Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans.

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

Genome sequencing of C. elegans balancer strains reveals previously unappreciated complex genomic rearrangements.

Genetic balancers in Caenorhabditis elegans are complex variants that allow lethal or sterile mutations to be stably maintained in a heterozygous state by suppressing crossover events. Balancers constitute an invaluable tool in the C. elegans scientific community and have been widely used for decades. The first/traditional balancers were created by applying X-rays, UV, or gamma radiation on C. elegans strains, generating random genomic rearrangements. Their structures have been mostly explored with low-resolution genetic techniques (e.g., fluorescence in situ hybridization or PCR), before genomic mapping and molecular characterization through sequencing became feasible. As a result, the precise nature of most chromosomal rearrangements remains unknown, whereas, more recently, balancers have been engineered using the CRISPR-Cas9 technique for which the structure of the chromosomal rearrangement has been predesigned. Using short-read whole-genome sequencing (srWGS) and tailored bioinformatic analyses, we previously interpreted the structure of four chromosomal balancers randomly created by mutagenesis processes. Here, we have extended our analyses to five CRISPR-Cas9 balancers and 17 additional traditional balancing rearrangements. We detected and experimentally validated their breakpoints and have interpreted the balancer structures. Many of the balancers were found to be more intricate than previously described, being composed of complex genomic rearrangements (CGRs) such as chromoanagenesis-like events. Furthermore, srWGS revealed additional structural variants and CGRs not known to be part of the balancer genomes. Altogether, our study provides a comprehensive resource of complex genomic variations in C. elegans and highlights the power of srWGS to study the complexity of genomes by applying tailored analyses.

A Near-Chromosome Level Genome Assembly of Anopheles stephensi.

Malaria remains a major healthcare risk to growing economies like India, and a chromosome-level reference genome of Anopheles stephensi is critical for successful vector management and understanding of vector evolution using comparative genomics. We report chromosome-level assemblies of an Indian strain, STE2, and a Pakistani strain SDA-500 by combining draft genomes of the two strains using a homology-based iterative approach. The resulting assembly IndV3/PakV3 with L50 of 9/12 and N50 6.3/6.9 Mb had scaffolds long enough for building 90% of the euchromatic regions of the three chromosomes, IndV3s/PakV3s, using low-resolution physical markers and enabled the generation of the next version of genome assemblies, IndV4/PakV4, using HiC data. We have validated these assemblies using contact maps against publicly available HiC raw data from two strains including STE2 and another lab strain of An. stephensi from UCI and compare the quality of the assemblies with other assemblies made available as preprints since the submission of the manuscript. We show that the IndV3s and IndV4 assemblies are sensitive in identifying a homozygous 2Rb inversion in the UCI strain and a 2Rb polymorphism in the STE2 strain. Multiple tandem copies of CYP6a14, 4c1, and 4c21 genes, implicated in insecticide resistance, lie within this inversion locus. Comparison of assembled genomes suggests a variation of 1 in 81 positions between the UCI and STE2 lab strains, 1 in 82 between SDA-500 and UCI strain, and 1 in 113 between SDA-500 and STE2 strains of An. stephensi, which are closer than 1 in 68 variations among individuals from two other lab strains sequenced and reported here. Based on the developmental transcriptome and orthology of all the 54 olfactory receptors (ORs) to those of other Anopheles species, we identify an OR with the potential for host recognition in the genus Anopheles. A comparative analysis of An. stephensi genomes with the completed genomes of a few other Anopheles species suggests limited inter-chromosomal gene flow and loss of synteny within chromosomal arms even among the closely related species.