DNA Sequence Datasets Research Articles

The Palaeozoic assembly of the holocephalan body plan far preceded post-Cretaceous radiations into the ocean depths.

Among cartilaginous fishes, Holocephali represents the species-depauperate, morphologically conservative sister to sharks, rays and skates and the last survivor of a once far greater Palaeozoic and Mesozoic diversity. Currently, holocephalan diversity is concentrated in deep-sea species, suggesting that this lineage might contain relictual diversity that now persists in the ocean depths. However, the relationships of living holocephalans to their extinct relatives and the timescale of their diversification remain unclear. Here, we reconstruct the evolutionary history of holocephalans using comprehensive morphological and DNA sequence datasets. Our results suggest that crown holocephalans entered and diversified in deep (below 1000 m) ocean waters after the Cretaceous-Palaeogene mass extinction, contrasting with the hypothesis that this ecosystem has acted as a refugium of ancient cartilaginous fishes. These invasions were decoupled from the evolution of key features of the holocephalan body plan, including crushing dentition, a single frontal clasper, and holostylic jaw suspension, during the Palaeozoic Era. However, these invasions considerably postdated the appearance of extant holocephalan families 150 million years ago during a major period of biotic turnover in oceans termed the Mesozoic Marine Revolution. These results clarify the origins of living holocephalans as the recent diversification of a single surviving clade among numerous Palaeozoic lineages.

An integrative framework reveals widespread gene flow during the early radiation of oaks and relatives in Quercoideae (Fagaceae)

ABSTRACTAlthough the frequency of ancient hybridization across the Tree of Life is greater than previously thought, little work has been devoted to uncovering the extent, timeline, and geographic and ecological context of ancient hybridization. Using an expansive new dataset of nuclear and chloroplast DNA sequences, we conducted a multifaceted phylogenomic investigation to identify ancient reticulation in the early evolution of oaks (Quercus). We document extensive nuclear gene tree and cytonuclear discordance among major lineages of Quercus and relatives in Quercoideae. Our analyses recovered clear signatures of gene flow against a backdrop of rampant incomplete lineage sorting, with gene flow most prevalent among major lineages of Quercus and relatives in Quercoideae during their initial radiation, dated to the Early‐Middle Eocene. Ancestral reconstructions including fossils suggest ancestors of Castanea + Castanopsis, Lithocarpus, and the Old World oak clade probably co‐occurred in North America and Eurasia, while the ancestors of Chrysolepis, Notholithocarpus, and the New World oak clade co‐occurred in North America, offering ample opportunity for hybridization in each region. Our study shows that hybridization—perhaps in the form of ancient syngameons like those seen today—has been a common and important process throughout the evolutionary history of oaks and their relatives. Concomitantly, this study provides a methodological framework for detecting ancient hybridization in other groups.

Multi-Objective Design of DNA-Stabilized Nanoclusters Using Variational Autoencoders With Automatic Feature Extraction.

DNA-stabilized silver nanoclusters (AgN-DNAs) have sequence-tuned compositions and fluorescence colors. High-throughput experiments together with supervised machine learning models have recently enabled design of DNA templates that select for AgN-DNA properties, including near-infrared (NIR) emission that holds promise for deep tissue bioimaging. However, these existing models do not enable simultaneous selection of multiple AgN-DNA properties, and require significant expert input for feature engineering and class definitions. This work presents a model for multiobjective, continuous-property design of AgN-DNAs with automatic feature extraction, based on variational autoencoders (VAEs). This model is generative, i.e., it learns both the forward mapping from DNA sequence to AgN-DNA properties and the inverse mapping from properties to sequence, and is trained on an experimental data set of DNA sequences paired with AgN-DNA fluorescence properties. Experimental testing shows that the model enables effective design of AgN-DNA emission, including bright NIR AgN-DNAs with 4-fold greater abundance compared to training data. In addition, Shapley analysis is employed to discern learned nucleobase patterns that correspond to fluorescence color and brightness. This generative model can be adapted for a range of biomolecular systems with sequence-dependent properties, enabling precise design of emerging biomolecular nanomaterials.

An Efficient Exact Algorithm for Planted Motif Search on Large DNA Sequence Datasets.

