Genetic Intervals Research Articles

Fine mapping of leaf rust resistance gene Rph13 from wild barley.

Fine mapping of the barley leaf rust resistance locus Rph13 on chromosome 3HL facilitates its use in breeding programs through marker-assisted selection. Barley leaf rust (BLR-caused by Puccinia hordei) is a widespread fungal disease that can be effectively controlled by genetic resistance. There is an ongoing need to both diversify and genetically characterise resistance loci to provide effective and durable control given the ongoing threat of rapidly evolving P. hordei populations. Here, we report on the molecular genetic characterisation of the Rph13 locus, originally derived from wild barley and transferred to barley accession Berac (then referred to as PI 531849). The 2017 reference genome of cv. Morex was used as a road map to rapidly narrow both a genetic and physical intervals around the Rph13 resistance locus. Using recombination-based mapping, we narrowed the physical interval to 116.6kb on chromosome 3H in a segregating population of a cross of the Rph13 carrying resistant line PI 531849 with the leaf rust-susceptible cultivar Gus. We identified two nucleotide-binding leucine-rich repeat genes as likely candidates for the Rph13 resistance. Sequences from the candidate genes enabled the development of a KASP marker that distinguished resistant and susceptible progeny and was found to be predictive and useful for MAS.

Genetic Dissection of Germinability under Low Temperature by Building a Resequencing Linkage Map in japonica Rice.

Among all cereals, rice is highly sensitive to cold stress, especially at the germination stage, which adversely impacts its germination ability, seed vigor, crop stand establishment, and, ultimately, grain yield. The dissection of novel quantitative trait loci (QTLs) or genes conferring a low-temperature germination (LTG) ability can significantly accelerate cold-tolerant rice breeding to ensure the wide application of rice cultivation through the direct seeding method. In this study, we identified 11 QTLs for LTG using 144 recombinant inbred lines (RILs) derived from a cross between a cold-tolerant variety, Lijiangxintuanheigu (LTH), and a cold-sensitive variety, Shennong265 (SN265). By resequencing two parents and RIL lines, a high-density bin map, including 2,828 bin markers, was constructed using 123,859 single-nucleotide polymorphisms (SNPs) between two parents. The total genetic distance corresponding to all 12 chromosome linkage maps was 2,840.12 cm. Adjacent markers were marked by an average genetic distance of 1.01 cm, corresponding to a 128.80 kb physical distance. Eight and three QTL alleles had positive effects inherited from LTH and SN265, respectively. Moreover, a pleiotropic QTL was identified for a higher number of erected panicles and a higher grain number on Chr-9 near the previously cloned DEP1 gene. Among the LTG QTLs, qLTG3 and qLTG7b were also located at relatively small genetic intervals that define two known LTG genes, qLTG3-1 and OsSAP16. Sequencing comparisons between the two parents demonstrated that LTH possesses qLTG3-1 and OsSAP16 genes, and SN-265 owns the DEP1 gene. These comparison results strengthen the accuracy and mapping resolution power of the bin map and population. Later, fine mapping was done for qLTG6 at 45.80 kb through four key homozygous recombinant lines derived from a population with 1569 segregating plants. Finally, LOC_Os06g01320 was identified as the most possible candidate gene for qLTG6, which contains a missense mutation and a 32-bp deletion/insertion at the promoter between the two parents. LTH was observed to have lower expression levels in comparison with SN265 and was commonly detected at low temperatures. In conclusion, these results strengthen our understanding of the impacts of cold temperature stress on seed vigor and germination abilities and help improve the mechanisms of rice breeding programs to breed cold-tolerant varieties.

