Complete genome sequence of Escherichia coli MP1

Here, we report the complete genome sequence of Escherichia coli strain MP1, consisting of one circular chromosome and one circular plasmid. Long-read assembly was performed using a consensus approach, followed by long- and short-read polishing, and gene annotation.

Comprehensive insights into the impact of bacterial indole-3-acetic acid on sensory preferences in Drosophila melanogaster

Several bacteria of environmental and clinical origins, including some human-associated strains secrete a cross-kingdom signaling molecule indole-3-acetic acid (IAA). IAA is a tryptophan (trp) derivative mainly known for regulating plant growth and development as a hormone. However, the nutritional sources that boost IAA secretion in bacteria and the impact of secreted IAA on non-plant eukaryotic hosts remained less explored. Here, we demonstrate significant trp-dependent IAA production in Pseudomonas juntendi NEEL19 when provided with ethanol as a carbon source in liquid cultures. IAA was further characterized to modulate the odor discrimination, motility and survivability in Drosophila melanogaster. A detailed analysis of IAA-fed fly brain proteome using high-resolution mass spectrometry showed significant (fold change, ± 2; p ≤ 0.05) alteration in the proteins governing neuromuscular features, audio-visual perception and energy metabolism as compared to IAA-unfed controls. Sex-wise variations in differentially regulated proteins were witnessed despite having similar visible changes in chemo perception and psychomotor responses in IAA-fed flies. This study not only revealed ethanol-specific enhancement in trp-dependent IAA production in P. juntendi, but also showed marked behavioral alterations in flies for which variations in an array of proteins governing odor discrimination, psychomotor responses, and energy metabolism are held responsible. Our study provided novel insights into disruptive attributes of bacterial IAA that can potentially influence the eukaryotic gut-brain axis having broad environmental and clinical implications.

The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

Hormesis of glyphosate on ferulic acid metabolism and antifungal volatile production in rice root biocontrol endophyte Burkholderia cepacia LS-044

Glyphosate (GP, N-phosphonomethyl glycine) is one of the most popular organophosphate herbicides widely used in agricultural practices worldwide. There have been extensive reports on the biohazard attributes and hormetic impacts of GP on plant and animal systems. However, the effects of GP on plant growth-promoting microbes and its ecological relevance remain unknown. Here, we show that GP does exert a hormetic impact on Burkholderia cepacia LS-044, a rice (Oryza sativa ssp. japonica cv. Tainung 71) root endophytic isolate. We used increasing doses of ferulic acid (FA, 1-25 mM) and GP (0.5-5 mM) to test the growth and antifungal volatile production in LS-044 by electrochemical, liquid chromatographic, gas chromatographic and spectrophotometric means. GP treatment at a low dose (0.5 mM) increased FA utilization and significantly (P < 0.0001) enhanced antifungal volatile activity in LS-044. Although FA (1 mM) was rapidly utilized by LS-044, no chromatographically detectable utilization of GP was observed at tested doses (0.5-5 mM). LS-044 emitted predominant amounts of tropone in addition to moderate-to-minor amounts of diverse ketones and/or their derivatives (acetone, acetophenone, 2-butanone, 1-propanone, 1-(2-furanyl-ethanone, 1-phenyl-1-propanone and 1-(3-pyridinyl)-1-propanone), d-menthol, 2-methoxy-3-(1-methylethyl)-pyrazine, dimethyl disulfide, pyridine and ammonium carbamate when grown under GP supplement. GP hormesis on LS-044 induced phenotypic variations in O. sativa ssp. japonica cv. Tainan 11 as evident through seed germination assay. Genes involved in the transformation of FA, and a key gene encoding 5-enolpyruvylshikimate 3-phosphate synthase (EPSPS) with Gly-94 and Tyr-95 residues localized at active site most likely rendering EPSPS sensitivity to GP, were detected in LS-044. This is the first report on the GP hormesis influencing morphological and metabolic aspects including volatile emission in a biocontrol bacterium that could modulate rice plant phenotype.

Genomic potential for inorganic carbon sequestration and xenobiotic degradation in marine bacterium Youngimonas vesicularis CC-AMW-ET affiliated to family Paracoccaceae

Ecological studies on marine microbial communities largely focus on fundamental biogeochemical processes or the most abundant constituents, while minor biological fractions are frequently neglected. Youngimonas vesicularis CC-AMW-ET, isolated from coastal surface seawater in Taiwan, is an under-represented marine Paracoccaceae (earlier Rhodobacteraceae) member. The CC-AMW-ET genome was sequenced to gain deeper insights into its role in marine carbon and sulfur cycles. The draft genome (3.7 Mb) contained 63.6% GC, 3773 coding sequences and 51 RNAs, and displayed maximum relatedness (79.06%) to Thalassobius litoralis KU5D5T, a Roseobacteraceae member. While phototrophic genes were absent, genes encoding two distinct subunits of carbon monoxide dehydrogenases (CoxL, BMS/Form II and a novel form III; CoxM and CoxS), and proteins involved in HCO3- uptake and interconversion, and anaplerotic HCO3- fixation were found. In addition, a gene coding for ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO, form II), which fixes atmospheric CO2 was found in CC-AMW-ET. Genes for complete assimilatory sulfate reduction, sulfide oxidation (sulfide:quinone oxidoreductase, SqrA type) and dimethylsulfoniopropionate (DMSP) cleavage (DMSP lyase, DddL) were also identified. Furthermore, genes that degrade aromatic hydrocarbons such as quinate, salicylate, salicylate ester, p-hydroxybenzoate, catechol, gentisate, homogentisate, protocatechuate, 4-hydroxyphenylacetic acid, N-heterocyclic aromatic compounds and aromatic amines were present. Thus, Youngimonas vesicularis CC-AMW-ET is a potential chemolithoautotroph equipped with genetic machinery for the metabolism of aromatics, and predicted to play crucial roles in the biogeochemical cycling of marine carbon and sulfur.

PHASTEST: faster than PHASTER, better than PHAST

PHASTEST (PHAge Search Tool with Enhanced Sequence Translation) is the successor to the PHAST and PHASTER prophage finding web servers. PHASTEST is designed to support the rapid identification, annotation and visualization of prophage sequences within bacterial genomes and plasmids. PHASTEST also supports rapid annotation and interactive visualization of all other genes (protein coding regions, tRNA/tmRNA/rRNA sequences) in bacterial genomes. Given that bacterial genome sequencing has become so routine, the need for fast tools to comprehensively annotate bacterial genomes has become progressively more important. PHASTEST not only offers faster and more accurate prophage annotations than its predecessors, it also provides more complete whole genome annotations and much improved genome visualization capabilities. In standardized tests, we found that PHASTEST is 31% faster and 2-3% more accurate in prophage identification than PHASTER. Specifically, PHASTEST can process a typical bacterial genome in 3.2 min (raw sequence) or in 1.3 min when given a pre-annotated GenBank file. Improvements in PHASTEST's ability to annotate bacterial genomes now make it a particularly powerful tool for whole genome annotation. In addition, PHASTEST now offers a much more modern and responsive visualization interface that allows users to generate, edit, annotate and interactively visualize (via zooming, rotating, dragging, panning, resetting), colourful, publication quality genome maps. PHASTEST continues to offer popular options such as an API for programmatic queries, a Docker image for local installations, support for multiple (metagenomic) queries and the ability to perform automated look-ups against thousands of previously PHAST-annotated bacterial genomes. PHASTEST is available online at https://phastest.ca.

Proksee: in-depth characterization and visualization of bacterial genomes

Proksee (https://proksee.ca) provides users with a powerful, easy-to-use, and feature-rich system for assembling, annotating, analysing, and visualizing bacterial genomes. Proksee accepts Illumina sequence reads as compressed FASTQ files or pre-assembled contigs in raw, FASTA, or GenBank format. Alternatively, users can supply a GenBank accession or a previously generated Proksee map in JSON format. Proksee then performs assembly (for raw sequence data), generates a graphical map, and provides an interface for customizing the map and launching further analysis jobs. Notable features of Proksee include unique and informative assembly metrics provided via a custom reference database of assemblies; a deeply integrated high-performance genome browser for viewing and comparing analysis results at individual base resolution (developed specifically for Proksee); an ever-growing list of embedded analysis tools whose results can be seamlessly added to the map or searched and explored in other formats; and the option to export graphical maps, analysis results, and log files for data sharing and research reproducibility. All these features are provided via a carefully designed multi-server cloud-based system that can easily scale to meet user demand and that ensures the web server is robust and responsive.

