scholarly journals Population genomics of Mediterranean oat (A. sativa) reveals high genetic diversity and three loci for heading date

2021 ◽  
Author(s):  
F. J. Canales ◽  
G. Montilla-Bascón ◽  
W. A. Bekele ◽  
C. J. Howarth ◽  
T. Langdon ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Population Genomics ◽  
Heading Date ◽  
Population Genetic Analysis ◽  
High Genetic Diversity ◽  
A Genome ◽  
Interactive Map

Key messageGenomic analysis of Mediterranean oats reveals high genetic diversity and three loci for adaptation to this environment. This information together with phenotyping and passport data, gathered in an interactive map, will be a vital resource for oat genetic improvement.AbstractDuring the twentieth century, oat landraces have increasingly been replaced by modern cultivars, resulting in loss of genetic diversity. However, landraces have considerable potential to improve disease and abiotic stress tolerance and may outperform cultivars under low input systems. In this work, we assembled a panel of 669 oat landraces from Mediterranean rim and 40 cultivated oat varieties and performed the first large-scale population genetic analysis of both red and white oat types of Mediterranean origin. We created a public database associated with an interactive map to visualize information for each accession. The oat collection was genotyped with 17,288 single-nucleotide polymorphism (SNP) loci to evaluate population structure and linkage disequilibrium (LD); to perform a genome-wide association study (GWAs) for heading date, a key character closely correlated with performance in this drought-prone area. Population genetic analysis using both structure and PCA distinguished two main groups composed of the red and white oats, respectively. The white oat group was further divided into two subgroups. LD decay was slower within white lines in linkage groups Mrg01, 02, 04, 12, 13, 15, 23, 33, whereas it was slower within red lines in Mrg03, 05, 06, 11, 21, 24, and 28. Association analysis showed several significant markers associated with heading date on linkage group Mrg13 in white oats and on Mrg01 and Mrg08 in red oats.

scholarly journals SINE jumping contributes to large-scale polymorphisms in the pig genomes

2021 ◽  
Author(s):  
Cai Chen ◽  
Enrico D'Alessandro ◽  
Eduard Murani ◽  
Yao Zheng ◽  
Domenico Giosa ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Structural Variations ◽  
Population Genetic Analysis ◽  
Protein Coding ◽  
Pig Breeds ◽  
A Genome ◽  
Trait Locus ◽  
And Cluster Analysis

Abstract Background: Molecular markers based on retrotransposon insertion polymorphisms (RIPs) have been developed and are widely used in plants and animals. Short interspersed nuclear elements (SINEs) exert wide impacts on gene activity and even on phenotypes. However, SINE RIP profiles in livestock remain largely unknown, and not be revealed in pigs. Results: Our data revealed that SINEA1 displayed the most polymorphic insertions (22.5% intragenic and 26.5% intergenic), followed by SINEA2 (10.5% intragenic and 9% intergenic) and SINEA3 (12.5% intragenic and 5.0% intergenic). We developed a genome-wide SINE RIP mining protocol and obtained a large number of SINE RIPs (36,284), with over 80% accuracy and an even distribution in chromosomes (14.5/Mb), and 74.34% of SINE RIPs generated by SINEA1 element. Over 65% of pig SINE RIPs overlap with genes, with significant enrichment in the first and second introns of protein-coding and long non-coding RNA genes. Nearly half of the RIPs are common in these pig breeds. Sixteen SINE RIPs were applied for population genetic analysis in 23 pig breeds, the phylogeny tree and cluster analysis were generally consistent with the geographical distributions of native pig breeds in China. Conclusions: Our analysis revealed that SINEA1–3 elements, particularly SINEA1, are high polymorphic across different pig breeds, and generate large-scale structural variations in the pig genomes. And over 35, 000 SINE RIP markers were obtained. These data indicate that young SINE elements play important roles in creating new genetic variations and shaping the evolution of pig genome, and also provide strong evidences to support the great potential of SINE RIPs as genetic markers, which can be used for population genetic analysis and quantitative trait locus (QTL) mapping in pig.

scholarly journals SINE jumping contributes to large-scale polymorphisms in the pig genomes

Mobile DNA ◽  
2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Cai Chen ◽  
Enrico D’Alessandro ◽  
Eduard Murani ◽  
Yao Zheng ◽  
Domenico Giosa ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Structural Variations ◽  
Population Genetic Analysis ◽  
Protein Coding ◽  
Pig Breeds ◽  
A Genome ◽  
Trait Locus ◽  
And Cluster Analysis

