Nielsen Lab Research Overview and Computational Needs (Fall 2022)

PI: Martin Nielsen

PhD Students: Nichol Ripley, Constance Finnerty

Research Overview

Our laboratory works with various aspects of equine helminth infections, including parasite control, drug resistance, diagnosis, health and disease manifestations, host/parasite interactions, and epidemiology. Recently, we have taken steps to venture into genomics and transcriptomics and two PhD students are currently working on projects aiming to address basic science questions about two major equine nematode parasites. Further details below. We are interested in understanding gene flow for these parasites, as it will help us understand how phenotypic resistance occurs and spreads within and between populations. Furthermore, we seek to study gene expression in migratory parasites to better understand their role in parasitic disease.

Assembly of S. vulgaris reference genome

In the last two decades of the 21^st century, Strongylus vulgaris was widely regarded as the most pathogenic parasite of horses and responsible for nearly all colics. Since the introduction of anthelmintics in the 1980s, S. vulgaris has been controlled, maintaining susceptibility to all drug classes, and nearly forgotten. However, widespread anthelmintic resistance, including multi-drug resistance, has been reported worldwide in almost all other species of Strongylidae effecting horses. Even with decades of documented resistance, no novel drugs or treatments have been brought to market in over 40 years. With this knowledge, conservation and responsible use of, the now compromised, anthelmintics has become top priority of researchers and clinicians worldwide. With fewer anthelmintic treatments, previously forgotten parasitic nematodes like S. vulgaris have become up to 4 times as prevalent than just 15 years ago. With the threat of the high pathogenicity of this nematode, and what little genetic information exists for it, we are currently working to build a reference genome to allow for further genetic studies. First, we are generating a de novo genome assembly using PacBio HiFi data backed up with Illumina NextSeq data. Second, we are also assembling draft transcriptomes for each life stage (project 2).

Personnel:

Nichol Ripley, Added on MCC cluster 09/06/2022

Computational methods:

Read processing, genome assembly, read mapping, and annotation.

Software:

HiCanu, FastQC, NCBI BLAST, Trimmomatic, Velvet.

Software availability: all programs are accessible on DLX.

vulgaris lifecycle stage draft transcriptomes

de novo and genome-guided transcriptome assembly using PacBio IsoSeq and RNAseq data.

Personnel:

Nichol Ripley, Added on MCC cluster, 09/06/2022

Computational methods:

read processing, transcriptome assembly, read mapping, annotation, and differential expression analysis

Software:

Jellyfish, Trinity, NCBI BLAST, BLAST2GO, DESeq, edgeR, baySeq
all programs are accessible on DLX EXCEPT BLAST2GO, DESeq (installation needs Bioconductor), edgeR (installation needs Bioconductor) baySeq (installation needs Bioconductor). BLAST2GO is commercially available.

Population genomic analysis of P. univalens

Parascaris spp. are pathogenic nematodes that affect the gastrointestinal system of young horses globally, causing clinical disease and death. Parascaris spp. is the only ascarid documented to have developed widespread resistance to macrocyclic lactones, which is the most widely used anthelmintic class in veterinary medicine. Population genetic studies are vital tools for understanding genetic variation, gene flow, genotypic frequency and how these associate with phenotypic traits such as infectivity, pathogenicity, and drug resistance. Substantial population genetic work has been done with trichostrongyle parasite species, such as Haemonchus contortus but these belong to clade V parasites, while ascarids are clade III parasites. This genetic distance between strongylids and ascarids means that population genetic structures likely differ substantially and that extrapolations should be made with the greatest caution. Recent work has investigated population genetic structures of other ascarid species such as Ascaris lumbricoides and A. suum, providing evidence of genetic structures within and between these closely related species. There have been three population genetic studies completed with Parascaris spp. These three population genetic studies have been done on Parascaris spp. with two utilizing whole genome sequencing and the other using amplified fragment length polymorphism (AFLP) to characterize the population structure in this parasite using previously established genetic markers. All three of these studies suggested that Parascaris spp. has homogenous population structure, with no apparent geographic barriers to gene flow. While there may be no population structure in the chosen genetic regions, we hypothesize that a more discrete genetic organization can be found outside these genomic markers. This study will use next generation sequencing (NGS) to investigate discreet levels of genetic variation in populations of Parascaris spp. The study aims to determine the population structure of Parascaris spp. in a hierarchical manner: 1) within a horse, 2) within an isolated herd, and 3) between horses in the state of Kentucky. Worms will be collected from the small intestine of foals approximately 5 months old, and DNA will be extracted for NGS. Sequencing data will be analyzed for evidence of selection through allelic frequencies and fitness through principal component analysis, AMOVA and STRUCTURE plots, allowing for discreet levels of population structure to be characterized. This study will provide new information on the population structure of Parascaris spp., creating a foundation for other population, pathogenicity, transmission, and anthelmintic resistance studies.

Personnel:

Constance Finnerty, Added on MCC cluster, 09/06/2022

Computational methods:

Read processing and filtering, demultiplexing, read assembly, SNP calling, and population genetic analysis.
SNP calling software, BLAT, MCL/MCXLOAD, Muscle, Samtools, GNU Parallel, Numpy, Gdata, Editdist, Genome Analysis Toolkit (GATK) Unified Genotyper.

Software:

Population genetic software (tentative list):

Arlequin, Migrate, Structure, Spagedi, IMA2, Eigensoft
Software availability: To our knowledge, these programs are not currently available on DLX. They should all be available for (free) download online. Many can be installed on an as needed basis within individual students’ working directories.

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