In silico prediction and expression analysis of vaccine candidate genes of Campylobacter jejuni.

Campylobacter jejuni (C. jejuni) is the most common food-borne pathogen that causes human gastroenteritis in the United States. Consumption of contaminated poultry products is considered as the major source of human Campylobacter infection. An effective vaccine would be a promising alternative to antibiotic supplements to curb C. jejuni colonization in poultry gastrointestinal (GI) tract. However, the genetic diversity among the C. jejuni isolates makes vaccine production more challenging. Despite many attempts, an effective Campylobacter vaccine is not yet available. This study aimed to identify suitable candidates to develop a subunit vaccine against C. jejuni, which could reduce colonization in the GI tract of the poultry. In the current study, 4 C. jejuni strains were isolated from retail chicken meat and poultry litter samples and their genomes were sequenced utilizing next-generation sequencing technology. The genomic sequences of C. jejuni strains were screened to identify potential antigens utilizing the reverse vaccinology approach. In silico genome analysis predicted 3 conserved potential vaccine candidates (phospholipase A [PldA], TonB dependent vitamin B12 transporter [BtuB], and cytolethal distending toxin subunit B [CdtB]) suitable for the development of a vaccine. Furthermore, the expression of predicted genes during host-pathogen interaction was analyzed by an infection study using an avian macrophage-like immortalized cell line (HD11). The HD11 was infected with C. jejuni strains, and the RT-qPCR assay was performed to determine the expression of the predicted genes. The expression difference was analyzed using ΔΔCt methods. The results indicate that all 3 predicted genes, PldA, BtuB, and CdtB, were upregulated in 4 tested C. jejuni strains irrespective of their sources of isolation. In conclusion, in silico prediction and gene expression analysis during host-pathogen interactions identified 3 potential vaccine candidates for C. jejuni.

A high-quality chromosome-level genome assembly of rohu carp, Labeo rohita, and its utilization in SNP-based exploration of gene flow and sex determination.

Labeo rohita (rohu) is a carp important to aquaculture in South Asia, with a production volume close to Atlantic salmon. While genetic improvements to rohu are ongoing, the genomic methods commonly used in other aquaculture improvement programs have historically been precluded in rohu, partially due to the lack of a high-quality reference genome. Here we present a high-quality de novo genome produced using a combination of next-generation sequencing technologies, resulting in a 946 Mb genome consisting of 25 chromosomes and 2,844 unplaced scaffolds. Notably, while approximately half the size of the existing genome sequence, our genome represents 97.9% of the genome size newly estimated here using flow cytometry. Sequencing from 120 individuals was used in conjunction with this genome to predict the population structure, diversity, and divergence in three major rivers (Jamuna, Padma, and Halda), in addition to infer a likely sex determination mechism in rohu. These results demonstrate the utility of the new rohu genome in modernizing some aspects of rohu genetic improvement programs.

Dual Domestication, Diversity, and Differential Introgression in Old World Cotton Diploids.

Domestication in the cotton genus is remarkable in that it has occurred independently four different times at two different ploidy levels. Relatively little is known about genome evolution and domestication in the cultivated diploid species Gossypium herbaceum and Gossypium arboreum, due to the absence of wild representatives for the latter species, their ancient domestication, and their joint history of human-mediated dispersal and interspecific gene flow. Using in-depth resequencing of a broad sampling from both species, we provide support for their independent domestication, as opposed to a progenitor-derivative relationship, showing that diversity (mean π = 6 × 10-3) within species is similar, and that divergence between species is modest (FST = 0.413). Individual accessions were homozygous for ancestral single-nucleotide polymorphisms at over half of variable sites, while fixed, derived sites were at modest frequencies. Notably, two chromosomes with a paucity of fixed, derived sites (i.e., chromosomes 7 and 10) were also strongly implicated as having experienced high levels of introgression. Collectively, these data demonstrate variable permeability to introgression among chromosomes, which we propose is due to divergent selection under domestication and/or the phenomenon of F2 breakdown in interspecific crosses. Our analyses provide insight into the evolutionary forces that shape diversity and divergence in the diploid cultivated species and establish a foundation for understanding the contribution of introgression and/or strong parallel selection to the extensive morphological similarities shared between species.

Comparative Analysis of Multiple GWAS Results Identifies Metabolic Pathways Associated with Resistance to A. flavus Infection and Aflatoxin Accumulation in Maize.

