Quantitative Trait Loci Database Research Articles

Causal relationship between key genes and metabolic dysfunction-associated fatty liver disease risk mediated by immune cells: A Mendelian randomization and mediation analysis.

Non-invasive diagnostics for metabolic dysfunction-associated fatty liver disease (MAFLD) remain challenging. We aimed to identify novel key genes as non-invasive biomarkers for MAFLD, elucidate causal relationships between biomarkers and MAFLD and determine the role of immune cells as potential mediators. Utilizing published transcriptome data of patients with biopsy-proven MAFLD, we applied linear models for microarray data, least absolute shrinkage and selector operation (LASSO) regressions and receiver operating characteristic (ROC) curve analyses to identify and validate biomarkers for MAFLD. Using the expression quantitative trait loci database and a cohort of 778 614 Europeans, we used Mendelian randomization to analyse the causal relationships between key biomarkers and MAFLD. Additionally, mediation analysis was performed to examine the involvement of 731 immunophenotypes in these relationships. We identified 31 differentially expressed genes, and LASSO regression showed three hub genes, IGFBP2, PEG10, and P4HA1, with area under the receiver operating characteristic (AUROC) curve of 0.807, 0.772 and 0.791, respectively, for identifying MAFLD. The model of these three genes had an AUROC of 0.959 and 0.800 in the development and validation data sets, respectively. This model was also validated using serum-based enzyme-linked immunosorbent assay data from MAFLD patients and control subjects (AUROC: 0.819, 95% confidence interval: 0.736-0.902). PEG10 was associated with an increased MAFLD risk (odds ratio = 1.106, p = 0.032) via inverse variance-weighted analysis, and about 30% of this risk was mediated by the percentage of CD11c + CD62L- monocytes. The MAFLD panels have good diagnostic accuracy, and the causal link between PEG10 and MAFLD was mediated by the percentage of CD11c + CD62L- monocytes.

Genome-wide association study for milk yield, frame, and udder conformation traits of Gir dairy cattle

Genome-wide association studies (GWAS) are employed to identify genomic regions and candidate genes associated with several traits. The aim of this study was to perform a GWAS to identify causative variants and genes associated with milk yield, frame, and udder conformation traits in Gir dairy cattle. Body conformation traits were classified as "frame," and "udder" traits for this study. After genotyping imputation and quality control 42,105 polymorphisms were available for analyses and 24,489 cows with pedigree information had phenotypes. First, P-value was calculated based on the variance of the prediction error of the SNP-effects on the first iteration. After that, 2 more iterations were performed to carry out the weighted single-step genome-wide association methodology, performed using genomic moving windows defined based on linkage disequilibrium. The significant SNPs and top 10 windows explaining the highest percentage of additive genetic variance were selected and used for QTL and gene annotation. The variants identified in our work overlapped with QTLs from the animal QTL database on chromosomes 1 to 23, except for chromosome 4. The Gir breed is less studied than the Holstein breed and as such the animal QTL database is biased to Holstein results. Hence it is noteworthy that our GWAS had similarities with previously described QTLs. These previously known QTLs were related to milk yield, body height, rump angle, udder width, and udder depth. In total, 5 genes were annotated. Of these genes, FAM13A and CMSS1 had been previously related to bone and carcass weight in cattle.

Identification of genes associated with color characteristics of meat and fat tissue of aberdeen-angus cattle

Currently, full genome association studies and identification of candidate genes for economically useful traits in farm animals are topical, scientifically sound and practice-oriented, and fulfill one of the objectives of the Strategy for Scientific and Technical Development of the Russian Federation. This article presents the results of GWAS on color spectral values of meat and fat tissue of Aberdeen-Angus cattle, known for its meat characteristics of high grade. The animals were genotyped on high-density BovineHD Genotyping BeadChip chips containing ≈53,000 SNPs. After quality control, 39,928 remained. By analysis and structural annotation, 25 and 26 candidate genes for meat and fat color were identified, respectively. According to functional annotation, the genes were categorized into 6 groups: nervous system functions, organ development, vascular, joints, metabolic processes and biosynthesis, cellular processes, muscle, tissue and bone, reproduction and embryonic development. The obtained genes were checked through the Animal QTL database, as a result of which 13 genes were confirmed, of which 3 were localized SNPs, in connection with which the LRP2, SCIN and ANTXR1 genes have advantages for their further application in the molecular diagnostics of cattle not only meat, but also dairy productivity.

