cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc29f1yr
title: CCDC 2127714: Experimental Crystal Structure Determination

description: Related Article: Yuki Kimura, Eisaku Ohashi, Sangita Karanjit, Takashi Taniguchi, Atsushi Nakayama, Hiroshi Imagawa, Ryota Sato, Kosuke Namba|2022|Org.Lett.|24|3297|doi:10.1021/acs.orglett.2c01215
DOI: 10.5517/ccdc.csd.cc29f261
title: CCDC 2127722: Experimental Crystal Structure Determination

description: Related Article: Yuki Kimura, Eisaku Ohashi, Sangita Karanjit, Takashi Taniguchi, Atsushi Nakayama, Hiroshi Imagawa, Ryota Sato, Kosuke Namba|2022|Org.Lett.|24|3297|doi:10.1021/acs.orglett.2c01215
DOI: 10.5517/ccdc.csd.cc29fq3l
title: CCDC 2128339: Experimental Crystal Structure Determination

description: Related Article: Meng-Hao Yi, Hai-Shan Jin, Ru-Bing Wang, Li-Ming Zhao|2022|J.Org.Chem.|87|5795|doi:10.1021/acs.joc.2c00122
DOI: 10.5517/ccdc.csd.cc29g9rv
title: CCDC 2128917: Experimental Crystal Structure Determination

description: Related Article: E. A. Silyanova, A. V. Samet, V. V. Semenov|2022|J.Org.Chem.|87|6444|doi:10.1021/acs.joc.2c00312
DOI: 10.5517/ccdc.csd.cc29g9vy
title: CCDC 2128920: Experimental Crystal Structure Determination

description: Related Article: E. A. Silyanova, A. V. Samet, V. V. Semenov|2022|J.Org.Chem.|87|6444|doi:10.1021/acs.joc.2c00312
DOI: 10.5517/ccdc.csd.cc29gj7k
title: CCDC 2129118: Experimental Crystal Structure Determination

description: Related Article: Shiyong Peng, Jieyin He, Liangliang Yang, Hong Zhang, Hongguang Li, Ming Lang, Chao Chen, Jian Wang|2022|J.Org.Chem.|87|6247|doi:10.1021/acs.joc.2c00482
DOI: 10.5517/ccdc.csd.cc29j141
title: CCDC 2130572: Experimental Crystal Structure Determination

description: Related Article: Leiqing Fu, Wenqiang Xu, Maoping Pu, Yun-Dong Wu, Yunyun Liu, Jie-Ping Wan|2022|Org.Lett.|24|3003|doi:10.1021/acs.orglett.2c00912
DOI: 10.5517/ccdc.csd.cc29j174
title: CCDC 2130575: Experimental Crystal Structure Determination

description: Related Article: Leiqing Fu, Wenqiang Xu, Maoping Pu, Yun-Dong Wu, Yunyun Liu, Jie-Ping Wan|2022|Org.Lett.|24|3003|doi:10.1021/acs.orglett.2c00912
DOI: 10.5517/ccdc.csd.cc29j196
title: CCDC 2130577: Experimental Crystal Structure Determination

description: Related Article: Leiqing Fu, Wenqiang Xu, Maoping Pu, Yun-Dong Wu, Yunyun Liu, Jie-Ping Wan|2022|Org.Lett.|24|3003|doi:10.1021/acs.orglett.2c00912
DOI: 10.5517/ccdc.csd.cc29k02z
title: CCDC 2131500: Experimental Crystal Structure Determination

description: Related Article: Wangyu Li, Dungai Wang, Xiao Liang, Zhixiong Jin, Shiwen Zhou, Guanru Chen, Yuanjiang Pan|2022|Org.Lett.|24|3086|doi:10.1021/acs.orglett.2c01115
DOI: 10.5517/ccdc.csd.cc29k041
title: CCDC 2131502: Experimental Crystal Structure Determination

