Last-gen nostalgia: a lighthearted rant and reflection on genome sequencing culture

I sometimes see them in my dreams. The colorful peaks and troughs, the sharp, crisp waves spread across my computer screen, the rolling nitrogenous mountains, each with its own nucleotide sitting solidly on the summit. I’m talking about electropherograms, of course. Remember them? Those beautiful but oh so “oldgen” bioinformatics data generated from automated Sanger sequencing machines, such as the Applied Biosystems 370— the geriatric of genome sequencers. Don’t laugh. It was these capillary-based electrophoretic technologies that gave us the draft human genome sequence (Lander et al., 2001) and the genomemaps of many other model organisms, from the bacterium Haemophilus influenza to the yeast Saccharomyces cerevisiae to the multicellular green alga Volvox carteri (Fleischmann et al., 1995; Goffeau et al., 1996; Prochnik et al., 2010). As a grad student, I spent countless hours pruning, editing, assembling, and occasionally oohing and awing over Sanger sequences (Sanger et al., 1977; Smith et al., 1986; Prober et al., 1987). These 800-nucleotide genetic snippets intrigued, inspired, and motivated me. They contained just enough data to pique my interests—a novel exon, strange repeat, or foreign gene—and always left me craving a bit more: one additional sequencing read to extend that PCR product, find that stop codon, or join those lonely contigs. Usually, it would take weeks or months to get that extra read, and when it arrived I would savor the experience, exploring and analyzing it like a new book from a favorite author. After I devoured the data, I would say to myself, “If only I could get my hands on a great number of sequencing reads from my organism of interest then all of my genomic woes would be over.” Naively, I believed that the more sequencing data I had, the more productive I would be. Be careful what you wish for from the genome gods. The onslaught of next-generation sequencing (NGS) technologies (Metzker, 2010; Koboldt et al., 2013) and the access to previously unfathomable amounts of genomic data have made me dizzy, disillusioned, and anything but efficient. Like the proverbial boiling frog, my mind is gradually overheating from an accumulation of NGS reads (Liu et al., 2012). It’s a paired-end nightmare, a SOLiD pain in the neck, and a massively parallel migraine. All this HiSeq and MiSeq is clogging-up my internal drive and externals disks. I’ve taken vacations and returned home only to find that my Illumina reads still haven’t finished downloading. I can’t move or backup a FASTQ file without needing a coffee break. Last month it got so bad that I tried calling 911 on my 454. I’m certain that I would have had two Nature papers by now if it weren’t for that pestering computer cursor that keeps spinning around and around, reminding me of my small memory and pitiful processing power. With all this NGS information, what have I gained (apart from being a chronic user of SEQanswers.com)? Well, I’m a co-investigator of a half a dozen, highly fragmented nuclear genome assemblies for various green algae, with no genome papers anywhere in sight. And don’t get me started on the number of transcriptome projects waiting to be written up. What’s worse is that I’m still sending more samples for sequencing. It’s becomemy default setting: when in doubt, sequence. If a colleague drops by my office and says, “Smitty, you interested in milkweeds?” My first response is, “You betcha. Let’s send some for sequencing?” Student asks: “Professor Smith, do you have any ideas for my honors thesis?” “Hmmm,” I say, “how about we sequence another green alga.” Grant money left over, what do I do? You guessed it: two for one RNA-seq at the campus sequencing facility. And if the data come back contaminated or the quality is poor? Easy, I sequence more! It’s gotten to the point where I should begin my conference presentations with, “Hello, my name is David and I’m a NGS addict.” There are some positives to being NGS obsessed. I’m constantly testing and learning the newest bioinformatics software and genome assembly programs. I know all of the hippest genome slang and genetic acronyms. I have learned more than I ever wanted to about Linux, Unix, and Perl, although, as my students regularly point out, I’m still a hack in all three of those areas. I love that I can go to the Sequence Read Archive at the National Centre for Biotechnology Information (Leinonen et al., 2011) (I visit the site incessantly) and in seconds access endless amounts of raw genomic and transcriptomic data from some of the coolest and most bizarre species on earth, and then use these data to mine genes for phylogenetic and other comparative analyses. I’m also an organelle genome junkie, and NGS techniques have made it