SEARCH · bioRxiv Science

Results for “bioinformatics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57Linked to original sources

bioRxiv2026

KBase Research Agent: Automated Multi-Agent Workflow Construction for Reproducible Genome Analysis

Constructing multi-step bioinformatics workflows, from read quality control through genome assembly to functional annotation, requires expertise in both biology and computational tool selection, creating a bottleneck for scalable and reproducible analysis. We present the KBase Research Agent, a multi-agent system for automating such workflows within the DOE Systems Biology Knowledgebase (KBase). Given a set of sequencing reads and a research objective, the agent constructs an analysis plan grounded in KBase documentation and a Knowledge Graph (KG) of the KBase application catalog, then selects, parameterizes, validates and executes appropriate KBase applications to carry out the workflow. The resulting analysis is preserved as a reproducible KBase Narrative. We evaluate the systems planning and execution quality against ground truth constructed from reference workflows derived from peer-reviewed Microbiology Resource Announcements. We further apply the agent to 100 previously unanalyzed bacterial isolate genomes from the JGI IMG/M database, where it autonomously performed read quality control, genome assembly, taxonomic classification with GTDB-Tk, and downstream analysis producing annotated genomes, reproducible Narratives, and draft manuscripts without human intervention. Across these experiments, the KBase Research Agent demonstrates the feasibility of domain-grounded, end-to-end scientific workflow automation in a production bioinformatics platform.

bioinformatics↗

bioRxiv2026

DivQuant: Estimation of Species Richness and Entropy from Small Samples

Estimating diversity properties of discrete distributions from a small observed sample is a fundamental problem in algorithmic statistics that has applications in many fields, in particular bioinformatics, but also in ecology or linguistics. The two most common diversity measures are the number of distinct elements in a multiset, also referred to as "species richness" in ecology or "alpha diversity" in microbial analysis, and the Shannon entropy, also referred to as "evenness". Estimating these properties from a small sample is particularly challenging for distributions with many rare elements. Thus, many estimators have been proposed in the past that, in practice, work well for different types of distributions. We present DivQuant, an optimization-based, extrapolating richness and entropy estimator with three contributions. First, we formulate the upsampling problem as a convex quadratic program with a Neyman{chi} 2 objective. Unlike the linear program of its predecessor RichnEst, DivQuant admits confidence intervals via{chi} 2 test inversion that are empirically well-calibrated. Second, we replace RichnEsts fixed-threshold fingerprint truncation with the rare/abundant fingerprint split of Valiant and Valiant, which strongly reduces problem size and preserves enough degrees of freedom for the confidence-interval program to remain valid and feasible. Third, we plug the optimal population fingerprint returned by the program into Shannons entropy formula to obtain an entropy estimate. DivQuant attains close-to-nominal 95% confidence intervals in essentially all tested regimes, including six simulated distribution families, Tara Oceans microbiome data, and 10X Genomics scRNA-seq data, while competing state-of-the-art methods (RichnEst, iNext, PreSeq) miss the true richness in up to 80% of instances, well above the nominal 5%. In addition, DivQuant outperforms classical asymptotic entropy estimators (Miller-Madow, CAE) and the extrapolating iNext estimator. Running times remain competitive, with DivQuant typically completing in seconds. DivQuant is available as a command-line tool at https://gitlab.com/rahmannlab/divquant. 2012 ACM Subject ClassificationMathematics of computing[->] Probability and statistics; Mathematics of computing[->] Linear programming; Mathematics of computing[->] Quadratic programming; Applied computing[->] Bioinformatics

bioinformatics↗

bioRxiv2026

Programmatic access to ICTV virus taxonomy through a public ontology API

The International Committee on Taxonomy of Viruses (ICTV) is responsible for developing and maintaining a universal virus taxonomy. As the reference framework for organising the viral world, it is essential for virology and related fields. Despite its widespread use in research and public health, programmatic access to ICTV taxonomy has remained limited, posing challenges for integration, versioning, and interoperability across databases and bioinformatics resources requiring up-to-date virus taxonomy. To address this, we developed a public and sustainable solution leveraging ontology-based APIs. Successive ICTV Master Species List (MSL) releases were transformed into a structured ontology and deployed as a unified representation through the Ontology Lookup Service (OLS). The framework also provides ICTV-NCBI mappings and helper libraries for integration into downstream systems. This enables, for the first time, public programmatic retrieval of current and historical virological taxon names, taxonomic relationships, metadata, and persistent identifiers through stable endpoints. More broadly, this work illustrates a general strategy for transforming structured biological datasets into semantically enriched graph resources exposed through scalable public APIs. These developments enhance interoperability, reduce manual curation, and support FAIR-aligned taxonomic data management in virology and pandemic preparedness. Key pointsO_LIICTV provides the official taxonomy for classifying viruses and naming virus taxa, but lacks standardised programmatic access. C_LIO_LITransforming ICTV data into an ontology enables semantic, machine-actionable access across releases via ontology-based APIs. C_LIO_LIICTV-NCBI mappings support interoperability across bioinformatics resources. C_LIO_LIThe framework enables programmatic resolution of current and historical viral taxa. C_LIO_LIThis approach provides a reusable model for exposing biological datasets through public APIs. C_LI

