Methods for Functional Characterization of Genetic Polymorphisms of Non-Coding Regulatory Regions of the Human Genome.

Currently, numerous associations between genetic polymorphisms and various diseases have been characterized through the Genome-Wide Association Studies. Majority of the clinically significant polymorphisms are localized in non-coding regions of the genome. While modern bioinformatic resources make it possible to predict molecular mechanisms that explain influence of the non-coding polymorphisms on gene expression, such hypotheses require experimental verification. This review discusses the methods for elucidating molecular mechanisms underlying dependence of the disease pathogenesis on specific genetic variants within the non-coding sequences. A particular focus is on the methods for identification of transcription factors with binding efficiency dependent on polymorphic variations. Despite remarkable progress in bioinformatic resources enabling prediction of the impact of polymorphisms on the disease pathogenesis, there is still the need for experimental approaches to investigate this issue.

Unraveling the genetic basis of methane emission in dairy cattle: a comprehensive exploration and breeding approach to lower methane emissions.

Ruminant animals, such as dairy cattle, produce CH4, which contributes to global warming emissions and reduces dietary energy for the cows. While the carbon foot print of milk production varies based on production systems, milk yield and farm management practices, enteric fermentation, and manure management are major contributors togreenhouse gas emissions from dairy cattle. Recent emerging evidence has revealed the existence of genetic variation for CH4 emission traits among dairy cattle, suggests their potential inclusion in breeding goals and genetic selection programs. Advancements in high-throughput sequencing technologies and analytical techniques have enabled the identification of potential metabolic biomarkers, candidate genes, and SNPs linked to methane emissions. Indeed, this review critically examines our current understanding of carbon foot print in milk production, major emission sources, rumen microbial community and enteric fermentation, and the genetic architecture of methane emission traits in dairy cattle. It also emphasizes important implications for breeding strategies aimed at halting methane emissions through selective breeding, microbiome driven breeding, breeding for feed efficiency, and breeding by gene editing.

Comparative Bioinformatic Analysis Reveals Conserved Regions in SARS-CoV-2 Genome for RAPID Pandemic Response.

In the face of the SARS-CoV-2 pandemic, characterized by the virus's rapid mutation rates, developing timely and targeted therapeutic and diagnostic interventions presents a significant challenge. This study utilizes bioinformatic analyses to pinpoint conserved genomic regions within SARS-CoV-2, offering a strategic advantage in the fight against this and future pathogens. Our approach has enabled the creation of a diagnostic assay that is not only rapid, reliable, and cost-effective but also possesses a remarkable capacity to detect a wide array of current and prospective variants with unmatched precision. The significance of our findings lies in the demonstration that focusing on these conserved genomic sequences can significantly enhance our preparedness for and response to emerging infectious diseases. By providing a blueprint for the development of versatile diagnostic tools and therapeutics, this research paves the way for a more effective global pandemic response strategy.

OGRE: calculate, visualize, and analyze overlap between genomic input regions and public annotations.

BACKGROUND: Modern genome sequencing leads to an ever-growing collection of genomic annotations. Combining these elements with a set of input regions (e.g. genes) would yield new insights in genomic associations, such as those involved in gene regulation. The required data are scattered across different databases making a manual approach tiresome, unpractical, and prone to error. Semi-automatic approaches require programming skills in data parsing, processing, overlap calculation, and visualization, which most biomedical researchers lack. Our aim was to develop an automated tool providing all necessary algorithms, benefiting both bioinformaticians and researchers without bioinformatic training. RESULTS: We developed overlapping annotated genomic regions (OGRE) as a comprehensive tool to associate and visualize input regions with genomic annotations. It does so by parsing regions of interest, mining publicly available annotations, and calculating possible overlaps between them. The user can thus identify location, type, and number of associated regulatory elements. Results are presented as easy to understand visualizations and result tables. We applied OGRE to recent studies and could show high reproducibility and potential new insights. To demonstrate OGRE's performance in terms of running time and output, we have conducted a benchmark and compared its features with similar tools. CONCLUSIONS: OGRE's functions and built-in annotations can be applied as a downstream overlap association step, which is compatible with most genomic sequencing outputs, and can thus enrich pre-existing analyses pipelines. Compared to similar tools, OGRE shows competitive performance, offers additional features, and has been successfully applied to two recent studies. Overall, OGRE addresses the lack of tools for automatic analysis, local genomic overlap calculation, and visualization by providing an easy to use, end-to-end solution for both biologists and computational scientists.