Development of 21 Microsatellite Loci and Diversity Analysis of Amur Grayling in Amur River

Amur grayling (Thymallus arcticus grubei Dybowski), a cold freshwater fish, is an economically valuable species that is endemic to Heilongjiang Province, China. In this study, we developed 21 polymorphic microsatellite loci obtained from transcriptome data, and genetically analyzed 66 individuals from three natural riverine populations. The genetic diversity analysis showed that the number of alleles per locus ranged from 2 to 12 with mean value of 4.7. The expected heterozygosity ranged from 0.0800 to 0.9400 with mean value of 0.4339, while the observed heterozygosity ranged from 0.0960 to 0.8832 with mean value of 0.5243. The polymorphism information content (PIC) varied from 0.8509 to 0.0380, with an average value of 0.52. The Hardy-Weinberg equilibrium (HWE) test showed that most of loci were complied with HWE. The population genetic structure inferred with Bayesian method showed that the three Amur populations was divided into two main groups, and the genetic intervals are mainly positively correlated with geographical intervals. These transcript-derived microsatellite markers and the genetic diversity analysis could be promising for conservation of Amur grayling.

Modelling Sex-Specific Crossover Patterning in Arabidopsis.

"Interference" is a major force governing the patterning of meiotic crossovers. A leading model describing how interference influences crossover patterning is the beam-film model, a mechanical model based on the accumulation and redistribution of crossover-promoting "stress" along the chromosome axis. We use the beam-film model in conjunction with a large Arabidopsis reciprocal backcross data set to gain "mechanistic" insights into the differences between male and female meiosis, and crossover patterning. Beam-film modeling suggests that the underlying mechanics of crossover patterning and interference are identical in the two sexes, with the large difference in recombination rates and distributions able to be entirely explained by the shorter chromosome axes in females. The modeling supports previous indications that fewer crossovers occur via the class II pathway in female meiosis and that this could be explained by reduced DNA double-strand breaks in female meiosis, paralleling the observed reduction in synaptonemal complex length between the two sexes. We also demonstrate that changes in the strength of suppression of neighboring class I crossovers can have opposite effects on "effective" interference depending on the distance between two genetic intervals.

Consensus map integration and QTL meta-analysis narrowed a locus for yield traits to 0.7\u2009cM and refined a region for late leaf spot resistance traits to 0.38\u2009cM on linkage group A05 in peanut (Arachis hypogaea L.)

BackgroundMany large-effect quantitative trait loci (QTLs) for yield and disease resistance related traits have been identified in different mapping populations of peanut (Arachis hypogaea L.) under multiple environments. However, only a limited number of QTLs have been used in marker-assisted selection (MAS) because of unfavorable epistatic interactions between QTLs in different genetic backgrounds. Thus, it is essential to identify consensus QTLs across different environments and genetic backgrounds for use in MAS. Here, we used QTL meta-analysis to identify a set of consensus QTLs for yield and disease resistance related traits in peanut.ResultsA new integrated consensus genetic map with 5874 loci was constructed. The map comprised 20 linkage groups (LGs) and was up to a total length of 2918.62 cM with average marker density of 2.01 loci per centimorgan (cM). A total of 292 initial QTLs were projected on the new consensus map, and 40 meta-QTLs (MQTLs) for yield and disease resistance related traits were detected on four LGs. The genetic intervals of these consensus MQTLs varied from 0.20 cM to 7.4 cM, which is narrower than the genetic intervals of the initial QTLs, meaning they may be suitable for use in MAS. Importantly, a region of the map that previously co-localized multiple major QTLs for pod traits was narrowed from 3.7 cM to 0.7 cM using an overlap region of four MQTLs for yield related traits on LG A05, which corresponds to a physical region of about 630.3 kb on the A05 pseudomolecule of peanut, including 38 annotated candidate genes (54 transcripts) related to catalytic activity and metabolic process. Additionally, one major MQTL for late leaf spot (LLS) was identified in a region of about 0.38 cM. BLAST searches identified 26 candidate genes (30 different transcripts) in this region, some of which were annotated as related to regulation of disease resistance in different plant species.ConclusionsCombined with the high-density marker consensus map, all the detected MQTLs could be useful in MAS. The biological functions of the 64 candidate genes should be validated to unravel the molecular mechanisms of yield and disease resistance in peanut.

