Germline sequence variation within the ribosomal DNA is associated with human complex traits.

The ribosome is one of the core macromolecules in the cell. The ribosomal RNAs (rRNA), which are essential components of the ribosome, are coded by the multi-copy ribosomal DNA (rDNA). Despite its highly conserved function, the rDNA displays substantial variation within all species analysed to date. This variation comprises both inter-individual differences in total copy number (CN) as well as inter- and intragenomic sequence variation in the form of single nucleotide variants (SNV) and insertions/deletions (INDELs) across rDNA copies. Whether germline variation of rDNA sequence associates with phenotypic traits in humans is, to date, unknown. Here, using the UK Biobank whole genome sequencing data, we first derive a high confidence list of rDNA-associated SNVs and INDELs that we validate in multiple ways. Using this list, we show that specific rDNA variants associate with several human traits. In particular, traits associated with body size appear enriched in variants within the Expansion Segment 15L region in the 28S rRNA. The strength of these associations does not diminish when accounting for the total rDNA CN of each individual. Our work represents the first large-scale association analysis of human traits with germline sequence variation in the rDNA, a source of human complex trait-relevant genetic variation that has thus far been largely ignored.

Simple SummaryThe number of thoracic vertebrae (TN) and lumbar vertebrae (LN) in Dezhou donkey population is different, which leads to the difference of meat production and skin yield, and it is regulated by a few genes. Nuclear receptor subfamily 6 group A member 1 (NR6A1) was found to be related to livestock vertebra development, but it is not reported in donkeys yet. In this study, seven single nucleotide variants (SNVs) were detected in the NR6A1 gene, and polymorphism information content (PIC) was moderate to high in the population. Then we analyzed the relationship between these SNVs and body size trait, carcass traits and the number of thoracolumbar vertebrae (TLN). We found that locus were associated with different traits, and the mutation effect was not completely consistent. The results suggested that these genetic variations in the NR6A1 gene may play an important role in regulating the development of thoracolumbar vertebrae of Dezhou donkey. This paper provides important preliminary work for the study of multi thoracolumbar vertebrae in Dezhou donkeys.The number of thoracolumbar vertebrae is a quantitative trait positively correlated with the economic traits of livestock. More thoracolumbar vertebrae individuals could genetically be used to improve the livestock population, as more thoracolumbar vertebrae means a longer carcass, which could bring more meat production. Nuclear receptor subfamily 6 group A member 1 (NR6A1) is considered a strong candidate gene for effecting the number of vertebrae in livestock. The purposes of this study are as follows: (a) Analyzing the effect of TLN variation on body size and carcass traits of Dezhou donkey; (b) Studying the distribution of seven single nucleotide variants (SNVs) in NR6A1 gene of Dezhou donkey; (c) Exploring the relationship between latent SNVs and TLN, the body size and carcass traits. We examined the thoracic and lumbar vertebrae number and seven SNVs in NR6A1 gene of 455 Dezhou donkeys, and analyzed the relationships between them. Five types of thoracolumbar combinations (T17L5 (individual with 17 thoracic and five lumbar vertebrae) 2.4%, T18L5 75.8%, T19L5 1.1%, T17L6 11.9%, and T18L6 8.8%) of Dezhou donkeys were detected in this study. For one thoracolumbar vertebra added, the body length of Dezhou donkey increases by 3 cm and the carcass weight increases by 6 kg. Seven SNVs (g.18093100G > T, g.18094587G > T, g.18106043G > T, g.18108764G > T, g.18110615T > G, g.18112000C > T and g.18114954T > G) of the NR6A1 gene were found to have a significant association with the TLN, body size and carcass traits of Dezhou donkey (p < 0.05), respectively. For instance, g.18114954C > T is significantly associated with lumber vertebrae number, the total number of thoracolumbar, and carcass weight, and individuals with TT genotype had significantly larger value than CC genotype (p < 0.05). Using these 7SNVs, 16 different haplotypes were estimated. Compared to Hap3Hap3, individuals homozygous for Hap2Hap2 showed significantly longer length in one thoracic spine (STL), the total thoracic vertebrae and one thoracolumbar spine. Our study will not only extend the understanding of genetic variation in the NR6A1 gene of Dezhou donkey, but also provide useful information for marker assisted selection in donkey breeding program.

