scholarly journals The Fate of Deleterious Variants in a Barley Genomic Prediction Population

Genetics ◽  
2019 ◽  
Vol 213 (4) ◽  
pp. 1531-1544
Author(s):  
Thomas J. Y. Kono ◽  
Chaochih Liu ◽  
Emily E. Vonderharr ◽  
Daniel Koenig ◽  
Justin C. Fay ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Genetic Variants ◽  
Exome Capture ◽  
Novel Approach ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Cultivated Species ◽  
Whole Genome Resequencing ◽  
Dna Resequencing

Targeted identification and purging of deleterious genetic variants has been proposed as a novel approach to animal and plant breeding. This strategy is motivated, in part, by the observation that demographic events and strong selection associated with cultivated species pose a “cost of domestication.” This includes an increase in the proportion of genetic variants that are likely to reduce fitness. Recent advances in DNA resequencing and sequence constraint-based approaches to predict the functional impact of a mutation permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley lines, we identified 3855 dSNPs among 497,754 total SNPs. We generated whole-genome resequencing data of Hordeum murinum ssp. glaucum as a phylogenetic outgroup to polarize SNPs as ancestral vs. derived. We also observed a higher proportion of dSNPs per synonymous SNPs (sSNPs) in low-recombination regions of the genome. Using 5215 progeny from a genomic prediction experiment, we examined the fate of dSNPs over three breeding cycles. Adjusting for initial frequency, derived alleles at dSNPs reduced in frequency or were lost more often than other classes of SNPs. The highest-yielding lines in the experiment, as chosen by standard genomic prediction approaches, carried fewer homozygous dSNPs than randomly sampled lines from the same progeny cycle. In the final cycle of the experiment, progeny selected by genomic prediction had a mean of 5.6% fewer homozygous dSNPs relative to randomly chosen progeny from the same cycle.

scholarly journals The fate of deleterious variants in a barley genomic prediction population

2018 ◽  
Author(s):  
TJY Kono ◽  
C Liu ◽  
EE Vonderharr ◽  
D Koenig ◽  
JC Fay ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Genetic Variants ◽  
Recombination Rate ◽  
Exome Capture ◽  
Whole Genome ◽  
Genome Resequencing ◽  
Initial Frequency ◽  
A Genome ◽  
Hordeum Murinum ◽  
Whole Genome Resequencing

AbstractTargeted identification and purging of deleterious genetic variants has been proposed as a novel approach to animal and plant breeding. This strategy is motivated, in part, by the observation that demographic events and strong selection associated with cultivated species pose a “cost of domestication.” This includes an increase in the proportion of genetic variants where a mutation is likely to reduce fitness. Recent advances in DNA resequencing and sequence constraint-based approaches to predict the functional impact of a mutation permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley 6-row spring breeding lines, we identify 3,855 dSNPs among 497,754 total SNPs. In order to polarize SNPs as ancestral versus derived, we generated whole genome resequencing data of Hordeum murinum ssp. glaucum as a phylogenetic outgroup. The dSNPs occur at higher density in portions of the genome with a higher recombination rate than in pericentromeric regions with lower recombination rate and gene density. Using 5,215 progeny from a genomic prediction experiment, we examine the fate of dSNPs over three breeding cycles. Average derived allele frequency is lower for dSNPs than any other class of variants. Adjusting for initial frequency, derived alleles at dSNPs reduce in frequency or are lost more often than other classes of SNPs. The highest yielding lines in the experiment, as chosen by standard genomic prediction approaches, carry fewer homozygous dSNPs than randomly sampled lines from the same progeny cycle. In the final cycle of the experiment, progeny selected by genomic prediction have a mean of 5.6% fewer homozygous dSNPs relative to randomly chosen progeny from the same cycle.Author SummaryThe nature of genetic variants underlying complex trait variation has been the source of debate in evolutionary biology. Here, we provide evidence that agronomically important phenotypes are influenced by rare, putatively deleterious variants. We use exome capture resequencing and a hypothesis-based test for codon conservation to predict deleterious SNPs (dSNPS) in the parents of a multi-parent barley breeding population. We also generated whole-genome resequencing data of Hordeum murinum, a phylogenetic outgroup to barley, to polarize dSNPs by ancestral versus derived state. dSNPs occur disproportionately in the gene-rich chromosome arms, rather than in the recombination-poor pericentromeric regions. They also decrease in frequency more often than other variants at the same initial frequency during recurrent selection for grain yield and disease resistance. Finally, we identify a region on chromosome 4H that strongly associated with agronomic phenotypes in which dSNPs appear to be hitchhiking with favorable variants. Our results show that targeted identification and removal of dSNPs from breeding programs is a viable strategy for crop improvement, and that standard genomic prediction approaches may already contain some information about unobserved segregating dSNPs.

