Subfunctionalization of phytochrome B1/B2 leads to differential auxin and photosynthetic responses

Gene duplication and polyploidization are genetic mechanisms that instantly add genetic material to an organism\u27s genome. Subsequent modification of the duplicated material leads to the evolution of neofunctionalization (new genetic functions), subfunctionalization (differential retention of genetic functions), redundancy, or a decay of duplicated genes to pseudogenes. Phytochromes are light receptors that play a large role in plant development. They are encoded by a small gene family that in tomato is comprised of five members: PHYA, PHYB1, PHYB2, PHYE, and PHYF. The most recent gene duplication within this family was in the ancestral PHYB gene. Using transcriptome profiling, co-expression network analysis, and physiological and molecular experimentation, we show that tomato SlPHYB1 and SlPHYB2 exhibit both common and non-redundant functions. Specifically, PHYB1 appears to be the major integrator of light and auxin responses, such as gravitropism and phototropism, while PHYB1 and PHYB2 regulate aspects of photosynthesis antagonistically to each other, suggesting that the genes have subfunctionalized since their duplication

Phytochrome A Regulates Carbon Flux in Dark Grown Tomato Seedlings

Phytochromes comprise a small family of photoreceptors with which plants gather environmental information that they use to make developmental decisions, from germination to photomorphogenesis to fruit development. Most phytochromes are activated by red light and de-activated by far-red light, but phytochrome A (phyA) is responsive to both and plays an important role during the well-studied transition of seedlings from dark to light growth. The role of phytochromes during skotomorphogenesis (dark development) prior to reaching light, however, has received considerably less attention although previous studies have suggested that phytochrome must play a role even in the dark. We profiled proteomic and transcriptomic seedling responses in tomato during the transition from dark to light growth and found that phyA participates in the regulation of carbon flux through major primary metabolic pathways, such as glycolysis, beta-oxidation, and the tricarboxylic acid (TCA) cycle. Additionally, phyA is involved in the attenuation of root growth soon after reaching light, possibly via control of sucrose allocation throughout the seedling by fine-tuning the expression levels of several sucrose transporters of the SWEET gene family even before the seedling reaches the light. Presumably, by participating in the control of major metabolic pathways, phyA sets the stage for photomorphogenesis for the dark grown seedling in anticipation of light

Lessons from model organisms: phenotypic robustness and missing heritability in complex disease.

Genetically tractable model organisms from phages to mice have taught us invaluable lessons about fundamental biological processes and disease-causing mutations. Owing to technological and computational advances, human biology and the causes of human diseases have become accessible as never before. Progress in identifying genetic determinants for human diseases has been most remarkable for Mendelian traits. In contrast, identifying genetic determinants for complex diseases such as diabetes, cancer, and cardiovascular and neurological diseases has remained challenging, despite the fact that these diseases cluster in families. Hundreds of variants associated with complex diseases have been found in genome-wide association studies (GWAS), yet most of these variants explain only a modest amount of the observed heritability, a phenomenon known as "missing heritability." The missing heritability has been attributed to many factors, mainly inadequacies in genotyping and phenotyping. We argue that lessons learned about complex traits in model organisms offer an alternative explanation for missing heritability in humans. In diverse model organisms, phenotypic robustness differs among individuals, and those with decreased robustness show increased penetrance of mutations and express previously cryptic genetic variation. We propose that phenotypic robustness also differs among humans and that individuals with lower robustness will be more responsive to genetic and environmental perturbations and hence susceptible to disease. Phenotypic robustness is a quantitative trait that can be accurately measured in model organisms, but not as yet in humans. We propose feasible approaches to measure robustness in large human populations, proof-of-principle experiments for robustness markers in model organisms, and a new GWAS design that takes differences in robustness into account

Current and suggested GWAS approaches.

