An official website of the United States government
PremiseUnderstanding relationships among orchid species and populations is of critical importance for orchid conservation. Target sequence capture has become a standard method for extracting hundreds of orthologous loci for phylogenomics. Up‐front cost and time associated with design of bait sets makes this method prohibitively expensive for many researchers. Therefore, we designed a target capture kit to reliably sequence hundreds of orthologous loci across orchid lineages. MethodsWe designed an Orchidaceae target capture bait set for 963 single‐copy genes identified in published orchid genome sequences. The bait set was tested on 28 orchid species, with representatives of the subfamilies Cypripedioideae, Orchidoideae, and Epidendroideae. ResultsBetween 1,518,041 and 87,946,590 paired‐end 150‐base reads were generated for target‐enriched genomic libraries. We assembled an average of 812 genes per library for Epidendroideae species and a mean of 501 genes for species in the subfamilies Orchidoideae and Cypripedioideae. Furthermore, libraries had on average 107 of the 254 genes that are included in the Angiosperms353 bait set, allowing for direct comparison of studies using either bait set. DiscussionThe Orchidaceae963 kit will enable greater accessibility and utility of next‐generation sequencing for orchid systematics, population genetics, and identification in the illegal orchid trade.
more »
« less
This content will become publicly available on November 12, 2025
Metagenomic sequencing of cyanobacterial-dominated Lake Victoria—an African Great Lake
ABSTRACT We report 40 metagenomic libraries collected from the Winam Gulf of Lake Victoria during May–July of 2022–2023 and an additional eight opportunistic libraries from adjacent Lakes Simbi, Naivasha, and regional river systems. The sampling period captured cyanobacterial bloom events – shedding insight onto community composition and genomic potential.
more »
« less
- PAR ID:
- 10554886
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Editor(s):
- Newton, Irene_L G
- Publisher / Repository:
- American Societry for Microbiology
- Date Published:
- Journal Name:
- Microbiology Resource Announcements
- ISSN:
- 2576-098X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract MotivationTandem mass spectrometry is an essential technology for characterizing chemical compounds at high sensitivity and throughput, and is commonly adopted in many fields. However, computational methods for automated compound identification from their MS/MS spectra are still limited, especially for novel compounds that have not been previously characterized. In recent years, in silico methods were proposed to predict the MS/MS spectra of compounds, which can then be used to expand the reference spectral libraries for compound identification. However, these methods did not consider the compounds’ 3D conformations, and thus neglected critical structural information. ResultsWe present the 3D Molecular Network for Mass Spectra Prediction (3DMolMS), a deep neural network model to predict the MS/MS spectra of compounds from their 3D conformations. We evaluated the model on the experimental spectra collected in several spectral libraries. The results showed that 3DMolMS predicted the spectra with the average cosine similarity of 0.691 and 0.478 with the experimental MS/MS spectra acquired in positive and negative ion modes, respectively. Furthermore, 3DMolMS model can be generalized to the prediction of MS/MS spectra acquired by different labs on different instruments through minor fine-tuning on a small set of spectra. Finally, we demonstrate that the molecular representation learned by 3DMolMS from MS/MS spectra prediction can be adapted to enhance the prediction of chemical properties such as the elution time in the liquid chromatography and the collisional cross section measured by ion mobility spectrometry, both of which are often used to improve compound identification. Availability and implementationThe codes of 3DMolMS are available at https://github.com/JosieHong/3DMolMS and the web service is at https://spectrumprediction.gnps2.org.more » « less
-
Becket, Elinne (Ed.)ABSTRACT We recovered 57 bacterial metagenome-assembled genomes (MAGs) from benthic microbial mat pinnacles from Lake Vanda, Antarctica. These MAGs provide access to genomes from polar environments and can assist in culturing and utilizing these Antarctic bacteria.more » « less
-
