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2015年4月7日讯 /生物谷BIOON/ –目前，全外显子测序和全基因组测序技术在遗传分析和发现导致疾病发生的潜在基因突变方面应用越来越广泛，随着测序技术的不断迭代更新，越来越成熟，昂贵的价格会逐渐降低，那么在排除价格因素之后，全外显子测序和全基因组测序在检测外显子突变方面究竟谁更加强大呢？来自美国的科学家对这一问题进行了相关研究，其研究结果发表在著名国际学术期刊PNAS上。
研究人员指出，全外显子测序(WES)是对具有蛋白编码功能的外显子进行的测序技术，近年来全外显子测序在发现外显子基因突变方面逐渐得到广泛应用，但全基因组测序(WGS)也越来越成为发现外显子基因突变的一项非常具有吸引力的测序技术。目前，全基因组测序比全外显子测序价格昂贵，但全基因组测序的价格应该会比全外显子测序下降得更快。
研究人员利用6个无关联个体的基因组比较了全外显子测序和全基因组测序。他们对WES捕获的一段基因区域分别利用WES和WGS进行内单核苷酸突变（SNV）和小片段插入/缺失突变（indel）检测，结果显示WES检测到的SNV和小片段插入/缺失突变的平均数为84,192和13,325，而WGS检测到的平均数为84,968和12,702。研究人员对SNV和indel的coverage depth，genotype quality和minor read ratio等参数的分布进行了评估，结果发现全基因组测序的结果更加均一。研究人员发现WGS和WES两种技术能检测出绝大多数SNV和indel，但利用WGS能够检测出大约650个高质量编码基因SNV（占编码基因突变的3%左右），而利用WES则错失了这些SNV。最后，研究人员还发现利用WES检测拷贝数突变（CNV）得到的结果并不可靠。
这项研究表明，虽然目前全基因组测序的价格高于全外显子测序，但全基因组测序在检测导致疾病发生的潜在基因突变方面更加强大，尤其是SNV检测方面。（基因宝jiyinbao.com）
Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants
Aziz Belkadia,b,1, Alexandre Bolzec,1,2, Yuval Itanc, Aurélie Cobata,b, Quentin B. Vincenta,b, Alexander Antipenkoc, Lei Shangc, Bertrand Boissonc, Jean-Laurent Casanovaa, and Laurent Abel
We compared whole-exome sequencing (WES) and whole-genome sequencing (WGS) in six unrelated individuals. In the regions targeted by WES capture (81.5% of the consensus coding genome), the mean numbers of single-nucleotide variants (SNVs) and small insertions/deletions (indels) detected per sample were 84,192 and 13,325, respectively, for WES, and 84,968 and 12,702, respectively, for WGS. For both SNVs and indels, the distributions of coverage depth, genotype quality, and minor read ratio were more uniform for WGS than for WES. After filtering, a mean of 74,398 (95.3%) high-quality (HQ) SNVs and 9,033 (70.6%) HQ indels were called by both platforms. A mean of 105 coding HQ SNVs and 32 indels was identified exclusively by WES whereas 692 HQ SNVs and 105 indels were identified exclusively by WGS. We Sanger-sequenced a random selection of these exclusive variants. For SNVs, the proportion of false-positive variants was higher for WES (78%) than for WGS (17%). The estimated mean number of real coding SNVs (656 variants, ?3% of all coding HQ SNVs) identified by WGS and missed by WES was greater than the number of SNVs identified by WES and missed by WGS (26 variants). For indels, the proportions of false-positive variants were similar for WES (44%) and WGS (46%). Finally, WES was not reliable for the detection of copy-number variations, almost all of which extended beyond the targeted regions. Although currently more expensive, WGS is more powerful than WES for detecting potential disease-causing mutations within WES regions, particularly those due to SNVs.