description: Related Article: Wangyu Li, Dungai Wang, Xiao Liang, Zhixiong Jin, Shiwen Zhou, Guanru Chen, Yuanjiang Pan|2022|Org.Lett.|24|3086|doi:10.1021/acs.orglett.2c01115
DOI: 10.5517/ccdc.csd.cc29k8qw
title: CCDC 2131768: Experimental Crystal Structure Determination

description: Related Article: Ajit Kumar Jha, Rajkiran Kumari, Srinivasan Easwar|2022|J.Org.Chem.|87|5760|doi:10.1021/acs.joc.2c00087
DOI: 10.5517/ccdc.csd.cc29kng0
title: CCDC 2132132: Experimental Crystal Structure Determination

description: Related Article: Shyamal Kanti Bera, Prasenjit Mal|2022|Org.Lett.|24|3144|doi:10.1021/acs.orglett.2c00847
DOI: 10.5517/ccdc.csd.cc29knk3
title: CCDC 2132135: Experimental Crystal Structure Determination

description: Related Article: Shyamal Kanti Bera, Prasenjit Mal|2022|Org.Lett.|24|3144|doi:10.1021/acs.orglett.2c00847
DOI: 10.5517/ccdc.csd.cc29lll3
title: CCDC 2133035: Experimental Crystal Structure Determination

description: Related Article: Xuling Chen, Tao Wang, Zhongyue Lu, Pengfei Li|2022|Org.Lett.|24|3102|doi:10.1021/acs.orglett.2c01154
DOI: 10.5517/ccdc.csd.cc29lnk4
title: CCDC 2133096: Experimental Crystal Structure Determination

description: Related Article: Dominique E. Blackmun, Stephen A. Chamness, Corinna S. Schindler|2022|Org.Lett.|24|3053|doi:10.1021/acs.orglett.2c01008
DOI: 10.5517/ccdc.csd.cc29lp2p
title: CCDC 2133112: Experimental Crystal Structure Determination

description: Related Article: George E. Bell, James W. B. Fyfe, Eva M. Israel, Alexandra M. Z. Slawin, Matthew Campbell, Allan J. B. Watson|2022|Org.Lett.|24|3024|doi:10.1021/acs.orglett.2c00959
DOI: 10.5517/ccdc.csd.cc29ls4v
title: CCDC 2133207: Experimental Crystal Structure Determination

description: Related Article: Qi Xu, Huan Zhang, Fang-Bei Ge, Xiao-Mei Wang, Peng Zhang, Chuan-Jun Lu, Ren-Rong Liu|2022|Org.Lett.|24|3138|doi:10.1021/acs.orglett.2c00812
DOI: 10.5517/ccdc.csd.cc29zjkd
title: CCDC 2144504: Experimental Crystal Structure Determination

description: Related Article: Shyamal Kanti Bera, Prasenjit Mal|2022|Org.Lett.|24|3144|doi:10.1021/acs.orglett.2c00847
DOI: 10.5517/ccdc.csd.cc2b0drj
title: CCDC 2145347: Experimental Crystal Structure Determination

description: Related Article: Kosuke Yamamoto, Yu Suganomata, Takumi Inoue, Masami Kuriyama, Yosuke Demizu, Osamu Onomura|2022|J.Org.Chem.|87|6479|doi:10.1021/acs.joc.2c00398
DOI: 10.5517/ccdc.csd.cc2b0npq
title: CCDC 2145593: Experimental Crystal Structure Determination

description: Related Article: Vladyslav A. Andriashvili, Serhii Zhersh, Andrey A. Tolmachev, Oleksandr O. Grygorenko|2022|J.Org.Chem.|87|6237|doi:10.1021/acs.joc.2c00480
DOI: 10.5517/ccdc.csd.cc2b0nqr
title: CCDC 2145594: Experimental Crystal Structure Determination

