Identification of candidate genome regions controlling disease resistance in Arachis

<p>Abstract</p> <p>Background</p> <p>Worldwide, diseases are important reducers of peanut (<it>Arachis hypogaea</it>) yield. Sources of resistance against many diseases are available in cultivated peanut genotypes, although often not in farmer preferred varieties. Wild species generally harbor greater levels of resistance and even apparent immunity, although the linkage of agronomically un-adapted wild alleles with wild disease resistance genes is inevitable. Marker-assisted selection has the potential to facilitate the combination of both cultivated and wild resistance loci with agronomically adapted alleles. However, in peanut there is an almost complete lack of knowledge of the regions of the <it>Arachis </it>genome that control disease resistance.</p> <p>Results</p> <p>In this work we identified candidate genome regions that control disease resistance. For this we placed candidate disease resistance genes and QTLs against late leaf spot disease on the genetic map of the A-genome of <it>Arachis</it>, which is based on microsatellite markers and legume anchor markers. These marker types are transferable within the genus <it>Arachis </it>and to other legumes respectively, enabling this map to be aligned to other <it>Arachis </it>maps and to maps of other legume crops including those with sequenced genomes. In total, 34 sequence-confirmed candidate disease resistance genes and five QTLs were mapped.</p> <p>Conclusion</p> <p>Candidate genes and QTLs were distributed on all linkage groups except for the smallest, but the distribution was not even. Groupings of candidate genes and QTLs for late leaf spot resistance were apparent on the upper region of linkage group 4 and the lower region of linkage group 2, indicating that these regions are likely to control disease resistance.</p

Mutation increasing β-carotene concentrations does not adversely affect concentrations of essential mineral elements in pepper fruit

<div><p>Vitamin and mineral deficiencies are prevalent in human populations throughout the world. Vitamin A deficiency affects hundreds of millions of pre-school age children in low income countries. Fruits of pepper (<i>Capsicum annuum</i> L.) can be a major dietary source of precursors to Vitamin A biosynthesis, such as β-carotene. Recently, pepper breeding programs have introduced the orange-fruited (<i>of</i>) trait of the mutant variety Oranzheva kapiya, which is associated with high fruit β-carotene concentrations, to the mutant variety Albena. In this manuscript, concentrations of β-carotene and mineral elements (magnesium, phosphorus, sulphur, potassium, zinc, calcium, manganese, iron and copper) were compared in fruit from P31, a red-fruited genotype derived from the variety Albena, and M38, a genotype developed by transferring the orange-fruited mutation (<i>of</i>) into Albena. It was observed that fruit from M38 plants had greater β-carotene concentration at both commercial and botanical maturity (4.9 and 52.7 mg / kg fresh weight, respectively) than fruit from P31 plants (2.3 and 30.1 mg / kg fresh weight, respectively). The mutation producing high β-carotene concentrations in pepper fruits had no detrimental effect on the concentrations of mineral elements required for human nutrition.</p></div

FIDEL—a retrovirus-like retrotransposon and its distinct evolutionary histories in the A- and B-genome components of cultivated peanut

In this paper, we describe a Ty3-gypsy retrotransposon from allotetraploid peanut (Arachis hypogaea) and its putative diploid ancestors Arachis duranensis (A-genome) and Arachis ipaënsis (B-genome). The consensus sequence is 11,223 bp. The element, named FIDEL (Fairly long Inter-Dispersed Euchromatic LTR retrotransposon), is more frequent in the A- than in the B-genome, with copy numbers of about 3,000 (±950, A. duranensis), 820 (±480, A. ipaënsis), and 3,900 (±1,500, A. hypogaea) per haploid genome. Phylogenetic analysis of reverse transcriptase sequences showed distinct evolution of FIDEL in the ancestor species. Fluorescent in situ hybridization revealed disperse distribution in euchromatin and absence from centromeres, telomeric regions, and the nucleolar organizer region. Using paired sequences from bacterial artificial chromosomes, we showed that elements appear less likely to insert near conserved ancestral genes than near the fast evolving disease resistance gene homologs. Within the Ty3-gypsy elements, FIDEL is most closely related with the Athila/Calypso group of retrovirus-like retrotransposons. Putative transmembrane domains were identified, supporting the presence of a vestigial envelope gene. The results emphasize the importance of FIDEL in the evolution and divergence of different Arachis genomes and also may serve as an example of the role of retrotransposons in the evolution of legume genomes in general

Study of Memristive Associative Capacitive Networks for CAM Applications

Resistively switching devices are key enabler for future hybrid CMOS/nano-crossbar array architectures. Due to the availability of nonvolatile states novel reconfigurable in-memory computing approaches become feasible. In particular complementary resistive switches are highly attractive cross-point junction elements due to their inherent sneak path prevention. By applying a nondestructive capacitive readout procedure the complementary resistive switches implement reconfigurable associative capacitive networks. Those networks establish the functionality of content addressable memories and enable memory intensive computing operations for realization of pattern recognition tasks. These are essential for router or network switch applications. In this study a highly accurate physics-based dynamical memristive device model is used to evaluate the network properties for various configurations. The high ON-to-OFF ratio of electrochemical metallization cells beneficially supports the functionality of the network. The voltage margin and energy consumption are analyzed for various crossbar array sizes. Moreover, a test setup to study those networks supported by measurements was developed and proof-of-concept results for a pre-programmed capacitive array are presented

Automatic hoof-on and -off detection in horses using hoof-mounted inertial measurement unit sensors

For gait classification, hoof-on and hoof-off events are fundamental locomotion characteristics of interest. These events can be measured with inertial measurement units (IMUs) which measure the acceleration and angular velocity in three directions. The aim of this study was to present two algorithms for automatic detection of hoof-events from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. Seven Warmblood horses were equipped with two wireless IMUs, which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted on a lead over a force plate for internal validation. The agreement between the algorithms for the acceleration and angular velocity signals with the force plate was evaluated by Bland Altman analysis and linear mixed model analysis. These analyses were performed for both hoof-on and hoof-off detection and for both algorithms separately. For the hoof-on detection, the angular velocity algorithm was the most accurate with an accuracy between 2.39 and 12.22 ms and a precision of around 13.80 ms, depending on gait and hoof. For hoof-off detection, the acceleration algorithm was the most accurate with an accuracy of 3.20 ms and precision of 6.39 ms, independent of gait and hoof. These algorithms look highly promising for gait classification purposes although the applicability of these algorithms should be investigated under different circumstances, such as different surfaces and different hoof trimming conditions

Pepper genotypes with fruit in technical and botanical maturity phase.

<p>a) M38 with orange colour of mature fruit; b) P31 with red colour of mature fruit.</p

Concentrations of mineral elements in the pericarp dry matter of pepper fruit from P31 and M38 plants.

<p>Data are mean ± standard error of the mean of 60 fruit from P31 plants and 59 fruit from M38 plants.</p