Phylogenetic Tree Reconstruction Research Articles

On the importance of sequence alignment inspections in plastid phylogenomics - an example from revisiting the relationships of the water-lilies.

The water-lily clade represents the second earliest-diverging branch of angiosperms. Most of its species belong to Nymphaeaceae, of which the "core Nymphaeaceae"-comprising the genera Euryale, Nymphaea and Victoria-is the most diverse clade. Despite previous molecular phylogenetic studies on the core Nymphaeaceae, various aspects of their evolutionary relationships have remained unresolved. The length-variable introns and intergenic spacers are known to contain most of the sequence variability within the water-lily plastomes. Despite the challenges with multiple sequence alignment, any new molecular phylogenetic investigation on the core Nymphaeaceae should focus on these noncoding plastome regions. For example, a new plastid phylogenomic study on the core Nymphaeaceae should generate DNA sequence alignments of all plastid introns and intergenic spacers based on the principle of conserved sequence motifs. In this investigation, we revisit the phylogenetic history of the core Nymphaeaceae by employing such an approach. Specifically, we use a plastid phylogenomic analysis strategy in which all coding and noncoding partitions are separated and then undergo software-driven DNA sequence alignment, followed by a motif-based alignment inspection and adjustment. This approach allows us to increase the reliability of the character base compared to the default practice of aligning complete plastomes through software algorithms alone. Our approach produces significantly different phylogenetic tree reconstructions for several of the plastome regions under study. The results of these reconstructions underscore that Nymphaea is paraphyletic in its current circumscription, that each of the five subgenera of Nymphaea is monophyletic, and that the subgenus Nymphaea is sister to all other subgenera of Nymphaea. Our results also clarify many evolutionary relationships within the Nymphaea subgenera Brachyceras, Hydrocallis and Nymphaea. In closing, we discuss whether the phylogenetic reconstructions obtained through our motif-based alignment adjustments are in line with morphological evidence on water-lily evolution.

Conserved DNA sequence analysis reveals the phylogeography and evolutionary events of Akebia trifoliata in the region across the eastern edge of the Tibetan Plateau and subtropical China

BackgroundThe eastern edge of the Qinghai‒Tibet Plateau (QTP) and subtropical China have various regions where plant species originate and thrive, but these regions have been the focus of very few integrative studies. Here, we elucidated the phylogeographic structure of a continuous and widespread Akebia trifoliata population across these two regions.ResultsSixty-one populations consisting of 391 genotypes were examined to assess population diversity and structure via network distribution analysis, maximum likelihood phylogenetic tree reconstruction, divergence time estimation, demographic history inference, and ancestral area reconstruction of both conserved internal transcribed spacer (ITS) and chloroplast (rps16) DNA sequences. The results showed that the ITS region was more variable than the rps16 region and could be suitable for studying intraspecific phylogeography. The A. trifoliata population displayed high genetic diversity, genetic differentiation and obvious phylogeographical structure, possibly originating on the eastern QTP, expanding during the last glacial-interglacial cycle, diverging in the early Pleistocene and middle Pleistocene, and extensively migrating thereafter. The migration route from west to east along rivers could be largely responsible for the long-distance dispersal of this species, while three main refuges (Qinba Mountains, Nanling Mountains and Yunnan-Guizhou Plateau) with multiple ice shelters facilitated its wide distribution.ConclusionsOur results suggested that the from west to east long migration accompanying with the minor short reciprocal migration in the south-north direction, and the three main refuges (the Qinba Mountains, Nanling Mountains and Yunnan-Guizhou Plateau) contributed to the extant geographical distribution of A. trifoliata. In addition, this finding also strongly reduced the discrepancy between glacial contraction and postglacial expansion and the in situ survival hypothesis by simultaneously considering the existence of many similar climate-related ecological niches and migration influences.

Identification of B cell subsets based on antigen receptor sequences using deep learning.

