QTL for nodal root angle in sorghum (Sorghum bicolor L. Moench) co-locate with QTL for traits associated with drought adaptation

Mace, Emma; Singh, Vijaya; Oosterom, Erik van; Hammer, Graeme; Hunt, Colleen H.; Jordan, David R.

doi:10.1007/s00122-011-1690-9

Cited by 246 publications

(254 citation statements)

References 42 publications

Supporting

Mentioning

232

Contrasting

Order By: Relevance

“…We co-located a fresh weight QTL and blade number QTL in the same region on chromosome 8. The co-location of QTLs has been reported in wheat and sorghum, especially for related traits (Mace et al, 2012;Lillemo et al, 2013). We also showed that fresh weight and blade number had a significant correlation.…”

Section: Discussionsupporting

confidence: 74%

QTL mapping of forage yield and forage yield component traits in Sorghum bicolor x S. sudanense

Liu

Wang

et al. 2015

Genet. Mol. Res.

View full text Add to dashboard Cite

ABSTRACT. The sorghum-sudangrass hybrid (Sorghum bicolor x S. sudanense) is an important forage crop. However, little is known about the genetic mechanisms related to forage yield and the 4 forage yield component traits in this forage crop. In this study, a linkage map was constructed with 124 assigned SSR markers using an F 2 mapping population derived from the crossing of sorghum Tx623A and sudangrass Sa. Nine quantitative trait loci (QTLs) were detected for forage yield and the 4 forage yield component traits using inclusive composite interval mapping. Five fresh weight QTLs were identified and contributed >50% of the total phenotypic variance. Of these QTLs, all showed additive and dominant effects, but most exhibited mainly dominant effects. These results will provide useful information for improvements in sorghum-sudangrass hybrid breeding.

show abstract

Section: Discussionsupporting

confidence: 74%

QTL mapping of forage yield and forage yield component traits in Sorghum bicolor x S. sudanense

Liu

Wang

et al. 2015

Genet. Mol. Res.

View full text Add to dashboard Cite

show abstract

“…In both wheat ) and sorghum , genetic variation in root system architecture has been reported and associated with increased water capture at depth. In both cases, there is evidence of association with enhanced adaptation to water limitation (Manschadi et al 2007;Mace et al 2011), especially in the case of sorghum, where genomic regions controlling root architecture were associated with yield performance in breeding trials (Mace et al 2011). …”

Section: Water Capture and Use Efficiencymentioning

confidence: 99%

The physiological basis of genetic improvement in maize (Zea mays L.) yield in the US Corn Belt

Ponce¹

View full text Add to dashboard Cite

Maize, along with rice and wheat, provides the foundation of human food supply. Ecological intensification of maize cropping systems and accelerated genetic improvement of maize yield will be necessary to satisfy an increasing demand from rapid population growth (Cassman 1999).Understanding of the physiological basis underpinning genetic improvement of maize can inform breeding efforts and improve tailoring of maize hybrids to intensified cropping systems.Maize yields in the US Corn Belt have increased at a rate of 1% a year for over 70+ years. A series of field studies using the so-called ERA hybrid set (Duvick et al. 2004a), which represent commercially successful hybrid releases over that period, demonstrated that yield improvement resulted from the interaction between genotype and plant population, and documented that yield advance was associated with increased leaf angle score and stay-green score, and decreases in anthesis-silking interval (ASI), tassel size scores, and barrenness. Changes in leaf angle scores and stay green scores have been implicated as determinants of increased radiation use efficiency and water capture (Hammer et al. 2009a;). Increased kernel number per unit area via reduced barrenness, shorter ASI, and reduced tassel size suggest that biomass allocation to the ear may have changed as the result of selection for yield in the ERA hybrids (Duvick et al. 2004a;Hammer et al. 2009a). Increased total biomass and increased partitioning to the kernels around silking and during early ear growth have been implicated as the major physiological determinants of the yield increase in short-season maize (Tollenaar et al. 2006a).We have a cursory understanding of the physiological drivers of yield improvement in temperate maize. This study provides empirical evidence to evaluate previously proposed hypotheses (i.e., water capture; Hammer et al. (2009a)) and deductions from field observations. This study utilizes a crop growth and development framework structured on concepts of resource capture, utilization efficiency and allocation to guide field experimentation. The experimental component of this study includes field experiments in managed stress environments located in USA and Chile during the growing seasons 2012 and 2011/2012 respectively, seeking to quantify genotypic differences in light and water capture, crop and ear growth, and resource allocation. Two seasons of experiments in 2012 utilizing the lysimeter and root chamber facilities located at UQ have been used to quantify genotypic differences in transpiration dynamics and efficiency, biomass allocation, and sensitivities to drought stress. Experimental work used a contrasting subset of single crosses from the ERA hybrids with seed available in Australia. All the experiments were planted at the highest plant density used in each location and platform.ii Measurement of soil water during two years of field experiments showed that total water capture under water-limited conditions did not differ between hybrids from another subset of t...