bioinformatics↗

bioRxiv2026

Reproducible-by-design: Romics Processor, a FAIR ecosystem for multi-omics and spatial-omics analysis

Multi-omics and spatial-omics technologies are exploding in use, producing increasingly complex datasets. Existing bioinformatics tools are developing rapidly but fail to fully enforce the FAIR principles, leaving the field vulnerable to escalating issues in computational reproducibility. Here, we introduce a reproducible-by-design paradigm represented in an omics data processing package, RomicsProcessor. At its core, the "Romics_object", which is a self-contained digital artifact that encapsulates the full history of the data from the original data to the fully processed state, capturing the details of the transformative steps and the required dependencies. This architecture ensures that computational workflows are fully portable and reproducible. In this manuscript, we demonstrate RomicProcessors computational capabilities and scalability on diverse datasets, including bulk proteomics, large-scale multiplexed immunofluorescence, and multi-batch mass spectrometry imaging. Providing a robust framework for truly FAIR Data Principles-based analysis, RomicsProcessor is a blueprint for the next generation of reproducible bioinformatics tools that can dramatically accelerate discovery in multi-omics biology in the era of artificial intelligence.

bioinformatics↗

bioRxiv2026

PlantAI: A Multi-Agent System for Plant Functional Genomics Analysis and Biological Knowledge Interpretation

Plant functional genomics requires the integration of sequence, expression, evolutionary, regulatory and literature evidence. However, the corresponding analyses are often distributed across disparate programs, scripts and databases, creating substantial barriers to task organization and result interpretation. Here, we present PlantAI, a multi-agent system that integrates bioinformatics analysis, project-level process tracking and knowledge-assisted interpretation. A Main Agent coordinates two complementary routes: an analysis route that invokes bioinformatics tools for RNA-seq and gene-family analyses, and a knowledge route that uses PlantAI-RAG for knowledge retrieval and evidence synthesis. PlantAI-RAG currently contains 31,207 plant-science literature records, comprising approximately 3.82 million normalized entities and 8.25 million literature-supported relation assertions. In an evaluation using plant-science questions, it achieved a Gold evidence-assertion recall of 86.7%, while strict accuracy ranged from 77% to 82% across three independent evaluator models. We further demonstrate an end-to-end task using 24 rice RNA-seq libraries collected under salt stress, spanning transcriptome analysis, candidate-family screening, HXK/HKL family analysis and knowledge-assisted interpretation, and prioritize OsHXK8 for experimental validation. By preserving analysis artifacts, run manifests, logs and environment records, PlantAI supports result verification and repeat execution while linking project-derived results to traceable literature evidence. Together, these capabilities provide an integrated and auditable framework to support plant functional genomics research.

bioinformatics↗

bioRxiv2026

An in-depth, updated benchmark for 16S amplicon sequencing

Amplicon-based techniques provide a rapid and cost-effective approach for profiling microbial communities. However, the observed microbial diversity is influenced by a wide range of factors, encompassing pre-analytical steps such as the choice of primers and target regions, as well as the bioinformatic pipeline, including the selection of tools, reference databases, and parameter settings. Several benchmarks are already available in the literature, but the updates to important tools and databases, namely LotuS3, the Ribosomal Database Project and GreenGenes2, prompted our investigation. In this study, we conducted a comprehensive benchmark of the main bioinformatic tools and databases. Using seven regions for three publicly available mock communities of increasing complexity, we tested 38 possible combinations of sequence resolution algorithms (DADA2 stand-alone, LotuS3 (DADA2/UPARSE)), taxonomic classifiers and search tools (Kraken2, DECIPHER, RDP, MMseqs2, Lambda, and Metaxa2), and databases (SILVA, GreenGenes2, RDP, RefSeq, and Metaxa2). The region V1-V3, coupled with DADA2+MMseqs2+SILVA, DADA2+Metaxa2, or LotuS3 (DADA2)+RDP yielded the highest-quality estimates of the true diversity according to the metrics. We also demonstrated that even certain dominant genera remain difficult to detect, and that the quantification of all genera can be substantially over- or under-estimated, even when using optimal combinations of tools and reference databases.

