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Contents Summary 1407 I. Introduction 1408 II. Technological advances and their utility for gene banks and breeding, and longer-term contributions to SDGs 1408 III. The challenges that must be overcome to realise emerging R&D opportunities 1410 IV. Renewed governance structures for PGR (and related big data) 1413 V. Access and benefit sharing and big data 1416 VI. Conclusion 1417 Acknowledgements 1417 ORCID 1417 References 1417 SUMMARY: Over the last decade, there has been an ongoing revolution in the exploration, manipulation and synthesis of biological systems, through the development of new technologies that generate, analyse and exploit big data. Users of Plant Genetic Resources (PGR) can potentially leverage these capacities to significantly increase the efficiency and effectiveness of their efforts to conserve, discover and utilise novel qualities in PGR, and help achieve the Sustainable Development Goals (SDGs). This review advances the discussion on these emerging opportunities and discusses how taking advantage of them will require data integration and synthesis across disciplinary, organisational and international boundaries, and the formation of multi-disciplinary, international partnerships. We explore some of the institutional and policy challenges that these efforts will face, particularly how these new technologies may influence the structure and role of research for sustainable development, ownership of resources, and access and benefit sharing. We discuss potential responses to political and institutional challenges, ranging from options for enhanced structure and governance of research discovery platforms to internationally brokered benefit-sharing agreements, and identify a set of broad principles that could guide the global community as it seeks or considers solutions., (© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.)

Abstract Extracellular matrix (ECM) stiffness influences cancer cell fate by altering gene expression. Previous studies suggest that stiffness-induced nuclear deformation may regulate gene expression through YAP nuclear localization. We investigated the role of the nuclear lamina in this process. We show that the nuclear lamina exhibits mechanical threshold behavior: once unwrinkled, the nuclear lamina is inextensible. A computational model predicts that the unwrinkled lamina is under tension, which is confirmed using a lamin tension sensor. Laminar unwrinkling is caused by nuclear flattening during cell spreading on stiff ECM. Knockdown of lamin A/C eliminates nuclear surface tension and decreases nuclear YAP localization. These findings show that nuclear deformation in cells conforms to the nuclear drop model and reveal a role for lamin A/C tension in controlling YAP localization in cancer cells.

Abstract Diminished mitochondrial function underlies many rare inborn errors of energy metabolism and contributes to more common age-associated metabolic and neurodegenerative disorders. Thus, boosting mitochondrial biogenesis has been proposed as a potential therapeutic approach for these diseases; however, currently we have a limited arsenal of compounds that can stimulate mitochondrial function. In this study, we designed molybdenum disulfide (MoS2) nanoflowers with predefined atomic vacancies that are fabricated by self-assembly of individual two-dimensional MoS2 nanosheets. Treatment of mammalian cells with MoS2 nanoflowers increased mitochondrial biogenesis by induction of PGC-1α and TFAM, which resulted in increased mitochondrial DNA copy number, enhanced expression of nuclear and mitochondrial-DNA encoded genes, and increased levels of mitochondrial respiratory chain proteins. Consistent with increased mitochondrial biogenesis, treatment with MoS2 nanoflowers enhanced mitochondrial respiratory capacity and adenosine triphosphate production in multiple mammalian cell types. Taken together, this study reveals that predefined atomic vacancies in MoS2 nanoflowers stimulate mitochondrial function by upregulating the expression of genes required for mitochondrial biogenesis.

Abstract Minerals play a vital role, working synergistically with enzymes and other cofactors to regulate physiological functions including tissue healing and regeneration. The bioactive characteristics of mineral‐based nanomaterials can be harnessed to facilitate in situ tissue regeneration by attracting endogenous progenitor and stem cells and subsequently directing tissue‐specific differentiation. Here, cellular responses of human mesenchymal stem/stromal cells to traditional bioactive mineral‐based nanomaterials, such as hydroxyapatite, whitlockite, silicon‐dioxide, and the emerging synthetic 2D nanosilicates are investigated. Transcriptome sequencing is utilized to probe the cellular response and determine the significantly affected signaling pathways due to exposure to these inorganic nanomaterials. Transcriptome profiles of stem cells treated with nanosilicates reveals a stabilized skeletal progenitor state suggestive of endochondral differentiation. This observation is bolstered by enhanced deposition of matrix mineralization in nanosilicate treated stem cells compared to control or other treatments. Specifically, use of 2D nanosilicates directs osteogenic differentiation of stem cells via activation of bone morphogenetic proteins and hypoxia‐inducible factor 1‐alpha signaling pathway. This study provides insight into impact of nanomaterials on cellular gene expression profile and predicts downstream effects of nanomaterial induction of endochondral differentiation.

