![]() ; ; Grünewald, Anne ![]() in Frontiers in Genetics (2022), 13 Background: Sequencing quality has improved over the last decade for long-reads, allowing for more accurate detection of somatic low-frequency variants. In this study, we used mixtures of mitochondrial ... [more ▼] Background: Sequencing quality has improved over the last decade for long-reads, allowing for more accurate detection of somatic low-frequency variants. In this study, we used mixtures of mitochondrial samples with different haplogroups (i.e., a specific set of mitochondrial variants) to investigate the applicability of nanopore sequencing for low-frequency single nucleotide variant detection.Methods: We investigated the impact of base-calling, alignment/mapping, quality control steps, and variant calling by comparing the results to a previously derived short-read gold standard generated on the Illumina NextSeq. For nanopore sequencing, six mixtures of four different haplotypes were prepared, allowing us to reliably check for expected variants at the predefined 5%, 2%, and 1% mixture levels. We used two different versions of Guppy for base-calling, two aligners (i.e., Minimap2 and Ngmlr), and three variant callers (i.e., Mutserve2, Freebayes, and Nanopanel2) to compare low-frequency variants. We used F<sub>1</sub> score measurements to assess the performance of variant calling.Results: We observed a mean read length of 11 kb and a mean overall read quality of 15. Ngmlr showed not only higher F<sub>1</sub> scores but also higher allele frequencies (AF) of false-positive calls across the mixtures (mean F<sub>1</sub> score = 0.83; false-positive allele frequencies < 0.17) compared to Minimap2 (mean F<sub>1</sub> score = 0.82; false-positive AF < 0.06). Mutserve2 had the highest F<sub>1</sub> scores (5% level: F<sub>1</sub> score >0.99, 2% level: F<sub>1</sub> score >0.54, and 1% level: F<sub>1</sub> score >0.70) across all callers and mixture levels.Conclusion: We here present the benchmarking for low-frequency variant calling with nanopore sequencing by identifying current limitations. [less ▲] Detailed reference viewed: 83 (3 UL)![]() Martinez Arbas, Susana ![]() ![]() ![]() in Frontiers in Genetics (2021) Detailed reference viewed: 86 (0 UL)![]() Soliman, Remon ![]() ![]() ![]() in Frontiers in Genetics (2020) Detailed reference viewed: 83 (7 UL)![]() Gui, Yujuan ![]() in Frontiers in Genetics (2020) Dopaminergic neurons in the midbrain are of particular interest due to their role in diseases such as Parkinson’s disease and schizophrenia. Genetic variation between individuals can affect the integrity ... [more ▼] Dopaminergic neurons in the midbrain are of particular interest due to their role in diseases such as Parkinson’s disease and schizophrenia. Genetic variation between individuals can affect the integrity and function of dopaminergic neurons but the DNA variants and molecular cascades modulating dopaminergic neurons and other cells types of ventral midbrain remain poorly defined. Three genetically diverse inbred mouse strains – C57BL/6J, A/J, and DBA/2J – differ significantly in their genomes (∼7 million variants), motor and cognitive behavior, and susceptibility to neurotoxins. To further dissect the underlying molecular networks responsible for these variable phenotypes, we generated RNA-seq and ChIP-seq data from ventral midbrains of the 3 mouse strains. We defined 1000–1200 transcripts that are differentially expressed among them. These widespread differences may be due to altered activity or expression of upstream transcription factors. Interestingly, transcription factors were significantly underrepresented among the differentially expressed genes, and only one transcription factor, Pttg1, showed significant differences between all three strains. The changes in Pttg1 expression were accompanied by consistent alterations in histone H3 lysine 4 trimethylation at Pttg1 transcription start site. The ventral midbrain transcriptome of 3-month-old C57BL/6J congenic Pttg1–/– mutants was only modestly altered, but shifted toward that of A/J and DBA/2J in 9-month-old mice. Principle component analysis (PCA) identified the genes underlying the transcriptome shift and deconvolution of these bulk RNA-seq changes using midbrain single cell RNA-seq data suggested that the changes were occurring in several different cell types, including neurons, oligodendrocytes, and astrocytes. Taken together, our results show that Pttg1 contributes to gene regulatory variation between mouse strains and influences mouse midbrain transcriptome during aging. [less ▲] Detailed reference viewed: 147 (22 UL)![]() ; Balling, Rudolf ![]() in Frontiers In Genetics (2019) Detailed reference viewed: 44 (0 UL)![]() Hanss, Zoé ![]() ![]() ![]() in Frontiers in Genetics (2019) Detailed reference viewed: 139 (28 UL)![]() Jarazo, Javier ![]() ![]() in Frontiers in Genetics (2019) Detailed reference viewed: 193 (9 UL)![]() Ravcheev, Dmitry ![]() ![]() in