bioinformatics↗

bioRxiv2026

Continuous Integration and Software Quality in Scientific Software: A Large-Scale Empirical Analysis of GitHub Repositories

Bioinformatics software plays a central role in biological research, yet many academic projects lack robust testing and continuous integration (CI) practices. This absence can compromise reproducibility, accessibility, and long-term maintainability. In this study, we conduct an empirical analysis of GitHub repositories spanning bioinformatics and other scientific software domains to examine the relationship between CI, software testing, and software quality. Repository discovery was performed using domain-specific search terms via GitHub's Application Programming Interface (API). This was followed by a layered data extraction pipeline, which included a Large Language Model (LLM) validation step, that connected repositories to published works, institutions, authors, funding, and citation counts. By integrating repository activity, community engagement, and backlog health into a composite Repository Quality Index (RQI), we find that the presence of CI and software tests is significantly associated with higher repository quality. Additionally, repositories with higher academic citation counts tend to cluster in higher RQI tiers, suggesting that software quality, which is driven by proper testing and integration, is associated with academic impact and funding status. These results demonstrate that adopting industry-standard development practices, such as CI and software testing, is a tractable path toward more sustainable and impactful academic software and funding opportunities.

bioinformatics↗

bioRxiv2015

A targeted subgenomic approach for phylogenomics based on microfluidic PCR and high throughput sequencing

Advances in high-throughput sequencing (HTS) have allowed researchers to obtain large amounts of biological sequence information at speeds and costs unimaginable only a decade ago. Phylogenetics, and the study of evolution in general, is quickly migrating towards using HTS to generate larger and more complex molecular datasets. In this paper, we present a method that utilizes microfluidic PCR and HTS to generate large amounts of sequence data suitable for phylogenetic analyses. The approach uses a Fluidigm microfluidic PCR array and two sets of PCR primers to simultaneously amplify 48 target regions across 48 samples, incorporating sample-specific barcodes and HTS adapters (2,304 unique amplicons per microfluidic array). The final product is a pooled set of amplicons ready to be sequenced, and thus, there is no need to construct separate, costly genomic libraries for each sample. Further, we present a bioinformatics pipeline to process the raw HTS reads to either generate consensus sequences (with or without ambiguities) for every locus in every sample or--more importantly--recover the separate alleles from heterozygous target regions in each sample. This is important because it adds allelic information that is well suited for coalescent-based phylogenetic analyses that are becoming very common in conservation and evolutionary biology. To test our subgenomic method and bioinformatics pipeline, we sequenced 576 samples across 96 target regions belonging to the South American clade of the genus Bartsia L. in the plant family Orobanchaceae. After sequencing cleanup and alignment, the experiment resulted in [~]25,300bp across 486 samples for a set of 48 primer pairs targeting the plastome, and [~]13,500bp for 363 samples for a set of primers targeting regions in the nuclear genome. Finally, we constructed a combined concatenated matrix from all 96 primer combinations, resulting in a combined aligned length of [~]40,500bp for 349 samples.

Evolutionary Biology↗

bioRxiv2015

What’s in my pot? Real-time species identification on the MinION™

Whole genome sequencing on next-generation instruments provides an unbiased way to identify the organisms present in complex metagenomic samples. However, the time-to-result can be protracted because of fixed-time sequencing runs and cumbersome bioinformatics workflows. This limits the utility of the approach in settings where rapid species identification is crucial, such as in the quality control of food-chain components, or in during an outbreak of an infectious disease. Here we present Whats in my Pot? (WIMP), a laboratory and analysis workflow in which, starting with an unprocessed sample, sequence data is generated and bacteria, viruses and fungi present in the sample are classified to subspecies and strain level in a quantitative manner, without prior knowledge of the sample composition, in approximately 3.5 hours. This workflow relies on the combination of Oxford Nanopore Technologies MinION sensing device with a real-time species identification bioinformatics application.

