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High-throughput genomic and phenomic data have enhanced the ability to detect genotype-to-phenotype associations that can resolve broad pleiotropic effects of mutations on plant phenotypes. As the scale of genotyping and phenotyping has advanced, rigorous methodologies have been developed to accommodate larger datasets and maintain statistical precision. However, determining the functional effects of associated genes/loci is expensive and limited due to the complexity associated with cloning and subsequent characterization. Here, we utilized phenomic imputation of a multi-year, multi-environment dataset using PHENIX which imputes missing data using kinship and correlated traits, and we screened insertions and deletions (InDels) from the recently whole-genome sequenced Sorghum Association Panel for putative loss-of-function effects. Candidate loci from genome-wide association results were screened for potential loss of function using a Bayesian Genome-Phenome Wide Association Study (BGPWAS) model across both functionally characterized and uncharacterized loci. Our approach is designed to facilitate in silico validation of associations beyond traditional candidate gene and literature-search approaches and to facilitate the identification of putative variants for functional analysis and reduce the incidence of false-positive candidates in current functional validation methods. Using this Bayesian GPWAS model, we identified associations for previously characterized genes with known loss-of-function alleles, specific genes falling within known quantitative trait loci, and genes without any previous genomewide associations while additionally detecting putative pleiotropic effects. In particular, we were able to identify the major tannin haplotypes at the Tan1 locus and effects of InDels on the protein folding. Depending on the haplotype present, heterodimer formation with Tan2 was significantly affected. We also identified major effect InDels in Dw2 and Ma1, where proteins were truncated due to frameshift mutations that resulted in early stop codons. These truncated proteins also lost most of their functional domains, suggesting that these indels likely result in loss of function. Here, we show that the Bayesian GPWAS model is able to identify loss-of-function alleles that can have significant effects upon protein structure and folding as well as multimer formation. Our approach to characterize loss-of-function mutations and their functional repercussions will facilitate precision genomics and breeding by identifying key targets for gene editing and trait integration. [ABSTRACT FROM AUTHOR]

High-throughput genomic and phenomic data have enhanced the ability to detect genotype-to-phenotype associations that can resolve broad pleiotropic effects of mutations on plant phenotypes. As the scale of genotyping and phenotyping has advanced, rigorous methodologies have been developed to accommodate larger datasets and maintain statistical precision. However, determining the functional effects of associated genes/loci is expensive and limited due to the complexity associated with cloning and subsequent characterization. Here, we utilized phenomic imputation of a multi-year, multi-environment dataset using PHENIX which imputes missing data using kinship and correlated traits, and we screened insertions and deletions (InDels) from the recently whole-genome sequenced Sorghum Association Panel for putative loss-of-function effects. Candidate loci from genome-wide association results were screened for potential loss of function using a Bayesian Genome-Phenome Wide Association Study (BGPWAS) model across both functionally characterized and uncharacterized loci. Our approach is designed to facilitate in silico validation of associations beyond traditional candidate gene and literature-search approaches and to facilitate the identification of putative variants for functional analysis and reduce the incidence of false-positive candidates in current functional validation methods. Using this Bayesian GPWAS model, we identified associations for previously characterized genes with known loss-of-function alleles, specific genes falling within known quantitative trait loci, and genes without any previous genome-wide associations while additionally detecting putative pleiotropic effects. In particular, we were able to identify the major tannin haplotypes at the Tan1 locus and effects of InDels on the protein folding. Depending on the haplotype present, heterodimer formation with Tan2 was significantly affected. We also identified major effect InDels in Dw2 and Ma1, where proteins were truncated due to frameshift mutations that resulted in early stop codons. These truncated proteins also lost most of their functional domains, suggesting that these indels likely result in loss of function. Here, we show that the Bayesian GPWAS model is able to identify loss-of-function alleles that can have significant effects upon protein structure and folding as well as multimer formation. Our approach to characterize loss-of-function mutations and their functional repercussions will facilitate precision genomics and breeding by identifying key targets for gene editing and trait integration.

Microsatellite sequences are particularly prone to slippage during DNA replication, forming insertion-deletion loops that, if left unrepaired, result in de novo mutations (expansions or contractions of the repeat array). Mismatch repair (MMR) is a critical DNA repair mechanism that corrects these insertion-deletion loops, thereby maintaining microsatellite stability. MMR deficiency gives rise to the molecular phenotype known as microsatellite instability (MSI). By sequencing MMR-proficient and -deficient (Mlh1+/+ and Mlh1−/−) single-cell exomes from mouse T cells, we reveal here several previously unrecognized features of in vivo MSI. Specifically, mutational dynamics of insertions and deletions were different on multiple levels. Factors that associated with propensity of mononucleotide microsatellites to insertions versus deletions were: microsatellite length, nucleotide composition of the mononucleotide tract, gene length and transcriptional status, as well replication timing. Here, we show on a single-cell level that deletions — the predominant MSI type in MMR-deficient cells — are preferentially associated with longer A/T tracts, long or transcribed genes and later-replicating genes. [ABSTRACT FROM AUTHOR]

African cichlid fishes are an ideal system for studying explosive rates of speciation and the origin of diversity in adaptive radiation. Within the last few million years, more than 2000 species have evolved in the Great Lakes of East Africa, the largest adaptive radiation in vertebrates. These young species show spectacular diversity in their coloration, morphology and behavior. However, little is known about the genomic basis of this astonishing diversity. Recently, five African cichlid genomes were sequenced, including that of the Nile tilapia (Oreochromis niloticus), a basal and only relatively moderately diversified lineage, and the genomes of four representative endemic species of the adaptive radiations, Neolamprologus brichardi, Astatotilapia burtoni, Metriaclima zebra, and Pundamila nyererei. Using the tilapia genome as the reference genome, we generated a high-resolution genomic variation map, consisting of single nucleotide polymorphisms (SNPs), short insertions and deletions (indels), inversions and deletions. In total, around 18.8, 17.7, 17.0 and 17.0 million SNPs, 2.3, 2.2, 1.4 and 1.9 million indels, 262, 306, 162, and 154 inversions, and 3509, 2705, 2710 and 2634 deletions were inferred to have evolved in the N. brichardi, A. burtoni, P. nyererei and M. zebra respectively. Many of these variations affected the annotated gene regions in the genome. Different patterns of genetic variation were detected during the adaptive radiation of African cichlid fishes. For SNPs, the highest rate of evolution was detected in the common ancestor of N. brichardi, A. burtoni, P. nyererei and M. zebra. However, for the evolution of inversions and deletions, we found that the rates at the terminal taxa are substantially higher than the rates at the ancestral lineages. The high-resolution map provides an ideal opportunity to understand the genomic bases of the adaptive radiation of African cichlid fishes.