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Paratachardina mithila Varshney
No full text<i>Paratachardina mithila</i> Varshney <p> <i>Paratachardina mithila</i> Varshney, 1968: 489; 1977: 58.</p> <p> <i>Paratachardina mithilae</i> Varshney, 1997: 30. Incorrect subsequent spelling [see 'Notes'].</p> <p> <b>Type data. Holotype,</b> adult female. <b>INDIA: Assam,</b> Shillong, in the gardens of Ward Lake, coll. R. K. Varshney, i.1967, on <i>Photinia notoniana</i> var. <i>macrophylla</i>. <b>Paratypes:</b> same data as holotype except some specimens coll. vi.1967 or viii.1970 (NZSI). [Types not seen; see 'Notes'.]</p> <p>Adult female</p> <p> The following descriptions of unmounted and mounted material are adapted from Varshney (1977). <b>Unmounted material.</b> Lac test of adult female almost round, brownish black, with three small openings on top for brachial and anal orifices; with 16 conspicuous longitudinal ridges that divide the test into sectors; a circular spot on the middle of each ridge, probably corresponding to marginal duct cluster openings.</p> <p> <b>Mounted material.</b> Body trilobed, 2.5–3.0 mm long, 2.8–3.0 mm wide. Brachia short, 103 µm long. Each brachial plate oval, distal half slightly larger, each 68–120 µm long, 51–70 µm wide; pseudospines totalling 44–50, occupying about two-thirds area of brachial plate center, with gaps on upper large portion. Anterior spiracles each 137 µm long, 86 µm wide, situated far away from brachial plates, spiracular pores with 5- loculi. Dorsal spine small, conical, 68–70 µm long, with a hollow, not pointed tip; membranous pedicel of dorsal spine well developed, 70–103 um long and 70–103 µm wide. Anal tubercle well developed, 86–170 µm long, 120–140 µm wide; supra-anal plate subequal or slightly longer than its maximum width. Anal ring not divided in sectors; supra-anal plate forming a cup-shaped cavity. Anal fringe of few acute lobes, with narrow and deep clefts. Anal ring setae just reach, or slightly protrude past anal fringe. Antennae minute and obscure. Marginal duct clusters in 8 pairs, each roughly round, poorly demarcated, with ducts arranged irregularly. Ventral duct clusters present.</p> <p> <b>Notes.</b> Subsequent to his original description, Varshney (1997) listed the species name as " mithilae " rather than " mithila ", without giving an explanation for his action. Varshney's (1968, 1977) descriptions do not specify the etymology of the name " mithila ", and do not indicate whether it should be regarded as a noun or an adjective. According to the Article 31.2.2 of the <i>International Code of Zoological Nomenclature</i> (ICZN 1999), the name “ mithila ” becomes a noun in apposition and should be retained as " mithila ". Even though Varshney (personal communication) emended " mithila " to " mithilae " because the species was named after a woman, articles 31, 32 and 33 of the ICZN (1999) make it clear that such an alteration to the species name is an incorrect subsequent spelling, as recognised by Ben-Dov (2006).</p> <p> According to Varshney (1977), this species is similar to <i>P. t h e a e</i>, from which it can be separated due to its larger adult female size, anal tubercle subequal in length and width, and pedicel of the dorsal spine not much longer than the length of the spine itself. Type material of <i>P. mithila</i> was not available in the present study, as we did not receive a reply to our request for a loan from the NZSI, and no type material or non-type topotypic specimens could be located in any other museum. Varshney (1977) gave a key to separate <i>P. mithila</i> and <i>P.</i></p> <p> <i>theae</i> as follows (Varshney 1977: 56, key couplet number 4):</p> <p> – Anal tubercle slightly longer than its maximum width; pedicel of dorsal spine as long as spine itself.................................................................................................................................................................... <i>mithila</i> – Anal tubercle distinctly broader than its maximum length; pedicel of dorsal spine much longer than the spine <i>....................................................................................................................................................... theae</i></p> <p> However, Varshney’s (1977) description of <i>P. mithila</i> overlaps with his description of <i>P. t h e a e</i> in the character states used to separate them in the key. The minimum length and width of the anal tubercle of <i>P. mithila</i> given by Varshney’s (1977) description is 86 µm and 120 µm, respectively, in which case, there must be specimens for which the anal tubercle is distinctly broader than its maximum length. On the other hand, the anal tubercle in the syntypes of <i>P. t h e a e</i> herein studied are approximately as long as wide, with some specimens being slightly longer than wide, and others being slightly wider than long. Furthermore, the length of the pedicel of the dorsal spine also varies in <i>P. t h e a e</i> and sometimes is about the same length as the spine. Specimens from China collected on the same host genus as <i>P. m i t h i l a</i>, i.e., on <i>Photinia benthamiana</i>, were available for study (see 'Other material studied' under <i>P. t h e a e</i>), but these could not be separated morphologically from <i>P. t h e a e</i>. Thus adult females of <i>P. mithilae</i> and <i>P. t h e a e</i> appear similar in all features considered and the two species cannot be separated with the available information (see also 'Diagnosis' of <i>P. ternata</i>).</p>Published as part of <i>Kondo, Takumasa & Gullan, Penny J., 2007, Taxonomic review of the lac insect genus Paratachardina Balachowsky (Hemiptera: Coccoidea: Kerriidae), with a revised key to genera of Kerriidae and description of two new species, pp. 1-41 in Zootaxa 1617</i> on pages 17-18, DOI: <a href="http://zenodo.org/record/179122">10.5281/zenodo.179122</a>
