Scientific Data最新文献

Adzuki bean (Vigna angularis) is a significant dietary legume crop that is prevalent in East Asia. It also holds traditional medicinal importance in China. In this study, we report a high-quality, chromosome-level genome assembly of adzuki bean obtained by employing Illumina short-read sequencing, PacBio long-read sequencing, and Hi-C technology. The assembly spans 447.8 Mb, encompassing 96.32% of the estimated genome, with contig and scaffold N50 values of 16.5 and 41.0 Mb, respectively. More than 98.2% of the 1,614 BUSCO genes were fully identified, and 25,939 genes were annotated, with 98.23% of them being functionally identifiable. Vigna angularis was estimated to diverge successively from Vigna unguiculata and Vigna radiata about 15.3 and 8.7 million years ago (Ma), respectively. This chromosome-level reference genome of Vigna angularis provides a robust foundation for exploring the functional genomics and genome evolution of adzuki bean, thereby facilitating advancements in molecular breeding of adzuki bean.

Anaemia, a decrease in total concentration of haemoglobin (Hb) in blood, affects substantial percentage of the population worldwide. Currently, the gold standard for determining the Hb level is the invasive analysis of venous blood. Yet, more and more research groups demonstrate the possibility of non-invasive Hb assessment using white light imaging of tissue sites where Hb is the main chromophore, in particular, fingernails. Despite the promising declarations, non-invasive Hb assessment via RGB-imaging is still poorly used in practice. The main reason is the difficulty in establishing the true accuracy of the methods presented in different works since they are tested on private datasets collected under different experimental conditions. Here we present an open dataset containing RGB images of skin and fingernails for patients with a known level of Hb, thus providing a single benchmark for researchers and engineers in the field, aimed at fostering translation of non-invasive imaging methods to the bedside.

As one of the two most ancient groups of extant vertebrates, lamprey has become an important model organism in various fields of biology. In this paper, we present a comprehensive tissue-wide spatial metabolomics dataset for lampreys, where 14 distinct tissues were analyzed using liquid chromatography-mass spectrometry (LC-MS) in both positive and negative ion modes. The dataset has been fully validated using internal standard and pooled quality control samples and is readily accessible at the UCSD Metabolomics Workbench. This dataset serves as a valuable resource for researchers using lampreys as a model organism. Additionally, it acts as a benchmark metabolomics dataset for evaluating new algorithms and software tools and comparing them with previously published results. A lamprey spatial metabolomics database is also provided to support studies utilizing lampreys as an animal model, and to complement and validate other spatial metabolomics studies on lampreys conducted with mass spectrometry imaging or other techniques.

Although advances in long-read sequencing technology and genome assembly techniques have facilitated the study of genomes, little is known about the genomes of unique Chinese indigenous breeds, including the Huai pig. Huai pig is an ancient domestic pig breed and is well-documented for its redder meat color and high forage tolerance compared to European domestic pigs. In the present study, we sequenced and assembled the Huai pig genome using PacBio, Hi-C, and Illumina sequencing technologies. The final highly contiguous chromosome-level Huai pig genome spans 2.53 Gb with a scaffold N50 of 138.92 Mb. The Benchmarking Universal Single-Copy Orthologs (BUSCO) completeness score for the assembled genome was 95.33%. Remarkably, 23,389 protein-coding genes were annotated in the Huai-pig genome, along with 45.87% repetitive sequences. Overall, this study provided new foundational resources for future genetic research on Chinese domestic pigs.

Astragalus membranaceus (Fisch.) Bge (AM) is a medicinal herb plant belonging to the Leguminosae family. In this study, we present a chromosome-scale genome assembly of AM, aiming to enhance the molecular biology and functional studies of Astragali Radix. The genome size of AM is about 1.43 Gb, with a contig N50 value of 1.67 Mb. A total of 98.16% of the assembly anchored to 9 pseudochromosomes using Hi-C technology. The assembly completeness was estimated to be 97.27% using BUSCO with the long terminal repeat assembly index (LAI) of 16.22 and quality value (QV) of 48.58. Additionally, the genome contained 67.98% repetitive sequences. Genome annotation predicted 29,914 protein-coding genes, including 73 genes involved in the flavonoid biosynthetic pathway and 2,048 transcription factors. The high-quality genome assembly and gene annotation resources will greatly facilitate future functional genomic studies in Leguminosae species.