B cell receptors (BCRs) denote antigen specificity, while corresponding cell subsets indicate B cell functionality. Since each B cell uniquely encodes this combination, physical isolation and subsequent processing of individual B cells become indispensable to identify both attributes. However, this approach accompanies high costs and inevitable information loss, hindering high-throughput investigation of B cell populations. Here, we present BCR-SORT, a deep learning model that predicts cell subsets from their corresponding BCR sequences by leveraging B cell activation and maturation signatures encoded within BCR sequences. Subsequently, BCR-SORT is demonstrated to improve reconstruction of BCR phylogenetic trees, and reproduce results consistent with those verified using physical isolation-based methods or prior knowledge. Notably, when applied to BCR sequences from COVID-19 vaccine recipients, it revealed inter-individual heterogeneity of evolutionary trajectories towards Omicron-binding memory B cells. Overall, BCR-SORT offers great potential to improve our understanding of B cell responses.

Diversity of actinomycetes on plant rhizosphere of karst ecosystem of Gorontalo, Indonesia

Abstract. Retnowati Y, Kandowangko NY, Katili AS, Pembengo W. 2024. Diversity of actinomycetes on plant rhizosphere of karst ecosystem of Gorontalo, Indonesia. Biodiversitas 25: 907-915. The objective of this study was to isolate and identify the actinomycetes associated with the rhizosphere of plants in the karst ecosystem. This study was descriptive-quantitative. Soil sampling was conducted at three locations of the karst ecosystem of Gorontalo, i.e., Bangga Hills at Bangga Bubaa Coastal area of Gorontalo District, Hills around Lake Limboto of Gorontalo District, and Oluhuta Beach Hills at Bone Bolango District. Rhizosphere-soil sample was collected from 15-30 cm of soil depth. Isolation of actinomycetes was performed using the plate method. The screening of phosphate-solubilizing bacteria was based on the ability to solubilize phosphates indicated by the clear zone on the Pikovskaya medium. Identification of actinomycetes bacteria based on morphology and molecular characters. The morphology character included the color of aerial and substrate mycelium. Molecular characteristics based on the sequence of 16S rRNA gene compared to sequence data on the gene bank of NCBI. The phylogenetic tree reconstruction was based on the Neighbor-joining algorithm. The results successfully found six isolates, including three actinomycetes isolates, two non-actinomycetes bacteria, and one yeast. They were isolated from the rhizosphere of Malastoma malabathrum, Chromolaena odorata, Cycas rumphii, Leucaena leucocephala, and Jatropha curcas. The actinomycetes isolate showed plant-growth-promoting potential indicated by solubilizing phosphate and Indole 3-Acetic Acid production activities. Based on the molecular analysis, actinomycetes were closely related to Streptomyces aegyptia (MT505707.1:42-1426), Streptomyces sp. GGCR-6 (MH718844.1:5-1391), and Streptomyces carpaticus strain PES-A23 (MH712039).

Multiple evidence reveals two new species and new distributions of Calocybe species (Lyophyllaceae) from northeastern China.

The Calocybe species possess notable economic and medicinal value, demonstrating substantial potential for resource utilization. The taxonomic studies of Calocybe are lacking in quality and depth. Based on the specimens collected from northeast China, this study provides a detailed description of two newly discovered species, namely Calocybebetulicola and Calocybecystidiosa, as well as two commonly found species, Calocybedecolorata and Calocybeionides. Additionally, a previously unrecorded species, C.decolorata, has recently been discovered in Jilin Province, China. The two newly discovered species can be accurately distinguished from other species within the genus Calocybe based on their distinct morphological characteristics. The primary distinguishing features of C.betulicola include its grayish-purple pileus, grayish-brown to dark purple stipe, smaller basidiomata, absence of cellular pileipellis, and its habitat on leaf litter within birch forests. Calocybecystidiosa is distinguished by its growth on the leaf litter of coniferous forests, a flesh-pink pileus, a fibrous stipe with a white tomentose covering at the base, non-cellular pileipellis, larger basidiospores, and the presence of cheilocystidia. The reconstruction of phylogenetic trees using combined ITS, nLSU, and tef1-α sequences, employing maximum likelihood and Bayesian inference analyses, showed that C.betulicola formed a cluster with C.decurrens, while C.cystidiosa clustered with C.vinacea. However, these two clusters formed separate branches themselves, which also supported the results obtained from our morphological studies. A key to the Calocybe species reported from northeast China is provided to facilitate future studies of the genus.

Learning From an Artificial Neural Network in Phylogenetics.