DNA motif is the pattern shared by similar fragments in DNA sequences, which plays a key role in regulating gene expression, and DNA motif discovery has become a key research topic. Exact planted ( l, d )-motif search (PMS) is one of the motif discovery approaches, which aims to find from t sequences all the ( l, d )-motifs that are motifs of l length appearing in at least qt sequences with at most d mismatches. The existing exact PMS algorithms are only suitable for small datasets of DNA sequences. The development of high-throughput sequencing technology generates vast amount of DNA sequence data, which brings challenges to solving exact PMS problems efficiently. Therefore, we propose an efficient exact PMS algorithm called PMmotif for large datasets of DNA sequences, after analyzing the time complexity of the existing exact PMS algorithms. PMmotif finds ( l, d )-motifs with strategy by searching the branches on the pattern tree that may contain ( l, d )-motifs. It is verified by experiments that the running time ratio of some existing excellent PMS algorithms to PMmotif is between 14.83 and 58.94. In addition, for the first time, PMmotif can solve the ( 15,5 )and ( 17,6 ) challenge problem instances on large DNA sequence datasets (3000 sequences of length 200) within 24 hours.

NIPT-PG: empowering non-invasive prenatal testing to learn from population genomics through an incremental pan-genomic approach.

Non-invasive prenatal testing (NIPT) is a quite popular approach for detecting fetal genomic aneuploidies. However, due to the limitations on sequencing read length and coverage, NIPT suffers a bottleneck on further improving performance and conducting earlier detection. The errors mainly come from reference biases and population polymorphism. To break this bottleneck, we proposed NIPT-PG, which enables the NIPT algorithm to learn from population data. A pan-genome model is introduced to incorporate variant and polymorphic loci information from tested population. Subsequently, we proposed a sequence-to-graph alignment method, which considers the read mis-match rates during the mapping process, and an indexing method using hash indexing and adjacency lists to accelerate the read alignment process. Finally, by integrating multi-source aligned read and polymorphic sites across the pan-genome, NIPT-PG obtains a more accurate z-score, thereby improving the accuracy of chromosomal aneuploidy detection. We tested NIPT-PG on two simulated datasets and 745 real-world cell-free DNA sequencing data sets from pregnant women. Results demonstrate that NIPT-PG outperforms the standard z-score test. Furthermore, combining experimental and theoretical analyses, we demonstrate the probably approximately correct learnability of NIPT-PG. In summary, NIPT-PG provides a new perspective for fetal chromosomal aneuploidies detection. NIPT-PG may have broad applications in clinical testing, and its detection results can serve as a reference for false positive samples approaching the critical threshold.

A comprehensive framework for the delimitation of species within the Bemisia tabaci cryptic complex, a global pest-species group.

Identifying cryptic species poses a substantial challenge to both biologists and naturalists due to morphological similarities. Bemisia tabaci is a cryptic species complex containing more than 44 putative species; several of which are currently among the world's most destructive crop pests. Interpreting and delimiting the evolution of this species complex has proved problematic. To develop a comprehensive framework for species delimitation and identification, we evaluated the performance of distinct data sources both individually and in combination among numerous samples of the B. tabaci species complex acquired worldwide. Distinct datasets include full mitogenomes, single-copy nuclear genes, restriction site-associated DNA sequencing, geographic range, host speciation, and reproductive compatibility datasets. Phylogenetically, our well-supported topologies generated from threedense molecular markers highlighted the evolutionary divergence of species of the B. tabaci complex and suggested that the nuclear markers serve as a more accurate representation of B. tabaci species diversity. Reproductive compatibility datasets facilitated the identification of at least 17 different cryptic species within our samples. Native geographic range information provides a complementary assessment of species recognition, while the host range datasets provide low rate of delimiting resolution. We further summarized different data performances in species classification when compared with reproductive compatibility, indicating that combination of mtCOI divergence, nuclear markers, geographic range provide a complementary assessment of species recognition. Finally, we represent a model for understanding and untangling the cryptic species complexes based on the evidence from this study and previously published articles.

