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The optimal loading concentration of the sequencing libraries is essential for a successful sequencing run. A
loading concentration that is too high results in over-clustering and run failure. On the other hand, a
loading concentration that is too low results in under-clustering and reduced output and accuracy. The
optimal loading concentration is dependent on the library type, sequencing system, and reagent kit, and it
requires to be adjusted empirically for each sequencer.

In order to achieve the ambitious target of sequencing 45,000-50,000 genomes by 2025, the Laboratory has
recently installed additional automation systems and the latest sequencer, NovaSeq X Plus, which promises
an increase of 2.5X throughput with the 25B flow cell that will be released later this year (2023). The higher
throughput and lower per unit sequencing cost will benefit population-scale projects like the HKGP.
Through standardisation of GS workflow and genomic data, it paves the way for data sharing and
[52]
collaboration, ultimately advancing the field of genomics and improving patient care .
Stepping into the future: the important role of WGS laboratory workflow in enhancing the
development of precision medicine in the genomic era
Due to lower assay cost and faster turn-around time, ES and gene panels have been the routine tests
employed in clinical genomic diagnosis for the past decade [53,54] . However, this targeted approach requires
PCR enrichment of the targeted regions, limiting the detection of small-sized variants found in exonic
regions and the overall efficacy. In contrast, GS enables comprehensive interrogation of the entire genome
with the option of PCR-free library preparation, allowing the unbiased identification of different types of
genetic variants, including protein-coding, regulatory and noncoding regions, as well as regions affecting
RNA splicing. Given the superior performance of GS and higher clinical utility compared to other
[55]
sequencing technologies, it is not only adopted by the HKGP and other international genome
projects [8-10,14,15,18,26] , but is also replacing ES as a first-tier test in the clinic [53,56] .

Advancements in long-read sequencing technologies and broad application have earned it the “Method of
[57]
the Year 2022” . Long-read sequencing has been shown to complement the shortcomings of short-read
technologies, such as directly identifying structural variants and methylation patterns, resolving complex
rearrangements, sequencing homologous and repetitive regions, phasing of alleles, and so on [58-60] , making
previously computationally challenging and inferential approaches more straightforward. Other
applications of long-read sequencing, like the characterisation of full-length RNA isoforms while preserving
native RNA modifications , and the detection of aberrant splicing and gene fusion events , have the
[61]
[58]
potential to facilitate functional interpretation of genomic variation . Considering the wide range of
[62]
applications in clinical genomics [63-65] , the Laboratory introduced the Oxford Nanopore Technology (ONT)
PromethION system to handle challenging cases such as certain neurological and neuromuscular diseases
that are known to be caused by short tandem repeat expansions, and others that are unresolved by short-
read GS. The longer reads also allow haplotype phasing of compound recessive variants and the detection of
structural variants with precise breakpoint details, as shown in our analysis of PKD1. Our preliminary data
showed that long-read GS uniformly covered many of the “dark regions” in the genome, including the
duplicated regions of PKD1 that are challenging for short-read GS.

To improve our understanding of the underlying biology of different diseases at the cellular and tissue
levels, single-cell genomics, spatial multi-omics, and proteomics technologies have been applied to
investigate thousands of individual cells in an unbiased approach [66-71] . In recent years, single-cell sequencing
has been widely adopted in cancer research to interrogate tumour microenvironment and heterogeneity,
and tumour clonal lineage [72,73] . The Laboratory has also established a single-cell sequencing platform to
integrate multi-omics information to enhance the characterisation of disease at the cellular and tissue levels
and enable the discovery of biomarkers for therapeutic targets. Integration of clinical information, GS,