Aflatoxins are carcinogenic secondary metabolites produced by several species of Aspergillus, including Aspergillus flavus, an important ear rot pathogen in maize. Most commercial corn hybrids are susceptible to infection by A. flavus, and aflatoxin contaminated grain causes economic damage to farmers. The creation of inbred lines resistant to Aspergillus fungal infection or the accumulation of aflatoxins would be aided by knowing the pertinent alleles and metabolites associated with resistance in corn lines. Multiple Quantitative Trait Loci (QTL) and association mapping studies have uncovered several dozen potential genes, but each with a small effect on resistance. Metabolic pathway analysis, using the Pathway Association Study Tool (PAST), was performed on aflatoxin accumulation resistance using data from four Genome-wide Association Studies (GWAS). The present research compares the outputs of these pathway analyses and seeks common metabolic mechanisms underlying each. Genes, pathways, metabolites, and mechanisms highlighted here can contribute to improving phenotypic selection of resistant lines via measurement of more specific and highly heritable resistance-related traits and genetic gain via marker assisted or genomic selection with multiple SNPs linked to resistance-related pathways.

Complete Genome Sequences of Four Campylobacter jejuni Strains Isolated from Retail Chicken Meat and Broiler Feces.

Campylobacter jejuni is the leading pathogen that causes foodborne infections. Here, we report the complete genome sequences of four C. jejuni strains isolated from retail chicken meat and broiler feces samples. Genes encoding type VI secretion and antibiotic resistance were detected among these isolates.

Identification of Antimicrobial Resistance Determinants in Aeromonas veronii Strain MS-17-88 Recovered From Channel Catfish (Ictalurus punctatus).

Aeromonas veronii is a Gram-negative species ubiquitous in different aquatic environments and capable of causing a variety of diseases to a broad host range. Aeromonas species have the capability to carry and acquire antimicrobial resistance (AMR) elements, and currently multi-drug resistant (MDR) Aeromonas isolates are commonly found across the world. A. veronii strain MS-17-88 is a MDR strain isolated from catfish in the southeastern United States. The present study was undertaken to uncover the mechanism of resistance in MDR A. veronii strain MS-17-88 through the detection of genomic features. To achieve this, genomic DNA was extracted, sequenced, and assembled. The A. veronii strain MS-17-88 genome comprised 5,178,226-bp with 58.6% G+C, and it encoded several AMR elements, including imiS, ampS, mcr-7.1, mcr-3, catB2, catB7, catB1, floR, vat(F), tet(34), tet(35), tet(E), dfrA3, and tetR. The phylogeny and resistance profile of a large collection of A. veronii strains, including MS-17-88, were evaluated. Phylogenetic analysis showed a close relationship between MS-17-88 and strain Ae5 isolated from fish in China and ARB3 strain isolated from pond water in Japan, indicating a common ancestor of these strains. Analysis of phage elements revealed 58 intact, 63 incomplete, and 15 questionable phage elements among the 53 A. veronii genomes. The average phage element number is 2.56 per genome, and strain MS-17-88 is one of two strains having the maximum number of identified prophage elements (6 elements each). The profile of resistance against various antibiotics across the 53 A. veronii genomes revealed the presence of tet(34), mcr-7.1, mcr-3, and dfrA3 in all genomes (100%). By comparison, sul1 and sul2 were detected in 7.5% and 1.8% of A. veronii genomes. Nearly 77% of strains carried tet(E), and 7.5% of strains carried floR. This result suggested a low abundance and prevalence of sulfonamide and florfenicol resistance genes compared with tetracycline resistance among A. veronii strains. Overall, the present study provides insights into the resistance patterns among 53 A. veronii genomes, which can inform therapeutic options for fish affected by A. veronii.

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information.

Recently, a new implementation of a previously described method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and released. The Pathway Association Study Tool (PAST) was developed to address concerns with user-friendliness and slow-running analyses. This new user-friendly tool has been released on Bioconductor and Github. In testing, PAST ran analyses in less than one hour that previously required twenty-four or more hours. In this article, we present the protocol for using either the Shiny application or the R console to run PAST.

Toward a more holistic method of genome assembly assessment.

BACKGROUND: A key use of high throughput sequencing technology is the sequencing and assembly of full genome sequences. These genome assemblies are commonly assessed using statistics relating to contiguity of the assembly. Measures of contiguity are not strongly correlated with information about the biological completion or correctness of the assembly, and a commonly reported metric, N50, can be misleading. Over the years, multiple research groups have rejected the overuse of N50 and sought to develop more informative metrics. RESULTS: This paper presents a review of problems that arise from relying solely on contiguity as a measure of genome assembly quality as well as current alternative methods. Alternative methods are compared on the basis of how informative they are about the biological quality of the assembly and how easy they are to use. A comprehensive method for using multiple metrics of measuring assembly quality is presented. CONCLUSIONS: This study aims to report on the status of assembly assessment methods and compare them, as well as to offer a comprehensive method that incorporates multiple facets of quality assessment. Weaknesses and strengths of varying methods are presented and explained, with recommendations based on speed of analysis and user friendliness.

