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Faithful reconstruction of haplotypes from diploid marker data (phasing) is important for many kinds of genetic analyses, including mapping of trait loci, prediction of genomic breeding values, and identification of signatures of selection. In human genetics, phasing most often exploits population information (linkage disequilibrium), while in animal genetics the primary source of information is familial (Mendelian segregation and linkage). We herein develop and evaluate a method that simultaneously exploits both sources of information. It builds on hidden Markov models that were initially developed to exploit population information only. We demonstrate that the approach improves the accuracy of allele phasing as well as imputation of missing genotypes. Reconstructed haplotypes are assigned to hidden states that are shown to correspond to clusters of genealogically related chromosomes. We show that these cluster states can directly be used to fine map QTL. The method is computationally effective at handling large data sets based on high-density SNP panels.

In vertebrates, including humans, individuals harbor gut microbial communities whose species composition and relative proportions of dominant microbial groups are tremendously varied. Although external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genomewide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.

Background High temperature is one of the major abiotic stresses in tomato and greatly reduces fruit yield and quality. Identifying high-temperature stress-responsive (HSR) genes and breeding heat-tolerant varieties is an effective way to address this issue. However, there are few reports on the fine mapping of heat-tolerance quantitative trait locus (QTL) and the identification of HSR genes in tomato. Here, we applied three heat tolerance-related physiological indexes, namely, relative electrical conductivity (REC), chlorophyll content (CC) and maximum photochemical quantum efficiency (F v /F m ) of PSII (photosystem II), as well as the phenotypic index, the heat injury index (HII), and conventional QTL analysis combined with QTL-seq technology to comprehensively detect heat-tolerance QTLs in tomato seedlings. In addition, we integrated the QTL mapping results with RNA-seq to identify key HSR genes within the major QTLs. Results A total of five major QTLs were detected: qHII-1-1 , qHII-1-2 , qHII-1-3 , qHII-2-1 and qCC-1-5 ( qREC-1-3 ). qHII-1-1 , qHII-1-2 and qHII-1-3 were located, respectively, in the intervals of 1.43, 1.17 and 1.19 Mb on chromosome 1, while the interval of qHII-2-1 was located in the intervals of 1.87 Mb on chromosome 2. The locations observed with conventional QTL mapping and QTL-seq were consistent. qCC-1-5 and qREC-1-3 for CC and REC, respectively, were located at the same position by conventional QTL mapping. Although qCC-1-5 was not detected in QTL-seq analysis, its phenotypic variation (16.48%) and positive additive effect (0.22) were the highest among all heat tolerance QTLs. To investigate the genes involved in heat tolerance within the major QTLs in tomato, RNA-seq analysis was performed, and four candidate genes ( SlCathB2, SlGST, SlUBC5, and SlARG1 ) associated with heat tolerance were finally detected within the major QTLs by DEG analysis, qRT-PCR screening and biological function analysis. Conclusions In conclusion, this study demonstrated that the combination of conventional QTL mapping, QTL-seq analysis and RNA-seq can rapidly identify candidate genes within major QTLs for a complex trait of interest to replace the fine-mapping process, thus greatly shortening the breeding process and improving breeding efficiency. The results have important applications for the fine mapping and identification of HSR genes and breeding for improved thermotolerance.

Local adaptation is the process by which natural selection drives adaptive phenotypic divergence across environmental gradients. Theory suggests that local adaptation results from genetic tradeoffs at individual genetic loci, where adaptation to one set of environmental conditions results in a cost to fitness in alternative environments. However, the degree to which there are costs associated with local adaptation is poorly understood because most of these experiments rely on two-site reciprocal transplant experiments. Here, we quantify the benefits and costs of locally adaptive loci across 17° of latitude in a four-grandparent outbred mapping population in outcrossing switchgrass (Panicum virgatum L.), an emerging biofuel crop and dominant tallgrass species. We conducted quantitative trait locus (QTL) mapping across 10 sites, ranging from Texas to South Dakota. This analysis revealed that beneficial biomass (fitness) QTL generally incur minimal costs when transplanted to other field sites distributed over a large climatic gradient over the 2 y of our study. Therefore, locally advantageous alleles could potentially be combined across multiple loci through breeding to create high-yielding regionally adapted cultivars.

Domestication of crop plants had effects on human lifestyle and agriculture. However, little is known about the underlying molecular mechanisms accompanying the changes in fruit appearance as a consequence of selection by early farmers. We report the fine mapping and cloning of a tomato (Solanum lycopersicum) fruit mass gene encoding the ortholog of KLUH, SlKLUH, a P450 enzyme of the CYP78A subfamily. The increase in fruit mass is predominantly the result of enlarged pericarp and septum tissues caused by increased cell number in the large fruited lines. SlKLUH also modulates plant architecture by regulating number and length of the side shoots, and ripening time, and these effects are particularly strong in plants that transgenically down-regulate SlKLUH expression carrying fruits of a dramatically reduced mass. Association mapping followed by segregation analyses revealed that a single nucleotide polymorphism in the promoter of the gene is highly associated with fruit mass. This single polymorphism may potentially underlie a regulatory mutation resulting in increased SlKLUH expression concomitant with increased fruit mass. Our findings suggest that the allele giving rise to large fruit arose in the early domesticates of tomato and becoming progressively more abundant upon further selections. We also detected association of fruit weight with CaKLUH in chile pepper (Capsicum annuum) suggesting that selection of the orthologous gene may have occurred independently in a separate domestication event. Altogether, our findings shed light on the molecular basis of fruit mass, a key domestication trait in tomato and other fruit and vegetable crops.