We show that an iterative ansatz of deep learning and human intelligence guided simplification may lead to surprisingly simple solutions for a difficult problem in phylogenetics. Distinguishing Farris and Felsenstein trees is a longstanding problem in phylogenetic tree reconstruction. The Artificial Neural Network F-zoneNN solves this problem for 4-taxon alignments evolved under the Jukes-Cantor model. It distinguishes between Farris and Felsenstein trees, but owing to its complexity, lacks transparency in its mechanism of discernment. Based on the simplification of F-zoneNN and alignment properties we constructed the function FarFelDiscerner. In contrast to F-zoneNN, FarFelDiscerner's decision process is understandable. Moreover, FarFelDiscerner is significantly simpler than F-zoneNN. Despite its simplicity this function infers the tree-type almost perfectly on noise-free data, and also performs well on simulated noisy alignments of finite length. We applied FarFelDiscerner to the historical Holometabola alignments where it places Strepsiptera with beetles, concordant with the current scientific view.

NewickTreeModifier: A simple web tool to prune and modify Newick trees.

Large-scale selection analyses of protein-coding sequences and phylogenetic tree reconstructions require suitable trees in Newick format. We developed the NewickTreeModifier (NTM), a simple web-based tool to trim and modify Newick trees for such analyses. The users can choose provided master trees or upload a tree to prune it to selected species available in FASTA, NEXUS, or PHYLIP sequence format with an internal converter, a simple species list, or directly determined from a checklist interface of the master trees. Plant, insect, and vertebrate master trees comprise the maximum number of species in an up-to-date phylogenetic order directly transferable to the pruned Newick outfile. NTM is available at https://retrogenomics.uni-muenster.de/tools/ntm.

Substitution Models of Protein Evolution with Selection on Enzymatic Activity.

Substitution models of evolution are necessary for diverse evolutionary analyses including phylogenetic tree and ancestral sequence reconstructions. At the protein level, empirical substitution models are traditionally used due to their simplicity, but they ignore the variability of substitution patterns among protein sites. Next, in order to improve the realism of the modeling of protein evolution, a series of structurally constrained substitution models were presented, but still they usually ignore constraints on the protein activity. Here, we present a substitution model of protein evolution with selection on both protein structure and enzymatic activity, and that can be applied to phylogenetics. In particular, the model considers the binding affinity of the enzyme-substrate complex as well as structural constraints that include the flexibility of structural flaps, hydrogen bonds, amino acids backbone radius of gyration, and solvent-accessible surface area that are quantified through molecular dynamics simulations. We applied the model to the HIV-1 protease and evaluated it by phylogenetic likelihood in comparison with the best-fitting empirical substitution model and a structurally constrained substitution model that ignores the enzymatic activity. We found that accounting for selection on the protein activity improves the fitting of the modeled functional regions with the real observations, especially in data with high molecular identity, which recommends considering constraints on the protein activity in the development of substitution models of evolution.

Halomonas citrativorans sp. nov., Halomonas casei sp. nov. and Halomonas colorata sp. nov., isolated from French cheese rinds.

Eight Gram-stain-negative bacterial strains were isolated from cheese rinds sampled in France. On the basis of 16S rRNA gene sequence analysis, all isolates were assigned to the genus Halomonas. Phylogenetic investigations, including 16S rRNA gene studies, multilocus sequence analysis, reconstruction of a pan-genome phylogenetic tree with the concatenated core-genome content and average nucleotide identity (ANI) calculations, revealed that they constituted three novel and well-supported clusters. The closest relative species, determined using the whole-genome sequences of the strains, were Halomonas zhanjiangensis for two groups of cheese strains, sharing 82.4 and 93.1 % ANI, and another cluster sharing 92.2 % ANI with the Halomonas profundi type strain. The strains isolated herein differed from the previously described species by ANI values <95 % and several biochemical, enzymatic and colony characteristics. The results of phenotypic, phylogenetic and chemotaxonomic analyses indicated that the isolates belonged to three novel Halomonas species, for which the names Halomonas citrativorans sp. nov., Halomonas casei sp. nov. and Halomonas colorata sp. nov. are proposed, with isolates FME63T (=DSM 113315T=CIRM-BIA2430T=CIP 111880T=LMG 32013T), FME64T (=DSM 113316T=CIRM-BIA2431T=CIP 111877T=LMG 32015T) and FME66T (=DSM 113318T=CIRM-BIA2433T=CIP 111876T=LMG 32014T) as type strains, respectively.

