Pairwise Distance Calculation Research Articles

Linearized Wasserstein dimensionality reduction with approximation guarantees

We introduce LOT Wassmap, a computationally feasible algorithm to uncover low-dimensional structures in the Wasserstein space. The algorithm is motivated by the observation that many datasets are naturally interpreted as probability measures rather than points in Rn, and that finding low-dimensional descriptions of such datasets requires manifold learning algorithms in the Wasserstein space. Most available algorithms are based on computing the pairwise Wasserstein distance matrix, which can be computationally challenging for large datasets in high dimensions. Our algorithm leverages approximation schemes such as Sinkhorn distances and linearized optimal transport to speed-up computations, and in particular, avoids computing a pairwise distance matrix. We provide guarantees on the embedding quality under such approximations, including when explicit descriptions of the probability measures are not available and one must deal with finite samples instead. Experiments demonstrate that LOT Wassmap attains correct embeddings and that the quality improves with increased sample size. We also show how LOT Wassmap significantly reduces the computational cost when compared to algorithms that depend on pairwise distance computations.

Kinematic Age of the β-Pictoris Moving Group

Accurate age estimation of nearby young moving groups (NYMGs) is important as they serve as crucial testbeds in various fields of astrophysics, including the formation and evolution of stars and planets, as well as loose stellar associations. The β-Pictoris moving group (BPMG), being one of the closest and youngest NYMGs, has been extensively investigated, and its estimated ages have a wide range from ∼10–25 Myr, depending on the age estimation methods and data used. Unlike other age dating methods, kinematic traceback analysis offers a model-independent age assessment hence the merit in comparing many seemingly discordant age estimates. In this study, we determine the kinematic ages of the BPMG using three methods: probabilistic volume calculation, mean pairwise distance calculation, and covariance matrix analysis. These methods yield consistent results, with estimated ages in the range of 14–20 Myr. Implementing corrections to radial velocities due to gravitational redshift and convectional blueshift increases the ages by ∼2–4 Myr. Conversely, considering data uncertainties decreases the estimated ages by 1–2 Myr. Taken together, our analysis determined the kinematic age of the BPMG to be 16.3−2.1+3.4 Myr. This age is significantly younger than the commonly accepted age of the BPMG (∼24 Myr) determined primarily from the lithium depletion boundary analysis. This younger kinematic age may point to the discrepancy between the luminosity evolution and lithium depletion models or the presence of unaccounted systematic error in the method. This result underscores the necessity for systematic reevaluations of age-dating methods for nearby, young moving groups.

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks

Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site—its constituency—as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions “centered” on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These “specialist” sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

Enhanced security using video summarization for surveillance system using deep LSTM model with K-means clustering technique

For the security of the Society, Video surveillance systems have become an important tool that can help in preventing crime in public or private establishments, leading to more safe and secure environment. With the rise of technology that can handle high volune video data and the need for continuous monitoring for security to citizens, the analysis of the video footages, during security breach attempts has become more challenging. Video summarization can play a crucial role in secure surveillance systems by optimizing the analysis time of the security breach. This research attempts to summarise the important aspects of the original video without losing its context and also optimizes the storage requirement. To achieve the same a unique KM-LSTM based technique has been developed that utilizes deep learning methods to understand links among highlight as well as non-highlight video segments through the use of pairwise distance calculations. A new Deep LSTM model has been used to extract the features from all segments of frames. These extracted features are clustered using k-means clustering. Then, such features are trained using a pairwise deep learning model to get highlight scores as well as leverage the comparative similarity among pairs of the highlight as well as non-highlight segments. At last, video summarization takes place to generate the video summary from the highlight segments only. From the results of these experiments discovering the moments of the user’s major or special interest (namely, highlights) in a video, to generating summarization of videos. The above technique can help in increasing the analysis of Video content and thus achieving a more vigilant and secure society.

