A divide-and-conquer phylogenomic approach based on character supermatrices resolves early steps in the evolution of the Archaea

Background The recent rise in cultivation-independent genome sequencing has provided key material to explore uncharted branches of the Tree of Life. This has been particularly spectacular concerning the Archaea, projecting them at the center stage as prominently relevant to understand early stages in evolution and the emergence of fundamental metabolisms as well as the origin of eukaryotes. Yet, resolving deep divergences remains a challenging task due to well-known tree-reconstruction artefacts and biases in extracting robust ancient phylogenetic signal, notably when analyzing data sets including the three Domains of Life. Among the various strategies aimed at mitigating these problems, divide-and-conquer approaches remain poorly explored, and have been primarily based on reconciliation among single gene trees which however notoriously lack ancient phylogenetic signal. Results We analyzed sub-sets of full supermatrices covering the whole Tree of Life with specific taxonomic sampling to robustly resolve different parts of the archaeal phylogeny in light of their current diversity. Our results strongly support the existence and early emergence of two main clades, Cluster I and Cluster II, which we name Ouranosarchaea and Gaiarchaea, and we clarify the placement of important novel archaeal lineages within these two clades. However, the monophyly and branching of the fast evolving nanosized DPANN members remains unclear and worth of further study. Conclusions We inferred a well resolved rooted phylogeny of the Archaea that includes all recently described phyla of high taxonomic rank. This phylogeny represents a valuable reference to study the evolutionary events associated to the early steps of the diversification of the archaeal domain. Beyond the specifics of archaeal phylogeny, our results demonstrate the power of divide-and-conquer approaches to resolve deep phylogenetic relationships, which should be applied to progressively resolve the entire Tree of Life.

ModelRevelator: Fast phylogenetic model estimation via deep learning

Selecting the best model of sequence evolution for a multiple sequence alignment (MSA) constitutes the first step of phylogenetic tree reconstruction. Common approaches for inferring nucleotide models typically apply maximum likelihood (ML) methods, with discrimination between models determined by one of several information criteria. This requires tree reconstruction and optimisation which can be computationally expensive. We demonstrate that neural networks can be used to perform model selection, without the need to reconstruct trees, optimise parameters, or calculate likelihoods. We introduce ModelRevelator, a model selection tool underpinned by two deep neural networks. The first neural network, NNmodelfind, recommends one of six commonly used models of sequence evolution, ranging in complexity from JC to GTR. The second, NNalphafind, recommends whether or not a Γ--distributed rate heterogeneous model should be incorporated, and if so, provides an estimate of the shape parameter, ɑ. Users can simply input an MSA into ModelRevelator, and swiftly receive output recommending the evolutionary model, inclusive of the presence or absence of rate heterogeneity, and an estimate of ɑ. We show that ModelRevelator performs comparably with likelihood-based methods over a wide range of parameter settings, with significant potential savings in computational effort. Further, we show that this performance is not restricted to the alignments on which the networks were trained, but is maintained even on unseen empirical data. ModelRevelator will be made freely available in the forthcoming version of IQ-Tree (http://www.iqtree.org), and we expect it will provide a valuable alternative for phylogeneticists, especially where traditional methods of model selection are computationally prohibitive.

ClusTRace, a bioinformatic pipeline for analyzing clusters in virus phylogenies

Summary: SARS-CoV-2 is the highly transmissible etiologic agent of coronavirus disease 2019 (COVID-19) and has become a global scientific and public health challenge since December 2019. Several new variants of SARS-CoV-2 have emerged globally raising concern about prevention and treatment of COVID-19. Early detection and in depth analysis of the emerging variants allowing pre-emptive alert and mitigation efforts are thus of paramount importance. Here we present ClusTRace, a novel bioinformatic pipeline for a fast and scalable analysis of sequence clusters or clades in large viral phylogenies. ClusTRace offers several high level functionalities including outlier filtering, aligning, phylogenetic tree reconstruction, cluster or clade extraction, variant calling, visualization and reporting. ClusTRace was developed as an aid for COVID-19 transmission chain tracing in Finland and the main emphasis has been on fast and unsupervised screening of phylogenies for markers of super-spreading events and other features of concern, such as high rates of cluster growth and/or accumulation of novel mutations. Availability: All code is freely available from https://bitbucket.org/plyusnin/clustrace/

Genetic structure and phylogenetic relationships of Phyllidiellapustulosa species from Seribu Islands, North Sulawesi, Halmahera, and West Papua

Phyllidiella pustulosa are brightly coloured gastropod molluscs frequently found in coral reefs of the tropical Indo-Pacific. Phyllidiella pustulosa is widely distributed in Indonesia, such as Seribu Island, North Sulawesi, West Papua, and Halmahera. Based on the genetic characteristics of an individual’s DNA sequence, differences between species can be identified. In this paper, we would like to provide the molecular analysis and phylogenetic relationship among nudibranchs from Indonesian waters. Identification was made by measuring the genetic distance between species. The phylogenetic tree reconstruction was made using the Kimura 2-parameter model with 1000 times bootstrap with neighbor-joining and maximum likelihood method. There is 46 DNA Sequence obtained from 4 different regions (Seribu Island, Halmahera, North Sulawesi, and West Papua). The genetic distance of West Papua and Halmahera has the smallest value among other populations, which is between 0.0051-1.4629, compared to the population in Halmahera. The phylogenetic tree also shows populations from West Papua and Halmahera are on the same lineage, indicating that the population in West Papua and Halmahera had the closest relation. The study suggested that North Sulawesi, Halmahera and West Papua have genetic mixing of the same region, which is distinctive from Seribu Island.

RDAClone: Deciphering Tumor Heterozygosity through Single-Cell Genomics Data Analysis with Robust Deep Autoencoder

Rapid advances in single-cell genomics sequencing (SCGS) have allowed researchers to characterize tumor heterozygosity with unprecedented resolution and reveal the phylogenetic relationships between tumor cells or clones. However, high sequencing error rates of current SCGS data, i.e., false positives, false negatives, and missing bases, severely limit its application. Here, we present a deep learning framework, RDAClone, to recover genotype matrices from noisy data with an extended robust deep autoencoder, cluster cells into subclones by the Louvain-Jaccard method, and further infer evolutionary relationships between subclones by the minimum spanning tree. Studies on both simulated and real datasets demonstrate its robustness and superiority in data denoising, cell clustering, and evolutionary tree reconstruction, particularly for large datasets.

A mitochondrial genome phylogeny of voles and lemmings (Rodentia: Arvicolinae): Evolutionary and taxonomic implications

Arvicolinae is one of the most impressive placental radiations with over 150 extant and numerous extinct species that emerged since the Miocene in the Northern Hemisphere. The phylogeny of Arvicolinae has been studied intensively for several decades using morphological and genetic methods. Here, we sequenced 30 new mitochondrial genomes to better understand the evolutionary relationships among the major tribes and genera within the subfamily. The phylogenetic and molecular dating analyses based on 11,391 bp concatenated alignment of protein-coding mitochondrial genes confirmed the monophyly of the subfamily. While Bayesian analysis provided a high resolution across the entire tree, Maximum Likelihood tree reconstruction showed weak support for the ordering of divergence and interrelationships of tribal level taxa within the most ancient radiation. Both the interrelationships among tribes Lagurini, Ellobiusini and Arvicolini, comprising the largest radiation and the position of the genus Dinaromys within it also remained unresolved. For the first time complex relationships between genus level taxa within the species-rich tribe Arvicolini received full resolution. Particularly Lemmiscus was robustly placed as sister to the snow voles Chionomys in the tribe Arvicolini in contrast with a long-held belief of its affinity with Lagurini. Molecular dating of the origin of Arvicolinae and early divergences obtained from the mitogenome data were consistent with fossil records. The mtDNA estimates for putative ancestors of the most genera within Arvicolini appeared to be much older than it was previously proposed in paleontological studies.

