Screening for signatures of selection of Tianzhu white yak using genome‐wide re‐sequencing

Abstract Background Runs of homozygosity (ROH) have become the state-of-the-art method for analysis of inbreeding in animal populations. Moreover, ROH are suited to detect signatures of selection via ROH islands and are used in other applications, such as genomic prediction and genome-wide association studies (GWAS). Currently, a vast amount of single nucleotide polymorphism (SNP) data is available online, but most of these data have never been used for ROH analysis. Therefore, we performed a ROH analysis on large medium-density SNP datasets in eight animal species (cat, cattle, dog, goat, horse, pig, sheep and water buffalo; 442 different populations) and make these results publicly available. Results The results include an overview of ROH islands per population and a comparison of the incidence of these ROH islands among populations from the same species, which can assist researchers when studying other (livestock) populations or when looking for similar signatures of selection. We were able to confirm many known ROH islands, for example signatures of selection for the myostatin (MSTN) gene in sheep and horses. However, our results also included multiple other ROH islands, which are common to many populations and not identified to date (e.g. on chromosomes D4 and E2 in cats and on chromosome 6 in sheep). Conclusions We are confident that our repository of ROH islands is a valuable reference for future studies. The discovered ROH island regions represent a unique starting point for new studies or can be used as a reference for future studies. Furthermore, we encourage authors to add their population-specific ROH findings to our repository.

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Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysisThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽

10.1139/g10-080 ◽

2010 ◽

Vol 53 (11) ◽

pp. 1002-1016 ◽

Cited By ~ 59

Author(s):

B.R. Cullis ◽

A.B. Smith ◽

C.P. Beeck ◽

W.A. Cowling

Keyword(s):

Pedigree Information ◽

Environment Interaction ◽

Correlation Matrices ◽

New Approach ◽

Genome Wide ◽

Selection Indices ◽

New Varieties ◽

Oilseed Brassicas ◽

Analytic Models ◽

Selection Of

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.

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A Robust Rerank Approach for Feature Selection and Its Application to Pooling-Based GWA Studies

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/860673 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Jia-Rou Liu ◽

Po-Hsiu Kuo ◽

Hung Hung

Keyword(s):

Characteristic Curve ◽

Real Data ◽

Tuning Parameter ◽

Practical Implementation ◽

Tuning Parameters ◽

Genome Wide ◽

Feature Based ◽

The Difference ◽

Gwa Studies ◽

Selection Of

Large-p-small-ndatasets are commonly encountered in modern biomedical studies. To detect the difference between two groups, conventional methods would fail to apply due to the instability in estimating variances int-test and a high proportion of tied values in AUC (area under the receiver operating characteristic curve) estimates. The significance analysis of microarrays (SAM) may also not be satisfactory, since its performance is sensitive to the tuning parameter, and its selection is not straightforward. In this work, we propose a robust rerank approach to overcome the above-mentioned diffculties. In particular, we obtain a rank-based statistic for each feature based on the concept of “rank-over-variable.” Techniques of “random subset” and “rerank” are then iteratively applied to rank features, and the leading features will be selected for further studies. The proposed re-rank approach is especially applicable for large-p-small-ndatasets. Moreover, it is insensitive to the selection of tuning parameters, which is an appealing property for practical implementation. Simulation studies and real data analysis of pooling-based genome wide association (GWA) studies demonstrate the usefulness of our method.

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Determination of Genetic Structure and Signatures of Selection in Three Strains of Tanzania Shorthorn Zebu, Boran and Friesian Cattle by Genome-Wide SNP Analyses

PLoS ONE ◽

10.1371/journal.pone.0171088 ◽

2017 ◽

Vol 12 (1) ◽

pp. e0171088 ◽

Cited By ~ 7

Author(s):

George Msalya ◽

Eui-Soo Kim ◽

Emmanuel L. K. Laisser ◽

Maulilio J. Kipanyula ◽

Esron D. Karimuribo ◽

...

Keyword(s):

Genetic Structure ◽

Genome Wide ◽

Signatures Of Selection ◽

Friesian Cattle

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Prioritization and Evaluation of Flooding Tolerance Genes in Soybean [Glycine max (L.) Merr.]