description: Related Article: Vladyslav A. Andriashvili, Serhii Zhersh, Andrey A. Tolmachev, Oleksandr O. Grygorenko|2022|J.Org.Chem.|87|6237|doi:10.1021/acs.joc.2c00480
DOI: 10.5517/ccdc.csd.cc2b4zn4
title: CCDC 2149746: Experimental Crystal Structure Determination

description: Related Article: George E. Bell, James W. B. Fyfe, Eva M. Israel, Alexandra M. Z. Slawin, Matthew Campbell, Allan J. B. Watson|2022|Org.Lett.|24|3024|doi:10.1021/acs.orglett.2c00959
DOI: 10.5517/ccdc.csd.cc26xk1r
title: CCDC 2053224: Experimental Crystal Structure Determination

description: Related Article: Xingfeng Bai, Wenrui Zheng, Shaozhong Ge, Yixin Lu|2022|Org.Lett.|24|3080|doi:10.1021/acs.orglett.2c01082
DOI: 10.5517/ccdc.csd.cc26xk0q
title: CCDC 2053223: Experimental Crystal Structure Determination

description: Related Article: Xingfeng Bai, Wenrui Zheng, Shaozhong Ge, Yixin Lu|2022|Org.Lett.|24|3080|doi:10.1021/acs.orglett.2c01082
DOI: 10.5517/ccdc.csd.cc2b9ly6
title: CCDC 2154188: Experimental Crystal Structure Determination

description: Related Article: Camilla Loro, Letizia Molteni, Marta Papis, Leonardo Lo Presti, Francesca Foschi, Egle M. Beccalli, Gianluigi Broggini|2022|Org.Lett.|24|3092|doi:10.1021/acs.orglett.2c01135
DOI: 10.5517/ccdc.csd.cc2bcwrc
title: CCDC 2156383: Experimental Crystal Structure Determination

description: Related Article: Yang Li, Yanan Wang, Zhegao Ye, Shangbiao Zhang, Xiaodong Ye, Zheliang Yuan|2022|Org.Lett.|24|3009|doi:10.1021/acs.orglett.2c00916
DOI: 10.5517/ccdc.csd.cc2bf5pn
title: CCDC 2157621: Experimental Crystal Structure Determination

description: Related Article: Runfa He, Yang Liu, Yingqi Feng, Lu Chen, Yubing Huang, Feng Xie, Yibiao Li|2022|Org.Lett.|24|3167|doi:10.1021/acs.orglett.2c00903
DOI: 10.5517/ccdc.csd.cc2bfw2r
title: CCDC 2158284: Experimental Crystal Structure Determination

description: Related Article: Poornenth Pushpanandan, Vratta Grover, Mangalampalli Ravikanth|2022|Org.Lett.|24|3184|doi:10.1021/acs.orglett.2c00949
DOI: 10.5517/ccdc.csd.cc2bfx2s
title: CCDC 2158315: Experimental Crystal Structure Determination

description: Related Article: Anu Jacob, Philip Barkawitz, Peter G. Jones, Daniel B. Werz|2022|Org.Lett.|24|3028|doi:10.1021/acs.orglett.2c00967
DOI: 10.5517/ccdc.csd.cc2bfwxl
title: CCDC 2158310: Experimental Crystal Structure Determination

description: Related Article: Anu Jacob, Philip Barkawitz, Peter G. Jones, Daniel B. Werz|2022|Org.Lett.|24|3028|doi:10.1021/acs.orglett.2c00967
DOI: 10.5517/ccdc.csd.cc2bfx0q
title: CCDC 2158313: Experimental Crystal Structure Determination

description: Related Article: Anu Jacob, Philip Barkawitz, Peter G. Jones, Daniel B. Werz|2022|Org.Lett.|24|3028|doi:10.1021/acs.orglett.2c00967
DOI: 10.5517/ccdc.csd.cc2bfwzn
title: CCDC 2158312: Experimental Crystal Structure Determination