PAST: The Pathway Association Studies Tool to Infer Biological Meaning from GWAS Datasets.

In recent years, a bioinformatics method for interpreting genome-wide association study (GWAS) data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 h to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns. PAST has been implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately half an hour to one hour by processing data in parallel and produced the same results as the previously developed method. PAST has many user-specified options for maximum customization. Thus, to promote a powerful new pathway analysis methodology that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible, efficient, and user-friendly tool. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotypes.

AOPERA: A proposed methodology and inventory of effective tools to link chemicals to adverse outcome pathways.

New approaches, like the Adverse Outcome Pathway (AOP) framework, have been developed to describe how chemicals cause toxicity by linking in vitro assays to adverse health outcomes. However, approaches, tools and resources for development of AOPs have not been well described. Here we review information resources for AOP development and define a streamlined process for linking a chemical to an existing AOP. We propose a four step process to facilitate AOP development: link the uncharacterized chemical directly to Molecular Initiating Events, Key Events, or Adverse Outcomes; identify analogs with toxicological information for the uncharacterized chemical; link the characterized chemical (initial chemical if characterized, a characterized analog if initial chemical is not) to Molecular Initiating Events, Key Events, or Adverse Outcomes; and identify AOPs that contain the Molecular Initiating Events, Key Events, or Adverse Outcomes that were found in Steps 1 and 3. The process and library of informational resources proposed and tested here served as the foundation for an informational online tool (AOPERA) that helps practitioners identify their current-state knowledge gaps, navigate the four-step process, and connect to relevant resources. AOPERA can be found at https://igbb.github.io/AOPERA_HTML. Additionally, we anticipate that by simplifying and standardizing the process of linking a chemical to a known AOP, we will lower the barrier to entry for this objective and increase its accessibility to new practitioners. In turn, this may increase the demand for new or improved AOPs to which practitioners can link chemicals, thereby contributing to the expansion of the library of known AOPs.

Keanu: a novel visualization tool to explore biodiversity in metagenomes.

BACKGROUND: One of the main challenges when analyzing complex metagenomics data is the fact that large amounts of information need to be presented in a comprehensive and easy-to-navigate way. In the process of analyzing FASTQ sequencing data, visualizing which organisms are present in the data can be useful, especially with metagenomics data or data suspected to be contaminated. Here, we describe the development and application of a command-line tool, Keanu, for visualizing and exploring sample content in metagenomics data. We developed Keanu as an interactive tool to make viewing complex data easier. RESULTS: Keanu, a tool for exploring sequence content, helps a user to understand the presence and abundance of organisms in a sample by analyzing alignments against a database that contains taxonomy data and displaying them in an interactive web page. The content of a sample can be presented either as a collapsible tree, with node size indicating abundance, or as a bilevel partition graph, with arc size indicating abundance. Here, we illustrate how Keanu works by exploring shotgun metagenomics data from a sample collected from a bluff that contained paleosols and a krotovina in an alpine site in Ft. Greely, Alaska. CONCLUSIONS: Keanu provides a simple means by which researchers can explore and visualize species present in sequence data generated from complex communities and environments. Keanu is written in Python and is freely available at https://github.com/IGBB/keanu .

Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis.

Maize (Zea mays mays) oil is a rich source of polyunsaturated fatty acids (FAs) and energy, making it a valuable resource for human food, animal feed, and bio-energy. Although this trait has been studied via conventional genome-wide association study (GWAS), the single nucleotide polymorphism (SNP)-trait associations generated by GWAS may miss the underlying associations when traits are based on many genes, each with small effects that can be overshadowed by genetic background and environmental variation. Detecting these SNPs statistically is also limited by the levels set for false discovery rate. A complementary pathways analysis that emphasizes the cumulative aspects of SNP-trait associations, rather than just the significance of single SNPs, was performed to understand the balance of lipid metabolism, conversion, and catabolism in this study. This pathway analysis indicated that acyl-lipid pathways, including biosynthesis of wax esters, sphingolipids, phospholipids and flavonoids, along with FA and triacylglycerol (TAG) biosynthesis, were important for increasing oil and FA content. The allelic variation found among the genes involved in many degradation pathways, and many biosynthesis pathways leading from FAs and carbon partitioning pathways, was critical for determining final FA content, changing FA ratios and, ultimately, to final oil content. The pathways and pathway networks identified in this study, and especially the acyl-lipid associated pathways identified beyond what had been found with GWAS alone, provide a real opportunity to precisely and efficiently manipulate high-oil maize genetic improvement.

Insights into the Evolution of the New World Diploid Cottons (Gossypium, Subgenus Houzingenia) Based on Genome Sequencing.

