Trait-associated SNPs Research Articles

A next-generation marker genotyping platform (AmpSeq) in heterozygous crops: a case study for marker-assisted selection in grapevine.

Marker-assisted selection (MAS) is often employed in crop breeding programs to accelerate and enhance cultivar development, via selection during the juvenile phase and parental selection prior to crossing. Next-generation sequencing and its derivative technologies have been used for genome-wide molecular marker discovery. To bridge the gap between marker development and MAS implementation, this study developed a novel practical strategy with a semi-automated pipeline that incorporates trait-associated single nucleotide polymorphism marker discovery, low-cost genotyping through amplicon sequencing (AmpSeq) and decision making. The results document the development of a MAS package derived from genotyping-by-sequencing using three traits (flower sex, disease resistance and acylated anthocyanins) in grapevine breeding. The vast majority of sequence reads (⩾99%) were from the targeted regions. Across 380 individuals and up to 31 amplicons sequenced in each lane of MiSeq data, most amplicons (83 to 87%) had <10% missing data, and read depth had a median of 220–244×. Several strengths of the AmpSeq platform that make this approach of broad interest in diverse crop species include accuracy, flexibility, speed, high-throughput, low-cost and easily automated analysis.

Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens.

BackgroundGenome-wide association studies in humans have found enrichment of trait-associated single nucleotide polymorphisms (SNPs) in coding regions of the genome and depletion of these in intergenic regions. However, a recent release of the ENCyclopedia of DNA elements showed that ~80 % of the human genome has a biochemical function. Similar studies on the chicken genome are lacking, thus assessing the relative contribution of its genic and non-genic regions to variation is relevant for biological studies and genetic improvement of chicken populations.MethodsA dataset including 1351 birds that were genotyped with the 600K Affymetrix platform was used. We partitioned SNPs according to genome annotation data into six classes to characterize the relative contribution of genic and non-genic regions to genetic variation as well as their predictive power using all available quality-filtered SNPs. Target traits were body weight, ultrasound measurement of breast muscle and hen house egg production in broiler chickens. Six genomic regions were considered: intergenic regions, introns, missense, synonymous, 5′ and 3′ untranslated regions, and regions that are located 5 kb upstream and downstream of coding genes. Genomic relationship matrices were constructed for each genomic region and fitted in the models, separately or simultaneously. Kernel-based ridge regression was used to estimate variance components and assess predictive ability. Contribution of each class of genomic regions to dominance variance was also considered.ResultsVariance component estimates indicated that all genomic regions contributed to marked additive genetic variation and that the class of synonymous regions tended to have the greatest contribution. The marked dominance genetic variation explained by each class of genomic regions was similar and negligible (~0.05). In terms of prediction mean-square error, the whole-genome approach showed the best predictive ability.ConclusionsAll genic and non-genic regions contributed to phenotypic variation for the three traits studied. Overall, the contribution of additive genetic variance to the total genetic variance was much greater than that of dominance variance. Our results show that all genomic regions are important for the prediction of the targeted traits, and the whole-genome approach was reaffirmed as the best tool for genome-enabled prediction of quantitative traits.

Verification of marker–trait associations in biparental winter barley (Hordeum vulgare L.) DH populations

In previous genome-wide association studies, marker–trait associations for grain yield and additional traits of agronomic importance were identified in the German winter barley (Hordeum vulgare L.) breeding gene pool. In the present study, seven doubled haploid populations segregating for the relevant alleles at the associated loci were used to get information whether these marker–trait associations can be verified in biparental populations and reliably used in applied barley breeding. The doubled haploid populations were phenotyped in field trials at two to five locations each in 1 year and genotyped by 40 trait-associated single nucleotide polymorphisms using an Illumina VeraCode GoldenGate assay. Large phenotypic variation was observed for all traits within at least one doubled haploid population. For 19 out of 58 marker–trait associations tested, the phenotypic means of both marker classes were significantly (p ≤ 0.005) different, thus confirming the association of the respective marker and the quantitative trait locus detected. For example, doubled haploid lines derived from a cross of ‘Malta’ × ‘Goldmine’ carrying different marker alleles differed by 0.41 t/ha in mean grain yield. The 19 (out of 58) marker–trait associations verified correspond to 10 (out of 27) genomic regions. Markers that were verified to be associated with a quantitative trait locus can be implemented directly in winter barley breeding for the selection of parental lines and marker-assisted pedigree selection.

