**Author details**

Synthetic association populations, such as the multi-parent advanced generation inter-cross (MAGIC) population [108] and the nested association mapping (NAM) population in maize [109], had been used for genome-wide association studies (GWAS); with which both high resolution and better population structure control can be achieved [110-111]. It is certain that such populations had been or are being developed in Upland cotton. Two artificially controlled multiple parent random-mating populations with each comprising more than 800 lines had been developed in our library, which should provide another theoretically ideal panel for

The other inherent constraint limiting the successful use of association mapping is rare alleles exiting in natural populations. Given that the number of individuals with a specific genotype is quite small, the effect of rare alleles on mapping can go far beyond the effect of small population sizes [112]. Large population size had been considered as an impor‐ tant factor to improve the QTL detection power in association mapping studies [3, 112]. Many more marker-trait associations for fiber yield were detected in our 356-accession panel [71] than in the 81-accession panel [69] between the same markers and target traits at the same significance level. While family–based linkage mapping can make use of alleles that occur at low frequencies in natural populations by designing crosses to create artificial populations with inflated frequencies of those alleles. So specifically designed mapping populations such as recombinant inbred lines (RIL) and near isogenic lines (NIL) will remain important. Furthermore, joint linkage and association mapping was recommended as an alternative approach to overcome some of the inherent limitations of both linkage and association mapping [105, 112], and this approach has proven to be a powerful tool to

Recently, two preliminary maps of the whole-genome scaffolds of *G. raimondii* (the putative diploid donor for tetraploid species) were separately released by two different groups [119-120], which will facilitate the tetraploid genome sequencing and assembly. Real genomewide association mapping will be realized in the near future through resequencing or other high-throughput genotyping technologies [121], which will dramatically accelerate genetic diversity exploitation and favorable allele mining in Upland cotton germplasm resources.

We thank all faculties and graduate students in Cotton Research Institute, Nanjing Agricultural University and the other members of the cotton genomics and breeding communities for their contributions, and apologize for not citing many enlightening papers owing to space limita‐ tions. This study was supported by grants from 973 (2011CB109300), 863, Jiangsu Province Key Project (BE2012329), and the Priority Academic Program Development of Jiangsu Higher

association mapping.

76 World Cotton Germplasm Resources

**Acknowledgements**

Education Institutions.

detecting architecture of complex traits [72, 113-118].

Hongxian Mei1 , Xiefei Zhu2 , Wangzhen Guo1 , Caiping Cai1 and Tianzhen Zhang1\*

\*Address all correspondence to: cotton@njau.edu.cn