Bioturbation is a key ecosystem function with a fundamental role in mediating major biogeochemical cycles. The intensity and depth of bioturbation is influenced by the taxa present, which is often a function of food supply. The deep sea is generally oligotrophic with sediments composed predominantly of small, shallow burrowing macrofauna (

Biodiversity genomics research requires reliable organismal identification, which can be difficult based on morphology alone. DNA-based identification using DNA barcoding can provide confirmation of species identity and resolve taxonomic issues but is rarely used in studies generating reference genomes. Here, we describe the development and implementation of DNA barcoding for the Darwin Tree of Life Project (DToL), which aims to sequence and assemble high quality reference genomes for all eukaryotic species in Britain and Ireland. We present a standardised framework for DNA barcode sequencing and data interpretation that is then adapted for diverse organismal groups. DNA barcoding data from over 12,000 DToL specimens has identified up to 20% of samples requiring additional verification, with 2% of seed plants and 3.5% of animal specimens subsequently having their names changed. We also make recommendations for future developments using new sequencing approaches and streamlined bioinformatic approaches.

Agricultural stewardship programs that incentivize practices such as winter cover cropping (WCC), grassland set-asides (GLSA), and hedgerows (HR) for intensive annual agricultural production are often implemented to improve both soil conditions and provision of wildlife habitat in coastal agricultural systems of the Fraser River Delta, British Columbia (BC). Although these programs have been shown to support numerous ecosystem services, it is unclear how they contribute to regenerative agricultural outcomes. Regenerative agricultural practices aim to increase soil carbon inputs and reduce carbon dioxide losses which in turn improves soil structure, optimizes soil water regulation, and provides climate mitigation and resiliency of agricultural systems. The objectives of this study were to quantify the effects of agricultural stewardship programs for regenerative outcomes through indicators of climate mitigation and adaptation. Twenty-six fields in the southwestern, BC were grouped by those that participated in stewardship programs between 1992 and 2016 and those that did not. In the spring of 2018, soil samples were collected; soil organic carbon (SOC) concentrations were measured, and stocks were calculated; pedo-transfer functions were used to estimate soil water regulation indicators; and differences among stewardship program and non-program fields were statistically analyzed using a linear mixed effects model. The SOC (mg kg−1) from 0 to 15 cm was greater with implementation of stewardship programs. Topsoil equivalent soil mass SOC stocks (t/ha) were 71 % and 63 % greater in HR and WCC + GLSA program fields, respectively, compared to non-program fields. Soil workability threshold was 25 % and 14 % greater in HR and WCC + GLSA program fields, respectively, compared to non-program. Our results indicate that stewardship programs that include hedgerows and grassland set-asides promote accrual of soil carbon and improved soil water regulation and show that these programs can effectively enhance regenerative outcomes and improve agroecosystem resilience in this important agricultural region.

UK natural science collections hold over 137 million items, an unrivalled source of data about 4.56 billion years of planetary development and hundreds of years of biological change, including the differences made by humans — but the scientific, commercial, and societal benefits of these collections are constrained by the limits of physical access, and by highly fragmented digitisation efforts with less than 10% digitally available. Following work with Frontier Economics in 2021, which showed potential for £2 billion in benefits to the UK economy from digitising all UK natural science collections, in 2022–23 the Natural History Museum London worked, with analytical support from McKinsey and Company, to understand the impact of what has already been digitised and shared by UK natural science collections — what is the demand for these data, what are they used for, and how does this deliver efficient, effective and impactful research?This study focuses on usage via the Global Biodiversity Information Facility, the largest source of relevant usage data, examining 7.6 million records from twelve UK institutions. While these UK collections data are just 0.3% of total GBIF occurrences, they are cited in 12% of peer reviewed publications citing GBIF data, showing the disproportionate impact of UK collections data and the historical, geographical, and taxonomic richness that they bring. Researchers have already benefited from more than £18 million of efficiency savings from digital UK specimen data. Data from natural science collections held in the UK are uniquely impactful resources, vital to a future in which people and planet thrive, and a step change in the pace of digitisation is needed to unlock their potential for researchers, policymakers, and society.

This study evaluated the use of endemic enteric coronaviruses polymerase chain reaction (PCR)-negative testing results as an alternative approach to detect the emergence of animal health threats with similar clinical diseases presentation. This retrospective study, conducted in the United States, used PCR-negative testing results from porcine samples tested at six veterinary diagnostic laboratories. As a proof of concept, the database was first searched for transmissible gastroenteritis virus (TGEV) negative submissions between January 1st, 2010, through April 29th, 2013, when the first porcine epidemic diarrhea virus (PEDV) case was diagnosed. Secondly, TGEV- and PEDV-negative submissions were used to detect the porcine delta coronavirus (PDCoV) emergence in 2014. Lastly, encountered best detection algorithms were implemented to prospectively monitor the 2023 enteric coronavirus-negative submissions. Time series (weekly TGEV-negative counts) and Seasonal Autoregressive-Integrated Moving-Average (SARIMA) were used to control for outliers, trends, and seasonality. The SARIMA's fitted and residuals were then subjected to anomaly detection algorithms (EARS, EWMA, CUSUM, Farrington) to identify alarms, defined as weeks of higher TGEV-negativity than what was predicted by models preceding the PEDV emergence. The best-performing detection algorithms had the lowest false alarms (number of alarms detected during the baseline) and highest time to detect (number of weeks between the first alarm and PEDV emergence). The best-performing detection algorithms were CUSUM, EWMA, and Farrington flexible using SARIMA fitted values, having a lower false alarm rate and identified alarms 4 to 17 weeks before PEDV and PDCoV emergences. No alarms were identified in the 2023 enteric negative testing results. The negative-based monitoring system functioned in the case of PEDV propagating epidemic and in the presence of a concurrent propagating epidemic with the PDCoV emergence. It demonstrated its applicability as an additional tool for diagnostic data monitoring of emergent pathogens having similar clinical disease as the monitored endemic pathogens.

Artificial Intelligence (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful and usable ways to integrate, compare and visualise large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in data management that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of Machine Learning (AI) which holds much promise for this domain.

PurposeThis study investigated the prevalence and risk factors of mental and general health symptoms among university students attending in-person and online classes during COVID-19. We also explored their experiences returning to in-person classes and their views on the university's COVID-19-related policies.MethodsIn this sequential explanatory mixed-methods study (2020-2021), U.S. university student respondents (N = 1030; 603 women [58.5%], 907 [88.1%] aged 18-24 years) completed a quantitative, cross-sectional survey assessing their mental and general health symptoms experienced while taking classes during the COVID-19 pandemic. The survey link was distributed through social media and email invitations. Three separate follow-up focus groups (n = 27), consisting of an average of nine focus group respondents who had completed the quantitative survey per group, were conducted using a semi-structured interview guide. Focus group respondents provided qualitative responses on their experiences returning to class during COVID-19 and adhering to COVID-19-related policies.ResultsThe prevalence of mental health symptoms among survey respondents were 57.6% (n = 593) for depression, 41.5% (n = 427) for anxiety, and 40.8% (n = 420) for stress. Over 90% of respondents reported perceptions of good general health. Female respondents and respondents identified as non-binary gender had an increased risk for mental health symptoms compared to male respondents. Respondents with preexisting medical conditions had an increased risk for worse general health. Themes identified through qualitative analysis included (1) attending class during COVID-19 is associated with unhealthy behaviors, and poor health, (2) perceived challenges of online learning and increased feelings of isolation, (3) demand for COVID-19 policy reform and greater transparency of COVID-19 statistics; (4) difficulties in adhering to COVID-19 policies; and (5) concerns about acquiring and transmitting COVID-19.ConclusionsOur findings indicate that university students attending classes during the pandemic are experiencing negative mental health impacts. Although students were aware of COVID-19-related policies, many found it challenging to comply. Broad acceptance of COVID-19 policies will require greater transparency and information sharing.

