Let me start with limitations since they can be significant depending on what you intend to use this machine for. You are currently limited to running macOS. Projects to port linux have been announced but they will take time and may be of limited utility in short term.

1. Memory
   Since the processor uses DMA architecture, memory is included on the same die as the CPU/GPU. While it provides fast access, it is limited to a maximum of 16GB. This will preclude using any software that needs more memory than 16. Upgrade to 16G is significant cost.
2. Form factor
   AFAIK M1 has been released in a single hardware version. M1 in the form factor of mac mini is likely to allow more sustained high frequency compute since macbook air does not have a fan and will throttle processor, if you are doing sustained compute on it.
3. Storage
   Unless you plan to use external thunderbolt storage enclosures, you are limited by internal storage. You are going to pay a premium to get a TB or two (max). You can only get that during the build since you can't add more storage later (internally).
4. Xcode
   There is a version of Xcode for M1 but some things may still be missing from open source software. These will eventually catch up. So if you need to compile something you may run into odd glitches.
5. External monitor
   You can connect only one. May not be a problem but may want to note.
6. External GPU
   Until AMD/NVIDIA make user mode graphics drivers available there is no possibility of using an external GPU.
7. Docker
   No support for docker at this time. Coming in future. Docker has released a version that now supports M1 processor (Apr 2021)

Plus points:

1. Performance
   M1 is running rings around Intel's offerings as you have already seen.
2. Battery life
   For casual use battery life is really great. Truly an all day machine if you are simply going to ssh into central/cloud compute for serious work.
3. Rosetta2
   Rosetta2 is making things seamless. So far conda runs fine (and thus much of the bioinformatics software should). R/Rstudio works as well. There does not seem to be much of a performance hit. Again I have not done any serious compute.
4. User experience
   Flawless. Indistinguishable from an Intel mac. macOS feels/works identically on both architectures. Universal binaries will work.

This is going to vary depending on the tools you want to use, at least at present.

There are a few Bioinformatics tools that are accelerated by some of the Intel AVX instructions. For example, GATK's HaplotypeCaller and Mutect2 both use PairHMM which is accelerated by at least an order of magnitude when run on AVX-capable CPUs, vs non-AVX fall-back mode on Intel hardware (in my experience at least).

I don't have an Apple device with an M1 chip to run comparison benchmarks, but AVX/AVX2/AVX512 are specifically listed as not supported by Rosetta2

For some other tools, you might be limited by available RAM. For example, the STAR RNA aligner loads the indexes and genome into RAM, and needs 10x the genome size or around 31GB for human and mouse genomes. As of March 8, 2021, the maximum amount of RAM that you can get in an M1 Mac is 16 GB, and the RAM is not expandable (it's integrated on the same chip as the processor).

Personally, I'm excited for the future, at least on a compute-per-watt basis, but software will need to catch up, and future Apple Silicon chips will probably provide more RAM.

IMHO, such powerful processor can not be ignored by bioinformatics, especially because coming in 2021 the next generation of M processors with more cores. At such low energy consumption they are the best for such tasks as reads assemblies. It is simply a future for bioinformatic! Intel RIP. And, I am not even talking about how perspective Swift for bioinformatics :). Just listen the Chris Lattner about swift to realise its power. More scientific apps written in swift is a near future.