Natural variation for sulfate content in Arabidopsis thaliana is highly controlled by APR2

Most agronomic traits of importance, whether physiological (such as nutrient use efficiency) or developmental (such as flowering time), are controlled simultaneously by multiple genes and their interactions with the environment. Here, we show that variation in sulfate content between wild Arabidopsis thaliana accessions Bay-0 and Shahdara is controlled by a major quantitative trait locus that results in a strong interaction with nitrogen availability in the soil. Combining genetic and biochemical results and using a candidate gene approach, we have cloned the underlying gene, showing how a single-amino acid substitution in a key enzyme of the assimilatory sulfate reduction pathway, adenosine 5'-phosphosulfate reductase, is responsible for a decrease in enzyme activity, leading to sulfate accumulation in the plant. This work illustrates the potential of natural variation as a source of new alleles of known genes, which can aid in the study of gene function and metabolic pathway regulation. Our new insights on sulfate assimilation may have an impact on sulfur fertilizer use and stress defense improvement.     

The neuronal sortilin-related receptor SORL1 is genetically associated with Alzheimer disease

The recycling of the amyloid precursor protein (APP) from the cell surface via the endocytic pathways plays a key role in the generation of amyloid beta peptide (Abeta) in Alzheimer disease. We report here that inherited variants in the SORL1 neuronal sorting receptor are associated with late-onset Alzheimer disease. These variants, which occur in at least two different clusters of intronic sequences within the SORL1 gene (also known as LR11 or SORLA) may regulate tissue-specific expression of SORL1. We also show that SORL1 directs trafficking of APP into recycling pathways and that when SORL1 is underexpressed, APP is sorted into Abeta-generating compartments. These data suggest that inherited or acquired changes in SORL1 expression or function are mechanistically involved in causing Alzheimer disease.     

Loss of ACTN3 gene function alters mouse muscle metabolism and shows evidence of positive selection in humans

More than a billion humans worldwide are predicted to be completely deficient in the fast skeletal muscle fiber protein alpha-actinin-3 owing to homozygosity for a premature stop codon polymorphism, R577X, in the ACTN3 gene. The R577X polymorphism is associated with elite athlete status and human muscle performance, suggesting that alpha-actinin-3 deficiency influences the function of fast muscle fibers. Here we show that loss of alpha-actinin-3 expression in a knockout mouse model results in a shift in muscle metabolism toward the more efficient aerobic pathway and an increase in intrinsic endurance performance. In addition, we demonstrate that the genomic region surrounding the 577X null allele shows low levels of genetic variation and recombination in individuals of European and East Asian descent, consistent with strong, recent positive selection. We propose that the 577X allele has been positively selected in some human populations owing to its effect on skeletal muscle metabolism.     

Extremely low-coverage sequencing and imputation increases power for genome-wide association studies

Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power.