Yao Wen, Li Yang, Xie Weibo, Wang Lei
National Key Laboratory of Wheat and Maize Crop Science, College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China.
National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China.
Comput Struct Biotechnol J. 2020 Oct 23;18:3207-3216. doi: 10.1016/j.csbj.2020.10.012. eCollection 2020.
We previously conducted a QTL analysis of small RNA (sRNA) abundance in flag leaves of an immortalized rice F (IMF2) population by aligning sRNA reads to the reference genome to quantify the expression levels of sRNAs. However, this approach missed about half of the sRNAs as only 50% of all sRNA reads could be uniquely aligned to the reference genome. Here, we quantified the expression levels of sRNAs and sRNA clusters without the use of a reference genome. QTL analysis of the expression levels of sRNAs and sRNA clusters confirmed the feasibility of this approach. sRNAs and sRNA clusters with identified QTLs were then aligned to the high-quality parental genomes of the IMF2 population to resolve the identified QTLs into vs. regulation mode. We were able to detect new QTL hotspots by considering sRNAs aligned to multiple positions of the parental genomes and sRNAs unaligned to the parental genomes. We found that several -QTL hotspots were caused by sequence variations in long inverted repeats, which probably function as precursors of sRNAs, between the two parental genomes. The expression levels of these sRNAs were significantly associated with the presence/absence of the long inverted repeats in the IMF2 population. Moreover, we found that the variations in whole-genome sRNA species composition among different IMF2s were attributed to sRNA biogenesis genes including and Our results highlight that genetic dissection of sRNA expression is a promising approach to disclose new components functioning in sRNA biogenesis and new mechanisms of sRNA biogenesis.
我们之前通过将小RNA（sRNA）读数与参考基因组进行比对，对一个永生化水稻F（IMF2）群体的旗叶中的sRNA丰度进行了QTL分析，以量化sRNAs的表达水平。然而，这种方法遗漏了大约一半的sRNAs，因为所有sRNA读数中只有50%能够唯一比对到参考基因组上。在此，我们在不使用参考基因组的情况下量化了sRNAs和sRNA簇的表达水平。对sRNAs和sRNA簇表达水平的QTL分析证实了这种方法的可行性。然后，将已鉴定出QTL的sRNAs和sRNA簇与IMF2群体的高质量亲本基因组进行比对，以将鉴定出的QTL解析为 与 调控模式。通过考虑比对到亲本基因组多个位置的sRNAs以及未比对到亲本基因组的sRNAs，我们能够检测到新的QTL热点。我们发现，几个 -QTL热点是由两个亲本基因组之间长反向重复序列中的序列变异引起的，这些长反向重复序列可能作为sRNAs的前体。在IMF2群体中，这些sRNAs的表达水平与长反向重复序列的存在与否显著相关。此外，我们发现不同IMF2之间全基因组sRNA种类组成的差异归因于包括 和 在内的sRNA生物合成基因。我们的结果表明，对sRNA表达进行遗传剖析是一种有前景的方法，可用于揭示在sRNA生物合成中发挥作用的新成分以及sRNA生物合成的新机制。