Genomics↗

bioRxiv2015

Progressive lengthening of 3′ untranslated regions of mRNAs by alternative cleavage and polyadenylation in cellular senescence of mouse embryonic fibroblasts

BackgroundCellular senescence has historically been viewed as an irreversible cell cycle arrest that acts to prevent cancer. Recent discoveries demonstrated that cellular senescence also played a vital role in normal embryonic development, tissue renewal and senescence-related diseases. Alternative cleavage and polyadenylation (APA) is an important layer of post-transcriptional regulation, which has been found playing an essential role in development, activation of immune cells and cancer progression. However, the role of APA in the process of cellular senescence remains unclear.\n\nMaterials and MethodsWe applied high-throughput paired-end polyadenylation sequencing (PA-seq) and strand-specific RNA-seq sequencing technologies, combined systematic bioinformatics analyses and experimental validation to investigate APA regulation in different passages of mouse embryonic fibroblasts (MEFs) and in aortic vascular smooth muscle cells of rats (VSMCs) with different ages.\n\nResultsBased on PA-seq, we found that genes in senescent cells tended to use distal pA sites and an independent bioinformatics analysis for RNA-seq drew the same conclusion. In consistent with these global results, both the number of genes significantly preferred to use distal pAs in senescent MEFs and VSMCs were significantly higher than genes tended to use proximal pAs. Interestingly, the expression levels of genes preferred to use distal pAs in senescent MFEs and VSMCs tended to decrease, while genes with single pAs did not show such trend. More importantly, genes preferred to use distal pAs in senescent MFEs and VSMCs were both enriched in common senescence-related pathways, including ubiqutin mediated proteolysis, regulation of actin cytoskeleton, cell cycle and wnt signaling pathway. By cis-elements analyses, we found that the longer 3' UTRs of the genes tended to use distal pAs progressively can introduce more conserved binding sites of senescence-related miRNAs and RBPs. Furthermore, 375 genes with progressive 3' UTR lengthening during MEF senescence tended to use more strong and conserved polyadenylation signal (PAS) around distal pA sites and this was accompanied the observation that expression level of core factors involved in cleavage and polyadenylation complex was decreased.\n\nConclusionsOur finding that genes preferred distal pAs in senescent mouse and rat cells provide new insights for aging cells posttranscriptional gene regulation in the view of alternative polyadenylation given senescence response was thought to be a tumor suppression mechanism and more genes tended to use proximal pAs in cancer cells. In short, APA was a hidden layer of post-transcriptional gene expression regulation involved in cellular senescence.

Genomics↗

bioRxiv2016

Computational Pan-Genomics: Status, Promises and Challenges

Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic datasets. Instead, novel, qualitatively different computational methods and paradigms are needed. We will witness the rapid extension of computational pan-genomics, a new sub-area of research in computational biology. In this paper, we generalize existing definitions and understand a pan-genome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies, and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pan-genomics can help address many of the problems currently faced in various domains.

Genomics↗

bioRxiv2016

A framework to interpret short tandem repeat variation in humans

Identifying regions of the genome that are depleted of mutations can reveal potentially deleterious variants. Short tandem repeats (STRs), also known as microsatellites, are among the largest contributors of de novo mutations in humans and are implicated in a variety of human disorders. However, because of the challenges STRs pose to bioinformatics tools, per-locus studies of STR mutations have been limited to highly ascertained panels of several dozen loci. Here, we harnessed bioinformatics tools and a novel analytical framework to estimate mutation parameters for each STR in the human genome by correlating STR genotypes with local sequence heterozygosity. We applied our method to obtain robust estimates of the impact of local sequence features on mutation parameters and used this to create a framework for measuring constraint at STRs by comparing observed vs. expected mutation rates. Constraint scores identified known pathogenic variants with early onset effects. Our constraint metrics will provide a valuable tool for prioritizing pathogenic STRs in medical genetics studies.

genetics↗

bioRxiv2016

rAmpSeq: Using repetitive sequences for robust genotyping

Repetitive sequences have been used for DNA fingerprinting and genotyping for more than a quarter century. Now, with our knowledge of whole genome sequences, repetitive sequences can be used to identify polymorphisms that can be mapped and scored in a systematic manner. We have developed a simple, robust platform for designing primers, PCR amplification, and high throughput cloning that allows hundreds to thousands of markers to be scored for less than $5 per sample. Conserved regions were used to design PCR primers for amplifying thousands of middle repetitive regions of the maize (Zea mays ssp. mays) genome. Bioinformatic scans were then used to identify DNA sequence polymorphisms in the low copy intervening sequences. When used in conjunction with simple DNA preps, optimized PCR conditions, high multiplex Illumina indexing and a bioinformatic marker calling platform tailored for repetitive sequences, this methodology provides a cost effective genotyping strategy for large-scale genomic selection projects. We show detailed results from four maize primer sets that produced between 1,335-3,225 good coverage loci with 1056 that segregated appropriately in a bi-parental family. This approach could have wide applicability to breeding and conservation biology, where hundreds of thousands of samples need to be genotyped for very minimal cost.

