A multiple near isogenic line (multi-NIL) RNA-seq approach to identify candidate genes underpinning QTL

Ahsan Habib, Jonathan J. Powell, Jiri Stiller, Miao Liu, Sergey Shabala, Meixue Zhou, Donald M. Gardiner, Chunji Liu

This study demonstrates how identification of genes underpinning disease-resistance QTL based on differential expression and SNPs can be improved by performing transcriptomic analysis on multiple near isogenic lines. Transcriptomic analysis has been widely used to understand the genetic basis of a trait of interest by comparing genotypes with contrasting phenotypes. However, these approaches identify such large sets of differentially expressed genes that it proves difficult to isolate which genes underpin the phenotype of interest. This study tests whether using multiple near isogenic lines (NILs) can improve the resolution of RNA-seq-based approaches to identify genes underpinning disease-resistance QTL. A set of NILs for a major effect Fusarium crown rot-resistance QTL in barley on the 4HL chromosome arm were analysed under Fusarium crown rot using RNA-seq. Differential gene expression and single nucleotide polymorphism detection analyses reduced the number of putative candidates from thousands within individual NIL pairs to only one hundred and two genes, which were differentially expressed or contained SNPs in common across NIL pairs and occurred on 4HL. Our findings support the value of performing RNA-seq analysis using multiple NILs to remove genetic background effects. The enrichment analyses indicated conserved differences in the response to infection between resistant and sensitive isolines suggesting that sensitive isolines are impaired in systemic defence response to Fusarium pseudograminearum.