PlasMapper 3.0-a web server for generating, editing, annotating and visualizing publication quality plasmid maps

PlasMapper 3.0 is a web server that allows users to generate, edit, annotate and interactively visualize publication quality plasmid maps. Plasmid maps are used to plan, design, share and publish critical information about gene cloning experiments. PlasMapper 3.0 is the successor to PlasMapper 2.0 and offers many features found only in commercial plasmid mapping/editing packages. PlasMapper 3.0 allows users to paste or upload plasmid sequences as input or to upload existing plasmid maps from its large database of >2000 pre-annotated plasmids (PlasMapDB). This database can be searched by plasmid names, sequence features, restriction sites, preferred host organisms, and sequence length. PlasMapper 3.0 also supports the annotation of new or never-before-seen plasmids using its own feature database that contains common promoters, terminators, regulatory sequences, replication origins, selectable markers and other features found in most cloning plasmids. PlasMapper 3.0 has several interactive sequence editors/viewers that allow users to select and view plasmid regions, insert genes, modify restriction sites or perform codon optimization. The graphics for PlasMapper 3.0 have also been substantially upgraded. It now offers an interactive, full-color plasmid viewer/editor that allows users to zoom, rotate, re-color, linearize, circularize, edit annotated features and modify plasmid images or labels to improve the esthetic qualities of their plasmid map and textual displays. All the plasmid images and textual displays are downloadable in multiple formats. PlasMapper 3.0 is available online at https://plasmapper.ca.

Characterisation of eight cattle with Swyer syndrome by whole-genome sequencing

Swyer syndrome is where an individual has the karyotype of a typical male yet is phenotypically a female. The lack of a (functional) SRY gene located on the Y-chromosome is implicated in some cases of the Swyer syndrome, although many Swyer individuals with an apparently fully functional SRY gene have also been documented. The present study undertook whole genome sequence analyses of eight cattle with suspected Swyer syndrome and compared their genome to that of both a control male and female. Sequence analyses coupled with female phenotypes confirmed that all eight individuals had the 60,XY sex reversal Swyer syndrome. Seven of the eight Swyer syndrome individuals had a deletion on the Y chromosome encompassing the SRY gene (i.e., SRY-). The eighth individual had no obvious mutation in the SRY gene (SRY+) or indeed in any reported gene associated with sex reversal in mammals; a necropsy was performed on this individual. No testicles were detected during the necropsy. Histological examination of the reproductive tract revealed an immature uterine body and horns with inactive glandular tissue of normal histological appearance; both gonads were elongated, a characteristic of most reported cases of Swyer in mammals. The flanking sequence of 11 single nucleotide polymorphisms within 10 kb of the SRY gene are provided to help diagnose some cases of Swyer syndrome. These single nucleotide polymorphisms will not, however, detect all cases of Swyer syndrome since, as evidenced from the present study (and other studies), some individuals with the Swyer condition still contain the SRY gene (i.e., SRY+).

Milk metabolomics analyses of lactating dairy cows with divergent residual feed intake reveals physiological underpinnings and novel biomarkers

The opportunity to select for feed efficient cows has been limited by inability to cost-effectively record individual feed efficiency on an appropriate scale. This study investigated the differences in milk metabolite profiles between high- and low residual feed intake (RFI) categories and identified biomarkers of residual feed intake and models that can be used to predict residual feed intake in lactating Holsteins. Milk metabolomics analyses were undertaken at early, mid and late lactation stages and residual feed intake was calculated in 72 lactating dairy cows. Cows were ranked and grouped into high residual feed intake (RFI >0.5 SD above the mean, n = 20) and low residual feed intake (RFI <0.5 SD below the mean, n = 20). Milk metabolite profiles were compared between high residual feed intake (least efficient) and low residual feed intake (most efficient) groups. Results indicated that early lactation was predominantly characterized by significantly elevated levels of medium chain acyl carnitines and glycerophospholipids in high residual feed intake cows. Citrate cycle and glycerophospholipid metabolism were the associated pathways enriched with the significantly different metabolites in early lactation. At mid lactation short and medium chain acyl carnitines, glycerophospholipids and amino acids were the main metabolite groups differing according to residual feed intake category. Late lactation was mainly characterized by increased levels of amino acids in high residual feed intake cows. Amino acid metabolism and biosynthesis pathways were enriched for metabolites that differed between residual feed intake groups at the mid and late lactation stages. Receiver operating characteristic curve analysis identified candidate biomarkers: decanoylcarnitine (area under the curve: AUC = 0.81), dodecenoylcarnitine (AUC = 0.81) and phenylalanine (AUC = 0.85) at early, mid and late stages of lactation, respectively. Furthermore, panels of metabolites predicted residual feed intake with validation coefficient of determination (R ²) of 0.65, 0.37 and 0.60 at early, mid and late lactation stages, respectively. The study sheds light on lactation stage specific metabolic differences between high-residual feed intake and low-residual feed intake lactating dairy cows. Candidate biomarkers that distinguished divergent residual feed intake groups and panels of metabolites that predict individual residual feed intake phenotypes were identified. This result supports the potential of milk metabolites to select for more efficient cows given that traditional residual feed intake phenotyping is costly and difficult to conduct in commercial farms.

Dietary benzoic acid and supplemental enzymes alter fiber-fermenting taxa and metabolites in the cecum of weaned pigs

Inclusion of enzymes and organic acids in pig diets is an important strategy supporting decreased antibiotic usage in pork production. However, limited knowledge exists about how these additives impact intestinal microbes and their metabolites. To examine the effects of benzoic acid and enzymes on gut microbiota and metabolome, 160 pigs were assigned to one of four diets 7 days after weaning: a control diet or the addition of 0.5% benzoic acid, 0.045% dietary enzymes (phytase, β-glucanase, xylanase, and α-amylase), or both and fed ad libitum for 21 to 22 d. Individual growth performance and group diarrhea incidence data were collected throughout the experimental period. A decrease of 20% in pen-level diarrhea incidence from days 8 to 14 in pigs-fed both benzoic acid and enzymes compared to the control diet (P = 0.047). Cecal digesta samples were collected at the end of the experimental period from 40 piglets (n = 10 per group) and evaluated for differences using 16S rRNA sequencing and two-dimensional gas chromatography and time-of-flight mass spectrometry (GCxGC-TOFMS). Analysis of cecal microbiota diversity revealed that benzoic acid altered microbiota composition (Unweighted Unifrac, P = 0.047, r2 = 0.07) and decreased α-diversity (Shannon, P = 0.041; Faith's Phylogenetic Diversity, P = 0.041). Dietary enzymes increased fiber-fermenting bacterial taxa such as Prevotellaceae. Two-step feature selection identified 17 cecal metabolites that differed among diets, including increased microbial cross-feeding product 1,2-propanediol in pigs-fed benzoic acid-containing diets. In conclusion, dietary benzoic acid and enzymes affected the gut microbiota and metabolome of weaned pigs and may support the health and resolution of postweaning diarrhea.

Imputation to whole-genome sequence and its use in genome-wide association studies for pork colour traits in crossbred and purebred pigs

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.

PSVIII-B-1 Biological Pathways Affecting Fertility in Dairy Cattle

Infertility is one of the most economically important traits for the dairy cattle industry, accounting for 22.1 % of culled cows in 2017. Therefore, the objectives of this study were to identify genomic regions via genome-wide association studies (GWAS) and to retrieve the biological pathways that are associated with variation in fertility traits in the dairy cow. Fertility records including days open (DO), Times Bred to Conception (TBRD), Calving Ease (CE), and Days in Milk (DIM) from the Cal Poly Dairy were collected from the DairyComp management system. After quality control, 345 individuals and about 782,000 SNPs were used in the GWAS analyses. Significant SNPs were mapped to the corresponding genes that were used for in-silico functional analyses using DAVID Software. A total of 3, 3, 8, 3, and 7 SNPs were significantly associated with chloride transmembrane transport, neutrophil chemotaxis, cell adhesion, starvation response and nervous system development. The functional analyses suggested potential molecular mechanisms such as chloride transmembrane transport (P = 0.017) and neutrophil chemotaxis (P = 0.02) as significant enriched biological pathways involved with variations seen for DO. Cell adhesion was found as a significant (P = 0.004) biological pathway for TBRD whereas the analysis revealed the starvation response mechanism as significant (P = 0.005) for CE. Nervous system development was significantly (P = 0.0003) associated with DIM. These results from the current study will be validated in a larger population with higher density panel and sequence data.

Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency

Background

Sharing individual phenotype and genotype data between countries is complex and fraught with potential errors, while sharing summary statistics of genome-wide association studies (GWAS) is relatively straightforward, and thus would be especially useful for traits that are expensive or difficult-to-measure, such as feed efficiency. Here we examined: (1) the sharing of individual cow data from international partners; and (2) the use of sequence variants selected from GWAS of international cow data to evaluate the accuracy of genomic estimated breeding values (GEBV) for residual feed intake (RFI) in Australian cows.

Results

GEBV for RFI were estimated using genomic best linear unbiased prediction (GBLUP) with 50k or high-density single nucleotide polymorphisms (SNPs), from a training population of 3797 individuals in univariate to trivariate analyses where the three traits were RFI phenotypes calculated using 584 Australian lactating cows (AUSc), 824 growing heifers (AUSh), and 2526 international lactating cows (OVE). Accuracies of GEBV in AUSc were evaluated by either cohort-by-birth-year or fourfold random cross-validations. GEBV of AUSc were also predicted using only the AUS training population with a weighted genomic relationship matrix constructed with SNPs from the 50k array and sequence variants selected from a meta-GWAS that included only international datasets. The genomic heritabilities estimated using the AUSc, OVE and AUSh datasets were moderate, ranging from 0.20 to 0.36. The genetic correlations (r_g) of traits between heifers and cows ranged from 0.30 to 0.95 but were associated with large standard errors. The mean accuracies of GEBV in Australian cows were up to 0.32 and almost doubled when either overseas cows, or both overseas cows and AUS heifers were included in the training population. They also increased when selected sequence variants were combined with 50k SNPs, but with a smaller relative increase.

Conclusions

The accuracy of RFI GEBV increased when international data were used or when selected sequence variants were combined with 50k SNP array data. This suggests that if direct sharing of data is not feasible, a meta-analysis of summary GWAS statistics could provide selected SNPs for custom panels to use in genomic selection programs. However, since this finding is based on a small cross-validation study, confirmation through a larger study is recommended.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00749-z.

Evaluating the potential of third generation metagenomic sequencing for the detection of BRD pathogens and genetic determinants of antimicrobial resistance in chronically ill feedlot cattle

Background

Bovine respiratory disease (BRD) is an important cause of morbidity and mortality and is responsible for most of the injectable antimicrobial use in the feedlot industry. Traditional bacterial culture can be used to diagnose BRD by confirming the presence of causative pathogens and to support antimicrobial selection. However, given that bacterial culture takes up to a week and early intervention is critical for treatment success, culture has limited utility for informing rapid therapeutic decision-making. In contrast, metagenomic sequencing has the potential to quickly resolve all nucleic acid in a sample, including pathogen biomarkers and antimicrobial resistance genes. In particular, third-generation Oxford Nanopore Technology sequencing platforms provide long reads and access to raw sequencing data in real-time as it is produced, thereby reducing the time from sample collection to diagnostic answer. The purpose of this study was to compare the performance of nanopore metagenomic sequencing to traditional culture and sensitivity methods as applied to nasopharyngeal samples from segregated groups of chronically ill feedlot cattle, previously treated with antimicrobials for nonresponsive pneumonia or lameness.

Results

BRD pathogens were isolated from most samples and a variety of different resistance profiles were observed across isolates. The sequencing data indicated the samples were dominated by Moraxella bovoculi, Mannheimia haemolytica, Mycoplasma dispar, and Pasteurella multocida, and included a wide range of antimicrobial resistance genes (ARGs), encoding resistance for up to seven classes of antimicrobials. Genes conferring resistance to beta-lactams were the most commonly detected, while the tetH gene was detected in the most samples overall. Metagenomic sequencing detected the BRD pathogens of interest more often than did culture, but there was limited concordance between phenotypic resistance to antimicrobials and the presence of relevant ARGs.

Conclusions

Metagenomic sequencing can reduce the time from sampling to results, detect pathogens missed by bacterial culture, and identify genetically encoded determinants of resistance. Increasing sequencing coverage of target organisms will be an essential component of improving the reliability of this technology, such that it can be better used for the surveillance of pathogens of interest, genetic determinants of resistance, and to inform diagnostic decisions.

Predicting enteric methane emission in lactating Holsteins based on reference methane data collected by the GreenFeed system

Methane emission is not included in the current breeding goals for dairy cattle mainly due to the expense and difficulty in obtaining sufficient data to generate accurate estimates of the relevant traits. While several models have been developed to predict methane emission from milk spectra using reference methane data obtained by the respiration chamber, SF6 and sniffer methods, the prediction of methane emission from milk mid-infrared (MIR) spectra using reference methane data collected by the GreenFeed system has not yet been explored. Methane emission was monitored for 151 cows using the GreenFeed system. Prediction models were developed for daily and average (for the trial period of 12 or 14 days) methane production (g/d), yield (g/kg DM intake (DMI)) and intensity (g/kg of fat- and protein-corrected milk) using partial least squares regression. The predictions were evaluated in 100 repeated validation cycles, where animals were randomly partitioned into training (80%) and testing (20%) populations for each cycle. The best performing model was observed for average methane intensity using MIR, parity and DMI with validation coefficient of determination (R²_val) and RMSE of prediction of 0.66 and 4.7 g/kg of fat- and protein-corrected milk, respectively. The accuracy of the best models for average methane production and average methane yield were poor (R²_val = 0.28 and 0.12, respectively). A lower accuracy of prediction was observed for methane intensity and production (R²_val = 0.42 and 0.17) when daily records were used while prediction for methane yield was comparable to that for average methane yield (R²_val = 0.16). Our results suggest the potential to predict methane intensity with moderate accuracy. In this case, prediction models for average methane values were generally better than for daily measures when using the GreenFeed system to obtain reference methane emission measurements.

Neural transcriptomic signature of chronic wasting disease in white-tailed deer

Background

The increasing prevalence and expanding geographical range of the chronic wasting disease (CWD) panzootic in cervids is threatening human, animal, environmental and economic health. The pathogenesis of CWD in cervids is, however, not well understood. We used RNA sequencing (RNA-seq) to compare the brain transcriptome from white-tailed deer (WTD; Odocoileus virginianus) clinically affected with CWD (n = 3) to WTD that tested negative (n = 8) for CWD. In addition, one preclinical CWD+ brain sample was analyzed by RNA-seq.

Results

We found 255 genes that were significantly deregulated by CWD, 197 of which were upregulated. There was a high degree of overlap in differentially expressed genes (DEGs) identified when using either/both the reference genome assembly of WTD for mapping sequenced reads to or the better characterized genome assembly of a closely related model species, Bos taurus. Quantitative PCR of a subset of the DEGs confirmed the RNA-seq data. Gene ontology term enrichment analysis found a majority of genes involved in immune activation, consistent with the neuroinflammatory pathogenesis of prion diseases. A metagenomic analysis of the RNA-seq data was conducted to look for the presence of spiroplasma and other bacteria in CWD infected deer brain tissue.

Conclusions

The gene expression changes identified highlight the role of innate immunity in prion infection, potential disease associated biomarkers and potential targets for therapeutic agents. An association between CWD and spiroplasma infection was not found.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08306-0.