S-D614G Mutation Reveals the Euro-America and East-Asia Origin SARS-CoV-2 Virus Spread in Indonesia

COVID-19 is a pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. The first case was found in the city of Wuhan, Hubei province, China. The first case in Indonesia was reported in March 2020 and currently there are 0.5 million cases with a death rate of 3.1%. This rapid increase in cases is thought to due to presence of the mutant strain S-D614G, which causes a faster rate of infection and spread. The purpose of this study was to determine the presence of S-D614G mutations in Indonesian samples in order to find the origin of COVID-19 which was spread in Indonesia based on the Spike gene sequences and the RdRp genes from 25 countries, and one control sequence China/Wuhan-Hu-1 obtained from the NCBI and GISAID databases. Mutation analysis was carried out through multiple alignments using BioEdit software. Phylogenetic tree reconstruction using MEGA6 software with the Neighbor Joining method. This study found mutation of S-D614G in one Indonesian sample, namely the Indonesian/SBY9 sample along with 23 samples from Europe, America, and Africa. The phylogenetic tree reconstruction confirmed these findings; the mutated samples were closely related to samples from these continents, while the non-mutated Indonesian samples were closely related to sample from East Asia. These findings indicate that the origin of the SARS-CoV-2 virus in Indonesia possibly came from the East Asia cluster and the European-American cluster.

3D Tree Reconstruction in Support of Urban Microclimate Simulation: A Comprehensive Literature Review

The negative climate change induced by rapid urbanization has become a global environmental issue. Numerous studies have been devoted to microclimate regulation functions performed by urban vegetation. Digital city information modeling provides a powerful tool for various simulations and data analytics for the sustainable development of urban areas. However, the method reconstructing urban trees is still in its early stage compared to the relatively mature building modeling. Most prior studies on tree reconstruction focused on retrieving geometric features, while other factors related to urban microclimate simulation were rarely addressed. This paper presents a comprehensive literature review and in-depth analysis covering two distinct research directions in relation to urban microclimate simulation. The first one is set on the identification of key factors related to trees’ impact on urban microclimate. The second one is dedicated to approaches for three-dimensional (3D) tree reconstruction. Based on the findings, the paper identifies information including trees’ geometric, physiological characteristics and relation to the surroundings required for 3D tree reconstruction in the context of urban microclimate simulation, and further assesses the potential of the 3D tree reconstruction approaches to accommodate these pieces of information. An appropriate 3D tree reconstruction approach, which allows for the supply of the required information for urban microclimate simulation, is recommended.

Analisis Filogenetik Ikan Tuna (Thunnus spp.) yang didaratkan di Pelabuhan Benoa, Bali

Tuna is one of the largest fisheries commodities in Indonesia after shrimp and demersal fish. The genus Thunnus is a type of tuna that dominates the international market. The genus Thunnus consisted of seven species of tuna. In some cases, the same morphological character has caused misidentification and data collection on tuna species. Therefore, this study aimed to identify tuna species that are landed at Benoa Harbor and analyzed their phylogenetic relationships. Species identification and phylogenetic analysed in this study used the mtDNA control region locus. The results of this study indicated that there are five tuna species landed at Benoa Harbor, namely yellowfin tuna (T. albacares), longtail tuna (T. tonggol), bigeye tuna (T. obesus), southern bluefin tuna (T. maccoyii), and albacore tuna (T. alalunga). Based on phylogenetic tree reconstruction, all samples were divided into five according to the number of tuna species resulted from molecular identification. Reconstruction of phylogenetic trees is supported by genetic distance between clades has a value of 0.075 - 0.212, with the closest kinship found in yellowfin tuna (T. albacares) with bigeye tuna (T. obesus) and the farthest found in yelowfin tuna (T. albacares) with albacore tuna (T. alalunga).