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A comparative analysis of the metagenomes from two 30 000 year-old permafrost samples, one of lake-alluvial origin and the other from late Pleistocene Ice Complex sediments, revealed significant differences within microbial communities. The late Pleistocene Ice Complex sediments (which have been characterized by the absence of methane with lower values of redox-potential and Fe2+ content) showed both a low abundance of methanogenic archaea and enzymes from the carbon, nitrogen and sulfur cycles. The metagenomic and geochemical analyses described in the paper provide evidence that the formation of the late Pleistocene Ice Complex sediments likely took place under much more aerobic conditions than lake-alluvial sediments. [ABSTRACT FROM AUTHOR]

Imputed whole-genome sequence (WGS) has been proposed to improve genome-wide association studies (GWAS), since all causative mutations responsible for phenotypic variation are expected to be present in the data. This approach was applied on a large number of purebred (PB) and crossbred (CB) pigs for 18 pork color traits to evaluate the impact of using imputed WGS relative to medium-density marker panels. The traits included Minolta A*, B*, and L* for fat (FCOL), quadriceps femoris muscle (QFCOL), thawed loin muscle (TMCOL), fresh ham gluteus medius (GMCOL), ham iliopsoas muscle (ICOL), and longissimus dorsi muscle on the fresh loin (FMCOL). Sequence variants were imputed from a medium-density marker panel (61K for CBs and 50K for PBs) in all genotyped pigs using BeagleV5.0. We obtained high imputation accuracy (average of 0.97 for PBs and 0.91 for CBs). GWAS were conducted for three datasets: 954 CBs and 891 PBs, and the combined CBs and PBs. For most traits, no significant associations were detected, regardless of panel density or population type. However, quantitative trait loci (QTL) regions were only found for a few traits including TMCOL Minolta A* and GMCOL Minolta B* (CBs), FMCOL Minolta B*, FMCOL Minolta L*, and ICOL Minolta B* (PBs) and FMCOL Minolta A*, FMCOL Minolta B*, GMCOL Minolta B*, and ICOL Minolta B* (Combined dataset). More QTL regions were identified with WGS ( n = 58) relative to medium-density marker panels ( n = 22). Most of the QTL were linked to previously reported QTLs or candidate genes that have been previously reported to be associated with meat quality, pH and pork color; e.g., VIL1, PRKAG3, TTLL4, and SLC11A1, USP37 . CTDSP1 gene on SSC15 has not been previously associated with meat color traits in pigs. The findings suggest any added value of WGS was only for detecting novel QTL regions when the sample size is sufficiently large as with the Combined dataset in this study. The percentage of phenotypic variance explained by the most significant SNPs also increased with WGS compared with medium-density panels. The results provide additional insights into identification of a number of candidate regions and genes for pork color traits in different pig populations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Heidaritabar, Huisman, Krivushin, Stothard, Dervishi, Charagu, Bink and Plastow.)

Multiple methods to detect copy number variants (CNV) relying on different types of data have been developed and CNV have been shown to have an impact on phenotypes of numerous traits of economic importance in cattle, such as reproduction and immunity. Further improvements in CNV detection are still needed in regard to the trade-off between high-true and low-false positive variant identification rates. Instead of improving single CNV detection methods, variants can be identified in silico with high confidence when multiple methods and datasets are combined. Here, CNV were identified from whole-genome sequences (WGS) and genotype array (GEN) data on 96 Holstein animals. After CNV detection, two sets of high confidence CNV regions (CNVR) were created that contained variants found in both WGS and GEN data following an animal-based (n = 52) and a population-based (n = 36) pipeline. Furthermore, the change in false positive CNV identification rates using different GEN marker densities was evaluated. The population-based approach characterized CNVR, which were more often shared among animals (average 40% more samples per CNVR) and were more often linked to putative functions (48 vs 56% of CNVR) than CNV identified with the animal-based approach. Moreover, false positive identification rates up to 22% were estimated on GEN information. Further research using larger datasets should use a population-wide approach to identify high confidence CNVR.