show abstract

“…A few studies have been conducted to identify the genetic regions controlling specific root traits in barley (Robinson et al, 2016), maize (Zurek et al, 2015;Pestsova et al, 2016), rice (Uga et al, 2011;Liang et al, 2013), sorghum (Mace et al, 2012;Rajkumar et al, 2013), and wheat (Sharma et al, 2011;Hamada et al, 2012;Bai et al, 2013;Christopher et al, 2013;Zhang et al, 2014). In some studies, root traits have been associated with yield and yield components under water-limited environments.…”

Section: Molecular Selectionmentioning

confidence: 99%

“…For instance in rice, a QTL for deep rooting DEEP ROOTING 1 (DRO1) was identified (Uga et al, 2011) and recently cloned in a shallow-rooting rice cultivar to enhance its yield under drought conditions by increasing deep rooting (Uga et al, 2013). In sorghum, genetic association between narrower nodal root angle and increased grain yield has been found, and manipulating nodal root angle through molecular breeding has been proposed to improve drought adaptation (Mace et al, 2012). In maize, QTL for the root traits primary root length, primary root diameter, primary root weight, and weight of the adventitious seminal roots and some of these QTL are overlapping with QTL for grain yield in the field (Tuberosa et al, 2002b).…”

Section: Molecular Selectionmentioning

confidence: 99%

“…In other cereals, the association between seminal root traits and deeper, more branching rooted systems has been demonstrated in sorghum, maize and rice (Singh et al, 2010;Uga et al, 2011). Additionally, a number of QTL showing homology across species have been reported recently (Mace et al, 2012). SRA and SRN are expressed at an early developmental stage, offering opportunities for large-scale screening.…”

Section: Identification Of Proxy Traitsmentioning

confidence: 99%

See 1 more Smart Citation

Breeding wheat for drought adaptation: Development of selection tools for root architectural traits

Richard¹

View full text Add to dashboard Cite

A crop's ability to explore the soil profile and extract available water at different depths is largely determined by root system architecture. For instance in wheat (Triticum aestivum L.), it has been suggested that a narrow and deep root system can provide better access to deep soil moisture. Such root systems are particularly beneficial for rain-fed regions where crops rely heavily on stored soil moisture at depth, as encountered in the eastern Australian wheat belt. Thus, by targeting desirable root architectural traits, wheat breeders could increase genetic gain for yield in response to the growing demand for food. Yet, selection for these below-ground traits is challenging because roots are difficult to measure and are under complex genetic control. The aim of this project was to develop new phenotypic and molecular selection tools to facilitate selection for root architectural traits in Australian wheat breeding programs targeting terminal moisture stress adaptation. This project focuses on narrow seminal root angle and high number of seminal roots in wheat seedlings; two proxy traits for desirable mature root system architecture. Firstly, to overcome the lack of efficient root screening methods, a high-throughput and cost-effective method for phenotyping seminal root angle and number in wheat was developed, using clear pots in a controlled environment growth facility. Compared to pre-existing phenotyping methods, the newly developed method successfully provided higher heritability, greater repeatability, and better efficiency in terms of time, space, and labour. Further, the clear-pot method revealed a high degree of phenotypic variation for both seminal root traits. Subsequently, to test the ability to introgressed allelic variation for seminal root angle into elite Australian wheat cultivars via phenotypic selection, backcross tail populations for both narrow and wide root angle were developed, using the clear-pot method. Rapid shifts in both population distribution and allele frequency were observed after just two rounds of selection. Further, comparison of the tail populations revealed some genomic regions under selection, for which marker-assisted selection appeared successful. Hence, genetic diversity can be exploited via phenotypic and molecular selection to target desired root system architecture in wheat breeding programs.

show abstract

QTL for nodal root angle in sorghum (Sorghum bicolor L. Moench) co-locate with QTL for traits associated with drought adaptation

Cited by 246 publications

References 42 publications

QTL mapping of forage yield and forage yield component traits in Sorghum bicolor x S. sudanense

QTL mapping of forage yield and forage yield component traits in Sorghum bicolor x S. sudanense

The physiological basis of genetic improvement in maize (Zea mays L.) yield in the US Corn Belt

Breeding wheat for drought adaptation: Development of selection tools for root architectural traits

Contact Info

Product

Resources

About