BackgroundBody weight and size are important economic traits in chickens. While many growth-related quantitative trait loci (QTLs) and candidate genes have been identified, further research is needed to confirm and characterize these findings. In this study, we investigate genetic and genomic markers associated with chicken body weight and size. This study provides new insights into potential markers for genomic selection and breeding strategies to improve meat production in chickens.MethodsWe performed whole-genome resequencing of and Wenshang Barred (WB) chickens (n = 596) and three additional breeds with varying body sizes (Recessive White (RW), WB, and Luxi Mini (LM) chickens; (n = 50)). We then used selective sweeps of mutations coupled with genome-wide association study (GWAS) to identify genomic markers associated with body weight and size.ResultsWe identified over 9.4 million high-quality single nucleotide polymorphisms (SNPs) among three chicken breeds/lines. Among these breeds, 287 protein-coding genes exhibited positive selection in the RW and WB populations, while 241 protein-coding genes showed positive selection in the LM and WB populations. Genomic heritability estimates were calculated for 26 body weight and size traits, including body weight, chest breadth, chest depth, thoracic horn, body oblique length, keel length, pelvic width, shank length, and shank circumference in the WB breed. The estimates ranged from 0.04 to 0.67. Our analysis also identified a total of 2,522 genome-wide significant SNPs, with 2,474 SNPs clustered around two genomic regions. The first region, located on chromosome 4 (7.41-7.64 Mb), was linked to body weight after ten weeks and body size traits. LCORL, LDB2, and PPARGC1A were identified as candidate genes in this region. The other region, located on chromosome 1 (170.46-171.53 Mb), was associated with body weight from four to eighteen weeks and body size traits. This region contained CAB39L and WDFY2 as candidate genes. Notably, LCORL, LDB2, and PPARGC1A showed highly selective signatures among the three breeds of chicken with varying body sizes.ConclusionOverall this study provides a comprehensive map of genomic variants associated with body weight and size in chickens. We propose two genomic regions, one on chromosome 1 and the other on chromosome 4, that could helpful for developing genome selection breeding strategies to enhance meat yield in chickens.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12864-024-10185-6.

BackgroundThe genotype information carried by Genome-wide association studies (GWAS) seems to have the potential to explain more of the ‘missing heritability’ of complex human phenotypes, given improved statistical approaches. Several lines of evidence support the involvement of microRNA (miRNA) and other non-coding RNA in complex human traits and diseases.We employed a novel, genetic annotation-informed enrichment method for GWAS that captures more polygenic effects than standard GWAS analysis, to investigate if miRNA-tagging Single Nucleotide Polymorphisms (SNPs) are enriched of associations with 15 complex human phenotypes. We then leveraged the enrichment using a conditional False Discovery Rate (condFDR) approach to assess any improvement in the detection of individual miRNA SNPs associated with the disorders.ResultsWe found SNPs tagging miRNA transcription regions to be significantly enriched of associations with 10 of 15 phenotypes. The enrichment remained significant after controlling for affiliation to other genomic categories, and was confirmed by replication. Albeit only nominally significant, enrichment was found also in miRNA binding sites for 10 phenotypes out of 15. Leveraging the enrichment in the condFDR framework, we observed a 2-4-fold increase in discovery of SNPs tagging miRNA regions.ConclusionsOur results suggest that miRNAs play an important role in the polygenic architecture of complex human disorders and traits, and therefore that miRNAs are a genomic category that can and should be used to improve gene discovery.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1513-5) contains supplementary material, which is available to authorized users.

Genetic variants introgressed into modern humans from Neanderthals tend to be depleted in their contribution to heritable trait variation relative to modern human variants consistent with the action of purifying selection.

Genetic variants introgressed into modern humans from Neanderthals tend to be depleted in their contribution to heritable trait variation relative to modern human variants consistent with the action of purifying selection.

Understanding the genetic and environmental factors affecting human complex genetic traits and diseases is a major challenge because of many interacting genes with individually small effects, whose expression is sensitive to the environment. Dissection of complex traits using the powerful genetic approaches available with Drosophila melanogaster has provided important lessons that should be considered when studying human complex traits. In Drosophila, large numbers of pleiotropic genes affect complex traits; quantitative trait locus alleles often have sex-, environment-, and genetic background-specific effects, and variants associated with different phenotypic are in noncoding as well as coding regions of candidate genes. Such insights, in conjunction with the strong evolutionary conservation of key genes and pathways between flies and humans, make Drosophila an excellent model system for elucidating the genetic mechanisms that affect clinically relevant human complex traits, such as alcohol dependence, sleep, and neurodegenerative diseases.

Genome-wide association studies (GWASs) have become the focus of the statistical analysis of complex traits in humans, successfully shedding light on several aspects of genetic architecture and biological aetiology. Single-nucleotide polymorphisms (SNPs) are usually modelled as having additive, cumulative and independent effects on the phenotype. Although evidently a useful approach, it is often argued that this is not a realistic biological model and that epistasis (that is, the statistical interaction between SNPs) should be included. The purpose of this Review is to summarize recent directions in methodology for detecting epistasis and to discuss evidence of the role of epistasis in human complex trait variation. We also discuss the relevance of epistasis in the context of GWASs and potential hazards in the interpretation of statistical interaction terms.

Multicopy nuclear ribosomal DNA (rDNA) genes have been used as markers for fungal identification for three decades. The rDNA sequences in a genome are thought to be homogeneous due to concerted evolution. However, intragenomic variation of rDNA sequences has recently been observed in many fungi, which may make fungal identification and species abundance estimation based on these loci problematic. Ceraceosorus is an enigmatic genus in the smut lineage Ustilaginomycotina for which very limited distribution data exist. Our previous research demonstrated intragenomic variation in the internal transcribed spacer (ITS1-5.8S-ITS2) region of two Ceraceosorus species. In this study, we described the fourth known species of Ceraceosorus, C. americanus, isolated from an asymptomatic rosemary leaf collected in Louisiana, USA. This is the first report of this genus in the Americas. We then selected all four known Ceraceosorus species, plus exemplar smut fungi representing all major lineages of subphylum Ustilaginomycotina, to examine sequence heterogeneity in three regions of the rDNA repeat (partial 18S, ITS, and partial 28S regions). Three methods were used: PCR-cloning-Sanger sequencing, targeted amplicon high-throughput sequencing, and whole-genome shotgun high-throughput sequencing. Our results show that Ceraceosorus is the only sampled fungal genus in Ustilaginomycotina with significant intragenomic variation at the ITS, with up to 25 nucleotide variant sites in the ITS1–5.8S–ITS2 region and 2.6% divergence among analyzed ITS haplotypes. We found many conflicting patterns across the three detection methods, with up to 27 conflicting variant sites recorded from a single individual. At least 40% of the conflicting patterns are possibly due to PCR-cloning-sequencing errors, as the corresponding variant sites were not observed in the other detection methods. Based on our data and the literature, we evaluated the characteristics and advantages/disadvantages of each detection method. Finally, a model for how intragenomic variation in the rDNA copies within a genome may arise is presented.Supplementary InformationThe online version contains supplementary material available at 10.1186/s43008-024-00172-7.

