Genetic analysis and molecular mapping of low amylose gene du12(t) in rice (Oryza sativa L.)

Key message

We obtained interesting results for genetic analysis and molecular mapping of the du12(t) gene.

Abstract

Control of the amylose content in rice is the major strategy for breeding rice with improved quality. In this study, we conducted genetic analysis and molecular mapping to identify the dull gene in the dull rice, Milyang262. A single recessive gene, tentatively designated as du12(t), was identified as the dull gene that leads to the low amylose character of Milyang262. To investigate the inheritance of du12(t), genetic analysis on an F₂ population derived from a cross between the gene carrier, Milyang262, and a moderate amylose content variety, Junam, was conducted. A segregation ratio of 3:1 (χ ² = 1.71, p = 0.19) was observed, suggesting that du12(t) is a single recessive factor that controls the dull character in Milyang262. Allelism tests confirmed that du12(t) is not allelic to other low amylose controlling genes, wx or du1. Recessive class analysis was performed to localize the du12(t) locus. Mapping of du12(t) was conducted on F₂ and F₃ populations of Baegokchal/Milyang262 cross. Linkage analysis of 120 F₂ plants revealed that RM6926 and RM3509 flank du12(t) at a 2.38-Mb region. To refine the du12(t) locus position, 986 F₂ and 289 F₃ additional normal plants were screened by the flanking markers. Twenty-six recombinant plants were identified and later genotyped with four additional adjacent markers located between RM6926 and RM3509. Finally, du12(t) was mapped to an 840-kb region on the distal region of the long arm of chromosome 6, delimited by SSR markers RM20662 and RM412, and co-segregated by RM3765 and RM176.     

Implications of the distribution of German household environmental footprints across income groups for integrating environmental and social policy design

The distribution of German household environmental footprints (EnvFs) across income groups is analyzed by using EXIOBASE v3.6 and the consumer expenditure survey of 2013. Expenditure underreporting is corrected by using a novel method, where the expenditures are modeled as truncated normal distribution. The focus lies on carbon (CF) and material (MF) footprints, which for average German households are 9.1 ± 0.4 metric tons CO₂e and 10.9 ± 0.6 metric tons material per capita. Although the lowest‐income group has the lowest share of transportation in EnvFs, at 10.4% (CF) and 3.9% (MF), it has the highest share of electricity and utilities in EnvFs, at 39.4% (CF) and 16.7% (MF). In contrast, the highest‐income group has the highest share of transportation in EnvFs, at 20.3% (CF) and 12.4% (MF). The highest‐income group has a higher share of emissions produced overseas (38.6% vs. 34.3%) and imported resource use (69.9% vs. 66.4%) compared to the average households. When substituting 50% of imported goods with domestic ones in a counterfactual scenario, this group only decreases its CF by 2.8% and MF by 5.3%. Although incomes in Germany are distributed more equally (Gini index 0.28), the German household CF is distributed less equally (0.16). A uniform carbon tax across all sectors would be regressive (Suits index ?0.13). Hence, a revenue recycling scheme is necessary to alleviate the burden on low‐income households. The overall carbon intensity shows an inverted‐U trend due to the increasing consumption of carbon‐intensive heating for lower‐income groups, indicating a possible rebound effect for these groups. This article met the requirements for a gold – gold JIE data openness badge described at http://jie.click/badges.