Subfertility in young male mice mutant for chromatin remodeler CECR2

Defects in spermatogenesis are an important cause of male infertility. Multiple aspects of spermatogenesis are controlled by chromatin remodelers, including regulating transcription. We previously described mutations in chromatin remodeling gene Cecr2 that resulted in the lethal neural tube defect exencephaly in most mutant mice, and subfertility in mice that were non-penetrant for exencephaly. Here, we show that the severity of male subfertility is dependent on age. Cecr2GT/Del males contain two mutant alleles, one of which is hypomorphic and therefore produces a small amount of protein. These males sire the fewest pups just after sexual maturity (88% fewer than Cecr2+/+ at P42-60) but improve with age (49% fewer than Cecr2+/+ at P81-100), although never completely recovering to Cecr2+/+ (wild type) levels. When young, they also have defects in testis histology, in vivo fertilization frequency, sperm number and motility, and testis weight that show similar improvement with age. Immunostaining of staged seminiferous tubules showed CECR2 in type A, In and B spermatogonia, and less in preleptotene and leptotene spermatocytes. Histological defects were first apparent in Cecr2GT/Del testes at P24, and RNA-seq analysis revealed 387 differentially expressed genes. This included 66 genes on the X chromosome (almost double the number on any other chromosome), all more highly expressed in Cecr2GT/Del testes. This inappropriate expression of X chromosome genes could be caused by a failure of effective meiotic sex chromosome inactivation. We identify several abnormally expressed genes that may contribute to defects in spermatogenesis at P24. Our results support a role for Cecr2 in juvenile spermatogenesis.

Distinctive roles between rumen epimural and content bacterial communities on beef cattle feed efficiency: A combined analysis

Rumen content-associated (RC) and epithelial tissue-attached (RT) bacterial communities are composed of different phylotypes and play distinctive roles. This study aimed to compare the composition of the RT and RC bacterial communities of steers differing in feed efficiency. The microbiota of RT and RC samples collected from sixteen beef steers with high or low residual feed intake (RFI) were analyzed through sequencing of partial 16S rRNA gene amplicons. Bacteroidetes, Proteobacteria and Firmicutes were the predominant phyla and Prevotella was the most abundant genus in both RC and RT bacterial communities. In total, 19 OTUs of the RC samples and 19 OTUs of the RT samples were differentially abundant (DA) between H-RFI and l-RFI steers. Among them, a common DA OTU belonged to Prevotella genus was identified in both RC and RT samples, making it the potential key microbial marker for indicating feed efficiency of steers. The co-occurrence of the DA OTUs among RT and RC samples suggest the importance of these two communities function as a complete system in influencing host feed efficiency.

166 Livestock Resiliency: Concepts and Approaches

Genetic improvement of health, welfare, efficiency, and fertility traits is challenging due to expensive and fuzzy phenotypes, the polygenic nature of traits, antagonistic genetic correlations to production traits and low heritabilities. Nevertheless, many organizations have introduced large-scale genetic evaluations for such traits in routine selection indexes. Medium and high-density arrays can be applied in genomic selection strategies to improve breeding value accuracy, and also in genome-wide association studies (GWAS) to identify causative mutations responsible for economically important traits. Genomic information is particularly helpful when traits have low heritability. The objective here is to provide a framework for including health, welfare, efficiency, and fertility traits taken from large-scale genetic and genomic analyses and identifying areas of potential improvement in terms of trait definition and performance testing. General tendencies between trait groups confirmed that a number of moderate unfavourable correlations (+/-0.20 or higher) exist between economically important trait complexes and health, welfare, and fertility traits. A number of trait complexes were identified in which “closer-to-biology” phenotypes could provide clear improvements to routine genetic and genomic selection programs. Here we outline development of these phenotypes and describe their collection. While conventional variance component estimation methods have underpinned the genomic component of some traits of economic interest, performance testing for health, welfare, efficiency, and fertility traits remains an elusive goal for breeding programs. Although our results are encouraging, there is much to be done in terms of trait definition and obtaining better measures of physiological parameters for wide-scale application in breeding programs. Close collaboration between veterinarians, physiologists, and geneticists is necessary to attain meaningful advancement in such areas. We would like to acknowledge the support and funding from all national and international partners involved in the RDGP project through the Large Scale Applied Research Project program from Genome Canada

168 Use of Genomic Tools to Improve Production Efficiency, Health Resilience and Carbon Footprint of Beef Production

The aim is to present validation studies that demonstrate the benefits of genomic retained heterozygosity, genomic enhanced expected progeny differences (gEPDs) for feed efficiency and carcass traits, as well as DNA pooling technologies, to the beef industry. Team members of Livestock Gentec are global leaders in beef genomics research as evidenced by their leadership roles on the Canadian Cattle Genome Project, 1,000 Bull Genomes Project, gEPDs for Commercial Cattle Project and the Functional Annotation of ANimal Genomes initiative. These large-scale projects have created databases of 380 whole bovine sequence genomes, &gt;24,000 cattle genotypes imputed to sequence variants using Run 6 genotypes from 1000 Bull Genomes project, and &gt;20,000 cattle with associated phenotypes for feed efficiency, carcass quality, cow fertility and methane emissions. The use of admixture analysis, genome wide association studies, and genomic prediction have resulted in new genomic tools that aid in mate selection, improve herd heterosis, female fertility, lifetime productivity and health resilience, and improve accuracy (acc. &gt;0.36) of gEPDs for 18 traits in crossbred cattle. Genomic retained heterozygosity has a benefit of $161/female over five parities while decreasing morbidity of calves and improving the carbon intensity of beef production. Multi-trait selection studies using gEPDs for residual feed intake (acc. &gt; 0.35) have demonstrated annual rates of genetic progress of 0.7%. Validation studies have reported that sires with superior gEPDs for increased marbling, decreased grade fat, increased ribeye and increased carcass weight (acc. &gt; 0.45) produced progeny with improved AAA retail cut yield (59.9 vs 56.7%). DNA pooling shows potential for cheaper genotyping while providing information on pooled records related to sire contribution, heterosis and performance as influenced by genetics. The application of these genomic tools has potential to improve calf crop percentage, health resilience, and retail cut yield while decreasing the carbon footprint of beef production.

PSXV-29 Late-Breaking: Investigating use of machine learning algorithms to predict days in herd for commercial beef cattle

The objective of this study was to explore the potential of Machine Learning (ML) algorithms to increase the accuracy of predicting individual days in the herd (an indicator of stayability) using reproductive records and genomic information. A total of 6943 cows from 3 herds with reproductive performance were included in the study from which 696 cows had genomic information (genotyped using Illumina Bovine 50k SNP BeadChip). Different libraries based on R and Python were used to test various ML models including Lazy Predict, Scikit-learn, PyCaret, and H2O Flow. Genomic information was subjected to quality control by removing SNPs with an allele frequency less than 0.05 or with a call rate lower than 0.95. A total of 42,689 SNP remained for further analysis and accounted for 11% of phenotypic variation (heritability of 0.11±0.02) in DIH. Different numbers of SNPs (500 SNPs, 1K, 5K, 10K, and 15K) were selected based on their contribution to phenotypic variation from GWAS and were included in the models. Model performance measures, such as mean absolute error (MAE) and mean square of error (MSE), worsened with increased SNPs in the model. Bayesian Ridge algorithm using 500 top SNPs contributed to the phenotypic variance, had the best performance to predict DIH with MAE of 612.6 and R2 of 0.52 in the training population using PyCaret program. When BWT and WWT were added to the model, in addition to SNPs, little change was observed in the model’s performance. Overall, we concluded that ML models had better performance compared to the conventional modeling approach and genomic analysis; CatBoost model had 55% lower mean square of error compared to the simple linear regression (734650 vs 1637410). The results suggest that ML tools have the potential to improve the accuracy of predicting DIH compared to simple linear regression and conventional genomic analysis.

A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits

Background

Imputation to whole-genome sequence is now possible in large sheep populations. It is therefore of interest to use this data in genome-wide association studies (GWAS) to investigate putative causal variants and genes that underpin economically important traits. Merino wool is globally sought after for luxury fabrics, but some key wool quality attributes are unfavourably correlated with the characteristic skin wrinkle of Merinos. In turn, skin wrinkle is strongly linked to susceptibility to “fly strike” (Cutaneous myiasis), which is a major welfare issue. Here, we use whole-genome sequence data in a multi-trait GWAS to identify pleiotropic putative causal variants and genes associated with changes in key wool traits and skin wrinkle.