Identification of Morphology and Molecular PCR-RAPD Bactrocera spp. in the Location of Red Guava Crops, Deli Serdang District

Various fruit flies are in Indonesia, but only a few species of fruit flies have been found at the red guava plant in Deli Serdang District. Knowing the species of fruit flies are needed to do the proper control. In addition to morphological identification, it is necessary to carry out molecular characterization to obtain accurate results in characterizing species differences. This study aims to identify the fruit fly based on morphology and molecularly PCR-RAPD for mapping the genetic closeness of the relationship between individual fruit flies. Bactrocera morphologically identified at LIPI, namely <em>B. carambolae, B. papayae, B. caudata, B. albistrigata, B. umbrosa, B. curcubitae, B. tau,</em><em> </em>and<em> </em><em>B. kinabalu</em>. For molecular identification PCR-RAPD, shows the dendrogram results from the Neighbor-Joining analysis based on RAPD markers of DNA band characters showing the genetic proximity of eight species divided into three groups of Bactrocera based on their location. The closeness of genetic relationships between individuals was analyzed using Pairwise Distance Calculation which describes the genetic distance between species. The results of Pairwise Distance Calculation ranged from 0.13-0.42. By knowing what species there fruit flies are in red guava plantations in the Deli Serdang district, it can make it easier for farmers to monitor and control fruit flies in red guava plantations.

Clustering biological sequences with dynamic sequence similarity threshold

BackgroundBiological sequence clustering is a complicated data clustering problem owing to the high computation costs incurred for pairwise sequence distance calculations through sequence alignments, as well as difficulties in determining parameters for deriving robust clusters. While current approaches are successful in reducing the number of sequence alignments performed, the generated clusters are based on a single sequence identity threshold applied to every cluster. Poor choices of this identity threshold would thus lead to low quality clusters. There is however little support provided to users in selecting thresholds that are well matched with the input sequences.ResultsWe present a novel sequence clustering approach called ALFATClust that exploits rapid pairwise alignment-free sequence distance calculations and community detection in graph for clusters generation. Instead of a single threshold applied to every generated cluster, ALFATClust is capable of dynamically determining the cut-off threshold for each individual cluster by considering both cluster separation and intra-cluster sequence similarity. Benchmarking analysis shows that ALFATClust generally outperforms existing approaches by simultaneously maintaining cluster robustness and substantial cluster separation for the benchmark datasets. The software also provides an evaluation report for verifying the quality of the non-singleton clusters obtained.ConclusionsALFATClust is able to generate sequence clusters having high intra-cluster sequence similarity and substantial separation between clusters without having users to decide precise similarity cut-off thresholds.

Visual Analysis of Neural Architecture Spaces for Summarizing Design Principles.

Recent advances in artificial intelligence largely benefit from better neural network architectures. These architectures are a product of a costly process of trial-and-error. To ease this process, we develop ArchExplorer, a visual analysis method for understanding a neural architecture space and summarizing design principles. The key idea behind our method is to make the architecture space explainable by exploiting structural distances between architectures. We formulate the pairwise distance calculation as solving an all-pairs shortest path problem. To improve efficiency, we decompose this problem into a set of single-source shortest path problems. The time complexity is reduced from O(kn2N) to O(knN). Architectures are hierarchically clustered according to the distances between them. A circle-packing-based architecture visualization has been developed to convey both the global relationships between clusters and local neighborhoods of the architectures in each cluster. Two case studies and a post-analysis are presented to demonstrate the effectiveness of ArchExplorer in summarizing design principles and selecting better-performing architectures.