genomics↗

bioRxiv2017

Qinichelins, novel catecholate-hydroxamate siderophores synthesized via a multiplexed convergent biosynthesis pathway

The explosive increase in genome sequencing and the advances in bioinformatic tools have revolutionized the rationale for natural product discovery from actinomycetes. In particular, this has revealed that actinomycete genomes contain numerous orphan gene clusters that have the potential to specify many yet unknown bioactive specialized metabolites, representing a huge unexploited pool of chemical diversity. Here, we describe the discovery of a novel group of catecholate-hydroxamate siderophores termed qinichelins (2-5) from Streptomyces sp. MBT76. Correlation between the metabolite levels and the protein expression profiles identified the biosynthetic gene cluster (BGC; named qch) most likely responsible for qinichelin biosynthesis. The structure of the molecules was elucidated by bioinformatics, mass spectrometry and NMR. Synthesis of the qinichelins requires the interplay between four gene clusters, for its synthesis and for precursor supply. This biosynthetic complexity provides new insights into the challenges scientists face when applying synthetic biology approaches for natural product discovery.\n\nPride repository reviewer account details:\n\nURL: https://www.ebi.ac.uk/pride/archive/login\n\nProject accession: PXD006577\n\nUsername: reviewer35793@ebi.ac.uk\n\nPassword: 3H0iM1FK

microbiology↗

bioRxiv2017

Translated Blast of L Polymerase as a Hit for Novel Arenaviruses Species

Many pathogenic viruses can transmit between human and animals as zoonotic viruses and cause dangerous diseases with obvious clinical signs globally. However, the world deals seriously with these viruses when the viruses infected either human or animals especially if the infection were confirmed that classified as zoonotic (Lal et al. 2005). There are many viruses distribution in many countries around the world including Ebolavirus, Marburgvirus, SARS and MERS coronaviruses, Hendra, Nipah and arenavirus haemorrhagic fever viruses were categorized as zoonotic RNA viruses that cause epidemic in some regions such as African countries (Fichet-Calvet & Rogers 2009) (Ehichioya et al. 2010). Consequently, structural bioinformatics of virus protein like L polymerase of arenaviruses was used for monitor the future outbreak that could be happens by new species of viruses. At this research, significant similarities with hemorrhagic fever viruses including arenaviruses were found on GenBank database. Translated blast (tBLASTn) available on https://blast.ncbi.nlm.nih.gov/Blast.cgi was used for searching translated nucleotide databases using a protein query of arenavirus L polymerase (McGinnis & Madden 2004). At this research, the new and archival metazoan transcriptome sequence data of the new TSA species that available on NCBI was used for identification with arenaviruses genes. Therefore, structure bioinformatics was utilized for better understanding and predication the evolution and natural history of the pools of uncharacterized virus on Genbank database that have led to emerging haemorrhagic fever in near future around the world.

microbiology↗

bioRxiv2017

Evidence-Based Design and Evaluation of a Whole Genome Sequencing Clinical Report for the Reference Microbiology Laboratory

BackgroundMicrobial genome sequencing is now being routinely used in many clinical and public health laboratories. Understanding how to report complex genomic test results to stakeholders who may have varying familiarity with genomics - including clinicians, laboratorians, epidemiologists, and researchers - is critical to the successful and sustainable implementation of this new technology; however, there are no evidence-based guidelines for designing such a report in the pathogen genomics domain. Here, we describe an iterative, human-centered approach to creating a report template for communicating tuberculosis (TB) genomic test results.\n\nMethodsWe used Design Study Methodology - a human centered multi-stage approach drawn from the information visualization domain - to redesign an existing clinical report. We used expert consults and an online questionnaire to discover various stakeholders needs around the types of data and tasks related to TB that they encounter in their daily workflow. We also evaluated their perceptions of and familiarity with genomic data, as well as its utility at various clinical decision points. These data shaped the design of multiple prototype reports that were compared against the existing report through a second online survey, with the resulting qualitative and quantitative data informing the final, redesigned, report.\n\nResultsWe recruited 78 participants, 65 of whom were clinicians, nurses, laboratorians, researchers, and epidemiologists involved in TB diagnosis, treatment, and/or surveillance. Our first survey indicated that participants were largely enthusiastic about genomic data, with the majority agreeing on its utility for certain TB diagnosis and treatment tasks and many reporting some confidence in their ability to interpret this type of data (between 58.8% and 94.1%, depending on the specific data type). When we compared our four prototype reports against the existing design, we found that for the majority (86.7%) of design comparisons, participants preferred the alternative prototype designs over the existing version, and that both clinicians and non-clinicians expressed similar design preferences. Participants articulated clearer design preferences when asked to compare individual design elements versus entire reports. Both the quantitative and qualitative data informed the design of a revised report, which is available online as a LaTeX template.\n\nConclusionsWe show how a human-centered design approach integrating quantitative and qualitative feedback can be used to design an alternative report for representing complex microbial genomic data. We suggest experimental and design guidelines to inform future design studies in the bioinformatics and microbial genomics domains, and suggest that this type of mixed-methods study is important to facilitate the successful translation of pathogen genomics in the clinic, not only for clinical reports but also more complex bioinformatics data visualization software.

