Mapping major quantitative trait loci (QTL) responsible for rice seed germinability under low temperature (GULT) can provide valuable genetic source for improving cold tolerance in rice breeding. In this study, 124 rice backcross recombinant inbred lines (BRILs) derived from a cross indica cv. Changhui 891 and japonica cv. 02428 were genotyped through re-sequencing technology. A bin map was generated which includes 3057 bins covering distance of 1266.5 cM with an average of 0.41 cM between markers. On the basis of newly constructed high-density genetic map, six QTL were detected ranging from 40 to 140 kb on Nipponbare genome. Among these, two QTL qCGR8 and qGRR11 alleles shared by 02428 could increase GULT and seed germination recovery rate after cold stress, respectively. However, qNGR1 and qNGR4 may be two major QTL affecting indica Changhui 891germination under normal condition. QTL qGRR1 and qGRR8 affected the seed germination recovery rate after cold stress and the alleles with increasing effects were shared by the Changhui 891 could improve seed germination rate after cold stress dramatically. These QTL could be a highly valuable genetic factors for cold tolerance improvement in rice lines. Moreover, the BRILs developed in this study will serve as an appropriate choice for mapping and studying genetic basis of rice complex traits.
Fruit flies in the genus Bactrocera are global, economically important pests of agricultural food crops. However, basic life history information about these pests, which is vital for designing more effective control methods, is currently lacking. Artificial diets can be used as a suitable replacement for natural host plants for rearing fruit flies under laboratory conditions, and this study reports on the two-sex life-table parameters of four Bactrocera species (Bactrocera correcta, Bactrocera dorsalis, Bactrocera cucurbitae, and Bactrocera tau) reared on a semi-artificial diet comprising corn flour, banana, sodium benzoate, yeast, sucrose, winding paper, hydrochloric acid and water. The results indicated that the larval development period of B. correcta (6.81 ± 0.65 days) was significantly longer than those of the other species. The fecundity of B. dorsalis (593.60 eggs female-1) was highest among the four species. There were no differences in intrinsic rate of increase (r) and finite rate of increase (λ) among the four species. The gross reproductive rate (GRR) and net reproductive rate (R0) of B. dorsalis were higher than those of the other species, and the mean generation time (T) of B. cucurbitae (42.08 ± 1.21 h) was longer than that of the other species. We conclude that the semi-artificial diet was most suitable for rearing B. dorsalis, due to its shorter development time and higher fecundity. These results will be useful for future studies of fruit fly management.
BackgroundFor capital breeding Lepidoptera, larval food quality is a key determinant of their fitness. A series of studies have suggested that the larval host species or varieties dramatically impact their development and reproductive output. However, few studies have reported the role of foliar age and adult mating success has often been ignored in these studies. In this paper, the influence of host species and needle age on larval performances, adult mating behavior and fitness consequences has been studied using a capital breeding caterpillar, Dendrolimus punctatus Walker (Lepidoptera:Lasiocampidae).ResultsIn larval performance trial, a strong effect of larval host species and needle age was found on survivorship, developmental duration, body weight, percentage of adult emergence, and growth index, but not on percentage of female progeny. In adult mating trial, larval host species and needle age also significantly affected mating latency and mating duration, but not mating success. In adult fitness trial, female fecundity, longevity and fitness index, but not oviposition duration and fertility, influenced by larval host species and needle age.ConclusionsThese results reveal the importance of larval host species and needle age on larval performance and adult reproductive fitness in this capital breeding insect and provide strong evidence that old needles of masson pine P. massoniana is the best host for D. punctatus.
The study of 1000-grain weight (TGW) and percentage of grains with chalkiness (PGWC) is very important in rice. In this study, a set of introgression lines (ILs), derived from Sasanishiki/Habataki with Sasanishiki as the recurrent parent, were used to detect correlations and quantitative trait loci (QTL) on TGW and PGWC in two different environments. Phenotypic correlation analysis showed that there was no significant correlation between TGW and PGWC in both environments, which indicated that the linkage of TGW and PGWC traits could be broken via suitable population. A total of 20 QTL were detected in both environments, nine QTL for 1000-paddy-grain weight (PTGW), five QTL for 1000-brown-grain weight (BTGW) and six QTL for percentage of grains with chalkiness (PGWC). Moreover, five QTL, qPTGW3, qPTGW8.2, qPTGW11.1 for PTGW and qPGWC1.1, qPGWC1.2 for PGWC, were stably expressed in both environments. Phenotypic values were significantly different (P < 0.01) between the introgression lines carrying these five QTL alleles and the genetic background parent, Sasanishiki. The introgression lines carrying these QTL also represent a useful genetic resource in the context of rice yield and quality improvement via a design-breeding approach.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.