1,721,213 research outputs found
An evo-devo perspective on root genetic variation in cereals
No full textEvolutionary developmental biology (evo-devo) deals with the identification of genetic events underlying the evolution of morphological diversity-a complex task. A new paper in Journal of Experimental Botany by Tai et al. (pages 403-414) provides evidence that evolutionarily young non-syntenic genes were involved in the appearance of seminal roots in the maize evolutionary lineage
The crop QTLome comes of age
No full textRecent progress in genomics and phenomics allows for a more accurate and comprehensive characterization of the Quantitative Trait Loci (QTLs) hereafter defined 'QTLome' as a whole that govern the variation targeted in breeding programs. High-density genotyping now provides unambiguous identification of QTL alleles, and for several traits beneficial alleles at major QTLs have already been deployed in marker-assisted breeding. However, the amount of QTLome information is enormous and approaches to distill and translate this information to breeders remain to be refined. Improved QTL meta-analyses, better estimation of QTL effects, improved crop modelling and full sharing of raw QTL data will enable a more effective exploitation of the QTLome
Understanding and exploiting the genetics of plant root traits
No full textThis chapter illustrates how genomics and other -omics approaches coupled with new-generation sequencing (NGS) platforms have been deployed to dissect the genetic make-up of RSA traits and better understand their functions, particularly under environmentally constrained conditions that commonly occur in most farmed soils. The major emphasis is devoted to studies during the past two decades in crops and only occasional reference is provided to the vast literature from RSA studies conducted in Arabidopsis and other model plants. The chapter also provides examples on how, in some cases, this knowledge is already benefiting farmers and how it can help in reducing the environmental impact of agriculture worldwide.. Tuberosa, Roberto & Frascaroli, Elisabetta & Maccaferri, Marco & Salvi, Silvio. (2021). Understanding and exploiting the genetics of plant root traits. 10.19103/AS.2020.0075.21
Drought adaptation characteristics of a giant reed mutant
No full textGiant reed (Arundo donax L.) is a spontaneous C3 perennial grass, which propagates only
vegetatively due to seed sterility. This prevents the development and establishment of
targeted improving breeding programmes. The development of mutants could improve the
performance and/or suitability of the species for bioenergy production purposes, especially in
stressful environments. Even though giant reed is considered a drought tolerant species,
nothing is known about the effects of mutagenesis on its morpho-productive and
physiological traits relevant to yield responses to drought. The objective of this study was to
characterise some phenotypic traits of mutagenised giant reed under drought conditions. The
trial was carried out under semi-controlled environmental conditions in a total of 16 rhizotrons
of one cubic meter capacity. Calibrated soil moisture probes were installed at different depths
in order to adjust the soil moisture content to 25% (field capacity) and 10% (v/v) in the wellwatered
and dry treatments, respectively. A mutant (UniBO3) developed by UniBO and
Genetic Lab through gamma-irradiation was selected from a pool of 100 mutants and
compared with the non-mutagenised precursor of local origin. Biometric, production, and
physiological parameters were evaluated at young and mature growth stages. Under wellwatered
conditions at both growth stages the tiller density of UniBO3 was significantly higher
than in the local genotype, but both genotypes showed similar biomass yield. The sustained
biomass yield of the droughted local genotype compared with the well-watered conditions
was related to unchanged number of tillers. On the other hand the reduced biomass yield of
the droughted mutant (UniBO3) was significantly correlated with reductions in photosynthetic
capacity (Pn), maximum carboxylation rate (Vcmax), potential electron transport rate (Jmax),
quantum yield (Fv/Fm), and leaf water potential (LWP) at young stages, while at mature
stages with Fv/Fm and LWP. In summary, the UniBO3 mutant showed a reduced tolerance
to drought at productive and physiological levels
Quantitative and Qualitative Biomass Production Potential of Giant Reed Mutants under Rainfed and Irrigated Conditions
No full textAdvances in molecular breeding techniques for barley: targeted induced local lesions in genomes (TILLING)
No full textTargeting Induced Local Lesions IN Genomes (TILLING) is a reverse genetics method enabling the identification of individuals carrying chemically induced allelic variants at a gene of interest, within a mutagenized population. TILLING was first described in Arabidopsis (McCallum et al., 2000) and Drosophila (Bentley et al., 2000), and then extended to several plant species including maize (Till et al., 2004b), wheat (Slade et al., 2005), rice (Suzuki et al., 2008; Till et al., 2007),
and others. It can be implemented in any species where a population of mutant individuals can be generated starting from a homogeneous line. Additionally, a version of TILLING has been described to help in discovery of polymorphisms in natural populations or in cultivars collections (EcoTILLING; Comai et al., 2004). Commonly, TILLING a gene implies three consecutive steps, namely (i) production or availability of a mutagenized population, (ii) PCR amplification of the target gene in a pool of individual genomic DNA samples, and (iii) detection of mutant alleles and individuals carrying them by means of a biochemical essay suitable for nucleotide polymorphism (e.g. SNP) identification. Most TILLING resources have been developed using chemical mutagenesis which mostly induces single-point mutations. This provides the investigator with a very informative range of allelic effects, from effective protein knockouts produced by stop-gain mutations to hypomorphic alleles caused by missense (i.e. amino acid
substitution) mutations. Such different functional alleles are not usually available within populations generated with other types of mutational agents such as insertional mutagenesis (e.g. T-DNA, transposons) or irradiation (e.g. gamma-ray, fast-neutrons), all of which mostly generate knockouts. One additional positive aspect of TILLING is that it does not require any prior genomic knowledge (except for the target gene sequence, which must be known)
Selection of reference genes suitable for normalization of qPCR data under abiotic stresses in bioenergy crop Arundo donax L.
Full text linkAbstract Suitable reference gene selection in qRT-PCR is a key pre-requisite to produce reliable data in gene expression analyses. In this study, novel primers for six commonly used reference genes (AC1, TLF, Act2, TUB α, EF-1α and GAPDH) plus two new candidates (pDUF221 and RPN6) were designed and comparatively tested for expression stability under abiotic stresses (osmotic, heavy metal and heat shock) in shoot, root and their combination of Arundo donax L., a raising non-food energy crop. Expression stability rankings from the most to the least stable gene in each condition and in two tissues (young shoots and roots) were generated with geNorm, NormFinder and BestKeeper programs. All programs provided similar rankings and, strikingly, in most cases identified one of the new candidates, RPN6, as the most suitable reference gene. This novel set of reliable references allows to choose either the best combination of reference genes across multiple stress/organ conditions or to select condition-specific genes that can improve the quality of qRT-PCR analysis. This work provides a solid basis for the functional characterization of A. donax, by enabling accurate quantification of the transcriptional responsiveness under a series of common stress conditions of any gene of interest in this promising biomass/bioenergy species
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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