Identifying potential drug targets for varicose veins through integration of GWAS and eQTL summary data.

Varicose veins (VV) are a common chronic venous disease that is influenced by multiple factors. It affects the quality of life of patients and imposes a huge economic burden on the healthcare system. This study aimed to use integrated analysis methods, including Mendelian randomization analysis, to identify potential pathogenic genes and drug targets for VV treatment. This study conducted Summary-data-based Mendelian Randomization (SMR) analysis and colocalization analysis on data collected from genome-wide association studies and cis-expression quantitative trait loci databases. Only genes with PP.H4 > 0.7 in colocalization were chosen from the significant SMR results. After the above analysis, we screened 12 genes and performed Mendelian Randomization (MR) analysis on them. After sensitivity analysis, we identified four genes with potential causal relationships with VV. Finally, we used transcriptome-wide association studies and The Drug-Gene Interaction Database data to identify and screen the remaining genes and identified four drug targets for the treatment of VV. We identified four genes significantly associated with VV, namely, KRTAP5-AS1 [Odds ratio (OR) = 1.08, 95% Confidence interval (CI): 1.05-1.11, p = 1.42e-10] and PLEKHA5 (OR = 1.13, 95% CI: 1.06-1.20, p = 6.90e-5), CBWD1 (OR = 1.05, 95% CI: 1.01-1.11, p = 1.42e-2) and CRIM1 (OR = 0.87, 95% CI: 0.81-0.95, p = 3.67e-3). Increased expression of three genes, namely, KRTAP5-AS1, PLEKHA5, and CBWD1, was associated with increased risk of the disease, and increased expression of CRIM1 was associated with decreased risk of the disease. These four genes could be targeted for VV therapy. We identified four potential causal proteins for varicose veins with MR. A comprehensive analysis indicated that KRTAP5-AS1, PLEKHA5, CBWD1, and CRIM1 might be potential drug targets for varicose veins.

Identification of candidate genes associated with growth and development of sheep from a crossbred population using genome-wide association studies

The article presents the results of a search for genome-wide associations with phenotypic traits characterizing the growth and development of sheep from a crossbred population obtained from crossing Romanov sheep and F1 hybrid rams (Romanov sheep x Katahdin). The phenotype database included ten body measurements (withers height, sacral height, back height, chest depth, chest width, ischial tuberosity width, body length, oblique body length, chest girth, pastern girth) recorded at the age of 6 days, 3, 6 and 9 months. Genotyping of sheep was carried out using high-density DNA chips containing about 600,000 SNP markers. Genome-wide association studies (GWAS) were performed using regression analysis in the STATISTICA 10 program. The search for candidate genes localized in the SNP region was performed using Ensembl genome browser 110. There was carried out an analysis of the matches of the identified SNPs with known quantitative trait loci (QTLs) described in the Sheep Quantitative Trait Locus Database. There were found SNPs that were significantly associated with the studied phenotypic traits overlapped with the QTLs, among which the most common categories were “Body weight (slaughter)”, “Muscle weight in carcass”, “Body weight (live)” and “Bone weight in carcass”. There has been established that SNPs significantly associated with exterior traits were localized within or in the immediate vicinity of 64 genes. There were found potential candidates regulating the growth of muscle (FOXO3, PRKAG3, MYOZ2, and ANKRD1) and cartilage tissues FGF12) and involved in metabolic processes, which were critical for the growth of lambs (CLDN, ALB, and MRC1). Along with the known in sheep functional candidates (CAST and SCD5) , there were identified genes that were not previously described in sheep, but regulated growth and development processes in other livestock species including genes RAB28, PRKAG3 and FOXO3. The identified SNPs can be recommended for inclusion in marker-guided selection programs in sheep breeding.

Exome-Wide Sequencing Study Identified Genetic Variants Associated With Sarcopenic Obesity.