description: Related Article: Anu Jacob, Philip Barkawitz, Peter G. Jones, Daniel B. Werz|2022|Org.Lett.|24|3028|doi:10.1021/acs.orglett.2c00967
DOI: 10.5517/ccdc.csd.cc2bfx1r
title: CCDC 2158314: Experimental Crystal Structure Determination

description: Related Article: Anu Jacob, Philip Barkawitz, Peter G. Jones, Daniel B. Werz|2022|Org.Lett.|24|3028|doi:10.1021/acs.orglett.2c00967
DOI: 10.5517/ccdc.csd.cc2bfwym
title: CCDC 2158311: Experimental Crystal Structure Determination

description: Related Article: Anu Jacob, Philip Barkawitz, Peter G. Jones, Daniel B. Werz|2022|Org.Lett.|24|3028|doi:10.1021/acs.orglett.2c00967
DOI: 10.5517/ccdc.csd.cc2bhdr0
title: CCDC 2159762: Experimental Crystal Structure Determination

description: Related Article: Amanda Ramdular, K. A. Woerpel|2022|Org.Lett.|24|3217|doi:10.1021/acs.orglett.2c01004
DOI: 10.5517/ccdc.csd.cc2bc271
title: CCDC 2155592: Experimental Crystal Structure Determination

description: Related Article: Jessie James Limlingan Malit, Chuanhai Wu, Xueying Tian, Wenchao Liu, Duli Huang, Herman H.-Y. Sung, Ling-Li Liu, Ian D. Williams, Pei-Yuan Qian|2022|Org.Lett.|24|2967|doi:10.1021/acs.orglett.2c00745
DOI: 10.5517/ccdc.csd.cc2blsh7
title: CCDC 2163009: Experimental Crystal Structure Determination

description: Related Article: Shiyong Peng, Jieyin He, Liangliang Yang, Hong Zhang, Hongguang Li, Ming Lang, Chao Chen, Jian Wang|2022|J.Org.Chem.|87|6247|doi:10.1021/acs.joc.2c00482
DOI: 10.5517/ccdc.csd.cc2blsj8
title: CCDC 2163010: Experimental Crystal Structure Determination

description: Related Article: Shiyong Peng, Jieyin He, Liangliang Yang, Hong Zhang, Hongguang Li, Ming Lang, Chao Chen, Jian Wang|2022|J.Org.Chem.|87|6247|doi:10.1021/acs.joc.2c00482
DOI: 10.5517/ccdc.csd.cc2bn3x1
title: CCDC 2164293: Experimental Crystal Structure Determination

description: Related Article: Shiyong Peng, Jieyin He, Liangliang Yang, Hong Zhang, Hongguang Li, Ming Lang, Chao Chen, Jian Wang|2022|J.Org.Chem.|87|6247|doi:10.1021/acs.joc.2c00482
DOI: 10.5517/ccdc.csd.cc2bnc8n
title: CCDC 2164521: Experimental Crystal Structure Determination

description: Related Article: Wei Hao, Kailu Li, Chenyang Ye, Wenquan Yu, Junbiao Chang|2022|Org.Lett.|24|3286|doi:10.1021/acs.orglett.2c01183
DOI: 10.6084/m9.figshare.19750730
title: Additional file 2 of Burden of cancers in India - estimates of cancer crude incidence, YLLs, YLDs and DALYs for 2021 and 2025 based on National Cancer Registry Program

description: Additional file 2.
DOI: 10.6084/m9.figshare.19750730.v1
title: Additional file 2 of Burden of cancers in India - estimates of cancer crude incidence, YLLs, YLDs and DALYs for 2021 and 2025 based on National Cancer Registry Program

description: Additional file 2.
DOI: 10.5281/zenodo.6540731
title: IGM Population of HFF structures using Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE data