Insights into breeding history, hotspot regions of selection, and untapped allelic diversity for bread wheat breeding.

Breeding has increasingly altered the genetics of crop plants since the domestication of their wild progenitors. It is postulated that the genetic diversity of elite wheat breeding pools is too narrow to cope with future challenges. In contrast, plant genetic resources (PGRs) of wheat stored in genebanks are valuable sources of unexploited genetic diversity. Therefore, to ensure breeding progress in the future, it is of prime importance to identify the useful allelic diversity available in PGRs and to transfer it into elite breeding pools. Here, a diverse collection consisting of modern winter wheat cultivars and genebank accessions was investigated based on reduced-representation genomic sequencing and an iSelect single nucleotide polymorphism (SNP) chip array. Analyses of these datasets provided detailed insights into population structure, levels of genetic diversity, sources of new allelic diversity, and genomic regions affected by breeding activities. We identified 57 regions representing genomic signatures of selection and 827 regions representing private alleles associated exclusively with genebank accessions. The presence of known functional wheat genes, quantitative trait loci, and large chromosomal modifications, i.e., introgressions from wheat wild relatives, provided initial evidence for putative traits associated within these identified regions. These findings were supported by the results of ontology enrichment analyses. The results reported here will stimulate further research and promote breeding in the future by allowing for the targeted introduction of novel allelic diversity into elite wheat breeding pools.

GenomicDistributions: fast analysis of genomic intervals with Bioconductor.

BACKGROUND: Epigenome analysis relies on defined sets of genomic regions output by widely used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of genomic region sets is essential to answer biological questions in gene regulation. As the epigenomics community continues generating data, there will be an increasing need for software tools that can efficiently deal with more abundant and larger genomic region sets. Here, we introduce GenomicDistributions, an R package for fast and easy summarization and visualization of genomic region data. RESULTS: GenomicDistributions offers a broad selection of functions to calculate properties of genomic region sets, such as feature distances, genomic partition overlaps, and more. GenomicDistributions functions are meticulously optimized for best-in-class speed and generally outperform comparable functions in existing R packages. GenomicDistributions also offers plotting functions that produce editable ggplot objects. All GenomicDistributions functions follow a uniform naming scheme and can handle either single or multiple region set inputs. CONCLUSIONS: GenomicDistributions offers a fast and scalable tool for exploratory genomic region set analysis and visualization. GenomicDistributions excels in user-friendliness, flexibility of outputs, breadth of functions, and computational performance. GenomicDistributions is available from Bioconductor ( https://bioconductor.org/packages/release/bioc/html/GenomicDistributions.html ).

Genome-wide characterization of microsatellite DNA in fishes: survey and analysis of their abundance and frequency in genome-specific regions.