Morpho-anatomical characterization and DNA barcoding of Artemesia vulgaris L.

Artemisia vulgaris L. belongs to Asteraceae, is a herbal plant that has various benefits in the medical field, so that its use in the medical field can be explored optimally, the plant must be thoroughly identified. This study aims to identify A. vulgaris both in terms of descriptive morpho-anatomy and DNA barcoding using BLAST and phylogenetic tree reconstruction. The morpho-anatomical character was observed on root, stem, and leaf. DNA barcoding analysis was carried out through amplification and alignment of the rbcL and matK genes. All studies were conducted on three samples from Taman Husada (Medicinal Plant Garden) Graha Famili Surabaya, Indonesia. The anatomical slide was prepared by the paraffin method. Morphological studies revealed that the leaves of A. vulgaris both on the lower-middle part and on the upper part of the stem have differences, especially in the character of the stipules, petioles, and incisions they have. Meanwhile, from the study of anatomy, A. vulgaris has an anomocytic type of stomata and its distribution is mostly on the ventral part of the leaves. Through the BLAST process and phylogenetic tree reconstruction, the plant sequences being studied are closely related to several species of the genus Artemisia as indicated by a percentage identity above 98% and branch proximity between taxa in the reconstructed phylogenetic tree.

DNA Barcoding of Anchovy in Tuban Regency as Database of Indonesian Marine Genetic Diversity

Anchovy is the main catch and the primary consumption of coastal communities in Indonesia, and its production shows an increase of more than 10% in 2021. Tuban district, in East Java, Indonesia is part of the WPP 712 (Wilayah Pengelolaan Perikanan or Fisheries Management Area) and highly produces anchovies’ fisheries. Anchovy has a small size, making it difficult to identify morphologically. This study aimed to genetically identify anchovy samples obtained from North Java (Tuban) waters. Molecular identification was conducted by utilizing Cytochrome Oxidase Subunit I (COI) gene using jg-HCO and jg-LCO primers. This study observed 12 individual samples with 623 base pair sequence length. Five species were obtained, namely four species of anchovies (Encrasicholina heteroloba, Encrasicholina punctifer, Stolephorus waitei, and Stolephorus insularis) and one species of sardines (Dussumieria elopsoides) with 99.84-100% similarity to NCBI sequences data. Anchovies typically have a streamlined body with a slightly compressed shape. Anchovies have cycloid scales, which are smooth-edged and relatively small, ranging from a few centimeters to around 20 centimeters in length. Some of the genus from the Anchovy group are Encrasicholina and Stolephorus. The phylogenetic tree reconstruction leads into four clades with a genetic distance between clades of 17,9-24,5 %. This research provides methods and data on the genetic diversity of anchovies taxa caught in Tuban, East Java. The findings are expected to support promoting new standards for healthier and more sustainable anchovy stocks in the country. Overall, this study contributes to providing valuable insights for fisheries management and conservation efforts in Indonesia.

Whole-Genome Sequencing Reveals Distinct Mutational Signatures in Multiple Myeloma Patients with African Ancestry Compared with Those of Non-African Ancestry