Sarcopenic obesity (SO) is an age-related disease characterized by the coexistence of excessive adiposity and low muscle mass or function. Although obesity and sarcopenia are heritable conditions, the genetic determinants of SO have not been fully understood. We conducted a large-scale exome-wide association analysis of SO in a sequenced sample of 2887 cases and 113284 controls and an imputed sample of 4003 cases and 161990 controls in the UK Biobank cohort. Single-variant association analysis identified one locus 1q41 (lead SNP rs1417066, LYPLAL1-AS1, odds ratio [OR] = 1.15, 95% confidence interval [CI] = [1.11-1.19], p = 1.75 × 10-14) that was significantly associated with SO at the exome-wide significance level (p < 1 × 10-8). Colocalization analysis in the Genotype-Tissue Expression expression quantitative trait locus database showed that LYPLAL1-AS1 was colocalized with SO in multiple musculoskeletal-related tissues. Gene-based burden test of rare loss-of-function variants identified 5 genes at the gene-wise significance level (p < 4.3 × 10-6): PDE3B (OR = 2.48, p = 1.10 × 10-6), MYOZ3 (OR = 25.49, p = 1.41 × 10-7), SLC15A3 (OR = 4.75, p = 6.82 × 10-7), RNF130 (OR = 25.83, p = 4.07 × 10-6), and TNK2 (OR = 4.25, p = 8.75 × 10-8). Overall, our study uncovered the genetic effects of both common and rare variants on SO susceptibility, expanded existing knowledge of the genetic architecture of SO, and improved understanding of the genetic mechanisms underlying SO.

135 Gene Variants in Bola-Dmb, DECR1, Fasn and SREBF1 Associated with Conceptus Death on Day 16 of Pregnancy in Holstein Cows

Abstract Investigating the influences of single nucleotide polymorphisms (SNP) associated with conceptus death (CD) on day 16 of pregnancy could distinguish cows who have inferior value for fertility traits. We hypothesized that CD is associated with SNP genotypes that disrupt maternal recognition and lead to early pregnancy loss. RNA sequences from Holstein cow pregnancies (n = 15) with normal conceptuses (Norm) or CD were subjected to SNP discovery via Qiagen CLC Genomics Workbench. Selected SNP were based on previous fertility studies, differentially expressed genes within pregnancy development analyses and proximity to SNP associated with fertility traits in the Cattle QTL Database. A second cohort of Holstein cows (n = 500) was used to conduct a validation and genotype to phenotype analysis of candidate SNP (cSNP) via DNA from blood samples and farm records. PLINK software was used to remove cows (n = 34) missing more than &amp;gt;20% cSNP and remove cSNP with monomorphic alleles, minor allele frequency (MAF) &amp;lt; 10% and not in Hardy-Weinberg Equilibrium (&amp;gt;1e-15). The GLM-one way ANOVA was used for all statistical models in SAS. Statistically significant models (P &amp;lt;0.05) were further analyzed for LSMEANS, Bonferroni adjustment of P-values, additive allele effect and predicted effect of amino acid (aa) change on protein function via SIFT analyses tool in the Ensembl variant table (scoring 0-1.0; &amp;lt; 0.05 being significant). Previously, we identified 69 cSNP on the RNA sequences of Norm or CD pregnancies from the initial group of Holstein cows and in proximity to &amp;gt;1 SNP associated with fertility traits from the Cattle QTL database. Quality control measures in PLINK reduced the number of Holstein cows in the second cohort to 466 and identified 4 cSNP associated with non-binary reproductive traits. Herein, we report an additional 4 cSNP discovered and validated with binary reproductive traits. The cSNP within genes were associated with the following roles: BOLA-DMB (antigen loading in the immune system), DECR1 (lipid metabolism), FASN (reconstitution of body reserves during pregnancy) and SREBF1 (synthesis of fatty acids). Cows with T allele, in BOLA-DMB and SREBF1, were less likely (P &amp;lt; 0.05) to become pregnant &amp;lt;150 days in milk (DIM). For DECR1 and FASN, cows were less likely (P &amp;lt; 0.05) to become pregnant at 1st artificial insemination with C or A allele, respectively. Only the cSNP in SREBF1 had both an additive allele effect and a predicted effect of aa change on protein function. When cows had C allele, in the SREBF1 cSNP, there was 6% greater (P &amp;lt; 0.01) probability of becoming pregnant &amp;lt;150 DIM. While SIFT revealed the cSNP in SREBF1 have a predicted significant effect with a score of 0.03 for the aa change of proline/leucine. The reported cSNP, specifically those influenced by CD, add valuable information for the development of improved genetic tools for the dairy industry. USDA-NIFA#2019-07133.