BACKGROUND: Microsatellite repeats are ubiquitous in organism genomes and play an important role in the chromatin organization, regulation of gene activity, recombination and DNA replication. Although microsatellite distribution patterns have been studied in most phylogenetic lineages, they are unclear in fish species. RESULTS: Here, we present the first systematic examination of microsatellite distribution in coding and non-coding regions of 14 fish genomes. Our study showed that the number and type of microsatellites displayed nonrandom distribution for both intragenic and intergenic regions, suggesting that they have potential roles in transcriptional or translational regulation and DNA replication slippage theories alone were insufficient to explain the distribution patterns. Our results showed that microsatellites are dominant in non-coding regions. The total number of microsatellites ranged from 78,378 to 1,012,084, and the relative density varied from 4925.76 bp/Mb to 25,401.97 bp/Mb. Overall, (A + T)-rich repeats were dominant. The dependence of repeat abundance on the length of the repeated unit (1-6 nt) showed a great similarity decrease, whereas more tri-nucleotide repeats were found in exonic regions than tetra-nucleotide repeats of most species. Moreover, the incidence of different repeated types appeared species- and genomic-specific. These results highlight potential mechanisms for maintaining microsatellite distribution, such as selective forces and mismatch repair systems. CONCLUSIONS: Our data could be beneficial for the studies of genome evolution and microsatellite DNA evolutionary dynamics, and facilitate the exploration of microsatellites structural, function, composition mode and molecular markers development in these species.

Understanding the Early Evolutionary Stages of a Tandem Drosophilamelanogaster-Specific Gene Family: A Structural and Functional Population Study.

Gene families underlie genetic innovation and phenotypic diversification. However, our understanding of the early genomic and functional evolution of tandemly arranged gene families remains incomplete as paralog sequence similarity hinders their accurate characterization. The Drosophila melanogaster-specific gene family Sdic is tandemly repeated and impacts sperm competition. We scrutinized Sdic in 20 geographically diverse populations using reference-quality genome assemblies, read-depth methodologies, and qPCR, finding that ∼90% of the individuals harbor 3-7 copies as well as evidence of population differentiation. In strains with reliable gene annotations, copy number variation (CNV) and differential transposable element insertions distinguish one structurally distinct version of the Sdic region per strain. All 31 annotated copies featured protein-coding potential and, based on the protein variant encoded, were categorized into 13 paratypes differing in their 3' ends, with 3-5 paratypes coexisting in any strain examined. Despite widespread gene conversion, the only copy present in all strains has functionally diverged at both coding and regulatory levels under positive selection. Contrary to artificial tandem duplications of the Sdic region that resulted in increased male expression, CNV in cosmopolitan strains did not correlate with expression levels, likely as a result of differential genome modifier composition. Duplicating the region did not enhance sperm competitiveness, suggesting a fitness cost at high expression levels or a plateau effect. Beyond facilitating a minimally optimal expression level, Sdic CNV acts as a catalyst of protein and regulatory diversity, showcasing a possible evolutionary path recently formed tandem multigene families can follow toward long-term consolidation in eukaryotic genomes.

Genome-wide association study and pathway analysis for fat deposition traits in nellore cattle raised in pasture-based systems.

Genome-wide association study (GWAS) is a powerful tool to identify candidate genes and genomic regions underlying key biological mechanisms associated with economically important traits. In this context, the aim of this study was to identify genomic regions and metabolic pathways associated with backfat thickness (BFT) and rump fat thickness (RFT) in Nellore cattle, raised in pasture-based systems. Ultrasound-based measurements of BFT and RFT (adjusted to 18 months of age) were collected in 11,750 animals, with 39,903 animals in the pedigree file. Additionally, 1,440 animals were genotyped using the GGP-indicus 35K SNP chip, containing 33,623 SNPs after the quality control. The single-step GWAS analyses were performed using the BLUPF90 family programs. Candidate genes were identified through the Ensembl database incorporated in the BioMart tool, while PANTHER and REVIGO were used to identify the key metabolic pathways and gene networks. A total of 18 genomic regions located on 10 different chromosomes and harbouring 23 candidate genes were identified for BFT. For RFT, 22 genomic regions were found on 14 chromosomes, with a total of 29 candidate genes identified. The results of the pathway analyses showed important genes for BFT, including TBL1XR1, AHCYL2, SLC4A7, AADAT, VPS53, IDH2 and ETS1, which are involved in lipid metabolism, synthesis of cellular amino acids, transport of solutes, transport between Golgi Complex membranes, cell differentiation and cellular development. The main genes identified for RFT were GSK3ß, LRP1B, EXT1, GRB2, SORCS1 and SLMAP, which are involved in metabolic pathways such as glycogen synthesis, lipid transport and homeostasis, polysaccharide and carbohydrate metabolism. Polymorphisms located in these candidate genes can be incorporated in commercial genotyping platforms to improve the accuracy of imputation and genomic evaluations for carcass fatness. In addition to uncovering biological mechanisms associated with carcass quality, the key gene pathways identified can also be incorporated in biology-driven genomic prediction methods.