Understanding the Genetic Diversity of Picobirnavirus: A Classification Update Based on Phylogenetic and Pairwise Sequence Comparison Approaches

Picobirnaviruses (PBVs) are small, double stranded RNA viruses with an ability to infect a myriad of hosts and possessing a high degree of genetic diversity. PBVs are currently classified into two genogroups based upon classification of a 200 nt sequence of RdRp. We demonstrate here that this phylogenetic marker is saturated, affected by homoplasy, and has high phylogenetic noise, resulting in 34% unsolved topologies. By contrast, full-length RdRp sequences provide reliable topologies that allow ancestralism of members to be correctly inferred. MAFFT alignment and maximum likelihood trees were established as the optimal methods to determine phylogenetic relationships, providing complete resolution of PBV RdRp and capsid taxa, each into three monophyletic groupings. Pairwise distance calculations revealed these lineages represent three species. For RdRp, the application of cutoffs determined by theoretical taxonomic distributions indicates that there are five genotypes in species 1, eight genotypes in species 2, and three genotypes in species 3. Capsids were also divided into three species, but sequences did not segregate into statistically supported subdivisions, indicating that diversity is lower than RdRp. We thus propose the adoption of a new nomenclature to indicate the species of each segment (e.g., PBV-C1R2).

Bioinformatic analysis of multi-drug resistant class 1 integron-coded protein of Citrobacter freundii

Background: The understanding of the secondary structure of the class 1 integron coded protein is necessary to decipher potential drug target and also to infer evolutionary ancestry at the proteomic level. This study was therefore aimed at determining the secondary structure of class 1 integron-coded protein and also to provide information on their evolutionary ancestry.
 Methodology: Five different sequences of Citrobacter freundii with the following accession numbers; KP902625.1, KP902624.1, KP902623.1, KP901093.1 and KP902609.1 were obtained using nucleotide BLAST (http://blast. ncbi.nlm.nih.gov/Blast.cgi) and subjected to evolutionary analysis, pairwise distance calculation, secondary structure and neutrality test using MEGA explorer, Kimura 2 parameter, SOPMA tool and Tajima’s test respectively.
 Results: Results of the NCBI queries revealed significant identity with class 1 integron of the studied Citrobacter freundii. The nucleotide sequence alignment depicted several conserved regions with varying degree of transitions, transversions, insertions, and deletions while the amino acid sequences of the nucleotides showed 42 conserved sites among all the sequences. The secondary structure of the class 1 integron coded protein depicted significant representation of the random coil (43.74±3.24), alpha helix (25.69±6.29) and the extended strands (22.42±2.41) than the beta turns (8.15±1.12). The Tajima’s Neutrality test of five nucleotide sequences of Citrobacter freundii analyzed by considering the first, second and third codons as well as the non-coding regions revealed a total of 127 positions in the final datasets while the Tajima’s Neutrality test was estimated to be -0.1038.
 Conclusion: The study confirmed common evolutionary ancestor for the class 1 integron coded protein found in Citrobacter freundii. Our study also documents the higher representation of random coil, alpha helix and extended strands than the beta turns. The negative value of the Tajima’s neutrality test suggests higher levels of both low and high frequency polymorphisms thus indicating a decrease in the class 1 integron population size and balancing selection
 Keywords: Evolutionary, Protein structure, Class 1 integrons, Citrobacter freundii

A novel data-driven method for structural health monitoring under ambient vibration and high-dimensional features by robust multidimensional scaling

Dealing with the problem of large volumes of high-dimensional features and detecting damage under ambient vibration are critical to structural health monitoring. To address these challenges, this article proposes a novel data-driven method for early damage detection of civil engineering structures by robust multidimensional scaling. The proposed method consists of some simple but effective computational parts including a segmentation process, a pairwise distance calculation, an iterative algorithm regarding robust multidimensional scaling, a matrix vectorization procedure, and a Euclidean norm computation. AutoRegressive Moving Average models are fitted to vibration time-domain responses caused by ambient excitations to extract the model residuals as high-dimensional features. In order to increase the reliability of damage detection and avoid any false alarm, the extreme value theory is considered to determine a reliable threshold limit. However, the selection of an appropriate extreme value distribution is crucial and troublesome. To cope with this limitation, this article introduces the generalized extreme value distribution and its shape parameter for choosing the best extreme value model among Gumbel, Fréchet, and Weibull distributions. The main contributions of this article include developing a novel data-driven strategy for early damage detection and addressing the limitation of using high-dimensional features. Experimental data sets of two well-known civil structures are utilized to validate the proposed method along with some comparative studies. Results demonstrate that the proposed data-driven method in conjunction with the extreme value theory is highly able to detect damage under ambient vibration and high-dimensional features.