Significance A core tenet in genetics is that genotype influences phenotype. In an individual, the same genome can be expressed in substantially different ways, depending on the tissue. Expression quantitative trait locus (eQTL) analysis, which associates genetic variants at millions of locations across the genome with the expression levels of each gene, can provide insight into genetic regulation of phenotype. In each of 13 tissues we performed an eQTL analysis, represented significant associations as edges in a network, and explored the structure of those networks. We found clusters of eQTL linked to shared functions across tissues and tissue-specific clusters linked to tissue-specific functions, driven by genetic variants with tissue-specific regulatory potential. Our findings provide unique insight into the genotype–phenotype relationship.

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

Background Salinity is a major abiotic stress seriously hindering crop yield. Development and utilization of tolerant varieties is the most economical way to address soil salinity. Upland cotton is a major fiber crop and pioneer plant on saline soil and thus its genetic architecture underlying salt tolerance should be extensively explored. Results In this study, genome-wide association analysis and RNA sequencing were employed to detect salt-tolerant qualitative-trait loci (QTLs) and candidate genes in 196 upland cotton genotypes at the germination stage. Using comprehensive evaluation values of salt tolerance in four environments, we identified 33 significant single-nucleotide polymorphisms (SNPs), including 17 and 7 SNPs under at least two and four environments, respectively. The 17 stable SNPs were located within or near 98 candidate genes in 13 QTLs, including 35 genes that were functionally annotated to be involved in salt stress responses. RNA-seq analysis indicated that among the 98 candidate genes, 13 were stably differentially expressed. Furthermore, 12 of the 13 candidate genes were verified by qRT-PCR. RNA-seq analysis detected 6640, 3878, and 6462 differentially expressed genes at three sampling time points, of which 869 were shared. Conclusions These results, including the elite cotton accessions with accurate salt tolerance evaluation, the significant SNP markers, the candidate genes, and the salt-tolerant pathways, could improve our understanding of the molecular regulatory mechanisms under salt stress tolerance and genetic manipulation for cotton improvement.

Plant water relations are critical for determining the distribution, persistence, and fitness of plant species. Studying the genetic basis of ecologically relevant traits, however, can be complicated by their complex genetic, physiological, and developmental basis and their interaction with the environment. Water use efficiency (WUE), the ratio of photosynthetic carbon assimilation to stomatal conductance to water, is a dynamic trait with tremendous ecological and agricultural importance whose genetic control is poorly understood. In the present study, we use a quantitative trait locus-mapping approach to locate, fine-map, clone, confirm, and characterize an allelic substitution that drives differences in WUE among natural accessions of Arabidopsis thaliana . We show that a single amino acid substitution in an abscisic acid-responsive kinase, AtMPK12, causes reduction in WUE, and we confirm its functional role using transgenics. We further demonstrate that natural alleles at AtMPK12 differ in their response to cellular and environmental cues, with the allele from the Cape Verde Islands (CVI) being less responsive to hormonal inhibition of stomatal opening and more responsive to short-term changes in vapor pressure deficit. We also show that the CVI allele results in constitutively larger stomata. Together, these differences cause higher stomatal conductance and lower WUE compared with the common allele. These physiological changes resulted in reduced whole-plant transpiration efficiency and reduced fitness under water-limited compared with well-watered conditions. Our work demonstrates how detailed analysis of naturally segregating functional variation can uncover the molecular and physiological basis of a key trait associated with plant performance in ecological and agricultural settings.

The role of natural selection in speciation, first described by Darwin, has finally been widely accepted. Yet, the nature and time course of the genetic changes that result in speciation remain mysterious. To date, genetic analyses of speciation have focused almost exclusively on retrospective analyses of reproductive isolation between species or subspecies and on hybrid sterility or inviability rather than on ecologically based barriers to gene flow. However, if we are to fully understand the origin of species, we must analyze the process from additional vantage points. By studying the genetic causes of partial reproductive isolation between specialized ecological races, early barriers to gene flow can be identified before they become confounded with other species differences. This population-level approach can reveal patterns that become invisible over time, such as the mosaic nature of the genome early in speciation. Under divergent selection in sympatry, the genomes of incipient species become temporary genetic mosaics in which ecologically important genomic regions resist gene exchange, even as gene flow continues over most of the genome. Analysis of such mosaic genomes suggests that surprisingly large genomic regions around divergently selected quantitative trait loci can be protected from interrace recombination by \"divergence hitchhiking.\" Here, I describe the formation of the genetic mosaic during early ecological speciation, consider the establishment, effects, and transitory nature of divergence hitchhiking around key ecologically important genes, and describe a 2-stage model for genetic divergence during ecological speciation with gene flow.