Transcriptome analysis of the Bactrian camel (Camelus bactrianus) reveals candidate genes affecting milk production traits

BackgroundMilk production traits are complex traits with vital economic importance in the camel industry. However, the genetic mechanisms regulating milk production traits in camels remain poorly understood. Therefore, we aimed to identify candidate genes and metabolic pathways that affect milk production traits in Bactrian camels.MethodsWe classified camels (fourth parity) as low- or high-yield, examined pregnant camels using B-mode ultrasonography, observed the microscopic changes in the mammary gland using hematoxylin and eosin (HE) staining, and used RNA sequencing to identify differentially expressed genes (DEGs) and pathways.ResultsThe average standard milk yield over the 300 days during parity was recorded as 470.18 ± 9.75 and 978.34 ± 3.80 kg in low- and high-performance camels, respectively. Nine female Junggar Bactrian camels were subjected to transcriptome sequencing, and 609 and 393 DEGs were identified in the low-yield vs. high-yield (WDL vs. WGH) and pregnancy versus colostrum period (RSQ vs. CRQ) comparison groups, respectively. The DEGs were compared with genes associated with milk production traits in the Animal Quantitative Trait Loci database and in Alashan Bactrian camels, and 65 and 46 overlapping candidate genes were obtained, respectively. Functional enrichment and protein–protein interaction network analyses of the DEGs and candidate genes were conducted. After comparing our results with those of other livestock studies, we identified 16 signaling pathways and 27 core candidate genes associated with maternal parturition, estrogen regulation, initiation of lactation, and milk production traits. The pathways suggest that emerged milk production involves the regulation of multiple complex metabolic and cellular developmental processes in camels. Finally, the RNA sequencing results were validated using quantitative real-time PCR; the 15 selected genes exhibited consistent expression changes.ConclusionsThis study identified DEGs and metabolic pathways affecting maternal parturition and milk production traits. The results provides a theoretical foundation for further research on the molecular mechanism of genes related to milk production traits in camels. Furthermore, these findings will help improve breeding strategies to achieve the desired milk yield in camels.Graphical

Prediction of some milk production traits using udder and teat measurements with a spotlight on their genetic background in Friesian cows

The aggregate udder shape (Bowl, Round, Cup), udder measurements (udder width, UW, udder front depth, UFD, udder rear depth, URD, udder levelness, ULV, udder heights, UH) and teat measurements (teat diameters, TD, front teat length, FTL, rear teat length, RTL, distance between front teats, DFT and distance between rear teats, DRT) were measured on 1300 Friesian cows located in a commercial farm under subtropical conditions (Egypt) to appraise udder and teats status and to evaluate the possible relationships with some milk production characteristics in conjunction with udder shape, age at first calving, sire and inbreeding effects on udder morphological traits and milk production ability. For such an available sample size, parity had affected (P < 0.01) UFD, TD, FTL and RTL. In addition, udder shape affected (P < 0.01) UW, UFD, URD, ULV and DFT. None of the other studied factors affected milk production traits. The bowl udder shape (P < 0.01) yielded a high total milk yield (3267.19 kg), adjusted milk yield (2443.01 kg) and lactation length (480.70 d) compared to other udder shapes. The genetic correlations of UW with total milk yield and persistency were strongly positive (0.86 and 0.93, respectively). However, strong negative genetic correlations were found between UW with peak milk yield and lactation length (− 0.92 and − 0.80, respectively), between RTL with peak milk yield (− 0.92) and DRT with persistency (− 0.79). As found from the stepwise multiple regression, UW and URD can be used as good indicators for predicting milk yield and lactation length. Additionally, this study spotlights the genetic background of udder characteristics based on reliable studies and the QTL database for cattle as a first step toward applying this knowledge side by side with phenotypic traits to improve the productivity of the Holstein breed under subtropical conditions.

