Cathy Gresham

Three crocodilian genomes reveal ancestral patterns of evolution among archosaurs

INTRODUCTION Crocodilians and birds are the two extant clades of archosaurs, a group that includes the extinct dinosaurs and pterosaurs. Fossils suggest that living crocodilians (alligators, crocodiles, and gharials) have a most recent common ancestor 80 to 100 million years ago. Extant crocodilians are notable for their distinct morphology, limited intraspecific variation, and slow karyotype evolution. Despite their unique biology and phylogenetic position, little is known about genome evolution within crocodilians. Evolutionary rates of tetrapods inferred from DNA sequences anchored by ultraconserved elements. Evolutionary rates among reptiles vary, with especially low rates among extant crocodilians but high rates among squamates. We have reconstructed the genomes of the common ancestor of birds and of all archosaurs (shown in gray silhouette, although the morphology of these species is uncertain). RATIONALE Genome sequences for the American alligator, saltwater crocodile, and Indian gharial—representatives of all three extant crocodilian families—were obtained to facilitate better understanding of the unique biology of this group and provide a context for studying avian genome evolution. Sequence data from these three crocodilians and birds also allow reconstruction of the ancestral archosaurian genome. RESULTS We sequenced shotgun genomic libraries from each species and used a variety of assembly strategies to obtain draft genomes for these three crocodilians. The assembled scaffold N50 was highest for the alligator (508 kilobases). Using a panel of reptile genome sequences, we generated phylogenies that confirm the sister relationship between crocodiles and gharials, the relationship with birds as members of extant Archosauria, and the outgroup status of turtles relative to birds and crocodilians. We also estimated evolutionary rates along branches of the tetrapod phylogeny using two approaches: ultraconserved element–anchored sequences and fourfold degenerate sites within stringently filtered orthologous gene alignments. Both analyses indicate that the rates of base substitution along the crocodilian and turtle lineages are extremely low. Supporting observations were made for transposable element content and for gene family evolution. Analysis of whole-genome alignments across a panel of reptiles and mammals showed that the rate of accumulation of micro-insertions and microdeletions is proportionally lower in crocodilians, consistent with a single underlying cause of a reduced rate of evolutionary change rather than intrinsic differences in base repair machinery. We hypothesize that this single cause may be a consistently longer generation time over the evolutionary history of Crocodylia. Low heterozygosity was observed in each genome, consistent with previous analyses, including the Chinese alligator. Pairwise sequential Markov chain analysis of regional heterozygosity indicates that during glacial cycles of the Pleistocene, each species suffered reductions in effective population size. The reduction was especially strong for the American alligator, whose current range extends farthest into regions of temperate climates. CONCLUSION We used crocodilian, avian, and outgroup genomes to reconstruct 584 megabases of the archosaurian common ancestor genome and the genomes of key ancestral nodes. The estimated accuracy of the archosaurian genome reconstruction is 91% and is higher for conserved regions such as genes. The reconstructed genome can be improved by adding more crocodilian and avian genome assemblies and may provide a unique window to the genomes of extinct organisms such as dinosaurs and pterosaurs. To provide context for the diversification of archosaurs—the group that includes crocodilians, dinosaurs, and birds—we generated draft genomes of three crocodilians: Alligator mississippiensis (the American alligator), Crocodylus porosus (the saltwater crocodile), and Gavialis gangeticus (the Indian gharial). We observed an exceptionally slow rate of genome evolution within crocodilians at all levels, including nucleotide substitutions, indels, transposable element content and movement, gene family evolution, and chromosomal synteny. When placed within the context of related taxa including birds and turtles, this suggests that the common ancestor of all of these taxa also exhibited slow genome evolution and that the comparatively rapid evolution is derived in birds. The data also provided the opportunity to analyze heterozygosity in crocodilians, which indicates a likely reduction in population size for all three taxa through the Pleistocene. Finally, these data combined with newly published bird genomes allowed us to reconstruct the partial genome of the common ancestor of archosaurs, thereby providing a tool to investigate the genetic starting material of crocodilians, birds, and dinosaurs.

AgBase: supporting functional modeling in agricultural organisms

AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website.

Stallion Sperm Transcriptome Comprises Functionally Coherent Coding and Regulatory RNAs as Revealed by Microarray Analysis and RNA-seq

Mature mammalian sperm contain a complex population of RNAs some of which might regulate spermatogenesis while others probably play a role in fertilization and early development. Due to this limited knowledge, the biological functions of sperm RNAs remain enigmatic. Here we report the first characterization of the global transcriptome of the sperm of fertile stallions. The findings improved understanding of the biological significance of sperm RNAs which in turn will allow the discovery of sperm-based biomarkers for stallion fertility. The stallion sperm transcriptome was interrogated by analyzing sperm and testes RNA on a 21,000-element equine whole-genome oligoarray and by RNA-seq. Microarray analysis revealed 6,761 transcripts in the sperm, of which 165 were sperm-enriched, and 155 were differentially expressed between the sperm and testes. Next, 70 million raw reads were generated by RNA-seq of which 50% could be aligned with the horse reference genome. A total of 19,257 sequence tags were mapped to all horse chromosomes and the mitochondrial genome. The highest density of mapped transcripts was in gene-rich ECA11, 12 and 13, and the lowest in gene-poor ECA9 and X; 7 gene transcripts originated from ECAY. Structural annotation aligned sperm transcripts with 4,504 known horse and/or human genes, rRNAs and 82 miRNAs, whereas 13,354 sequence tags remained anonymous. The data were aligned with selected equine gene models to identify additional exons and splice variants. Gene Ontology annotations showed that sperm transcripts were associated with molecular processes (chemoattractant-activated signal transduction, ion transport) and cellular components (membranes and vesicles) related to known sperm functions at fertilization, while some messenger and micro RNAs might be critical for early development. The findings suggest that the rich repertoire of coding and non-coding RNAs in stallion sperm is not a random remnant from spermatogenesis in testes but a selectively retained and functionally coherent collection of RNAs.

An atlas of bovine gene expression reveals novel distinctive tissue characteristics and evidence for improving genome annotation

BackgroundA comprehensive transcriptome survey, or gene atlas, provides information essential for a complete understanding of the genomic biology of an organism. We present an atlas of RNA abundance for 92 adult, juvenile and fetal cattle tissues and three cattle cell lines.ResultsThe Bovine Gene Atlas was generated from 7.2 million unique digital gene expression tag sequences (300.2 million total raw tag sequences), from which 1.59 million unique tag sequences were identified that mapped to the draft bovine genome accounting for 85% of the total raw tag abundance. Filtering these tags yielded 87,764 unique tag sequences that unambiguously mapped to 16,517 annotated protein-coding loci in the draft genome accounting for 45% of the total raw tag abundance. Clustering of tissues based on tag abundance profiles generally confirmed ontology classification based on anatomy. There were 5,429 constitutively expressed loci and 3,445 constitutively expressed unique tag sequences mapping outside annotated gene boundaries that represent a resource for enhancing current gene models. Physical measures such as inferred transcript length or antisense tag abundance identified tissues with atypical transcriptional tag profiles. We report for the first time the tissue-specific variation in the proportion of mitochondrial transcriptional tag abundance.ConclusionsThe Bovine Gene Atlas is the deepest and broadest transcriptome survey of any livestock genome to date. Commonalities and variation in sense and antisense transcript tag profiles identified in different tissues facilitate the examination of the relationship between gene expression, tissue, and gene function.

De Novo Transcriptome Assembly and Analyses of Gene Expression during Photomorphogenesis in Diploid Wheat Triticum monococcum

Background Triticum monococcum (2n) is a close ancestor of T. urartu, the A-genome progenitor of cultivated hexaploid wheat, and is therefore a useful model for the study of components regulating photomorphogenesis in diploid wheat. In order to develop genetic and genomic resources for such a study, we constructed genome-wide transcriptomes of two Triticum monococcum subspecies, the wild winter wheat T. monococcum ssp. aegilopoides (accession G3116) and the domesticated spring wheat T. monococcum ssp. monococcum (accession DV92) by generating de novo assemblies of RNA-Seq data derived from both etiolated and green seedlings. Principal Findings The de novo transcriptome assemblies of DV92 and G3116 represent 120,911 and 117,969 transcripts, respectively. We successfully mapped ∼90% of these transcripts from each accession to barley and ∼95% of the transcripts to T. urartu genomes. However, only ∼77% transcripts mapped to the annotated barley genes and ∼85% transcripts mapped to the annotated T. urartu genes. Differential gene expression analyses revealed 22% more light up-regulated and 35% more light down-regulated transcripts in the G3116 transcriptome compared to DV92. The DV92 and G3116 mRNA sequence reads aligned against the reference barley genome led to the identification of ∼500,000 single nucleotide polymorphism (SNP) and ∼22,000 simple sequence repeat (SSR) sites. Conclusions De novo transcriptome assemblies of two accessions of the diploid wheat T. monococcum provide new empirical transcriptome references for improving Triticeae genome annotations, and insights into transcriptional programming during photomorphogenesis. The SNP and SSR sites identified in our analysis provide additional resources for the development of molecular markers.