Investigation of Splicing Quantitative Trait Loci inArabidopsis thaliana

The alteration of alternative splicing patterns has an effect on the quantification of functional proteins, leading to phenotype variation. The splicing quantitative trait locus (sQTL) is one of the main genetic elements affecting splicing patterns. Here, we report the results of genome-wide sQTLs across 141 strains of Arabidopsis thaliana with publicly available next generation sequencing datasets. As a result, we found 1,694 candidate sQTLs in Arabidopsis thaliana at a false discovery rate of 0.01. Furthermore, among the candidate sQTLs, we found 25 sQTLs that overlapped with the list of previously examined trait-associated single nucleotide polymorphisms (SNPs). In summary, this sQTL analysis provides new insight into genetic elements affecting alternative splicing patterns in Arabidopsis thaliana and the mechanism of previously reported trait-associated SNPs.

TraseR: an R package for performing trait-associated SNP enrichment analysis in genomic intervals.

Genome-wide association studies (GWASs) have successfully identified many sequence variants that are significantly associated with common diseases and traits. Tens of thousands of such trait-associated SNPs have already been cataloged, which we believe form a great resource for genomic research. Recent studies have demonstrated that the collection of trait-associated SNPs can be exploited to indicate whether a given genomic interval or intervals are likely to be functionally connected with certain phenotypes or diseases. Despite this importance, currently, there is no ready-to-use computational tool able to connect genomic intervals to phenotypes. Here, we present traseR, an easy-to-use R Bioconductor package that performs enrichment analyses of trait-associated SNPs in arbitrary genomic intervals with flexible options, including testing method, type of background and inclusion of SNPs in LD. The traseR R package preloaded with up-to-date collection of trait-associated SNPs are freely available in Bioconductor zhaohui.qin@emory.edu Supplementary data are available at Bioinformatics online.

Genetic control of morphometric diversity in the maize shoot apical meristem.

The maize shoot apical meristem (SAM) comprises a small pool of stem cells that generate all above-ground organs. Although mutational studies have identified genetic networks regulating SAM function, little is known about SAM morphological variation in natural populations. Here we report the use of high-throughput image processing to capture rich SAM size variation within a diverse maize inbred panel. We demonstrate correlations between seedling SAM size and agronomically important adult traits such as flowering time, stem size and leaf node number. Combining SAM phenotypes with 1.2 million single nucleotide polymorphisms (SNPs) via genome-wide association study reveals unexpected SAM morphology candidate genes. Analyses of candidate genes implicated in hormone transport, cell division and cell size confirm correlations between SAM morphology and trait-associated SNP alleles. Our data illustrate that the microscopic seedling SAM is predictive of adult phenotypes and that SAM morphometric variation is associated with genes not previously predicted to regulate SAM size.

Abstract 16053: Dynamic Trans Gene Expression Regulation by eQTLs in Complex Disease Traits

Genome-wide association studies (GWAS) have been widely used to identify genetic variants associated with complex traits. However, for many of these diseases, it remains unclear how the genetic variants exert their effect on the phenotype, and especially how they affect gene expression of remote genes (trans-eQTL). In a previous study, we found that a large proportion of trans-eQTLs are also cis-eQTLs. Therefore, we hypothesized that some trans-eQTLs influence expression of distant genes through effects on expression levels of a cis-transcript. Using 42,271 SNPs associated with 1,960 complex traits available in public data sets curated in GRASP, we first explored the gene expression associations of trait-associated SNPs in 5,257 individuals from the Framingham Heart Study (FHS) and then we tested mediation effects of cis-transcripts on trans-transcripts when both were associated with the same eQTL. At FDR&lt;0.05, we identified 2,324 trans-eQTLs; 84% of them (1,953) were found to have cis-associated transcripts. Mediation testing suggested that for 797 (41%) of these 1953 trans-eQTLs, the disease-associated SNP may alter expression of the trans-transcript via expression of genes near the eQTL (p&lt;0.0005 for 10,000 permutations). We searched across 7 cardiometabolic traits (BMI, systolic/ diastolic blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, glucose) and identified several cis mediators affecting the expression of multiple downstream genes; the cis mediators include SH2B3, ALDH2, NLRC5, PCSK7 and ALAS2. The expression of each cis mediator gene was significantly associated with one or more CVD phenotype in 5,257 FHS participants. These findings highlight a novel approach to identifying promising drug targets.

Super Enhancers in Cancers, Complex Disease, and Developmental Disorders.