Estimating gross primary production (GPP) of terrestrial ecosystems is important for understanding the terrestrial carbon cycle. However, existed nationwide GPP datasets are primarily driven by coarse spatial resolutions (≥500 m) remotely sensed data, which fails to capture the spatial heterogeneity of GPP across different ecosystem types at land surface. This paper introduces a new GPP dataset, Hi-GLASS GPP v1, with a fine spatial resolution (30-m) and monthly temporal resolution from 2016 to 2020 in China. The Hi-GLASS GPP v1 dataset is generated from 30-m Landsat data using a process based light use efficiency model. The Hi-GLASS GPP v1 model integrates a detailed map of maize plantations, a crucial C4 crop in China known for its higher photosynthetic efficiency compared to C3 crops. This inclusion helps correct the underestimation of GPP that typically occurs when all croplands are categorized as C3. The Hi-GLASS GPP v1 dataset demonstrates a robust correlation with GPP data derived from eddy covariance towers, thereby enabling a more accurate assessment of terrestrial carbon sequestration across China.

Examining tumor-associated macrophages in the immune microenvironment of non-small cell lung cancer (NSCLC) is essential for gaining an understanding of the genesis and development of NSCLC as well as for identifying key clinical therapeutic targets. Although previous studies have reported the diverse phenotypes and functions of macrophages in tumor tissues, thereby highlighting their significant role in the tumor microenvironment, the characteristic differences and correlations between tumor and peritumor tissue-derived macrophages that are necessary for an understanding of NSCLC progression remain unclear. Based on single-cell RNA sequencing, we generated a comprehensive dataset of transcriptomes from NSCLC tumor and peritumor tissues, thereby facilitating comprehensive analysis and providing significant insights. In summary, our dataset will serve as a valuable transcriptomic resource for further studies investigating NSCLC development.

Deep-sea trenches representing an intriguing ecosystem for exploring the survival and evolutionary strategies of microbial communities in the highly specialized deep-sea environments. Here, 29 metagenomes were obtained from sediment samples collected from Kermadec and Diamantina trenches. Notably, those samples covered a varying sampling depths (from 5321 m to 9415 m) and distinct layers within the sediment itself (from 0~40 cm in Kermadec trench and 0~24 cm in Diamantina trench). Through metagenomic binning process, we reconstructed 982 metagenome assembled genomes (MAGs) with completeness >60% and contamination <5%. Within them, completeness of 351 MAGs were >90%, while an additional 331 were >80%. Phylogenomic analysis for the MAGs revealed nearly all of them were distantly related to known cultivated isolates. The abundant bacterial MAGs affiliated to phyla of Proteobacteria, Planctomycetota, Nitrospirota, Acidobacteriota, Actinobacteriota, and Chlorofexota, while the abundant archaeal phyla affiliated with Nanoarchaeota and Thermoproteota. These results provide a dataset available for further interrogation of diversity, distribution and ecological function of deep-sea microbes existed in the trenches.

Climate change is currently one of humanity's greatest threats. To help scholars understand the psychology of climate change, we conducted an online quasi-experimental survey on 59,508 participants from 63 countries (collected between July 2022 and July 2023). In a between-subjects design, we tested 11 interventions designed to promote climate change mitigation across four outcomes: climate change belief, support for climate policies, willingness to share information on social media, and performance on an effortful pro-environmental behavioural task. Participants also reported their demographic information (e.g., age, gender) and several other independent variables (e.g., political orientation, perceptions about the scientific consensus). In the no-intervention control group, we also measured important additional variables, such as environmentalist identity and trust in climate science. We report the collaboration procedure, study design, raw and cleaned data, all survey materials, relevant analysis scripts, and data visualisations. This dataset can be used to further the understanding of psychological, demographic, and national-level factors related to individual-level climate action and how these differ across countries.