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Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics

Determining mutational landscapes in a spatial context is essential for understanding genetically heterogeneous cell microniches. Current approaches, such as Multiple Displacement Amplification (MDA), offer high genome coverage but limited multiplexing, which hinders large-scale spatial genomic stud...

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Detalles Bibliográficos
Autores principales: Kim, Jinhyun, Kim, Sungsik, Yeom, Huiran, Song, Seo Woo, Shin, Kyoungseob, Bae, Sangwook, Ryu, Han Suk, Kim, Ji Young, Choi, Ahyoun, Lee, Sumin, Ryu, Taehoon, Choi, Yeongjae, Kim, Hamin, Kim, Okju, Jung, Yushin, Kim, Namphil, Han, Wonshik, Lee, Han-Byoel, Lee, Amos C., Kwon, Sunghoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10465490/
https://www.ncbi.nlm.nih.gov/pubmed/37644058
http://dx.doi.org/10.1038/s41467-023-41019-w
Descripción
Sumario:Determining mutational landscapes in a spatial context is essential for understanding genetically heterogeneous cell microniches. Current approaches, such as Multiple Displacement Amplification (MDA), offer high genome coverage but limited multiplexing, which hinders large-scale spatial genomic studies. Here, we introduce barcoded MDA (bMDA), a technique that achieves high-coverage genomic analysis of low-input DNA while enhancing the multiplexing capabilities. By incorporating cell barcodes during MDA, bMDA streamlines library preparation in one pot, thereby overcoming a key bottleneck in spatial genomics. We apply bMDA to the integrative spatial analysis of triple-negative breast cancer tissues by examining copy number alterations, single nucleotide variations, structural variations, and kataegis signatures for each spatial microniche. This enables the assessment of subclonal evolutionary relationships within a spatial context. Therefore, bMDA has emerged as a scalable technology with the potential to advance the field of spatial genomics significantly.