Sequencing the Chickpea Genome
No full textThe importance of chickpea and constraints in chickpea production urged the need of chickpea genome. Varshney and colleagues in 2013 reported the draft genome of chickpea (kabuli). The genome assembly was 532.29 Mb spanning across 7,163 scaffolds and consisted of 28,269 gene models. The estimated size of chickpea genome was 738.09 Mb based on k-mer analysis. The draft genome assembly covered 73.8% of the total estimated genome size for chickpea. Gene annotation was carried for predicted gene models, though the UTRs and promoters have not been yet been predicted. Genome duplication and synteny analysis with other closely related legume crops showed gene conservation and segmental duplications spread across the draft genome assembly. The genome assembly provides resource for targeting genes responsible for disease resistance which are of agronomic importance. The genome assembly has been used for genome-assisted breeding and is further utilized to study the diversity and domestication of chickpea
Can genomics boost productivity of orphan crops?
No full textRajeev K Varshney, Jean-Marcel Ribaut, Edward S Buckler, Roberto Tuberosa, J Antoni Rafalski & Peter Langridg
Multi-RF Beamforming-Based Cellular Communication Over Wideband mmWaves
No full textThe existing literature on cellular multi-user mmWave communication focus on joint baseband and RF precoding designs to enable spatial multiple access with minimum interference. These studies either assume the number of users M is less than the number of RF units N(RF )or schedule the users in time domain by dedicating one RF unit to each user if M > N-RF. It is expected that serving multiple users over OFDMA in each analog beam will offer better utilization of the wideband channel. To this end, for the scenario with M >> N-RF we propose a sectored-cell model that is supported by multi-RF chains over the widehand mmWave channel, with each beam serving multiple users within a sector and the sectors being scheduled in round-robin fashion. We also propose a variable time frame structure that conducts sector-wise initial access, with simultaneous access to all users within a sector. It provides improved spectrum efficiency and decreased initial access delay as compared to the initial access using exhaustive beam search method. We then jointly estimate the optimum beamwidth and optimum N-RF that offer maximum average long-run user rate. Further, we introduce a reduced-complexity sector sojourn time optimization for non-homogeneously distributed users, that improves fairness of long-run user rates leveraging the variable time frame structure. The numerical results show that, while a high value of N-RF causes more interference to peak data rate, the average long-run user rate improves. Additionally, using a very narrow beam is also not optimal for providing maximum rate support. The proposed beamforming method offers a higher average long-run user rate over the competitive beamforming schemes while the complexity of user scheduling is independent of M
Requirement of Whole-Genome Sequencing and Background History of the National and International Genome Initiatives
No full textChickpea is the second most important grain legume for food and nutritional security in the arid and semi-arid regions of the world. The genome sequence provides the basis for a wide range of studies, from the important goal of accelerated breeding to identifying the molecular basis of key agronomic traits, in addition to understanding the basic legume biology. The discussions during 5th International Conference on Legume Genetics and Genomics, held during July 8–10, 2010 in Asilomar, USA, provided the platform for the genesis of International Chickpea Genome Sequencing Consortium (ICGSC http://ceg.icrisat.org/gt-bt/ICGGC/ICGSC.htm), and as result of global research partnership co-led by ICRISAT, UC-Davis, and BGI-Shenzhen, involving 49 scientists from 23 organizations in 10 countries the draft genome of kabuli genotype CDC Frontier was published. On the other hand, the Next Generation Challenge Programme on Chickpea Genomics (NGCPCG) initiative unraveled the genome sequence of desi genotype ICC 4958. This chapter summarizes the background history of two independent efforts to generate draft genome sequence of kabuli and desi chickpea genomes. In addition, the chapter also highlights key developments of application of genome sequence for crop improvement
Model Plants and Crop Improvement
No full textWithin the past decade, there has been an explosion of research in both the public and private sectors regarding the use of plant genetic models to improve crop yield. Bringing together experts from across the globe, Model Plants and Crop Improvement provides a critical assessment of the potential of model plant species for crop improvement. The first comprehensive summary of the use of model plant systems, the book delineates the model species' contribution to understanding the genomes of crop species.
