Preclinical evaluation and first-in-dog clinical trials of PBMC-expanded natural killer cells for adoptive immunotherapy in dogs with cancer

BACKGROUND

Natural killer (NK) cells are cytotoxic cells capable of recognizing heterogeneous cancer targets without prior sensitization, making them promising prospects for use in cellular immunotherapy. Companion dogs develop spontaneous cancers in the context of an intact immune system, representing a valid cancer immunotherapy model. Previously, CD5 depletion of peripheral blood mononuclear cells (PBMCs) was used in dogs to isolate a CD5dim-expressing NK subset prior to co-culture with an irradiated feeder line, but this can limit the yield of the final NK product. This study aimed to assess NK activation, expansion, and preliminary clinical activity in first-in-dog clinical trials using a novel system with unmanipulated PBMCs to generate our NK cell product.

METHODS

Starting populations of CD5-depleted cells and PBMCs from healthy beagle donors were co-cultured for 14 days, phenotype, cytotoxicity, and cytokine secretion were measured, and samples were sequenced using the 3'-Tag-RNA-Seq protocol. Co-cultured human PBMCs and NK-isolated cells were also sequenced for comparative analysis. In addition, two first-in-dog clinical trials were performed in dogs with melanoma and osteosarcoma using autologous and allogeneic NK cells, respectively, to establish safety and proof-of-concept of this manufacturing approach.

RESULTS

Calculated cell counts, viability, killing, and cytokine secretion were equivalent or higher in expanded NK cells from canine PBMCs versus CD5-depleted cells, and immune phenotyping confirmed a CD3-NKp46+ product from PBMC-expanded cells at day 14. Transcriptomic analysis of expanded cell populations confirmed upregulation of NK activation genes and related pathways, and human NK cells using well-characterized NK markers closely mirrored canine gene expression patterns. Autologous and allogeneic PBMC-derived NK cells were successfully expanded for use in first-in-dog clinical trials, resulting in no serious adverse events and preliminary efficacy data. RNA sequencing of PBMCs from dogs receiving allogeneic NK transfer showed patient-unique gene signatures with NK gene expression trends in response to treatment.

CONCLUSIONS

Overall, the use of unmanipulated PBMCs appears safe and potentially effective for canine NK immunotherapy with equivalent to superior results to CD5 depletion in NK expansion, activation, and cytotoxicity. Our preclinical and clinical data support further evaluation of this technique as a novel platform for optimizing NK immunotherapy in dogs.

Biogeographic distribution of five Antarctic cyanobacteria using large-scale k-mer searching with sourmash branchwater

Cyanobacteria form diverse communities and are important primary producers in Antarctic freshwater environments, but their geographic distribution patterns in Antarctica and globally are still unresolved. There are however few genomes of cultured cyanobacteria from Antarctica available and therefore metagenome-assembled genomes (MAGs) from Antarctic cyanobacteria microbial mats provide an opportunity to explore distribution of uncultured taxa. These MAGs also allow comparison with metagenomes of cyanobacteria enriched communities from a range of habitats, geographic locations, and climates. However, most MAGs do not contain 16S rRNA gene sequences, making a 16S rRNA gene-based biogeography comparison difficult. An alternative technique is to use large-scale k-mer searching to find genomes of interest in public metagenomes. This paper presents the results of k-mer based searches for 5 Antarctic cyanobacteria MAGs from Lake Fryxell and Lake Vanda, assigned the names Phormidium pseudopriestleyi FRX01, Microcoleus sp. MP8IB2.171, Leptolyngbya sp. BulkMat.35, Pseudanabaenaceae cyanobacterium MP8IB2.15, and Leptolyngbyaceae cyanobacterium MP9P1.79 in 498,942 unassembled metagenomes from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). The Microcoleus sp. MP8IB2.171 MAG was found in a wide variety of environments, the P. pseudopriestleyi MAG was found in environments with challenging conditions, the Leptolyngbyaceae cyanobacterium MP9P1.79 MAG was only found in Antarctica, and the Leptolyngbya sp. BulkMat.35 and Pseudanabaenaceae cyanobacterium MP8IB2.15 MAGs were found in Antarctic and other cold environments. The findings based on metagenome matches and global comparisons suggest that these Antarctic cyanobacteria have distinct distribution patterns ranging from locally restricted to global distribution across the cold biosphere and other climatic zones.

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Acipenserid herpesvirus 2 genome and partial validation of a qPCR for its detection in white sturgeon Acipenser transmontanus

White sturgeon Acipenser transmontanus is the primary species used for caviar and sturgeon meat production in the USA. An important pathogen of white sturgeon is acipenserid herpesvirus 2 (AciHV-2). In this study, 4 archived isolates from temporally discrete natural outbreaks spanning the past 30 yr were sequenced via Illumina and Oxford Nanopore Technologies platforms. Assemblies of approximately 134 kb were obtained for each isolate, and the putative ATPase subunit of the terminase gene was selected as a potential quantitative PCR (qPCR) target based on sequence conservation among AciHV-2 isolates and low sequence homology with other important viral pathogens. The qPCR was repeatable and reproducible, with a linear dynamic range covering 5 orders of magnitude, an efficiency of approximately 96%, an R2 of 0.9872, and an analytical sensitivity of 103 copies per reaction after 35 cycles. There was no cross-reaction with other known viruses or closely related sturgeon species, and no inhibition by sturgeon DNA. Clinical accuracy was assessed from white sturgeon juveniles exposed to AciHV-2 by immersion. Viral culture (gold standard) and qPCR were in complete agreement for both cell culture negative and cell culture positive samples, indicating that this assay has 100% relative accuracy compared to cell culture during an active outbreak. The availability of a whole-genome sequence for AciHV-2 and a highly specific and sensitive qPCR assay for detection of AciHV-2 in white sturgeon lays a foundation for further studies on host-pathogen interactions while providing a specific and rapid test for AciHV-2 in captive and wild populations.

Pluripotency of a founding field: rebranding developmental biology

The field of developmental biology has declined in prominence in recent decades, with off-shoots from the field becoming more fashionable and highly funded. This has created inequity in discovery and opportunity, partly due to the perception that the field is antiquated or not cutting edge. A 'think tank' of scientists from multiple developmental biology-related disciplines came together to define specific challenges in the field that may have inhibited innovation, and to provide tangible solutions to some of the issues facing developmental biology. The community suggestions include a call to the community to help 'rebrand' the field, alongside proposals for additional funding apparatuses, frameworks for interdisciplinary innovative collaborations, pedagogical access, improved science communication, increased diversity and inclusion, and equity of resources to provide maximal impact to the community.