Frontiers in Genetics (2017), 8 The colonic mucus layer is a dynamic and complex structure formed by secreted and transmembrane mucins, which are high-molecular-weight and heavily glycosylated proteins. Colonic mucus consists of a loose ... [more ▼] The colonic mucus layer is a dynamic and complex structure formed by secreted and transmembrane mucins, which are high-molecular-weight and heavily glycosylated proteins. Colonic mucus consists of a loose outer layer and a dense epithelium-attached layer. The outer layer is inhabited by various representatives of the human gut microbiota (HGM). Glycans of the colonic mucus can be used by the HGM as a source of carbon and energy when dietary fibers are not sufficiently available. Both commensals and pathogens can utilize mucin glycans. Commensals are mostly involved in the cleavage of glycans, while pathogens mostly utilize monosaccharides released by commensals. This HGM-derived degradation of the mucus layer increases pathogen susceptibility and causes many other health disorders. Here, we analyzed 397 individual HGM genomes to identify pathways for the cleavage of host-synthetized mucin glycans to monosaccharides as well as for the catabolism of the derived monosaccharides. Our key results are as follows: (i) Genes for the cleavage of mucin glycans were found in 86% of the analyzed genomes, which significantly higher than a previous estimation. (ii) Genes for the catabolism of derived monosaccharides were found in 89% of the analyzed genomes. (iii) Comparative genomic analysis identified four alternative forms of the monosaccharide-catabolizing enzymes and four alternative forms of monosaccharide transporters. (iv) Eighty-five percent of the analyzed genomes may be involved in potential feeding pathways for the monosaccharides derived from cleaved mucin glycans. (v) The analyzed genomes demonstrated different abilities to degrade known mucin glycans. Generally, the ability to degrade at least one type of mucin glycan was predicted for 81% of the analyzed genomes. (vi) Eighty-two percent of the analyzed genomes can form mutualistic pairs that are able to degrade mucin glycans and are not degradable by any of the paired organisms alone. Taken together, these findings provide further insight into the inter-microbial communications of the HGM as well as into host-HGM interactions. [less ▲] Detailed reference viewed: 170 (3 UL)![]() ; Thiele, Ines ![]() in Frontiers in Genetics (2016) Detailed reference viewed: 118 (4 UL)![]() Magnusdottir, Stefania ![]() ![]() in Frontiers in Genetics (2015), 6 The human gut microbiota supplies its host with essential nutrients, including B-vitamins. Using the PubSEED platform, we systematically assessed the genomes of 256 common human gut bacteria for the ... [more ▼] The human gut microbiota supplies its host with essential nutrients, including B-vitamins. Using the PubSEED platform, we systematically assessed the genomes of 256 common human gut bacteria for the presence of biosynthesis pathways for eight B-vitamins: biotin, cobalamin, folate, niacin, pantothenate, pyridoxine, riboflavin, and thiamin. On the basis of the presence and absence of genome annotations, we predicted that each of the eight vitamins was produced by 40–65% of the 256 human gut microbes. The distribution of synthesis pathways was diverse; some genomes had all eight biosynthesis pathways, whereas others contained no de novo synthesis pathways. We compared our predictions to experimental data from 16 organisms and found 88% of our predictions to be in agreement with published data. In addition, we identified several pairs of organisms whose vitamin synthesis pathway pattern complemented those of other organisms. This analysis suggests that human gut bacteria actively exchange B-vitamins among each other, thereby enabling the survival of organisms that do not synthesize any of these essential cofactors. This result indicates the co-evolution of the gut microbes in the human gut environment. Our work presents the first comprehensive assessment of the B-vitamin synthesis capabilities of the human gut microbiota. We propose that in addition to diet, the gut microbiota is an important source of B-vitamins, and that changes in the gut microbiota composition can severely affect our dietary B-vitamin requirements. [less ▲] Detailed reference viewed: 256 (24 UL)![]() ; Simeonidis, Vangelis ![]() in Frontiers in Genetics (2015), 6 A commentary on: Bioremediation in marine ecosystems: a computational study combining ecological modeling and flux balance analysis by Taffi, M., Paoletti, N., Angione, C., Pucciarelli, S., Marini, M. and ... [more ▼] A commentary on: Bioremediation in marine ecosystems: a computational study combining ecological modeling and flux balance analysis by Taffi, M., Paoletti, N., Angione, C., Pucciarelli, S., Marini, M. and Liò, P. (2014). Front Genet 5:319. doi: 10.3389/fgene.2014.00319 [less ▲] Detailed reference viewed: 130 (5 UL) |
||