Recently, unique areas of transcriptional regulation termed super-enhancers have been identified and implicated in human disease. Defined by their magnitude of size, transcription factor density, and binding of transcriptional machinery, super-enhancers have been associated with genes driving cell differentiation. While their functions are not completely understood, it is clear that these regions driving high-level transcription are susceptible to perturbation, and trait-associated single nucleotide polymorphisms (SNPs) occur within super-enhancers of disease-relevant cell types. Here we review evidence for super-enhancer involvement in cancers, complex diseases, and developmental disorders and discuss interactions between super-enhancers and cofactors/chromatin regulators.

Development and validation of a SNP panel for parentage assignment in rainbow trout

In salmonid aquaculture, family-based selective breeding programs rely on accurate pedigree information for estimating genetic merits. The pedigree information can be tracked through the use of Passive Integrated Transponder (PIT) tags. However, PIT tags can be expensive, and cannot be used with small fish. DNA markers offer an alternative approach for pedigree tracking and microsatellites have been previously used for parentage assignments in rainbow trout. Single nucleotide polymorphisms (SNPs) are becoming increasingly popular in aquaculture research because they are highly abundant and are amenable for high throughput genotyping. The objectives of this study were to develop a SNP panel for parentage assignment in rainbow trout and to evaluate the accuracy of parentage assignment using fish with known pedigrees. Two groups of SNPs were targeted: 1) genome SNPs distributed across all 29 chromosomes; and 2) previously identified trait-associated SNPs. Among the 128 SNPs selected for assay development, 102 (79.7%) working assays were developed. A panel of 95 SNP assays including 68 genome SNPs and 27 trait-associated SNPs was used to genotype 499 fish with known pedigrees from Troutlodge, Inc. and from the USDA/ARS National Center for Cool and Cold Water Aquaculture. Parentage assignments matched perfectly with the known pedigrees when all 95 SNPs were used. Near perfect parentage assignment was obtained with the 68 genome SNPs, and the accuracy of parentage assignment was over 98% with a subset of 48 genome SNPs. Therefore, these SNP assays are robust and enable accurate parentage analysis in populations that are typically used in rainbow trout breeding programs. Statement of relevanceProvide alternative method to track pedigrees.

Genome-wide association study of 29 morphological traits in Aegilops tauschii.

Aegilops tauschii is the D-genome progenitor of hexaploid wheat (Triticum aestivum). It is considered to be an important source of genetic variation for wheat breeding, and its genome is an invaluable reference for wheat genomics. We conducted a genome-wide association study using 7,185 single nucleotide polymorphism (SNP) markers across 322 diverse accessions of Ae. tauschii that were systematically phenotyped for 29 morphological traits in order to identify marker-trait associations and candidate genes, assess genetic diversity, and classify the accessions based on phenotypic data and genotypic comparison. Using the general linear model and mixed linear model, we identified a total of 18 SNPs significantly associated with 10 morphological traits. Systematic search of the flanking sequences of trait-associated SNPs in public databases identified several genes that may be linked to variations in phenotypes. Cluster analysis using phenotypic data grouped accessions into four clusters, while accessions in the same cluster were not from the same Ae. tauschii subspecies or from the same area of origin. This work establishes a fundamental research platform for association studies in Ae. tauschii and also provides useful information for understanding the genetic mechanism of agronomic traits in wheat.

Analysis of non-coding transcriptome in rice and maize uncovers roles of conserved lncRNAs associated with agriculture traits.

Long non-coding RNAs (lncRNAs) have recently been found to widely exist in eukaryotes and play important roles in key biological processes. To extend our knowledge of lncRNAs in crop plants we performed both non-directional and strand-specific RNA-sequencing experiments to profile non-coding transcriptomes of various rice and maize organs at different developmental stages. Analysis of more than 3 billion reads identified 22334 long intergenic non-coding RNAs (lincRNAs) and 6673 pairs of sense and natural antisense transcript (NAT). Many lincRNA genes were associated with epigenetic marks. Expression of rice lincRNA genes was significantly correlated with that of nearby protein-coding genes. A set of NAT genes also showed expression correlation with their sense genes. More than 200 rice lincRNA genes had homologous non-coding sequences in the maize genome. Much more lincRNA and NAT genes were derived from conserved genomic regions between the two cereals presenting positional conservation. Protein-coding genes flanking or having a sense-antisense relationship to these conserved lncRNA genes were mainly involved in development and stress responses, suggesting that the associated lncRNAs might have similar functions. Integrating previous genome-wide association studies (GWAS), we found that hundreds of lincRNAs contain trait-associated SNPs (single nucleotide polymorphisms [SNPs]) suggesting their putative contributions to developmental and agriculture traits.

