Detecting genomic elements of extreme conservation in higher eukaryotes by integration of hash mapping and cache-oblivious in-memory computing

Genomics is one of the first life science disciplines to enter the era of Big Data, facing challenges in all three dimensions--volume, variety, and velocity. Yet, in spite of a plethora of sequencing data, we are still far from creating a complete encyclopedia of functional and structural elements of the genome. In 2004, an example of this knowledge gap came about when Bejerano and Haussler discovered 481 DNA elements in the syntenic positions of human, mouse and rat genomes that were 100% identical, called the ultra-conserved elements (UCEs). Our ultimate goal is to provide a comprehensive atlas of the regions of extreme conservation in higher eukaryotes providing insights into the structural organization, function and evolution of these elements. Here, we present a new hybrid approach that integrates the ideas of hash mapping and cache-oblivious in-memory computing. Our algorithm leverages the concept of help-me-help-you, where the data structures are tailored to maximize cache-hit while minimizing cache-miss. As a result, our hybrid algorithm is approximately 800 times faster than the current state-of-the-art method and is scalable to deal with the unassembled genomes. The new hybrid approach has been applied to detect the earliest evidence of extreme conservation by including into the large-scale analysis recently sequenced genomes of coelacanth and lamprey. The integration of efficient software with hardware-optimized approaches has shown to be a promising direction in comparative genomics, allowing scientists to provide even deeper insights into the function and evolution of eukaryotic genomes

Novel global effector mining from the transcriptome of early life stages of the soybean cyst nematode Heterodera glycines

Soybean cyst nematode (SCN) Heterodera glycines is an obligate parasite that relies on the secretion of effector proteins to manipulate host cellular processes that favor the formation of a feeding site within host roots to ensure its survival. The sequence complexity and co-evolutionary forces acting upon these effectors remain unknown. Here we generated a de novo transcriptome assembly representing the early life stages of SCN in both a compatible and an incompatible host interaction to facilitate global effector mining efforts in the absence of an available annotated SCN genome. We then employed a dual effector prediction strategy coupling a newly developed nematode effector prediction tool, N-Preffector, with a traditional secreted protein prediction pipeline to uncover a suite of novel effector candidates. Our analysis distinguished between effectors that co-evolve with the host genotype and those conserved by the pathogen to maintain a core function in parasitism and demonstrated that alternative splicing is one mechanism used to diversify the effector pool. In addition, we confirmed the presence of viral and microbial inhabitants with molecular sequence information. This transcriptome represents the most comprehensive whole-nematode sequence currently available for SCN and can be used as a tool for annotation of expected genome assemblies

Phytonematode Peptide Effectors Exploit a Host Post‐Translational Trafficking Mechanism to the ER using a Novel Translocation Signal

Summary Cyst nematodes induce a multicellular feeding site within roots called a syncytium. It remains unknown how root cells are primed for incorporation into the developing syncytium. Furthermore, it is an enigma how CLAVATA3/ESR (CLE) peptide effectors secreted into the cytoplasm of the initial feeding cell could have an effect on plant cells so distant from where the nematode is feeding as the syncytium expands. Here we describe a novel translocation signal within nematode CLE effectors that is recognized by plant cell secretory machinery to redirect these peptides from the cytoplasm to the apoplast of plant cells. We show that the translocation signal is functionally conserved across CLE effectors identified in nematode species spanning three genera and multiple plant species, operative across plant cell types, and can traffic other unrelated small peptides from the cytoplasm to the apoplast of host cells via a previously unknown post‐translational mechanism of ER translocation. Our results uncover an unprecedented mechanism of effector trafficking by any plant pathogen to date and illustrates how phytonematodes can deliver effector proteins into host cells and then hijack plant cellular processes for their export back out of the cell to function as external signaling molecules to distant cells

neg.fasta

Contains non-effector protein sequences used for training and testing

Data from: Genome-wide prediction of bacterial effector candidates across six secretion system types using a feature-based statistical framework

Gram-negative bacteria are responsible for hundreds of millions infections worldwide, including the emerging hospital-acquired infections and neglected tropical diseases in the third-world countries. Finding a fast and cheap way to understand the molecular mechanisms behind the bacterial infections is critical for efficient diagnostics and treatment. An important step towards understanding these mechanisms is the discovery of bacterial effectors, the proteins secreted into the host through one of the six common secretion system types. Unfortunately, current prediction methods are designed to specifically target one of three secretion systems, and no accurate “secretion system-agnostic” method is available. Here, we present PREFFECTOR, a computational feature-based approach to discover effector candidates in Gram-negative bacteria, without prior knowledge on bacterial secretion system(s) or cryptic secretion signals. Our approach was first evaluated using several assessment protocols on a manually curated, balanced dataset of experimentally determined effectors across all six secretion systems, as well as non-effector proteins. The evaluation revealed high accuracy of the top performing classifiers in PREFFECTOR, with the small false positive discovery rate across all six secretion systems. Our method was also applied to six bacteria that had limited knowledge on virulence factors or secreted effectors. PREFFECTOR web-server is freely available at: http://korkinlab.org/preffector

pos.fasta

File pos.fasta contains effector protein sequences used for training and testing

Novel global effector mining from the transcriptome of early life stages of the soybean cyst nematode Heterodera glycines