Genetic and transcriptional variations in NRAMP-2 and OPAQUE1 genes are associated with salt stress response in wheat

Key messageSNP alleles on chromosomes 4BL and 6AL are associated with sensitivity to salt tolerance in wheat and upon validation can be exploited in the development of salt-tolerant wheat varieties.The dissection of the genetic and molecular components of salt stress response offers strong opportunities toward understanding and improving salt tolerance in crops. In this study, GWAS was employed to identify a total of 106 SNP loci (R2 = 0.12–63.44%) linked to salt stress response in wheat using leaf chlorophyll fluorescence, grain quality and shoot ionic (Na+ and K+ ions) attributes. Among them, 14 SNP loci individually conferred pleiotropic effects on multiple independent salinity tolerance traits including loci at 99.04 cM (R2 ≥ 14.7%) and 68.45 cM (R2 ≥ 4.10%) on chromosomes 6AL and 4BL, respectively, that influenced shoot Na+-uptake, shoot K+/Na+ ratio, and specific energy fluxes for absorption (ABS/RC) and dissipation (DIo/RC). Analysis of the open reading frame (ORF) containing the SNP markers revealed that they are orthologous to genes involved in photosynthesis and plant stress (salt) response. Further transcript abundance and qRT-PCR analyses indicated that the genes are mostly up-regulated in salt-tolerant and down-regulated in salt-sensitive wheat genotypes including NRAMP-2 and OPAQUE1 genes on 4BL and 6AL, respectively. Both genes showed highest differential expression between contrasting genotypes when expressions of all the genes within their genetic intervals were analyzed. Possible cis-acting regulatory elements and coding sequence variation that may be involved in salt stress response were also identified in both genes. This study identified genetic and molecular components of salt stress response that are associated with Na+-uptake, shoot Na+/K+ ratio, ABS/RC, DIo/RC, and grain quality traits and upon functional validation would facilitate the development of gene-specific markers that could be deployed to improve salinity tolerance in wheat.

Exploration of genetic selection in rice leaf length and width

Leaf length and width are two of the most important components of rice (Oryza sativa L.) plant architecture and directly contribute to yield. The genetic effects of leaf length and width are controlled by quantitative trait loci (QTLs). In this study, a double haploid (DH) population derived from a cross of O. sativa subsp. japonica cultivar ‘Maybelle’ and subsp. indica cultivar ‘Baiyeqiu’ (‘BYQ’) was used to determine genetic effects on leaf length and width. Analysis of phenotypic effects indicated that all of the detected traits exhibited continuous, transgressive distributions in the DH population. Correlation analysis revealed a strong association between the two adjacent leaves for the same trait. A total of 25 QTLs within 17 genetic intervals distributed on chromosomes 1, 2, 3, 4, 5, 6, 8, and 12 were detected for rice leaf length and width, with likelihood of odds values that ranged from 2.75 to 10.62. Among these loci, two major QTLs, which were located in the intervals RM3262–RM3452 and RM16432–RM7472, played very important roles in regulating leaf length and width, respectively. Diversity analysis of the two major QTLs revealed that the genetic interval RM16432–RM7472 should be an optimal target for rice breeding programs, and may inspire new research efforts.

The Beavis Effect in Next-Generation Mapping Panels in Drosophila melanogaster.

A major goal in the analysis of complex traits is to partition the observed genetic variation in a trait into components due to individual loci and perhaps variants within those loci. However, in both QTL mapping and genetic association studies, the estimated percent variation attributable to a QTL is upwardly biased conditional on it being discovered. This bias was first described in two-way QTL mapping experiments by William Beavis, and has been referred to extensively as “the Beavis effect.” The Beavis effect is likely to occur in multiparent population (MPP) panels as well as collections of sequenced lines used for genome-wide association studies (GWAS). However, the strength of the Beavis effect is unknown—and often implicitly assumed to be negligible—when “hits” are obtained from an association panel consisting of hundreds of inbred lines tested across millions of SNPs, or in multiparent mapping populations where mapping involves fitting a complex statistical model with several d.f. at thousands of genetic intervals. To estimate the size of the effect in more complex panels, we performed simulations of both biallelic and multiallelic QTL in two major Drosophila melanogaster mapping panels, the GWAS-based Drosophila Genetic Reference Panel (DGRP), and the MPP the Drosophila Synthetic Population Resource (DSPR). Our results show that overestimation is determined most strongly by sample size and is only minimally impacted by the mapping design. When < 100, 200, 500, and 1000 lines are employed, the variance attributable to hits is inflated by factors of 6, 3, 1.5, and 1.1, respectively, for a QTL that truly contributes 5% to the variation in the trait. This overestimation indicates that QTL could be difficult to validate in follow-up replication experiments where additional individuals are examined. Further, QTL could be difficult to cross-validate between the two Drosophila resources. We provide guidelines for: (1) the sample sizes necessary to accurately estimate the percent variance to an identified QTL, (2) the conditions under which one is likely to replicate a mapped QTL in a second study using the same mapping population, and (3) the conditions under which a QTL mapped in one mapping panel is likely to replicate in the other (DGRP and DSPR).

