Project description:Purpose: Kraft pulp yield (KPY) is a key determinant of plantation profitability and increasing the KPY of trees grown in plantations is a major breeding objective. To speed up the breeding process, molecular markers that can predict KPY are desirable. To achieve this goal, we carried out RNA-Seq studies on trees at extremes of KPY in two different trials to identify genes and alleles whose expression correlated with KPY. Methods: We analyzed samples from the extremes of the distribution of KPY in two Eucalyptus nitens trials which also differed in growth to identify genes having differential expression between high and low KPY samples. We used reference-guided transcriptome mapping to study gene expression. Results: Several genes showed differential expression between low and high KPY samples. Gene ontology (GO) enrichment tests revealed up-regulation of stress-related gene categories and down-regulation of gene categories related to wood formation and growth in low KPY samples. More than 110,000 single nucleotide polymorphisms (SNPs) were detected in both the trials and 2103 of these showed differential allelic expression. Allelic expression of 30% of these variants was correlated with total gene expression. To identify the genes showing patterns of positive selection among the genes expressed in the cambial tissue we compared Ka/Ks ratios. The Ka/Ks ratios compare the rate of nonsynonymous substitutions (Ka) to synonymous substitutions (Ks) which can help identifying genes under selection. By comparing the two trials we observed in total 196 genes which had Ka/Ks ratios of more than 1.5 in both the trials strongly suggesting that these genes are under positive selection. A total of six GO categories were enriched in both trials for genes showing signatures of positive selection . All six categories include genes involved in apoptosis, cell death and defense responses. Conclusions: By conducting RNA-Seq analysis in two trials we identified a number of candidate genes and alleles whose expression is correlated with KPY and growth traits in E. nitens. Most of the down-regulated genes in low KPY samples are cell wall-related genes, suggesting that the identified candidate genes are biologically relevant. A number of potential functional polymorphisms were also identified that showed DAE. We detected positive selection signatures in numerous genes that are consistent with the results from RNA-Seq study in E. camaldulensis. The genes and alleles identified in this study form a valuable resource for association and genomic selection studies. Xylem mRNA profiles of Eucalyptus nitens from low and high KPY samples were generated by deep sequencing, in two trials, using Illumina HiSeq.

Project description:Purpose: Kraft pulp yield (KPY) is a key determinant of plantation profitability and increasing the KPY of trees grown in plantations is a major breeding objective. To speed up the breeding process, molecular markers that can predict KPY are desirable. To achieve this goal, we carried out RNA-Seq studies on trees at extremes of KPY in two different trials to identify genes and alleles whose expression correlated with KPY. Methods: We analyzed samples from the extremes of the distribution of KPY in two Eucalyptus nitens trials which also differed in growth to identify genes having differential expression between high and low KPY samples. We used reference-guided transcriptome mapping to study gene expression. Results: Several genes showed differential expression between low and high KPY samples. Gene ontology (GO) enrichment tests revealed up-regulation of stress-related gene categories and down-regulation of gene categories related to wood formation and growth in low KPY samples. More than 110,000 single nucleotide polymorphisms (SNPs) were detected in both the trials and 2103 of these showed differential allelic expression. Allelic expression of 30% of these variants was correlated with total gene expression. To identify the genes showing patterns of positive selection among the genes expressed in the cambial tissue we compared Ka/Ks ratios. The Ka/Ks ratios compare the rate of nonsynonymous substitutions (Ka) to synonymous substitutions (Ks) which can help identifying genes under selection. By comparing the two trials we observed in total 196 genes which had Ka/Ks ratios of more than 1.5 in both the trials strongly suggesting that these genes are under positive selection. A total of six GO categories were enriched in both trials for genes showing signatures of positive selection . All six categories include genes involved in apoptosis, cell death and defense responses. Conclusions: By conducting RNA-Seq analysis in two trials we identified a number of candidate genes and alleles whose expression is correlated with KPY and growth traits in E. nitens. Most of the down-regulated genes in low KPY samples are cell wall-related genes, suggesting that the identified candidate genes are biologically relevant. A number of potential functional polymorphisms were also identified that showed DAE. We detected positive selection signatures in numerous genes that are consistent with the results from RNA-Seq study in E. camaldulensis. The genes and alleles identified in this study form a valuable resource for association and genomic selection studies.

Project description:Alpine goat phenotypes for quality components have been routinely recorded for many years and deposited in the Council on Dairy Cattle Breeding (CDCB) repository. The data collected were used to conduct an exploratory genome-wide association study (GWAS) from 72 female Alpine goats originating from locations throughout the U.S. Genotypes were identified with the Illumina Goat 50K single nucleotide polymorphisms (SNP) Beadchip. The analysis used a polygenic model where the dropping criteria was the Call Rate ≥ 0.95. The initial dataset was composed of ~ 60,000 rows of SNPs, 21 columns of phenotypic traits and composed of 53,384 scaffolds containing other informative data points used for genomic predictive power. Phenotypic association with the 50KBeadchip revealed 26,074 reads of candidate genes. These candidate genes segregated as separate novel SNPs and were identified as statistically significant regions for genome and chromosome level trait associations. Candidate genes associated differently for each of the following phenotypic traits: test day milk yield (13,469 candidate genes), test day protein yield (25,690 candidate genes), test day fat yield (25,690 candidate genes), percentage protein (25,690 candidate genes), percentage fat (25,690 candidate genes), and percentage lactose content (25,690 candidate genes). The outcome of this study supports elucidation of novel genes that are important for livestock species in association to key phenotypic traits. Validation towards the development of marker-based selection that provide precision breeding methods will thereby increase breeding value. Specific aims: 1) Improve on contributions to the phenotype repository, the Council on Dairy Cattle Breeding (CDCB) for milk quality traits that are economically important for goat production while developing a corresponding DNA repository for each of the animals with significant genotype-phenotype associations. 2) Develop genomic prediction tools and provide data for a better database for tools to predict phenotypic traits by initially using the high density Goat50KSNP BeadChip for the selection of more specific SNPs associated with select signatures (genes) for phenotypic traits in American Alpine goats. 3) To establish whether a low number of goat subjects (< 300 goats) will provide statistically significant (p < 0.05) predictive capabilities for desired breeding traits in American Alpine dairy goats.

			Action	DRS
	PRJEB38764_mergedfile.accessioned.vcf.gz	Vcf
	PRJEB38764_mergedfile.accessioned.vcf.gz.tbi	Vcf
	PRJEB38764_mergedfile.vcf.gz	Vcf
	PRJEB38764_mergedfile.vcf.gz.tbi	Vcf

Dataset Information

Whole genome re-sequencing reveals recent signatures of selection in three strains of farmed Nile tilapia (Oreochromis niloticus)

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets