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Temperature controls plant growth and development, and climate change has already altered the phenology of wild plants and crops1. However, the mechanisms by which plants sense temperature are not well understood. The evening complex is a major signalling hub and a core component of the plant circadian clock2,3. The evening complex acts as a temperature-responsive transcriptional repressor, providing rhythmicity and temperature responsiveness to growth through unknown mechanisms2,4-6. The evening complex consists of EARLY FLOWERING 3 (ELF3)4,7, a large scaffold protein and key component of temperature sensing; ELF4, a small α-helical protein; and LUX ARRYTHMO (LUX), a DNA-binding protein required to recruit the evening complex to transcriptional targets. ELF3 contains a polyglutamine (polyQ) repeat8-10, embedded within a predicted prion domain (PrD). Here we find that the length of the polyQ repeat correlates with thermal responsiveness. We show that ELF3 proteins in plants from hotter climates, with no detectable PrD, are active at high temperatures, and lack thermal responsiveness. The temperature sensitivity of ELF3 is also modulated by the levels of ELF4, indicating that ELF4 can stabilize the function of ELF3. In both Arabidopsis and a heterologous system, ELF3 fused with green fluorescent protein forms speckles within minutes in response to higher temperatures, in a PrD-dependent manner. A purified fragment encompassing the ELF3 PrD reversibly forms liquid droplets in response to increasing temperatures in vitro, indicating that these properties reflect a direct biophysical response conferred by the PrD. The ability of temperature to rapidly shift ELF3 between active and inactive states via phase transition represents a previously unknown thermosensory mechanism.

The MADS transcription factors (TF) are an ancient eukaryotic protein family. In plants, the family is divided into two main lineages. Here, we demonstrate that DNA binding in both lineages absolutely requires a short amino acid sequence C-terminal to the MADS domain (M domain) called the Intervening domain (I domain) that was previously defined only in type II lineage MADS. Structural elucidation of the MI domains from the floral regulator, SEPALLATA3 (SEP3), shows a conserved fold with the I domain acting to stabilise the M domain. Using the floral organ identity MADS TFs, SEP3, APETALA1 (AP1) and AGAMOUS (AG), domain swapping demonstrate that the I domain alters genome-wide DNA-binding specificity and dimerisation specificity. Introducing AG carrying the I domain of AP1 in the Arabidopsis ap1 mutant resulted in strong complementation and restoration of first and second whorl organs. Taken together, these data demonstrate that the I domain acts as an integral part of the DNA-binding domain and significantly contributes to the functional identity of the MADS TF. MADS transcription factors regulate multiple aspects of plant development. Here the authors show that the intervening I domain is conserved in both type I and type II plant MADS lineages and contributes to the functional identity of the protein by influencing both DNA binding activity and dimerisation specificity.

Background Restrictions to gene flow, genetic drift, and divergent selection associated with different environments are significant drivers of genetic differentiation. The black tiger shrimp ( Penaeus monodon ), is widely distributed throughout the Indian and Pacific Oceans including along the western, northern and eastern coastline of Australia, where it is an important aquaculture and fishery species. Understanding the genetic structure and the influence of environmental factors leading to adaptive differences among populations of this species is important for farm genetic improvement programs and sustainable fisheries management. Results Based on 278 individuals obtained from seven geographically disparate Australian locations, 10,624 high-quality SNP loci were used to characterize genetic diversity, population structure, genetic connectivity, and adaptive divergence. Significant population structure and differentiation were revealed among wild populations (average F ST  = 0.001–0.107; p  <  0.05). Eighty-nine putatively outlier SNPs were identified to be potentially associated with environmental variables by using both population differentiation (BayeScan and PCAdapt) and environmental association (redundancy analysis and latent factor mixed model) analysis methods. Clear population structure with similar spatial patterns were observed in both neutral and outlier markers with three genetically distinct groups identified (north Queensland, Northern Territory, and Western Australia). Redundancy, partial redundancy, and multiple regression on distance matrices analyses revealed that both geographical distance and environmental factors interact to generate the structure observed across Australian P. monodon populations. Conclusion This study provides new insights on genetic population structure of Australian P. monodon in the face of environmental changes, which can be used to advance sustainable fisheries management and aquaculture breeding programs.