Soybean cyst nematode (SCN) Heterodera glycines is an obligate parasite that relies on the secretion of effector proteins to manipulate host cellular processes that favor the formation of a feeding site within host roots to ensure its survival. The sequence complexity and co-evolutionary forces acting upon these effectors remain unknown. Here we generated a de novo transcriptome assembly representing the early life stages of SCN in both a compatible and an incompatible host interaction to facilitate global effector mining efforts in the absence of an available annotated SCN genome. We then employed a dual effector prediction strategy coupling a newly developed nematode effector prediction tool, N-Preffector, with a traditional secreted protein prediction pipeline to uncover a suite of novel effector candidates. Our analysis distinguished between effectors that co-evolve with the host genotype and those conserved by the pathogen to maintain a core function in parasitism and demonstrated that alternative splicing is one mechanism used to diversify the effector pool. In addition, we confirmed the presence of viral and microbial inhabitants with molecular sequence information. This transcriptome represents the most comprehensive whole-nematode sequence currently available for SCN and can be used as a tool for annotation of expected genome assemblies.This article is published as Gardner, Michael, Andi Dhroso, Nathan Johnson, Eric L. Davis, Thomas J. Baum, Dmitry Korkin, and Melissa G. Mitchum. "Novel global effector mining from the transcriptome of early life stages of the soybean cyst nematode Heterodera glycines." Scientific reports 8 (2018): 2505. doi: 10.1038/s41598-018-20536-5.</p

Tools for annotation and comparison of structural variation [version 1; referees: 1 approved, 2 approved with reservations]

The impact of structural variants (SVs) on a variety of organisms and diseases like cancer has become increasingly evident. Methods for SV detection when studying genomic differences across cells, individuals or populations are being actively developed. Currently, just a few methods are available to compare different SVs callsets, and no specialized methods are available to annotate SVs that account for the unique characteristics of these variant types. Here, we introduce SURVIVOR_ant, a tool that compares types and breakpoints for candidate SVs from different callsets and enables fast comparison of SVs to genomic features such as genes and repetitive regions, as well as to previously established SV datasets such as from the 1000 Genomes Project. As proof of concept we compared 16 SV callsets generated by different SV calling methods on a single genome, the Genome in a Bottle sample HG002 (Ashkenazi son), and annotated the SVs with gene annotations, 1000 Genomes Project SV calls, and four different types of repetitive regions. Computation time to annotate 134,528 SVs with 33,954 of annotations was 22 seconds on a laptop

Phytonematode Peptide Effectors Exploit a Host Post‐Translational Trafficking Mechanism to the ER using a Novel Translocation Signal

Summary Cyst nematodes induce a multicellular feeding site within roots called a syncytium. It remains unknown how root cells are primed for incorporation into the developing syncytium. Furthermore, it is an enigma how CLAVATA3/ESR (CLE) peptide effectors secreted into the cytoplasm of the initial feeding cell could have an effect on plant cells so distant from where the nematode is feeding as the syncytium expands. Here we describe a novel translocation signal within nematode CLE effectors that is recognized by plant cell secretory machinery to redirect these peptides from the cytoplasm to the apoplast of plant cells. We show that the translocation signal is functionally conserved across CLE effectors identified in nematode species spanning three genera and multiple plant species, operative across plant cell types, and can traffic other unrelated small peptides from the cytoplasm to the apoplast of host cells via a previously unknown post‐translational mechanism of ER translocation. Our results uncover an unprecedented mechanism of effector trafficking by any plant pathogen to date and illustrates how phytonematodes can deliver effector proteins into host cells and then hijack plant cellular processes for their export back out of the cell to function as external signaling molecules to distant cells. This is a manuscript of an article published as Wang, Jianying, Andi Dhroso, Xunliang Liu, Thomas J. Baum, Richard S. Hussey, Eric L. Davis, Xiaohong Wang, Dmitry Korkin, and Melissa G. Mitchum. "Phytonematode Peptide Effectors Exploit a Host Post‐Translational Trafficking Mechanism to the ER using a Novel Translocation Signal." New Phytologist (2020). doi: 10.1111/nph.16765.</p