The book provides an in-depth examination of the achievements and limitations of the model paradigm. It explores how continued research in models can contribute to the goal of delivering the outputs of molecular biology to crops. Covering the major genetic models such as Arabidopsis thaliana, Lotus japonicus, and Medigago, the book goes on to discuss applications to food plants of global importance including rice, canola, and legumes. The book introduces the evolutionary, genetic, genomic, and morphological attributes of B. distachyon that make it such an attractive new model plant system.
As the post-genomic era dawns, a key question to address is how this growing body of genetic and biological information can be extended beyond the model to the modeled species. This book takes you one step closer to applying modeling results to crops in the field
Advances in Chickpea Genomic Resources for Accelerating the Crop Improvement
No full textChickpea plays a major role in food and nutritional security worldwide. Its productivity is severely affected by various biotic and abiotic stresses; hence development of stress resilience varieties that can yield higher under stress environment remains the call of the hour. Conventional breeding approaches clubbed with the genome information, commonly known as genomic-assisted breeding (GAB) have the potential to accelerate the crop improvement efforts. In order to deploy the GAB for crop improvement in chickpea, there was need to convert an orphan crop chickpea into the genomic resource-rich crop. Advent of sequencing technology has resulted in reduction of cost and led to development of huge genomic resources in chickpea. A variety of markers have been developed, used for various mapping studies including linkage mapping and association mapping and finally deployed for developing the superior varieties using GAB approached such as marker assisted backcrossing and genomic selection. The chapter reviews the journey of chickpea status from orphan crop with almost no marker resources to a genome resource-rich crop, which are being used for achieving the genetic gains at a momentum
Genomic Selection for Crop Improvement: New Molecular Breeding Strategies for Crop Improvement
No full textGenomic Selection for Crop Improvement serves as handbook for users by providing basic as well as advanced understandings of genomic selection. This useful review explains germplasm use, phenotyping evaluation, marker genotyping methods, and statistical models involved in genomic selection. It also includes examples of ongoing activities of genomic selection for crop improvement and efforts initiated to deploy the genomic selection in some important crops. In order to understand the potential of GS breeding, it is high time to bring complete information in the form of a book that can serve as a ready reference for geneticist and plant breeders
Genomic Selection for Crop Improvement: An Introduction
No full textMarker-assisted selection (MAS) exploits the markers associated with traits of interest for selecting lines with superior alleles for developing improved lines. However use of MAS is restricted to simple traits due to its inability to handle complex traits. Advancements in genomics technologies have been able to dramatically reduce the cost of genotyping, enabling the use of genome-wide marker data for selecting lines with higher breeding value. Genomic selection (GS), a modern breeding approach that uses genome-wide marker data to estimate the breeding value and has the potential to address the complex traits. GS exploits the genotyping and phenotyping data on a training population to train the prediction models to calculate the genomic estimated breeding value (GEBV). GS has the capability to reduce selection cycle duration and increase selection accuracy, intensity, efficiency, and gains per unit of time, thereby enhancing the rate of genetic gains. Availability of cost-effective genotyping platforms has enabled the cost-effective generation of large-scale genotyping data, facilitating the deployment of GS in several crop species. This chapter provides an introduction to the book, highlighting the basic and advanced principles of GS breeding and its applications for crop improvement
Current Status and Prospects of Genomic Selection in Legumes
No full textLegumes play a major role in food and nutritional security across the world. The current rate of genetic gains in legume breeding programs is not enough to meet the food and nutritional requirement of an ever increasing global population. To feed this growing population, it is essential to enhance the rate of genetic gains for increased productivity of these legumes. Genomics tools have great potential in developing improved cultivars faster and more precisely by deploying modern breeding approaches. Marker-assisted backcrossing (MABC) and marker-assisted recurrent selection (MARS) approaches have been successfully deployed in several legume crops for improving traits with simple genetic behaviour. However, it is difficult to address the complex traits using MABC and MARS as several large and small effect quantitative trait loci (QTLs) are involved in their expression. Genomic selection (GS) has potential to capture small and large effect genetic factors and deal with the complex traits. Over the last decade, large scale genomic resources have been developed in majority of the legume crops, which provide a perfect platform to deploy genome-wide information in selecting breeding material for enhancing the rate of genetic gain. Many legume breeders have already took initiatives towards deploying GS breeding by developing training populations, standardizing the GS models, studying effect of marker density, size of training population, and genotype and environment interaction. This chapter presents an overview on the current status of GS and presents the future prospects of its deployment in some legume breeding programs
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