Frontiers in Genetics ◽

10.3389/fgene.2020.612131 ◽

2021 ◽

Vol 11 ◽

Author(s):

Mu-Chien Lai ◽

Zheng-Yuan Lai ◽

Li-Hsin Jhan ◽

Ya-Syuan Lai ◽

Chung-Feng Kao

Keyword(s):

Glycine Max ◽

Genome Wide Association Study ◽

Meta Analysis ◽

Soybean Seeds ◽

Flooding Tolerance ◽

Big Data Mining ◽

Genome Wide ◽

Glycine Max L ◽

Mapping Gene ◽

Selection Of

Soybean [Glycine max (L.) Merr.] is one of the most important legume crops abundant in edible protein and oil in the world. In recent years there has been increasingly more drastic weather caused by climate change, with flooding, drought, and unevenly distributed rainfall gradually increasing in terms of the frequency and intensity worldwide. Severe flooding has caused extensive losses to soybean production and there is an urgent need to breed strong soybean seeds with high flooding tolerance. The present study demonstrates bioinformatics big data mining and integration, meta-analysis, gene mapping, gene prioritization, and systems biology for identifying prioritized genes of flooding tolerance in soybean. A total of 83 flooding tolerance genes (FTgenes), according to the appropriate cut-off point, were prioritized from 36,705 test genes collected from multidimensional genomic features linking to soybean flooding tolerance. Several validation results using independent samples from SoyNet, genome-wide association study, SoyBase, GO database, and transcriptome databases all exhibited excellent agreement, suggesting these 83 FTgenes were significantly superior to others. These results provide valuable information and contribution to research on the varieties selection of soybean.

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Autophagy as a mechanism for adaptive prediction-mediated emergence of drug resistance

10.1101/2021.02.02.429461 ◽

2021 ◽

Author(s):

Nivedita Nivedita ◽

John D. Aitchison ◽

Nitin S. Baliga

Keyword(s):

Drug Resistance ◽

Stressful Environment ◽

Adaptive Prediction ◽

Genome Wide ◽

Microbial Infections ◽

Effective Therapeutic Strategy ◽

Subsequent Selection ◽

Tolerant State ◽

Core Genes ◽

Selection Of

ABSTRACTDrug resistance is a major problem in treatment of microbial infections and cancers. There is growing evidence that a transient drug tolerant state may precede and potentiate the emergence of drug resistance. Therefore, understanding the mechanisms leading to tolerance is critical for combating drug resistance and for the development of effective therapeutic strategy. Through laboratory evolution of yeast, we recently demonstrated that adaptive prediction (AP), a strategy employed by organisms to anticipate and prepare for a future stressful environment, can emerge within 100 generations by linking the response triggered by a neutral cue (caffeine) to a mechanism of protection against a lethal agent (5-FOA). Here, we demonstrate that mutations selected across multiple laboratory evolved lines had linked the neutral cue response to core genes of autophagy. Across these evolved lines, conditional activation of autophagy through AP conferred tolerance, and potentiated subsequent selection of mutations in genes specific to overcoming the toxicity of 5-FOA. We propose a model to explain how extensive genome-wide genetic interactions of autophagy facilitates emergence of AP over short evolutionary timescales to potentiate selection of resistance-conferring mutations.

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Genome-wide association mapping reveals race-specific SNP markers associated with anthracnose resistance in carioca common beans

PLoS ONE ◽

10.1371/journal.pone.0251745 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0251745

Author(s):

Caléo Panhoca de Almeida ◽

Jean Fausto de Carvalho Paulino ◽

Caio Cesar Ferrari Barbosa ◽

Gabriel de Moraes Cunha Gonçalves ◽

Roberto Fritsche-Neto ◽

...