<p>(A) Current approach. GWAS identify variants that are overrepresented in cases. Rare variants of large effect (red square, blue star) may escape detection, thereby contributing to missing heritability. Common variants that are overrepresented in cases (small yellow bar, 6 versus 2) do not contribute strongly to disease risk. A cryptic disease-related variant does not show significant overrepresentation in cases (open circle). (B) Suggested approach. Individuals are first analyzed for phenotypic robustness (bold box) and then for variants associated with disease. Rare variants of large effect will be enriched in robust cases, although they may also be present in nonrobust cases. Variants that are overrepresented in all cases (robust, nonrobust) will show higher penetrance in nonrobust individuals (large yellow bars). The formerly cryptic, disease-related variant (open circle) is significantly enriched in nonrobust cases versus nonrobust controls (and robust cases) and can therefore be identified. Together, heritability significantly increases. The formerly cryptic genetic variant and higher penetrance variant can be thought of as “disease-specifiers” as they determine the specific disease phenotype of individuals carrying them. Note symbols represent highly simplified frequencies of specific variant in indicated groups and not individuals carrying certain variants.</p

MIPSTR: a method for multiplex genotyping of germline and somatic STR variation across many individuals

Short tandem repeats (STRs) are highly mutable genetic elements that often reside in regulatory and coding DNA. The cumulative evidence of genetic studies on individual STRs suggests that STR variation profoundly affects phenotype and contributes to trait heritability. Despite recent advances in sequencing technology, STR variation has remained largely inaccessible across many individuals compared to single nucleotide variation or copy number variation. STR genotyping with short-read sequence data is confounded by (1) the difficulty of uniquely mapping short, low-complexity reads; and (2) the high rate of STR amplification stutter. Here, we present MIPSTR, a robust, scalable, and affordable method that addresses these challenges. MIPSTR uses targeted capture of STR loci by single-molecule Molecular Inversion Probes (smMIPs) and a unique mapping strategy. Targeted capture and our mapping strategy resolve the first challenge; the use of single molecule information resolves the second challenge. Unlike previous methods, MIPSTR is capable of distinguishing technical error due to amplification stutter from somatic STR mutations. In proof-of-principle experiments, we use MIPSTR to determine germline STR genotypes for 102 STR loci with high accuracy across diverse populations of the plant A. thaliana. We show that putatively functional STRs may be identified by deviation from predicted STR variation and by association with quantitative phenotypes. Using DNA mixing experiments and a mutant deficient in DNA repair, we demonstrate that MIPSTR can detect low-frequency somatic STR variants. MIPSTR is applicable to any organism with a high-quality reference genome and is scalable to genotyping many thousands of STR loci in thousands of individuals

MIPSTR: a method for multiplex genotyping of germline and somatic STR variation across many individuals

Short tandem repeats (STRs) are highly mutable genetic elements that often reside in regulatory and coding DNA. The cumulative evidence of genetic studies on individual STRs suggests that STR variation profoundly affects phenotype and contributes to trait heritability. Despite recent advances in sequencing technology, STR variation has remained largely inaccessible across many individuals compared to single nucleotide variation or copy number variation. STR genotyping with short-read sequence data is confounded by (1) the difficulty of uniquely mapping short, low-complexity reads; and (2) the high rate of STR amplification stutter. Here, we present MIPSTR, a robust, scalable, and affordable method that addresses these challenges. MIPSTR uses targeted capture of STR loci by single-molecule Molecular Inversion Probes (smMIPs) and a unique mapping strategy. Targeted capture and our mapping strategy resolve the first challenge; the use of single molecule information resolves the second challenge. Unlike previous methods, MIPSTR is capable of distinguishing technical error due to amplification stutter from somatic STR mutations. In proof-of-principle experiments, we use MIPSTR to determine germline STR genotypes for 102 STR loci with high accuracy across diverse populations of the plant A. thaliana. We show that putatively functional STRs may be identified by deviation from predicted STR variation and by association with quantitative phenotypes. Using DNA mixing experiments and a mutant deficient in DNA repair, we demonstrate that MIPSTR can detect low-frequency somatic STR variants. MIPSTR is applicable to any organism with a high-quality reference genome and is scalable to genotyping many thousands of STR loci in thousands of individuals