Genome-wide association study identifies multiple susceptibility loci for craniofacial microsomia

Craniofacial microsomia (CFM) is a rare congenital anomaly that involves immature derivatives from the first and second pharyngeal arches. The genetic pathogenesis of CFM is still unclear. Here we interrogate 0.9 million genetic variants in 939 CFM cases and 2,012 controls from China. After genotyping of an additional 443 cases and 1,669 controls, we identify 8 significantly associated loci with the most significant SNP rs13089920 (logistic regression P 1�4 2.15 � 10 � 120) and 5 suggestive loci. The above 13 associated loci, harboured by candidates of ROBO1, GATA3, GBX2, FGF3, NRP2, EDNRB, SHROOM3, SEMA7A, PLCD3, KLF12 and EPAS1, are found to be enriched for genes involved in neural crest cell (NCC) development and vasculogenesis. We then perform whole-genome sequencing on 21 samples from the case cohort, and identify several novel loss-of-function mutations within the associated loci. Our results provide new insights into genetic background of craniofacial microsomia

Mutation analysis of **TMC1** identifies four new mutations and suggests an additional deafness gene at loci DFNA36 and DFNB7/11

Hearing loss is the most frequent sensorineural disorder affecting 1 in 1000 newborns. In more than half of these babies, the hearing loss is inherited. Hereditary hearing loss is a very heterogeneous trait with about 100 gene localizations and 44 gene identifications for non-syndromic hearing loss. Transmembrane channel-like gene 1 (TMC1) has been identified as the disease-causing gene for autosomal dominant and autosomal recessive non-syndromic hearing loss at the DFNA36 and DFNB7/11 loci, respectively. To date, 2 dominant and 18 recessive TMC1 mutations have been reported as the cause of hearing loss in 34 families. In this report, we describe linkage to DFNA36 and DFNB7/11 in 1 family with dominant and 10 families with recessive non-syndromic sensorineural hearing loss. In addition, mutation analysis of TMC1 was performed in 51 familial Turkish patients with autosomal recessive hearing loss. TMC1 mutations were identified in seven of the families segregating recessive hearing loss. The pathogenic variants we found included two known mutations, c.100C > T and c.1165C > T, and four new mutations, c.2350C > T, c.776+1G > A, c.767delT and c.1166G > A. The absence of TMC1 mutations in the remaining six linked families implies the presence of mutations outside the coding region of this gene or alternatively at least one additional deafness-causing gene in this region. The analysis of copy number variations in TMC1 as well as DNA sequencing of 15 additional candidate genes did not reveal any proven pathogenic changes, leaving both hypotheses open

SSM-iCrop2 : A simple model for diverse crop species over large areas

Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senescence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straight-forward. The resultant model (SSM-iCrop2) was parameterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees.</p

SSM-iCrop2 : a simple model for diverse crop species over large areas

Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senescence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straight-forward. The resultant model (SSM-iCrop2) was parameterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees