17 research outputs found

    Genetic differentiation and admixture between sibling allopolyploids in the Dactylorhiza majalis complex

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    Allopolyploidization often happens recurrently, but the evolutionary significance of its iterative nature is not yet fully understood. Of particular interest are the gene flow dynamics and the mechanisms that allow young sibling polyploids to remain distinct while sharing the same ploidy, heritage and overlapping distribution areas. By using eight highly variable nuclear microsatellites, newly reported here, we investigate the patterns of divergence and gene flow between 386 polyploid and 42 diploid individuals, representing the sibling allopolyploids Dactylorhiza majalis s.s. and D. traunsteineri s.l. and their parents at localities across Europe. We make use in our inference of the distinct distribution ranges of the polyploids, including areas in which they are sympatric (that is, the Alps) or allopatric (for example, Pyrenees with D. majalis only and Britain with D. traunsteineri only). Our results show a phylogeographic signal, but no clear genetic differentiation between the allopolyploids, despite the visible phenotypic divergence between them. The results indicate that gene flow between sibling Dactylorhiza allopolyploids is frequent in sympatry, with potential implications for the genetic patterns across their entire distribution range. Limited interploidal introgression is also evidenced, in particular between D. incarnata and D. traunsteineri. Altogether the allopolyploid genomes appear to be porous for introgression from related diploids and polyploids. We conclude that the observed phenotypic divergence between D. majalis and D. traunsteineri is maintained by strong divergent selection on specific genomic areas with strong penetrance, but which are short enough to remain undetected by genotyping dispersed neutral markers.UE FWF; P22260UE: Y66

    Groundwater in a water-rich environment : Wales, a land of plenty

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    Traditionally, Wales has relied on surface water, with only 8% of the total public supply currently derived from groundwater sources. There are various significant aquifers in Wales, including the Carboniferous Limestone in South and North-East Wales and the Triassic aquifer in the Vale of Clwyd, as well as superficial granular deposits that are of particular importance in West Wales. Groundwater quality is generally good and minimal treatment is required. Hydrogeological data in the public domain for Wales are scarce: the Carboniferous Limestone, for example, is particularly poorly documented. Despite this lack of information there are some notable groundwater schemes, but current legislative aspects now require a better overall understanding of the hydrogeology of Wales. A key recommendation is the preparation of public domain data-sets and a comprehensive report on the hydrogeology of Wales

    Selection of parents for crossing based on genotyping and phenotyping for stripe rust (Puccinia striiformis) resistance and agronomic traits in bread wheat breeding

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    Bread wheat (Triticum aestivum L.) germplasm consisting of 45 genotypes were clustered phenotypically using ten morphological traits and Area Under Disease Progress Curve (AUDPC) as measure of stripe rust resistance. The clustering was ratified by using twenty three molecular markers (SSR, EST and STS) linked to stripe rust (Puccinia striiformis f. sp. tritici) resistant QTLs. The aim was to asses the extent of genetic variability among the genotypes in order to select the parents for crossing between the resistant and susceptible genotypes with respect to stripe rust. The Euclidian dissimilarity values resulted from phenotypic data regarding morphological traits and AUDPC were used to construct a dendrogram for clustering the accessions. Using un-weighted pair group method with arithmetic means, another dendrogram resulted from the similarity coefficient values was used to distinguish the genotypes with respect to stripe rust. Clustering based on phenotypic data produced two major groups and five clusters (with Euclidian dissimilarity ranging from 2.44 to 16.16) whereas genotypic data yielded two major groups and four clusters (with percent similarity coefficient values ranging from 0.1 to 46.0) to separate the gene pool into highly resistant, resistant, moderately resistant, moderately susceptible and susceptible genotypes. With few exceptions, the outcome of both type of clustering was almost similar and resistant as well as susceptible genotypes came in the same clusters of molecular genotyping as yielded by phenotypic clustering. As a result seven genotypes (Bakhtawar-92, Frontana, Saleem 2000, Tatara, Inqilab-91, Fakhre Sarhad and Karwan) of diverse genetic background were selected for pyramiding stripe rust resistant genes as well as some other agronomic traits after hybridization.45 генотипов мягкой пшеницы (Triticum aestivum L.) были фенотипически кластеризованы по десяти морфологическим признакам и Area Under Disease Progress Curve (AUDPC) как показателя устойчивости к желтой ржавчине. Кластеризация была подтверждена использованием 23 молекулярных маркеров (SSR, EST and STS), связанных с QTL локусами устойчивости к Puccinia striiformis f. sp. tritici. Целью работы было оценить степень генетической изменчивости, чтобы отобрать родителей для скрещиваний между устойчивыми и чувствительными к желтой ржавчине генотипами. Показатели отклонения, полученные из анализа морфологических признаков и AUDPC, были исполь-зованы для построения дендрограмм для кластеризации образцов. С использованием невзвешенного попарно-группового метода со среднеарифметическими значениями другая дендрограмма, полученная на основе сходства значений коэффициентов, была использована для того, чтобы отличить генотипы по устойчивости к желтой ржавчине. Кластеризация по фенотипическим признакам дала в результате две основные группы и пять кластеров, в то время как генотипические данные дали две основные группы и четыре кластера, что позволило выделить высокоустойчивые, устойчивые, среднеустойчивые, среднечувствительные и чувствительные генотипы. За некоторыми исключениями, результат обоих способов кластеризации был почти одинаков: устойчивые и чувствительные генотипы попали в одни и те же кластеры как в результате молекулярного генотипирования, так и фенотипической кластеризации. В итоге было отобрано семь генотипов (Bakhtawar-92, Frontana, Saleem-2000, Tatara, Inqilab-91, Fakhre Sarhad and Karwan) с разным генетическим фоном для генов устойчивости к желтой ржавчине и некоторых других агрономических признаков после гибридизации

    Functionally associated molecular genetic marker map construction in perennial ryegrass (Lolium perenne L.)

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    A molecular marker-based map of perennial ryegrass (Lolium perenne L.) has been constructed through the use of polymorphisms associated with expressed sequence tags (ESTs). A pair-cross between genotypes from a North African ecotype and the cultivar Aurora was used to generate a two-way pseudo-testcross population. A selection of 157 cDNAs assigned to eight different functional categories associated with agronomically important biological processes was used to detect polymorphic EST-RFLP loci in the F 1(NA 6 x AU 6) population. A comprehensive set of EST-SSR markers was developed from the analysis of 14,767 unigenes, with 310 primer pairs showing efficient amplification and detecting 113 polymorphic loci. Two parental genetic maps were produced: the NA 6 genetic map contains 88 EST-RFLP and 71 EST-SSR loci with a total map length of 963 cM, while the AU 6 genetic map contains 67 EST-RFLP and 58 EST-SSR loci with a total map length of 757 cM. Bridging loci permitted the alignment of homologous chromosomes between the parental maps, and a sub-set of genomic DNA-derived SSRs was used to relate linkage groups to the perennial ryegrass reference map. Regions of segregation distortion were identified, in some instances in common with other perennial ryegrass maps. The EST-derived marker-based map provides the basis for in silico comparative genetic mapping, as well as the evaluation of co-location between QTLs and functionally associated genetic loci
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