In this opinion article, we discuss the formatting of files from (plant) genotyping studies, in particular the formatting of metadata in Variant Call Format (VCF) files. The flexibility of the VCF format specification facilitates its use as a generic interchange format across domains but can lead to inconsistency between files in the presentation of metadata. To enable fully autonomous machine actionable data flow, generic elements need to be further specified. We strongly support the merits of the FAIR principles and see the need to facilitate them also through technical implementation specifications. They form a basis for the proposed VCF extensions here. We have learned from the existing application of VCF that the definition of relevant metadata using controlled standards, vocabulary and the consistent use of cross-references via resolvable identifiers (machine-readable) are particularly necessary and propose their encoding. VCF is an established standard for the exchange and publication of genotyping data. Other data formats are also used to capture variant data (for example, the HapMap and the gVCF formats), but none currently have the reach of VCF. For the sake of simplicity, we will only discuss VCF and our recommendations for its use, but these recommendations could also be applied to gVCF. However, the part of the VCF standard relating to metadata (as opposed to the actual variant calls) defines a syntactic format but no vocabulary, unique identifier or recommended content. In practice, often only sparse descriptive metadata is included. When descriptive metadata is provided, proprietary metadata fields are frequently added that have not been agreed upon within the community which may limit long-term and comprehensive interoperability. To address this, we propose recommendations for supplying and encoding metadata, focusing on use cases from plant sciences. We expect there to be overlap, but also divergence, with the needs of other domains.

Pregnancy determination is difficult in the giant panda (Ailuropoda melanolecua), representing a challenge for ex situ conservation efforts. Research in other species experiencing pseudopregnancy indicates that urinary/fecal concentrations of 13,14, dihydro-15-keto-prostaglandin F2α (PGFM) can accurately determine pregnancy status. Our objective was to determine if urinary PGFM concentrations are associated with pregnancy status in the giant panda. Urinary PGFM concentrations were measured in female giant pandas (n = 4) throughout gestation (n = 6) and pseudopregnancy (n = 4) using a commercial enzyme immunoassay. Regardless of pregnancy status, PGFM excretion followed a predictable pattern: 1) baseline concentrations for 11-19 weeks following ovulation; 2) a modest, initial peak 14-36 days after the start of the secondary urinary progestagen rise; 3) a subsequent period of relatively low concentrations; and 4) a large, terminal peak at the end of the luteal phase. Pregnant profiles were distinguished by an earlier initial peak (P = 0.024), higher inter-peak concentrations (P < 0.001), and a larger terminal peak (P = 0.003) compared to pseudopregnancy profiles. Parturition occurred 23 to 25 days from the initial PGFM surge and within 24 hours of the start of the terminal increase. These pattern differences indicate that urinary PGFM monitoring can be used to predict pregnancy status and time parturition in the giant panda. Furthermore, this is the only species known to exhibit a significant PGFM increase during pseudopregnancy, suggesting a unique physiological mechanism for regulating the end of the luteal phase in the giant panda.

Organic matter (OM) production and degradation is important in coastal estuaries, and OM fate is strongly influenced by the coupled interactions of bioturbation and biogeochemistry. From April to September 2013 sediment cores and a benthic observing system, Wormcam, were used to investigate the in situ relationship of biogeochemistry and macrofauna bioturbation in Cape Lookout Bight North Carolina. Wormcam imagery provided a vivid depiction of macrofauna functioning in an environment not previously observed, and affirmed the importance of fine-scale temporal observations of the benthic environment in situ. Observation of macrofauna presence and bioturbation during the summer contradicted previous studies that found this area to be azoic during methane activity and sulfide build-up. Sulfate concentrations decreased while sulfide and dissolved inorganic carbon concentrations increased during the summer. This coincided with changes in the depth and rates of bioturbation. Summer burrow depths (~0.8 cm) and rates (~0.4 cm h-1) were significantly less than spring burrow depths (~3.0 cm) and rates (~1.0 cm h-1). While sulfate reduction and OM degradation increased with temperature at a microscopic level, macroscopic OM degradation was reduced. As a result, reduced conditions dominated and a thin aerobic sediment layer, a few millimeters in thickness, was visible at the sediment surface. Decreases in macrofauna burrow depth and rates diminishes the area of influence of bioturbators, limiting bioturbation and subsequently the important ecosystem functions these organisms provide.