MINTyper: an outbreak-detection method for accurate and rapid SNP typing of clonal clusters with noisy long reads.

For detection of clonal outbreaks in clinical settings, we present a complete pipeline that generates a single-nucleotide polymorphisms-distance matrix from a set of sequencing reads. Importantly, the program is able to handle a separate mix of both short reads from the Illumina sequencing platforms and long reads from Oxford Nanopore Technologies’ (ONT) platforms as input. MINTyper performs automated reference identification, alignment, alignment trimming, optional methylation masking, and pairwise distance calculations. With this approach, we could rapidly and accurately cluster a set of DNA sequenced isolates, with a known epidemiological relationship to confirm the clustering. Functions were built to allow for both high-accuracy methylation-aware base-called MinION reads (hac_m Q10) and fast generated lower-quality reads (fast Q8) to be used, also in combination with Illumina data. With fast Q8 reads a higher number of base pairs were excluded from the calculated distance matrix, compared with the high-accuracy methylation-aware Q10 base-calling of ONT data. Nonetheless, when using different qualities of ONT data with corresponding input parameters, the clustering of isolates were nearly identical.

Pelacakkan Molekuler terhadap Hasil Sitaan Karkas Trenggiling pada Perdagangan Ilegal di Indonesia Berbasis Gen Barkode

Illegal trade in pangolins are generally in the form of carcasses, flour, scales, embryos, blood and bones. Therefore, physical tracking and identification are difficult so molecular analysis is needed to identify the specimen precisely. Investigations in the illegal trade of wildlife have benefited greatly from the advancement of DNA forensic techniques. Here, I reconstructed phylogenetic trees from the neighbor-joining analyses based on the CO1 gene sequences from the confiscated carcasses of pangolins. The genetic distance matrix calculations with the Kimura Two-parameter model (K2P) were implemented in the pairwise distance calculation in the Mega (Molecular Evolutionary Genetics Analysis) program version 6.05. I included total 77 sequences of pangolins from confiscated and 92 sequences from GenBank (Manis javanica, Manis sp., Manis pentadactyla, Manis culionensis, Phataginus tricuspis, Phataginus tetradactyla, Smutsia temminckii, and Smutsia gigantea). The results of phylogenetic analysis revealed two clades of Asia and Africa with a genetic distance of 23.85±2.38% and all pangolin haplotypes confiscated identified as a species of Manis javanica. The genetic distance between Manis javanica and Manis culionensis was 3.9 ±0.89%, which it was a sister clade and the farthest genetic distance between Manis culionensis and Smutsia temmickii was 23.19±2.14%. The phylogenetic tree shows the monophyletic clade of pangolins species in the world. Phylogenetic relationships between haplotypes from Manis javanica were confiscated separately into two subclades, namely subclade A1 (19 haplotypes) and A2 (12 haplotypes). The genetic distance in subclade A1 averaged were 0.59±0.14% and subclade A2 were 1.01±0.24%, whereas it was 3.09 ± 0.64% between subclades A1 and A2. Total there were 31 haplotypes showing Manis javanica originating from a different habitat with a wide distribution.

Pelacakkan Molekuler terhadap Hasil Sitaan Karkas Trenggiling pada Perdagangan Ilegal di Indonesia Berbasis Gen Barkode