Whole human exome capture for high-throughput sequencing

Genome ◽  
2010 ◽  
Vol 53 (7) ◽  
pp. 568-574 ◽  
Author(s):  
Dae-Won Kim ◽  
Seong-Hyeuk Nam ◽  
Ryong Nam Kim ◽  
Sang-Haeng Choi ◽  
Hong-Seog Park
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Exome Capture ◽  
Microarray Design ◽  
Genome Wide ◽  
Human Genes ◽  
Practical Usefulness ◽  
A Genome ◽  
Wide Scale ◽  
Total Base

We captured the whole human exome by hybridization using synthesized oligonucleotides, based on a high-density microarray design, and we sequenced those captured human exons using high-throughput sequencing on a Genome Sequencer FLX instrument. Of the uniquely mapped reads, 71% fell within target regions, and these corresponded to coverage of 94% of human genes, 87% of exons, and 70% of the total base-pair length of the CCDS set. Our study provides strong evidence for the practical usefulness of this method on a genome-wide scale, showing the resequenced whole human exome database with 501 microRNAs and 307 novel SNPs.

scholarly journals F-Box Genes in the Wheat Genome and Expression Profiling in Wheat at Different Developmental Stages

Genes ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1154
Author(s):  
Min Jeong Hong ◽  
Jin-Baek Kim ◽  
Yong Weon Seo ◽  
Dae Yeon Kim
Keyword(s):  
Developmental Stages ◽  
Brachypodium Distachyon ◽  
Triticum Aestivum L ◽  
Wheat Genome ◽  
Post Translational Modification ◽  
Genome Wide ◽  
A Genome ◽  
High Sequence Homology ◽  
Wide Scale

Genes of the F-box family play specific roles in protein degradation by post-translational modification in several biological processes, including flowering, the regulation of circadian rhythms, photomorphogenesis, seed development, leaf senescence, and hormone signaling. F-box genes have not been previously investigated on a genome-wide scale; however, the establishment of the wheat (Triticum aestivum L.) reference genome sequence enabled a genome-based examination of the F-box genes to be conducted in the present study. In total, 1796 F-box genes were detected in the wheat genome and classified into various subgroups based on their functional C-terminal domain. The F-box genes were distributed among 21 chromosomes and most showed high sequence homology with F-box genes located on the homoeologous chromosomes because of allohexaploidy in the wheat genome. Additionally, a synteny analysis of wheat F-box genes was conducted in rice and Brachypodium distachyon. Transcriptome analysis during various wheat developmental stages and expression analysis by quantitative real-time PCR revealed that some F-box genes were specifically expressed in the vegetative and/or seed developmental stages. A genome-based examination and classification of F-box genes provide an opportunity to elucidate the biological functions of F-box genes in wheat.

scholarly journals Genome-wide mapping of unexplored essential regions in the Saccharomyces cerevisiae genome: evidence for hidden synthetic lethal combinations in a genetic interaction network

2014 ◽  
Vol 42 (15) ◽  
pp. 9838-9853 ◽  
Author(s):  
Saeed Kaboli ◽  
Takuya Yamakawa ◽  
Keisuke Sunada ◽  
Tao Takagaki ◽  
Yu Sasano ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Genetic Interaction ◽  
Interaction Network ◽  
Essential Genes ◽  
Genetic Interactions ◽  
Lethal Gene ◽  
Synthetic Lethal ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale

Abstract Despite systematic approaches to mapping networks of genetic interactions in Saccharomyces cerevisiae, exploration of genetic interactions on a genome-wide scale has been limited. The S. cerevisiae haploid genome has 110 regions that are longer than 10 kb but harbor only non-essential genes. Here, we attempted to delete these regions by PCR-mediated chromosomal deletion technology (PCD), which enables chromosomal segments to be deleted by a one-step transformation. Thirty-three of the 110 regions could be deleted, but the remaining 77 regions could not. To determine whether the 77 undeletable regions are essential, we successfully converted 67 of them to mini-chromosomes marked with URA3 using PCR-mediated chromosome splitting technology and conducted a mitotic loss assay of the mini-chromosomes. Fifty-six of the 67 regions were found to be essential for cell growth, and 49 of these carried co-lethal gene pair(s) that were not previously been detected by synthetic genetic array analysis. This result implies that regions harboring only non-essential genes contain unidentified synthetic lethal combinations at an unexpectedly high frequency, revealing a novel landscape of genetic interactions in the S. cerevisiae genome. Furthermore, this study indicates that segmental deletion might be exploited for not only revealing genome function but also breeding stress-tolerant strains.

scholarly journals Machine-learning annotation of human splicing branchpoints

2016 ◽  
Author(s):  
Bethany Signal ◽  
Brian S Gloss ◽  
Marcel E Dinger ◽  
Timothy R Mercer
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Gene Splicing ◽  
Genetic Encoding ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
A Genome ◽  
Wide Scale ◽  
The Impact ◽  
Splicing Patterns

ABSTRACTBackgroundThe branchpoint element is required for the first lariat-forming reaction in splicing. However due to difficulty in experimentally mapping at a genome-wide scale, current catalogues are incomplete.ResultsWe have developed a machine-learning algorithm trained with empirical human branchpoint annotations to identify branchpoint elements from primary genome sequence alone. Using this approach, we can accurately locate branchpoints elements in 85% of introns in current gene annotations. Consistent with branchpoints as basal genetic elements, we find our annotation is unbiased towards gene type and expression levels. A major fraction of introns was found to encode multiple branchpoints raising the prospect that mutational redundancy is encoded in key genes. We also confirmed all deleterious branchpoint mutations annotated in clinical variant databases, and further identified thousands of clinical and common genetic variants with similar predicted effects.ConclusionsWe propose the broad annotation of branchpoints constitutes a valuable resource for further investigations into the genetic encoding of splicing patterns, and interpreting the impact of common- and disease-causing human genetic variation on gene splicing.

scholarly journals Emerging Technologies for Genome-Wide Profiling of DNA Breakage

2021 ◽  
Vol 11 ◽  
Author(s):  
Matthew J. Rybin ◽  
Melina Ramic ◽  
Natalie R. Ricciardi ◽  
Philipp Kapranov ◽  
Claes Wahlestedt ◽  
...  
Keyword(s):  
Genome Instability ◽  
Dna Double Strand Breaks ◽  
Single Nucleotide ◽  
Strand Breaks ◽  
Single Strand Breaks ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Nucleotide Resolution ◽  
Genomic Regions

Genome instability is associated with myriad human diseases and is a well-known feature of both cancer and neurodegenerative disease. Until recently, the ability to assess DNA damage—the principal driver of genome instability—was limited to relatively imprecise methods or restricted to studying predefined genomic regions. Recently, new techniques for detecting DNA double strand breaks (DSBs) and single strand breaks (SSBs) with next-generation sequencing on a genome-wide scale with single nucleotide resolution have emerged. With these new tools, efforts are underway to define the “breakome” in normal aging and disease. Here, we compare the relative strengths and weaknesses of these technologies and their potential application to studying neurodegenerative diseases.

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