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Damerum, A.

Publications and source records attributed to Damerum, A..

3 recordsLinked to original sources

Highly accurate metagenome-assembled genomes from human gut microbiota using long-read assembly, binning, and consolidation methods

Long-read metagenomic sequencing is a powerful approach for cataloging the microbial diversity present in complex microbiomes, including the human gut microbiome. We performed a deep-sequencing experiment using PacBio HiFi reads to obtain metagenome-assembled genomes (MAGs) from a pooled human gut microbiome. We performed long-read metagenome assembly using two methods (hifiasm-meta, metMDBG), used improved bioinformatic and proximity ligation binning strategies to cluster contigs and identify MAGs, and developed a novel framework to compare and consolidate MAGs (pb-MAG-mirror). We found proximity ligation binning yielded more MAGs than bioinformatic binning, but our novel comparison framework resulted in higher MAG yields than either binning strategy individually. In total, from 255 Gbp of total HiFi data we produced 595 total MAGs (including 175 high-quality MAGs) using hifiasm-meta, and 547 total MAGs (including 277 high-quality MAGs) with metaMDBG. Hifiasm-meta assembled almost twice as many strain-level MAGs as metaMDBG (246 vs. 156), but both assembly methods produced up to five strains for a species. Approximately 85% of the MAGs were assigned to known species, but we recovered >35 high-quality MAGs that represent uncultured diversity. Based on strict similarity scores, we found 125 MAGs were unequivocally shared across the assembly methods at the strain level, representing [~]22% of the total MAGs recovered per method. Finally, we detected more total viral sequences in the metaMDBG assembly versus the hifiasm-meta assembly ([~]6,700 vs. [~]4,500). Overall, we find the use of HiFi sequencing, improved metagenome assembly methods, and complementary binning strategies is highly effective for rapidly cataloging microbial genomes in complex microbiomes.

microbiology↗

Population genomics of a natural Cannabis sativa L. collection from Iran identifies novel genetic loci for flowering time, morphology, sex and chemotyping

Future breeding and selection of Cannabis sativa L. for drug production and industrial purposes require a source of germplasm with wide genetic variation, such as that found in wild relatives and progenitors of highly cultivated plants. Limited directional selection and breeding have occurred in this crop, especially informed by molecular markers. Here, we investigated the population genomics of a natural cannabis collection of male and female individuals from differing climatic zones in Iran. Using Genotyping-By-Sequencing (GBS), we sequenced 228 genotypes from 35 populations. The results obtained from GBS were used to perform association analysis identifying links between genotype and important phenotypes, including inflorescence characteristics, flowering time, plant morphology, tetrahydrocannabinol (THC) content, cannabidiol (CBD) content and sex. Approximately 23,266 significant SNPs of high quality were detected to establish associations between markers and traits, and population structure showed that Iranian cannabis plants fall into five groups. A comparison of Iranian samples from this study to global data suggests that the Iranian population is distinctive and, in general, is closer to marijuana than to hemp, although some populations in this collection are closer to hemp. The GWAS results showed that novel genetic loci, not previously identified, contribute to sex, yield and chemotype traits in cannabis and are worthy of further study.

genomics↗

Good and bad lettuce leaf microbes? Unravelling the genetic architecture of the microbiome to inform plant breeding for enhanced food safety and reduced food waste

Lettuce is a high value food crop, consumed raw around the world. Engineering of the leaf microbiome could provide significant benefits for enhanced crop yield and stress resistance and help to reduce food waste caused by microbial spoilage. Lettuce leaves also act as a vector for human pathogens, implicated in several high-profile food-borne disease outbreaks. Since host genotype helps determine microbiome composition, we hypothesize that leaf surface traits can be defined that associate with good bacterial microbiomes providing benefits to the crop and that bad microbiomes, where spoilage organisms and human pathogens are abundant, can also be associated to underlying leaf genetics, providing key targets for future crop breeding. Using a Recombinant Inbred Line (RIL) population, we show that cultivated and wild parental genotypes differ with reduced bacterial diversity, larger leaves and fewer, larger stomata, smaller epidermal cells and more hydrophilic leaf surfaces found in the cultivated compared to wild lettuce. Functional analysis of the associated microbiome revealed increased abundance of genes associated with disease virulence for the cultivated lettuce genotype, suggesting domestication has had broad impacts on leaf and associated bacterial microbiome traits. We defined the core lettuce bacterial microbiome from 171 RILs, comprised of 45 taxa in the phyla Proteobacteria, Actinobacteria, Firmicutes, Chloroflexi and Deinococcus-Thermus. Leaf surface characteristics important in influencing bacterial diversity and abundance were identified as stomatal size (length and width), epidermal cell area and number and leaf surface hydrophobicity of the abaxial leaf surface. Quantitative trait loci (QTL) for leaf surface traits, frequently mapped alongside those for the extended phenotype of bacterial taxa abundance, including for human pathogens Campylobacter spp., Escherichia-Shigella spp., Clostridium spp. (LG 4, 5 and 6) and spoilage bacteria, Pseudomonas spp. (LG 1, 3, 4, 6 and 9). Candidate genes underlying these QTL were enriched in GO terms for cell wall assembly and modification, defence response, hormone-mediated signalling and biosynthesis and anatomical structure development. This work provides the first insight into the genetic architecture of host surface traits in a leafy crop alongside the mapped genetic architecture of bacterial communities and has identified areas of the lettuce genome as important targets for future microbiome engineering.

plant biology↗