Genetic dissection of days to flowering via genome-wide association studies in Turkish common bean germplasm.

Common bean is a nutrient-dense legume crop serving as a source of food for millions of people. Characterization of unexplored common bean germplasm to unlock the phenotypic and genetic variations is still needed to explore the breeding potential of this crop. The current study aimed to dissect the genetic basis having association for days to flowering (DF). A total of 188 common bean accessions collected from 19 provinces of Turkey were used as plant material under five environments and two locations. Analysis of variance (ANOVA) revealed that genotypes and genotype by environment interaction have significant effects on DF. A total of 10 most stable accessions were evaluated from stability analysis. Overall maximum (75) and minimum (54) DF were observed for Hakkari-51 and Mus-46 accessions, respectively. The implemented constellation plot divided studied germplasm according to their DF and growth habit. A total of 7900 DArTseq markers were used for association analysis. Mixed linear model using the Q + K Model resulted a total of 18 DArTseq markers from five environments. DArT-8668385 marker identified in Bolu during 2016 was also associated with DF in Sivas during 2017. Combined data of five years resulted a total of four markers (DArT-22346534, DArT-3369768, DArT-3374613, and DArT-3370801) having significant association ( p < 0.01 ) for DF. DArT-22346534 present on Pv 08 accounted a maximum of 9.89% variation to the studied trait. A total of four putative candidate genes were predicted from sequences reflecting homology to identified four DArTseq markers. We envisage that exploitation of identified DArTseq markers will hopefully beneficial for the development of new common bean varieties having better adaptation ability to changing climatic conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01029-8.

Discovery of genomic regions and candidate genes controlling shelling percentage using QTL-seq approach in cultivated peanut (Arachis hypogaea L.).

Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing high-quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics-assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL-seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68-4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89-790.32 million reads and achieving 91.85%-93.18% genome coverage and 14.04-21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68-4/two bulks) using the QTL-seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non-synonymous effects or in UTRs were identified in these regions for SP. Cost-effective KASP (Kompetitive Allele-Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties.

New candidate loci and marker genes on chromosome 7 for improved chilling tolerance in sorghum.

Sorghum is often exposed to suboptimal low temperature stress under field conditions, particularly at the seedling establishment stage. Enhancing chilling tolerance will facilitate earlier planting and so minimize the negative impacts of other stresses experienced at later growth stages. Genome-wide association mapping was performed on a sorghum association panel grown under control (30/20 °C; day/night) and chilling (20/10 °C) conditions. Genomic regions on chromosome 7, controlling the emergence index and seedling (root and shoot) vigor, were associated with increased chilling tolerance but they did not co-localize with undesirable tannin content quantitative trait loci (QTLs). Shoot and root samples from highly contrasting haplotype pairs expressing differential responses to chilling stress were used to identify candidate genes. Three candidate genes (an alpha/beta hydrolase domain protein, a DnaJ/Hsp40 motif-containing protein, and a YTH domain-containing RNA-binding protein) were expressed at significantly higher levels under chilling stress in the tolerant haplotype compared with the sensitive haplotype and BTx623. Moreover, two CBF/DREB1A transcription factors on chromosome 2 showed a divergent response to chilling in the contrasting haplotypes. These studies identify haplotype differences on chromosome 7 that modulate chilling tolerance by either regulating CBF or feeding back into this signaling pathway. We have identified new candidate genes that will be useful markers in ongoing efforts to develop tannin-free chilling-tolerant sorghum hybrids.