Quantitative trait loci identification and meta-analysis for rice panicle-related traits.

Rice yield is a complex trait controlled by quantitative trait loci (QTLs). In the past three decades, thousands of QTLs for rice yield traits have been detected, but only a very small percentage has been cloned to date, as identifying the QTL genes requires a substantial investment of time and money. Meta-analysis provides a simple, reliable, and economical method for integrating information from multiple QTL studies across various environmental and genetic backgrounds, detecting consistent QTLs powerfully and estimating their genetic positions precisely. In this study, we aimed to locate consistent QTL regions associated with rice panicle traits by applying a genome-wide QTL meta-analysis approach. We first conducted a QTL analysis of 5 rice panicle traits using 172 plants in 2011 and 138 plants in 2012 from an F2 population derived from a cross between Nipponbare and H71D rice cultivators. A total of 54 QTLs were detected, and these were combined with 1085 QTLs collected from 82 previous studies to perform a meta-analysis using BioMercator v4.2. The integration of 82 maps resulted in a consensus map with 6970 markers and a total map length of 1823.1 centimorgan (cM), on which 837 QTLs were projected. These QTLs were then integrated into 87 meta-quantitative trait loci (MQTLs) by meta-analysis, and the 95% confidence intervals (CI) of them were smaller than the mean value of the original QTLs. Also, 30 MQTLs covered 47 of the 54 QTLs detected from the cross between Nipponbare and H71D in this study. Among them, the two major and stable QTLs, spp10.1 and sd10.1, were found to be included in MQTL10.4. The three other major QTLs, pl3.1, sb2.1, and sb10.1, were included in MQTL3.3, MQTL2.2, and MQTL10.3, respectively. A total of 21 of the 87 MQTLs' phenotypic variation were>20%. In total, 24 candidate genes were found in 15 MQTLs that spanned physical intervals<0.2Mb, including genes that have been cloned previously, e.g., EP3, LP, MIP1, HTD1, DSH1, and OsPNH1. However, it would be beneficial to identify a greater number of candidate genes from these MQTLs. Mining new genes that modulate yield and its related traits would assist researchers to better understand the relevant molecular mechanisms. The MQTLs found in this study that have small physical and genetic intervals are useful not only for marker-assisted selection and pyramiding, but they also provide important information of rice yield and related gene mining for future research.

Molecular genetic analysis of Varroa destructor mites in brood, fallen injured mites, and worker bee longevity in honey bees

Two important traits that contribute to honey bee (Apis mellifera) colony survival are resistance to varroa and longevity of worker bees. We investigated the relationship between a panel of single nucleotide polymorphism markers and three phenotypic measurements of colonies: (a) percentage of mites in brood (MIB); (b) proportion of fallen injured mites; and (c) longevity of workers. We used single marker analysis to identify genetic intervals that may confer resistance and increased lifespan. One gene related to memory and learning, Ddc was identified for MIB, as was acj6, which functions for olfactory perception. These genes may contribute to elevated levels of mite detection and removal. Three genes were identified with high relevance for mite injury. CYP315A1 and Ptp69D function in motor neuron axon guidance in response to chemical stimuli. RabGAP11 is also involved in sensory function, specifically sensory organ development. Evidence for the longevity quantitative trait locus was also strong and one gene (Orct) is related to improved lifespan in both humans and Drosophila. Together, these genes provide possible avenues to be pursued for further development for eventual marker-assisted selection.

Mutations in Caenorhabditis briggsae identify new genes important for limiting the response to EGF signaling during vulval development.

