Munro, J. E. | Search bioRxiv

bioRxiv2021

Population-level genome-wide STR typing in Plasmodium species reveals higher resolution population structure and genetic diversity relative to SNP typing

Short tandem repeats (STRs) are highly informative genetic markers that have been used extensively in population genetics analysis. They are an important source of genetic diversity and can also have functional impact. Despite the availability of bioinformatic methods that permit large-scale genome-wide genotyping of STRs from whole genome sequencing data, they have not previously been applied to sequencing data from large collections of malaria parasite field samples. Here, we have genotyped STRs using HipSTR in more than 3,000 Plasmodium falciparum and 174 Plasmodium vivax published whole-genome sequence data from samples collected across the globe. High levels of noise and variability in the resultant callset necessitated the development of a novel method for quality control of STR genotype calls. A set of high-quality STR loci (6,768 from P. falciparum and 3,496 from P. vivax) were used to study Plasmodium genetic diversity, population structures and genomic signatures of selection and these were compared to genome-wide single nucleotide polymorphism (SNP) genotyping data. In addition, the genome-wide information about genetic variation and other characteristics of STRs in P. falciparum and P. vivax have been made available in an interactive web-based R Shiny application PlasmoSTR (https://github.com/bahlolab/PlasmoSTR). Author summaryMalaria is a severe disease caused by a genus of parasites called Plasmodium and is transmitted to humans through infected Anopheles mosquitoes. P. falciparum and P. vivax are the predominant species responsible for more than 95% of all human malaria infections which continue to pose a significant challenge to human health. Antimalarial drug resistance is a serious threat hindering the elimination of malaria. As such, it is important to understand the role of genomic variation in the development of antimalarial drug resistance. STRs are an important source of genomic variation that, from a population genetics perspective, have several advantages over SNPs, including being highly polymorphic, having a higher mutation rate, and having been widely used to study the population structure and genetic diversity. However, STRs are not routinely genotyped with bioinformatic tools across the whole genome with short read sequencing data because they are difficult to identify and genotype accurately, as they vary in size and may align poorly to the reference genome, therefore requiring rigorous quality control (QC). In this study, we genotype STRs using HipSTR[1] in more than 3,000 P. falciparum and 174 P. vivax whole-genome sequence samples collected world-wide. We develop a multivariable logistic regression model for the measurement and prediction of the quality of STRs. In addition, we use a set of genome-wide high-quality STRs to study parasite population genetics and compare them to genome-wide SNP genotyping data, revealing both high consistency with SNP based signals, as well as identifying some signals unique to the STR marker data. These results demonstrate that the identification of highly informative STR markers from large numbers of population samples is a powerful approach to study the genetic diversity, population structures and genomic signatures of selection in P. falciparum and P. vivax. Furthermore, we built an interactive web-based R Shiny application PlasmoSTR (https://github.com/bahlolab/PlasmoSTR) that includes genome-wide information about genetic variation and other characteristics of the high quality STRs identified in P. falciparum and P. vivax, allowing researchers to explore and visualize the specific STRs.

genetics↗

bioRxiv2019

Cell type and cortex-specific RNA editing in single human neurons informs neuropsychiatric disorders

BACKGROUNDConversion of adenosine to inosine in RNA by ADAR enzymes occurs at thousands of sites in the human transcriptome, and is essential for healthy brain development. This RNA editing process is dysregulated in many neuropsychiatric diseases, but is little understood at the level of individual neurons. METHODSWe quantified RNA editing sites in full-length capture nuclear transcriptomes of 3055 neurons from six cortical regions of a neurotypical post-mortem female donor. Putative editing sites were intersected with sites in bulk human tissue transcriptomes including healthy and neuropsychiatric brain tissue, and sites identified in single nuclei from unrelated brain donors. Differential editing between cell types and cortical regions, and individual sites and genes therein, was quantified using linear models. Associations between gene expression and editing were also tested. RESULTSWe identified 41,930 RNA editing sites with robust read coverage in at least ten neuronal nuclei. Most sites were located within Alu repeats in introns or 3 UTRs, and approximately 80% were catalogued in published RNA editing databases. We identified 9285 putative novel RNA editing sites, 29% of which were also detectable neuronal transcriptomes from unrelated donors. Inhibitory neurons showed higher overall transcriptome editing than excitatory neurons. Among the strongest correlates of global editing rates were snoRNAs from the SNORD115 and SNORD116 cluster (15q11), known to modulate serotonin receptor processing and to colocalize with ADAR2. We identified 29 genes preferentially edited in excitatory neurons and 44 genes edited more heavily in inhibitory neurons including RBFOX1, its target genes and small nucleolar RNA-associated genes in the autism-associated Prader-Willi locus 15q11. These results provide cell-type and spatial context for 1730 and 910 sites that are also edited in the brains of schizophrenic and autistic patients respectively, and a reference for future studies of RNA editing in single brain cells from these cohorts. CONCLUSIONSRNA editing, including thousands of previously unreported sites, is robustly detectable in single neuronal nuclei, where gene editing differences are stronger between cell subtypes than between cortical regions. Insufficient editing of ASD-related genes in inhibitory neurons may manifest in the specific perturbation of these cells in autism.

neuroscience↗