description: This repository accompanies the manuscript "<strong>Integrative Genome Modeling Platform reveals essentiality of rare contact events in 3D genome organizations</strong>", to appear in Nat. Methods (2022), see also https://www.biorxiv.org/content/10.1101/2021.08.22.457288v1. It contains the preprocessed input data files (Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE) for the HFF fibroblast cell line to be used in the Integrative Genome Modeling platform (IGM) developed in the Alber lab at UCLA (https://github.com/alberlab/igm). Also, we provide the configuration file to run IGM with those datasets, as we did in generating the HDSF population discussed in the accompanying manuscript. Such population is also provided as an "hss" file. Documentation and a simple demo/tutorial on how IGM can be run is given on the Alber lab Github @ https://github.com/alberlab/igm. All files can be read in using the <em>h5py</em> and <em>alabtools</em> (available @https://github.com/alberlab/alabtools) Python packages. More detailed information is provided in the manuscript and associated Supplementary Information file. For any inquiry/suggestions/doubts please reach out to Lorenzo Boninsegna (bonimba@g.ucla.edu) or Dr. Frank Alber (falber@g.ucla.edu).
description: This work was supported by the National Institutes of Health (grants U54DK107981 and 1UM1HG011593 to F.A), and an NSF CAREER grant (1150287 to F.A.). We thank the laboratories of Profs. Job Dekker (University of Massachusetts Medical School, UMass), Bas Van Steensel (Netherlands Cancer Institute, NKI), Tom Misteli (National Institutes of Health, NIH), and Andrew Belmont (University of Illinois Urbana-Champaign, UIUC) for kindly providing the experimental data (in situ Hi-C, lamina DamID, 3D HIPMap FISH, DNA SPRITE and SON TSA-seq, respectively) used for generating and validating our genome models
DOI: 10.5281/zenodo.6540730
title: IGM Population of HFF structures using Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE data

description: This repository accompanies the manuscript "<strong>Integrative Genome Modeling Platform reveals essentiality of rare contact events in 3D genome organizations</strong>", to appear in Nat. Methods (2022), see also https://www.biorxiv.org/content/10.1101/2021.08.22.457288v1. It contains the preprocessed input data files (Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE) for the HFF fibroblast cell line to be used in the Integrative Genome Modeling platform (IGM) developed in the Alber lab at UCLA (https://github.com/alberlab/igm). Also, we provide the configuration file to run IGM with those datasets, as we did in generating the HDSF population discussed in the accompanying manuscript. Such population is also provided as an "hss" file. Documentation and a simple demo/tutorial on how IGM can be run is given on the Alber lab Github @ https://github.com/alberlab/igm. All files can be read in using the <em>h5py</em> and <em>alabtools</em> (available @https://github.com/alberlab/alabtools) Python packages. More detailed information is provided in the manuscript and associated Supplementary Information file. For any inquiry/suggestions/doubts please reach out to Lorenzo Boninsegna (bonimba@g.ucla.edu) or Dr. Frank Alber (falber@g.ucla.edu).
description: This work was supported by the National Institutes of Health (grants U54DK107981 and 1UM1HG011593 to F.A), and an NSF CAREER grant (1150287 to F.A.). We thank the laboratories of Profs. Job Dekker (University of Massachusetts Medical School, UMass), Bas Van Steensel (Netherlands Cancer Institute, NKI), Tom Misteli (National Institutes of Health, NIH), and Andrew Belmont (University of Illinois Urbana-Champaign, UIUC) for kindly providing the experimental data (in situ Hi-C, lamina DamID, 3D HIPMap FISH, DNA SPRITE and SON TSA-seq, respectively) used for generating and validating our genome models
DOI: 10.21227/5rrb-9y02
title: Experimental Study of Outdoor UAV Localization and Tracking using Passive RF Sensing