Exploring the rice dispensable genome using a metagenome-like assembly strategy.

BackgroundThe dispensable genome of a species, consisting of the dispensable sequences present only in a subset of individuals, is believed to play important roles in phenotypic variation and genome evolution. However, construction of the dispensable genome is costly and labor-intensive at present, and so the influence of the dispensable genome in genetic and functional genomic studies has not been fully explored.ResultsWe construct the dispensable genome of rice through a metagenome-like de novo assembly strategy based on low-coverage (1–3×) sequencing data of 1483 cultivated rice (Oryza sativa L.) accessions. Thousands of protein-coding genes are successfully assembled, including most of the known agronomically important genes absent from the Nipponbare rice reference genome. We develop an integration approach based on alignment and linkage disequilibrium, which is able to assign genomic positions relative to the reference genome for more than 78.2 % of the dispensable sequences. We carry out association mapping studies for rice grain width and 840 metabolic traits using 0.46 million polymorphisms between the dispensable sequences of different rice accessions. About 23.5 % of metabolic traits have more significant association signals with polymorphisms from dispensable sequences than with SNPs from the reference genome, and 41.6 % of trait-associated SNPs have concordant genomic locations with associated dispensable sequences.ConclusionsOur results suggest the feasibility of building a species’ dispensable genome using low-coverage population sequencing data. The constructed sequences will be helpful for understanding the rice dispensable genome and are complementary to the reference genome for identifying candidate genes associated with phenotypic variation.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0757-3) contains supplementary material, which is available to authorized users.

Genome-wide association for grain yield under rainfed conditions in historical wheat cultivars from Pakistan.

Genome-wide association studies (GWAS) were undertaken to identify SNP markers associated with yield and yield-related traits in 123 Pakistani historical wheat cultivars evaluated during 2011–2014 seasons under rainfed field conditions. The population was genotyped by using high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay, and finally 14,960 high quality SNPs were used in GWAS. Population structure examined using 1000 unlinked markers identified seven subpopulations (K = 7) that were representative of different breeding programs in Pakistan, in addition to local landraces. Forty four stable marker-trait associations (MTAs) with -log p > 4 were identified for nine yield-related traits. Nine multi-trait MTAs were found on chromosomes 1AL, 1BS, 2AL, 2BS, 2BL, 4BL, 5BL, 6AL, and 6BL, and those on 5BL and 6AL were stable across two seasons. Gene annotation and syntey identified that 14 trait-associated SNPs were linked to genes having significant importance in plant development. Favorable alleles for days to heading (DH), plant height (PH), thousand grain weight (TGW), and grain yield (GY) showed minor additive effects and their frequencies were slightly higher in cultivars released after 2000. However, no selection pressure on any favorable allele was identified. These genomic regions identified have historically contributed to achieve yield gains from 2.63 million tons in 1947 to 25.7 million tons in 2015. Future breeding strategies can be devised to initiate marker assisted breeding to accumulate these favorable alleles of SNPs associated with yield-related traits to increase grain yield. Additionally, in silico identification of 454-contigs corresponding to MTAs will facilitate fine mapping and subsequent cloning of candidate genes and functional marker development.

Genome-wide association study for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm.

BackgroundSoybean (Glycine max) is a photoperiod-sensitive and self-pollinated species. Days to flowering (DTF) and maturity (DTM), duration of flowering-to-maturity (DFTM) and plant height (PH) are crucial for soybean adaptability and yield. To dissect the genetic architecture of these agronomically important traits, a population consisting of 309 early maturity soybean germplasm accessions was genotyped with the Illumina Infinium SoySNP50K BeadChip and phenotyped in multiple environments. A genome-wide association study (GWAS) was conducted using a mixed linear model that involves both relative kinship and population structure.ResultsThe linkage disequilibrium (LD) decayed slowly in soybean, and a substantial difference in LD pattern was observed between euchromatic and heterochromatic regions. A total of 27, 6, 18 and 27 loci for DTF, DTM, DFTM and PH were detected via GWAS, respectively. The Dt1 gene was identified in the locus strongly associated with both DTM and PH. Ten candidate genes homologous to Arabidopsis flowering genes were identified near the peak single nucleotide polymorphisms (SNPs) associated with DTF. Four of them encode MADS-domain containing proteins. Additionally, a pectin lyase-like gene was also identified in a major-effect locus for PH where LD decayed rapidly.ConclusionsThis study identified multiple new loci and refined chromosomal regions of known loci associated with DTF, DTM, DFTM and/or PH in soybean. It demonstrates that GWAS is powerful in dissecting complex traits and identifying candidate genes although LD decayed slowly in soybean. The loci and trait-associated SNPs identified in this study can be used for soybean genetic improvement, especially the major-effect loci associated with PH could be used to improve soybean yield potential. The candidate genes may serve as promising targets for studies of molecular mechanisms underlying the related traits in soybean.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1441-4) contains supplementary material, which is available to authorized users.

