AtSRP1, SMALL RUBBER PARTICLE PROTEIN HOMOLOG, functions in pollen growth and development in Arabidopsis

Hun, Yong; Kim, Sun Young; Lee, Eun Seon; Jung, Young Jun; Park, Joung Hun; Paeng, Seol Ki; Oh, Hun Taek; Melencion, Sarah Mae Boyles; Alinapon, Cresilda Vergara; Lee, Sang Yeol

doi:10.1016/j.bbrc.2016.05.083

Cited by 8 publications

(2 citation statements)

References 34 publications

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“…In such cases, the concatenated word gets labelled as one entity type called ‘tagged protein’ and sub labels are used to differentiate between protein and methodology (Supplemental Fig. S1, Supplemental table S3) 18,19 .…”

Section: Resultsmentioning

confidence: 99%

Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network

David

Menezes

Klerk

et al. 2020

Preprint

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With the advent of increased diversity and scale of molecular data, there has been a growing appreciation for the applications of machine learning and statistical methodologies to gain new biological insights. An important step in achieving this aim is the Relation Extraction process which specifies if an interaction exists between two or more biological entities in a published study. Here, we employed natural-language processing (CBOW) and deep Recurrent Neural Network (bi-directional LSTM) to predict relations between biological entities that describe protein subcellular localisation in plants. We applied our system to 1700 published Arabidopsis protein subcellular studies from the SUBA manually curated dataset. The system was able to extract relevant text and the classifier predicted interactions between protein name, subcellular localisation and experimental methodology. It obtained a final precision, recall rate, accuracy and F1 scores of 0.951, 0.828, 0.893 and 0.884 respectively. The classifier was subsequently tested on a similar problem in crop species (CropPAL) and demonstrated a comparable accuracy measure (0.897). Consequently, our approach can be used to extract protein functional features from unstructured text in the literature with high accuracy. The developed system will improve dissemination or protein functional data to the scientific community and unlock the potential of big data text analytics for generating new hypotheses from diverse datasets.

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Section: Resultsmentioning

confidence: 99%

Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network

David

Menezes

Klerk

et al. 2020

Preprint

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“…In Arabidopsis, double mutants of npc2-1 npc6-2 exhibited reduced viability of ovules and pollens [50]. A small rubber particle protein3 (Ghir_D11G032630) which associates with lipid droplet surfaces, was reported to be a positive regulator of tissue growth and development and was induced by ABA [51]. Other highly connected hub genes include 2 glycosylphosphatidylinositol-anchored lipid protein transfer 1 ( Ghir_D04G019930/Ghir_A04G015210 ) which bind to lipids and function as a component of the cuticular lipid export machinery that performs extensive export of intracellular lipids from epidermal cells to the surface to build the cuticular wax layer and silique walls [52], a LTP family protein Ghir_A08G018060 with unclear function, and a isoprenoid biosynthesis enzyme DXR (Ghir_D09G017510) which caused a seedling lethal, albino phenotype when were knockout or strongly silenced [53].…”

Section: Hub Genes Identi Cation Through Wgcnamentioning

confidence: 99%

Deficiencies in the formation and regulation of anther cuticle and tryphine contribute to male sterility in cotton PGMS line

Zhang

Liu

et al. 2020

Preprint

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Background: Male sterility is a simple and efficient pollination control system that is widely exploited in hybrid breeding. In upland cotton, CCRI9106, a photosensitive genetic male sterile (PGMS) mutant isolated from CCRI040029, was reported of great advantages to cotton heterosis. However, little information concerning the male sterility of CCRI9106 is known. Here, comparative transcriptome analysis of CCRI9106 (the mutant, MT) and CCRI040029 (the wild type, WT) anthers in Anyang (long-day, male sterile condition to CCRI9106) was performed to reveal the potential male sterile mechanism of CCRI9106.Results: Light and electron microscopy revealed that the male sterility phenotype of MT was mainly attributed to irregularly exine, lacking tryphine and immature anther cuticle. Based on the cytological characteristics of MT anthers, anther RNA libraries (18 in total) of tetrad (TTP), late uninucleate (LUNP) and binucleate (BNP) stages in MT and WT were constructed for transcriptomic analysis, therefore revealing a total of 870,4 differentially expressed genes (DEGs). By performing gene expression pattern analysis and protein-protein interaction (PPI) networks construction, we found down-regulation of DEGs, which enriched by the lipid biosynthetic process and the synthesis pathways of several types of secondary metabolites such as terpenoids, flavonoids and steroids, may crucial to the male sterility phenotype of MT, and resulting in the defects of anther cuticle and tryphine, even the irregularly exine. Furthermore, several lipid-related genes together with ABA-related genes and MYB transcription factors were identified as hub genes via weighted gene co-expression network analysis (WGCNA). Additionally, the ABA content of MT anthers was reduced across all stages when compared with WT anthers. At last, genes related to the formation of anther cuticle and tryphine could activated in MT under short-day condition.Conclusions: We propose that the down-regulation of genes related to the assembly of anther cuticle and tryphine may lead to the male sterile phenotype of MT, and MYB transcription factors together with ABA played key regulatory roles in these processes. The conversion of fertility in different photoperiods may closely relate to the functional expression of these genes. These findings contribute to elucidate the mechanism of male sterility in upland cotton.

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Multifunctional liposome-quantum dot hybrid nanocarriers for drug targeting to brain tumors

Das,

Ranjan,

Rao

et al. 2022

Nanocarriers for Drug-Targeting Brain Tumors

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AtSRP1, SMALL RUBBER PARTICLE PROTEIN HOMOLOG, functions in pollen growth and development in Arabidopsis

Cited by 8 publications

References 34 publications

Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network

Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network

Deficiencies in the formation and regulation of anther cuticle and tryphine contribute to male sterility in cotton PGMS line

Multifunctional liposome-quantum dot hybrid nanocarriers for drug targeting to brain tumors

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