Decreased CNNM2 expression in prefrontal cortex affects sensorimotor gating function, cognition, dendritic spine morphogenesis and risk of schizophrenia.

Genome-wide association studies (GWASs) have reported multiple single nucleotide polymorphisms (SNPs) associated with schizophrenia, yet the underlying molecular mechanisms are largely unknown. In this study, we aimed to identify schizophrenia relevant genes showing alterations in mRNA and protein expression associated with risk SNPs at the 10q24.32-33 GWAS locus. We carried out the quantitative trait loci (QTL) and summary data-based Mendelian randomization (SMR) analyses, using the PsychENCODE dorsolateral prefrontal cortex (DLPFC) expression QTL (eQTL) database, as well as the ROSMAP and Banner DLPFC protein QTL (pQTL) datasets. The gene CNNM2 (encoding a magnesium transporter) at 10q24.32-33 was identified to be a robust schizophrenia risk gene, and was highly expressed in human neurons according to single cell RNA-seq (scRNA-seq) data. We further revealed that reduced Cnnm2 in the mPFC of mice led to impaired cognition and compromised sensorimotor gating function, and decreased Cnnm2 in primary cortical neurons altered dendritic spine morphogenesis, confirming the link between CNNM2 and endophenotypes of schizophrenia. Proteomics analyses showed that reduced Cnnm2 level changed expression of proteins associated with neuronal structure and function. Together, these results identify a robust gene in the pathogenesis of schizophrenia.

Molecular regulatory mechanism of key LncRNAs in subclinical mastitic cows with folic acid supplementation

BackgroundFolic acid is a water-soluble B vitamin (B9), which is closely related to the body’s immune and other metabolic pathways. The folic acid synthesized by rumen microbes has been unable to meet the needs of high-yielding dairy cows. The incidence rate of subclinical mastitis in dairy herds worldwide ranged between 25%~65% with no obvious symptoms, but it significantly causes a decrease in lactation and milk quality. Therefore, this study aims at exploring the effects of folic acid supplementation on the expression profile of lncRNAs, exploring the molecular mechanism by which lncRNAs regulate immunity in subclinical mastitic dairy cows.ResultsThe analysis identified a total of 4384 lncRNA transcripts. Subsequently, differentially expressed lncRNAs in the comparison of two groups (SF vs. SC, HF vs. HC) were identified to be 84 and 55 respectively. Furthermore, the weighted gene co-expression network analysis (WGCNA) and the KEGG enrichment analysis result showed that folic acid supplementation affects inflammation and immune response-related pathways. The two groups have few pathways in common. One important lncRNA MSTRG.11108.1 and its target genes (ICAM1, CCL3, CCL4, etc.) were involved in immune-related pathways. Finally, through integrated analysis of lncRNAs with GWAS data and animal QTL database, we found that differential lncRNA and its target genes could be significantly enriched in SNPs and QTLs related to somatic cell count (SCC) and mastitis, such as MSTRG.11108.1 and its target gene ICAM1, CXCL3, GRO1.ConclusionsFor subclinical mastitic cows, folic acid supplementation can significantly affect the expression of immune-related pathway genes such as ICAM1 by regulating lncRNAs MSTRG.11108.1, thereby affecting related immune phenotypes. Our findings laid a ground foundation for theoretical and practical application for feeding folic acid supplementation in subclinical mastitic cows.

A combinatorial approach implementing new database structures to facilitate practical data curation management of QTL, association, correlation and heritability data on trait variants

A precise description of traits is essential in genetics and genomics studies to facilitate comparative genetics and meta-analyses. It is an ongoing challenge in research and production environments to unambiguously and consistently compare traits of interest from data collected under various conditions. Despite previous efforts to standardize trait nomenclature, it remains a challenge to fully and accurately capture trait nomenclature granularity in a way that ensures long-term data sustainability in terms of the data curation processes, data management logistics and the ability to make meaningful comparisons across studies. In the Animal Quantitative Trait Loci Database and the Animal Trait Correlation Database, we have recently introduced a new method to extend livestock trait ontologies by using trait modifiers and qualifiers to define traits that differ slightly in how they are measured, examined or combined with other traits or factors. Here, we describe the implementation of a system in which the extended trait data, with modifiers, are managed at the experiment level as 'trait variants'. This has helped us to streamline the management and curation of such trait information in our database environment. Database URL https://www.animalgenome.org/PGNET/.