SNPsnap: a Web-based tool for identification and annotation of matched SNPs.

An important computational step following genome-wide association studies (GWAS) is to assess whether disease or trait-associated single-nucleotide polymorphisms (SNPs) enrich for particular biological annotations. SNP-based enrichment analysis needs to account for biases such as co-localization of GWAS signals to gene-dense and high linkage disequilibrium (LD) regions, and correlations of gene size, location and function. The SNPsnap Web server enables SNP-based enrichment analysis by providing matched sets of SNPs that can be used to calibrate background expectations. Specifically, SNPsnap efficiently identifies sets of randomly drawn SNPs that are matched to a set of query SNPs based on allele frequency, number of SNPs in LD, distance to nearest gene and gene density. SNPsnap server is available at http://www.broadinstitute.org/mpg/snpsnap/. joelh@broadinstitute.org Supplementary data are available at Bioinformatics online.

Genetic determinants of age-related macular degeneration in diverse populations from the PAGE study.

Substantial progress has been made in identifying susceptibility variants for AMD in European populations; however, few studies have been conducted to understand the role these variants play in AMD risk in diverse populations. The present study aims to examine AMD risk across diverse populations in known and suspected AMD complement factor and lipid-related loci. Targeted genotyping was performed across study sites for AMD and lipid trait-associated single nucleotide polymorphism (SNPs). Genetic association tests were performed at individual sites and then meta-analyzed using logistic regression assuming an additive genetic model stratified by self-described race/ethnicity. Participants included cases with early or late AMD and controls with no signs of AMD as determined by fundus photography. Populations included in this study were European Americans, African Americans, Mexican Americans, and Singaporeans from the Population Architecture using Genomics and Epidemiology (PAGE) study. Index variants of AMD, rs1061170 (CFH) and rs10490924 (ARMS2), were associated with AMD at P=3.05×10(-8) and P=6.36×10(-6), respectively, in European Americans. In general, none of the major AMD index variants generalized to our non-European populations with the exception of rs10490924 in Mexican Americans at an uncorrected P value<0.05. Four lipid-associated SNPS (LPL rs328, TRIB1 rs6987702, CETP rs1800775, and KCTD10/MVK rs2338104) were associated with AMD in African Americans and Mexican Americans (P<0.05), but these associations did not survive strict corrections for multiple testing. While most associations did not generalize in the non-European populations, variants within lipid-related genes were found to be associated with AMD. This study highlights the need for larger well-powered studies in non-European populations.

Identification and Validation of Genetic Variants that Influence Transcription Factor and Cell Signaling Protein Levels

Many genetic variants associated with human disease have been found to be associated with alterations in mRNA expression. Although it is commonly assumed that mRNA expression changes will lead to consequent changes in protein levels, methodological challenges have limited our ability to test the degree to which this assumption holds true. Here, we further developed the micro-western array approach and globally examined relationships between human genetic variation and cellular protein levels. We collected more than 250,000 protein level measurements comprising 441 transcription factor and signaling protein isoforms across 68 Yoruba (YRI) HapMap lymphoblastoid cell lines (LCLs) and identified 12 cis and 160 trans protein level QTLs (pQTLs) at a false discovery rate (FDR) of 20%. Whereas up to two thirds of cis mRNA expression QTLs (eQTLs) were also pQTLs, many pQTLs were not associated with mRNA expression. Notably, we replicated and functionally validated a trans pQTL relationship between the KARS lysyl-tRNA synthetase locus and levels of the DIDO1 protein. This study demonstrates proof of concept in applying an antibody-based microarray approach to iteratively measure the levels of human proteins and relate these levels to human genome variation and other genomic data sets. Our results suggest that protein-based mechanisms might functionally buffer genetic alterations that influence mRNA expression levels and that pQTLs might contribute phenotypic diversity to a human population independently of influences on mRNA expression.

