Long vs short read sequencing. Long read sequencing technology is poised to replace short read sequencing (e.g. Illumina). a. What is the typical read length in short read sequencing, and what is the read length range for long range sequencing? b. What are the downsides for using short read sequencing for genome assembly/SNP calling, and RNA isoform discovery/quantification? c. Which genomic protocols and/or applications are expected to benefit the most from long read sequencing? 1. Sequencing DNA that are accessible (e.g. ATAC-seq/DNASE-seq). 2. Measuring histone modifications (e.g. for ChIP-seq). 3. Measuring gene expression levels. 4. Measuring messenger RNA isoform diversity. 5. DNA sequencing for genome assembly. 6. DNA sequencing for variant calling (SNPs? Large structural variants?). d. Bulk versus single cell. Most if not all genomics protocols described have been or can be adapted to probe gene regulation in a single cell. What are some of the difficulties that make measuring DNA, RNA, and/or protein more difficult in single cells? Select the answer that applies. 1. The small number of molecules (DNA, RNA, protein) in a single cell is the general limiting factor for single cell genomics. 2. Handling single cells is a lot more difficult because they tend to undergo apoptosis. c. Making sure that you actually sequence one cell instead of multiple cells. 3. Finding a good way to dissociate cells is difficult for many tissue-types. e. You attend a seminar and hear about a super cool approach called SUPER AWESOME DNA- seq (SAD-seq). SAD-seq is able to measure, at nucleotide resolution, DNA bases that interact with other DNA bases (DNA-DNA interactions). The speaker shows data that demonstrate SAD seqs ability to recapitulate enhancer and promoter activity in two cancer-relevant cell lines (e.g. HeLa cells and K562). The speaker further shows that SAD-seq can be used to identify differentially expressed genes by comparing promoter activation. SAD-seq can do it all! Naturally, you start to wonder whether you should be using SAD-seq in your project, or whether you should start developing methods for analyzing SAD-seq. What are some important questions you should ask yourself before jumping head in?.