Background The black-lip rock oyster ( Saccostrea echinata ) has considerable potential for aquaculture throughout the tropics. Previous attempts to farm S. echinata failed due to an insufficient supply of wild spat; however, the prospect of hatchery-based aquaculture has stimulated renewed interest, and small-scale farming is underway across northern Australia and in New Caledonia. The absence of knowledge surrounding the population genetic structure of this species has raised concerns about the genetic impacts of this emerging aquaculture industry. This study is the first to examine population genetics of S. echinata and employs both mitochondrial cytochrome c oxidase subunit I gene (COI) and single nucleotide polymorphism (SNP) markers. Results The mitochondrial COI data set included 273 sequences of 594 base pair length, which comprised 74 haplotypes. The SNP data set included 27,887 filtered SNPs for 272 oysters and of these 31 SNPs were identified as candidate adaptive loci. Data from the mitochondrial COI analyses, supports a broad tropical Indo-Pacific distribution of S. echinata, and showed high haplotype and nucleotide diversities (0.887–1.000 and 0.005–0.008, respectively). Mitochondrial COI analyses also revealed a ‘star-like’ haplotype network, and significant and negative neutrality tests (Tajima’s D =  − 2.030, Fu’s F s = − 25.638, P  < 0.001) support a recent population expansion after a bottleneck. The SNP analyses showed significant levels of population subdivision and four genetic clusters were identified: (1) the Noumea (New Caledonia) sample location; (2) the Bowen (north Queensland, Australia) sample location, and remaining sample locations in the Northern Territory, Australia ( n  = 8) were differentiated into two genetic clusters. These occurred at either side of the Wessel Islands and were termed (3) ‘west’ and (4) ‘east’ clusters, and two migrant individuals were detected between them. The SNP data showed a significant positive correlation between genetic and geographic distance (Mantel test, P < 0.001 , R 2  = 0.798) and supported isolation by distance. Three candidate adaptive SNPs were identified as occurring within known genes and gene ontology was well described for the sex peptide receptor gene. Conclusions Data supports the existence of genetically distinct populations of S. echinata , suggesting that management of wild and farmed stocks should be based upon multiple management units. This research has made information on population genetic structure and connectivity available for a new aquaculture species.

Multigene delivery and subsequent cellular expression is emerging as a key technology required in diverse research fields including, synthetic and structural biology, cellular reprogramming and functional pharmaceutical screening. Current viral delivery systems such as retro- and adenoviruses suffer from limited DNA cargo capacity, thus impeding unrestricted multigene expression. We developed MultiPrime, a modular, non-cytotoxic, non-integrating, baculovirus-based vector system expediting highly efficient transient multigene expression from a variety of promoters. MultiPrime viruses efficiently transduce a wide range of cell types, including non-dividing primary neurons and induced-pluripotent stem cells (iPS). We show that MultiPrime can be used for reprogramming, and for genome editing and engineering by CRISPR/Cas9. Moreover, we implemented dual-host-specific cassettes enabling multiprotein expression in insect and mammalian cells using a single reagent. Our experiments establish MultiPrime as a powerful and highly efficient tool, to deliver multiple genes for a wide range of applications in primary and established mammalian cells. Current viral gene delivery systems are limited in the amount of foreign DNA they can deliver to cells. Here the authors develop MultiPrime, a baculovirus-based vector system capable of multigene delivery into a wide variety of cells, and use Multiprime for genome engineering by CRISPR/Cas9.

Understanding the evolutionary leap from non-flowering (gymnosperms) to flowering (angiosperms) plants and the origin and vast diversification of the floral form has been one of the focuses of plant evolutionary developmental biology. The evolving diversity and increasing complexity of organisms is often due to relatively small changes in genes that direct development. These \"developmental control genes\" and the transcription factors (TFs) they encode, are at the origin of most morphological changes. TFs such as LEAFY (LFY) and the MADS-domain TFs act as central regulators in key developmental processes of plant reproduction including the floral transition in angiosperms and the specification of the male and female organs in both gymnosperms and angiosperms. In addition to advances in genome wide profiling and forward and reverse genetic screening, structural techniques are becoming important tools in unraveling TF function by providing atomic and molecular level information that was lacking in purely genetic approaches. Here, we summarize previous structural work and present additional biophysical and biochemical studies of the key master regulators of plant reproduction - LEAFY and the MADS-domain TFs SEPALLATA3 and AGAMOUS. We discuss the impact of structural biology on our understanding of the complex evolutionary process leading to the development of the bisexual flower.