Studies of vulval development in the nematode C. elegans have identified many genes that are involved in cell division and differentiation processes. Some of these encode components of conserved signal transduction pathways mediated by EGF, Notch, and Wnt. To understand how developmental mechanisms change during evolution, we are doing a comparative analysis of vulva formation in C. briggsae, a species that is closely related to C. elegans. Here, we report 14 mutations in 7 Multivulva (Muv) genes in C. briggsae that inhibit inappropriate division of vulval precursors. We have developed a new efficient and cost-effective gene mapping method to localize Muv mutations to small genetic intervals on chromosomes, thus facilitating cloning and functional studies. We demonstrate the utility of our method by determining molecular identities of three of the Muv genes that include orthologs of Cel-lin-1 (ETS) and Cel-lin-31 (Winged-Helix) of the EGF-Ras pathway and Cel-pry-1 (Axin), of the Wnt pathway. The remaining four genes reside in regions that lack orthologs of known C. elegans Muv genes. Inhibitor studies demonstrate that the Muv phenotype of all four new genes is dependent on the activity of the EGF pathway kinase, MEK. One of these, Cbr-lin(gu167), shows modest increase in the expression of Cbr-lin-3/EGF compared to wild type. These results argue that while Cbr-lin(gu167) may act upstream of Cbr-lin-3/EGF, the other three genes influence the EGF pathway downstream or in parallel to Cbr-lin-3. Overall, our findings demonstrate that the genetic program underlying a conserved developmental process includes both conserved and divergent functional contributions.

Natural variation at sympathy for the ligule controls penetrance of the semidominant Liguleless narrow-R mutation in Zea mays.

Leaf architecture determines plant structural integrity, light harvesting, and economic considerations such as plant density. Ligules, junctions at the leaf sheath and blade in grasses, protect stalks from environmental stresses and, in conjunction with auricles, controls leaf angle. Previous studies in mutants have recessive liguleless mutants (lg1 and lg2) and dominant mutations in knotted1-like homeobox genes (Lg3-O, Lg4, and Kn1) involved in ligule development. Recently, a new semidominant liguleless mutant, Liguleless narrow (Lgn-R), has been characterized in maize that affects ligule and auricle development and results in a narrow leaf phenotype. We show that quantitative genetic variation affects penetrance of Lgn-R. To examine the genetic architecture underlying Lgn-R expressivity, crosses between Lgn-R/+ mutants in a B73 background and intermated B73 x Mo17 recombinant inbred lines were evaluated in multiple years and locations. A single main-effect quantitative trait locus (QTL) on chromosome 1 (sympathy for the ligule; sol) was discovered with a Mo17-contributed allele that suppressed Lgn-R mutant phenotypes. This QTL has a genetic-interaction with a locus on chromosome 7 (lucifer; lcf) for which the B73-contributed allele increases the ability of the solMo17 allele to suppress Lgn-R. Neither of the genetic intervals likely to contain sol or lcf overlap with any current liguleless genes nor with previously identified genome-wide association QTL connected to leaf architecture. Analysis of phenotypes across environments further identified a genotype by enviroment interaction determining the strength of the sol x lcf interaction.

QTL analysis for phytonutrient compounds and the antioxidant molecule in mustard (Brassica juncea L.)

A recombinant inbred line (RIL) population was developed following hybridization between a low glucosinolate B. juncea genotype, NUDH-YJ-04 and a high glucosinolate cultivar, RL-1359. RILs differed for seed and leaf glucosinolates, total tocopherols and oil content. A linkage map of length covering 2346.9 cM was constructed. It comprised 198 markers distributed across the 18 linkage groups. The linkage map facilitated analysis of quantitative trait loci (QTL) associated with phytonutrient compounds and the antioxidant molecules. The composite interval mapping helped to identify 21 QTLs on 11 linkage groups with R2 values between 15–53 % at logarithmic of odd (LOD) scores of 3.1–8.6. For seed aliphatic glucosinolates, most significant QTL, explaining 53 % of the phenotypic variation was located on J9, for glucoiberin (IBE-S). QTLs were also identified for indole glucosinolate (NEO-S) (44 %) on J7 and aromatic glucosinolate (NAS-S) (38 %) on J4. Total leaf glucosinolates (TGLC-L) explaining 15–21 % phenotypic variance were mapped to three different genetic intervals on J6 and J14, and total seed glucosinolates (TGLC-S) explained 17 % of the variance on J18. Tocopherol (TOC) QTL was confined to chromosome no. J6 (28 %) and J12 (19 %) at LOD score of 4.8 and 3.1. QTL for Oil content was tagged on J9 at LOD score of 3.2. Candidate genes underlying SIN-S, NEO-S and NAS-S QTLs, were considered to be GSL-elong, MYB-76 and MYB-28 in A4, A7 and A10 respectively. Despite a lower coverage, this is a first linkage map in this crop based solely on SSR markers and can serve as a basic map.

