GigaByte (Hong Kong, China)最新文献

This paper introduces a new approach to cell clustering using the Variable Neighborhood Search (VNS) metaheuristic. The purpose of this method is to cluster cells based on both gene expression and spatial coordinates. Initially, we confronted this clustering challenge as an Integer Linear Programming minimization problem. Our approach introduced a novel model based on the VNS technique, demonstrating the efficacy in navigating the complexities of cell clustering. Notably, our method extends beyond conventional cell-type clustering to spatial domain clustering. This adaptability enables our algorithm to orchestrate clusters based on information gleaned from gene expression matrices and spatial coordinates. Our validation showed the superior performance of our method when compared to existing techniques. Our approach advances current clustering methodologies and can potentially be applied to several fields, from biomedical research to spatial data analysis.

As genomic sequencing technology continues to advance, it becomes increasingly important to perform joint analyses of multiple datasets of transcriptomics. However, batch effect presents challenges for dataset integration, such as sequencing data measured on different platforms, and datasets collected at different times. Here, we report the development of BatchEval Pipeline, a batch effect workflow used to evaluate batch effect on dataset integration. The BatchEval Pipeline generates a comprehensive report, which consists of a series of HTML pages for assessment findings, including a main page, a raw dataset evaluation page, and several built-in methods evaluation pages. The main page exhibits basic information of the integrated datasets, a comprehensive score of batch effect, and the most recommended method for removing batch effect from the current datasets. The remaining pages exhibit evaluation details for the raw dataset, and evaluation results from the built-in batch effect removal methods after removing batch effect. This comprehensive report enables researchers to accurately identify and remove batch effects, resulting in more reliable and meaningful biological insights from integrated datasets. In summary, the BatchEval Pipeline represents a significant advancement in batch effect evaluation, and is a valuable tool to improve the accuracy and reliability of the experimental results.

Availability & implementation: The source code of the BatchEval Pipeline is available at https://github.com/STOmics/BatchEval.

In spatially resolved transcriptomics, Stereo-seq facilitates the analysis of large tissues at the single-cell level, offering subcellular resolution and centimeter-level field-of-view. Our previous work on StereoCell introduced a one-stop software using cell nuclei staining images and statistical methods to generate high-confidence single-cell spatial gene expression profiles for Stereo-seq data. With advancements allowing the acquisition of cell boundary information, such as cell membrane/wall staining images, we updated our software to a new version, STCellbin. Using cell nuclei staining images, STCellbin aligns cell membrane/wall staining images with spatial gene expression maps. Advanced cell segmentation ensures the detection of accurate cell boundaries, leading to more reliable single-cell spatial gene expression profiles. We verified that STCellbin can be applied to mouse liver (cell membranes) and Arabidopsis seed (cell walls) datasets, outperforming other methods. The improved capability of capturing single-cell gene expression profiles results in a deeper understanding of the contribution of single-cell phenotypes to tissue biology.

Availability & implementation: The source code of STCellbin is available at https://github.com/STOmics/STCellbin.

The basic analysis steps of spatial transcriptomics require obtaining gene expression information from both space and cells. The existing tools for these analyses incur performance issues when dealing with large datasets. These issues involve computationally intensive spatial localization, RNA genome alignment, and excessive memory usage in large chip scenarios. These problems affect the applicability and efficiency of the analysis. Here, a high-performance and accurate spatial transcriptomics data analysis workflow, called Stereo-seq Analysis Workflow (SAW), was developed for the Stereo-seq technology developed at BGI. SAW includes mRNA spatial position reconstruction, genome alignment, gene expression matrix generation, and clustering. The workflow outputs files in a universal format for subsequent personalized analysis. The execution time for the entire analysis is ∼148 min with 1 GB reads 1 × 1 cm chip test data, 1.8 times faster than with an unoptimized workflow.

Trimeresurus albolabris, also known as the white-lipped pit viper or white-lipped tree viper, is a highly venomous snake distributed across Southeast Asia and the cause of many snakebite cases. In this study, we report the first whole genome assembly of T. albolabris obtained with next-generation sequencing from a specimen collected in Mengzi, Yunnan, China. After genome sequencing and assembly, the genome of this male T. albolabris individual was 1.51 Gb in length and included 38.42% repeat-element content. Using this genome, 21,695 genes were identified, and 99.17% of genes could be annotated using gene functional databases. Our genome assembly and annotation process was validated using a phylogenetic tree, which included six species and focused on single-copy genes of nuclear genomes. This research will contribute to future studies on Trimeresurus biology and the genetic basis of snake venom.