Missing a "Missing Self" Mechanism: Modeling and Detection of Ly49 Expression in Canine NK Cells

NK cells are a key focus in immuno-oncology, based on their ability to eliminate malignant cells without prior sensitization. Dogs are valuable models for translational immunotherapy studies, especially for NK cells, where critical species differences exist between mice and humans. Given that the mechanism for recognition of "self" by canine NK cells is currently unknown, we sought to evaluate expression of Ly49 in canine NK cells using in silico and high-throughput techniques. We interrogated the identified polymorphism/mutation in canine Ly49 and assessed the potential impact on structure using computational modeling of three-dimensional protein structure and protein-protein docking of canine Ly49 with MHC class I (MHC-I). Bulk and single-cell RNA-sequencing analysis was performed to detect gene expression of Ly49/KLRA1 in resting and activated NK cells. Tertiary protein structure demonstrated significant structural similarity to the known murine system. Molecular docking of canine Ly49 with MHC-I was favorable, converging at a single low-energy conformation. RNA sequencing revealed expression of Ly49/KLRA1 in both resting and activated NK cells and demonstrated almost exclusive expression of the gene in the NK cluster at the single-cell level. Despite prior reports of a mutated, nonfunctional canine Ly49, our data support that the protein product is predicted to bind to MHC-I in a comparable conformation to the murine system and is expressed in canine NK cells with upregulation following activation. Taken together, these data suggest that Ly49 is capable of recognizing MHC-I and therefore regulating NK cell function in dogs.

Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets

BACKGROUND

Long-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates.

RESULTS

Our results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing.

CONCLUSIONS

Our critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

Making Common Fund data more findable: catalyzing a data ecosystem

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs' Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs.

genomeRxiv: a microbial whole-genome database and diagnostic marker design resource for classification, identification, and data sharing

genomeRxiv is a newly-funded US-UK collaboration to provide a public, web-accessible database of public genome sequences, accurately catalogued and classified by whole-genome similarity independent of their taxonomic affiliation. Our goal is to supply the basic and applied research community with rapid, precise and accurate identification of unknown isolates based on genome sequence alone, and with molecular tools for environmental analysis.

The DNA sequencing revolution enabled the use of cultured and uncultured microorganism genomes for fast and precise identification. However, precise identification is impossible without

1. reference databases that precisely circumscribe classes of microorganisms, and label these with their uniquely-shared characteristics

2. fast algorithms that can handle the volumes of genome data

Our approach integrates the highly-resolved classification framework of Life Identification Numbers (LINs) with the speed and computational efficiency of sourmash and k-mer hashing algorithms, and the precision and filtering of average nucleotide identity (ANI). We aim to construct a single genome-based indexing scheme that extends from phylum to strain, enabling the unique and consistent placement of any sequenced prokaryote genome.

genomeRxiv includes protocols for confidentiality, allowing groups to identify and announce the identities of newly-sequenced organisms without sharing genome data directly. This protects communities working with commercially- and ethically-sensitive organisms (e.g. production engineering strains, potential bioweapons, and to enable benefit sharing with indigenous communities).

genomeRxiv will also provide online capability to design molecular diagnostic tools for metabarcoding and qPCR, to enable tracking of specific groupings of bacteria directly in the environment.

Could a Focus on the “Why” of Taxonomy Help Taxonomy Better Respond to the Needs of Science and Society?

Genomics has put prokaryotic rank-based taxonomy on a solid phylogenetic foundation. However, most taxonomic ranks were set long before the advent of DNA sequencing and genomics. In this concept paper, we thus ask the following question: should prokaryotic classification schemes besides the current phylum-to-species ranks be explored, developed, and incorporated into scientific discourse? Could such alternative schemes provide better solutions to the basic need of science and society for which taxonomy was developed, namely, precise and meaningful identification? A neutral genome-similarity based framework is then described that could allow alternative classification schemes to be explored, compared, and translated into each other without having to choose only one as the gold standard. Classification schemes could thus continue to evolve and be selected according to their benefits and based on how well they fulfill the need for prokaryotic identification.

Critical Assessment of Metagenome Interpretation: the second round of challenges

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

This study presents the results of the second round of the Critical Assessment of Metagenome Interpretation challenges (CAMI II), which is a community-driven effort for comprehensively benchmarking tools for metagenomics data analysis.

Microbial metabolites in the marine carbon cycle

One-quarter of photosynthesis-derived carbon on Earth rapidly cycles through a set of short-lived seawater metabolites that are generated from the activities of marine phytoplankton, bacteria, grazers and viruses. Here we discuss the sources of microbial metabolites in the surface ocean, their roles in ecology and biogeochemistry, and approaches that can be used to analyse them from chemistry, biology, modelling and data science. Although microbial-derived metabolites account for only a minor fraction of the total reservoir of marine dissolved organic carbon, their flux and fate underpins the central role of the ocean in sustaining life on Earth.

Draft genome assemblies using sequencing reads from Oxford Nanopore Technology and Illumina platforms for four species of North American Fundulus killifish

BACKGROUND

Whole-genome sequencing data from wild-caught individuals of closely related North American killifish species (Fundulus xenicus, Fundulus catenatus, Fundulus nottii, and Fundulus olivaceus) were obtained using long-read Oxford Nanopore Technology (ONT) PromethION and short-read Illumina platforms.

FINDINGS

Draft de novo reference genome assemblies were generated using a combination of long and short sequencing reads. For each species, the PromethION platform was used to generate 30-45× sequence coverage, and the Illumina platform was used to generate 50-160× sequence coverage. Illumina-only assemblies were fragmented with high numbers of contigs, while ONT-only assemblies were error prone with low BUSCO scores. The highest N50 values, ranging from 0.4 to 2.7 Mb, were from assemblies generated using a combination of short- and long-read data. BUSCO scores were consistently >90% complete using the Eukaryota database.

CONCLUSIONS

High-quality genomes can be obtained from a combination of using short-read Illumina data to polish assemblies generated with long-read ONT data. Draft assemblies and raw sequencing data are available for public use. We encourage use and reuse of these data for assembly benchmarking and other analyses.