Results

A stepwise conditional multi-trait GWAS (CM-GWAS) identified putative causal variants and related genes from 178 independent quantitative trait loci (QTL) of 16 wool and skin wrinkle traits, measured on up to 7218 Merino sheep with 31 million imputed whole-genome sequence (WGS) genotypes. Novel candidate gene findings included the MAT1A gene that encodes an enzyme involved in the sulphur metabolism pathway critical to production of wool proteins, and the ESRP1 gene. We also discovered a significant wrinkle variant upstream of the HAS2 gene, which in dogs is associated with the exaggerated skin folds in the Shar-Pei breed.

Conclusions

The wool and skin wrinkle traits studied here appear to be highly polygenic with many putative candidate variants showing considerable pleiotropy. Our CM-GWAS identified many highly plausible candidate genes for wool traits as well as breech wrinkle and breech area wool cover.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00651-0.

Breeding for reduced methane emission and feed-efficient Holstein cows: An international response

Selecting for lower methane (CH₄) emitting animals is one of the best approaches to reduce CH₄ given that genetic progress is permanent and cumulative over generations. As genetic selection requires a large number of animals with records and few countries actively record CH₄, combining data from different countries could help to expedite accurate genetic parameters for CH₄ traits and build a future genomic reference population. Additionally, if we want to include CH₄ in the breeding goal, it is important to know the genetic correlations of CH₄ traits with other economically important traits. Therefore, the aim of this study was first to estimate genetic parameters of 7 suggested methane traits, as well as genetic correlations between methane traits and production, maintenance, and efficiency traits using a multicountry database. The second aim was to estimate genetic correlations within parities and stages of lactation for CH₄. The third aim was to evaluate the expected response of economically important traits by including CH₄ traits in the breeding goal. A total of 15,320 methane production (MeP, g/d) records from 2,990 cows belonging to 4 countries (Canada, Australia, Switzerland, and Denmark) were analyzed. Records on dry matter intake (DMI), body weight (BW), body condition score, and milk yield (MY) were also available. Additional traits such as methane yield (MeY; g/kg DMI), methane intensity (MeI; g/kg energy-corrected milk), a genetic standardized methane production, and 3 definitions of residual methane production (g/d), residual feed intake, metabolic BW (MBW), BW change, and energy-corrected milk were calculated. The estimated heritability of MeP was 0.21, whereas heritability estimates for MeY and MeI were 0.30 and 0.38, and for the residual methane traits heritability ranged from 0.13 to 0.16. Genetic correlations between different methane traits were moderate to high (0.41 to 0.97). Genetic correlations between MeP and economically important traits ranged from 0.29 (MY) to 0.65 (BW and MBW), being 0.41 for DMI. Selection index calculations showed that residual methane had the most potential for inclusion in the breeding goal when compared with MeP, MeY, and MeI, as residual methane allows for selection of low methane emitting animals without compromising other economically important traits. Inclusion of residual feed intake in the breeding goal could further reduce methane, as the correlation with residual methane is moderate and elicits a favorable correlated response. Adding a negative economic value for methane could facilitate a substantial reduction in methane emissions while maintaining an increase in milk production.

Genome-wide association study between copy number variants and hoof health traits in Holstein dairy cattle

Genome-wide association studies based on SNP have been completed for multiple traits in dairy cattle; however, copy number variants (CNV) could add genomic information that has yet to be harnessed. The objectives of this study were to identify CNV in genotyped Holstein animals and assess their association with hoof health traits using deregressed estimated breeding values as pseudophenotypes. A total of 23,256 CNV comprising 1,645 genomic regions were identified in 5,845 animals. Fourteen genomic regions harboring structural variations, including 9 deletions and 5 duplications, were associated with at least 1 of the studied hoof health traits. This group of traits included digital dermatitis, interdigital dermatitis, heel horn erosion, sole ulcer, white line lesion, sole hemorrhage, and interdigital hyperplasia; no regions were associated with toe ulcer. Twenty candidate genes overlapped with the regions associated with these traits including SCART1, NRXN2, KIF26A, GPHN, and OR7A17. In this study, an effect on infectious hoof lesions could be attributed to the PRAME (Preferentially Expressed Antigen in Melanoma) gene. Almost all genes detected in association with noninfectious hoof lesions could be linked to known metabolic disorders. The knowledge obtained considering information of associated CNV to the traits of interest in this study could improve the accuracy of estimated breeding values. This may further increase the genetic gain for these traits in the Canadian Holstein population, thus reducing the involuntary animal losses due to lameness.

Comparative analyses of enteric methane emissions, dry matter intake, and milk somatic cell count in different residual feed intake categories of dairy cows

This study compared the different residual feed intake (RFI) categories of lactating Holsteins with respect to methane (CH4) emissions, dry matter intake (DMI, kg), milk somatic cell count (SCC, 103∙mL−1), and β-hydroxybutyrate (BHB, mmol∙L−1). The RFI was calculated in 131 lactating Holstein cows that were then categorized into −RFI (RFI < 0) vs. +RFI (RFI > 0) and low- [RFI < −0.5 standard deviation (SD)] vs. high-RFI (RFI > 0.5 SD) groups. Milk traits were recorded in 131 cows, whereas CH4 and carbon dioxide were measured in 83. Comparisons of −RFI vs. +RFI and low- vs. high-RFI showed 7.9% (22.3 ± 0.40 vs. 24.2 ± 0.39) and 12.8% (21.1 ± 0.40 vs. 24.2 ± 0.45) decrease (P < 0.05) in DMI of −RFI and low-RFI groups, respectively. Similarly, −RFI and low-RFI cows had lower (P < 0.05) CH4 (g∙d−1) by 9.7% (343.5 ± 11.1 vs. 380.4 ± 10.9) and 15.5% (332.5 ± 12.9 vs. 393.5 ± 12.6), respectively. Milk yield was not different (P > 0.05) in −RFI vs. +RFI and low vs. high comparisons. The −RFI and low-RFI cows had lower (P < 0.05) SCC in −RFI vs. +RFI and low-RFI vs. high-RFI comparisons. The BHB was lower (P < 0.05) in low-RFI compared with the high-RFI group. Low-RFI dairy cows consumed less feed, emitted less CH4 (g∙d−1), and had lower milk SCC and BHB without differing in milk yield.

Comparative Genomic Analysis of Three Pseudomonas Species Isolated from the Eastern Oyster (Crassostrea virginica) Tissues, Mantle Fluid, and the Overlying Estuarine Water Column

The eastern oysters serve as important keystone species in the United States, especially in the Gulf of Mexico estuarine waters, and at the same time, provide unparalleled economic, ecological, environmental, and cultural services. One ecosystem service that has garnered recent attention is the ability of oysters to sequester impurities and nutrients, such as nitrogen (N), from the estuarine water that feeds them, via their exceptional filtration mechanism coupled with microbially-mediated denitrification processes. It is the oyster-associated microbiomes that essentially provide these myriads of ecological functions, yet not much is known on these microbiota at the genomic scale, especially from warm temperate and tropical water habitats. Among the suite of bacterial genera that appear to interplay with the oyster host species, pseudomonads deserve further assessment because of their immense metabolic and ecological potential. To obtain a comprehensive understanding on this aspect, we previously reported on the isolation and preliminary genomic characterization of three Pseudomonas species isolated from minced oyster tissue (P. alcaligenes strain OT69); oyster mantle fluid (P. stutzeri strain MF28) and the water collected from top of the oyster reef (P. aeruginosa strain WC55), respectively. In this comparative genomic analysis study conducted on these three targeted pseudomonads, native to the eastern oyster and its surrounding environment, provided further insights into their unique functional traits, conserved gene pools between the selected pseudomonads, as well as genes that render unique characteristics in context to metabolic traits recruited during their evolutionary history via horizontal gene transfer events as well as phage-mediated incorporation of genes. Moreover, the strains also supported extensively developed resistomes, which suggests that environmental microorganisms native to relatively pristine environments, such as Apalachicola Bay, Florida, have also recruited an arsenal of antibiotic resistant gene determinants, thus posing an emerging public health concern.

Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing

The identification of functional genetic variants and associated candidate genes linked to feed efficiency may help improve selection for feed efficiency in dairy cattle, providing economic and environmental benefits for the dairy industry. This study used RNA-sequencing data obtained from liver tissue from 9 Holstein cows [n = 5 low residual feed intake (RFI), n = 4 high RFI] and 10 Jersey cows (n = 5 low RFI, n = 5 high RFI), which were selected from a single population of 200 animals. Using RNA-sequencing, 3 analyses were performed to identify: (1) variants within low or high RFI Holstein cattle; (2) variants within low or high RFI Jersey cattle; and (3) variants within low or high RFI groups, which are common across both Holstein and Jersey cattle breeds. From each analysis, all variants were filtered for moderate, modifier, or high functional effect, and co-localized quantitative trait loci (QTL) classes, enriched biological processes, and co-localized genes related to these variants, were identified. The overlapping of the resulting genes co-localized with functional SNP from each analysis in both breeds for low or high RFI groups were compared. For the first two analyses, the total number of candidate genes associated with moderate, modifier, or high functional effect variants fixed within low or high RFI groups were 2,810 and 3,390 for Holstein and Jersey breeds, respectively. The major QTL classes co-localized with these variants included milk and reproduction QTL for the Holstein breed, and milk, production, and reproduction QTL for the Jersey breed. For the third analysis, the common variants across both Holstein and Jersey breeds, uniquely fixed within low or high RFI groups were identified, revealing a total of 86,209 and 111,126 functional variants in low and high RFI groups, respectively. Across all 3 analyses for low and high RFI cattle, 12 and 31 co-localized genes were overlapping, respectively. Among the overlapping genes across breeds, 9 were commonly detected in both the low and high RFI groups (INSRR, CSK, DYNC1H1, GAB1, KAT2B, RXRA, SHC1, TRRAP, PIK3CB), which are known to play a key role in the regulation of biological processes that have high metabolic demand and are related to cell growth and regeneration, metabolism, and immune function. The genes identified and their associated functional variants may serve as candidate genetic markers and can be implemented into breeding programs to help improve the selection for feed efficiency in dairy cattle.

Development of SNP-Based Genomic Tools for the Canadian Bison Industry: Parentage Verification and Subspecies Composition

Genomic technologies have been increasingly applied in livestock production due to their utility in production management and animal genetic improvement. The current project aimed to develop genomic resources for the Canadian bison industry, specifically a parentage verification tool and a subspecies composition tool. Both products stand to help with building and maintaining purebred and crossbred bison populations, and in turn bison conservation and production. The development of this genomic toolkit proceeded in two stages. In the single-nucleotide polymorphism (SNP) discovery and selection stage, raw sequence information from 41 bison samples was analyzed, and approximately 52.5 million candidate biallelic SNPs were discovered from 21 samples with high sequence quality. A set of 19,954 SNPs (2,928 for parentage verification and 17,026 for subspecies composition) were then selected for inclusion on an Axiom myDesign custom array. In the refinement and validation stage, 480 bison were genotyped using the custom SNP panel, and the resulting genotypes were analyzed to further filter SNPs and assess tool performance. In various tests using real and simulated genotypes, the two genomic tools showed excellent performance for their respective tasks. Final SNP sets consisting of 191 SNPs for parentage and 17,018 SNPs for subspecies composition are described. As the first SNP-based genomic toolkit designed for the Canadian bison industry, our results may provide a new opportunity in improving the competitiveness and profitability of the industry in a sustainable manner.

Characterization of water treatment-resistant and multidrug-resistant urinary pathogenic Escherichia coli in treated wastewater

A growing body of evidence has demonstrated that extraintestinal pathogenic E. coli (ExPEC), such as the urinary pathogenic E. coli (UPEC), are common constituents of treated wastewater, and therefore represent a potential public health risk. However, no single virulence gene, or set of virulence genes, can be used to conclusively identify this genetically diverse pathotype. As such we sought to identify and characterize the public health relevance of potential UPEC found in treated sewage/wastewater using a comparative genomics approach. Presumptive wastewater UPEC (W-UPEC) were initially identified by virulence gene screening against 5 virulence genes, and for which isolates containing ≥3 virulence genes were whole genome sequenced (n = 24). Single nucleotide polymorphic (SNP) spanning tree analysis demonstrated that many of these wastewater UPEC (WUPEC) were virtually identical at the core genome (0.4 Mbp) when compared to clinical UPEC (C-UPEC) sequences obtained from NCBI, varying by as little as 1 SNP. Remarkably, at the whole genome level, W-UPEC isolates displayed >96% whole genome similarity to C-UPEC counterparts in NCBI, with one strain demonstrating 99.5% genome similarity to a particular C-UPEC strain. The W-UPEC populations were represented by sequence types (ST) known to be clinically important, including ST131, ST95, ST127 and ST640. Many of the W-UPEC carried the exact same complement of virulence genes as their most closely related C-UPEC strains. For example, O25b-ST131 W-UPEC strains possessed the same 80 virulence genes as their most closely related C-UPEC counterparts. Concerningly, W-UPEC strains also carried a plethora of antibiotic resistance genes, and O25b-ST131strains were designated as extended spectrum beta-lactamase (ESBL) producing E. coli by both genome profiling and phenotypic resistance testing. W-UPEC ST131 strains were found in the effluents of a single treatment plant at different times, as well as different wastewater treatment plants, suggesting a differentially ability to survive wastewater treatment. Indeed, in sewage samples treated with chlorine doses sufficient for inducing a ∼99.99% reduction in total E. coli levels, UPEC represented a significant proportion of the chlorine-resistant population. By contrast, no Shiga toxin-producing E. coli were observed in these chlorinated sewage libraries. Our results suggest that clinically-relevant UPEC exist in treated wastewater effluents and that they appear to be specifically adapted to survive wastewater treatment processes.

High confidence copy number variants identified in Holstein dairy cattle from whole genome sequence and genotype array data

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.

Visualizing and comparing circular genomes using the CGView family of tools

Graphical genome maps are widely used to assess genome features and sequence characteristics. The CGView (Circular Genome Viewer) software family is a popular collection of tools for generating genome maps for bacteria, organelles and viruses. In this review, we describe the capabilities of the original CGView program along with those of subsequent companion applications, including the CGView Server and the CGView Comparison Tool. We also discuss GView, a graphical user interface-enabled rewrite of CGView, and the GView Server, which offers several integrated analyses for identifying shared or unique genome regions relative to a collection of comparison genomes. We conclude with some remarks about our current development efforts related to CGView aimed at adding new functionality while increasing ease of use.

Differential visible spectral influence on carbon metabolism in heterotrophic marine flavobacteria

The visible spectrum of solar radiation is known to stimulate photoheterotrophic bacterial carbon metabolism. However, its impact on 'strictly' heterotrophic bacteria remains less explored. Here, we show that heterotrophic flavobacteria exhibit enhanced uptake and mineralization of dissolved organic carbon with increasing wavelengths of visible light, without employing any 'known' light-harvesting mechanisms. RNA sequencing identified blue light as a major constraint in the extracellular enzymatic hydrolysis of polymeric carbohydrates and acquisition of sugars, despite acting as a stimulus for inorganic carbon sequestration. In contrast, green-red and continuous full-spectrum lights activated diverse hydrolytic enzymes and sugar transporters, but obstructed inorganic carbon fixation. This 'metabolic switching' was apparent through limited nutrient uptake, suppressed light-sensitivity, oxidative stress response and promotion of inorganic carbon sequestration pathways under blue light. The visible light impact on metabolism may be of significant ecological relevance as it appears to promote cell-mediated mineralization of organic carbon in 'green-colored' chlorophyll-rich copiotrophic coastal seawater and inorganic carbon sequestration in 'blue-colored' oligotrophic open ocean. Thus, a novel regulatory role played by light on heterotrophic metabolism and a hidden potential of flavobacteria to sense and respond differentially to monochromatic lights influencing marine carbon cycling were unraveled.

A large interactive visual database of copy number variants discovered in taurine cattle

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.

