Identification and characterization of stable QTLs for vascular bundle number at the panicle neck in rice (Oryza sativa L.).

A large vascular bundle number (VBN) in the panicle neck in rice (Oryza sativa L.) is related to the ability to transport assimilates from stem and leaf to reproductive organs during seed maturation. Several quantitative trait loci (QTLs) for VBN have been identified by using segregating populations derived from a cross between indica and japonica rice cultivars. However, the detailed location, effect, and interaction of QTLs for VBN were not understood well. Here, to elucidate the genetic basis of VBN, we identified three stable QTLs for VBN-qVBN5, qVBN6 and qVBN11-by using 71 recombinant inbred lines derived from a cross between indica 'IR24' and japonica 'Asominori'. We confirmed their positions and characterized their effects by using chromosome segment substitution lines (CSSLs) with an 'IR24' genetic background. qVBN6 had the most substantial effect on VBN, followed by qVBN11 and qVBN5. We developed pyramided lines carrying two QTLs for VBN to estimate their interaction. The combination of qVBN6 and qVBN11 accumulated VBN negatively in the pyramided lines owing to the independent actions of each QTL. The QTLs detected for VBN will enhance our understanding of genetic mechanisms of VBN and can be used in rice breeding.

Faster Exact Computation of rSPR Distance via Better Approximation.

Due to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to measure the dissimilarity of the two trees. The rooted subtree prune and regraft (rSPR) distance of the two trees has been used for this purpose. The problem of computing the rSPR distance of two given trees has many applications but is NP-hard. Accordingly, a number of programs have been developed for solving the problem either exactly or approximately. In this paper, we develop two new programs one of which solves the problem exactly and outperforms the previous best (namely, Whidden et al.'s rSPR-v1.3.0) significantly, while the other solves the problem approximately and outputs significantly better lower and upper bounds on the rSPR distance of the two given trees than the previous best due to Schalekamp et al. Our programs can be downloaded at http://rnc.r.dendai.ac.jp/rspr.html.