**5. Conclusions**

This study aims to use wild rice to develop CSSLs for cultivated rice and use these CSSLs for comparative mapping of traits related to plant architecture and yield. We focused on germplasm innovation in rice through the identification and transfer of beneficial genes/QTLs from the wild species. We introduced the DP30-CSSL library platform to facilitate pre-designed breeding of cultivated rice to utilize favorable alleles dispersed in Guangxi wild rice resources. The QTLs presented here are expected to provide further clues to identifying underlying mechanisms involved in plant architecture and improved grain. Our ongoing experiments are aimed at confirming the genomic regions and narrowing down of number of genes reported within the QTLs in the present study through comprehensive studies involving high-resolution linkage mapping via high-throughput genotyping by sequencing of advanced generation progenies.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2073-4425/11/9/980/s1, Figure S1: Frequency distributions of quantitative traits in DP30-CSSLs during fall and spring, Figure S2: Phenotypic variation in plant-architecture-related traits and heading date in CSSLs and 93-11, Figure S3: Cold tolerance phenotype of some CSSLs and 93-11 at seedling stages (bar = 10 cm), Figure S4: Phenotypic variation of leaf traits in CSSLs and 93-11, Figure S5: Phenotypic variation of in apiculi, glumes and seed coats in CSSLs and 93-11, Figure S6: The distribution of the 36 QTLs in DP30-CSSLs. The molecular markers are shown on the left and the QTL sites are shown on the right. A QTL overlap indicates that there are two QTL in the same region. Table S1: Whole-genome re-sequencing analysis of wild rice DP30. Table S2: The sequence of DP30-CSSLs molecular markers, Table S3: Substitution segments of DP30-CSSLs population, Table S4: The markers sequences of InDel molecular markers for mapping QTL qCT2.1, Table S5: Genotypes and phenotypes of secondary F2 populations.

**Author Contributions:** Conceptualization, R.Y. and N.Z.; Data curation, B.U., S.L. and G.N.; Formal analysis, R.Y., N.Z. and Y.Q.; Funding acquisition, R.L.; Investigation, R.Y., B.U., L.L., Y.Q. and G.N.; Methodology, R.Y., L.L., S.L. and G.N.; Project administration, R.L.; Resources, R.L.; Software, N.Z.; validation, R.L.; Visualization, B.U.; Writing—Original draft, R.Y., N.Z., B.U. and G.N.; Writing–review & editing, B.U. and R.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Key Technology Research and Development Program Guike, Guangxi (Guike AB16380066; Guike AB16380093).

**Acknowledgments:** We would like to thank Mohsin Niaz, Umair Khalid, Mudassar Abbas, Baoxiang Qin and Fang Liu for the helpful discussion and invaluable comments to make this research meaningful.

**Conflicts of Interest:** The authors declare no conflict of interest.
