MOTIVATION: The emergence of the 'telomere-to-telomere' genomics brought the challenge of identifying segmental duplications (SDs) in complete genomes. It further opened a possibility for identifying the differences in SDs across individual human genomes and studying the SD evolution. These newly emerged challenges require algorithms for reconstructing SDs in the most complex genomic regions that evaded all previous attempts to analyze their architecture, such as rapidly evolving immunoglobulin loci. RESULTS: We describe the GenomeDecoder algorithm for inferring SDs and apply it to analyzing genomic architectures of various loci in primate genomes. Our analysis revealed that multiple duplications/deletions led to a rapid birth/death of immunoglobulin genes within the human population and large changes in genomic architecture of immunoglobulin loci across primate genomes. Comparison of immunoglobulin loci across primate genomes suggests that they are subjected to diversifying selection. AVAILABILITY AND IMPLEMENTATION: GenomeDecoder is available at https://github.com/ZhangZhenmiao/GenomeDecoder. The software version and test data used in this paper are uploaded to https://doi.org/10.5281/zenodo.14753844.

Metagenome assembly is an efficient approach to reconstruct microbial genomes from metagenomic sequencing data. Although short-read sequencing has been widely used for metagenome assembly, linked- and long-read sequencing have shown their advancements in assembly by providing long-range DNA connectedness. Many metagenome assembly tools were developed to simplify the assembly graphs and resolve the repeats in microbial genomes. However, there remains no comprehensive evaluation of metagenomic sequencing technologies, and there is a lack of practical guidance on selecting the appropriate metagenome assembly tools. This paper presents a comprehensive benchmark of 19 commonly used assembly tools applied to metagenomic sequencing datasets obtained from simulation, mock communities or human gut microbiomes. These datasets were generated using mainstream sequencing platforms, such as Illumina and BGISEQ short-read sequencing, 10x Genomics linked-read sequencing, and PacBio and Oxford Nanopore long-read sequencing. The assembly tools were extensively evaluated against many criteria, which revealed that long-read assemblers generated high contig contiguity but failed to reveal some medium- and high-quality metagenome-assembled genomes (MAGs). Linked-read assemblers obtained the highest number of overall near-complete MAGs from the human gut microbiomes. Hybrid assemblers using both short- and long-read sequencing were promising methods to improve both total assembly length and the number of near-complete MAGs. This paper also discussed the running time and peak memory consumption of these assembly tools and provided practical guidance on selecting them.

BACKGROUND: Due to the complexity of microbial communities, de novo assembly on next generation sequencing data is commonly unable to produce complete microbial genomes. Metagenome assembly binning becomes an essential step that could group the fragmented contigs into clusters to represent microbial genomes based on contigs' nucleotide compositions and read depths. These features work well on the long contigs, but are not stable for the short ones. Contigs can be linked by sequence overlap (assembly graph) or by the paired-end reads aligned to them (PE graph), where the linked contigs have high chance to be derived from the same clusters. RESULTS: We developed METAMVGL, a multi-view graph-based metagenomic contig binning algorithm by integrating both assembly and PE graphs. It could strikingly rescue the short contigs and correct the binning errors from dead ends. METAMVGL learns the two graphs' weights automatically and predicts the contig labels in a uniform multi-view label propagation framework. In experiments, we observed METAMVGL made use of significantly more high-confidence edges from the combined graph and linked dead ends to the main graph. It also outperformed many state-of-the-art contig binning algorithms, including MaxBin2, MetaBAT2, MyCC, CONCOCT, SolidBin and GraphBin on the metagenomic sequencing data from simulation, two mock communities and Sharon infant fecal samples. CONCLUSIONS: Our findings demonstrate METAMVGL outstandingly improves the short contig binning and outperforms the other existing contig binning tools on the metagenomic sequencing data from simulation, mock communities and infant fecal samples.

Driven by the recent adoption of temporal expressions into SQL:2011, extensions of temporal support in conventional database management systems (a.b.a. DBMSs) have re-emerged as a research hotspot. In this paper, we present a lightweight yet efficient built-in temporal implementation in Tencent's distributed database management system, namely TDSQL. The novelty of TDSQL's temporal implementation includes: (1) a new temporal data model with the extension of SQL:2011, (2) a built-in temporal implementation with various optimizations, which are also applicable to other DBMSs, and (3) a low-storage-consumption in which only data changes are maintained. For the repeatability purpose, we elaborate the integration of our proposed techniques into MySQL. We conduct extensive experiments on both real-life dataset and synthetic TPC benchmarks by comparing TD-SQL with other temporal databases. The results show that TDSQL is lightweight and efficient.