genomics↗

bioRxiv2019

Rapid assessment of phytoplankton assemblages using Next Generation Sequencing - Barcode of Life database: a widely applicable toolkit to monitor biodiversity and harmful algal blooms (HABs)

Harmful algal blooms have important implications for the health, functioning and services of aquatic ecosystems. Our ability to detect and monitor these events is often challenged by the lack of rapid and cost-effective methods to identify bloom-forming organisms and their potential for toxin production, Here, we developed and applied a combination of DNA barcoding and Next Generation Sequencing (NGS) for the rapid assessment of phytoplankton community composition with focus on two important indicators of ecosystem health: toxigenic bloom-forming cyanobacteria and impaired planktonic biodiversity. To develop this molecular toolset for identification of cyanobacterial and algal species present in HABs (Harmful Algal Blooms), hereafter called HAB-ID, we optimized NGS protocols, applied a newly developed bioinformatics pipeline and constructed a BOLD (Barcode of Life Data System) 16S reference database from cultures of 203 cyanobacterial and algal strains representing 101 species with particular focus on bloom and toxin producing taxa. Using the new reference database of 16S rDNA sequences and constructed mock communities of mixed strains for protocol validation we developed new NGS primer set which can recover 16S from both cyanobacteria and eukaryotic algal chloroplasts. We also developed DNA extraction protocols for cultured algal strains and environmental samples, which match commercial kit performance and offer a cost-efficient solution for large scale ecological assessments of harmful blooms while giving benefits of reproducibility and increased accessibility. Our bioinformatics pipeline was designed to handle low taxonomic resolution for problematic genera of cyanobacteria such as the Anabaena-Aphanizomenon-Dolichospermum species complex, two clusters of Anabaena (I and II), Planktothrix and Microcystis. This newly developed HAB-ID toolset was further validated by applying it to assess cyanobacterial and algal composition in field samples from waterbodies with recurrent HABs events.

molecular biology↗

bioRxiv2020

Mitochondrial fostering: the mitochondrial genome may play a role in plant orphan gene evolution

Plant mitochondrial genomes exhibit odd evolutionary patterns. They have a high rearrangement but low mutation rate, and a large size. Based on massive mitochondrial DNA transfers to the nucleus as well as the mitochondrial unique evolutionary traits, we propose a "Mitochondrial Fostering" theory where the organelle genome plays an integral role in the arrival and development of orphan genes (genes with no homologues in other lineages). Two approaches were used to test this theory: 1) bioinformatic analysis of nuclear mitochondrial DNA (Numts: mitochondrial originating DNA that has migrated to the nucleus) at the genome level, and 2) bioinformatic analysis of particular orphan sequences present in both the mitochondrial genome and the nuclear genome of Arabidopsis thaliana. One study example is given about one orphan sequence that codes for two unique orphan genes: one in the mitochondrial genome and another one in the nuclear genome. DNA alignments show regions of this A. thaliana orphan sequence exist scattered throughout other land plant mitochondrial genomes. This is consistent with the high recombination rates of mitochondrial genomes in land plants. This may also enable the creation of novel coding sequences within the orphan loci, which can then be transferred to the nuclear genome and become exposed to new evolutionary pressures. Our study also reveals a high correlation between mitochondrial DNA rate transferred to the nuclear genome and number of orphan genes in land plants. All the data suggests the mitochondrial genome may play a role in nuclear orphan gene evolution in land plants.

evolutionary biology↗