Abstract 3543: TWNeoDB: A web-based database for tumor neoantigens in the Taiwanese population

Abstract Tumor neoantigens are highly immunogenic. Two types of neoantigens have been reported for their ability to be shared among patients. One is a mutated tumor-specific antigen (mTSA) derived from somatic mutations in tumor cells. The other is an aberrantly expressed TSA (aeTSA), influenced by epigenetic changes or abnormal RNA splicing. Tumor neoantigens can bind with the major histocompatibility complex (MHC) and be recognized by the T cell receptor (TCR). Consequently, they can trigger the immune system to attack cancer cells. Until now, some neoantigen databases have been available, they mostly focus on the Western population and primarily contain peptides derived from mTSAs. In contrast, our database provides peptides not only from mTSA but also from aeTSA with a strong emphasis on the Taiwanese population. Initially, we obtained public sequencing raw data from the NCBI database and employed a neoantigen pipeline for analysis, identifying potential neoantigens. The data collection criteria included samples from Taiwanese individuals, with paired DNA-seq or RNA-seq from both normal and tumor tissues of the same patients. RNA sequencing datasets were utilized to identify aeTSAs and mTSAs, whereas DNA sequencing datasets served for mTSA identification. Additionally, human leukocyte antigen (HLA) genotyping was performed for every sample. The identified peptides were further compared to previously validated data available on IEDB. This data was used to develop a web-based database with several functionalities. Users can search for specific peptides and download relevant data from the website. The website also included data cross-referenced and validated with IEDB. In addition, we incorporated clinically validated peptides capable of stimulating T cells to release cytotoxins or interferons. A machine-learning-based LightGBM model was trained to predict immunogenicity for these peptides through a series of cross-validations based on random data splitting. Users can access comprehensive information on tumor-specific peptides in the online database. We collected sequencing data from 243 patients, spanning five different types of cancer. The predominant HLA genotype is HLA-A*11:01, a common allele in the Taiwanese population. Peptide characteristics, such as hydrophobicity, binding affinity, and binding stability, have been calculated and stored in the database. Notably, the LightGBM model excelled in predicting immunogenicity, achieving an AUC of 0.95 on the training dataset and 0.8 on the testing dataset. Implemented in the online database, this model allows users to forecast their own candidates. The state-of-the-art database serves as a comprehensive platform for gathering Taiwanese-specific neoantigens, contributing to the advancement of personalized cancer vaccines and immunotherapies. Citation Format: Yu-Hsuan Tseng, Chia-Hsin Wu, Chia-Yu Sung, Huang Kevin Chih Yang, Mong-Hsun Tsai, Liang-Chuan Lai, Tzu-Pin Lu, K.S. Clifford Chao, Eric Y. Chuang, Chien-Yueh Lee. TWNeoDB: A web-based database for tumor neoantigens in the Taiwanese population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3543.

Shared phylogeographic patterns and environmental responses of co-distributed soybean pests: Insights from comparative phylogeographic studies of Riptortus pedestris and Riptortus linearis in the subtropics of East Asia

Comparative phylogeographic studies of closely related species sharing co-distribution areas can elucidate the role of shared historical factors and environmental changes in shaping their phylogeographic pattern. The bean bugs, Riptortus pedestris and Riptortus linearis, which both inhabit subtropical regions in East Asia, are recognized as highly destructive soybean pests. Many previous studies have investigated the biological characteristics, pheromones, chemicals and control mechanisms of these two pests, but few studies have explored their phylogeographic patterns and underlying factors. In this study, we generated a double-digest restriction site-associated DNA sequencing (ddRAD-seq) dataset to investigate phylogeographic patterns and construct ecological niche models (ENM) for both Riptortus species. Our findings revealed similar niche occupancies and population genetic structures between the two species, with each comprising two phylogeographic lineages (i.e., the mainland China and the Indochina Peninsula clades) that diverged approximately 0.1 and 0.3 million years ago, respectively. This divergence likely resulted from the combined effects of temperatures variation and geographical barriers in the mountainous regions of Southwest China. Further demographic history and ENM analyses suggested that both pests underwent rapid expansion prior to the Last Glacial Maximum (LGM). Furthermore, ENM predicts a northward shift of both pests into new soybean-producing regions due to global warming. Our study indicated that co-distribution soybean pests with overlapping ecological niches and similar life histories in subtropical regions of East Asia exhibit congruent phylogeographic and demographic patterns in response to shared historical biogeographic drivers.