ABSTRACT Illegal trade in pangolins are generally in the form of carcasses, flour, scales, embryos, blood and bones. Therefore, physical tracking and identification are difficult so molecular analysis is needed to identify the specimen precisely. Investigations in the illegal trade of wildlife have benefited greatly from the advancement of DNA forensic techniques. Here, I reconstructed phylogenetic trees from the neighbor-joining analyses based on the CO1 gene sequences from the confiscated carcasses of pangolins. The genetic distance matrix calculations with the Kimura Two-parameter model (K2P) were implemented in the pairwise distance calculation in the Mega (Molecular Evolutionary Genetics Analysis) program version 6.05. I included total 77 sequences of pangolins from confiscated and 92 sequences from GenBank (Manis javanica, Manis sp., Manis pentadactyla, Manis culionensis, Phataginus tricuspis, Phataginus tetradactyla, Smutsia temminckii, and Smutsia gigantea). The results of phylogenetic analysis revealed two clades of Asia and Africa with a genetic distance of 23.85±2.38% and all pangolin haplotypes confiscated identified as a species of Manis javanica. The genetic distance between Manis javanica and Manis culionensis was 3.9 ±0.89%, which it was a sister clade and the farthest genetic distance between Manis culionensis and Smutsia temmickii was 23.19±2.14%. The phylogenetic tree shows the monophyletic clade of pangolins species in the world. Phylogenetic relationships between haplotypes from Manis javanica were confiscated separately into two subclades, namely subclade A1 (19 haplotypes) and A2 (12 haplotypes). The genetic distance in subclade A1 averaged were 0.59±0.14% and subclade A2 were 1.01±0.24%, whereas it was 3.09 ± 0.64% between subclades A1 and A2. Total there were 31 haplotypes showing Manis javanica originating from a different habitat with a wide distribution. Keywords: Illegal trade, pangolin, gene barcode

First identification of Sapoviruses in wild boar

Sapoviruses (SaVs) are enteric viruses that have been detected in human and animals previously; however, SaVs have not been identified in wild boar yet. Using a metagenomics approach, we identified SaVs in fecal samples of free-living wild boars in Japan for the first time. Six of the 48 specimens identified belonged to one genogroup (G)III, one GV and four GVI SaV sequence reads. We successfully determined complete genome of GV and GVI SaV strains using the long reverse transcription PCR strategy and the 5' rapid amplification of cDNA end method. Phylogenetic tree analysis and pairwise distance calculation revealed that GV SaV detected from wild boar was related to recently assigned GV.5 strains from pig, while GVI SaV was assigned to a new genotype within GVI. Moreover, wild boar may act as a reservoir for transmission of SaVs to the pig population (and vice versa) because GIII, GV, and GVI SaVs were all detected in pigs previously.

Towards Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize-Scale Layer

Recent advances on fine-grained image retrieval prefer learning convolutional neural network (CNN) with specific fullyconnect layer designed loss function for discriminative feature representation. Essentially, such loss should establish a robust metric to efficiently distinguish high-dimensional features within and outside fine-grained categories. To this end, the existing loss functions are defected in two aspects: (a) The feature relationship is encoded inside the training batch. Such a local scope leads to low accuracy. (b) The error is established by the mean square, which needs pairwise distance computation in training set and results in low efficiency. In this paper, we propose a novel metric learning scheme, termed Normalize-Scale Layer and Decorrelated Global Centralized Ranking Loss, which achieves extremely efficient and discriminative learning, i.e., 5× speedup over triplet loss and 12% recall boost on CARS196. Our method originates from the classic softmax loss, which has a global structure but does not directly optimize the distance metric as well as the inter/intra class distance. We tackle this issue through a hypersphere layer and a global centralized ranking loss with a pairwise decorrelated learning. In particular, we first propose a Normalize-Scale Layer to eliminate the gap between metric distance (for measuring distance in retrieval) and dot product (for dimension reduction in classification). Second, the relationship between features is encoded under a global centralized ranking loss, which targets at optimizing metric distance globally and accelerating learning procedure. Finally, the centers are further decorrelated by Gram-Schmidt process, leading to extreme efficiency (with 20 epochs in training procedure) and discriminability in feature learning. We have conducted quantitative evaluations on two fine-grained retrieval benchmark. The superior performance demonstrates the merits of the proposed approach over the state-of-the-arts.