BACKGROUND:Triticum monococcum (2n) is a close ancestor of T. urartu, the A-genome progenitor of cultivated hexaploid wheat, and is therefore a useful model for the study of components regulating photomorphogenesis in diploid wheat. In order to develop genetic and genomic resources for such a study, we constructed genome-wide transcriptomes of two Triticum monococcum subspecies, the wild winter wheat T. monococcum ssp. aegilopoides (accession G3116) and the domesticated spring wheat T. monococcum ssp. monococcum (accession DV92) by generating de novo assemblies of RNA-Seq data derived from both etiolated and green seedlings. PRINCIPAL FINDINGS:The de novo transcriptome assemblies of DV92 and G3116 represent 120,911 and 117,969 transcripts, respectively. We successfully mapped ∼90% of these transcripts from each accession to barley and ∼95% of the transcripts to T. urartu genomes. However, only ∼77% transcripts mapped to the annotated barley genes and ∼85% transcripts mapped to the annotated T. urartu genes. Differential gene expression analyses revealed 22% more light up-regulated and 35% more light down-regulated transcripts in the G3116 transcriptome compared to DV92. The DV92 and G3116 mRNA sequence reads aligned against the reference barley genome led to the identification of ∼500,000 single nucleotide polymorphism (SNP) and ∼22,000 simple sequence repeat (SSR) sites. CONCLUSIONS:De novo transcriptome assemblies of two accessions of the diploid wheat T. monococcum provide new empirical transcriptome references for improving Triticeae genome annotations, and insights into transcriptional programming during photomorphogenesis. The SNP and SSR sites identified in our analysis provide additional resources for the development of molecular markers.

Hypoxia in Chesapeake Bay has substantially increased in recent decades, with detrimental effects on macrobenthic production; the production of these fauna link energy transfer from primary consumers to epibenthic and demersal predators. As such, the development of accurate predictive models that determine the impact of hypoxia on macrobenthic production is important. A continuous-time, biomass-based model was developed for the lower Rappahannock River, a Bay tributary prone to seasonal hypoxia. Phytoplankton, zooplankton, and macrobenthic state variables were modeled, with a focus on quantitatively constraining the effect of hypoxia on macrobenthic biomass. This was accomplished through regression with Z': a sigmoidal function between macrobenthic biomass and dissolved oxygen concentration, derived using macrobenthic data collected from the Rappahannock River during the summers of 2007 and 2008, and applied to compute hypoxia-induced mortality as a rate process. The model was verified using independent monitoring data collected by the Chesapeake Bay Program. Simulations showed that macrobenthic biomass was strongly linked to dissolved oxygen concentrations, with fluctuations in biomass related to the duration and severity of hypoxia. Our model demonstrated that hypoxia negatively affected macrobenthic biomass, as longer durations of hypoxia and greater hypoxic severity resulted in an increasing loss in biomass. This exercise represents an important contribution to modeling anthropogenically impacted coastal ecosystems, by providing an empirically constrained relationship between hypoxia and macrobenthic biomass, and applying that empirical relationship in a mechanistic model to quantify the effect of the severity, duration, and frequency of hypoxia on benthic biomass dynamics.

Bioturbation, the displacement and mixing of sediment particles by fauna or flora, facilitates life supporting processes by increasing the quality of marine sediments. In the marine environment bioturbation is primarily mediated by infaunal organisms, which are susceptible to perturbations in their surrounding environment due to their sedentary life history traits. Of particular concern is hypoxia, dissolved oxygen (DO) concentrations ≤2.8 mg l(-1), a prevalent and persistent problem that affects both pelagic and benthic fauna. A benthic observing system (Wormcam) consisting of a buoy, telemetering electronics, sediment profile camera, and water quality datasonde was developed and deployed in the Rappahannock River, VA, USA, in an area known to experience seasonal hypoxia from early spring to late fall. Wormcam transmitted a time series of in situ images and water quality data, to a website via wireless internet modem, for 5 months spanning normoxic and hypoxic periods. Hypoxia was found to significantly reduce bioturbation through reductions in burrow lengths, burrow production, and burrowing depth. Although infaunal activity was greatly reduced during hypoxic and near anoxic conditions, some individuals remained active. Low concentrations of DO in the water column limited bioturbation by infaunal burrowers and likely reduced redox cycling between aerobic and anaerobic states. This study emphasizes the importance of in situ observations for understanding how components of an ecosystem respond to hypoxia.