Comparative Immunogenomics of Canine Natural Killer Cells as Immunotherapy Target

Natural killer (NK) cells are key effectors of the innate immune system, but major differences between human and murine NK cells have impeded translation. Outbred dogs offer an important link for studies of NK biology and immunotherapy. We analyzed gene expression of putative NK populations from healthy dogs and dogs with naturally-occurring cancers examining differential gene expression across multiple conditions, including steady-state, in vitro activation with cytokines and co-culture, and in vivo activation with inhaled IL-15 in dogs receiving IL-15 immunotherapy. We also compared dog, mouse and human CD3-NKp46+ NK cells using a novel orthologous transcriptome. Distinct transcriptional profiles between NK populations exist between conditions and in vitro versus in vivo treatments. In cross-species analysis, canine NK cells were globally more similar to human NK cells than mice. These data define canine NK cell gene expression under multiple conditions and across species, filling an important gap in translational NK studies.

The Degenerate Tale of Ascidian Tails

Ascidians are invertebrate chordates, with swimming chordate tadpole larvae that have distinct heads and tails. The head contains the small brain, sensory organs, including the ocellus (light) and otolith (gravity) and the presumptive endoderm, while the tail has a notochord surrounded by muscle cells and a dorsal nerve cord. One of the chordate features is a post-anal tail. Ascidian tadpoles are nonfeeding, and their tails are critical for larval locomotion. After hatching the larvae swim up toward light and are carried by the tide and ocean currents. When competent to settle, ascidian tadpole larvae swim down, away from light, to settle and metamorphose into a sessile adult. Tunicates are classified as chordates because of their chordate tadpole larvae; in contrast, the sessile adult has a U-shaped gut and very derived body plan, looking nothing like a chordate. There is one group of ascidians, the Molgulidae, where many species are known to have tailless larvae. The Swalla Lab has been studying the evolution of tailless ascidian larvae in this clade for over 30 years and has shown that tailless larvae have evolved independently several times in this clade. Comparison of the genomes of two closely related species, the tailed Molgula oculata and tailless Molgula occulta reveals much synteny, but there have been multiple insertions and deletions that have disrupted larval genes in the tailless species. Genomics and transcriptomics have previously shown that there are pseudogenes expressed in the tailless embryos, suggesting that the partial rescue of tailed features in their hybrid larvae is due to the expression of intact genes from the tailed parent. Yet surprisingly, we find that the notochord gene regulatory network is mostly intact in the tailless M. occulta, although the notochord does not converge and extend and remains as an aggregate of cells we call the "notoball." We expect that eventually many of the larval gene networks will become evolutionarily lost in tailless ascidians and the larval body plan abandoned, with eggs developing directly into an adult. Here we review the current evolutionary and developmental evidence on how the molgulids lost their tails.

MQF and buffered MQF: quotient filters for efficient storage of k-mers with their counts and metadata

Background

Specialized data structures are required for online algorithms to efficiently handle large sequencing datasets. The counting quotient filter (CQF), a compact hashtable, can efficiently store k-mers with a skewed distribution.

Result

Here, we present the mixed-counters quotient filter (MQF) as a new variant of the CQF with novel counting and labeling systems. The new counting system adapts to a wider range of data distributions for increased space efficiency and is faster than the CQF for insertions and queries in most of the tested scenarios. A buffered version of the MQF can offload storage to disk, trading speed of insertions and queries for a significant memory reduction. The labeling system provides a flexible framework for assigning labels to member items while maintaining good data locality and a concise memory representation. These labels serve as a minimal perfect hash function but are ~ tenfold faster than BBhash, with no need to re-analyze the original data for further insertions or deletions.

Conclusions

The MQF is a flexible and efficient data structure that extends our ability to work with high throughput sequencing data.

Whole-genome assembly of Culex tarsalis

The mosquito, Culex tarsalis, is a key vector in the western United States due to its role in transmission of zoonotic arboviruses that affect human health. Extensive research has been conducted on Cx. tarsalis ecology, feeding behavior, vector competence, autogeny, diapause, genetics, and insecticide resistance. Population genetic analyses in the western U.S. have identified at least three genetic clusters that are geographically distinct. However, in-depth genetic studies have been hindered by the lack of a reference genome. In this study, we present the first whole-genome assembly of this mosquito species (CtarK1) based on PacBio HiFi reads from high-molecular-weight DNA extracted from a single male. The CtarK1 assembly is 790 Mb with an N50 of 58 kb, which is 27% larger than Culex quinquefasciatus (578 Mb). This difference appears to be mostly composed of transposable elements. To annotate CtarK1, we used a previously assembled Cx. tarsalis transcriptome and approximately 17,456 protein genes from Cx. quinquefasciatus (N = 17,456). Genome completeness was assessed using the Benchmarking Universal Single-Copy Orthologs (BUSCO) tool, which identified 84.8% of the 2799 Dipteran BUSCO genes. Using a Bayesian phylogeny based on mitochondrial genomes, we place Cx. tarsalis in the context of other mosquito species and estimate the divergence between Cx. tarsalis and Cx. quinquefasciatus to be between 15.8 and 22.2 million years ago (MYA). Important next steps from this work include characterizing the genetic basis of diapause and sex determination in Culex mosquitoes.

Streamlining data-intensive biology with workflow systems

As the scale of biological data generation has increased, the bottleneck of research has shifted from data generation to analysis. Researchers commonly need to build computational workflows that include multiple analytic tools and require incremental development as experimental insights demand tool and parameter modifications. These workflows can produce hundreds to thousands of intermediate files and results that must be integrated for biological insight. Data-centric workflow systems that internally manage computational resources, software, and conditional execution of analysis steps are reshaping the landscape of biological data analysis and empowering researchers to conduct reproducible analyses at scale. Adoption of these tools can facilitate and expedite robust data analysis, but knowledge of these techniques is still lacking. Here, we provide a series of strategies for leveraging workflow systems with structured project, data, and resource management to streamline large-scale biological analysis. We present these practices in the context of high-throughput sequencing data analysis, but the principles are broadly applicable to biologists working beyond this field.