Kajian Genetika untuk Konservasi Badak Sumatera (Dicerorhinus sumatrensis Gloger, 1841)

ABSTRACT The Sumatran rhinoceros is one of the most critically endangered species of large mammals due to habitat loss, fragmentation and illegal hunting so that the population of this species drastically decreased. At present, reproductive problems with a limited population are also a threat and require an appropriate solution. Therefore, data on molecular genetic information is very important as a basis for conservation management in maintaining long-term persistence of this species. Phylogenetic analysis based on sequences of CO1, 12SrRNA, and Cytochrome b gen from mitochondrial DNA genomes using neighbor-joining and genetic distance matrix calculations with the Kimura 2-parameter model (K2P) were implemented in pairwise distance calculations in the Mega (Molecular Evolutionary Genetics Analysis) program version 6.05. The study results show the genetic distance of Sumatran Rhinos from Sumatra and Kalimantan respectively 0.2 ± 0.00%, 0.8 ± 0.4%, and 0%. These results were reconfirmed that the Sumatran Rhino species in Sumatra and Kalimantan were taxonomy is no different. The study of genetic diversity based on D-loop of mitochondrial DNA contained 5 haplotypes, namely haplotypes 1 and 2 originating from the island of Sumatra and haplotypes 3, 4, and 5 originating from the island of Borneo. The genetic distance between individuals in this study ranged from 2.54 ± 1.4%, haplotype diversity (Hd) was 0.8 ± 0.172, nucleotide diversity (Pi) was 0.02269, Fu’s Fs value was 2.523, and Tajima’s test was 0.69497. The positive value (Fu’s Fs and Tajima’s test) indicated low genetic diversity and population expansion in the Sumatran rhino. In the study using 10 microsatellite loci, where the average number of allel/loci in Kalimantan (1.68) was higher than in Sumatra (1.22). Data from this study show that genetic variation between Sumatran rhinoceros from Sumatra and Kalimantan can be used as a basis for alternative that the populations of Sumatra and Borneo be considered as a single management unit. Keywords: Sumateran Rhinoceros, Mitochondrial DNA, Microsatellite

Analysis of genetic distance and phylogenetic relationships of “natural/admixed” and “introgressive” hybridization of Fasciola spp. in Vietnam

Fasciola hepatica, F. gigantica and “intermediate” forms of Fasciola species, are responsible for fascioliasis in ruminant animals and humans in many countries. There are two forms: “natural/admixed” and “introgressive” hybridization. Vietnam is a "hot spot" country, where the “hybrid” Fasciola forms have been found nationwide. Determination of phylogenetic relationships and genetic distance of these hybrid forms with those in family Fasciolidae and class Trematoda (Phyllum Platyhelminthes) is necessary to confirm their taxonomic classification. In this study, we sequenced the ITS1 and ITS2 for discrimination of two kinds of hybrid Fasciola mentioned above. The deduced amino acid sequences of the entire mitochondrial genes, cytochrome b (cob), nicotinamide dehydrogenase 1 (nad1) and cytochrome oxidase 1 (cox1), from two hybrid Fasciola spp. including Fsp-DL11-VN (from buffalo, admixed hybrid), Fsp-FH1-VN (from human, introgressive hybrid) and “pure” F. gigantica (Fgig-T4V-VN, from cattle) were obtained and combined (cob+nad1+cox1). These sequences were used as markers for phylogenetic analysis together with 28 representative isolates/species of Fasciolidae and Trematoda. Genetic distances between 13 isolates/species in the family Fasciolidae have also been determined to accurately account for their species-relationships. As results, pairwise genetic distance calculation showed that the distance rate was only 0.4% – 0.7% between Fasciola spp. hybrids of Vietnam and China, slightly higher, 1.3 – 2.0% with “pure” F. gigantica, whilist this rate was quite high compared with F. hepatica (5.7% – 5.9%), with Fasciolopsis buski (20.6% – 21.0%), and two other fasciolids, Fasciola jacksoni and Fascioloides magna (11.0% – 12.6%). The phylogenetic tree of 31 strains/species showed 5 distinct groups, corresponding to 5 families, ie., Fasciolidae, Echinostomatidae, Echinochasmidae, Heterophyidae, Opisthorchiidae and an outgroup, Schistosomatidae. Two "hybrid" Fasciola species of Vietnam (Fsp-FH1-VN and Fsp-DL11-VN) grouped with the reference "hybrid" Fsp-GHL-CN strain of China; and “pure” Fgig-T4V-VN with the two “pure” F. gigantica, Fgig-Bali-ID (Indonesia) and Fgig-GX-CN (China). These results confirmed that “hybrid” Fasciola spp. were of the maternally inherited mitochondrial lineage from F. gigantica.