Liver transcriptome profiling of beef steers with divergent growth rate, feed intake, or metabolic body weight phenotypes1

Average daily gain (ADG) and daily dry matter intake (DMI) are key determinants of beef industry profitability. These traits together with metabolic body weight (MWT) are combined as component traits to calculate residual feed intake (RFI), a common measure of feed efficiency in beef cattle. Recently, there have been significant efforts towards molecular genetic characterization of RFI through transcriptomic studies in different breeds and tissues. However, molecular mechanisms of RFI component traits still remain predominately unexplored. Therefore, in the current study, we investigated the hepatic transcriptomic profiles and their associations with ADG, DMI, and MWT in Angus, Charolais, and Kinsella Composite (KC) populations through global RNAseq analyses. In each population and for each trait, 12 steers with extreme phenotypes (n = 6 low and n = 6 high) were analyzed for differential gene expression. These animals were from 20 beef steers of each Angus, Charolais, and KC breed population that were initially selected for a transcriptome study of RFI. At a false discovery rate <0.05 and fold change >1.5, we identified 123, 102, and 78 differentially expressed (DE) genes between high- and low-ADG animals of Angus, Charolais, and KC populations, respectively. For DMI, 108, 180, and 156 DE genes were identified between high- and low-DMI from Angus, Charolais, and KC populations, respectively, while for MWT, 80, 82, and 84 genes were differentially expressed between high- and low-MWT animals in Angus, Charolais, and KC populations, respectively. The identified DE genes were largely breed specific (81.7% for ADG, 82.7% for DMI, and 83% for MWT), but were largely involved in the same biological functions across the breeds. Among the most enriched biological functions included metabolism of major nutrients (lipids, carbohydrates, amino acids, vitamins, and minerals), small molecule biochemistry, cellular movement, cell morphology, and cell-to-cell signaling and interaction. Notably, we identified multiple DE genes that are involved in cholesterol biosynthesis, and immune response pathways for the 3 studied traits. Thus, our findings present potential molecular genetic mechanisms and candidate genes that influence feed intake, growth, and MWT of beef cattle.

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: I: feed efficiency and component traits

BACKGROUND

Genome wide association studies (GWAS) on residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) were conducted in a population of 7573 animals from multiple beef cattle breeds based on 7,853,211 imputed whole genome sequence variants. The GWAS results were used to elucidate genetic architectures of the feed efficiency related traits in beef cattle.

RESULTS

The DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants followed a scaled inverse chi-squared distribution to a greater extent. With a threshold of P-value < 1.00E-05, 16, 72, 88, and 116 lead DNA variants on multiple chromosomes were significantly associated with RFI, DMI, ADG, and MWT, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on DMI, ADG, and MWT were found on chromosomes 6, 14 and 20. On average, missense, 3'UTR, 5'UTR, and other regulatory region variants exhibited larger allele substitution effects in comparison to other functional classes. Intergenic and intron variants captured smaller proportions of additive genetic variance per DNA variant. Instead 3'UTR and synonymous variants explained a greater amount of genetic variance per DNA variant for all the traits examined while missense, 5'UTR and other regulatory region variants accounted for relatively more additive genetic variance per sequence variant for RFI and ADG, respectively. In total, 25 to 27 enriched cellular and molecular functions were identified with lipid metabolism and carbohydrate metabolism being the most significant for the feed efficiency traits.

CONCLUSIONS

RFI is controlled by many DNA variants with relatively small effects whereas DMI, ADG, and MWT are influenced by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory region and synonymous functional classes play a more important role per sequence variant in determining variation of the feed efficiency traits. The genetic architecture as revealed by the GWAS of the imputed 7,853,211 DNA variants will improve our understanding on the genetic control of feed efficiency traits in beef cattle.

Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: II: carcass merit traits

BACKGROUND

Genome wide association studies (GWAS) were conducted on 7,853,211 imputed whole genome sequence variants in a population of 3354 to 3984 animals from multiple beef cattle breeds for five carcass merit traits including hot carcass weight (HCW), average backfat thickness (AFAT), rib eye area (REA), lean meat yield (LMY) and carcass marbling score (CMAR). Based on the GWAS results, genetic architectures of the carcass merit traits in beef cattle were elucidated.

RESULTS

The distributions of DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants conformed to a scaled inverse chi-squared distribution to a greater extent. At a threshold of P-value < 10-5, 51, 33, 46, 40, and 38 lead DNA variants on multiple chromosomes were significantly associated with HCW, AFAT, REA, LMY, and CMAR, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on HCW, AFAT, REA, and LMY were found on chromosome 6. On average, missense variants, 3'UTR variants, 5'UTR variants, and other regulatory region variants exhibited larger allele substitution effects on the traits in comparison to other functional classes. The amounts of additive genetic variance explained per DNA variant were smaller for intergenic and intron variants on all the traits whereas synonymous variants, missense variants, 3'UTR variants, 5'UTR variants, downstream and upstream gene variants, and other regulatory region variants captured a greater amount of additive genetic variance per sequence variant for one or more carcass merit traits investigated. In total, 26 enriched cellular and molecular functions were identified with lipid metabolisms, small molecular biochemistry, and carbohydrate metabolism being the most significant for the carcass merit traits.

CONCLUSIONS

The GWAS results have shown that the carcass merit traits are controlled by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory, synonymous, and missense functional classes have relatively larger impacts per sequence variant on the variation of carcass merit traits. The genetic architecture as revealed by the GWAS will improve our understanding on genetic controls of carcass merit traits in beef cattle.

Draft genome sequence reveals co-occurrence of multiple antimicrobial resistance and plant probiotic traits in rice root endophytic strain Burkholderia sp. LS-044 affiliated to Burkholderia cepacia complex

OBJECTIVES

Members of the Burkholderia cepacia complex (Bcc) have been isolated from various environmental and clinical samples and reportedly pose a threat to human health. Here we examine the draft genome sequence of Burkholderia sp. LS-044, an antibiotic-resistant endophytic strain affiliated to the Bcc (ST895) inhabiting rice (Oryza sativa ssp. japonica cv. Tainung 71) root.

METHODS

Antimicrobial susceptibility of LS-044 was evaluated comparatively with other Burkholderia sp. (CC-Al74 and CC-3XP9) using commercial ATB PSE 5 test strips. The genome of LS-044 was sequenced using an Illumina MiSeq platform. Plant probiotic and antimicrobial resistance genes were screened by Rapid Annotation using Subsystem Technology (RAST), CARD 2017, NCBI and/or UniProt.

RESULTS

Plant-associated members of Bcc (LS-044 and CC-Al74) exhibited greater resistance to the majority of antibiotics tested. The draft genome sequence of LS-044 contained 8.78 Mbp in 62 contigs having a G + C content of 66.5%, 8868 coding sequences and 75 RNAs. The genome harboured genes coding for LysR-type β-lactamase transcription regulator, classes A, C and D β-lactamases, several metal-dependent β-lactamases, antibiotic efflux proteins, and proteins conferring resistance to colistin, streptothricin, colicin and fluoroquinolones. Similarly, it also possessed genes for copper homeostasis, copper-cobalt-zinc-cadmium-chromium resistance and reduction of mercury. Genes involved in flagellar motility, hydrolysis of murein and chitin, production of siderophore and auxin, and metabolism of aromatic compounds were also found.

CONCLUSION

Genome sequence data revealed an interlinked occurrence of plant probiotic traits and antimicrobial resistance in the rice root endophyte LS-044.

