Dataset Information

Improvement of Rice Biomass Yield through QTL-Based Selection.

ABSTRACT: Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related traits in recombinant inbred lines. Phenotypic values for these traits showed a continuous distribution with transgressive segregation, suggesting that selection can affect plant weight in the progeny. Four significant QTLs were mapped for plant weight, three for grain weight, and five for stem and leaf weight (at ? = 0.05); some of them overlapped. Multiple regression analysis showed that about 43% of the phenotypic variance of plant weight was significantly explained (P < 0.0001) by six of the QTLs. From F2 plants derived from the same parental cross as the recombinant inbred lines, we divergently selected lines that carried alleles with positive or negative additive effects at these QTLs, and performed successive selfing. In the resulting F6 lines and parents, plant weight significantly differed among the genotypes (at ? = 0.05). These results demonstrate that QTL-based selection is effective in improving rice biomass yield.

SUBMITTER: Matsubara K

PROVIDER: S-EPMC4795639 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Improvement of Rice Biomass Yield through QTL-Based Selection.

Matsubara Kazuki K Yamamoto Eiji E Kobayashi Nobuya N Ishii Takuro T Tanaka Junichi J Tsunematsu Hiroshi H Yoshinaga Satoshi S Matsumura Osamu O Yonemaru Jun-Ichi J Mizobuchi Ritsuko R Yamamoto Toshio T Kato Hiroshi H Yano Masahiro M

PloS one 20160317 3

Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related ...[more]

PMID: 26986071

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Project description:In molecular breeding of super rice, it is essential to isolate the best quantitative trait loci (QTLs) and genes of leaf shape and explore yield potential using large germplasm collections and genetic populations. In this study, a recombinant inbred line (RIL) population was used, which was derived from a cross between the following parental lines: hybrid rice Chunyou84, that is, japonica maintainer line Chunjiang16B (CJ16); and indica restorer line Chunhui 84 (C84) with remarkable leaf morphological differences. QTLs mapping of leaf shape traits was analyzed at the heading stage under different environmental conditions in Hainan (HN) and Hangzhou (HZ). A major QTL qLL9 for leaf length was detected and its function was studied using a population derived from a single residual heterozygote (RH), which was identified in the original population. qLL9 was delimitated to a 16.17 kb region flanked by molecular markers C-1640 and C-1642, which contained three open reading frames (ORFs). We found that the candidate gene for qLL9 is allelic to DEP1 using quantitative real-time polymerase chain reaction (qRT-PCR), sequence comparison, and the clustered regularly interspaced short palindromic repeat-associated Cas9 nuclease (CRISPR/Cas9) genome editing techniques. To identify the effect of qLL9 on yield, leaf shape and grain traits were measured in near isogenic lines (NILs) NIL-qLL9CJ16 and NIL-qLL9C84, as well as a chromosome segment substitution line (CSSL) CSSL-qLL9KASA with a Kasalath introgressed segment covering qLL9 in the Wuyunjing (WYJ) 7 backgrounds. Our results showed that the flag leaf lengths of NIL-qLL9C84 and CSSL-qLL9KASA were significantly different from those of NIL-qLL9CJ16 and WYJ 7, respectively. Compared with NIL-qLL9CJ16, the spike length, grain size, and thousand-grain weight of NIL-qLL9C84 were significantly higher, resulting in a significant increase in yield of 15.08%. Exploring and pyramiding beneficial genes resembling qLL9C84 for super rice breeding could increase both the source (e.g., leaf length and leaf area) and the sink (e.g., yield traits). This study provides a foundation for future investigation of the molecular mechanisms underlying the source⁻sink balance and high-yield potential of rice, benefiting high-yield molecular design breeding for global food security.

Project description:BackgroundThe genetic and genomic basis of flowering time and biomass yield in alfalfa (Medicago sativa L.) remains poorly understood mainly due to the autopolyploid nature of the species and the lack of adequate genomic resources. We constructed linkage maps using genotyping-by-sequencing (GBS) based single dose allele (SDA) SNP and mapped alfalfa timing of flowering (TOF), spring yield (SY), and cumulative summer biomass (CSB) in a pseudo-testcross F1 population derived from a fall dormant (3010) and a non-dormant (CW 1010) cultivars. We analyzed the quantitative trait loci (QTL) to identify conserved genomic regions and detected molecular markers and potential candidate genes associated with the traits to improve alfalfa and provide genomic resources for the future studies.ResultsThis study showed that both fall dormant and non-dormant alfalfa cultivars harbored QTL for early and late flowering, suggesting that flowering time in alfalfa is not an indicator of its fall dormancy (FD) levels. A weak phenotypic correlation between the flowering time and fall dormancy (FD) in F1 and checks also corroborated that alfalfa FD and TOF are not the predictors of one another. The relationship between flowering time and alfalfa biomass yield was not strong, but the non-dormant had relatively more SY than dormant. Therefore, selecting superior alfalfa cultivars that are non-dormant, winter-hardy, and early flowering would allow for an early spring harvest with enhanced biomass. In this study, we found 25 QTL for TOF, 17 for SY and six QTL for CSB. Three TOF related QTL were stable and four TOF QTL were detected in the corresponding genomic locations of the flowering QTL of M. truncatula, an indication of possible evolutionarily conserved regions. The potential candidate genes for the SNP sequences of QTL regions were identified for all three traits and these genes would be potential targets for further molecular studies.ConclusionsThis research showed that variation in alfalfa flowering time after spring green up has no association with dormancy levels. Here we reported QTL, markers, and potential candidate genes associated with spring flowering time and biomass yield of alfalfa, which constitute valuable genomic resources for improving these traits via marker-assisted selection (MAS).

Dataset Information

Improvement of Rice Biomass Yield through QTL-Based Selection.

Publications

Improvement of Rice Biomass Yield through QTL-Based Selection.

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