Citizen science platforms, social media and smart phone applications enable the collection of large amounts of georeferenced images. This provides a huge opportunity in biodiversity and ecological research, but also creates challenges for efficient data handling and processing. Recreational and small-scale fisheries is one of the fields that could be revolutionised by efficient, widely accessible and machine learning-based processing of georeferenced images. Most non-commercial inland and coastal fisheries are considered data poor and are rarely assessed, yet they provide multiple societal benefits and can have substantial ecological impacts. Given that large quantities of georeferenced fish images are being collected by fishers every day, artificial intelligence (AI) and computer vision applications offer a great opportunity to automate their analyses by providing species identification, and potentially also fish size estimation. This would deliver data needed for fisheries management and fisher engagement. To date, however, many AI image analysis applications in fisheries are focused on the commercial sector, limited to specific species or settings, and are not publicly available. In addition, using AI and computer vision tools often requires a strong background in programming. In this study, we aim to facilitate broader use of computer vision tools in fisheries and ecological research by compiling an open-source user friendly and modular framework for large-scale image storage, handling, annotation and automatic classification, using cost- and labour-efficient methodologies. The tool is based on TensorFlow Lite Model Maker library, and includes data augmentation and transfer learning techniques applied to different convolutional neural network models. We demonstrate the potential application of this framework using a small example dataset of fish images taken through a recreational fishing smartphone application. The framework presented here can be used to develop region-specific species identification models, which could potentially be combined into a larger hierarchical model.

Understanding genetic diversity and population connectivity in marine organisms is essential for fisheries management. In the present study, we examined the population genetics of the European squid, Loligo vulgaris , along the western Iberian Peninsula at two genetic resolutions using the mitochondrial cytochrome oxidase subunit I gene (COI) and genomic markers obtained via double digest restriction-site associated DNA sequencing (ddRADseq). The results obtained revealed 79 haplotypes out of 160 COI sequences, while the SNP data set included 86,431 loci after filtering for 38 individuals with 86,319 neutral data. Mitochondrial COI analyses revealed high haplotype (0.961) and nucleotide (0.010) diversities, and the haplotype network reveals complex sub-structure in Turkish waters within a panmictic population. Both Tajima’s D and Fu’s Fs tests suggest that the population of L. vulgaris analysed is evolving neutrally. Pairwise F st for neutral SNPs were low (0 < F st <0.002) and not significant showing high homogeneity among populations, while pairwise comparations for candidate adaptive SNPs (112 loci) showed F st values ranging from 0.026 to 0.234. While neutral SNPs showed admixture, the candidate adaptive SNPs showed a moderate significant structure with a latitudinal discrimination. Overall, both genetic approaches showed homogeneity and strong genetic flux identifying a unique population along the Western Iberian Peninsula.

The New Zealand green-lipped mussel aquaculture industry is largely dependent on the supply of young mussels that wash up on Ninety Mile Beach (so-called Kaitaia spat), which are collected and trucked to aquaculture farms. The locations of source populations of Kaitaia spat are unknown and this lack of knowledge represents a major problem because spat supply may be irregular. We combined genotypic (microsatellite) and phenotypic (shell geochemistry) data in a geospatial framework to determine if this new approach can help identify source populations of mussels collected from two spat-collecting and four non-spat-collecting sites further south. Genetic analyses resolved differentiated clusters (mostly three clusters), but no obvious source populations. Shell geochemistry analyses resolved six differentiated clusters, as did the combined genotypic and phenotypic data. Analyses revealed high levels of spatial and temporal variability in the geochemistry signal. Whilst we have not been able to identify the source site(s) of Kaitaia spat our analyses indicate that geospatial testing using combined genotypic and phenotypic data is a powerful approach. Next steps should employ analyses of single nucleotide polymorphism markers with shell geochemistry and in conjunction with high resolution physical oceanographic modelling to resolve the longstanding question of the origin of Kaitaia spat.