description: Extensive use of unmanned aerial vehicles (UAVs) is expected to raise privacy and security concerns among individuals and
communities. In this context, detection and localization of UAVs will be critical for maintaining safe and secure airspace in the
future. In this work, Keysight N6854A radio frequency (RF) sensors are used to detect and locate a UAV by passively monitoring
the signals emitted from the UAV. First, the Keysight sensor detects the UAV by comparing the received RF signature with various
other UAVs’ RF signatures in the Keysight database using an envelope detection algorithm. Afterward, time difference of arrival
(TDoA) based localization is performed by a central controller using the sensor data, and the drone is localized with some error.
To mitigate the localization error, implementation of an extended Kalman filter (EKF) is proposed in this study. The performance
of the proposed approach is evaluated on a realistic experimental dataset. EKF requires basic assumptions on the type of motion
throughout the trajectory, i.e., the movement of the object is assumed to fit some motion model (MM) such as constant velocity
(CV), constant acceleration (CA), and constant turn (CT). In the experiments, an arbitrary trajectory is followed, therefore it is
not feasible to fit the whole trajectory into a single MM. Consequently, the trajectory is segmented into sub-parts and a different
MM is assumed in each segment while building the EKF model. Simulation results demonstrate an improvement in error statistics
when EKF is used if the MM assumption aligns with the real motion.
DOI: 10.5281/zenodo.6540993
title: Dataset for "Investigating multiple observations around a seismic gap during the Lushan earthquake in Sichuan, China"

description: "MsCatalog.csv" includes the catalog used in the paper. "staGPS.txt" includes the locations of GNSS stations used in this paper. "gnss2013" includes the daily horizontal surface displacement (E and N components) in the South China Block frame in 2013.
DOI: 10.6084/m9.figshare.19087646
title: Supplementary_The effect of endogenous Cushing's syndrome on all-cause and cause-specific mortality. A systematic review and meta-analysis.docx

description: The supplementary data generated during and/or analyzed during the current study for "The effect of endogenous Cushing's syndrome on all-cause and cause-specific mortality. A systematic review and meta-analysis".
DOI: 10.6084/m9.figshare.19747657.v1
title: jhq1

description: afsdafa <br>
DOI: 10.5281/zenodo.6540997
title: Hot Dense Silica Glass with Ultrahigh Elastic Moduli

description: Dataset for manuscript "Hot Dense Silica Glass with Ultrahigh Elastic Moduli"
DOI: 10.5281/zenodo.6540996
title: Hot Dense Silica Glass with Ultrahigh Elastic Moduli

description: Dataset for manuscript "Hot Dense Silica Glass with Ultrahigh Elastic Moduli"
DOI: 10.6084/m9.figshare.17088994.v1
title: Identification of resurrection genes from the transcriptome of dehydrated and rehydrated <i>Selaginella tamariscina</i>

description: <i>Selaginella tamariscina</i> is a lycophyta species that survives under extremely dry conditions via the mechanism of resurrection. This phenomenon involves the regulation of numerous genes that play vital roles in desiccation tolerance and subsequent rehydration. To identify resurrection-related genes, we analyzed the transcriptome between dehydration conditions and rehydration conditions of <i>S. tamariscina</i>. The <i>de novo</i> assembly generated 124,417 transcripts with an average size of 1,000 bp and 87,754 unigenes. Among these genes, 1,267 genes and 634 genes were up and down regulated by rehydration compared to dehydration. To understand gene function, we annotated Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The unigenes encoding early light-inducible protein (<i>ELIP</i>) were down-regulated, whereas pentatricopeptide repeat-containing protein (<i>PPR</i>), late embryogenesis abundant proteins (<i>LEA</i>), sucrose nonfermenting protein (<i>SNF</i>), trehalose phosphate phosphatase (<i>TPP</i>), trehalose phosphate synthase (<i>TPS</i>), and ABC transporter G family (<i>ABCG</i>) were significantly up-regulated in response to rehydration conditions by differentially expressed genes (DEGs) analysis. Several studies provide evidence that these genes play a role in stress environment. The <i>ELIP</i> and <i>PPR</i> genes are involved in chloroplast protection during dehydration and rehydration. <i>LEA, SNF</i>, and trehalose genes are known to be oxidant scavengers that protect the cell structure from the deleterious effect of drought. <i>TPP</i> and <i>TPS</i> genes were found in the starch and sucrose metabolism pathways, which are essential sugar-signaling metabolites regulating plant metabolism and other biological processes. <i>ABC-G</i> gene interacts with abscisic acid (ABA) phytohormone in the stomata opening during stress conditions. Our findings provide valuable information and candidate resurrection genes for future functional analysis aimed at improving the drought tolerance of crop plants.
DOI: 10.6084/m9.figshare.16971260.v1
title: Genome-wide investigation of <i>ZINC-IRON PERMEASE (ZIP)</i> genes in <i>Areca catechu</i> and potential roles of ZIPs in Fe and Zn uptake and transport