Arabidopsis PTD Is Required for Type I Crossover Formation and Affects Recombination Frequency in Two Different Chromosomal Regions

In eukaryotes, crossovers together with sister chromatid cohesion maintain physical association between homologous chromosomes, ensuring accurate chromosome segregation during meiosis I and resulting in exchange of genetic information between homologues. The Arabidopsis PTD (Parting Dancers) gene affects the level of meiotic crossover formation, but its functional relationships with other core meiotic genes, such as AtSPO11-1, AtRAD51, and AtMSH4, are unclear; whether PTD has other functions in meiosis is also unknown. To further analyze PTD function and to test for epistatic relationships, we compared the meiotic chromosome behaviors of Atspo11-1 ptd and Atrad51 ptd double mutants with the relevant single mutants. The results suggest that PTD functions downstream of AtSPO11-1 and AtRAD51 in the meiotic recombination pathway. Furthermore, we found that meiotic defects in rck ptd and Atmsh4 ptd double mutants showed similar meiotic phenotypes to those of the relevant single mutants, providing genetic evidences for roles of PTD and RCK in the type I crossovers pathway. Moreover, we employed a pollen tetrad-based fluorescence method and found that the meiotic crossover frequencies in two genetic intervals were significantly reduced from 6.63% and 22.26% in wild-type to 1.14% and 6.36%, respectively, in the ptd-2 mutant. These results revealed new aspects of PTD function in meiotic crossover formation.

Candidate gene association mapping of Sclerotinia stalk rot resistance in sunflower (Helianthus annuus L.) uncovers the importance of COI1 homologs

Functional markers for Sclerotinia basal stalk rot resistance in sunflower were obtained using gene-level information from the model species Arabidopsis thaliana. Sclerotinia stalk rot, caused by Sclerotinia sclerotiorum, is one of the most destructive diseases of sunflower (Helianthus annuus L.) worldwide. Markers for genes controlling resistance to S. sclerotiorum will enable efficient marker-assisted selection (MAS). We sequenced eight candidate genes homologous to Arabidopsis thaliana defense genes known to be associated with Sclerotinia disease resistance in a sunflower association mapping population evaluated for Sclerotinia stalk rot resistance. The total candidate gene sequence regions covered a concatenated length of 3,791 bp per individual. A total of 187 polymorphic sites were detected for all candidate gene sequences, 149 of which were single nucleotide polymorphisms (SNPs) and 38 were insertions/deletions. Eight SNPs in the coding regions led to changes in amino acid codons. Linkage disequilibrium decay throughout the candidate gene regions declined on average to an r (2) = 0.2 for genetic intervals of 120 bp, but extended up to 350 bp with r (2) = 0.1. A general linear model with modification to account for population structure was found the best fitting model for this population and was used for association mapping. Both HaCOI1-1 and HaCOI1-2 were found to be strongly associated with Sclerotinia stalk rot resistance and explained 7.4 % of phenotypic variation in this population. These SNP markers associated with Sclerotinia stalk rot resistance can potentially be applied to the selection of favorable genotypes, which will significantly improve the efficiency of MAS during the development of stalk rot resistant cultivars.