EaQTLdb: An atlas of enhancer activity quantitative trait loci across cancer types.

Enhancers are key regulatory elements that exert crucial roles in diverse biological processes, including tumorigenesis and cancer development. Active enhancers could produce transcripts termed enhancer RNAs (eRNAs), which could be used as an index of enhancer activity. Here, we present a versatile data portal, enhancer activity quantitative trait loci database (eaQTLdb; http://www.bioailab.com:3838/eaQTLdb), for exploring the effects of genetic variants on enhancer activity and prioritizing candidate variants across different cancer types. By leveraging the accumulated multiomics data, we systematically identified genetic variants which influence enhancer activity in different cancer types, termed as eaQTLs. We have linked the eaQTLs to hallmarks of cancer and patients' overall survival to illustrate their potential biological roles in cancer development and progression. Notably, eaQTLs associated with the infiltration abundance of 24 different immune cell types were identified and incorporated into eaQTLdb. In addition, we applied colocalization analyses to examine 59 complex diseases and traits to identify eaQTLs colocalized with diseases/traits GWAS signals. Overall, eaQTLdb, incorporating a rich resource for exploration of eaQTLs in different cancer types, will not only benefit users in prioritizing candidate genetic variants and enhancers, but also help researchers decipher the roles of eaQTLs in the dysregulated pathways of cancer and tumor immune microenvironment, opening new diagnostic and therapeutic avenues in precise medicine.

Alternative splicing of PSMD13 mediated by genetic variants is significantly associated with endometrial cancer risk.

Accumulating evidence has shown that aberrant alternative splicing events are closely associated with the onset and development of cancer. However, whether genetic variants-associated alternative splicing is linked to risk of endometrial cancer remains largely uncertain. We identified single nucleotide polymorphisms (SNPs) locates in the splicing number trait locus (sQTL) of endometrial cancer using the CancerSplicing QTL database. In parallel with bioinformatics analysis, we conducted a case-control study comprising 2,000 cases and 2,013 controls to assess the association between identified SNP which possesses mRNA splicing function and endometrial cancer susceptibility. Furthermore, we used the Kaplan-Meier Plotter, The Human Protein Atlas, SPNR, and Spliceman2 databases for sQTL and differential gene expression analyses to identify the genetic variant which most potentially influence the risk of endometrial cancer through alternative splicing to reveal the potential mechanism by which candidate SNPs regulate the risk of endometrial cancer. The results indicated that SNP rs7128029 A<G was significantly associated with an increased risk of endometrial cancer (odds ratio=1.384; 95% confidence interval=1.038-1.964). Moreover, the carcinogenic effect of SNP rs7128029 A<G was consistently revealed by propensity matching analysis, an additive model, and a dominant model. Importantly, sQTL analysis showed that SNP rs7128029 could affect the transcriptional modification of PSMD13 via regulating the exon skipping of PSMD13. When the rs7128029 allele was mutated from A to G, the expression of exon 2 of PSMD13 was markedly lower (p<0.001). Furthermore, compared with participants who had higher PSMD13 expression, those who had lower PSMD13 expression had shorter survival times. These findings suggest that SNP rs7128029-mediated alternative splicing events in PSMD13 are associated with endometrial cancer risk and may be a potential early screening biomarker for endometrial cancer-susceptible populations.

WheatQTLdb V2.0: a supplement to the database for wheat QTL.

We recently developed a database for hexaploid wheat QTL (WheatQTLdb; www.wheatqtldb.net), which included 11,552 QTL affecting various traits of economic importance. However, that database did not include valuable QTL from other wheat species and/or progenitors of hexaploidwheat. Therefore, an updated and improved version of wheat QTL database (WheatQTLdb V2.0) was developed, which now includes information on hexaploid wheat (Triticum aestivum) and the following seven other related species: T. durum, T. turgidum, T. dicoccoides, T. dicoccum, T. monococcum, T. boeoticum, and Aegilops tauschii. WheatQTLdb V2.0 includes a much-improved list of QTL, including 27,518 main effect QTL, 202 epistatic QTL, and 1321 metaQTL. This newly released WheatQTLdb V2.0 also has additional valuable options to search and choose the QTL, category-wise, and trait-wise data for their use inresearch or breeding programs.