INTRODUCTION: Improving health outcomes for patients with African ancestry (AA) is a key healthcare aim, but there is uncertainty in whether disparities arise predominantly from socioeconomic differences or from genetic differences in tumor biology. It remains an open question as to whether multiple myeloma (MM) occurring in AA patients has a similar or different spectrum of genomic abberations when compared to patients having European ancestry. To date, studies have suggested that AA have an excess of t(11;14) and a deficiency of TP53 mutations. We have established a series of 302 cases of MM precursor and newly diagnosed MM with whole-genome sequencing (WGS) available that is enriched for self-declared AA or diverse ethnic background. METHODS: In collaboration with the NYGC and Polyethnic-1000 consortium, we sequenced tumor samples to a depth of 60-80X and normal tissue to 30-40X. We a employed bioinformatics pipeline with a consensus mechanism for somatic variant calling, including Mutect2, Strelka2, and VarScan2 for SNVs; Mutect2, Strelka2, VarScan2, and SvABA for InDels; Battenberg and FACETS for CNVs; Manta, SvABA, DELLY2, and IgCaller for SVs. Additionally, an admixture workflow was used to estimate each individual's ancestral lineage using continentally-distinct references, comprising 23 regional populations within 5 super-populations from the 1000 Genomes Project (https://github.com/pblaney/mgp1000). Mutational signature were calculated using the R package mmsig (Rustad et al. Comm. Bio. 2021). RESULTS: Using admixture estimations from 302 patients with high-coverage WGS together with 941 patients from the CoMMpass trial, we identified five clusters corresponding to single dominant genetic ancestries (median proportion &amp;gt;75% assignment to reference super-population), together with a cluster characterized by highly admixed individuals with no dominant genetic ancestry (median proportion &amp;lt;50%). Of the total, 53.0% are in the European dominant (EUR) cluster, 26.5% African dominant (AFR), 8.6% American dominant (AMR), 7.9% highly admixed, 2.0% East Asian dominant (EAS) and South-East Asian dominant (SAS) clusters, respectively. Stratifying patients by their cluster assignment and calculating the frequency of subtype translocations, we show that t(11;14) occurred in 25.8% of EUR patients while in only 14.6% of AFR (p=0.045) and 7.7% of AMR (p=0.05) patients. The frequency of the t(4;14) was more closely distributed, with 15.7% in EUR, 11.5% in AMR, and 11% in AFR clusters. For the acquired somatic mutations, the tumor mutational burden (TMB) was lowest in the AFR cluster 2.21 (median, somatic mutations per Mb), significantly lower by comparison to the EUR cluster at 2.94 (FDR adj. P=4.3x10 -6). The most striking genomic difference was observed when comparing the mutational signatures landscape between AA and the other racial groups. Using WGS, AA had lower SBS1 and SBS5 absolute contribution compared to EUR, and this was largely responsible for the difference in TMB. SBS1 and SBS5 are known to be clock-like signatures, accumulating at a constant rate over time. Because no differences in age, cancer cell fraction, and coverage were observed between AA and EUR, this finding suggest different mutational clock-like rate between AA and EUR. The higher TMB observed in EUR was also driven by the higher APOBEC-mutational activity (SBS2 and SBS13) compared to AA (p=0.05). Interestingly, 72% of all EUR had APOBEC-activity evident, in contrast to 45% of the AA (p=0.001). This difference was confirmed after excluding the MM precursor patients, previously demonstrated to have lower APOBEC-activity (Oben et al. Natur Comm. 2021), and was validated on CoMMpass whole-exomes. CONCLUSIONS: Leveraging one of the largest series of diverse patients with WGS, and integrating genomic data with comprehensive ancestry information, AA MM emerged as biologically different in term of genomic drivers and mutational signatures, suggesting potential differences in etiology and genomic evolution over time. Further analysis will include molecular timing of clonal copy number gains, and reconstruction of phylogenetic trees, with view to improving our understanding of the etiology of MM development across patient genetic backgrounds. FIGURE: Genomic characteristics of myeloma across ancestries. A) Translocation percentage (number per cluster) and B) Tumor mutational burden across clusters.

Genome Sequencing to Discover Drivers of Clonal Expansion in Smoldering Multiple Myeloma

Background Better prediction models are required to identify patients with high-risk smoldering multiple myeloma (SMM) who can benefit from early intervention therapy before progression. Several studies have reported heterogeneity of genetic abnormalities found at the SMM stage, but whether any mutations are sufficient to cause, or instead prevent progression, remains an important open question. We leveraged whole-genome sequencing (WGS) in a large cohort of precursor patients, including repeated assessment over time, to discover drivers of disease growth and monitor malignant transformation to multiple myeloma (MM). Methods WGS was performed on tumor and normal cells from 141 untreated patients with SMM or Monoclonal Gammopathy of Undetermined Significance (MGUS) from the PCROWD study. Moreover, this dataset was combined with genomic data from the literature totaling 1,034 patients with WGS and/or exomes sampled across MM stages for comparative analysis and biomarker discovery. MutSig2CV, GISTIC2, and a novel method for structural variants were used to establish the list of candidate drivers across disease stages, with statistical power to detect myeloma drivers from points mutations found in ≥2% of patients. Longitudinal WGS data were analyzed with the PhylogicNDT suite of tools to characterize clonal competition in treated and untreated patients. Results Patients were followed for a median time of 20 months from the sample date (range: 3 to 78 months), during which 11 progressed. Patients evenly distributed across 20/2/20 stages: 44 Low-Risk (37%), 29 Intermediate-Risk (24%), 47 High-Risk (39%) SMM were combined with 20 MGUS, showing our method is reliable to perform WGS in lower disease burden settings. A validation cohort comprising 61 SMM with a median follow-up time of 36 months (range: 5 to 121), with 22 progressions was used to corroborate our findings. As significant drivers could be specifically enriched among indolent disease (i.e., protective alleles), we ran de novo driver mutation discovery across MM stages. In addition to well-characterized MM drivers ( KRAS, NRAS, etc.), 16 new candidate genes were found significantly mutated, including IKFZ3 (Aiolos), a transcription factor and direct target of degradation with lenalidomide therapy, harboring frameshift and stop-gain mutations in the protein dimerization domain which could affect complete differentiation of plasma cells. Mutants in KRAS found primarily at codons Q61, G12, G13, and A146, were found in all disease risk groups and associated with progression to overt myeloma (Odds Ratio: 6.1, CI95%: [1.4, 27], p=0.01, q&amp;lt;0.1). Next, we investigated genes targeted by copy-number abnormalities and found candidates in four regions with focal gains, including on chr(1q21), chr(8q24)( MYC), chr(3q26), and chr(16p13) encompassing BCMA. These genes have higher expression in patients with broad gain (e.g. BCMA: P=8.8E-3) or focal amplification (e.g. BCMA: P=6.2E-5), and therefore are likely to be underlying targets of the rearrangements driving cancer growth. Of note, BCMA antigen point mutations remained undetected in SMM, therefore patients with gain(16p) represent an attractive population for targeted therapy with anti-BCMA agents, in particular when the gain is clonal (n=3/8, 38%). In 15 patients, serial sampling of tumor cells allowed longitudinal WGS analyses and reconstruction of phylogenetic trees of disease clones (2 to 3 timepoints, 4 progressors, median 14 months). Maintenance of the major clone with subclonal structure evolving over time was confirmed in all patients, and we observed a steady increase in the cancer cell fraction of known MM mutations (del(13q), KRAS, DIS3 loss of function) in untreated patients. In one patient receiving early interventional treatment, a 70% reduction of M-spike concentration was achieved after four cycles of therapy; however, partial response was found in tandem with the selection of a high-risk del(1p) and of a KRAS activating G12S mutation, before increase and clinical progression to MM. Conclusion These results highlight the power of genomic profiling in MM for early detection, discovery of novel drivers, monitoring of clonal selection and transformation to malignant disease. We show SMM is not a simple genomically-mature disorder, but rather a dynamic state with competing subclones, which could be leveraged for therapeutic interventions.

Evolutionary history and systematics of European blind mole rats (Rodentia: Spalacidae: Nannospalax): Multilocus phylogeny and species delimitation in a puzzling group

Species delimitation is a powerful approach to assist taxonomic decisions in challenging taxa where species boundaries are hard to establish. European taxa of the blind mole rats (genus Nannospalax) display small morphological differences and complex chromosomal evolution at a shallow evolutionary divergence level. Previous analyses led to the recognition of 25 ‘forms’ in their distribution area. We provide a comprehensive framework to improve knowledge on the evolutionary history and revise the taxonomy of European blind mole rats based on samples from all but three of the 25 forms. We sequenced two nuclear-encoded genetic regions and the whole mitochondrial cytochrome b gene for phylogenetic tree reconstructions using concatenation and coalescence-based species-tree estimations. The phylogenetic analyses confirmed that Aegean N. insularis belongs to N. superspecies xanthodon, and that it represents the second known species of this superspecies in Europe. Mainland taxa reached Europe from Asia Minor in two colonisation events corresponding to two superspecies-level taxa: N. superspecies monticola (taxon established herewith) reached Europe c. 2.1 million years ago (Mya) and was followed by N. superspecies leucodon (re-defined herewith) c. 1.5 Mya. Species delimitation allowed the clarification of the taxonomic contents of the above superspecies. N. superspecies monticola contains three species geographically confined to the western periphery of the distribution of blind mole rats, whereas N. superspecies leucodon is more speciose with six species and several additional subspecies. The observed geographic pattern hints at a robust peripatric speciation process and rapid chromosomal evolution. The present treatment is thus regarded as the minimum taxonomic content of each lineage, which can be further refined based on other sources of information such as karyological traits, crossbreeding experiments, etc. The species delimitation models also allowed the recognition of a hitherto unnamed blind mole rat taxon from Albania, described here as a new subspecies.

Comparative sequence analysis elucidates the evolutionary patterns of Yersinia pestis in New Mexico over thirty-two years.

Yersinia pestis, a Gram-negative bacterium, is the causative agent of plague. Y. pestis is a zoonotic pathogen that occasionally infects humans and became endemic in the western United States after spreading from California in 1899. To better understand evolutionary patterns in Y. pestis from the southwestern United States, we sequenced and analyzed 22 novel genomes from New Mexico. Analytical methods included, assembly, multiple sequences alignment, phylogenetic tree reconstruction, genotype-phenotype correlation, and selection pressure. We identified four genes, including Yscp and locus tag YPO3944, which contained codons undergoing negative selection. We also observed 42 nucleotide sites displaying a statistically significant skew in the observed residue distribution based on the year of isolation. Overall, the three genes with the most statistically significant variations that associated with metadata for these isolates were sapA, fliC, and argD. Phylogenetic analyses point to a single introduction of Y. pestis into the United States with two subsequent, independent movements into New Mexico. Taken together, these analyses shed light on the evolutionary history of this pathogen in the southwestern US over a focused time range and confirm a single origin and introduction into North America.

Impacts of climate change on herpetofauna diversity in the Qinghai-Tibetan Plateau.

Although numerous studies on the impacts of climate change on biodiversity have been published, only a handful are focused on the intraspecific level or consider population-level models (separate models per population). We endeavored to fill this knowledge gap relative to the Qinghai-Tibetan plateau (QTP) by combining species distribution modeling (SDMs) with population genetics (i.e., population-level models) and phylogenetic methods (i.e., phylogenetic tree reconstruction and phylogenetic diversity analyses). We applied our models to 11 endemic and widely distributed herpetofauna species inhabiting high elevations in the QTP. We aimed to determine the influence of environmental heterogeneity on species' responses to climate change, the magnitude of climate-change impacts on intraspecific diversity, and the relationship between species range loss and intraspecific diversity losses under 2 shared socioeconomic pathways (SSP245 and SSP585) and 3 future periods (2050s, 2070s, and 2090s). The effects of global climatic change were more pronounced at the intraspecific level (22% of haplotypes lost and 36% of populations lost) than the morphospecies level in the SSP585 climate change scenario. Maintenance of genetic diversity was in general determined by a combination of factors including range changes, species genetic structure, and the part of the range predicted to be lost. This is owing to the fact that the loss and survival of populations were observed in species irrespective of the predicted range changes (contraction or expansion). In the southeast (mountainous regions), climate change had less of an effect on range size (>100% in 3 species) than in central and northern QTP plateau regions (range size <100% in all species). This may be attributed to environmental heterogeneity, which provided pockets of suitable climate in the southeast, whereas ecosystems in the north and central regions were homogeneous. Generally, our results imply that mountainous regions with high environmental heterogeneity and high genetic diversity may buffer the adverse impacts of climate change on species distribution and intraspecific diversity. Therefore, genetic structure and characteristics of the ecosystem may be crucial for conservation under climate change.

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 Jukes and Cantor to General Time Reversible. 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 and the recently published machine learning method ModelTeller 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. We expect that ModelRevelator will provide a valuable alternative for phylogeneticists, especially where traditional methods of model selection are computationally prohibitive.

