Explore the vast range of titles available.

BackgroundVariation in the prevalence of Huntington’s disease (HD) is associated with differences in chromosome 4 haplogroup proportions between populations. No data have been published on mutant HTT (mHTT) repeat stability in different haplogroups.AimTo study intergenerational CAG repeat stability in different mHTT haplotypes.MethodsA previously identified Finnish cohort of 207 HD patients and data on mHTT repeat lengths obtained from the diagnostic laboratories were used as a basis to identify parent-offspring pairs using several national registries. DNA remaining from diagnostic testing was analysed to determine haplogroups defined by the SNPs rs762855 and rs4690073. Haplogroup A haplotypes were further defined using four additional SNPs, rs2857936, rs363096, rs2276881 and rs362307. (Warby et al. 2009) The SNPs were determined either with restriction fragment analysis, allele specific amplification using locked nucleic acid primers or by sequencing.ResultsmHTT haplogroup and CAG repeat could be phased in 49 transmissions (haplogroup A, 38; haplogroup C, 10; other haplogroup, 1). The mean change in the length of CAG repeats differed between haplogroups A and C in paternal inheritances (p=0.038), but not in maternal inheritances (p=0.17). The change in haplogroup C was negative in paternal as well as maternal transmissions (p=0.74 for difference; figure 1), whereas the repeats in haplogroup A expanded in paternal transmissions in comparison to maternal transmissions (p=0.008). The difference was most obvious in haplotype A1 inheritances (p=0.022).Abstract C07 Figure 1The mean change (%) in the length of CAG repeats in haplogroups A and C in paternal and maternal transmissions[Figure omitted. See PDF]ConclusionsIntergenerational stability of the CAG repeat differed between mHTT haplogroups in a sex-dependent manner.

Summary Genome phasing is a recently developed assembly method that separates heterozygous eukaryotic genomic regions and builds haplotype‐resolved assemblies. Because differences between haplotypes are ignored in most published de novo genomes, assemblies are available as consensus genomes consisting of haplotype mixtures, thus increasing the need for genome phasing. Here, we review the operating principles and characteristics of several freely available and widely used phasing tools (TrioCanu, FALCON‐Phase, and ALLHiC). An examination of downstream analyses using haplotype‐resolved genome assemblies in plants indicated significant differences among haplotypes regarding chromosomal rearrangements, sequence insertions, and expression of specific alleles that contribute to the acquisition of the biological characteristics of plant species. Finally, we suggest directions to solve addressing limitations of current genome‐phasing methods. This review provides insights into the current progress, limitations, and future directions of de novo genome phasing, which will enable researchers to easily access and utilize genome‐phasing in studies involving highly heterozygous complex plant genomes.

Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework.

Haplotype-based breeding, a recent promising breeding approach to develop tailor-made crop varieties, deals with identification of superior haplotypes and their deployment in breeding programmes. In this context, whole genome re-sequencing data of 292 genotypes from pigeonpea reference set were mined to identify the superior haplotypes for 10 droughtresponsive candidate genes. A total of 83, 132 and 60 haplotypes were identified in breeding lines, landraces and wild species, respectively. Candidate gene-based association analysis of these 10 genes on a subset of 137 accessions of the pigeonpea reference set revealed 23 strong marker-trait associations (MTAs) in five genes influencing seven drought-responsive component traits. Haplo-pheno analysis for the strongly associated genes resulted in the identification of most promising haplotypes for three genes regulating five component drought traits. The haplotype C. cajan_23080-H2 for plant weight (PW), fresh weight (FW) and turgid weight (TW), the haplotype C. cajan_30211-H6 for PW, FW, TW and dry weight (DW), the haplotype C. cajan_26230-H11 for FW and DW and the haplotype C. cajan_26230-H5 for relative water content (RWC) were identified as superior haplotypes under drought stress condition. Furthermore, 17 accessions containing superior haplotypes for three drought-responsive genes were identified. The identified superior haplotypes and the accessions carrying these superior haplotypes will be very useful for deploying haplotype-based breeding to develop nextgeneration tailor-made better drought-responsive pigeonpea cultivars.

