In human genomic studies, on average, 10% of next-generation sequencing (NGS) reads fail to align with the human reference genome. These unmapped reads vary across samples and have three main potential sources. First, they could represent contamination introduced during sample processing or from the sequencing technology itself. Second, these sequences might originate from microorganisms, like viruses, bacteria, and fungi, that have coevolved with humans and residing within humans. These natural inhabitants of the human body make up the human microbiota. During taking the human cell samples, the microbiota of the surroundings can infect the human samples. Third, these reads could come from active or dormant pathogens residing in the taken human cell samples, like viruses. Research shows that the composition of these microbial species changes with the health and condition of human tissues. In this study, author proposes that unmapped reads may serve as indicators of the pathological state of various tissues and cell types. An outline is marked for experimental approaches to test these ideas and explore the potential of these reads as diagnostic markers.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Diverse Facets of Nonhuman Sequences in Read Outputs of the Human Next-Generation Sequencing Data and Their Relevance with Viruses

  • Amit Pathania

摘要

In human genomic studies, on average, 10% of next-generation sequencing (NGS) reads fail to align with the human reference genome. These unmapped reads vary across samples and have three main potential sources. First, they could represent contamination introduced during sample processing or from the sequencing technology itself. Second, these sequences might originate from microorganisms, like viruses, bacteria, and fungi, that have coevolved with humans and residing within humans. These natural inhabitants of the human body make up the human microbiota. During taking the human cell samples, the microbiota of the surroundings can infect the human samples. Third, these reads could come from active or dormant pathogens residing in the taken human cell samples, like viruses. Research shows that the composition of these microbial species changes with the health and condition of human tissues. In this study, author proposes that unmapped reads may serve as indicators of the pathological state of various tissues and cell types. An outline is marked for experimental approaches to test these ideas and explore the potential of these reads as diagnostic markers.