# Genomic Approaches for Monogenic Kidney Diseases:
## 2 Genetic Testing: The Current Framework
### Whole-Genome Sequencing  
The most advanced technological approach is WGS, which allows for the investigation of the entire genome, including regulatory regions and non-coding variants via short- or long-read technology. It has good coverage, an improved mappability compared to WES and no GC-bias, reducing rates of false-negative variant calls [67]. Table 3 summarizes the list of advantages and disadvantages of applying WES or WGS. The WGS approach overcomes the pseudogene sequence similarity and duplicate regions [36]. These characteristics are especially important for some diagnoses, such as ADPKD [74]. The PKD1 (_Polycystin-1_) gene shows six pseudogenes with a sequence similarity of 97%. [PERSON] et al. [36] report a diagnostic yield of WGS in ADPKD patients of 80%. A similar yield was reported by [PERSON] et al. [20] in a cohort of clinically \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Technology** & **N\({}^{\circ}\) Cases** & **Diagnostic Yield (\%)** & **Incremental (\%)** & **References** \\ \hline Panel (2703 genes) & 482 & 42.6 & No statistical & \\ Singleton-WES & 196 & 36.2 & differences & \\ Trio-WES & 317 & 44.8 & (\(p>0.05\)) & \\ \hline Panels (virtual analysis) & 3315 & 4.1 & 5 & \\ WES & 3315 & 9.3 & (\(p<0.01\)) & \\ \hline Panels (disease specific) & 324 & 20.0 & 10 & \\ WES & 324 & 30.0 & (\(p<0.01\)) & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of technologies’ yield in the same population setting. WES, whole-exome sequencing. diagnosed ADPKD patients. In this study, patients were screened with a panel of 140 genes. The only limitation of this approach is the redesigning and revalidating of the setting, each time a new gene is discovered. The WGS short-read technology approach, still largely adopted in next-generation systems, is struggling to detect complex structural variants such as large inversions, deletions, or translocations. The technology advancement of long-read technology could overcome this limitation [75]. Despite its potential, WGS is still not widely used in clinical practice due to its higher costs and less developed analytical tools compared to more established sequencing methods, such as WES. However, with ongoing advancements and cost reductions, WGS may become more commonly employed in the future, especially for cases where its unique benefits are crucial, such as diagnosing complex genetic conditions like PKD. Nevertheless, the requirement of dedicated infrastructures, trained specialists, functional studies for uncertain significance variants (VUS) interpretation is a challenge for clinical centers and for large-scale implementation of these approaches [76]. An extensive application of WES would lead to the multiplication of the VUS to be documented. The problem is exacerbated by WGS where huge portions of the non-coding genome are effectively uninterpretable. From a research perspective, the availability of large amounts of data has led to the establishment of large-scale WGS projects, such as the European program Beyond 1 Million Genomes [77]. However, in a routine clinical context, a panel approach is a more effective and manageable implementation. These data will contribute to the advanced identification of rare pathogenic variants in the coding and non-coding domain. Currently, studies reporting the diagnostic performance of WGS in the field of kidney diseases are few and none met our study's inclusion criteria. Various non-neuphrological studies have reported an increase in the effectiveness of WGS, but results are conflicting. [PERSON] [78] et al. in a study including 1007 patients with neurological diseases, demonstrated that 30% of the unsolved WES cases could benefit from WGS. However, the interpretation of these data is not unique. [PERSON] et al. [79], in a responding letter to the [PERSON] et al. study, reported that the genomic variants identified by WGS can also be identified using a well-established WES technology, suggesting that only 1.4%, and not 30%, of the genomic variants can be identified by the WGS approach.