Single-cell genomics-based analysis reveals a vital ecological role of Thiocapsa sp. LSW in the meromictic Lake Shunet, Siberia

Meromictic lakes usually harbour certain prevailing anoxygenic phototrophic bacteria in their anoxic zone, such as the purple sulfur bacterium (PSB) Thiocapsa sp. LSW (hereafter LSW) in Lake Shunet, Siberia. PSBs have been suggested to play a vital role in carbon, nitrogen and sulfur cycling at the oxic–anoxic interface of stratified lakes; however, the ecological significance of PSBs in the lake remains poorly understood. In this study, we explored the potential ecological role of LSW using a deep-sequencing analysis of single-cell genomics associated with flow cytometry. An approximately 2.7 Mb draft genome was obtained based on the co-assembly of five single-cell genomes. LSW might grow photolithoautotrophically and could play putative roles not only as a carbon fixer and diazotroph, but also as a sulfate reducer/oxidizer in the lake. This study provides insights into the potential ecological role of Thiocapsa sp. in meromictic lakes.

RDAClone: Deciphering Tumor Heterozygosity through Single-Cell Genomics Data Analysis with Robust Deep Autoencoder

Rapid advances in single-cell genomics sequencing (SCGS) have allowed researchers to characterize tumor heterozygosity with unprecedented resolution and reveal the phylogenetic relationships between tumor cells or clones. However, high sequencing error rates of current SCGS data, i.e., false positives, false negatives, and missing bases, severely limit its application. Here, we present a deep learning framework, RDAClone, to recover genotype matrices from noisy data with an extended robust deep autoencoder, cluster cells into subclones by the Louvain-Jaccard method, and further infer evolutionary relationships between subclones by the minimum spanning tree. Studies on both simulated and real datasets demonstrate its robustness and superiority in data denoising, cell clustering, and evolutionary tree reconstruction, particularly for large datasets.

Single cell genomics reveals plastid-lacking Picozoa are close relatives of red algae

The endosymbiotic origin of plastids from cyanobacteria gave eukaryotes photosynthetic capabilities and launched the diversification of countless forms of algae. These primary plastids are found in members of the eukaryotic supergroup Archaeplastida. All known archaeplastids still retain some form of primary plastids, which are widely assumed to have a single origin. Here, we use single-cell genomics from natural samples combined with phylogenomics to infer the evolutionary origin of the phylum Picozoa, a globally distributed but seemingly rare group of marine microbial heterotrophic eukaryotes. Strikingly, the analysis of 43 single-cell genomes shows that Picozoa belong to Archaeplastida, specifically related to red algae and the phagotrophic rhodelphids. These picozoan genomes support the hypothesis that Picozoa lack a plastid, and further reveal no evidence of an early cryptic endosymbiosis with cyanobacteria. These findings change our understanding of plastid evolution as they either represent the first complete plastid loss in a free-living taxon, or indicate that red algae and rhodelphids obtained their plastids independently of other archaeplastids.