Abstract BackgroundProtists, single-celled eukaryotic organisms, are critical to food web ecology, contributing to primary productivity and connecting small bacteria and archaea to higher trophic levels. Lake Mendota is a large, eutrophic natural lake that is a Long-Term Ecological Research site and among the world’s best-studied freshwater systems. Metagenomic samples have been collected and shotgun sequenced from Lake Mendota for the last 20 years. Here, we analyze this comprehensive time series to infer changes to the structure and function of the protistan community and to hypothesize about their interactions with bacteria. ResultsBased on small subunit rRNA genes extracted from the metagenomes and metagenome-assembled genomes of microeukaryotes, we identify shifts in the eukaryotic phytoplankton community over time, which we predict to be a consequence of reduced zooplankton grazing pressures after the invasion of a invasive predator (the spiny water flea) to the lake. The metagenomic data also reveal the presence of the spiny water flea and the zebra mussel, a second invasive species to Lake Mendota, prior to their visual identification during routine monitoring. Furthermore, we use species co-occurrence and co-abundance analysis to connect the protistan community with bacterial taxa. Correlation analysis suggests that protists and bacteria may interact or respond similarly to environmental conditions. Cryptophytes declined in the second decade of the timeseries, while many alveolate groups (e.g., ciliates and dinoflagellates) and diatoms increased in abundance, changes that have implications for food web efficiency in Lake Mendota. ConclusionsWe demonstrate that metagenomic sequence-based community analysis can complement existing efforts to monitor protists in Lake Mendota based on microscopy-based count surveys. We observed patterns of seasonal abundance in microeukaryotes in Lake Mendota that corroborated expectations from other systems, including high abundance of cryptophytes in winter and diatoms in fall and spring, but with much higher resolution than previous surveys. Our study identified long-term changes in the abundance of eukaryotic microbes and provided context for the known establishment of an invasive species that catalyzes a trophic cascade involving protists. Our findings are important for decoding potential long-term consequences of human interventions, including invasive species introduction.more » « less
-
Reverchon, Frédérique (Ed.)ABSTRACT Microbial activities in sub-alpine forest soil influence global cycling of the potent greenhouse gas methane. Understanding the dynamics of methane-oxidizing bacterial communities, particularly the roles of potentially active versus total microbial populations, is necessary for reducing uncertainty in global methane budget estimates. However, our understanding of the factors influencing methane cycling in forest soils is limited by our lack of knowledge about the biology of the microbes involved and how these communities are shaped by their environment. Here, we compared the composition and potential activity of microbial communities using 16S rRNA gene amplicon sequencing of total genomic DNA (gDNA) and potentially active complementary DNA (cDNA) from shallow soil in Red Butte Canyon (Salt Lake City, Utah, USA). We compared riparian and upland soils at two time points in the growing season and found distinct differences in both the community composition of the gDNA and cDNA libraries and the potential drivers of these community structures. Aerobic methane-oxidizing bacteria (methanotrophs) were detected in all samples, with cDNA libraries containing a higher average relative abundance and diversity of methanotrophs compared to gDNA libraries. Methane flux at the sample sites did not significantly correlate to the relative abundance (gDNA) or potential activity (cDNA) of methanotrophs. In the cDNA libraries, there were significant positive correlations between the abundance ofMethylococcaceaefamily methanotrophs and several non-methanotrophic methylotrophs previously found to be associated with methane-oxidizing bacterial communities. These findings suggest a complex relationship between methane-cycling bacterial communities and methane flux and highlight the need for furtherin situstudies to understand the environmental and ecological influences of these microbial consortia. IMPORTANCEMethane-oxidizing bacteria are found in diverse soil and sediment environments and play an important role in mitigating flux of this potent greenhouse gas into the atmosphere. However, it is unclear how these bacteria and their associated communities are structured in the environment and how their activity ultimately influences methane flux. In this work, we examine the composition and structure of methane-oxidizing bacterial communities in sub-alpine forest soil and find soil- and time-specific differences between the stable and potentially active populations. We also find that the potentially active populations of certain methanotrophs and non-methanotrophs are positively correlated. This work provides a step toward refining our understanding of microbially mediated biogeochemical cycles.more » « less
