What is currently the highest quality data you can reliably and with reasonable effort / cost generate on the Illumina platform? The data will be aligned versus a reference.
For a single diploid individual with a sub 1 GB genome size.
This with the purpose of constructing genome wide benchmark SNP / SV genotypes for that individual. And later use of the benchmark genotypes for optimizing other low cost / high throughput genotyping methods: See also: http://www.nature.com/nbt/journal/v32/n3/full/nbt.2835.html
Two important factors I guess are maximizing the read lenght to 250 bp and generating above 40 X coverage. 250 bp would mean sequencing on the MiSeq as no other Illumina platform supports this.
What I am less sure about is the library type.
Standard paired end is the easiest and cheapest to generate. But is (very) limited for SV detection.
Paired end with overlapping reads offers longer synthetic reads which are more useful for small SV detection. But stitching the reads together can introduce noise for SNP calling?
Mate pair library prep is more difficult and expensive. The library prep even often fails in a lot of hands?
But mate pair offers somewhat (how much?) increased SV detection. Is it the best to choose one specific mate pair insert size, 3kbp , 5 kbp or 10kbp? Or a mix of these insert sizes?
Big question I think is if PE stitching or MP libraries are worth the cost / effort versus standard (higher coverage) PE for creating SNP / SV benchmark genotypes.
Or to just go with another method / platform (PacBio/ Nanopore, BioNano?) for creating SV benchmark genotypes.