The snake pipefish, Entelurus aequoreus (Linnaeus, 1758), is a northern Atlantic fish inhabiting open seagrass environments that recently expanded its distribution range. Here, we present a highly contiguous, near chromosome-scale genome of E. aequoreus. The final assembly spans 1.6 Gbp in 7,391 scaffolds, with a scaffold N50 of 62.3 Mbp and L50 of 12. The 28 largest scaffolds (>21 Mbp) span 89.7% of the assembly length. A BUSCO completeness score of 94.1% and a mapping rate above 98% suggest a high assembly completeness. Repetitive elements cover 74.93% of the genome, one of the highest proportions identified in vertebrates. Our demographic modeling identified a peak in population size during the last interglacial period, suggesting the species might benefit from warmer water conditions. Our updated snake pipefish assembly is essential for future analyses of the morphological and molecular changes unique to the Syngnathidae.

Understanding the distribution of Anopheles species is essential for planning and implementing malaria control programmes. This study assessed the composition and distribution of cryptic species of the main malaria vector, the Anopheles gambiae complex, in different districts of Kinshasa. Anopheles were sampled using CDC light traps in the four Kinshasa districts between July 2021 and June 2022, and then morphologically identified. Equal proportions of Anopheles gambiae s.l. per site were subjected to polymerase chain reaction to identify the cryptic species of the Anopheles gambiae complex. Anopheles gambiae complex specimens were identified throughout Kinshasa. The average density significantly differed inside and outside households. Two species of this complex circulate in Kinshasa: Anopheles gambiae and Anopheles coluzzii. In all the study sites, Anopheles gambiae was the most widespread species. Our results provide an important basis for future studies on the ecology and dynamics of cryptic species of the Anopheles gambiae complex in Kinshasa.

Antimicrobial resistance (AMR) is a global public health threat. Environmental microbial communities act as reservoirs for AMR, containing genes associated with resistance, their precursors, and the selective pressures promoting their persistence. Genomic surveillance could provide insights into how these reservoirs change and impact public health. Enriching for AMR genomic signatures in complex microbial communities would strengthen surveillance efforts and reduce time-to-answer. Here, we tested the ability of nanopore sequencing and adaptive sampling to enrich for AMR genes in a mock community of environmental origin. Our setup implemented the MinION mk1B, an NVIDIA Jetson Xavier GPU, and Flongle flow cells. Using adaptive sampling, we observed consistent enrichment by composition. On average, adaptive sampling resulted in a target composition 4× higher than without adaptive sampling. Despite a decrease in total sequencing output, adaptive sampling increased target yield in most replicates. We also demonstrate enrichment in a diverse community using an environmental sample. This method enables rapid and flexible genomic surveillance.

The king ratsnake (Elaphe carinata) of the genus Elaphe is a common large, non-venomous snake widely distributed in Southeast and East Asia. It is an economically important farmed species. As a non-venomous snake, the king ratsnake predates venomous snakes, such as cobras and pit vipers. However, the immune and digestive mechanisms of the king ratsnake remain unclear. Despite their economic and research importance, we lack genomic resources that would benefit toxicology, phylogeography, and immunogenetics studies. Here, we used single-tube long fragment read sequencing to generate the first contiguous genome of a king ratsnake from Huangshan City, Anhui province, China. The genome size is 1.56 GB with a scaffold N50 of 6.53M. The total length of the genome is approximately 621 Mb, while the repeat content is 42.26%. Additionally, we predicted 22,339 protein-coding genes, including 22,065 with functional annotations. Our genome is a potentially useful addition to those available for snakes.

Planorbidae comprises approximately 40 genera of freshwater gastropods, including roughly 250 species. Among the Planorbidae subfamilies, the significance of Planorbinae is due to its genus Biomphalaria, whose species are intermediate hosts of the trematode Schistosoma mansoni Sambon, 1907, which causes schistosomiasis in humans and animals. Here, we present the analysis of the dataset of Planorbidae housed in the Collection of Mollusks of the Oswaldo Cruz Institute, with a special focus on Biomphalaria species. This dataset includes 7,267 lots originating from 55 countries, representing 20 genera and 75 species collected from 1948 to 2023. Collections were performed in all regions of Brazil, comprising specimens from 26 states and the Federal District, particularly from the Southeast and Northeast. Within the dataset, Biomphalaria includes 3,926 lots of 31 species from 42 countries. These records will help improve our comprehension of schistosomiasis transmission dynamics and the geographic distributions of these medically important species.