After ovulation, non-pregnant female giant pandas experience pseudopregnancy. During pseudopregnancy, non-pregnant females exhibit physiological and behavioral changes similar to pregnancy. Monitoring hormonal patterns that are usually different in pregnant mammals are not effective at determining pregnancy status in many animals that undergo pseudopregnancy, including the giant panda. Therefore, a physiological test to distinguish between pregnancy and pseudopregnancy in pandas has eluded scientists for decades. We examined other potential markers of pregnancy and found that activity of the acute phase protein ceruloplasmin increases in urine of giant pandas in response to pregnancy. Results indicate that in term pregnancies, levels of active urinary ceruloplasmin were elevated the first week of pregnancy and remain elevated until 20-24 days prior to parturition, while no increase was observed during the luteal phase in known pseudopregnancies. Active ceruloplasmin also increased during ultrasound-confirmed lost pregnancies; however, the pattern was different compared to term pregnancies, particularly during the late luteal phase. In four out of the five additional reproductive cycles included in the current study where females were bred but no birth occurred, active ceruloplasmin in urine increased during the luteal phase. Similar to the known lost pregnancies, the temporal pattern of change in urinary ceruloplasmin during the luteal phase deviated from the term pregnancies suggesting that these cycles may have also been lost pregnancies. Among giant pandas in captivity, it has been presumed that there is a high rate of pregnancy loss and our results are the first to provide evidence supporting this notion.

Abstract Despite numerous studies investigating resilience and personality trials, a paucity of information regarding their neurobiological commonalities at the level of the large resting-state networks (rsNWs) remains. Here we address this topic using the advantages of ultra-high-field (UHF) 7T-MRI, characterized by higher signal-to-noise ratio and increased sensitivity. The association between resilience, personality traits and three fMRI measures (fractional amplitude of low-frequency fluctuations (fALFF), degree centrality (DC) and regional homogeneity (ReHo)) determined for three core rsNWs (default mode (DMN), salience (SN), and central executive network (CEN)) were examined in 32 healthy volunteers. The investigation revealed a significant role of SN in both resilience and personality traits and a tight association of the DMN with resilience. DC in CEN emerged as a significant moderator for the correlations of resilience with the personality traits of neuroticism and extraversion. Our results indicate that the common neurobiological basis of resilience and the Big Five personality traits may be reflected at the level of the core rsNWs.

Youth homelessness has been demonstrated to disproportionately affect sexual and gender minority (SGM) youth compared to heterosexual cisgender peers. In this context, we aimed to compare health risks between service-seeking SGM and heterosexual cisgender youth experiencing homelessness, including harmful risks stemming from substance use and severity of symptoms of mental health disorders. We recruited 100 racially diverse, unstably housed participants aged 18-24 who access services at an urban non-profit organization in San Francisco, CA. Data analysis included 56 SGM participants who identified as gay, lesbian, bisexual, pansexual, unsure, transgender, and nongender, and 44 heterosexual cisgender participants. In contrast to previous studies reporting significantly higher frequency of substance use and more severe symptoms of depression, generalized anxiety, and post-traumatic stress disorder among SGM youth compared to heterosexual cisgender peers, many of these health disparities were not observed in our diverse study population of service-seeking youth. Furthermore, with the exception of methamphetamine, SGM participants did not exhibit greater harmful risks resulting from substance use, such as health, social, financial, and legal complications. We discuss the reduced burden of health disparities between SGM and heterosexual cisgender youth in our service-seeking study population within the context of gender- and sexuality-affirming programming offered at the partnering community organization. We conclude that longitudinal data on these tailored community-level interventions are needed to further explore the reduced burden of health disparities observed among service-seeking SGM youth experiencing homelessness in San Francisco in order to continue supporting pathways out of homelessness for youth of all sexual and gender identities nationwide.

Abstract Diatoms are one of the most successful and ecologically important groups of eukaryotic phytoplankton in the modern ocean. Deciphering their genomes is a key step towards better understanding of their biological innovations, evolutionary origins, and ecological underpinnings. Here, we have used 90 RNA-Seq datasets from different growth conditions combined with published expressed sequence tags and protein sequences from multiple taxa to explore the genome of the model diatom Phaeodactylum tricornutum, and introduce 1,489 novel genes. The new annotation additionally permitted the discovery of extensive alternative splicing in diatoms, including intron retention and exon skipping, which increase the diversity of transcripts generated in changing environments. In addition, we have used up-to-date reference sequence libraries to dissect the taxonomic origins of diatom genes. We show that the P. tricornutum genome is enriched in lineage-specific genes, with up to 47% of the gene models present only possessing orthologues in other stramenopile groups. Finally, we have performed a comprehensive de novo annotation of repetitive elements showing novel classes of transposable elements such as SINE, MITE and TRIM/LARD. This work provides a solid foundation for future studies of diatom gene function, evolution and ecology.