description: Iron (Fe) and Zinc (Zn) are essential nutrient elements for plant growth and development. Here, we observed the effects of Fe and Zn deficiency in seedlings of <i>Areca catechu</i> L. (areca palm), one of the most cultured palm trees in tropic regions. Results revealed that Fe deficiency causes strong chlorosis with the significantly decreased chlorophyll biosynthesis level and photosynthetic activities in the top third young leaf (L3) of seedlings. Zn deficiency caused light chlorosis in all three young leaves which slightly decreased chlorophyll biosynthesis and photosynthetic activities. Analysis of the Fe and Zn concentration in leaves and roots indicated that absorption and distribution of these two ions share cooperative pathways, since Zn deficiency caused Fe increasing, and vice versa. Therefore, we focused on the <i>ZINC-IRON PERMEASE (ZIP)</i> genes in areca trees. From the whole-genome data set we obtained, 6 <i>ZIP</i> genes were classified, and a phylogenetic tree was constructed with other 38 <i>ZIP</i> genes from model plants to find their potential functions. We also analyzed the expression pattern of <i>AcZIP1-6</i> genes under Zn and Fe deficiency by transcriptomic approaches. With these results, we constructed an expression atlas of <i>AcZIP1-6</i> genes in leaves and roots of areca seedlings with the dynamic expression levels under Fe and Zn deficient conditions. In conclusion, we provide evidence to understand the absorption and transport of nutrient elements, Fe and Zn, in the tropic agricultural plant <i>A. catechu.</i>
DOI: 10.6084/m9.figshare.16971260
title: Genome-wide investigation of <i>ZINC-IRON PERMEASE (ZIP)</i> genes in <i>Areca catechu</i> and potential roles of ZIPs in Fe and Zn uptake and transport

description: Iron (Fe) and Zinc (Zn) are essential nutrient elements for plant growth and development. Here, we observed the effects of Fe and Zn deficiency in seedlings of <i>Areca catechu</i> L. (areca palm), one of the most cultured palm trees in tropic regions. Results revealed that Fe deficiency causes strong chlorosis with the significantly decreased chlorophyll biosynthesis level and photosynthetic activities in the top third young leaf (L3) of seedlings. Zn deficiency caused light chlorosis in all three young leaves which slightly decreased chlorophyll biosynthesis and photosynthetic activities. Analysis of the Fe and Zn concentration in leaves and roots indicated that absorption and distribution of these two ions share cooperative pathways, since Zn deficiency caused Fe increasing, and vice versa. Therefore, we focused on the <i>ZINC-IRON PERMEASE (ZIP)</i> genes in areca trees. From the whole-genome data set we obtained, 6 <i>ZIP</i> genes were classified, and a phylogenetic tree was constructed with other 38 <i>ZIP</i> genes from model plants to find their potential functions. We also analyzed the expression pattern of <i>AcZIP1-6</i> genes under Zn and Fe deficiency by transcriptomic approaches. With these results, we constructed an expression atlas of <i>AcZIP1-6</i> genes in leaves and roots of areca seedlings with the dynamic expression levels under Fe and Zn deficient conditions. In conclusion, we provide evidence to understand the absorption and transport of nutrient elements, Fe and Zn, in the tropic agricultural plant <i>A. catechu.</i>