Genome-wide search for associations with QTL of beef productivity in cattle of Kazakh White-headed and Auliekol breeds

Genomic breeding is a very young field of science, which has quickly become the most modern methodology in the world for selecting breeding schemes for farm animals, especially cattle. The high efficiency of genomic selection is due to the identification at an early age of genetically elite animals based on information about the state of single-nucleotide polymorphisms of DNA genome. With the help of increased accuracy of selection at a young age, generation intervals can be shortened and genetic progress in animal husbandry can be signifi cantly accelerated. The purpose of the work was a genome-wide search for associations with QTL of beef productivity in cattle of Kazakh Whiteheaded and Auliekol breeds. The results of the genome-wide search for SNP associations of beef cattle of Kazakh White-headed and Auliekol breeds with QTL responsible for traits of beef productivity have been reflected in the paper. SNP typing of animals was carried out using a GeneSeek GGP Bovine 150K biochip with an average coverage density of 150 000 SNP (Illumina Inc., USA). The genome-wide association study was performed using Plink. Polymorphic sites were annotated with rs identifiers using the SNP ChimpV3 database. Using rs identifiers, polymorphic sites were annotated using the Ensembl database to obtain information about the type of mutation, localization in the gene, potential effect, etc. Identifiers rs were also used to annotate SNPs using QTL using the cattle QTL database. It is shown that in both breeds at a significance level of 0,00001 and 0,001, QTL are detected that are not described in the QTL Cattle DB databases. The analysis of the distribution of significant SNPs by chromosomes was given.

Regional heritability mapping and genome‐wide association identify loci for rice traits

AbstractAlthough genome‐wide association studies (GWAS) based on single‐marker analysis have been widely applied in plant breeding programs, the effectivity of the methodology is still undermined by high false‐positive rates and the limited power to detect associations. Bayesian methods, which estimate marker effects simultaneously, proved to be efficient, indicating genes with important effects. Regional heritability mapping (RHM), on the other hand, determines the genome region (group of markers) associated with the phenotype, considers population structure and familial relatedness, and is more powerful to detect quantitative trait loci (QTL) and reduced false‐positive rates than single‐marker methodologies. A single‐marker mixed model (SM‐MM) Bayesian approach and RHM were used for 11 traits in 413 rice (Oryza sativa L.) accessions genotyped for 44,100 single‐nucleotide polymorphism (SNP) markers. Using RHM in regions of 0.21 and 0.69 Mb, respectively, detected five and seven associated regions with 163 and 569 SNPs. Bayesian method with regions of 0.21 and 0.69 Mb detected regions for all traits, whereas SM‐MM detected four single SNP–trait associations. For the 11 traits, RHM explained approximately 25–40 and 25–76% using genome regions of 0.21 and 0.69 Mb, respectively, and SM‐MM using single markers explained 1–7% of the genomic heritability. Regional heritability mapping was more effective than SM‐MM in capturing major proportions of genomic heritability. The regions found in this study were within or close to the QTL noted in the Q‐TARO and Gramene QTL databases.

Investigation of genetic diversity and selection signatures in Czech cattle genetic resources revealed by genome-wide analysis

Preserving genetic diversity and preventing its loss in livestock populations is essential for further sustainable development and breeding. The main purposes of this study were to estimate the current status of genetic diversity of the approved genetic resources (GRs) in indigenous Czech Red (CR) and Czech Spotted (CS) cattle and assess the impact of diversifying selection on two CR subpopulations based on genome-wide single-nucleotide polymorphism (SNP) analysis. The main within-breed genetic diversity indicators of CR and CS (share of polymorphic SNPs, observed heterozygosity, and minor allele frequency) are intermediate or high, and the inbreeding coefficients are below zero. The small degree of genetic differentiation (maximum FST = 0.088) suggests a low divergence between the breeds and populations. Principal component analysis (PCA) shows a less genetic variation in CS and, in contrast, larger variability within and genetic similarity between the two analysed CR subpopulations. Putative selection signatures based on FST revealed that the ten most differentiated genomic regions between the two CR subpopulations were located on chromosomes 1, 3, 11, 12, 18, and 22, encompassing only 7 Mb of sequence and 69 protein-coding genes. Selection differences are low and probably attributed to the influence of the CS genome exploited in CR cattle revitalization. The majority of the candidate genes are involved in the immune system response, fertility, and neuronal and brain function. Gene Ontology enrichment and quantitative trait loci database analyses show that the genes act in milk and meat production and reproductive performance. These findings expand our knowledge about the genomic diversity of endangered Czech indigenous cattle and provide helpful information to organize their breeding programmes and preservation.