Time-dependent Gene Expression Analysis of the Developing Superior Olivary Complex

The superior olivary complex (SOC) is an essential auditory brainstem relay involved in sound localization. To identify the genetic program underlying its maturation, we profiled the rat SOC transcriptome at postnatal days 0, 4, 16, and 25 (P0, P4, P16, and P25, respectively), using genome-wide microarrays (41,012 oligonucleotides (oligos)). Differences in gene expression between two consecutive stages were highest between P4 and P16 (3.6%) and dropped to 0.06% between P16 and P25. To identify SOC-related genetic programs, we also profiled the entire brain at P4 and P25. The number of differentially expressed oligonucleotides between SOC and brain almost doubled from P4 to P25 (4.4% versus 7.6%). These data demonstrate considerable molecular specification around hearing onset, which is rapidly finalized. Prior to hearing onset, several transcription factors associated with the peripheral auditory system were up-regulated, probably coordinating the development of the auditory system. Additionally, crystallin-γ subunits and serotonin-related genes were highly expressed. The molecular repertoire of mature neurons was sculpted by SOC-related up- and down-regulation of voltage-gated channels and G-proteins. Comparison with the brain revealed a significant enrichment of hearing impairment-related oligos in the SOC (26 in the SOC, only 11 in the brain). Furthermore, 29 of 453 SOC-related oligos mapped within 19 genetic intervals associated with hearing impairment. Together, we identified sequential genetic programs in the SOC, thereby pinpointing candidates that may guide its development and ensure proper function. The enrichment of hearing impairment-related genes in the SOC may have implications for restoring hearing because central auditory structures might be more severely affected than previously appreciated.

GentrepidV2.0: a web server for candidate disease gene prediction

BackgroundCandidate disease gene prediction is a rapidly developing area of bioinformatics research with the potential to deliver great benefits to human health. As experimental studies detecting associations between genetic intervals and disease proliferate, better bioinformatic techniques that can expand and exploit the data are required.DescriptionGentrepid is a web resource which predicts and prioritizes candidate disease genes for both Mendelian and complex diseases. The system can take input from linkage analysis of single genetic intervals or multiple marker loci from genome-wide association studies. The underlying database of the Gentrepid tool sources data from numerous gene and protein resources, taking advantage of the wealth of biological information available. Using known disease gene information from OMIM, the system predicts and prioritizes disease gene candidates that participate in the same protein pathways or share similar protein domains. Alternatively, using an ab initio approach, the system can detect enrichment of these protein annotations without prior knowledge of the phenotype.ConclusionsThe system aims to integrate the wealth of protein information currently available with known and novel phenotype/genotype information to acquire knowledge of biological mechanisms underpinning disease. We have updated the system to facilitate analysis of GWAS data and the study of complex diseases. Application of the system to GWAS data on hypertension using the ICBP data is provided as an example. An interesting prediction is a ZIP transporter additional to the one found by the ICBP analysis. The webserver URL is https://www.gentrepid.org/.

Genetic analysis of an elite super-hybrid rice parent using high-density SNP markers.

BackgroundWith an increasing world population and a gradual decline in the amount of arable land, food security remains a global challenge. Continued increases in rice yield will be required to break through the barriers to grain output. In order to transition from hybrid rice to super-hybrid rice, breeding demands cannot be addressed through traditional heterosis. Therefore, it is necessary to incorporate high yield loci from other rice genetic groups and to scientifically utilize intersubspecific heterosis in breeding lines. In this study, 781 lines from a segregating F2 population constructed by crossing the indica variety, “Giant Spike Rice” R1128 as trait donor with the japonica cultivar ‘Nipponbare’, were re-sequenced using high-throughout multiplexed shotgun genotyping (MSG) technology. In combination with high-density single nucleotide polymorphisms, quantitative trait locus (QTL) mapping and genetic effect analysis were performed for five yield factors (spikelet number per panicle, primary branches per panicle, secondary branches per panicle, plant height, and panicle length) to explore the genetic mechanisms underlying the formation of the giant panicle of R1128. Also, they were preformed to locate new high-yielding rice genetic intervals, providing data for super-high-yielding rice breeding.ResultsQTL mapping and genetic effect analysis for five yield factors in the population gave the following results: 49 QTLs for the five yield factors were distributed on 11 of 12 chromosomes. The super-hybrid line R1128 carries multiple major genes for good traits, including Sd1 for plant height, Hd1 and Ehd1 for heading date, Gn1a for spikelet number and IPA1 for ideal plant shape. These genes accounted for 44.3%, 21.9%, 6.2%, 12.9% and 10.6% of the phenotypic variation in the individual traits. Six novel QTLs, qph1-2, qph9-1, qpl12-1, qgn3-1, qgn11-1 and qsbn11-1 are reported here for the first time.ConclusionsHigh-throughout sequencing technology makes it convenient to study rice genomics and makes the QTL/gene mapping direct, efficient, and more reliable. The genetic regions discovered in this study will be valuable for breeding in rice varieties because of the diverse genetic backgrounds of the rice.Electronic supplementary materialThe online version of this article (doi:10.1186/1939-8433-6-21) contains supplementary material, which is available to authorized users.

