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Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large ( n  = 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population-specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide-binding groove, explaining 12.9% of trait variance. A high-resolution reference panel based on whole-genome sequencing data enables accurate imputation of HLA alleles across diverse populations and fine-mapping of HLA association signals for HIV-1 host response.

Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding.

Asian soybean rust (ASR), caused by Phakopsora pachyrhizi, is one of the most serious soybean (Glycine max) diseases in tropical and subtropical regions. To facilitate the development of resistant varieties using gene pyramiding, DNA markers closely linked to seven resistance genes, namely, Rpp1, Rpp1-b, Rpp2, Rpp3, Rpp4, Rpp5, and Rpp6, were identified. Linkage analysis of resistance-related traits and marker genotypes using 13 segregating populations of ASR resistance, including eight previously published by our group and five newly developed populations, identified the resistance loci with markers at intervals of less than 2.0 cM for all seven resistance genes. Inoculation was conducted of the same population with two P. pachyrhizi isolates of different virulence, and two resistant varieties, ‘Kinoshita’ and ‘Shiranui,’ previously thought to only harbor Rpp5, was found to also harbor Rpp3. Markers closely linked to the resistance loci identified in this study will be used for ASR-resistance breeding and the identification of the genes responsible for resistance.

With the development of network-on-chip (NoC) theory, lots of mapping algorithm have been proposed to solve the application mapping problem which is an NP-hard (non-polynomial hard) problem. Most algorithms are based on a heuristic algorithm. They are trapped by iterations limited, not by the distance between iterations, because of the isomorphism of mapping sequence. In this study, the authors define and analyse the isomorphism with the genetic algorithm (GA) which is a heuristic algorithm. Then, they proposed an approach called density direction transform algorithm to eliminate the isomorphism of mapping sequence and accelerate the convergence of population. To verify this approach, they developed a density-direction-based genetic mapping algorithm (DDGMAP) and make a comparison with genetic mapping algorithm (GMA). The experiment demonstrates that compared to the random algorithm, their algorithm (DDGMAP) can achieve on an average 23.48% delay reduction and 7.15% power reduction. And DDGMAP gets better performance than GA in searching the optimal solution.

The choroid plexus, an epithelial-based structure localized in the brain ventricle, is the major component of the blood-cerebrospinal fluid barrier. The choroid plexus produces the cerebrospinal fluid and regulates the components of the cerebrospinal fluid. Abnormal choroid plexus function is associated with neurodegenerative diseases, tumor formation in the choroid plexus epithelium, and hydrocephaly. In this study, we used zebrafish (Danio rerio) as a model system to understand the genetic components of choroid plexus development. We generated an enhancer trap line, Et(cp:EGFP) (sj2), that expresses enhanced green fluorescent protein (EGFP) in the choroid plexus epithelium. Using immunohistochemistry and fluorescent tracers, we demonstrated that the zebrafish choroid plexus possesses brain barrier properties such as tight junctions and transporter activity. Thus, we have established zebrafish as a functionally relevant model to study choroid plexus development. Using an unbiased approach, we performed a forward genetic dissection of the choroid plexus to identify genes essential for its formation and function. Using Et(cp:EGFP) (sj2), we isolated 10 recessive mutant lines with choroid plexus abnormalities, which were grouped into five classes based on GFP intensity, epithelial localization, and overall choroid plexus morphology. We also mapped the mutation for two mutant lines to chromosomes 4 and 21, respectively. The mutants generated in this study can be used to elucidate specific genes and signaling pathways essential for choroid plexus development, function, and/or maintenance and will provide important insights into how these genetic mutations contribute to disease.

Genetic mapping provides a powerful approach to identify genes and biological processes underlying any trait influenced by inheritance, including human diseases. We discuss the intellectual foundations of genetic mapping of Mendelian and complex traits in humans, examine lessons emerging from linkage analysis of Mendelian diseases and genome-wide association studies of common diseases, and discuss questions and challenges that lie ahead.

Pear (Pyrus spp) is an important fruit crop, grown in all temperate regions of the world, with global production ranked after grape and apples among deciduous tree crops. A high-density linkage map is a valuable tool for fine mapping quantitative trait loci (QTL) and map-based gene cloning. In this study, we firstly constructed a high-density linkage map of pear using SNPs integrated with SSRs, developed by the rapid and robust technology of restriction-associated DNA sequencing (RADseq). The linkage map consists of 3143 SNP markers and 98 SSRs, 3241 markers in total, spanning 2243.4 cM, with an average marker distance of 0.70 cM. Anchoring SSRs were able to anchor seventeen linkage groups to their corresponding chromosomes. Based on this high-density integrated pear linkage map and two years of fruit phenotyping, a total of 32 potential QTLs for 11 traits, including length of pedicel (LFP), single fruit weight (SFW), soluble solid content (SSC), transverse diameter (TD), vertical diameter (VD), calyx status (CS), flesh colour (FC), juice content (JC), number of seeds (NS), skin colour (SC), and skin smooth (SS), were identified and positioned on the genetic map. Among them, some important fruit-related traits have for the first time been identified, such as calyx status, length of pedicel, and flesh colour, and reliable localization of QTLs were verified repeatable. This high-density linkage map of pear is a worthy reference for mapping important fruit traits, QTL identification, and comparison and combination of different genetic maps. A highly saturated pear genetic map was constructed using over 3000 SNP markers developed by RADseq integrated with anchored SSR markers. The reliable QTLs of several fruit traits were also identified.

A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.

In mammals the regulation of genomic instability plays a key role in tumor suppression and also controls genome plasticity, which is important for recombination during the processes of immunity and meiosis. Most studies to identify regulators of genomic instability have been performed in cells in culture or in systems that report on gross rearrangements of the genome, yet subtle differences in the level of genomic instability can contribute to whole organism phenotypes such as tumor predisposition. Here we performed a genome-wide association study in a population of 1379 outbred Crl:CFW(SW)-US_P08 mice to dissect the genetic landscape of micronucleus formation, a biomarker of chromosomal breaks, whole chromosome loss, and extranuclear DNA. Variation in micronucleus levels is a complex trait with a genome-wide heritability of 53.1%. We identify seven loci influencing micronucleus formation (false discovery rate <5%), and define candidate genes at each locus. Intriguingly at several loci we find evidence for sexual dimorphism in micronucleus formation, with a locus on chromosome 11 being specific to males.

Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They are very effective at identifying DNA repair pathways, highlighting new damage-dependent roles for the Slt2 kinase, Pph3 phosphatase, and histone variant Htz1. The data also reveal that protein complexes are generally stable in response to perturbation, but the functional relations between these complexes are substantially reorganized. Differential networks chart a new type of genetic landscape that is invaluable for mapping cellular responses to stimuli.