Abstract Background Molecular markers based on retrotransposon insertion polymorphisms (RIPs) have been developed and are widely used in plants and animals. Short interspersed nuclear elements (SINEs) exert wide impacts on gene activity and even on phenotypes. However, SINE RIP profiles in livestock remain largely unknown, and not be revealed in pigs. Results Our data revealed that SINEA1 displayed the most polymorphic insertions (22.5 % intragenic and 26.5 % intergenic), followed by SINEA2 (10.5 % intragenic and 9 % intergenic) and SINEA3 (12.5 % intragenic and 5.0 % intergenic). We developed a genome-wide SINE RIP mining protocol and obtained a large number of SINE RIPs (36,284), with over 80 % accuracy and an even distribution in chromosomes (14.5/Mb), and 74.34 % of SINE RIPs generated by SINEA1 element. Over 65 % of pig SINE RIPs overlap with genes, most of them (> 95 %) are in introns. Overall, about one forth (23.09 %) of the total genes contain SINE RIPs. Significant biases of SINE RIPs in the transcripts of protein coding genes were observed. Nearly half of the RIPs are common in these pig breeds. Sixteen SINE RIPs were applied for population genetic analysis in 23 pig breeds, the phylogeny tree and cluster analysis were generally consistent with the geographical distributions of native pig breeds in China. Conclusions Our analysis revealed that SINEA1–3 elements, particularly SINEA1, are high polymorphic across different pig breeds, and generate large-scale structural variations in the pig genomes. And over 35,000 SINE RIP markers were obtained. These data indicate that young SINE elements play important roles in creating new genetic variations and shaping the evolution of pig genome, and also provide strong evidences to support the great potential of SINE RIPs as genetic markers, which can be used for population genetic analysis and quantitative trait locus (QTL) mapping in pig.

scholarly journals Large-scale population genetic analysis for hemoglobinopathies reveals different mutation spectra in Central Greece compared to the rest of the country

2007 ◽  
Vol 82 (7) ◽  
pp. 634-636 ◽  
Author(s):  
Maria Samara ◽  
Ioanna Chiotoglou ◽  
Angelos Kalamaras ◽  
Sophia Likousi ◽  
Christos Chassanidis ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Population Genetic Analysis ◽  
Central Greece ◽  
Scale Population ◽  
Mutation Spectra

scholarly journals Population genetic analysis ofGiardia duodenalis: genetic diversity and haplotype sharing between clinical and environmental sources

2017 ◽  
Vol 6 (2) ◽  
pp. e00424 ◽  
Author(s):  
Mauricio Durigan ◽  
Maisa Ciampi-Guillardi ◽  
Ricardo C. A. Rodrigues ◽  
Juliane A. Greinert-Goulart ◽  
Isabel C. V. Siqueira-Castro ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genetic Analysis ◽  
Population Genetic ◽  
Haplotype Sharing ◽  
Population Genetic Analysis

scholarly journals mSphere of Influence: the Wild Genetic Diversity of Our Closest Yeast Companions

mSphere ◽  
2019 ◽  
Vol 4 (5) ◽  
Author(s):  
Douda Bensasson
Keyword(s):  
Genetic Diversity ◽  
Population Genetic ◽  
Natural Variation ◽  
Field Survey ◽  
Population Genomics ◽  
Yeast Species ◽  
Natural Environments ◽  
Population Genetic Analysis ◽  
Content Type ◽  
Wild Yeast

ABSTRACT Douda Bensasson uses the population genomics of model yeast species to understand how wild yeast colonize new environments, such as humans or their food. In this mSphere of Influence article, she reflects on how the discovery of “Surprisingly diverged populations of Saccharomyces cerevisiae in natural environments remote from human activity” (Q.-M. Wang, W.-Q. Liu, G. Liti, S.-A. Wang, and F.-Y. Bai, Mol Ecol 21:5404–5417, 2012, https://doi.org/10.1111/j.1365-294X.2012.05732.x) showed that a field survey and population genetic analysis of old growth forests could “unveil the hidden part of the iceberg” of natural variation in S. cerevisiae that went unnoticed for over a hundred years of yeast research.

Sign in / Sign up

Export Citation Format

Share Document