scholarly journals Comparative Transcriptomic Analysis of Root Cadmium Responses in Two Chinese Rice Cultivars Yuzhenxiang and Xiangwanxian 12

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Shangdu Zhang ◽  
Zhenliang Luo ◽  
Xiang Wu ◽  
Bangzhi Shi ◽  
Huidan Jiang ◽  
...  
Keyword(s):  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Transcriptomic Analysis ◽  
Rice Cultivars ◽  
Rice Varieties ◽  
Go Annotation ◽  
Pollution Problem ◽  
Search Tool ◽  
The Difference ◽  
Comparative Transcriptomic Analysis

Cadmium (Cd) pollution in paddy soil is an increasingly serious issue in rice production. It has been reported that there is a higher or lower grain Cd accumulation in the rice cultivars Yuzhenxiang (YZX) or Xiangwanxian 12 (XWX), respectively. To better manage the Cd pollution problem, the genes that might play vital roles in governing the difference in root Cd responses between these two rice cultivars were examined. In this study, the results of RNA sequencing (RNA-seq) showed that there were 341 and 161 differentially expressed genes in the roots of YZX and XWX after Cd exposure, respectively. Among these genes, 7 genes, such as Os06g0196300 (OsJ_019618), Os07g0570700 (OsJ_24808), ADI1, GDCSH, HSFB2C, PEX11-4, and CLPB1, possessed higher degree nodes with each other, through interaction analysis by the STRING (search tool for the retrieval of interacting genes/proteins) software, suggesting that they might play vital roles in Cd response. Based on GO enrichment analysis, 41 differently expressed genes after Cd treatment in YZX or XWX were identified to be related to Cd response. Through comparative transcriptomic analysis, 257 genes might be associated with the root Cd response difference between YZX and XWX. Furthermore, we supposed that ADI1, CFBP1, PEX11-4, OsJ_019618, OsJ_24808, GDCSH, CLPB1, LAC6, and WNK3 might be implicated in Cd response based on the combined analysis of RT-qPCR, interaction, and GO annotation analysis. In conclusion, the numerous genes that might be related to Cd stress response and root Cd response difference between YZX and XWX at the booting stage may be of benefit for the development of rice varieties with low Cd consumption.

scholarly journals Comparative Transcriptomic Analysis of the Pituitary Gland between Cattle Breeds Differing in Growth: Yunling Cattle and Leiqiong Cattle

Animals ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1271
Author(s):  
Xubin Lu ◽  
Abdelaziz Adam Idriss Arbab ◽  
Zhipeng Zhang ◽  
Yongliang Fan ◽  
Ziyin Han ◽  
...  
Keyword(s):  
Pituitary Gland ◽  
Interaction Analysis ◽  
Decisive Role ◽  
Enrichment Analysis ◽  
Zebu Cattle ◽  
Association Analyses ◽  
Cattle Breeds ◽  
Pituitary Glands ◽  
The Difference ◽  
Hpt Axis

The hypothalamic–pituitary–thyroid (HPT) axis hormones regulate the growth and development of ruminants, and the pituitary gland plays a decisive role in this process. In order to identify pivotal genes in the pituitary gland that could affect the growth of cattle by regulating the secretion of hormones, we detected the content of six HPT hormones related to growth in the plasma of two cattle breeds (Yunling and Leiqiong cattle, both also known as the zebu cattle) with great differences in growth and compared the transcriptome data of their pituitary glands. Our study found that the contents of GH, IGF, TSH, thyroxine, triiodothyronine, and insulin were significantly different between the two breeds, which was the main cause of the difference in growth; 175 genes were identified as differentially expressed genes (DEGs). Functional association analyses revealed that DEGs were mainly involved in the process of transcription and signal transduction. Combining the enrichment analysis and protein interaction analysis, eight DEGs were predicted to control the growth of cattle by affecting the expression of growth-related hormones in the pituitary gland. In summary, our results suggested that SLC38A1, SLC38A3, DGKH, GNB4, GNAQ, ESR1, NPY, and GAL are candidates in the pituitary gland for regulating the growth of Yunling and Leiqiong cattle by regulating the secretion of growth-related hormones. This study may help researchers further understand the growth mechanisms and improve the artificial selection of zebu cattle.

scholarly journals Effects of Trace Irrigation at Different Depths on Transcriptome Expression Pattern in Cotton (G. hirsutum L.) Leaves

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Li-yu Chen ◽  
Li-feng Zhang ◽  
Zhan-yuan Lu ◽  
Feng Xian ◽  
Jian-zhong Zhang ◽  
...  
Keyword(s):  
Inner Mongolia ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Transcriptomic Analysis ◽  
Functional Enrichment ◽  
Limiting Factor ◽  
Cotton Yield ◽  
Plant Tolerance ◽  
The Difference ◽  
Transcriptome Expression

