Species discrimination and hybrid detection in terrestrial orchids using Bar-HRM: A case of the Calanthe group

Plant Gene ◽  
2021 ◽  
pp. 100349
Author(s):  
Kittisak Buddhachat ◽  
Nattaporn Sripairoj ◽  
Tasanai Punjansing ◽  
Anupan Kongbangkerd ◽  
Phithak Inthima ◽  
...  
Plants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 84
Author(s):  
Huanchu Liu ◽  
Hans Jacquemyn ◽  
Xingyuan He ◽  
Wei Chen ◽  
Yanqing Huang ◽  
...  

Human pressure on the environment and climate change are two important factors contributing to species decline and overall loss of biodiversity. Orchids may be particularly vulnerable to human-induced losses of habitat and the pervasive impact of global climate change. In this study, we simulated the extent of the suitable habitat of three species of the terrestrial orchid genus Cypripedium in northeast China and assessed the impact of human pressure and climate change on the future distribution of these species. Cypripedium represents a genus of long-lived terrestrial orchids that contains several species with great ornamental value. Severe habitat destruction and overcollection have led to major population declines in recent decades. Our results showed that at present the most suitable habitats of the three species can be found in Da Xing’an Ling, Xiao Xing’an Ling and in the Changbai Mountains. Human activity was predicted to have the largest impact on species distributions in the Changbai Mountains. In addition, climate change was predicted to lead to a shift in distribution towards higher elevations and to an increased fragmentation of suitable habitats of the three investigated Cypripedium species in the study area. These results will be valuable for decision makers to identify areas that are likely to maintain viable Cypripedium populations in the future and to develop conservation strategies to protect the remaining populations of these enigmatic orchid species.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Can Yuan ◽  
Xiufen Sha ◽  
Miao Xiong ◽  
Wenjuan Zhong ◽  
Yu Wei ◽  
...  

AbstractLigusticum L., one of the largest members in Apiaceae, encompasses medicinally important plants, the taxonomic statuses of which have been proved to be difficult to resolve. In the current study, the complete chloroplast genomes of seven crucial plants of the best-known herbs in Ligusticum were presented. The seven genomes ranged from 148,275 to 148,564 bp in length with a highly conserved gene content, gene order and genomic arrangement. A shared dramatic decrease in genome size resulted from a lineage-specific inverted repeat (IR) contraction, which could potentially be a promising diagnostic character for taxonomic investigation of Ligusticum, was discovered, without affecting the synonymous rate. Although a higher variability was uncovered in hotspot divergence regions that were unevenly distributed across the chloroplast genome, a concatenated strategy for rapid species identification was proposed because separate fragments inadequately provided variation for fine resolution. Phylogenetic inference using plastid genome-scale data produced a concordant topology receiving a robust support value, which revealed that L. chuanxiong had a closer relationship with L. jeholense than L. sinense, and L. sinense cv. Fuxiong had a closer relationship to L. sinense than L. chuanxiong, for the first time. Our results not only furnish concrete evidence for clarifying Ligusticum taxonomy but also provide a solid foundation for further pharmaphylogenetic investigation.


2021 ◽  
Vol 11 (6) ◽  
pp. 2608
Author(s):  
Chien-Hsun Liu ◽  
Willybrordus H. P. Muda ◽  
Cheng-Chien Kuo

A power transformer (PT) in power generation or transmission is critical to maintaining electrical continuity. Fault detection on a PT is needed, especially of incipient faults, which are often caused by a turn-to-turn fault (TTF) before it develops into a more severe fault. We use a hybrid algorithm between conventional and modern techniques to detect a developing fault in a PT. The current response signals from a negative sequence current directional algorithm, extended park vector algorithm (EPVA), differential negative sequence current, and EPVA-fuzzy system are combined to distinguish the possibility of a TTF. The subalgorithms are combined using a hybrid detection algorithm to distinguish the faults. The model is a 10 MVA, three-phase PT with Δ-Y configuration 150/300 kV, simulated using MATLAB Simulink software. The results show that by combining the subalgorithms, several limitations are distinguished within the TTF with a slight increase in accuracy.


