In PLOS Genetics, a pair of investigators from Johns Hopkins University investigate potential pleiotropic effects for genetic risk variants using a statistical method known as "pleiotropic analysis under composite null hypothesis" (PLACO) that draws on available data from genome-wide association studies. "We propose a new approach, PLACO, that uses aggregate-level genotype-phenotype association statistics — commonly referred to as GWAS summary statistics — to identify genetic variants that influence risk of two traits or diseases," they write, noting that the approach "can account for potential correlation across traits, such as that arising due to share controls in case-control studies." Using summary statistic data from prior GWAS on type 2 diabetes or prostate cancer, for example, the duo explored inverse associations documented for the conditions in the past, uncovering several shared loci.
A Spanish team takes a look at transcriptomic features in Culex pipiens mosquitoes known for transmitting Rift Valley fever virus (RVFV) for a paper in PLOS Neglected Tropical Diseases. Using RNA sequencing and de novo transcriptome assembly, the investigators compared transcriptomic features over time in pools of female mosquitoes that consumed RVFV-containing or RVFV-free blood. Their search unearthed hundreds of genes that were differentially expressed in mosquitoes after two hours, three days, or two weeks of RVFV exposure, particularly genes related to RNA interference, ubiquitin-proteasome-related genes, and pathways related to apoptosis or immune responses. "At an early stage of infection, some crucial defense effectors are inhibited, providing an opportunity for RVFV to disseminated," they reported, adding that "the present work provides a number of target genes and hypotheses on which to base future functional studies of the mechanisms inducing viral replication and resistance to RVFV infection."
For a paper in PLOS One, investigators in Egypt and Qatar present findings from a comparative transcriptomics study of the same human cell line, following infection with SARS-CoV-2 or with other respiratory viruses, including related coronaviruses such as SARS-CoV and MERS-CoV and unrelated viruses such as influenza A H1N1 or Ebola virus (EBOV) that share some clinical features with SARS-CoV-2. "We identified common and specific differentially expressed genes in the response to SARS-CoV-2 that are shared with SARS-CoV, MERS-CoV, H1N1, and EBOV," they write, noting that "the virogenomic transcriptome of infection, gene modulation of host antiviral responses, and [gene ontology] terms of SARS-CoV-2 and EBOV were more similar than to SARS, H1N1, and MERS."