HPIDB 2.0: a curated database for host–pathogen interactions

Identification and analysis of host–pathogen interactions (HPI) is essential to study infectious diseases. However, HPI data are sparse in existing molecular interaction databases, especially for agricultural host–pathogen systems. Therefore, resources that annotate, predict and display the HPI that underpin infectious diseases are critical for developing novel intervention strategies. HPIDB 2.0 (http://www.agbase.msstate.edu/hpi/main.html) is a resource for HPI data, and contains 45, 238 manually curated entries in the current release. Since the first description of the database in 2010, multiple enhancements to HPIDB data and interface services were made that are described here. Notably, HPIDB 2.0 now provides targeted biocuration of molecular interaction data. As a member of the International Molecular Exchange consortium, annotations provided by HPIDB 2.0 curators meet community standards to provide detailed contextual experimental information and facilitate data sharing. Moreover, HPIDB 2.0 provides access to rapidly available community annotations that capture minimum molecular interaction information to address immediate researcher needs for HPI network analysis. In addition to curation, HPIDB 2.0 integrates HPI from existing external sources and contains tools to infer additional HPI where annotated data are scarce. Compared to other interaction databases, our data collection approach ensures HPIDB 2.0 users access the most comprehensive HPI data from a wide range of pathogens and their hosts (594 pathogen and 70 host species, as of February 2016). Improvements also include enhanced search capacity, addition of Gene Ontology functional information, and implementation of network visualization. The changes made to HPIDB 2.0 content and interface ensure that users, especially agricultural researchers, are able to easily access and analyse high quality, comprehensive HPI data. All HPIDB 2.0 data are updated regularly, are publically available for direct download, and are disseminated to other molecular interaction resources. Database URL: http://www.agbase.msstate.edu/hpi/main.html

Facilitating functional annotation of chicken microarray data

BackgroundModeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO). However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information.ResultsWe have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM) tool to help researchers to quickly retrieve corresponding functional information for their dataset.ConclusionResults from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and will be updated on regular basis.

Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize

BackgroundAspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin.ResultsIn order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus.ConclusionsCFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database across different types of experiments. The database is publically available at http://agbase.msstate.edu.

A Public Platform for the Verification of the Phenotypic Effect of Candidate Genes for Resistance to Aflatoxin Accumulation and Aspergillus flavus Infection in Maize

A public candidate gene testing pipeline for resistance to aflatoxin accumulation or Aspergillus flavus infection in maize is presented here. The pipeline consists of steps for identifying, testing, and verifying the association of selected maize gene sequences with resistance under field conditions. Resources include a database of genetic and protein sequences associated with the reduction in aflatoxin contamination from previous studies; eight diverse inbred maize lines for polymorphism identification within any maize gene sequence; four Quantitative Trait Loci (QTL) mapping populations and one association mapping panel, all phenotyped for aflatoxin accumulation resistance and associated phenotypes; and capacity for Insertion/Deletion (InDel) and SNP genotyping in the population(s) for mapping. To date, ten genes have been identified as possible candidate genes and put through the candidate gene testing pipeline, and results are presented here to demonstrate the utility of the pipeline.

Insight into the Salivary Gland Transcriptome of Lygus lineolaris (Palisot de Beauvois)

The tarnished plant bug (TPB), Lygus lineolaris (Palisot de Beauvois) is a polyphagous, phytophagous insect that has emerged as a major pest of cotton, alfalfa, fruits, and vegetable crops in the eastern United States and Canada. Using its piercing-sucking mouthparts, TPB employs a “lacerate and flush” feeding strategy in which saliva injected into plant tissue degrades cell wall components and lyses cells whose contents are subsequently imbibed by the TPB. It is known that a major component of TPB saliva is the polygalacturonase enzymes that degrade the pectin in the cell walls. However, not much is known about the other components of the saliva of this important pest. In this study, we explored the salivary gland transcriptome of TPB using Illumina sequencing. After in silico conversion of RNA sequences into corresponding polypeptides, 25,767 putative proteins were discovered. Of these, 19,540 (78.83%) showed significant similarity to known proteins in the either the NCBI nr or Uniprot databases. Gene ontology (GO) terms were assigned to 7,512 proteins, and 791 proteins in the sialotranscriptome of TPB were found to collectively map to 107 Kyoto Encyclopedia of Genes and Genomes (KEGG) database pathways. A total of 3,653 Pfam domains were identified in 10,421 sialotranscriptome predicted proteins resulting in 12,814 Pfam annotations; some proteins had more than one Pfam domain. Functional annotation revealed a number of salivary gland proteins that potentially facilitate degradation of host plant tissues and mitigation of the host plant defense response. These transcripts/proteins and their potential roles in TPB establishment are described.