In previous studies polygene mapping of a backcross population derived from haploid potato (Solanum tuberosum) and a diploid wild species (Solanum berthaultiij showed at least eight quantitative trait loci (QTLs) associated with tuber dormancy. The same population was mapped for abscisic acid (ABA) content in tubers so that any QTLs identified could be compared with those detected previously. At least three distinct loci on three chromosomes (2, 4, and 7) were associated with variation in ABA content. One of the QTLs was detected only as a main (single locus) effect, and two QTLs were found through two-locus interaction analysis (epistasis). Interaction between QTLs at markers TG234 (chromosome 2) and TG755 (chromosome 4) explained 20% of total phenotypic variante for this trait. The interaction closely resembled one previously detected for dormancy, suggesting an association between high ABA content and long tuber dormancy. Although relationships between ABA leve1 and dormancy could be demonstrated through polygene mapping, there was no indication of a relationship between these traits when they were subjected to a conventional correlation test. This illustrates the usefulness of polygene mapping as a tool to identify possible associations between hormone levels and plant development.A well-tested approach for understanding growth and development is the analysis of differences between two phenotypes that contain different alleles of a single major gene. For example, analyses of dwarf and wild-type siblings have revealed hormonal differences associated with the mutant genotype (Reid and Howell, 1995). Although this approach has been productive, a limitation is that the control of many developmental processes is polygenic, i.e. inheritance is quantitative rather than qualitative. Thus, although it is interesting to know what physiological effect was produced by a dwarf mutation, it might be much more informative to learn about the physiological effects pro- duced by the polygenes that control plant height. In the past the study of quantitative inheritance was so difficult that it yielded only very generalized information, and little could be learned that would elucidate the physiology of growth and development. The situation has changed dramatically with the availability of new methods for mapping polygenes (Tanksley et al., 1989;Tanksley, 1993;Young, 1993). The new mapping methods rely on DNA-based genetic markers, such as RFLP markers. Through such mapping, a number of QTLs may be found that are associated with the control of a trait such as plant height. A QTL denotes a region of chromosome linked to the marker gene that has a significant effect on the quantitative trait (Tanksley, 1993).With the availability of this tool for mapping quantitative traits, polygenes can be used to study the physiology of growth and development in a manner analogous to, but more powerful than, the way single genes have been used in the past. Once the QTLs have been detected that are associated with the control of a given stage of...

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We analyzed the sequence alignment on 25 AA rice and 24 non-AA rice chloroplasts using two length diversity markers (ORF 100 and ORF29-TrnC GCA) and four sequence markers existed in introns of rps16 gene and TrnT U-GU-TrnL UAA spacer to explore the chloroplast diversity of different types of rice using PCR amplification and sequencing. Results showed that in terms of the length of ORF100 and ORF29-TrnC GCA , chloroplast DNA (cp DNA) of Hainan ordinary wild rice, Dongxiang ordinary wild rice, Hepu ordinary wild rice and three-line cytoplasmic male sterile wild rice were indica-type, Chaling ordinary wild rice, Fusui ordinary wild rice, Niwara wild rice, Brazilian upland rice and Lemont were japonica-type among in AA genome. Besides, all non-AA wild rice was japonica-type. There were 4 indica-japonica markers utilizing introns of rps16 gene and TrnT UGU-TrnL UAA. We found that all the ordinary wild rice in Chaling and Fusui of AA genome presented as japonica specific sites, while the others owned two indica and japonica specific sites, respectively. There were two indica-japonica sites separately and a 6-base specific fragment in three-line cytoplasmic male sterile materials except Yuetai A, simultaneously, 2-base difference from Hainan wild rice. Moreover, Brazilian upland rice and Lemont were entire japonica specific sites. Result of three markers indicated that the cp DNA of non-AA wild rice was japonica-type and result of one marker showed indica-type. Sequencing results also suggested that wild rice existed many polymorphic base sites, CCDD genome, wart wild rice and malay wild rice had their own specific sites. In conclusion, significant differentiation trend of indica-japonica exhibits in chloroplast of ordinary wild rice, and non-AA wild rice is generally japonica-type. The cytoplasmic polymorphism level of three-line sterile lines is low.

We tested the hypothesis that single-cell RNA-sequencing (scRNA-seq) analysis of human kidney allograft biopsies will reveal distinct cell types and states and yield insights to decipher the complex heterogeneity of alloimmune rejection. We selected 3 kidney biopsies from 3 individuals for scRNA-seq and processed them fresh using an identical protocol on the 10x Chromium platform; (i) HK: native kidney biopsy from a living donor, (ii) AK1: allograft kidney with transplant glomerulopathy and tubulointerstitial fibrosis, and worsening graft function, and (iii) AK2: allograft kidney after successful treatment of active antibody-mediated rejection. We generated 7217 high-quality single cell transcriptomes. Taking advantage of the recipient-donor sex mismatches, we determined that in AK1 with fibrosis, more than half of the kidney allograft fibroblasts were—unexpectedly—recipient-derived and therefore likely migratory and graft infiltrative, whereas in the AK2 without fibrosis, all the fibroblasts were donor-derived. Furthermore, AK1 was enriched by tubular cells that overexpressed profibrotic extracellular matrix genes. AK2, eight months after successful treatment of rejection, contained endothelial cells that expressed T-cell chemoattractant cytokines. In addition to these key findings, our analysis revealed unique cell types and cell states. Altogether, single cell transcriptomics yielded novel mechanistic insights for individualizing the care of transplant recipients.