Background: Copy number variants (CNVs) contribute to genetic diversity and phenotypic variation. We aimed to discover CNVs in taurine cattle using a large collection of whole-genome sequences and to provide an interactive database of the identified CNV regions (CNVRs) that includes visualizations of sequence read alignments, CNV boundaries, and genome annotations., Results: CNVs were identified in each of 4 whole-genome sequencing datasets, which together represent >500 bulls from 17 breeds, using a popular multi-sample read-depth-based algorithm, cn.MOPS. Quality control and CNVR construction, performed dataset-wise to avoid batch effects, resulted in 26,223 CNVRs covering 107.75 unique Mb (4.05%) of the bovine genome. Hierarchical clustering of samples by CNVR genotypes indicated clear separation by breeds. An interactive HTML database was created that allows data filtering options, provides graphical and tabular data summaries including Hardy-Weinberg equilibrium tests on genotype proportions, and displays genes and quantitative trait loci at each CNVR. Notably, the database provides sequence read alignments at each CNVR genotype and the boundaries of constituent CNVs in individual samples. Besides numerous novel discoveries, we corroborated the genotypes reported for a CNVR at the KIT locus known to be associated with the piebald coat colour phenotype in Hereford and some Simmental cattle., Conclusions: We present a large comprehensive collection of taurine cattle CNVs in a novel interactive visual database that displays CNV boundaries, read depths, and genome features for individual CNVRs, thus providing users with a powerful means to explore and scrutinize CNVRs of interest more thoroughly., (© The Author(s) 2019. Published by Oxford University Press.)

Despite the recent advancements in culturomics, isolation of the majority of environmental microbiota performing critical ecosystem services, such as bioremediation of contaminants, remains elusive. Towards this end, we conducted a metagenomics-guided comparative assessment of soil microbial diversity and functions present in uraniferous soils relative to those that grew in diffusion chambers (DC) or microbial traps (MT), followed by isolation of uranium (U) resistant microbiota. Shotgun metagenomic analysis performed on the soils used to establish the DC/MT chambers revealed Proteobacterial phyla and Burkholderia genus to be the most abundant among bacteria. The chamber-associated growth conditions further increased their abundances relative to the soils. Ascomycota was the most abundant fungal phylum in the chambers relative to the soils, with Penicillium as the most dominant genus. Metagenomics-based taxonomic findings completely mirrored the taxonomic composition of the retrieved isolates such that the U-resistant bacteria and fungi mainly belonged to Burkholderia and Penicillium species, thus confirming that the chambers facilitated proliferation and subsequent isolation of specific microbiota with environmentally relevant functions. Furthermore, shotgun metagenomic analysis also revealed that the gene classes for carbohydrate metabolism, virulence, and respiration predominated with functions related to stress response, membrane transport, and metabolism of aromatic compounds were also identified, albeit at lower levels. Of major note was the successful isolation of a potentially novel Penicillium species using the MT approach, as evidenced by whole genome sequence analysis and comparative genomic analysis, thus enhancing our overall understanding on the uranium cycling microbiota within the tested uraniferous soils., Competing Interests: Conflict of Interest: The authors declare no conflict of interest.

Polar permafrost is at the forefront of climate change, yet only a few studies have enriched the native methane-producing microbes that might provide positive feedbacks to climate change. Samples Ant1 and Ant2, collected in Antarctic Miers Valley from permafrost sediments, with and without biogenic methane, respectively, were evaluated for methanogenic activity and presence of methanogens. After a one-year incubation of both samples under anaerobic conditions, methane production was observed only at room temperature in microcosm Ant1 with CO2/H2 (20/80) as carbon and energy sources and was monitored during the subsequent 10 years. The concentration of methane in the headspace of microcosm Ant1 changed from 0.8% to a maximum of 45%. Archaeal 16S rRNA genes from microcosm Ant1 were related to psychrotolerant Methanosarcina lacustris. Repeated efforts at achieving a pure culture of this organism were unsuccessful. Metagenomic reads obtained for the methane-producing microcosm Ant1 were assembled and resulted in a 99.84% complete genome affiliated with the genus Methanosarcina. The metagenome assembled genome contained cold-adapted enzymes and pathways suggesting that the novel uncultured Methanosarcina sp. Ant1 is adapted to sub-freezing conditions in permafrost. This is the first methanogen genome reported from the 15 000 years old permafrost of the Antarctic Dry Valleys.