Reconstructing phylogenetic trees from genome-wide somatic mutations in clonal samples.

Phylogenetic trees are a powerful means to display the evolutionary history of species, pathogens and, more recently, individual cells of the human body. Whole-genome sequencing of laser capture microdissections or expanded stem cells has allowed the discovery of somatic mutations in clones, which can be used as natural barcodes to reconstruct the developmental history of individual cells. Here we describe Sequoia, our pipeline to reconstruct lineage trees from clones of normal cells. Candidate somatic mutations are called against the human reference genome and filtered to exclude germline mutations and artifactual variants. These filtered somatic mutations form the basis for phylogeny reconstruction using a maximum parsimony framework. Lastly, we use a maximum likelihood framework to explicitly map mutations to branches in the phylogenetic tree. The resulting phylogenies can then serve as a basis for many subsequent analyses, including investigating embryonic development, tissue dynamics in health and disease, and mutational signatures. Sequoia can be readily applied to any clonal somatic mutation dataset, including single-cell DNA sequencing datasets, using the commands and scripts provided. Moreover, Sequoia is highly flexible and can be easily customized. Typically, the runtime of the core script ranges from minutes to an hour for datasets with a moderate number (50,000-150,000) of variants. Competent bioinformatic skills, including in-depth knowledge of the R programming language, are required. A high-performance computing cluster (one that is capable of running mutation-calling algorithms and other aspects of the analysis at scale) is also required, especially if handling large datasets.

DNA Barcoding and Fertilization Strategies in Sideritis syriaca subsp. syriaca, a Local Endemic Plant of Crete with High Medicinal Value.

Herein, we applied DNA barcoding for the genetic characterization of Sideritis syriaca subsp. syriaca (Lamiaceae; threatened local Cretan endemic plant) using seven molecular markers of cpDNA. Five fertilization schemes were evaluated comparatively in a pilot cultivation in Crete. Conventional inorganic fertilizers (ChFs), integrated nutrient management (INM) fertilizers, and two biostimulants were utilized (foliar and soil application). Plant growth, leaf chlorophyll fluorescence, and color were assessed and leaf content of chlorophyll, key antioxidants (carotenoids, flavonoids, phenols), and nutrients were evaluated. Fertilization schemes induced distinct differences in leaf shape, altering quality characteristics. INM-foliar and ChF-soil application promoted yield, without affecting tissue water content or biomass partitioning to inflorescences. ChF-foliar application was the most stimulatory treatment when the primary target was enhanced antioxidant contents while INM-biostimulant was the least effective one. However, when the primary target is yield, INM, especially by foliar application, and ChF, by soil application, ought to be employed. New DNA sequence datasets for the plastid regions of petB/petD, rpoC1, psbK-psbI, and atpF/atpH were deposited in the GenBank for S. syriaca subsp. syriaca while the molecular markers rbcL, trnL/trnF, and psbA/trnH were compared to those of another 15 Sideritis species retrieved from the GenBank, constructing a phylogenetic tree to show their genetic relatedness.

PANDA: Processing in Magnetic Random-Access Memory-Accelerated de Bruijn Graph-Based DNA Assembly

In this work, we present an efficient Processing in MRAM-Accelerated De Bruijn Graph-based DNA Assembly platform, named PANDA, based on an optimized and hardware-friendly genome assembly algorithm. PANDA is able to assemble large-scale DNA sequence datasets from all-pair overlaps. We first design a PANDA platform that exploits MRAM as computational memory and converts it to a potent processing unit for genome assembly. PANDA can not only execute efficient bulk bit-wise X(N)OR-based comparison/addition operations heavily required for the genome assembly task but also a full set of 2-/3-input logic operations inside the MRAM chip. We then develop a highly parallel and step-by-step hardware-friendly DNA assembly algorithm for PANDA that only requires the developed in-memory logic operations. The platform is then configured with a novel data partitioning and mapping technique that provides local storage and processing to utilize the algorithm level’s parallelism fully. The cross-layer simulation results demonstrate that PANDA reduces the run time and power by a factor of 18 and 11, respectively, compared with CPU. Moreover, speed-ups of up to 2.5 to 10× can be obtained over other recent processing in-memory platforms to perform the same task, like STT-MRAM, ReRAM, and DRAM.