Author(s):  
Ashish Singh ◽  
Kakali Chatterjee ◽  
Suresh Chandra Satapathy

AbstractThe Mobile Edge Computing (MEC) model attracts more users to its services due to its characteristics and rapid delivery approach. This network architecture capability enables users to access the information from the edge of the network. But, the security of this edge network architecture is a big challenge. All the MEC services are available in a shared manner and accessed by users via the Internet. Attacks like the user to root, remote login, Denial of Service (DoS), snooping, port scanning, etc., can be possible in this computing environment due to Internet-based remote service. Intrusion detection is an approach to protect the network by detecting attacks. Existing detection models can detect only the known attacks and the efficiency for monitoring the real-time network traffic is low. The existing intrusion detection solutions cannot identify new unknown attacks. Hence, there is a need of an Edge-based Hybrid Intrusion Detection Framework (EHIDF) that not only detects known attacks but also capable of detecting unknown attacks in real time with low False Alarm Rate (FAR). This paper aims to propose an EHIDF which is mainly considered the Machine Learning (ML) approach for detecting intrusive traffics in the MEC environment. The proposed framework consists of three intrusion detection modules with three different classifiers. The Signature Detection Module (SDM) uses a C4.5 classifier, Anomaly Detection Module (ADM) uses Naive-based classifier, and Hybrid Detection Module (HDM) uses the Meta-AdaboostM1 algorithm. The developed EHIDF can solve the present detection problems by detecting new unknown attacks with low FAR. The implementation results illustrate that EHIDF accuracy is 90.25% and FAR is 1.1%. These results are compared with previous works and found improved performance. The accuracy is improved up to 10.78% and FAR is reduced up to 93%. A game-theoretical approach is also discussed to analyze the security strength of the proposed framework.


mSystems ◽  
2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Matthew R. Olm ◽  
Alexander Crits-Christoph ◽  
Spencer Diamond ◽  
Adi Lavy ◽  
Paula B. Matheus Carnevali ◽  
...  

ABSTRACT Longstanding questions relate to the existence of naturally distinct bacterial species and genetic approaches to distinguish them. Bacterial genomes in public databases form distinct groups, but these databases are subject to isolation and deposition biases. To avoid these biases, we compared 5,203 bacterial genomes from 1,457 environmental metagenomic samples to test for distinct clouds of diversity and evaluated metrics that could be used to define the species boundary. Bacterial genomes from the human gut, soil, and the ocean all exhibited gaps in whole-genome average nucleotide identities (ANI) near the previously suggested species threshold of 95% ANI. While genome-wide ratios of nonsynonymous and synonymous nucleotide differences (dN/dS) decrease until ANI values approach ∼98%, two methods for estimating homologous recombination approached zero at ∼95% ANI, supporting breakdown of recombination due to sequence divergence as a species-forming force. We evaluated 107 genome-based metrics for their ability to distinguish species when full genomes are not recovered. Full-length 16S rRNA genes were least useful, in part because they were underrecovered from metagenomes. However, many ribosomal proteins displayed both high metagenomic recoverability and species discrimination power. Taken together, our results verify the existence of sequence-discrete microbial species in metagenome-derived genomes and highlight the usefulness of ribosomal genes for gene-level species discrimination. IMPORTANCE There is controversy about whether bacterial diversity is clustered into distinct species groups or exists as a continuum. To address this issue, we analyzed bacterial genome databases and reports from several previous large-scale environment studies and identified clear discrete groups of species-level bacterial diversity in all cases. Genetic analysis further revealed that quasi-sexual reproduction via horizontal gene transfer is likely a key evolutionary force that maintains bacterial species integrity. We next benchmarked over 100 metrics to distinguish these bacterial species from each other and identified several genes encoding ribosomal proteins with high species discrimination power. Overall, the results from this study provide best practices for bacterial species delineation based on genome content and insight into the nature of bacterial species population genetics.


1993 ◽  
Vol 19 (11) ◽  
pp. 2721-2735 ◽  
Author(s):  
G. Sz�cs ◽  
M. T�th ◽  
W. Francke ◽  
F. Schmidt ◽  
P. Philipp ◽  
...  

Parasitology ◽  
2017 ◽  
Vol 144 (7) ◽  
pp. 954-964 ◽  
Author(s):  
NELE A. M. BOON ◽  
WOUTER FANNES ◽  
SARA ROMBOUTS ◽  
KATJA POLMAN ◽  
FILIP A. M. VOLCKAERT ◽  
...  

SUMMARYHybrid parasites may have an increased transmission potential and higher virulence compared to their parental species. Consequently, hybrid detection is critical for disease control. Previous crossing experiments showed that hybrid schistosome eggs have distinct morphotypes. We therefore compared the performance of egg morphology with molecular markers with regard to detecting hybridization in schistosomes. We studied the morphology of 303 terminal-spined eggs, originating from 19 individuals inhabiting a hybrid zone with natural crosses between the human parasite Schistosoma haematobium and the livestock parasite Schistosoma bovis in Senegal. The egg sizes showed a high variability and ranged between 92·4 and 176·4 µm in length and between 35·7 and 93·0 µm in width. No distinct morphotypes were found and all eggs resembled, to varying extent, the typical S. haematobium egg type. However, molecular analyses on the same eggs clearly showed the presence of two distinct partial mitochondrial cox1 profiles, namely S. bovis and S. haematobium, and only a single nuclear ITS rDNA profile (S. haematobium). Therefore, in these particular crosses, egg morphology appears not a good indicator of hybrid ancestry. We conclude by discussing strengths and limitations of molecular methods to detect hybrids in the context of high-throughput screening of field samples.


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