Meta-analyses of QTL for grain yield and anthesis silking interval in 18 maize populations evaluated under water-stressed and well-watered environments

BackgroundIdentification of QTL with large phenotypic effects conserved across genetic backgrounds and environments is one of the prerequisites for crop improvement using marker assisted selection (MAS). The objectives of this study were to identify meta-QTL (mQTL) for grain yield (GY) and anthesis silking interval (ASI) across 18 bi-parental maize populations evaluated in the same conditions across 2-4 managed water stressed and 3-4 well watered environments.ResultsThe meta-analyses identified 68 mQTL (9 QTL specific to ASI, 15 specific to GY, and 44 for both GY and ASI). Mean phenotypic variance explained by each mQTL varied from 1.2 to 13.1% and the overall average was 6.5%. Few QTL were detected under both environmental treatments and/or multiple (>4 populations) genetic backgrounds. The number and 95% genetic and physical confidence intervals of the mQTL were highly reduced compared to the QTL identified in the original studies. Each physical interval of the mQTL consisted of 5 to 926 candidate genes.ConclusionsMeta-analyses reduced the number of QTL by 68% and narrowed the confidence intervals up to 12-fold. At least the 4 mQTL (mQTL2.2, mQTL6.1, mQTL7.5 and mQTL9.2) associated with GY under both water-stressed and well-watered environments and detected up to 6 populations may be considered for fine mapping and validation to confirm effects in different genetic backgrounds and pyramid them into new drought resistant breeding lines. This is the first extensive report on meta-analysis of data from over 3100 individuals genotyped using the same SNP platform and evaluated in the same conditions across a wide range of managed water-stressed and well-watered environments.

CloudMap: A Cloud-Based Pipeline for Analysis of Mutant Genome Sequences

Whole genome sequencing (WGS) allows researchers to pinpoint genetic differences between individuals and significantly shortcuts the costly and time-consuming part of forward genetic analysis in model organism systems. Currently, the most effort-intensive part of WGS is the bioinformatic analysis of the relatively short reads generated by second generation sequencing platforms. We describe here a novel, easily accessible and cloud-based pipeline, called CloudMap, which greatly simplifies the analysis of mutant genome sequences. Available on the Galaxy web platform, CloudMap requires no software installation when run on the cloud, but it can also be run locally or via Amazon's Elastic Compute Cloud (EC2) service. CloudMap uses a series of predefined workflows to pinpoint sequence variations in animal genomes, such as those of premutagenized and mutagenized Caenorhabditis elegans strains. In combination with a variant-based mapping procedure, CloudMap allows users to sharply define genetic map intervals graphically and to retrieve very short lists of candidate variants with a few simple clicks. Automated workflows and extensive video user guides are available to detail the individual analysis steps performed (http://usegalaxy.org/cloudmap). We demonstrate the utility of CloudMap for WGS analysis of C. elegans and Arabidopsis genomes and describe how other organisms (e.g., Zebrafish and Drosophila) can easily be accommodated by this software platform. To accommodate rapid analysis of many mutants from large-scale genetic screens, CloudMap contains an in silico complementation testing tool that allows users to rapidly identify instances where multiple alleles of the same gene are present in the mutant collection. Lastly, we describe the application of a novel mapping/WGS method ("Variant Discovery Mapping") that does not rely on a defined polymorphic mapping strain, and we integrate the application of this method into CloudMap. CloudMap tools and documentation are continually updated at http://usegalaxy.org/cloudmap.