BARKODING DNA BURUNG ELANG (FAMILI ACCIPITRIDAE) DI INDONESIA

The cytochrome c oxidase subunit I (COI) gene is a reprensentative of all the protein-coding genes of the mitochondrial DNA genome that has been widely used as an animal species identification tool. In this study, 86 sequences of DNA barcodes of members of the family Accipitridae in Indonesia including Nisaetus bartelsi, Nisaetus cirrhatus, Haliaeetus leucogaster, Spilornis cheela, Haliastur indus, and 11 sequences from Genbank were examined. Each species was confirmed through the Basic Local Alignment Search Tool (BLAST). The construction of phylogeny trees based on COI gene sequences was performed by the Neighbors-joining method where the calculation of the genetic distance matrix with the Kimura 2-parameter model was implemented in pairwise distance calculation in the Mega version 6.05 programe. The results of the analysis showed that the divergence within species ranged from 0 to 0.3% (0.13 ± 0.12%), between species ranged from 1.6 to 18.5% (12.8 ± 3.73%), between genera ranged from 13 to 18.6%, and the average in the Accipitridae Family was 11.8%. Therefore, it could form clusters in each species cohesively and clearly separated between the taxa analyzed.

Baculovirus Kimura two-parameter species demarcation criterion is confirmed by the distances of 38 core gene nucleotide sequences.

Kimura two-parameter nucleotide distance comparisons based on polyhedrin/granulin (polh/gran), late expression factor 8 (lef-8) and late expression factor 9 (lef-9) are a widely applied method for species demarcation for lepidopteran-specific baculoviruses. Baculoviruses are considered to belong to the same species when a pairwise distance threshold of 0.015 is not exceeded and are considered as possibly belonging to the same species with a distance of up to 0.050. In the present work this method was revised and extended for 172 entirely sequenced lepidopteran, hymenopteran and dipteran baculovirus genomes by applying the nucleotide sequences of all 38 known baculovirus core genes for pairwise distance calculations. On the basis of this large dataset, the previously established standard thresholds for baculovirus species demarcation were adjusted for pairwise nucleotide distances estimated from the alignments of all 38 core genes. With the newly applied thresholds for the 38 core-gene dataset, a more sophisticated Kimura two-parameter method was established, avoiding the possible influence of the chimerical polh gene of the Autographa californica multiple nucleopolyhedrovirus. Based on the new dataset, the present classification of baculovirus species was confirmed. Thereby the Kimura two-parameter method for baculovirus demarcation was extended to include the information from all 38 Baculoviridae core genes, which represent the established standard information for baculovirus phylogeny to date.

Molecular Characterization of Bovine Papillomaviruses Obtained From Cattle Cutaneous Warts in Nigeria

Bovine papillomatosis is a benign, self-limiting tumor in cattle that is caused by a wide diverse of bovine papillomaviruses (BPVs 1-23). The disease is of high economic importance to the beef and hide industries in Nigeria. To date, there is no information on the molecular characterization of BPVs in Nigeria. Consequently, we collected cutaneous wart lesions from 31 cows in Ibadan, Nigeria and screened them for BPV using a degenerate primer that amplify partial L1 gene sequence of the virus in PCR. Six samples (19.4%) were positive for bovine papillomavirus. Thereafter, amplicons were purified and sequenced. BLAST search, pairwise sequence alignments, pairwise genetic distance calculations, multiple sequence alignment and phylogenetic analysis revealed the viruses to be bovine papillomavirus-1 belonging to the genus Deltapapillomavirus.