Background: Increasing marker density was proposed to have potential to improve the accuracy of genomic prediction for quantitative traits; whole-sequence data is expected to give the best accuracy of prediction, since all causal mutations that underlie a trait are expected to be included. However, in cattle and chicken, this assumption is not supported by empirical studies. Our objective was to compare the accuracy of genomic prediction of feed efficiency component traits in Duroc pigs using single nucleotide polymorphism (SNP) panels of 80K, imputed 650K, and whole-genome sequence variants using GBLUP, BayesB and BayesRC methods, with the ultimate purpose to determine the optimal method to increase genetic gain for feed efficiency in pigs., Results: Phenotypes of average daily feed intake (ADFI), average daily gain (ADG), ultrasound backfat depth (FAT), and loin muscle depth (LMD) were available for 1363 Duroc boars from a commercial breeding program. Genotype imputation accuracies reached 92.1% from 80K to 650K and 85.6% from 650K to whole-genome sequence variants. Average accuracies across methods and marker densities of genomic prediction of ADFI, FAT, LMD and ADG were 0.40, 0.65, 0.30 and 0.15, respectively. For ADFI and FAT, BayesB outperformed GBLUP, but increasing marker density had little advantage for genomic prediction. For ADG and LMD, GBLUP outperformed BayesB, while BayesRC based on whole-genome sequence data gave the best accuracies and reached up to 0.35 for LMD and 0.25 for ADG., Conclusions: Use of genomic information was beneficial for prediction of ADFI and FAT but not for that of ADG and LMD compared to pedigree-based estimates. BayesB based on 80K SNPs gave the best genomic prediction accuracy for ADFI and FAT, while BayesRC based on whole-genome sequence data performed best for ADG and LMD. We suggest that these differences between traits in the effect of marker density and method on accuracy of genomic prediction are mainly due to the underlying genetic architecture of the traits.

A genomic reconstruction belonging to the genus Methanosarcina was assembled from metagenomic data from a methane-producing enrichment of Antarctic permafrost. This is the first methanogen genome reported from permafrost of the Dry Valleys and can help shed light on future climate-affected methane dynamics., (Copyright © 2016 Buongiorno et al.)

The present study reports metagenomic shotgun sequencing of microbial communities of two ancient permafrost horizons of the Russian Arctic. Results demonstrate a significant difference in microbial community structure of the analyzed samples in general and microorganisms of the methane cycle in particular., (Copyright © 2015 Krivushin et al.)

The ability of terrestrial microorganisms to grow in the near-surface environment of Mars is of importance to the search for life and protection of that planet from forward contamination by human and robotic exploration. Because most water on present-day Mars is frozen in the regolith, permafrosts are considered to be terrestrial analogs of the martian subsurface environment. Six bacterial isolates were obtained from a permafrost borehole in northeastern Siberia capable of growth under conditions of low temperature (0 °C), low pressure (7 mbar), and a CO(2)-enriched anoxic atmosphere. By 16S ribosomal DNA analysis, all six permafrost isolates were identified as species of the genus Carnobacterium, most closely related to C. inhibens (five isolates) and C. viridans (one isolate). Quantitative growth assays demonstrated that the six permafrost isolates, as well as nine type species of Carnobacterium (C. alterfunditum, C. divergens, C. funditum, C. gallinarum, C. inhibens, C. maltaromaticum, C. mobile, C. pleistocenium, and C. viridans) were all capable of growth under cold, low-pressure, anoxic conditions, thus extending the low-pressure extreme at which life can function.

This study summarizes the findings of our research on the genesis of methane, its content and distribution in permafrost horizons of different age and origin. Supported by reliable data from a broad geographical sweep, these findings confirm the presence of methane in permanently frozen fine-grained sediments. In contrast to the omnipresence of carbon dioxide in permafrost, methane-containing horizons (up to 40.0 mL kg(-1)) alternate with strata free of methane. Discrete methane-containing horizons representing over tens of thousands of years are indicative of the absence of methane diffusion through the frozen layers. Along with the isotopic composition of CH(4) carbon (delta(13)C -64 per thousand to -99 per thousand), this confirms its biological origin and points to in situ formation of this biogenic gas. Using (14)C-labeled substrates, the possibility of methane formation within permafrost was experimentally shown, as confirmed by delta(13)C values. Extremely low values (near -99 per thousand) indicate that the process of CH(4) formation is accompanied by the substantial fractionation of carbon isotopes. For the first time, cultures of methane-forming archaea, Methanosarcina mazei strain JL01 VKM B-2370, Methanobacterium sp. strain M2 VKM B-2371 and Methanobacterium sp. strain MK4 VKM B-2440 from permafrost, were isolated and described.