Drought is a limiting factor for cotton productivity and quality. Irrigation could increase cotton yield. This study is aimed at formulating a proper irrigation depth for cotton at China’ Inner Mongolia and at investigating the molecular mechanism underlying the difference induced by irrigation. Transcriptomic analysis was carried out to reveal the global transcriptome profiles on the leaves of cotton seedlings (G. hirsutum L. cv. “Zhongmian 92”) with trace irrigation tapes at 30 cm (D30) and 50 cm (D50) underground. The differentially expressed genes (DEGs) were identified and clustered by functional enrichment analysis. The results showed that no significant differences were found in the lint percentage. The yields of unpinned and lint cotton were increased by the D30 regime but decreased by the D50 regime. Transcriptomic analysis showed that 4,549 nonoverlapped DEGs were identified by comparative analysis. Transcription factors, including bZIP, WARK, Myb, and NAC, were altered between D50 and D30. The D50 regime induced more DEGs compared with the D30 regime, which was associated with plant tolerance to abiotic stresses and drought. In conclusion, trace irrigation at 30 cm underground was suitable for cotton irrigation at China’s Inner Mongolia, while the D50 irrigation regime influenced the cotton yield via drought stress in cotton plants.

scholarly journals Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suthanthiram Backiyarani ◽  
Rajendran Sasikala ◽  
Simeon Sharmiladevi ◽  
Subbaraya Uma
Keyword(s):  
Candidate Genes ◽  
Protein Interaction ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Auxin Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

scholarly journals Identification of Key Genes and miRNAs in Osteosarcoma Patients with Chemoresistance by Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Binbin Xie ◽  
Yiran Li ◽  
Rongjie Zhao ◽  
Yuzi Xu ◽  
Yuhui Wu ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Functional Annotations ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Search Tool ◽  
Poor Outcomes

Chemoresistance is a significant factor associated with poor outcomes of osteosarcoma patients. The present study aims to identify Chemoresistance-regulated gene signatures and microRNAs (miRNAs) in Gene Expression Omnibus (GEO) database. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) included positive regulation of transcription, DNA-templated, tryptophan metabolism, and the like. Then differentially expressed genes (DEGs) were uploaded to Search Tool for the Retrieval of Interacting Genes (STRING) to construct protein-protein interaction (PPI) networks, and 9 hub genes were screened, such as fucosyltransferase 3 (Lewis blood group) (FUT3) whose expression in chemoresistant samples was high, but with a better prognosis in osteosarcoma patients. Furthermore, the connection between DEGs and differentially expressed miRNAs (DEMs) was explored. GEO2R was utilized to screen out DEGs and DEMs. A total of 668 DEGs and 5 DEMs were extracted from GSE7437 and GSE30934 differentiating samples of poor and good chemotherapy reaction patients. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to perform GO and KEGG pathway enrichment analysis to identify potential pathways and functional annotations linked with osteosarcoma chemoresistance. The present study may provide a deeper understanding about regulatory genes of osteosarcoma chemoresistance and identify potential therapeutic targets for osteosarcoma.

scholarly journals Brown spot disease severity, yield and yield loss relationships in pigmented upland rice cultivars from East Nusa Tenggara, Indonesia

2020 ◽  
Vol 21 (4) ◽  
Author(s):  
Yosep S. Mau ◽  
Antonius Ndiwa ◽  
Shirly Oematan
Keyword(s):  
Disease Severity ◽  
Yield Loss ◽  
Upland Rice ◽  
Brown Spot ◽  
Yield Reduction ◽  
Rice Cultivars ◽  
Rice Varieties ◽  
Resistance Level ◽  
Spot Disease ◽  
Brown Spot Disease

Abstract. Mau YS, Ndiwa ASS, Oematan SS. 2020. Brown spot disease severity, yield and yield loss relationships in pigmented upland rice cultivars from East Nusa Tenggara, Indonesia. Biodiversitas 21: 1625-1634. Brown spot is one of the most devastating diseases of rice, which could lead to total yield loss. The disease has a worldwide distribution, more specifically in areas where water supply is scarce, most specifically in the dry upland areas. Almost all stages of rice are affected by the disease, where leaves and grains are mostly affected. Considerable differences exist in susceptibility to brown spot among rice varieties, which may cause a large variation in yield loss caused by the disease. Therefore, the resistance level of rice varieties and their yield reduction has to be regularly evaluated and updated. There are only a few reports on the relationship between brown spot severity with yield and yield loss of upland rice, and is even lacking in pigmented upland rice. The objectives of the present study were to assess the brown spot severity and resistance level in pigmented upland rice cultivars from East Nusa Tenggara Province, Indonesia, and to elucidate their relationships with yield and yield reduction. Twenty four pigmented upland rice genotypes were evaluated in the field during May to October 2019, and their disease responses and yields were recorded. Disease severity was observed weekly and used to calculate Area Under the Disease Progress Curve (AUDPC) for comparison among the genotypes. The relationships between disease severity and AUDPC with yield and yield loss were also examined. The results showed significant variation in brown spot severity and AUDPC, ranging from, respectively, 11.11% to 40.70% and 398.42%-days to 1081.30%-days. Yields and yield losses of test genotypes also varied substantially. Yields under diseased-free and diseased plots ranged from, respectively, 2.34 t ha-1 to 6.13 t ha-1 and 1.68 t ha-1 to 3.74 t ha-1 while yield loss was between 10.46% and 56.15%. Six genotypes were moderately resistant, four genotypes were moderately susceptible and 14 genotypes were susceptible to brown spot. Neither disease severity nor AUDPC had a linear relationship with yield but both exhibited positive and linear relationships with yield loss.

Sign in / Sign up

Export Citation Format

Share Document