A single-nucleotide-polymorphism in the 5'-flanking region of MSX1 gene as a predictive marker candidate for platinum-based therapy of esophageal carcinoma.

Background:Platinum derivatives are important treatment options for patients with esophageal carcinoma (EC), and a predictive marker for platinum-based therapy is needed for precision medicine.Patients and methods:This study contained two cohorts consisting of EC patients treated using platinum-based chemoradiation therapy (CRT) as the first-line and another external cohort of nationwide clinicogenomic data from the BioBank Japan (BBJ).Results:Genome-wide association study (GWAS) of therapeutic outcomes, refractory disease or not, following platinum-based CRT as first-line in 94 patients in the first cohort suggested the association of 89 SNPs using p < 0.0001. The top 10 SNPs selected from each chromosomal region by odds ratio were evaluated for progression-free survival (PFS) and overall survival (OS) hazard ratios in the first cohort, resulting in four candidates (p < 0.0025). The four selected candidates were re-evaluated in another cohort of 24 EC patients, which included patients prospectively enrolled in this study to fulfill the sample size statistically suggested by the results of the first cohort, and of the four, only rs3815544 was replicated (p < 0.0125). Furthermore, this candidate genotype of rs3815544 proceeded to the re-evaluation study in an external cohort consisting of EC patients treated with platinum derivatives and/or by radiation therapy as the first-line treatment in BBJ, which confirmed that the alternative allele (G) of rs3815544 was statistically associated with non-response (SD or PD) to platinum-based therapy in EC patients (odds ratio = 1.801, p = 0.048). The methylation QTL database as well as online clinicogenomic databases suggested that the region including rs3815544 may regulate MSX1 expression through CpG methylation, and this down-regulation was statistically associated with poor prognosis after platinum-based therapies for EC.Conclusion:rs3815544 is a novel candidate predictive marker for platinum-based EC therapy.

Breed-specific SNP markers of beef productivity of cattle of Kazakh White-headed breed

One of the most promising modern methods used to identify loci that control quantitative traits of productivity in cattle is the method of Genome-wide association of (GWA), which makes it possible to establish a link between allelic variation in a certain region of the genome and the trait under study. The purpose of the research was to establish breed-specific SNP markers of beef productivity of cattle of Kazakh white-headed breed. The results of the search for breed-specific genetic markers of increased beef productivity for Kazakh White-headed breed based on the data of DNA typing of animals using the GGP Gene Search chip Cattle 150 thousand (Illumina Inc., USA) have been presented. Genotyping data processing for each SNP and each sample was performed using the PLINK 1.9 software package (http://zzz.bwh.harvard.edu/plink/). The search for unique regions of the genome has been carried out by using homozygosity rows (ROH). Homozygosity rows (ROH) have been evaluated for each animal using the QTL database of Cattle PLINK. Seven SNP markers of increased beef productivity have been identified in Kazakh White-headed cattle: allele C (rs109910863) in the histatherin gene (histatherin (HSTN)), allele C (rs110065568) in the myostatin gene (myostatin (MSTN)), allele g (rs110320975) in the histatherin gene (histatherin (HSTN)), allele C ( rs135748641) in the gene of a nucleolar protein interacting with the domain of risk factor MKI67 (nucleolar proteins interacting with FCA domain MKI67 (NIFK), allele g (rs136552787) in the gene of insulin-like factor 6 binding protein (protein, binding insulin-like growth factor 6 (IGFBP6-202)), allele A (rs137243785) in the histatherin gene (histaterin (HSTN-201)), allele A (rs522351439) in the myostatin gene (myostatin (MSTN)).