BackgroundDue to the advancement in high throughput technology, single nucleotide polymorphism (SNP) is routinely being incorporated along with phenotypic information into genetic evaluation. However, this approach often cannot achieve high accuracy for some complex traits. It is possible that SNP markers are not sufficient to predict these traits due to the missing heritability caused by other genetic variations such as microsatellite and copy number variation (CNV), which have been shown to affect disease and complex traits in humans and other species.ResultsIn this study, CNVs were included in a SNP based genomic selection framework. A Nellore cattle dataset consisting of 2230 animals genotyped on BovineHD SNP array was used, and 9 weight and carcass traits were analyzed. A total of six models were implemented and compared based on their prediction accuracy. For comparison, three models including only SNPs were implemented: 1) BayesA model, 2) Bayesian mixture model (BayesB), and 3) a GBLUP model without polygenic effects. The other three models incorporating both SNP and CNV included 4) a Bayesian model similar to BayesA (BayesA+CNV), 5) a Bayesian mixture model (BayesB+CNV), and 6) GBLUP with CNVs modeled as a covariable (GBLUP+CNV). Prediction accuracies were assessed based on Pearson’s correlation between de-regressed EBVs (dEBVs) and direct genomic values (DGVs) in the validation dataset. For BayesA, BayesB and GBLUP, accuracy ranged from 0.12 to 0.62 across the nine traits. A minimal increase in prediction accuracy for some traits was noticed when including CNVs in the model (BayesA+CNV, BayesB+CNV, GBLUP+CNV).ConclusionsThis study presents the first genomic prediction study integrating CNVs and SNPs in livestock. Combining CNV and SNP marker information proved to be beneficial for genomic prediction of some traits in Nellore cattle.

Integrative analysis of liver-specific non-coding regulatory SNPs associated with the risk of coronary artery disease

With the availability of high-density maps of single nucleotide polymorphism (SNP)markers, population-based linkage disequilibrium (LD) mapping or association studies are widely used to identify genetic variants that influence human complex trait. The simplest LD method is to use an excellent measure to quantify LD between the trait locus and the marker locus linked with it. Here, we review LD measures for fine-scale mapping of human complex trait locus. Key words: Complex trait ; Fine-scale mapping ; Linkage disequilibrium ;

Copy number variation (CNV) represents an important source of genetic variation complementary to single nucleotide polymorphism (SNP) and provides valuable insights into the genetic architecture of complex traits in humans and livestock animals. However, many factors affect CNV detection, including sample size. Previous studies in Holstein cattle have only used hundreds of individuals. Therefore, in the present study, CNVs were identified from high-density genotype array data in 3,529 Holstein cows from 16 herds located in 7 U.S. states. CNVs were derived from 546,802 autosomal SNP markers with MAF &amp;gt; 0.05 and call rate &amp;gt; 0.90 using the intensity signals at each SNP position in a hidden Markov model implemented in PennCNV software. The log R ratio (LRR) values were corrected based on the guanine-cytosine content in the genomic regions located 500 kb upstream and downstream of each marker. After detection, CNVs presenting LRR ≤ 0.30, B allele frequency drift &amp;lt; 0.01, waviness factor ≤ 0.05, number of SNPs &amp;gt; 10 and length &amp;gt; 1 kb were merged into CNV regions (CNVR) using CNVRanger. A total of 1,881 non-redundant CNV events spanning the entire genome were identified in 1,771 cows, with a mean of 10 CNVs per individual and ranging from 1 to 27. The highest percentage of CNV calls was located on BTA7 (16%), while only 9 CNVs were identified on BTA9. The CNV calls were grouped into 685 CNVRs covering 3.07% of the bovine autosomal genome. The number of CNVRs with copy loss and gain were 356 and 310, and both types were observed in 19 regions. The chromosomal distribution of CNVR revealed that BTA7 harbors 38 CNVRs, while only 2 were detected on BTA28. These results will support further research on the contribution of CNVs and CNVRs to the genetic architecture of complex traits in Holstein cattle.

Investigators conducting studies of the molecular genetics of complex traits in humans often need rationally to select a set of single nucleotide polymorphisms (SNPs) from the hundreds or thousands available for a candidate gene. Accomplishing this requires integration of genomic data from distributed databases and is both time-consuming and error-prone. We developed the TAMAL (Technology And Money Are Limiting) web site to help identify promising SNPs for further investigation. For a given list of genes, TAMAL identifies SNPs that meet user-specified criteria (e.g. haplotype tagging SNPs or SNP predicted to lead to amino acid changes) from current versions of online resources (i.e. HapMap, Perlegen, Affymetrix, dbSNP and the UCSC genome browser). TAMAL is a platform independent web-based application available free of charge at http://neoref.ils.unc.edu/tamal. http://neoref.ils.unc.edu/tamal/.

Contrasting evolutionary patterns of 28S and ITS rRNA genes reveal high intragenomic variation in Cephalenchus (Nematoda): Implications for species delimitation