Combined approaches to identify genomic regions involved in phenotypic differentiation between low divergent breeds: Application in Sardinian sheep populations.

Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case-control genome-wide association study (GWAS), the Bayesian population differentiation analysis (FST ) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and FST and one marker between GWAS and Rsb. Three markers detected by Rsb were also located near (<2 Mb) to highly significant regions identified by GWAS and FST analyses. Moreover, one candidate marker identified by GWAS and FST approaches was located in a run of homozygosity island that was shared by both breeds. We identified several genes involved in many phenotypic differences (such as stature and growth, reproduction, ear size, coat colour, behaviour) between the two analysed breeds. This study shows that combining several genome-wide approaches could improve discovery of regions involved in the variability of breeding traits and responsible for the phenotypic diversity even between closely related breeds. Overall, the combination of such genome-wide methods can be extended to other livestock breeds that share between them a similar genetic background, to understand the process that shapes the patterns of genetic variability between closely related populations.

Small Supernumerary Marker Chromosome May Provide Information on Dosage-insensitive Pericentric Regions in Human.

BACKGROUND: Cytogenetically visible chromosomal imbalances in humans are deleterious and adverse in the majority of the cases. However, healthy persons living with chromosomal imbalances in the range of several megabasepairs (Mbps) in size, like carriers of small Supernumerary Marker Chromosomes (sSMCs) exist. MATERIALS & METHODS: The identification of healthy sSMC carriers with euchromatic centromere-near (ECN) imbalances led to the following proposal: ECN-regions do not contain any dosage sensitive genes. Due to own previous work, dosage-insensitive pericentric ECN-regions were already determined with an accuracy of 0.3 and 5 Mbp. Based on this data we established 43 new pericentromeric probe sets spanning about 3-5 Mbp of each euchromatic human chromosome arm starting from the known insensitive regions towards distal. Such so called pericentromeric-critical region fluorescence in situ hybridization (PeCR-FISH) probe sets were applied exemplarily and successful here in 15 sSMC cases as available from the Else Kröner-Fresenius-sSMC-cellbank . CONCLUSION: Most of the involved sSMC breakpoints could be characterized as a higher resolution than before. An unexpected result was that in 5/15 cases cryptic mosaicism was characterized. The latter is also to be considered to have potentially an influence on the clinical outcome in these so-called discontinuous sSMCs. Overall, the suitability of PeCR-FISH to characterize sSMCs was proven; the potential of this probe set to further delineate sizes of dosage insensitive pericentric regions is obvious but dependent on suited cases. Furthermore, discontinuous sSMCs can be identified by this approach and this new subtype of sSMC needs to be studied in more detail in future.

Genomic Regions Analysis of Seedling Root Traits and Their Regulation in Responses to Phosphorus Deficiency Tolerance in CSSL Population of Elite Super Hybrid Rice.

Phosphorus (P) is the essential macro-element supporting rice productivity. Quantitative trait loci (QTL) underlying related traits at the seedling stage under two different phosphorus levels was investigated in rice using a population of 76 Chromosomal Sequence Substitution Lines (CSSLs) derived from a cross between the maintainer variety XieqingzaoB (P stress tolerant) and the restorer variety Zhonghui9308 (P stress sensitive); the parents of super hybrid rice Xieyou9308. A genetic linkage map with 120 DNA marker loci was constructed. At logarithmic odd (LOD) value of 2.0, a total of seven QTLs were detected for studied traits under two P levels and their relative ratio. The LOD values ranged from 2.00 to 3.32 and explaining 10.82% to 18.46% of phenotypic variation. Three QTLs were detected under low phosphorus (P-), one under normal (P⁺) and three under their relative ratio (P-/P⁺) on the rice chromosomes 3, 5, 6, 8 and 10. No significant QTLs were found for shoot dry weight (SDW) and total dry weight (TDW). The pleiotropic QTLs influencing root number (qRN5) and root dry weight (qRDW5) as novel QTLs under P- level were detected near marker RM3638 on chromosome 5, which considered to directly contributing to phosphorus deficiency tolerance in rice. These QTLs need further analysis, including the fine mapping and cloning, which may use in molecular marker assisted breeding.

Detecting PKD1 variants in polycystic kidney disease patients by single-molecule long-read sequencing.

A genetic diagnosis of autosomal-dominant polycystic kidney disease (ADPKD) is challenging due to allelic heterogeneity, high GC content, and homology of the PKD1 gene with six pseudogenes. Short-read next-generation sequencing approaches, such as whole-genome sequencing and whole-exome sequencing, often fail at reliably characterizing complex regions such as PKD1. However, long-read single-molecule sequencing has been shown to be an alternative strategy that could overcome PKD1 complexities and discriminate between homologous regions of PKD1 and its pseudogenes. In this study, we present the increased power of resolution for complex regions using long-read sequencing to characterize a cohort of 19 patients with ADPKD. Our approach provided high sensitivity in identifying PKD1 pathogenic variants, diagnosing 94.7% of the patients. We show that reliable screening of ADPKD patients in a single test without interference of PKD1 homologous sequences, commonly introduced by residual amplification of PKD1 pseudogenes, by direct long-read sequencing is now possible. This strategy can be implemented in diagnostics and is highly suitable to sequence and resolve complex genomic regions that are of clinical relevance.

In silico screening of the chicken genome for overlaps between genomic regions: microRNA genes, coding and non-coding transcriptional units, QTL, and genetic variations.

MicroRNAs (miRNAs) are a class of non-coding RNAs involved in posttranscriptional regulation of target genes. Regulation requires complementarity between target mRNA and the mature miRNA seed region, responsible for their recognition and binding. It has been estimated that each miRNA targets approximately 200 genes, and genetic variability of miRNA genes has been reported to affect phenotypic variability and disease susceptibility in humans, livestock species, and model organisms. Polymorphisms in miRNA genes could therefore represent biomarkers for phenotypic traits in livestock animals. In our previous study, we collected polymorphisms within miRNA genes in chicken. In the present study, we identified miRNA-related genomic overlaps to prioritize genomic regions of interest for further functional studies and biomarker discovery. Overlapping genomic regions in chicken were analyzed using the following bioinformatics tools and databases: miRNA SNiPer, Ensembl, miRBase, NCBI Blast, and QTLdb. Out of 740 known pre-miRNA genes, 263 (35.5 %) contain polymorphisms; among them, 35 contain more than three polymorphisms The most polymorphic miRNA genes in chicken are gga-miR-6662, containing 23 single nucleotide polymorphisms (SNPs) within the pre-miRNA region, including five consecutive SNPs, and gga-miR-6688, containing ten polymorphisms including three consecutive polymorphisms. Several miRNA-related genomic hotspots have been revealed in chicken genome; polymorphic miRNA genes are located within protein-coding and/or non-coding transcription units and quantitative trait loci (QTL) associated with production traits. The present study includes the first description of an exonic miRNA in a chicken genome, an overlap between the miRNA gene and the exon of the protein-coding gene (gga-miR-6578/HADHB), and the first report of a missense polymorphism located within a mature miRNA seed region. Identified miRNA-related genomic hotspots in chicken can serve researchers as a starting point for further functional studies and association studies with poultry production and health traits and the basis for systematic screening of exonic miRNAs and missense/miRNA seed polymorphisms in other genomes.

Genomic variation at the tips of the adaptive radiation of Darwin's finches.