Trimers Conjugated to Fibrin Hydrogels Promote Salivary Gland Function

New strategies for tissue engineering have great potential for restoring and revitalizing impaired tissues and organs, including the use of smart hydrogels that can be modified to enhance organization and functionality of the salivary glands. For instance, monomers of laminin-111 peptides chemically conjugated to fibrin hydrogel (L_1pM-FH) promote cell cluster formation in vitro and salivary gland regeneration in vivo when compared with fibrin hydrogel (FH) alone; however, L_1pM-FH produce only weak expression of acinar differentiation markers in vivo (e.g., aquaporin-5 and transmembrane protein 16). Since previous studies demonstrated that a greater impact can be achieved when trimeric forms were used as compared with monomeric or dimeric forms, we investigated the extent to which trimers of laminin-111 chemically conjugated to FH (L_1pT-FH) can increase the expression of acinar differentiation markers and elevate saliva secretion. In vitro studies using Par-C10 acinar cells demonstrated that when compared with L_1pM-FH, L_1pT-FH induced similar levels of acinar-like cell clustering, polarization, lumen formation, and calcium signaling. To assess the performance of the trimeric complex in vivo, we compared the ability of L_1pM-FH and L_1pT-FH to increase acinar differentiation markers and restore saliva flow rate in a salivary gland wound model of C57BL/6 mice. Our results show that L_1pT-FH applied to wounded mice significantly improved the expression of the acinar differentiation markers and saliva secretion when compared with the monomeric form. Together, these positive effects of L_1pT-FH warrant its future testing in additional models of hyposalivation with the ultimate goal of applying this technology in humans.

A Missense Variant in ALDH5A1 Associated with Canine Succinic Semialdehyde Dehydrogenase Deficiency (SSADHD) in the Saluki Dog

Dogs provide highly valuable models of human disease due to the similarity in phenotype presentation and the ease of genetic analysis. Seven Saluki puppies were investigated for neurological abnormalities including seizures and altered behavior. Magnetic resonance imaging showed a diffuse, marked reduction in cerebral cortical thickness, and symmetrical T2 hyperintensity in specific brain regions. Cerebral cortical atrophy with vacuolation (status spongiosus) was noted on necropsy. Genome-wide association study of 7 affected and 28 normal Salukis revealed a genome-wide significantly associated region on CFA 35. Whole-genome sequencing of three confirmed cases from three different litters revealed a homozygous missense variant within the aldehyde dehydrogenase 5 family member A1 (ALDH5A1) gene (XM_014110599.2: c.866G>A; XP_013966074.2: p.(Gly288Asp). ALDH5A1 encodes a succinic semialdehyde dehydrogenase (SSADH) enzyme critical in the gamma-aminobutyric acid neurotransmitter (GABA) metabolic pathway. Metabolic screening of affected dogs showed markedly elevated gamma-hydroxybutyric acid in serum, cerebrospinal fluid (CSF) and brain, and elevated succinate semialdehyde in urine, CSF and brain. SSADH activity in the brain of affected dogs was low. Affected Saluki dogs had striking similarities to SSADH deficiency in humans although hydroxybutyric aciduria was absent in affected dogs. ALDH5A1-related SSADH deficiency in Salukis provides a unique translational large animal model for the development of novel therapeutic strategies.

Abstract 1339: Transcriptomic profiles improve characterization natural killer cells and predict response to cytokine therapy in clinical trial for dogs with pulmonary metastases

Introduction: Natural killer (NK) cells are key effectors of the innate immune system, but major differences between human and murine NK cells have been a barrier to translation. Outbred dogs are an important link for NK-based cancer immunotherapy studies, so better characterization of canine NK cells is needed. We used RNAseq to compare gene expression profiles of ex vivo dog NK cells to in vivo NK signatures from dogs with pulmonary metastases receiving inhaled recombinant human (rh) IL-15 in a phase I clinical trial.

Methods: Eight dogs with spontaneous pulmonary metastases were enrolled on an IACUC and clinical trials review board-approved Phase I clinical trial of inhaled rhIL-15 using a 3+3 cohort design with escalating doses of inhaled rhIL-15. Blood was collected from study subjects immediately pre-treatment and on days 7, 14 and 21 after treatment initiation for isolation of NK cells (CD5dim) and RNAseq. We performed differential gene expression (DGE) comparing trial patients to healthy beagle CD5dim NK populations (resting) and ex vivo activated beagle NK cells using IL-15 and feeder line co-culture. We assessed global transcriptional profile, specific activating and inhibitory receptors of NK function, and principal component analysis (PCA) for variation between treatment groups (FDR &lt;0.05).

Results: Of 8 dogs, 2 demonstrated &gt; 100-day survival with 1 stable disease and 1 partial response based on RECIST criteria. DGE revealed distinct transcriptional profiles between the ex vivo resting, IL-15 and co-cultured canine NK cells. Among treated patients, hierarchical clustering revealed that in vivo NK cell transcriptional signatures grouped by individual dog, and not amount of time exposed to treatment. PCA showed in vivo profiles of the long term survivors were distinctly separate from the non-responding patients (PC1 38%, PC2 12%). This suggests response to therapy could be determined by baseline NK cell characteristics rather than changes over time following treatment. Patient in vivo NK cell transcription profiles most closely resembled those of ex vivo resting NK cells and not IL-15 or co-culture activated (PC1 43%, PC2 19%), likely reflecting key differences in activation ex vivo vs in vivo. Key genes induced in vivo (&gt;20X) post inhalation of rhIL-15 include DLA-DRA, B2M, and thymosin beta 4, while key genes induced ex vivo post rhIL-15 exposure include CD96, KLRB1, and SPP1/OPN.

Conclusion: In this first transcriptomic sequencing of dog NK cells, we demonstrate distinct gene profiles of ex vivo activated NK cells from healthy donors compared to circulating NK cells from dogs receiving inhaled rhIL-15 on clinical trial. Baseline NK cell profiles appear to predict response more than changes over time. These data highlight the strength of the outbred dog model in speeding novel immunotherapy and biomarker studies.

Citation Format: Alicia A. Gingrich, Taylor Reiter, Sean Judge, Daniel York, Mio Yanagisawa, Ian Sturgill, Rachel Brady, Kevin Stoffel, Arta Monjazeb, C. Titus Brown, Robert Rebhun, Robert J. Canter. Transcriptomic profiles improve characterization natural killer cells and predict response to cytokine therapy in clinical trial for dogs with pulmonary metastases [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1339.

