A multi-trait approach identified 7 novel genes for back pain.

Introduction: Back pain (BP) is a complex heritable trait with an estimated heritability of 40% to 60%. Less than half of this can be explained by known genetic variants identified in genome-wide association studies.

Objectives: We applied a powerful multi-trait and gene-based approach to association analysis of BP to identify novel genes associated with BP.

A New Method for Conditional Gene-Based Analysis Effectively Accounts for the Regional Polygenic Background.

Gene-based association analysis is a powerful tool for identifying genes that explain trait variability. An essential step of this analysis is a conditional analysis. It aims to eliminate the influence of SNPs outside the gene, which are in linkage disequilibrium with intragenic SNPs.

Multi-Trait Exome-Wide Association Study of Back Pain-Related Phenotypes.

Back pain (BP) is a major contributor to disability worldwide, with heritability estimated at 40-60%. However, less than half of the heritability is explained by common genetic variants identified by genome-wide association studies. More powerful methods and rare and ultra-rare variant analysis may offer additional insight.

Genetic Structure Analysis of 155 Transboundary and Local Populations of Cattle (, and ) Based on STR Markers.

Every week, 1-2 breeds of farm animals, including local cattle, disappear in the world. As the keepers of rare allelic variants, native breeds potentially expand the range of genetic solutions to possible problems of the future, which means that the study of the genetic structure of these breeds is an urgent task. Providing nomadic herders with valuable resources necessary for life, domestic yaks have also become an important object of study.

A Novel Framework for Analysis of the Shared Genetic Background of Correlated Traits.

We propose a novel effective framework for the analysis of the shared genetic background for a set of genetically correlated traits using SNP-level GWAS summary statistics. This framework called SHAHER is based on the construction of a linear combination of traits by maximizing the proportion of its genetic variance explained by the shared genetic factors. SHAHER requires only full GWAS summary statistics and matrices of genetic and phenotypic correlations between traits as inputs.

sumSTAAR: A flexible framework for gene-based association studies using GWAS summary statistics.

Gene-based association analysis is an effective gene-mapping tool. Many gene-based methods have been proposed recently. However, their power depends on the underlying genetic architecture, which is rarely known in complex traits, and so it is likely that a combination of such methods could serve as a universal approach.

Genetic Diversity, Population Structure and Phylogeny of Indigenous Goats of Mongolia Revealed by SNP Genotyping.

Mongolian goats are of great interest for studying ancient migration routes and domestication, and also represent a good model of adaptability to harsh environments. Recent climatic disasters and uncontrolled massive breeding endangered the valuable genetic resources of Mongolian goats and raised the question of their conservation status. Meanwhile, Mongolian goats have never been studied on genomic scale.

Microsatellite Diversity and Phylogenetic Relationships among East Eurasian Breeds with an Emphasis on Rare and Ancient Local Cattle.

We report the genetic analysis of 18 population samples of animals, which were taken from cattle () breeds of European and Asian origins. The main strength of our study is the use of rare and ancient native cattle breeds: the Altai, Ukrainian Grey, Tagil, and Buryat ones. The cattle samples studied have different production purposes, belong to various eco-geographic regions, and consequently have distinct farming conditions.

Nonsynonymous Variation in NKPD1 Increases Depressive Symptoms in European Populations.

Background: Despite high heritability, little success was achieved in mapping genetic determinants of depression-related traits by means of genome-wide association studies.

Methods: To identify genes associated with depressive symptomology, we performed a gene-based association analysis of nonsynonymous variation captured using exome-sequencing and exome-chip genotyping in a genetically isolated population from the Netherlands (n = 1999). Finally, we reproduced our significant findings in an independent population-based cohort (n = 1604).

Rapid variance components-based method for whole-genome association analysis.

The variance component tests used in genome-wide association studies (GWAS) including large sample sizes become computationally exhaustive when the number of genetic markers is over a few hundred thousand. We present an extremely fast variance components-based two-step method, GRAMMAR-Gamma, developed as an analytical approximation within a framework of the score test approach. Using simulated and real human GWAS data sets, we show that this method provides unbiased estimates of the SNP effect and has a power close to that of the likelihood ratio test-based method.