28 research outputs found

    Measuring and Predicting Individual Differences in Executive Functions at 14 Months: A Longitudinal Study.

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    This study of 195 (108 boys) children seen twice during infancy (Time 1: 4.12 months; Time 2: 14.42 months) aimed to investigate the associations between and infant predictors of executive function (EF) at 14 months. Infants showed high levels of compliance with the EF tasks at 14 months. There was little evidence of cohesion among EF tasks but simple response inhibition was related to performance on two other EF tasks. Infant attention (but not parent-rated temperament) at 4 months predicted performance on two of the four EF tasks at 14 months. Results suggest that EF skills build on simpler component skills such as attention and response inhibition.ESR

    A sorghum practical haplotype graph facilitates genome‐wide imputation and cost‐effective genomic prediction

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    Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to accelerate cultivar development. To help with this, we developed a Sorghum bicolor Practical Haplotype Graph (PHG) pangenome database that stores haplotypes and variant information. We developed two PHGs in sorghum that were used to identify genome-wide variants for 24 founders of the Chibas sorghum breeding program from 0.01x sequence coverage. The PHG called single nucleotide polymorphisms (SNPs) with 5.9% error at 0.01x coverage—only 3% higher than PHG error when calling SNPs from 8x coverage sequence. Additionally, 207 progenies from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes were imputed from PHG parental haplotypes and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from .57–.73 and are similar to prediction accuracies obtained with genotyping-by-sequencing or targeted amplicon sequencing (rhAmpSeq) markers. This study demonstrates the use of a sorghum PHG to impute SNPs from low-coverage sequence data and shows that the PHG can unify genotype calls across multiple sequencing platforms. By reducing input sequence requirements, the PHG can decrease the cost of genotyping, make GS more feasible, and facilitate larger breeding populations. Our results demonstrate that the PHG is a useful research and breeding tool that maintains variant information from a diverse group of taxa, stores sequence data in a condensed but readily accessible format, unifies genotypes across genotyping platforms, and provides a cost-effective option for genomic selection
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