We employed phylogenomic methods to study molecular evolutionary processes and phylogeny in the geographically widely dispersed New World diploid cottons (Gossypium, subg. Houzingenia). Whole genome resequencing data (average of 33× genomic coverage) were generated to reassess the phylogenetic history of the subgenus and provide a temporal framework for its diversification. Phylogenetic analyses indicate that the subgenus likely originated following transoceanic dispersal from Africa about 6.6 Ma, but that nearly all of the biodiversity evolved following rapid diversification in the mid-Pleistocene (0.5-2.0 Ma), with multiple long-distance dispersals required to account for range expansion to Arizona, the Galapagos Islands, and Peru. Comparative analyses of cpDNAversus nuclear data indicate that this history was accompanied by several clear cases of interspecific introgression. Repetitive DNAs contribute roughly half of the total 880 Mb genome, but most transposable element families are relatively old and stable among species. In the genic fraction, pairwise synonymous mutation rates average 1% per Myr, with nonsynonymous changes being about seven times less frequent. Over 1.1 million indels were detected and phylogenetically polarized, revealing a 2-fold bias toward deletions over small insertions. We suggest that this genome down-sizing bias counteracts genome size growth by TE amplification and insertions, and helps explain the relatively small genomes that are restricted to this subgenus. Compared with the rate of nucleotide substitution, the rate of indel occurrence is much lower averaging about 17 nucleotide substitutions per indel event.

Genome-Wide Association and Metabolic Pathway Analysis of Corn Earworm Resistance in Maize.

Maize ( L.) is a staple crop of economic, industrial, and food security importance. Damage to the growing ears by corn earworm [ (Boddie)] is a major economic burden and increases secondary fungal infections and mycotoxin levels. To identify biochemical pathways associated with native resistance mechanisms, a genome-wide association analysis was performed, followed by pathway analysis using a gene-set enrichment-based approach. The gene-set enrichment exposed the cumulative effects of genes in pathways to identify those that contributed the most to resistance. Single nucleotide polymorphism-trait associations were linked to genes including transcription factors, protein kinases, hormone-responsive proteins, hydrolases, pectinases, xylogluconases, and the flavonol synthase gene (in the maysin biosynthesis pathway). The most significantly associated metabolic pathways identified included those that modified cell wall components, especially homogalacturonan, wax esters, and fatty acids; those involved in antibiosis, especially 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA), flavonoids, and phenolics; and those involved in plant growth, including N uptake and energy production. The pathways identified in this study, and especially the cell wall-associated pathways, identified here for the first time, provide clues to resistance mechanisms that could guide the identification of new resistant ideotypes and candidate genes for creation of resistant maize germplasm via selection of natural variants or gene editing.

Quack: A quality assurance tool for high throughput sequence data.

The quality of data generated by high-throughput DNA sequencing tools must be rapidly assessed in order to determine how useful the data may be in making biological discoveries; higher quality data leads to more confident results and conclusions. Due to the ever-increasing size of data sets and the importance of rapid quality assessment, tools that analyze sequencing data should quickly produce easily interpretable graphics. Quack addresses these issues by generating information-dense visualizations from FASTQ files at a speed far surpassing other publicly available quality assurance tools in a manner independent of sequencing technology.

Comparative Genomics of an Unusual Biogeographic Disjunction in the Cotton Tribe (Gossypieae) Yields Insights into Genome Downsizing.

Long-distance insular dispersal is associated with divergence and speciation because of founder effects and strong genetic drift. The cotton tribe (Gossypieae) has experienced multiple transoceanic dispersals, generating an aggregate geographic range that encompasses much of the tropics and subtropics worldwide. Two genera in the Gossypieae, Kokia and Gossypioides, exhibit a remarkable geographic disjunction, being restricted to the Hawaiian Islands and Madagascar/East Africa, respectively. We assembled and use de novo genome sequences to address questions regarding the divergence of these two genera from each other and from their sister-group, Gossypium. In addition, we explore processes underlying the genome downsizing that characterizes Kokia and Gossypioides relative to other genera in the tribe. Using 13,000 gene orthologs and synonymous substitution rates, we show that the two disjuncts last shared a common ancestor ∼5 Ma, or half as long ago as their divergence from Gossypium. We report relative stasis in the transposable element fraction. In comparison to Gossypium, there is loss of ∼30% of the gene content in the two disjunct genera and a history of genome-wide accumulation of deletions. In both genera, there is a genome-wide bias toward deletions over insertions, and the number of gene losses exceeds the number of gains by ∼2- to 4-fold. The genomic analyses presented here elucidate genomic consequences of the demographic and biogeographic history of these closest relatives of Gossypium, and enhance their value as phylogenetic outgroups.