Background: Heterodera glycines, commonly referred to as the soybean cyst nematode (SCN), is an obligatory and sedentary plant parasite that causes over a billion-dollar yield loss to soybean production annually. Although there are genetic determinants that render soybean plants resistant to certain nematode genotypes, resistant soybean cultivars are increasingly ineffective because their multi-year usage has selected for virulent H. glycines populations. The parasitic success of H. glycines relies on the comprehensive re-engineering of an infection site into a syncytium, as well as the long-term suppression of host defense to ensure syncytial viability. At the forefront of these complex molecular interactions are effectors, the proteins secreted by H. glycines into host root tissues. The mechanisms of effector acquisition, diversification, and selection need to be understood before effective control strategies can be developed, but the lack of an annotated genome has been a major roadblock. Results: Here, we use PacBio long-read technology to assemble a H. glycines genome of 738 contigs into 123 Mb with annotations for 29,769 genes. The genome contains significant numbers of repeats (34%), tandem duplicates (18.7 Mb), and horizontal gene transfer events (151 genes). A large number of putative effectors (431 genes) were identified in the genome, many of which were found in transposons. Conclusions: This advance provides a glimpse into the host and parasite interplay by revealing a diversity of mechanisms that give rise to virulence genes in the soybean cyst nematode, including: tandem duplications containing over a fifth of the total gene count, virulence genes hitchhiking in transposons, and 107 horizontal gene transfers not reported in other plant parasitic nematodes thus far. Through extensive characterization of the H. glycines genome, we provide new insights into H. glycines biology and shed light onto the mystery underlying complex host-parasite interactions. This genome sequence is an important prerequisite to enable work towards generating new resistance or control measures against H. glycines.

The soybean cyst nematode (Heterodera glycines) is a sedentary plant parasite that exceeds billion USD annually in yield losses. This problem is exacerbated by H. glycines populations overcoming the limited sources of natural resistance in soybean and by the lack of effective and safe alternative treatments. Although there are genetic determinants that render soybeans resistant to nematode genotypes, resistant soybeans are increasingly ineffective because their multiyear usage has selected for virulent H. glycines populations. Successful H. glycines infection relies on the comprehensive re‐engineering of soybean root cells into a syncytium, as well as the long‐term suppression of host defences to ensure syncytial viability. At the forefront of these complex molecular interactions are effectors, the proteins secreted by H. glycines into host root tissues. The mechanisms that control genomic effector acquisition, diversification, and selection are important insights needed for the development of essential novel control strategies. As a foundation to obtain this understanding, we created a nine‐scaffold, 158 Mb pseudomolecule assembly of the H. glycines genome using PacBio, Chicago, and Hi‐C sequencing. A Mikado consensus gene prediction produced an annotation of 22,465 genes using short‐ and long‐read expression data. To evaluate assembly and annotation quality, we cross‐examined synteny among H. glycines assemblies, and compared BUSCO across related species. To describe the predicted proteins involved in H. glycines’ secretory pathway, we contrasted expression between preparasitic and parasitic stages with functional gene information. Here, we present the results from our assembly and annotation of the H. glycines genome and contribute this resource to the scientific community.

Centromeric DNA sequences alone are neither necessary nor sufficient for centromere specification. The centromere specific histone, CenH3, evolves rapidly in many species, perhaps as a coevolutionary response to rapidly evolving centromeric DNA. To gain insight into CenH3 evolution, we characterized patterns of nucleotide and protein diversity among diploids and allopolyploids within three diverse angiosperm genera, Brassica, Oryza, and Gossypium (cotton), with a focus on evidence for diversifying selection in the various domains of the CenH3 gene. In addition, we compare expression profiles and alternative splicing patterns for CenH3 in representatives of each genus. All three genera retain both duplicated CenH3 copies, while Brassica and Gossypium exhibit pronounced homoeologous expression level bias. Comparisons among genera reveal shared and unique aspects of CenH3 evolution, variable levels of diversifying selection in different CenH3 domains, and that alternative splicing contributes significantly to CenH3 diversity. Since the N terminus is subject to diversifying selection but the DNA binding domains do not appear to be, rapidly evolving centromere sequences are unlikely to be the primary driver of CenH3 sequence diversification. At present, the functional explanation for the diversity generated by both conventional protein evolution in the N terminal domain, as well as alternative splicing, remains unexplained.

The soybean cyst nematode Heterodera glycines is the most economically devastating pathogen of soybean in the United States and threatens to become even more damaging through the selection of virulent nematode populations in the field that can overcome natural resistance mechanisms in soybean cultivars. This pathogen, therefore, demands intense transcriptomic/genomic research inquiries into the biology of its parasitic mechanisms. H. glycines delivers effector proteins that are produced in specialized gland cells into the soybean root to enable infection. The study of effector proteins, thus, is particularly promising when exploring novel management options against this pathogen. Here, we announce the availability of a gland cell–specific RNA-seq resource. These data represent an expression snapshot of gland cell activity during early soybean infection of a virulent and an avirulent H. glycines population, providing a unique and highly valuable resource for scientists examining effector biology and nematode virulence. [ ] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Rocky Mountain elk (Cervus canadensis) populations have significant economic implications to the cattle industry, as they are a major reservoir forBrucella abortusin the Greater Yellowstone area. Vaccination attempts against intracellular bacterial diseases in elk populations have not been successful due to a negligible adaptive cellular immune response. A lack of genomic resources has impeded attempts to better understand why vaccination does not induce protective immunity. To overcome this limitation, PacBio, Illumina, and Hi-C sequencing with a total of 686-fold coverage was used to assemble the elk genome into 35 pseudomolecules. A robust gene annotation was generated resulting in 18,013 gene models and 33,422 mRNAs. The accuracy of the assembly was assessed using synteny to the red deer and cattle genomes identifying several chromosomal rearrangements, fusions and fissions. Because this genome assembly and annotation provide a foundation for genome-enabled exploration of Cervus species, we demonstrate its utility by exploring the conservation of immune system-related genes. We conclude by comparing cattle immune system-related genes to the elk genome, revealing eight putative gene losses in elk.

Creating a scalable computational infrastructure to analyze the wealth of information contained in data repositories is difficult due to significant barriers in organizing, extracting and analyzing relevant data. Shared data science infrastructures like Boag is needed to efficiently process and parse data contained in large data repositories. The main features of Boag are inspired from existing languages for data intensive computing and can easily integrate data from biological data repositories. As a proof of concept, Boa for genomics, Boag, has been implemented to analyze RefSeq’s 153,848 annotation (GFF) and assembly (FASTA) file metadata. Boag provides a massive improvement from existing solutions like Python and MongoDB, by utilizing a domain-specific language that uses Hadoop infrastructure for a smaller storage footprint that scales well and requires fewer lines of code. We execute scripts through Boag to answer questions about the genomes in RefSeq. We identify the largest and smallest genomes deposited, explore exon frequencies for assemblies after 2016, identify the most commonly used bacterial genome assembly program, and address how animal genome assemblies have improved since 2016. Boag databases provide a significant reduction in required storage of the raw data and a significant speed up in its ability to query large datasets due to automated parallelization and distribution of Hadoop infrastructure during computations. In order to keep pace with our ability to produce biological data, innovative methods are required. The Shared Data Science Infrastructure, Boag, provides researchers a greater access to researchers to efficiently explore data in new ways. We demonstrate the potential of a the domain specific language Boag using the RefSeq database to explore how deposited genome assemblies and annotations are changing over time. This is a small example of how Boag could be used with large biological datasets.