Exploring neighborhoods in large metagenome assembly graphs using spacegraphcats reveals hidden sequence diversity

Genomes computationally inferred from large metagenomic data sets are often incomplete and may be missing functionally important content and strain variation. We introduce an information retrieval system for large metagenomic data sets that exploits the sparsity of DNA assembly graphs to efficiently extract subgraphs surrounding an inferred genome. We apply this system to recover missing content from genome bins and show that substantial genomic sequence variation is present in a real metagenome. Our software implementation is available at https://github.com/spacegraphcats/spacegraphcats under the 3-Clause BSD License.

Sequencing data discovery with MetaSeek

SUMMARY

Sequencing data resources have increased exponentially in recent years, as has interest in large-scale meta-analyses of integrated next-generation sequencing datasets. However, curation of integrated datasets that match a user's particular research priorities is currently a time-intensive and imprecise task. MetaSeek is a sequencing data discovery tool that enables users to flexibly search and filter on any metadata field to quickly find the sequencing datasets that meet their needs. MetaSeek automatically scrapes metadata from all publicly available datasets in the Sequence Read Archive, cleans and parses messy, user-provided metadata into a structured, standard-compliant database and predicts missing fields where possible. MetaSeek provides a web-based graphical user interface and interactive visualization dashboard, as well as a programmatic API to rapidly search, filter, visualize, save, share and download matching sequencing metadata.

AVAILABILITY AND IMPLEMENTATION

The MetaSeek online interface is available at https://www.metaseek.cloud/. The MetaSeek database can also be accessed via API to programmatically search, filter and download all metadata. MetaSeek source code, metadata scrapers and documents are available at https://github.com/MetaSeek-Sequencing-Data-Discovery/metaseek/.

Cross-species gene expression analysis of human, canine and murine natural killer cells suggests convergence of activated dog and human transcriptomic profiles

Key species differences exist between human and murine natural killer (NK) cells. Although outbred dogs are a link for translational NK studies, better characterization of dog NK cells is needed. We used RNAseq to profile resting and activated NK cells from mice, dogs and humans. Cells were isolated based on putative NK cell populations from healthy humans (CD56+CD3−), beagles (CD5dim) and C57BL/6J mice (NK1.1+CD3−) and sequenced from steady-state or following exposure to irradiated human feeder cells (K562 clone 9) with 100 IU/mL rhIL-2 × 14 days (human and dog) or 1000 IU/mL rhIL-2 × 7 days. Purity of expanded human and dog NK cells was ~ 90%, while for mouse it was ~ 70%. We performed differential gene expression (DGE) across species and conditions using ~7000 1:1 orthologous genes. DGE revealed distinct transcriptional profiles for each species (FDR &lt;0.05). Hierarchical clustering demonstrated mouse NK cells as an outgroup compared to dog and human. PCA showed within-species spatial clustering of resting NK cells. After activation, variance between dog and human NK cells decreased, variance between human and mouse NK cells increased (PC1 40%, PC2 28%). Species differed in expression of key genes after activation, including PRF1, GZMA, SPP1, IL2RB, CTSD and FCER1G, which showed greater increases in abundance counts in mice than dogs and humans. In this first transcriptomic sequencing of dog NK cells, we show distinct gene profiles of resting cells across the most commonly used mouse, dog, and human NK populations, with convergence of dog and human NK cells upon stimulation under these standard conditions. By defining the cross-species comparative transcriptional profiles of putative NK cells, these data fill a gap in translational NK studies.

Whole genome sequencing for mutation discovery in a single case of lysosomal storage disease (MPS type 1) in the dog

Mucopolysaccharidosis (MPS) is a metabolic storage disorder caused by the deficiency of any lysosomal enzyme required for the breakdown of glycosaminoglycans. A 15-month-old Boston Terrier presented with clinical signs consistent with lysosomal storage disease including corneal opacities, multifocal central nervous system disease and progressively worsening clinical course. Diagnosis was confirmed at necropsy based on histopathologic evaluation of multiple organs demonstrating accumulation of mucopolysaccharides. Whole genome sequencing was used to uncover a frame-shift insertion affecting the alpha-L-iduronidase (IDUA) gene (c.19_20insCGGCCCCC), a mutation confirmed in another Boston Terrier presented 2 years later with a similar clinical picture. Both dogs were homozygous for the IDUA mutation and shared coat colors not recognized as normal for the breed by the American Kennel Club. In contrast, the mutation was not detected in 120 unrelated Boston Terriers as well as 202 dogs from other breeds. Recent inbreeding to select for recessive and unusual coat colors may have concentrated this relatively rare allele in the breed. The identification of the variant enables ante-mortem diagnosis of similar cases and selective breeding to avoid the spread of this disease in the breed. Boston Terriers carrying this variant represent a promising model for MPS I with neurological abnormalities in humans.

Genomic and phenotypic analyses of six offspring of a genome-edited hornless bull

Genome editing followed by reproductive cloning was previously used to produce two hornless dairy bulls. We crossed one genome-edited dairy bull, homozygous for the dominant PC Celtic POLLED allele, with horned cows (pp) and obtained six heterozygous (PCp) polled calves. The calves had no horns and were otherwise healthy and phenotypically unremarkable. We conducted whole-genome sequencing of all animals using an Illumina HiSeq4000 to achieve ~20× coverage. Bioinformatics analyses revealed the bull was a compound heterozygote, carrying one naturally occurring PC Celtic POLLED allele and an allele containing an additional introgression of the homology-directed repair donor plasmid along with the PC Celtic allele. These alleles segregated in the offspring of this bull, and inheritance of either allele produced polled calves. No other unintended genomic alterations were observed. These data can be used to inform conversations in the scientific community, with regulatory authorities and with the public around 'intentional genomic alterations' and future regulatory actions regarding genome-edited animals.

Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes

BACKGROUND

De novo transcriptome assemblies are required prior to analyzing RNA sequencing data from a species without an existing reference genome or transcriptome. Despite the prevalence of transcriptomic studies, the effects of using different workflows, or "pipelines," on the resulting assemblies are poorly understood. Here, a pipeline was programmatically automated and used to assemble and annotate raw transcriptomic short-read data collected as part of the Marine Microbial Eukaryotic Transcriptome Sequencing Project. The resulting transcriptome assemblies were evaluated and compared against assemblies that were previously generated with a different pipeline developed by the National Center for Genome Research.

