research in parallel. Then we employed our program into centrifugal force microscope for DNA stretching study. Our results not only demonstrate the application of this program in single molecule techniques, also indicate the capability of multiple single molecule study with centrifugal force microscopy.

     
    more » « less
  2. Abstract Background

    Idiopathic pulmonary fibrosis (IPF) is a progressive, irreversible, and usually fatal lung disease of unknown reasons, generally affecting the elderly population. Early diagnosis of IPF is crucial for triaging patients’ treatment planning into anti‐fibrotic treatment or treatments for other causes of pulmonary fibrosis. However, current IPF diagnosis workflow is complicated and time‐consuming, which involves collaborative efforts from radiologists, pathologists, and clinicians and it is largely subject to inter‐observer variability.

    Purpose

    The purpose of this work is to develop a deep learning‐based automated system that can diagnose subjects with IPF among subjects with interstitial lung disease (ILD) using an axial chest computed tomography (CT) scan. This work can potentially enable timely diagnosis decisions and reduce inter‐observer variability.

    Methods

    Our dataset contains CT scans from 349 IPF patients and 529 non‐IPF ILD patients. We used 80% of the dataset for training and validation purposes and 20% as the holdout test set. We proposed a two‐stage model: at stage one, we built a multi‐scale, domain knowledge‐guided attention model (MSGA) that encouraged the model to focus on specific areas of interest to enhance model explainability, including both high‐ and medium‐resolution attentions; at stage two, we collected the output from MSGA and constructed a random forest (RF) classifier for patient‐level diagnosis, to further boost model accuracy. RF classifier is utilized as a final decision stage since it is interpretable, computationally fast, and can handle correlated variables. Model utility was examined by (1) accuracy, represented by the area under the receiver operating characteristic curve (AUC) with standard deviation (SD), and (2) explainability, illustrated by the visual examination of the estimated attention maps which showed the important areas for model diagnostics.

    Results

    During the training and validation stage, we observe that when we provide no guidance from domain knowledge, the IPF diagnosis model reaches acceptable performance (AUC±SD = 0.93±0.07), but lacks explainability; when including only guided high‐ or medium‐resolution attention, the learned attention maps are not satisfactory; when including both high‐ and medium‐resolution attention, under certain hyperparameter settings, the model reaches the highest AUC among all experiments (AUC±SD = 0.99±0.01) and the estimated attention maps concentrate on the regions of interests for this task. Three best‐performing hyperparameter selections according to MSGA were applied to the holdout test set and reached comparable model performance to that of the validation set.

    Conclusions

    Our results suggest that, for a task with only scan‐level labels available, MSGA+RF can utilize the population‐level domain knowledge to guide the training of the network, which increases both model accuracy and explainability.

     
    more » « less
  3. Abstract

    Brassinosteroids (BRs) are essential plant growth‐promoting hormones involved in many processes throughout plant development, from seed germination to flowering time. SinceBRsdo not undergo long‐distance transport, cell‐ and tissue‐specific regulation of hormone levels involves both biosynthesis and inactivation. To date, tenBR‐inactivating enzymes, with at least five distinct biochemical activities, have been experimentally identified in the model plantArabidopsis thaliana. Epigenetic interactions betweenT‐DNAinsertion alleles and genetic linkage have hindered analysis of higher‐order null mutants in these genes. A previous study demonstrated that thebas1‐2 sob7‐1 ben1‐1triple‐null mutant could not be characterized due to epigenetic interactions between the exonicT‐DNAinsertions inbas1‐2andsob7‐1,causing the intronicT‐DNAinsertion ofben1‐1to revert to a partial loss‐of‐function allele. We usedCRISPR‐Cas9genome editing to avoid this problem and generated thebas1‐2 sob7‐1 ben1‐3triple‐null mutant. This triple‐null mutant resulted in an additive seedling long‐hypocotyl phenotype. We also uncovered a role forBEN1‐mediatedBR‐inactivation in seedling cotyledon petiole elongation that was not observed in the singleben1‐2null mutant but only in the absence of bothBAS1andSOB7. In addition, genetic analysis demonstrated thatBEN1does not contribute to the early‐flowering phenotype, whichBAS1andSOB7redundantly regulate. Our results show thatBAS1,BEN1,andSOB7have overlapping and independent roles based on their differential spatiotemporal tissue expression patterns

     
    more » « less
  4. Summary

    The flowering plantArabidopsis thalianais a dicot model organism for research in many aspects of plant biology. A comprehensive annotation of its genome paves the way for understanding the functions and activities of all types of transcripts, includingmRNA, the various classes of non‐codingRNA, and smallRNA. TheTAIR10 annotation update had a profound impact on Arabidopsis research but was released more than 5 years ago. Maintaining the accuracy of the annotation continues to be a prerequisite for future progress. Using an integrative annotation pipeline, we assembled tissue‐specificRNA‐Seq libraries from 113 datasets and constructed 48 359 transcript models of protein‐coding genes in eleven tissues. In addition, we annotated various classes of non‐codingRNAincluding microRNA, long intergenicRNA, small nucleolarRNA, natural antisense transcript, small nuclearRNA, and smallRNAusing published datasets and in‐house analytic results. Altogether, we identified 635 novel protein‐coding genes, 508 novel transcribed regions, 5178 non‐codingRNAs, and 35 846 smallRNAloci that were formerly unannotated. Analysis of the splicing events andRNA‐Seq based expression profiles revealed the landscapes of gene structures, untranslated regions, and splicing activities to be more intricate than previously appreciated. Furthermore, we present 692 uniformly expressed housekeeping genes, 43% of whose human orthologs are also housekeeping genes. This updated Arabidopsis genome annotation with a substantially increased resolution of gene models will not only further our understanding of the biological processes of this plant model but also of other species.

     
    more » « less
  5. Abstract

    ATPase family AAA domain–containing 3 (ATAD3) proteins are unique mitochondrial proteins that arose deep in the eukaryotic lineage but that are surprisingly absent in Fungi and Amoebozoa. These ∼600-amino acid proteins are anchored in the inner mitochondrial membrane and are essential in metazoans and Arabidopsis thaliana. ATAD3s comprise a C-terminal ATPases Associated with a variety of cellular Activities (AAA+) matrix domain and an ATAD3_N domain, which is located primarily in the inner membrane space but potentially extends to the cytosol to interact with the ER. Sequence and structural alignments indicate that ATAD3 proteins are most similar to classic chaperone unfoldases in the AAA+ family, suggesting that they operate in mitochondrial protein quality control. A. thaliana has four ATAD3 genes in two distinct clades that appear first in the seed plants, and both clades are essential for viability. The four genes are generally coordinately expressed, and transcripts are highest in growing apices and imbibed seeds. Plants with disrupted ATAD3 have reduced growth, aberrant mitochondrial morphology, diffuse nucleoids and reduced oxidative phosphorylation complex I. These and other pleiotropic phenotypes are also observed in ATAD3 mutants in metazoans. Here, we discuss the distribution of ATAD3 proteins as they have evolved in the plant kingdom, their unique structure, what we know about their function in plants and the challenges in determining their essential roles in mitochondria.

     
    more » « less