Figure 2.

Integrative Genome and Transcriptome Sequence Analyses of Single Cells. Single-cell genotype–phenotype correlations are enabled by sequencing its DNA and RNA, including (A) investigating gene expression dosage effects resulting from DNA copy number alterations; (B) detecting the expression of fusion transcripts from DNA structural variation, permitting base-level reconstruction of both fusion transcript and the causative genomic lesion; (C) studying the expression of coding genomic variants – including allele-specific expression or the expression of an acquired single nucleotide variant – or observing RNA editing; and (D) examining the expression level of transcripts from genes mutated in their coding or noncoding genomic parts (e.g., a gene regulatory region), and thus determining the functional consequences of acquired genetic variation on the cell. We note that limitations of transcriptional profiling for inferring genomic variation include that (i) only genomic variants within or encompassing expressed genes in the cell can be represented in the single cell's RNA-seq data – that is, nontranscribed genomic variation may not be inferred from the cell's RNA-seq data alone; (ii) artefacts resulting from whole-transcriptome amplification (and whole-genome amplification) should be taken into account when inferring genomic variation; and (iii) transcriptional profiles can be less predictive of genomic variation when read coverage is limited.