RESULTS

New transcriptome assemblies contained the majority of previous contigs as well as new content. On average, 7.8% of the annotated contigs in the new assemblies were novel gene names not found in the previous assemblies. Taxonomic trends were observed in the assembly metrics. Assemblies from the Dinoflagellata showed a higher number of contigs and unique k-mers than transcriptomes from other phyla, while assemblies from Ciliophora had a lower percentage of open reading frames compared to other phyla.

CONCLUSIONS

Given current bioinformatics approaches, there is no single "best" reference transcriptome for a particular set of raw data. As the optimum transcriptome is a moving target, improving (or not) with new tools and approaches, automated and programmable pipelines are invaluable for managing the computationally intensive tasks required for re-processing large sets of samples with revised pipelines and ensuring a common evaluation workflow is applied to all samples. Thus, re-assembling existing data with new tools using automated and programmable pipelines may yield more accurate identification of taxon-specific trends across samples in addition to novel and useful products for the community.

Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes

Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth.

Risk of re-operation after outpatient distal hypospadias repair in a large, multistate cohort

BACKGROUND

Repair of distal hypospadias is one of the most common pediatric urology procedures in the US. However, the risk of postsurgical complications has been reported primarily from single-institution and tertiary center studies, with short duration of patient follow-up.

OBJECTIVE

The aim of the study was to examine the incidence of re-operation and risk factors for re-operation following outpatient distal hypospadias repair in a large, representative sample of US children.

METHODS

A retrospective cohort study of patients aged 0-18 years undergoing single-stage distal hypospadias repair was conducted. Data were obtained from the State Ambulatory Surgery and Services Databases of 9 participating states. Patients who underwent outpatient surgery in 2008-2013 were identified using Current Procedural Terminology (CPT) codes. Patients with records suggesting prior surgery for hypospadias (CPT) were excluded, as were patients who underwent the initial repair <2 years before the end of state data availability. Return outpatient surgery visits across institutions within each of the 9 states were tracked to identify re-operations after the single-stage repair, using CPT codes for surgical treatment of hypospadias complications in 2008-2015. Time-to-event analyses were used to estimate the probability (risk) of re-operation over time and to examine whether patient and institutional characteristics were predictive of re-operation (age, race/ethnicity, health insurance, facility ownership, and institutional volume of hypospadias repair).

RESULTS

A total of 4673 children treated across 148 institutions were included. The median follow-up time was 4.1 years (range: 2-7.9). Most patients were <1 year of age at the time of initial repair (53%). The risk of re-operation was 2.6% (95% confidence interval [CI]: 2.1-3.0%) at 1 year and 6.7% (95% CI: 6.0-7.5%) at 5 years after initial repair (Figure). Approximately 13% of re-operation patients had the re-operation at a different institution. None of the patient or institutional factors examined was a significant predictor of the risk of re-operation.

DISCUSSION

In this population-based cohort, the estimated 5-year risk of re-operation following single-stage distal hypospadias repair was 6.7% (95% CI: 6.0-7.5). Most re-operations occurred after the first year, informing long-term expectations about postoperative complications. This study was limited by a lack of data on severity of hypospadias and surgeon characteristics and the inability to track re-operations outside of the state in which the original repair was performed.

CONCLUSION

Approximately 7% of children undergoing distal hypospadias repair undergo a re-operation within 5 years. None of the factors studied were predictive of re-operations.

Kevlar: A Mapping-Free Framework for Accurate Discovery of De Novo Variants

De novo genetic variants are an important source of causative variation in complex genetic disorders. Many methods for variant discovery rely on mapping reads to a reference genome, detecting numerous inherited variants irrelevant to the phenotype of interest. To distinguish between inherited and de novo variation, sequencing of families (parents and siblings) is commonly pursued. However, standard mapping-based approaches tend to have a high false-discovery rate for de novo variant prediction. Kevlar is a mapping-free method for de novo variant discovery, based on direct comparison of sequences between related individuals. Kevlar identifies high-abundance k-mers unique to the individual of interest. Reads containing these k-mers are partitioned into disjoint sets by shared k-mer content for variant calling, and preliminary variant predictions are sorted using a probabilistic score. We evaluated Kevlar on simulated and real datasets, demonstrating its ability to detect both de novo single-nucleotide variants and indels with high accuracy.

Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

ANISEED 2017: extending the integrated ascidian database to the exploration and evolutionary comparison of genome-scale datasets

ANISEED (www.aniseed.cnrs.fr) is the main model organism database for tunicates, the sister-group of vertebrates. This release gives access to annotated genomes, gene expression patterns, and anatomical descriptions for nine ascidian species. It provides increased integration with external molecular and taxonomy databases, better support for epigenomics datasets, in particular RNA-seq, ChIP-seq and SELEX-seq, and features novel interactive interfaces for existing and novel datatypes. In particular, the cross-species navigation and comparison is enhanced through a novel taxonomy section describing each represented species and through the implementation of interactive phylogenetic gene trees for 60% of tunicate genes. The gene expression section displays the results of RNA-seq experiments for the three major model species of solitary ascidians. Gene expression is controlled by the binding of transcription factors to cis-regulatory sequences. A high-resolution description of the DNA-binding specificity for 131 Ciona robusta (formerly C. intestinalis type A) transcription factors by SELEX-seq is provided and used to map candidate binding sites across the Ciona robusta and Phallusia mammillata genomes. Finally, use of a WashU Epigenome browser enhances genome navigation, while a Genomicus server was set up to explore microsynteny relationships within tunicates and with vertebrates, Amphioxus, echinoderms and hemichordates.

Large-scale sequence comparisons with sourmash

The sourmash software package uses MinHash-based sketching to create "signatures", compressed representations of DNA, RNA, and protein sequences, that can be stored, searched, explored, and taxonomically annotated. sourmash signatures can be used to estimate sequence similarity between very large data sets quickly and in low memory, and can be used to search large databases of genomes for matches to query genomes and metagenomes. sourmash is implemented in C++, Rust, and Python, and is freely available under the BSD license at http://github.com/dib-lab/sourmash.