Adaptive radiation unfolds as selection acts on the genetic variation underlying functional traits. The nature of this variation can be revealed by studying the tips of an ongoing adaptive radiation. We studied genomic variation at the tips of the Darwin's finch radiation; specifically focusing on polymorphism within, and variation among, three sympatric species of the genus Geospiza. Using restriction site-associated DNA (RAD-seq), we characterized 32 569 single-nucleotide polymorphisms (SNPs), from which 11 outlier SNPs for beak and body size were uncovered by a genomewide association study (GWAS). Principal component analysis revealed that these 11 SNPs formed four statistically linked groups. Stepwise regression then revealed that the first PC score, which included 6 of the 11 top SNPs, explained over 80% of the variation in beak size, suggesting that selection on these traits influences multiple correlated loci. The two SNPs most strongly associated with beak size were near genes associated with beak morphology across deeper branches of the radiation: delta-like 1 homologue (DLK1) and high-mobility group AT-hook 2 (HMGA2). Our results suggest that (i) key adaptive traits are associated with a small fraction of the genome (11 of 32 569 SNPs), (ii) SNPs linked to the candidate genes are dispersed throughout the genome (on several chromosomes), and (iii) micro- and macro-evolutionary variation (roots and tips of the radiation) involve some shared and some unique genomic regions.

Dynamics of 1α,25-dihydroxyvitamin D3-dependent chromatin accessibility of early vitamin D receptor target genes.

The signaling cascade of the transcription factor vitamin D receptor (VDR) is triggered by its specific ligand 1α,25-dihydroxyvitamin D3 (1α,25(OH)2D3). In this study we demonstrate that in THP-1 human monocytic leukemia cells 87.4% of the 1034 most prominent genome-wide VDR binding sites co-localize with loci of open chromatin. At 165 of them 1α,25(OH)2D3 strongly increases chromatin accessibility and has at further 217 sites weaker effects. Interestingly, VDR binding sites in 1α,25(OH)2D3-responsive chromatin regions are far more often composed of direct repeats with 3 intervening nucleotides (DR3s) than those in ligand insensitive regions. DR3-containing VDR sites are enriched in the neighborhood of genes that are involved in controling cellular growth, while non-DR3 VDR binding is often found close to genes related to immunity. At the example of six early VDR target genes we show that the slope of their 1α,25(OH)2D3-induced transcription correlates with the basal chromatin accessibility of their major VDR binding regions. However, the chromatin loci controlling these genes are indistinguishable in their VDR association kinetics. Taken together, ligand responsive chromatin loci represent dynamically regulated contact points of VDR with the genome, from where it controls early 1α,25(OH)2D3 target genes.

Genetic mapping of regions associated with root system architecture in rice using MutMap QTL-seq.

The root system architecture is an important complex trait in rice. With changing climatic conditions and soil nutrient deficiencies, there is an immediate need to breed nutrient-use-efficient rice varieties with robust root system architectural (RSA) traits. To map the genomic regions associated with crucial component traits of RSA viz. root length and root volume, a biparental F2 mapping population was developed using TI-128, an Ethyl Methane Sulphonate (EMS) mutant of a mega variety BPT-5204 having high root length (RL) and root volume (RV) with wild type BPT-5204. Extreme bulks having high RL and RV and low RL and RV were the whole genome re-sequenced along with parents. Genetic mapping using the MutMap QTL-Seq approach elucidated two genomic intervals on Chr.12 (3.14-3.74 Mb, 18.11-20.85 Mb), and on Chr.2 (23.18-23.68 Mb) as potential regions associated with both RL and RV. The Kompetitive Allele Specific PCR (KASP) assays for SNPs with delta SNP index near 1 were associated with higher RL and RV in the panel of sixty-two genotypes varying in root length and volume. The KASP_SNPs viz. Chr12_S4 (C→T; Chr12:3243938), located in the 3' UTR region of LOC_Os12g06670 encoding a protein kinase domain-containing protein and Chr2_S6 (C→T; Chr2:23181622) present upstream in the regulator of chromosomal condensation protein LOC_Os2g38350. Validation of these genes using qRT-PCR and in-silico studies using various online tools and databases revealed higher expression in TI-128 as compared to BPT- 5204 at the seedling and panicle initiation stages implying the functional role in enhancing RL and RV.