Analysis of the Conservation Status, Genetic Diversity and Population Structure of Endangered Ostrya rehderiana Resources Using SSR Markers

Climate change and anthropogenic habitat destruction have led to the extinction of many species. Ostrya rehderiana (Betulaceae) is a typical rare and endangered species, and only five wild individuals have survived. In the 1980s, the offspring of the five wild trees were planted for ex situ conservation and have grown into stable cultivated populations. To protect O. rehderiana resources, the genetic diversity and genetic structure of this species were analysed using SSR markers. A total of 167 alleles were detected among 116 individuals from the only wild population and five cultivated populations at 12 SSR loci. The genetic diversity level of O. rehderiana was He = 0.88. Genetic differentiations occurred among populations (Fst = 0.17), which was also validated via an analysis of molecular variance (AMOVA). The cultivated populations TM1, TM2 and WC showed considerable genetic differences from the wild population WP based on Bayesian clustering analysis, phylogenetic tree reconstruction and principal coordinate analysis (PCoA). The cultivated populations had more genetic diversity than the wild one. It is speculated that novel alleles may have emerged out of natural processes of evolution and adaptation. The cultivated population QY with the most unique alleles has begun to propagate seedlings naturally, and the small population size and geographical isolation may negatively influence the founding of this population. To weaken the effects of bottlenecks and genetic drift, anthropogenic gene flow among populations is necessary. In addition to the wild population, the cultivated population QY and six individuals from populations QY and WC were also found to be important for the conservation of O. rehderiana. The results of this study may guide the development of conservation policies for endangered O. rehderiana.

Phylogenetic and comparative analyses of Hydnora abyssinica plastomes provide evidence for hidden diversity within Hydnoraceae

BackgroundTo date, plastid genomes have been published for all but two holoparasitic angiosperm families. However, only a single or a few plastomes represent most of these families. Of the approximately 40 genera of holoparasitic angiosperms, a complete plastid genome sequence is available for only about half. In addition, less than 15 species are currently represented with more than one published plastid genome, most of which belong to the Orobanchaceae. Therefore, a significant portion of the holoparasitic plant plastome diversity remains unexplored. This limited information could hinder potential evolutionary pattern recognition as well as the exploration of inter- and intra-species plastid genome diversity in the most extreme holoparasitic angiosperms.ResultsHere, we report the first plastomes of Kenyan Hydnora abyssinica accessions. The plastomes have a typical quadripartite structure and encode 24 unique genes. Phylogenetic tree reconstruction recovers the Kenyan accessions as monophyletic and together in a clade with the Namibian H. abyssinica accession and the recently published H. arabica from Oman. Hydnora abyssinica as a whole however is recovered as non-monophyletic, with H. arabica nested within. This result is supported by distinct structural plastome synapomorphies as well as pairwise distance estimates that reveal hidden diversity within the Hydnora species in Africa.ConclusionWe propose to increase efforts to sample widespread holoparasitic species for their plastid genomes, as is the case with H. abyssinica, which is widely distributed in Africa. Morphological reinvestigation and further molecular data are needed to fully investigate the diversity of H. abyssinica along the entire range of distribution, as well as the diversity of currently synonymized taxa.

Designing Weights for Quartet-Based Methods When Data are Heterogeneous Across Lineages

Homogeneity across lineages is a general assumption in phylogenetics according to which nucleotide substitution rates are common to all lineages. Many phylogenetic methods relax this hypothesis but keep a simple enough model to make the process of sequence evolution more tractable. On the other hand, dealing successfully with the general case (heterogeneity of rates across lineages) is one of the key features of phylogenetic reconstruction methods based on algebraic tools. The goal of this paper is twofold. First, we present a new weighting system for quartets (ASAQ) based on algebraic and semi-algebraic tools, thus especially indicated to deal with data evolving under heterogeneous rates. This method combines the weights of two previous methods by means of a test based on the positivity of the branch lengths estimated with the paralinear distance. ASAQ is statistically consistent when applied to data generated under the general Markov model, considers rate and base composition heterogeneity among lineages and does not assume stationarity nor time-reversibility. Second, we test and compare the performance of several quartet-based methods for phylogenetic tree reconstruction (namely QFM, wQFM, quartet puzzling, weight optimization and Willson’s method) in combination with several systems of weights, including ASAQ weights and other weights based on algebraic and semi-algebraic methods or on the paralinear distance. These tests are applied to both simulated and real data and support weight optimization with ASAQ weights as a reliable and successful reconstruction method that improves upon the accuracy of global methods (such as neighbor-joining or maximum likelihood) in the presence of long branches or on mixtures of distributions on trees.