Keeping it light: (re)analyzing community-wide datasets without major infrastructure

DNA sequencing technology has revolutionized the field of biology, shifting biology from a data-limited to data-rich state. Central to the interpretation of sequencing data are the computational tools and approaches that convert raw data into biologically meaningful information. Both the tools and the generation of data are actively evolving, yet the practice of re-analysis of previously generated data with new tools is not commonplace. Re-analysis of existing data provides an affordable means of generating new information and will likely become more routine within biology, yet necessitates a new set of considerations for best practices and resource development. Here, we discuss several practices that we believe to be broadly applicable when re-analyzing data, especially when done by small research groups.

The principles of tomorrow's university

In the 21st Century, research is increasingly data- and computation-driven. Researchers, funders, and the larger community today emphasize the traits of openness and reproducibility. In March 2017, 13 mostly early-career research leaders who are building their careers around these traits came together with ten university leaders (presidents, vice presidents, and vice provosts), representatives from four funding agencies, and eleven organizers and other stakeholders in an NIH- and NSF-funded one-day, invitation-only workshop titled "Imagining Tomorrow's University." Workshop attendees were charged with launching a new dialog around open research - the current status, opportunities for advancement, and challenges that limit sharing. The workshop examined how the internet-enabled research world has changed, and how universities need to change to adapt commensurately, aiming to understand how universities can and should make themselves competitive and attract the best students, staff, and faculty in this new world. During the workshop, the participants re-imagined scholarship, education, and institutions for an open, networked era, to uncover new opportunities for universities to create value and serve society. They expressed the results of these deliberations as a set of 22 principles of tomorrow's university across six areas: credit and attribution, communities, outreach and engagement, education, preservation and reproducibility, and technologies. Activities that follow on from workshop results take one of three forms. First, since the workshop, a number of workshop authors have further developed and published their white papers to make their reflections and recommendations more concrete. These authors are also conducting efforts to implement these ideas, and to make changes in the university system.  Second, we plan to organise a follow-up workshop that focuses on how these principles could be implemented. Third, we believe that the outcomes of this workshop support and are connected with recent theoretical work on the position and future of open knowledge institutions.

Whole genome variant association across 100 dogs identifies a frame shift mutation in DISHEVELLED 2 which contributes to Robinow-like syndrome in Bulldogs and related screw tail dog breeds

Domestic dog breeds exhibit remarkable morphological variations that result from centuries of artificial selection and breeding. Identifying the genetic changes that contribute to these variations could provide critical insights into the molecular basis of tissue and organismal morphogenesis. Bulldogs, French Bulldogs and Boston Terriers share many morphological and disease-predisposition traits, including brachycephalic skull morphology, widely set eyes and short stature. Unlike other brachycephalic dogs, these breeds also exhibit vertebral malformations that result in a truncated, kinked tail (screw tail). Whole genome sequencing of 100 dogs from 21 breeds identified 12.4 million bi-allelic variants that met inclusion criteria. Whole Genome Association of these variants with the breed defining phenotype of screw tail was performed using 10 cases and 84 controls and identified a frameshift mutation in the WNT pathway gene DISHEVELLED 2 (DVL2) (Chr5: 32195043_32195044del, p = 4.37 X 10-37) as the most strongly associated variant in the canine genome. This DVL2 variant was fixed in Bulldogs and French Bulldogs and had a high allele frequency (0.94) in Boston Terriers. The DVL2 variant segregated with thoracic and caudal vertebral column malformations in a recessive manner with incomplete and variable penetrance for thoracic vertebral malformations between different breeds. Importantly, analogous frameshift mutations in the human DVL1 and DVL3 genes cause Robinow syndrome, a congenital disorder characterized by similar craniofacial, limb and vertebral malformations. Analysis of the canine DVL2 variant protein showed that its ability to undergo WNT-induced phosphorylation is reduced, suggesting that altered WNT signaling may contribute to the Robinow-like syndrome in the screwtail breeds.

Sustainable computational science: the ReScience initiative

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results; however, computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested and are hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests.

Central nervous system transcriptome of Biomphalaria alexandrina, an intermediate host for schistosomiasis

Objective

Globally, more than 200 million people live at risk of the neglected tropical disease schistosomiasis (or snail fever). Larval schistosomes require the presence of specific snail species that act as intermediate hosts, supporting their multiplication and transformation into forms that can infect humans. This project was designed to generate a transcriptome from the central nervous system (CNS) of Biomphalaria alexandrina, the major intermediate host for Schistosoma mansoni in Egypt.

Results

A transcriptome was generated from five pooled central nervous systems dissected from uninfected specimens of B. alexandrina. Raw Illumina RNA-seq data (~ 20.3 million paired end reads of 150 base pairs length each) generated a transcriptome consisting of 144,213 transcript elements with an N50 contig size of 716 base pairs. Orthologs of 15,246 transcripts and homologs for an additional 16,810 transcripts were identified in the UniProtKB/Swiss-Prot database. The B. alexandrina CNS transcriptome provides a resource for future research exploring parasite-host interactions in a simpler nervous system. Moreover, increased understanding of the neural signaling mechanisms involved in the response of B. alexandrina to infection by S. mansoni larvae could lead to novel and highly specific strategies for the control of snail populations.

Electronic supplementary material

The online version of this article (10.1186/s13104-017-3018-6) contains supplementary material, which is available to authorized users.

Draft genome of tule elk Cervus canadensis nannodes

This paper presents the first draft genome of the tule elk ( Cervus elaphus nannodes), a subspecies native to California that underwent an extreme genetic bottleneck in the late 1800s.  The genome was generated from Illumina HiSeq 3000 whole genome sequencing of four individuals, resulting in the assembly of 2.395 billion base pairs (Gbp) over 602,862 contigs over 500 bp and N50 = 6,885 bp. This genome provides a resource to facilitate future genomic research on elk and other cervids.

Evolutionary loss of melanogenesis in the tunicate Molgula occulta

BACKGROUND

Analyzing close species with diverse developmental modes is instrumental for investigating the evolutionary significance of physiological, anatomical and behavioral features at a molecular level. Many examples of trait loss are known in metazoan populations living in dark environments. Tunicates are the closest living relatives of vertebrates and typically present a lifecycle with distinct motile larval and sessile adult stages. The nervous system of the motile larva contains melanized cells associated with geotactic and light-sensing organs. It has been suggested that these are homologous to vertebrate neural crest-derived melanocytes. Probably due to ecological adaptation to distinct habitats, several species of tunicates in the Molgulidae family have tailless (anural) larvae that fail to develop sensory organ-associated melanocytes. Here we studied the evolution of Tyrosinase family genes, indispensible for melanogenesis, in the anural, unpigmented Molgula occulta and in the tailed, pigmented Molgula oculata by using phylogenetic, developmental and molecular approaches.