Keyword(s):

Quantitative Resistance ◽

Association Studies ◽

Colletotrichum Lindemuthianum ◽

Genome Wide Association ◽

High Yield ◽

Genome Wide Association Studies ◽

Anthracnose Resistance ◽

Resistant Cultivars ◽

Genome Wide ◽

Selection Of

Brazil is the largest consumer of dry edible beans (Phaseolus vulgaris L.) in the world, 70% of consumption is of the carioca variety. Although the variety has high yield, it is susceptible to several diseases, among them, anthracnose (ANT) can lead to losses of up to 100% of production. The most effective strategy to overcome ANT, a disease caused by the fungus Colletotrichum lindemuthianum, is the development of resistant cultivars. For that reason, the selection of carioca genotypes resistant to multiple ANT races and the identification of loci/markers associated with genetic resistance are extremely important for the genetic breeding process. Using a carioca diversity panel (CDP) with 125 genotypes and genotyped by BeadChip BARCBean6K_3 and a carioca segregating population AM (AND-277 × IAC-Milênio) genotyped by sequencing (GBS). Multiple interval mapping (MIM) and genome-wide association studies (GWAS) were used as mapping tools for the resistance genes to the major ANT physiological races present in the country. In general, 14 single nucleotide polymorphisms (SNPs) showed high significance for resistance by GWAS, and loci associated with multiple races were also identified, as the Co-3 locus. The SNPs ss715642306 and ss715649427 in linkage disequilibrium (LD) at the beginning of chromosome Pv04 were associated with all the races used, and 16 genes known to be related to plant immunity were identified in this region. Using the resistant cultivars and the markers associated with significant quantitative resistance loci (QRL), discriminant analysis of principal components (DAPC) was performed considering the allelic contribution to resistance. Through the DAPC clustering, cultivar sources with high potential for durable anthracnose resistance were recommended. The MIM confirmed the presence of the Co-14 locus in the AND-277 cultivar which revealed that it was the only one associated with resistance to ANT race 81. Three other loci were associated with race 81 on chromosomes Pv03, Pv10, and Pv11. This is the first study to identify new resistance loci in the AND-277 cultivar. Finally, the same Co-14 locus was also significant for the CDP at the end of Pv01. The new SNPs identified, especially those associated with more than one race, present great potential for use in marker-assisted and early selection of inbred lines.

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Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

Frontiers in Genetics ◽

10.3389/fgene.2021.600789 ◽

2021 ◽

Vol 12 ◽

Author(s):

Nur Shuhadah Mohd Saad ◽

Anita A. Severn-Ellis ◽

Aneeta Pradhan ◽

David Edwards ◽

Jacqueline Batley

Keyword(s):

Climate Change ◽

Reverse Genetics ◽

Agronomic Traits ◽

Crop Evolution ◽

Breeding Cycle ◽

World Population ◽

Genome Wide ◽

The Face ◽

Selection Of ◽

The Way

Meeting the needs of a growing world population in the face of imminent climate change is a challenge; breeding of vegetable and oilseed Brassica crops is part of the race in meeting these demands. Available genetic diversity constituting the foundation of breeding is essential in plant improvement. Elite varieties, land races, and crop wild species are important resources of useful variation and are available from existing genepools or genebanks. Conservation of diversity in genepools, genebanks, and even the wild is crucial in preventing the loss of variation for future breeding efforts. In addition, the identification of suitable parental lines and alleles is critical in ensuring the development of resilient Brassica crops. During the past two decades, an increasing number of high-quality nuclear and organellar Brassica genomes have been assembled. Whole-genome re-sequencing and the development of pan-genomes are overcoming the limitations of the single reference genome and provide the basis for further exploration. Genomic and complementary omic tools such as microarrays, transcriptomics, epigenetics, and reverse genetics facilitate the study of crop evolution, breeding histories, and the discovery of loci associated with highly sought-after agronomic traits. Furthermore, in genomic selection, predicted breeding values based on phenotype and genome-wide marker scores allow the preselection of promising genotypes, enhancing genetic gains and substantially quickening the breeding cycle. It is clear that genomics, armed with diversity, is set to lead the way in Brassica improvement; however, a multidisciplinary plant breeding approach that includes phenotype = genotype × environment × management interaction will ultimately ensure the selection of resilient Brassica varieties ready for climate change.

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