A global test of hybrid ancestry from genome-scale data.

Methods based on the multi-species coalescent have been widely used in phylogenetic tree estimation using genome-scale DNA sequence data to understand the underlying evolutionary relationship between the sampled species. Evolutionary processes such as hybridization, which creates new species through interbreeding between two different species, necessitate inferring a species network instead of a species tree. A species tree is strictly bifurcating and thus fails to incorporate hybridization events which require an internal node of degree three. Hence, it is crucial to decide whether a tree or network analysis should be performed given a DNA sequence data set, a decision that is based on the presence of hybrid species in the sampled species. Although many methods have been proposed for hybridization detection, it is rare to find a technique that does so globally while considering a data generation mechanism that allows both hybridization and incomplete lineage sorting. In this paper, we consider hybridization and coalescence in a unified framework and propose a new test that can detect whether there are any hybrid species in a set of species of arbitrary size. Based on this global test of hybridization, one can decide whether a tree or network analysis is appropriate for a given data set.

Ultraconserved bacteriophage genome sequence identified in 1300-year-old human palaeofaeces

Bacteriophages are widely recognised as rapidly evolving biological entities. However, knowledge about ancient bacteriophages is limited. Here, we analyse DNA sequence datasets previously generated from ancient palaeofaeces and human gut-content samples, and identify an ancient phage genome nearly identical to present-day Mushuvirus mushu, a virus that infects gut commensal bacteria. The DNA damage patterns of the genome are consistent with its ancient origin and, despite 1300 years of evolution, the ancient Mushuvirus genome shares 97.7% nucleotide identity with its modern counterpart, indicating a long-term relationship between the prophage and its host. In addition, we reconstruct and authenticate 297 other phage genomes from the last 5300 years, including those belonging to unknown families. Our findings demonstrate the feasibility of reconstructing ancient phage genome sequences, thus expanding the known virosphere and offering insights into phage-bacteria interactions spanning several millennia.

Species Delimitation and Exploration of Species Partitions with ASAP and LIMES.

DNA barcoding plays an important role in exploring undescribed biodiversity and is increasingly used to delimit lineages at the species level (see Chap. 4 by Miralles et al.). Although several approaches and programs have been developed to perform species delimitation from datasets of single-locus DNA sequences, such as DNA barcodes, most of these were not initially provided as user-friendly GUI-driven executables. In spite of their differences, most of these tools share the same goal, i.e., inferring de novo a partition of subsets, potentially each representing a distinct species. More recently, a proposed common exchange format for the resulting species partitions (SPART) has been implemented by several of these tools, paving the way toward developing an interoperable digital environment entirely dedicated to integrative and comparative species delimitation. In this chapter, we provide detailed protocols for the use of two bioinformatic tools, one for single locus molecular species delimitation (ASAP) and one for statistical comparison of species partitions resulting from any kind of species delimitation analyses (LIMES).

Sample design in biodiversity studies matters: a fine-scale study of Lawrence's velvet worm, Peripatopsis lawrencei (Onychophora: Peripatopsidae), reveals hidden diversity.

A fine-scale phylogenetic and phylogeographic analysis of Peripatopsis lawrencei s.l. was conducted with both mitochondrial and nuclear DNA sequence data, using both external morphology and scanning electron microscopy of taxonomically important characters. A total of 119 sequences were used for the mitochondrial cytochrome c oxidase subunit I (COI ) whereas a single representative specimen from each locality was sequenced for the nuclear 18S rRNA locus. Phylogenetic analyses were conducted on the total COI data set and the combined COI + 18S rRNA data set using a Bayesian analysis and maximum likelihood analyses. For the combined DNA sequence data set, a divergence time estimation was further undertaken in BEAST and specimens placed in a phylogenetic framework including all the described Peripatopsis species from South Africa. In addition, a phylogeographic study was conducted exclusively on P. lawrencei s.s. (clade A) using an analysis of molecular variance and haplotype network. Phylogenetic results indicated that, at the Oubos sample locality, two highly distinct genetic lineages were present (clades A and B), whereas a divergence time estimation suggests a Miocene cladogenesis of the novel Oubos lineage. Marked phylogeographic structure was observed for P. lawrencei s.s. (restricted to clade A) across the distribution range with limited maternal dispersal. Morphologically, the two sympatric lineages at Oubos A and B differed in leg pair number, ventral colour and dorsal scale rank counts, as evident from scanning electron microscopy. Our results support the recognition of a distinct species that occurs in sympatry with P. lawrencei s.s. The new species, P. aereus sp. nov. (clade B) is described and the implication for fine-scale taxonomic studies on saproxylic taxa is discussed. ZooBank: urn:lsid:zoobank.org:pub:AB6E0BDA-7B5F-4FD3-A863-BA7C814E278C.

