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Genome Research Studies Explore Malaria Mosquito CNVs, LncRNA Interactions, More

Members of the Anopheles gambiae 1000 Genomes Consortium present findings from a copy number variant analysis in that malaria parasite vector mosquito. The team did whole-genome sequencing on 1,142 An. gambiae samples, focusing in on 250 CNVs impacting 267 genes. When they took a closer look at the genes affected by CNVs, the investigators focused in on 44 CNVs that showed up in five gene clusters previously implicated in metabolic resistance to insecticides. Those copy number shifts were found at high frequency in some local An. gambiae populations, and appeared to be influenced by positive selection. "Our results demonstrate the importance of CNVs in the response to selection, highlighting the urgent need to identify the contribution of each CNV to insecticide resistance and to track their spread as the use of insecticides in malaria endemic countries intensifies," the authors note.

Researchers in the UK and Germany compare and contrast several approaches for predicting transcription factor activity based on target gene expression, from manual curation approaches to strategies that rely on chromatin immunoprecipitation sequencing, in silico transcription factor binding predictions, or reverse-engineered regulons representing target gene expression from large datasets. Using a set of more than 1,500 transcription factor-target interactions, the team analyzed a wide range of transcription factor features in the context of their binding and regulatory profiles. From there, the authors looked at how such features might impact transcription factor predictions done using different approaches, and came up with general guidance for profiling transcription factor activities. "[F]or almost half of the [transcription factors], only one of the four strategies report targets," they write, noting that the results "highlight the importance of the literature-curated regulons to infer [transcription factor] activities, with the highest precision achieved for interactions supported by more than one resource or expert's review."

A team from China and the US describes a sequencing-based assay it developed to look at long non-coding RNA (lncRNA) interactions with gene promoter DNA. The method — called "chromatin RNA in situ reverse transcription sequencing," or CRIST-seq — relies on RNA biotin labeling in combination with guide RNAs from a catalytically inactive version of CRISPR-Cas9, the researchers say, which help to crosslink chromatin DNA and RNA interactions prior to the reverse transcription, immunoprecipitation, purification, and sequencing steps of the assay. The authors used CRIST-seq to profile a lncRNA network surrounding Sox2 and Pou5f1 gene promoters involved in stem cell pluripotency, for example, and applied the approach to lncRNA interactions that may impact tumor-associated genes. Based on their findings, they suggest that "CRIST-seq technology can be broadly used to screen lncRNAs and mRNAs that interact with any chromatin regulatory regions, such as promoters or enhancers."