RESULTS

We performed an evolutionary reconstruction of the tunicate Tyrosinase gene family: in particular, we found that M. oculata possesses genes predicted to encode one Tyrosinase (Tyr) and three Tyrosinase-related proteins (Tyrps) while M. occulta has only Tyr and Tyrp.a pseudogenes that are not likely to encode functional proteins. Analysis of Tyr sequences from various M. occulta individuals indicates that different alleles independently acquired frameshifting short indels and/or larger mobile genetic element insertions, resulting in pseudogenization of the Tyr locus. In M. oculata, Tyr is expressed in presumptive pigment cell precursors as in the model tunicate Ciona robusta. Furthermore, a M. oculata Tyr reporter gene construct was active in the pigment cell precursors of C. robusta embryos, hinting at conservation of the regulatory network underlying Tyr expression in tunicates. In contrast, we did not observe any expression of the Tyr pseudogene in M. occulta embryos. Similarly, M. occulta Tyr allele expression was not rescued in pigmented interspecific M. occulta × M. oculata hybrid embryos, suggesting deleterious mutations also to its cis-regulatory sequences. However, in situ hybridization for transcripts from the M. occulta Tyrp.a pseudogene revealed its expression in vestigial pigment cell precursors in this species.

CONCLUSIONS

We reveal a complex evolutionary history of the melanogenesis pathway in tunicates, characterized by distinct gene duplication and loss events. Our expression and molecular data support a tight correlation between pseudogenization of Tyrosinase family members and the absence of pigmentation in the immotile larvae of M. occulta. These results suggest that relaxation of purifying selection has resulted in the loss of sensory organ-associated melanocytes and core genes in the melanogenesis biosynthetic pathway in M. occulta.

Centromere location in Arabidopsis is unaltered by extreme divergence in CENH3 protein sequence

During cell division, spindle fibers attach to chromosomes at centromeres. The DNA sequence at regional centromeres is fast evolving with no conserved genetic signature for centromere identity. Instead CENH3, a centromere-specific histone H3 variant, is the epigenetic signature that specifies centromere location across both plant and animal kingdoms. Paradoxically, CENH3 is also adaptively evolving. An ongoing question is whether CENH3 evolution is driven by a functional relationship with the underlying DNA sequence. Here, we demonstrate that despite extensive protein sequence divergence, CENH3 histones from distant species assemble centromeres on the same underlying DNA sequence. We first characterized the organization and diversity of centromere repeats in wild-type Arabidopsis thaliana. We show that A. thaliana CENH3-containing nucleosomes exhibit a strong preference for a unique subset of centromeric repeats. These sequences are largely missing from the genome assemblies and represent the youngest and most homogeneous class of repeats. Next, we tested the evolutionary specificity of this interaction in a background in which the native A. thaliana CENH3 is replaced with CENH3s from distant species. Strikingly, we find that CENH3 from Lepidium oleraceum and Zea mays, although specifying epigenetically weaker centromeres that result in genome elimination upon outcrossing, show a binding pattern on A. thaliana centromere repeats that is indistinguishable from the native CENH3. Our results demonstrate positional stability of a highly diverged CENH3 on independently evolved repeats, suggesting that the sequence specificity of centromeres is determined by a mechanism independent of CENH3.

Tissue resolved, gene structure refined equine transcriptome

BACKGROUND

Transcriptome interpretation relies on a good-quality reference transcriptome for accurate quantification of gene expression as well as functional analysis of genetic variants. The current annotation of the horse genome lacks the specificity and sensitivity necessary to assess gene expression especially at the isoform level, and suffers from insufficient annotation of untranslated regions (UTR) usage. We built an annotation pipeline for horse and used it to integrate 1.9 billion reads from multiple RNA-seq data sets into a new refined transcriptome.

RESULTS

This equine transcriptome integrates eight different tissues from 59 individuals and improves gene structure and isoform resolution, while providing considerable tissue-specific information. We utilized four levels of transcript filtration in our pipeline, aimed at producing several transcriptome versions that are suitable for different downstream analyses. Our most refined transcriptome includes 36,876 genes and 76,125 isoforms, with 6474 candidate transcriptional loci novel to the equine transcriptome.

CONCLUSIONS

We have employed a variety of descriptive statistics and figures that demonstrate the quality and content of the transcriptome. The equine transcriptomes that are provided by this pipeline show the best tissue-specific resolution of any equine transcriptome to date and are flexible for several downstream analyses. We encourage the integration of further equine transcriptomes with our annotation pipeline to continue and improve the equine transcriptome.

METHODS TO ENSURE THE REPRODUCIBILITY OF BIOMEDICAL RESEARCH

Science is not done in a vacuum - across fields of biomedicine, scientists have built on previous research and used data published in previous papers. A mainstay of scientific inquiry is the publication of one's research and recognition for this work is given in the form of citations and notoriety - ideally given in proportion to the quality of the work. Academic incentives, however, may encourage individual researchers to prioritize career ambitions over scientific truth. Recently, the New England Journal of Medicine published a commentary calling scientists who repurpose data "research parasites" who misuse data generated by others to demonstrate alternative hypotheses. In our opinion, the concept of data hoarding not only runs contrary to the spirit of, but also hinders scientific progress. Scientific research is meant to seek objective truth, rather than promote a personal agenda, and the only way to do so is through maximum transparency and reproducibility, no matter who is using the data….

Walking the Talk: Adopting and Adapting Sustainable Scientific Software Development processes in a Small Biology Lab

The khmer software project provides both research and production functionality for largescale nucleic-acid sequence analysis. The software implements several novel data structures and algorithms that perform data pre-fltering for common bioinformatics tasks, including sequence mapping and de novo assembly. Development is driven by a small lab with one full-time developer (MRC), as well as several graduate students and a professor (CTB) who contribute regularly to research features. Here we describe our efforts to bring better design, testing, and more open development to the khmer software project as of version 1.1. The khmer software is developed openly at http://github.com/dib-lab/khmer/.