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. Choudhary , M. , Hoßsain , F. , Muthusamy , V. , Thirunavukkarasu , N. , Saha , S. , Pandey , N. , Jha , S.K. , Gupta , H.S. 2015 . Microsatellite marker-based genetic diversity analyses of novel maize inbreds poßsessing rare

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Cereal Research Communications
Authors: R. Goswami, R.U. Zunjare, S. Khan, V. Muthusamy, A. Baveja, A.K. Das, S.K. Jaiswal, J.S. Bhat, S.K. Guleria, and F. Hossain

Vitamin-A deficiency is a major health concern. Traditional yellow maize possesses low provitamin-A (proA). Mutant crtRB1 gene significantly enhances proA. 24 experimental hybrids possessing crtRB1 allele were evaluated for β-carotene (BC), β-cryptoxanthin (BCX), lutein (LUT), zeaxanthin (ZEA), total carotenoids (TC) and grain yield at multi-locations. BC (0.64–17.24 µg/g), BCX (0.45–6.84 µg/g), proA (0.86–20.46 µg/g), LUT (9.60–31.03 µg/g), ZEA (1.24–12.73 µg/g) and TC (20.60–64.02 µg/g) showed wide variation. No significant genotype × location interaction was observed for carotenoids. The mean BC (8.61 µg/g), BCX (4.04 µg/g) and proA (10.63 µg/g) in crtRB1-based hybrids was significantly higher than normal hybrids lacking crtRB1-favourable allele (BC: 1.73 µg/g, BCX: 1.29 µg/g and proA: 2.37 µg/g). Selected crtRB1-based hybrids possessed 33% BC and 40% BCX compared to 6% BC and 5% BCX in normal hybrids. BC showed positive correlation with BCX (r = 0.90), proA (r = 0.99) and TC (r = 0.64) among crtRB1-based hybrids. Carotenoids didn't show association with grain yield. Average yield potential of proA rich hybrids (6794 kg/ha) was at par with normal hybrids (6961 kg/ha). PROAH-13, PROAH-21, PROAH-17, PROAH-11, PROAH-23, PROAH-24 and PROAH-3 were the most promising with >12 µg/g proA and >6000 kg/ha grain yield. The newly identified crtRB1-based hybrids assume significance in alleviating malnutrition.

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Cereal Research Communications
Authors: J. Bányai, P. Szűcs, I. Karsai, K. Mészáros, Cs. Kuti, L. Láng, and Z. Bedő

A total of 96 winter wheat ( Triticum aestivum L.) cultivars registered in Hungary were analysed using 15 wheat microsatellite markers located on different chromosome arms. Analyses revealed 91 SSR alleles with sizes ranging from 123–239 base pairs. The total number of alleles per locus ranged from 2 (Gwm664 and Gwm415) to 11 (Gwm219) with an average number of 6.1. The polymorphic information content (PIC) values ranged from 0.06 to 0.85 with an average number of 0.60 for all markers. Several markers included allele sizes characteristic of a single or a small number of cultivars. At most 9 SSR markers were required to distinguish the 96 cultivars, so the simple sequence repeats could serve as a relatively cheap, rapid method for identifying winter wheat cultivars.

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High molecular weight (HMW-GS) and low molecular weight (LMW-GS) glutenin subunits play a significant role in bread making quality and extensibility, though they signify merely 10% and 40% of the entire seed storage proteins. For the estimation of bread quality on the basis of allelic difference in HMW-GS and LMW-GS at Glu-1 and 3 loci, wheat germplasm (77 genotypes) was collected from diverse agro-climatic regions of Pakistan and characterized by using sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Thirty distinct allelic arrangements were identified with a sum of thirteen Glu-1 alleles. Maximum frequency of allele 1 was found in twenty-nine genotypes at Glu-A1 locus while high proportion of subunit pairs 13 + 16 and 2 + 12 was detected in 33 and 32 genotypes at Glu-B1 as well as Glu-D1 locus, respectively. Few rare alleles were also separated out. The quality scores ranged from 4–10, however highest quality score of ten was more recurrent (36.36%). A good quality score of 8 and 6 were found in 32.47% as well as 19.48% of genotypes individually. In LMW-GS, seventeen diverse combinations of alleles with aggregate of ten Glu-3 alleles were detected. Glu-A3c and Glu-B3d alleles were observed in 33 (42.85%) genotypes, encoding high sedimentation and protein contents. Hence, this will enable the breeders to utilize both glutenin subunits as biochemical indicator for selecting superior wheat genotypes possessing enhanced bread making quality.

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The geometric mean of fitness is considered to be the main indicator of evolutionary change in stochastic models. However, this measure was initially derived for models with infinite population sizes, where the long-term evolutionary behavior can be described with certainty. In this paper we begin an exploration of the limitations and utility of this approach to evolution in finite populations and discuss alternate methods for predicting evolutionary dynamics. We reanalyze a model of lottery competition under environmental stochasticity by including population finiteness, and show that the geometric mean predictions do not always agree with those based on the fixation probability of rare alleles. Further, the fixation probability can be inserted into adaptive dynamics equations to derive the mean state of the population. We explore the effects of increasing population size on these conclusions through simulations. These simulations show that for small population sizes the fixation probability accurately predicts the course of evolution, but as population size becomes large the geometric mean predictions are upheld. The two approaches are reconciled because the time scale on which the fixation probability approach applies becomes very large as population size grows.

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One hundred and sixty Pakistani Hordeum vulgare ssp. vulgare accessions were analyzed for genetic diversity on the basis of hordein, seed storage proteins. In total we have analyzed 7 Hor-1, 12 Hor-2 and 5 Hor-3 alleles for three hordein loci in barley accessions on SDS-PAGE. Out of 24 polymorphic alleles, three rare alleles (Hor 3.1, Hor 2.1, Hor 1.1) were detected. Abundant genetic variability was observed in Pakistani barley accessions for hordein loci. Genetic similarities calculated for all pair wise comparisons of H. vulgare accessions were used to form 83 banding patterns that represent the core collections of Pakistan, which included 50 unique patterns. Multivariate analysis conducted to generate similarity matrix using Jaccard’s coefficient (Jaccard, 1908) to estimate relatedness and divergence among 160 accessions ranged from 0.11 to 1.00, representing high level of genetic variability. Clustering was carried out to determine genetic diversity among the core collections that clustered them into three major clusters. In this study genetic diversity for cultivated barley belonging to different regions of Pakistan were in the order of Punjab> Balochistan> Northern Area> Sindh> A.J.K.> N.W.F.P.

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. Natural Selection: Domains, Levels, and Challenges Slatkin, M. (1985): Rare alleles as indicators of gene flow. Evolution 39 :53-65. Rare alleles as

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genetic drift the rare alleles may be lost by chance and common alleles may become fixed, resulting in low diversity ( Frankham et al . 2004 ). Thus, populations of H. involuta commonly distributed in Mount Abu show moderately high genetic variation

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