RTeQTL: Real-Time Online Engine for Expression Quantitative Trait Loci Analyses.

Our database tool, called Real-Time Engine for Expression Quantitative Trait Loci Analyses (RTeQTL), can efficiently provide eQTL association results that are not available in existing eQTL databases browsers. These functions include (i) single SNP (single-nucleotide polymorphism) and (ii) two-SNP conditional eQTL effects on gene expression regardless of the magnitude of P-values. The database is based on lymphoblastoid cell lines from >900 samples with global gene expression and genome-wide genotyped and imputed SNP data. The detailed result for any pairs of gene and SNPs can be efficiently computed and browsed online, as well as downloaded in batch mode. This is the only tool that can assess the independent effect of a disease- or trait-associated SNP on gene expression conditioning on other SNPs of interest, such as the top eQTL of the same gene. It is also useful to identify eQTLs for candidate genes, which are often missed in existing eQTL browsers, which only store results with genome-wide significant P-value. Additional analyses stratifying by gender can also be easily achieved by this tool.Database URL: http://eqtl.rc.fas.harvard.edu/

Blood cis-eQTL analysis fails to identify novel association signals among sub-threshold candidates from genome-wide association studies in restless legs syndrome.

Restless legs syndrome (RLS) is a common neurologic disorder characterized by nightly dysesthesias affecting the legs primarily during periods of rest and relieved by movement. RLS is a complex genetic disease and susceptibility factors in six genomic regions have been identified by means of genome-wide association studies (GWAS). For some complex genetic traits, expression quantitative trait loci (eQTLs) are enriched among trait-associated single nucleotide polymorphisms (SNPs). With the aim of identifying new genetic susceptibility factors for RLS, we assessed the 332 best-associated SNPs from the genome-wide phase of the to date largest RLS GWAS for cis-eQTL effects in peripheral blood from individuals of European descent. In 740 individuals belonging to the KORA general population cohort, 52 cis-eQTLs with pnominal<10−3 were identified, while in 976 individuals belonging to the SHIP-TREND general population study 53 cis-eQTLs with pnominal<10−3 were present. 23 of these cis-eQTLs overlapped between the two cohorts. Subsequently, the twelve of the 23 cis-eQTL SNPs, which were not located at an already published RLS-associated locus, were tested for association in 2449 RLS cases and 1462 controls. The top SNP, located in the DET1 gene, was nominally significant (p<0.05) but did not withstand correction for multiple testing (p = 0.42). Although a similar approach has been used successfully with regard to other complex diseases, we were unable to identify new genetic susceptibility factor for RLS by adding this novel level of functional assessment to RLS GWAS data.

LncRNAs: insights into their function and mechanics in underlying disorders.

Genomes of complex organisms are characterized by the pervasive expression of different types of noncoding RNAs (ncRNAs). lncRNAs constitute a large family of long—arbitrarily defined as being longer than 200 nucleotides—ncRNAs that are expressed throughout the cell and that include thousands of different species. While these new and enigmatic players in the complex transcriptional milieu are encoded by a significant proportion of the genome, their functions are mostly unknown at present. Existing examples suggest that lncRNAs have fulfilled a wide variety of regulatory roles at almost every stage of gene expression. These roles, which encompass signal, decoy, scaffold and guide capacities, derive from folded modular domains in lncRNAs. Early discoveries support a paradigm in which lncRNAs regulate transcription networks via chromatin modulation, but new functions are steadily emerging. Given the biochemical versatility of RNA, lncRNAs may be used for various tasks, including posttranscriptional processing. In addition, long intergenic ncRNAs (lincRNAs) are strongly enriched for trait-associated SNPs, which suggest a new mechanism by which intergenic trait-associated regions might function. Moreover, multiple lines of evidence increasingly link mutations and dysregulations of lncRNAs to diverse human diseases, especially disorders related to aging. In this article, we review the current state of the knowledge of the lncRNA field, discussing what is known about the genomic contexts, biological functions and mechanisms of action of these molecules. We highlight the growing evidence for the importance of lncRNAs in diverse human disorders and the indications that their dysregulations and mutations underlie some aging-related disorders. Finally, we consider the potential medical implications, and future potential in the application of lncRNAs as therapeutic targets and diagnostic markers.