Phylogeny, taxonomy, and biogeography of the Sphaeriinae (Bivalvia: Sphaeriidae)

Abstract The subfamily Sphaeriinae is a diverse and ecologically significant group of freshwater invertebrates, playing a keystone role in the energy flow and nutrient cycling in aquatic ecosystems. Despite a long history of its study, the taxonomic structure and species content of this group are a matter of ongoing disputes between malacologists. We clarify the taxonomy, distribution, and evolutionary biogeography of the Sphaeriinae around the world based on the largest dataset of DNA sequences of these clams ever accumulated, which includes the data on specimens collected from various continents and countries around the globe. Our 16S rRNA and two-locus phylogenies reveal that the Sphaeriinae is a monophyletic group, containing at least seven genus-level clades: Sphaerium Scopoli, 1777, Pisidium C. Pfeifffer, 1821 (s.s.), Euglesa Jenyns, 1832, Odhneripisidium Kuiper, 1962, Conventus Pirogov & Starobogatov stat. nov., 1974, ‘Pisidium’ sterkianum group, and Hindupisidium Vinarski & Bespalaya gen. nov. Our 16S rRNA phylogenetic tree contains 80 well-supported clades corresponding to the putative species-level taxa. Four species new to science are described here: Euglesa kolymensis Bespalaya, Aksenova & Bolotovsp. nov., Euglesa kyrgyzica Bespalaya, Aksenova, Kondakov & Palatovsp. nov., Euglesa moroccana Bespalaya, Vinarski, Aksenova, Mabrouki, Kondakov & Palatovsp. nov., Odhneripisidium caucasus Bespalaya, Vinarski, Aksenova, Kondakov & Palatovsp. nov. Our fossil-calibrated phylogeny and generalized biogeographic model indicate that the most recent common ancestor of the Sphaeriidae could have originated somewhere within a broad area covering China near the Lower Cretaceous boundary.

Phylogeography of two codistributed terrestrial snails in the Maputaland–Pondoland–Albany biodiversity hotspot, South Africa

Abstract We investigated the evolutionary patterns of two forest-dwelling endemic terrestrial snails (Gittenedouardia spadicea and Maizania wahlbergi) in the Maputaland–Pondoland–Albany biodiversity hotspot in South Africa to examine the degree of phylogeographical congruence between the two species. Phylogenetic relationships and divergence time estimations within each species were inferred using the combined mitochondrial DNA (mtDNA) sequence dataset for the cytochrome c oxidase subunit I (COI) and large subunit ribosomal RNA (16S rRNA). In addition, the rapidly evolving COI datasets were used to infer intraspecific genetic structure and population differentiation within both species. Phylogeographical concordance factor (PCF) analysis was used to statistically estimate the degree of congruence between the two species at localities where both species were sampled. Phylogenetically, G. spadicea exhibited two clades that diverged during the Plio/Pleistocene, while M. wahlbergi formed a single shallow clade that showed Pleistocene divergence. The haplotype networks for the COI locus demonstrated evidence of geographical and genetic isolation within both species. PCF analysis demonstrated partial phylogeographical concordance, suggesting that the two species may have been affected by similar ancient climatic events. Traits other than poor dispersal capabilities and limited gene flow may also influence how a species responds to fluctuating climate change.

CloneRate: fast estimation of single-cell clonal dynamics using coalescent theory.