Though several genes governing various major traits have been reported in rice, their superior haplotype combinations for developing ideal variety remains elusive. In this study, haplotype analysis of 120 previously functionally characterized genes, influencing grain yield (87 genes) and grain quality (33 genes) revealed significant variations in the 3K rice genome (RG) panel. For selected genes, meta‐expression analysis using already available datasets along with co‐expression network provided insights at systems level. Also, we conducted candidate gene based association study for the 120 genes and identified 21 strongly associated genes governing 10‐grain yield and quality traits. We report superior haplotypes upon phenotyping the subset of 3K RG panel, SD1‐H8 with haplotype frequency (HF) of 30.13% in 3K RG panel, MOC1‐H9 (HF: 23.08%), IPA1‐H14 (HF: 6.64%), DEP3‐H2 (HF: 5.59%), DEP1‐H2 (HF: 37.53%), SP1‐H3 (HF: 5.05%), LAX1‐H5 (HF: 1.56%), LP‐H13 (3.64%), OSH1‐H4 (5.52%), PHD1‐H14 (HF: 15.21%), AGO7‐H15 (HF: 3.33%), ROC5‐H2 (31.42%), RSR1‐H8 (HF: 4.20%) and OsNAS3‐H2 (HF: 1.00%). For heading date, Ghd7‐H8 (HF: 3.08%), TOB1‐H10 (HF: 4.60%) flowered early, Ghd7‐H14 (HF: 42.60%), TRX1‐H9 (HF: 27.97%), OsVIL3‐H14 (HF: 1.72%) for medium duration flowering, while Ghd7‐H6 (HF: 1.65%), SNB‐H9 (HF: 9.35%) were late flowering. GS5‐H4 (HF: 65.84%) attributed slender, GS5‐H5 (HF: 29.00%), GW2‐H2 (HF: 4.13%) were medium slender and GS5‐H9 (HF: 2.15%) for bold grains. Furthermore, haplotype analysis explained possible genetic basis for superiority of selected mega‐varieties. Overall, this study suggests the possibility for developing next‐generation tailor‐made rice with superior haplotype combinations of target genes suiting future food and nutritional demands via haplotype‐based breeding.

Lin D, Feng R, Chen J (2010) Maximum Likelihood Methods for Assessing Genetic Imprinting Using Case-Control Mother-Child Pair Data. Citation: Feng R, Wu Y, Jang GH, Ordovas JM, Arnett D (2012) Correction: A Powerful Test of Parent-of-Origin Effects for Quantitative Traits Using Haplotypes.

The S locus, a single polymorphic locus, is responsible for self-incompatibility (SI) in the Brassicaceae family and many related plant families. Despite its importance, our knowledge of S-locus evolution is largely restricted to the causal genes encoding the S-locus receptor kinase (SRK) receptor and S-locus cysteine-rich protein (SCR) ligand of the SI system. Here, we present high-quality sequences of the genomic region of six S-locus haplotypes: Arabidopsis (Arabidopsis thaliana; one haplotype), Arabidopsis lyrata (four haplotypes), and Capsella rubella (one haplotype). We compared these with reference S-locus haplotypes of the self-compatible Arabidopsis and its SI congener A. lyrata. We subsequently reconstructed the likely genomic organization of the S locus in the most recent common ancestor of Arabidopsis and Capsella. As previously reported, the two SI-determining genes, SCR and SRK, showed a pattern of coevolution. In addition, consistent with previous studies, we found that duplication, gene conversion, and positive selection have been important factors in the evolution of these two genes and appear to contribute to the generation of new recognition specificities. Intriguingly, the inactive pseudo-S-locus haplotype in the self-compatible species C. rubella is likely to be an old S-locus haplotype that only very recently became fixed when C. rubella split off from its SI ancestor, Capsella grandiflora.

Recent long-read assemblies often exceed the quality and completeness of available reference genomes, making validation challenging. Here we present Merqury, a novel tool for reference-free assembly evaluation based on efficient k-mer set operations. By comparing k-mers in a de novo assembly to those found in unassembled high-accuracy reads, Merqury estimates base-level accuracy and completeness. For trios, Merqury can also evaluate haplotype-specific accuracy, completeness, phase block continuity, and switch errors. Multiple visualizations, such as k-mer spectrum plots, can be generated for evaluation. We demonstrate on both human and plant genomes that Merqury is a fast and robust method for assembly validation.

Summary Here, we describe a worldwide haplotype map for soybean (GmHapMap) constructed using whole‐genome sequence data for 1007 Glycine max accessions and yielding 14.9 million variants as well as 4.3 M tag single‐nucleotide polymorphisms (SNPs). When sampling random subsets of these accessions, the number of variants and tag SNPs plateaued beyond approximately 800 and 600 accessions, respectively. This suggests extensive coverage of diversity within the cultivated soybean. GmHapMap variants were imputed onto 21 618 previously genotyped accessions with up to 96% success for common alleles. A local association analysis was performed with the imputed data using markers located in a 1‐Mb region known to contribute to seed oil content and enabled us to identify a candidate causal SNP residing in the NPC1 gene. We determined gene‐centric haplotypes (407 867 GCHs) for the 55 589 genes and showed that such haplotypes can help to identify alleles that differ in the resulting phenotype. Finally, we predicted 18 031 putative loss‐of‐function (LOF) mutations in 10 662 genes and illustrated how such a resource can be used to explore gene function. The GmHapMap provides a unique worldwide resource for applied soybean genomics and breeding.