Evidence for the evolution, clonal expansion and global dissemination of water treatment-resistant naturalized strains of Escherichia coli in wastewater

We previously demonstrated the existence of naturalized strains of E. coli in wastewater and herein perform an in-depth comparative whole genome analysis of these strains (n = 17). Fourteen of the Canadian E. coli strains, isolated from geographically separated wastewater treatment plants, were virtually identical at the core genome and were ≥96% similar at the whole genome level, suggesting clonal-relatedness among these isolates. Remarkably, these strains were shown to be extremely similar to the genome of an E. coli isolated from wastewater in Switzerland, suggesting a global distribution of these strains. The genomes of three other Canadian wastewater strains were more diverse but very similar to the genomes of E. coli isolates collected from U.S. wastewater samples. Based on maximum likelihood phylogenetic analysis, wastewater strains from Canada, the U.S. and Switzerland formed a clade separate from other known enteric phylogroups (i.e., A, B1, B2, D, E) and the cryptic clades. All Canadian, Swiss and U.S. wastewater strains possessed a common SNP biomarker pattern across their genomes, and a sub-population (i.e., 14 Canadian and 1 Swiss strain) also possessed a previously identified wastewater-specific marker known as uspC-IS30-flhDC element. Biochemical heat mapping of 518 categories of genes recapitulated phylogeny, with wastewater strains phenotypically clustering separately from enteric and cryptic clades. Wastewater strains were enriched for stress-response genes (i.e., nutrient acquisition/deprivation, DNA repair, oxidative stress, and UV resistance) - elements reflective of their environmental survival challenges. Wastewater strains were shown to carry a plethora of known antibiotic resistance (AR) genes, the patterns of which were remarkably similar among all Canadian, U.S. and Swiss wastewater strains. Virulence gene composition was also similar among all the wastewater strains, with an abundant representation of virulence genes commonly associated with urinary pathogenic E. coli (UPEC) as well as enterohemorrhagic (EHEC) E. coli. The remarkable degree of similarity between all wastewater strains from Canada, Switzerland and the U.S. suggests the evolution and global-dissemination of water treatment-resistant clone of E. coli. These finding, along with others, raise some important concerns about the potential for emergence of E. coli pathotypes resistant to water-treatment.

Optimizing Selection of the Reference Population for Genotype Imputation From Array to Sequence Variants

Imputation of high-density genotypes to whole-genome sequences (WGS) is a cost-effective method to increase the density of available markers within a population. Imputed genotypes have been successfully used for genomic selection and discovery of variants associated with traits of interest for the population. To allow for the use of imputed genotypes for genomic analyses, accuracy of imputation must be high. Accuracy of imputation is influenced by multiple factors, such as size and composition of the reference group, and the allele frequency of variants included. Understanding the use of imputed WGSs prior to the generation of the reference population is important, as accurate imputation might be more focused, for instance, on common or on rare variants. The aim of this study was to present and evaluate new methods to select animals for sequencing relying on a previously genotyped population. The Genetic Diversity Index method optimizes the number of unique haplotypes in the future reference population, while the Highly Segregating Haplotype selection method targets haplotype alleles found throughout the majority of the population of interest. First the WGSs of a dairy cattle population were simulated. The simulated sequences mimicked the linkage disequilibrium level and the variants’ frequency distribution observed in currently available Holstein sequences. Then, reference populations of different sizes, in which animals were selected using both novel methods proposed here as well as two other methods presented in previous studies, were created. Finally, accuracies of imputation obtained with different reference populations were compared against each other. The novel methods were found to have overall accuracies of imputation of more than 0.85. Accuracies of imputation of rare variants reached values above 0.50. In conclusion, if imputed sequences are to be used for discovery of novel associations between variants and traits of interest in the population, animals carrying novel information should be selected and, consequently, the Genetic Diversity Index method proposed here may be used. If sequences are to be used to impute the overall genotyped population, a reference population consisting of common haplotypes carriers selected using the proposed Highly Segregating Haplotype method is recommended.

Novel Stenotrophomonas maltophilia temperate phage DLP4 is capable of lysogenic conversion

BACKGROUND

Temperate bacteriophages are capable of lysogenic conversion of new bacterial hosts. This phenomenon is often ascribed to "moron" elements that are acquired horizontally and transcribed independently from the rest of the phage genes. Whereas some bacterial species exhibit relatively little prophage-dependent phenotypic changes, other bacterial species such as Stenotrophomonas maltophilia appear to commonly adopt prophage genetic contributions.

RESULTS

The novel S. maltophilia bacteriophage DLP4 was isolated from soil using the highly antibiotic-resistant S. maltophilia strain D1585. Genome sequence analysis and functionality testing showed that DLP4 is a temperate phage capable of lysogenizing D1585. Two moron genes of interest, folA (BIT20_024) and ybiA (BIT20_065), were identified and investigated for their putative activities using complementation testing and phenotypic and transcriptomic changes between wild-type D1585 and the D1585::DLP4 lysogen. The gp24 / folA gene encodes dihydrofolate reductase (DHFR: FolA), an enzyme responsible for resistance to the antibiotic trimethoprim. I-TASSER analysis of DLP4 FolA predicted structural similarity to Bacillus anthracis DHFR and minimum inhibitory concentration experiments demonstrated that lysogenic conversion of D1585 by DLP4 provided the host cell with an increase in trimethoprim resistance. The gp65 / ybiA gene encodes N-glycosidase YbiA, which in E. coli BW25113 is required for its swarming motility phenotype. Expressing DLP4 ybiA in strain ybiA770(del)::kan restored its swarming motility activity to wildtype levels. Reverse transcription-PCR confirmed the expression of both of these genes during DLP4 lysogeny.

CONCLUSIONS

S. maltophilia temperate phage DLP4 contributes to the antibiotic resistance exhibited by its lysogenized host strain. Genomic analyses can greatly assist in the identification of phage moron genes potentially involved in lysogenic conversion. Further research is required to fully understand the specific contributions temperate phage moron genes provide with respect to the antibiotic resistance and virulence of S. maltophilia host cells.

Defining the role of Parasutterella, a previously uncharacterized member of the core gut microbiota

The genus of Parasutterella has been defined as a core component of the human and mouse gut microbiota, and has been correlated with various health outcomes. However, like most core microbes in the gastrointestinal tract (GIT), very little is known about the biology of Parasutterella and its role in intestinal ecology. In this study, Parasutterella was isolated from the mouse GIT and characterized in vitro and in vivo. Mouse, rat, and human Parasutterella isolates were all asaccharolytic and producers of succinate. The murine isolate stably colonized the mouse GIT without shifting bacterial composition. Notable changes in microbial-derived metabolites were aromatic amino acid, bilirubin, purine, and bile acid derivatives. The impacted bile acid profile was consistent with altered expression of ileal bile acid transporter genes and hepatic bile acid synthesis genes, supporting the potential role of Parasutterella in bile acid maintenance and cholesterol metabolism. The successful colonization of Parasutterella with a single environmental exposure to conventional adult mice demonstrates that it fills the ecological niche in the GIT and contributes to metabolic functionalities. This experiment provides the first indication of the role of Parasutterella in the GIT, beyond correlation, and provides insight into how it may contribute to host health.

Accuracy of imputation to whole-genome sequence in sheep

Background

The use of whole-genome sequence (WGS) data for genomic prediction and association studies is highly desirable because the causal mutations should be present in the data. The sequencing of 935 sheep from a range of breeds provides the opportunity to impute sheep genotyped with single nucleotide polymorphism (SNP) arrays to WGS. This study evaluated the accuracy of imputation from SNP genotypes to WGS using this reference population of 935 sequenced sheep.

Results

The accuracy of imputation from the Ovine Infinium^® HD BeadChip SNP (~ 500 k) to WGS was assessed for three target breeds: Merino, Poll Dorset and F1 Border Leicester × Merino. Imputation accuracy was highest for the Poll Dorset breed, although there were more Merino individuals in the sequenced reference population than Poll Dorset individuals. In addition, empirical imputation accuracies were higher (by up to 1.7%) when using larger multi-breed reference populations compared to using a smaller single-breed reference population. The mean accuracy of imputation across target breeds using the Minimac3 or the FImpute software was 0.94. The empirical imputation accuracy varied considerably across the genome; six chromosomes carried regions of one or more Mb with a mean imputation accuracy of < 0.7. Imputation accuracy in five variant annotation classes ranged from 0.87 (missense) up to 0.94 (intronic variants), where lower accuracy corresponded to higher proportions of rare alleles. The imputation quality statistic reported from Minimac3 (R²) had a clear positive relationship with the empirical imputation accuracy. Therefore, by first discarding imputed variants with an R² below 0.4, the mean empirical accuracy across target breeds increased to 0.97. Although accuracy of genomic prediction was less affected by filtering on R² in a multi-breed population of sheep with imputed WGS, the genomic heritability clearly tended to be lower when using variants with an R² ≤ 0.4.

Conclusions

The mean imputation accuracy was high for all target breeds and was increased by combining smaller breed sets into a multi-breed reference. We found that the Minimac3 software imputation quality statistic (R²) was a useful indicator of empirical imputation accuracy, enabling removal of very poorly imputed variants before downstream analyses.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0443-5) contains supplementary material, which is available to authorized users.