While evolutionary approaches to medicine show promise, measuring evolution itself is difficult due to experimental constraints and the dynamic nature of body systems. In cancer evolution, continuous observation of clonal architecture is impossible, and longitudinal samples from multiple timepoints are rare. Increasingly available DNA sequencing datasets at single-cell resolution enable the reconstruction of past evolution using mutational history, allowing for a better understanding of dynamics prior to detectable disease. There is an unmet need for an accurate, fast, and easy-to-use method to quantify clone growth dynamics from these datasets. We derived methods based on coalescent theory for estimating the net growth rate of clones using either reconstructed phylogenies or the number of shared mutations. We applied and validated our analytical methods for estimating the net growth rate of clones, eliminating the need for complex simulations used in previous methods. When applied to hematopoietic data, we show that our estimates may have broad applications to improve mechanistic understanding and prognostic ability. Compared to clones with a single or unknown driver mutation, clones with multiple drivers have significantly increased growth rates (median 0.94 versus 0.25 per year; P = 1.6×10-6). Further, stratifying patients with a myeloproliferative neoplasm (MPN) by the growth rate of their fittest clone shows that higher growth rates are associated with shorter time to MPN diagnosis (median 13.9 versus 26.4 months; P = 0.0026). We developed a publicly available R package, cloneRate, to implement our methods (Package website: https://bdj34.github.io/cloneRate/). Source code: https://github.com/bdj34/cloneRate/.

IDeLUCS: a deep learning interactive tool for alignment-free clustering of DNA sequences.

We present an interactive Deep Learning-based software tool for Unsupervised Clustering of DNA Sequences (iDeLUCS), that detects genomic signatures and uses them to cluster DNA sequences, without the need for sequence alignment or taxonomic identifiers. iDeLUCS is scalable and user-friendly: its graphical user interface, with support for hardware acceleration, allows the practitioner to fine-tune the different hyper-parameters involved in the training process without requiring extensive knowledge of deep learning. The performance of iDeLUCS was evaluated on a diverse set of datasets: several real genomic datasets from organisms in kingdoms Animalia, Protista, Fungi, Bacteria, and Archaea, three datasets of viral genomes, a dataset of simulated metagenomic reads from microbial genomes, and multiple datasets of synthetic DNA sequences. The performance of iDeLUCS was compared to that of two classical clustering algorithms (k-means++ and GMM) and two clustering algorithms specialized in DNA sequences (MeShClust v3.0 and DeLUCS), using both intrinsic cluster evaluation metrics and external evaluation metrics. In terms of unsupervised clustering accuracy, iDeLUCS outperforms the two classical algorithms by an average of ∼20%, and the two specialized algorithms by an average of ∼12%, on the datasets of real DNA sequences analyzed. Overall, our results indicate that iDeLUCS is a robust clustering method suitable for the clustering of large and diverse datasets of unlabeled DNA sequences. iDeLUCS is available at https://github.com/Kari-Genomics-Lab/iDeLUCS under the terms of the MIT licence.

Comparative genomic analysis of 5Mg chromosome of Aegilops geniculata and 5Uu chromosome of Aegilops umbellulata reveal genic diversity in the tertiary gene pool.

Wheat is one of the most important cereal crops for the global food security. Due to its narrow genetic base, modern bread wheat cultivars face challenges from increasing abiotic and biotic stresses. Since genetic improvement is the most sustainable approach, finding novel genes and alleles is critical for enhancing the genetic diversity of wheat. The tertiary gene pool of wheat is considered a gold mine for genetic diversity as novel genes and alleles can be identified and transferred to wheat cultivars. Aegilops geniculata and Ae. umbellulata are the key members of the tertiary gene pool of wheat and harbor important genes against abiotic and biotic stresses. Homoeologous-group five chromosomes (5Uu and 5Mg) have been extensively studied from Ae. geniculata and Ae. umbellulata as they harbor several important genes including Lr57, Lr76, Yr40, Yr70, Sr53 and chromosomal pairing loci. In the present study, using chromosome DNA sequencing and RNAseq datasets, we performed comparative analysis to study homoeologous gene evolution in 5Mg, 5Uu, and group 5 wheat chromosomes. Our findings highlight the diversity of transcription factors and resistance genes, resulting from the differential expansion of the gene families. Both the chromosomes were found to be enriched with the "response to stimulus" category of genes providing resistance against biotic and abiotic stress. Phylogenetic study positioned the M genome closer to the D genome, with higher proximity to the A genome than the B genome. Over 4000 genes were impacted by SNPs on 5D, with 4-5% of those genes displaying non-disruptive variations that affect gene function.