IDENTIFYING THE GENETIC BASIS FOR HUMAN DISEASE 227 report diagnostic yields in the 20 to 40% range, depending on clinical indication, which leaves the majority of cases without an identified causative variant and answer.识别人类疾病的遗传基础 227 报告诊断率在20%到40%之间,具体取决于临床指征,这导致大多数病例无法找到确定的致病变异和答案。
There are several reasons for this observation.造成这一观察结果有几个原因。
First, some disorders are intractable to standard genome-wide sequencing, including methylation disorders (e. g., Prader-Willi and Angelman syndromes) or those involving certain types of Uniparental disomy (UPD) if parents are not sequenced (i. e., heterodisomy).首先,某些疾病对标准全基因组测序难以处理,包括甲基化疾病(例如,普拉德-威利综合征和天使综合征)或涉及某些类型的单亲二倍体(UPD)的疾病(如果父母未进行测序,即异源二倍体)。
Second (and related), genome-wide sequencing may miss certain classes of variation that are difficult to detect by routine short-read sequencing alone (e. g., balanced changes, repeat expansions).其次(且与此相关),全基因组测序可能遗漏某些难以通过常规短读长测序单独检测的变异类别(例如,平衡性变异、重复扩增)。
As discussed earlier, whole genome sequencing has technological advantages over exome sequencing, with the ability to detect a broader range of variation; however, there are still limitations in accurately detecting or resolving complex regions of the genome.如前所述,全基因组测序在外显子组测序方面具有技术优势,能够检测更广泛的变异;然而,在准确检测或解析基因组复杂区域方面仍存在局限性。
Third, variation is detected that is difficult to interpret with our current understanding of the genome.第三,检测到的变异在当前对基因组的理解下难以解释。
This is particularly true of genome sequencing and the rare variation detected in noncoding and regulatory genomic regions.这对于基因组测序以及在非编码和调控基因组区域中检测到的罕见变异尤其如此。
Finally, at present, whole genome sequencing cannot actually sequence the entire genome in any one individual.最后,目前全基因组测序实际上无法对任何个体进行全基因组测序。
Cost limits most of the sequencing to short-reads and aligning back to a reference genome (termed resequencing) to detect variation.成本限制使得大部分测序采用短读长,并回帖到参考基因组(称为重测序)以检测变异。
Some sequence is too complex and/or highly homologous or repetitive to be technically sequenced or mapped back to the reference genome.有些序列过于复杂和/或高度同源或重复,技术上无法测序或回帖到参考基因组。
Additionally, sequence novel to one’s genome, i. e., not in the reference assembly, will be filtered out even though it may be pathogenic.此外,个体基因组中特有的序列(即不在参考组装中的序列)即使可能具有致病性,也会被过滤掉。
Such limitations are starting to be addressed in several ways.这些局限性正开始通过多种方式得到解决。
Improvements in both sequencing technology and informatics algorithms for variant detection allow a more accurate catalogue of genomic variation.测序技术和用于变异检测的信息学算法的改进,使得基因组变异目录更加准确。
The increasing number of genomes sequenced and the subsequent aggregation of data allow more accurate interpretation of variation.测序基因组数量的增加以及随后数据的聚合,使得对变异的解释更加准确。
In addition, the advancement of other -omic technologies, such as RNA sequencing or methylation experiments, are proving to be valuable tests ancillary to genome-wide sequencing for the interpretation of noncoding variation.此外,其他组学技术的进步,如RNA测序或甲基化实验,正被证明是辅助全基因组测序解释非编码变异的有价值检测方法。
The emergence of long-read sequencing technology (reads up to 10–100 kb in length) has provided insight into regions of the genome that have been intractable to short-read sequencing, including highly homologous or repetitive regions, with detection of variation previously unseen.长读长测序技术(读长达10–100 kb)的出现,为短读长测序难以处理的基因组区域(包括高度同源或重复区域)提供了见解,能够检测到以前未见的变异。
Long-read technology can also be used to advance de novo assembly of genomes, rather than reference-based assembly, to get a more complete picture of the genome.长读长技术还可用于推进基因组的从头组装,而非基于参考的组装,以获取更完整的基因组图像。
These advances will lead to a better understanding of our genome, its variation, and its relation to disease.这些进展将有助于更好地理解我们的基因组、其变异及其与疾病的关系。
ACKNOWLEDGMENT We wish to thank and Gregory Costain for contributing to this chapter.致谢 我们感谢Gregory Costain对本章的贡献。
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