Danilo Hottis Lyra

Danilo is a quantitative and statistical geneticist at Rothamsted Research since 2018. He holds an M.S. and Ph.D. degree in Genetics and Plant Breeding having an extensive background in potato, maize, and wheat breeding/genomics. Danilo has a research background in classical field-based breeding activities, and experience in modern statistical genomics approaches where he focuses on understanding the genetic architecture of quantitative traits. He also received professional training at Iowa State University (Jianming Yu) and CIMMYT-Mexico (Jose Crossa). Briefly, his expertise is statistics, quantitative genetics, population genomics, QTL mapping, association studies, genomic selection, and plant breeding for abiotic stress tolerance (e.g. heat, drought, and nitrogen stress). Previously, he looked at several genomic selection approaches (i) including multi-trait models (Lyra et al. 2017), (ii) controlling population structure (Lyra et al. 2018), and (iii) incorporating dominance and copy number variation effects (Lyra et al. 2019) in maize hybrids. Currently, he is working on four main projects with extensive collaborations (e.g. JIC, Earlham) in hexaploid wheat: 1) combining high-throughput plant phenotyping and molecular genetics for trait dissection (Lyra et al. 2020); 2) gene-based mapping of trehalose biosynthetic pathway genes for source- and sink-related traits (Lyra et al. 2020); 3) development of a quantitative genetics pipeline for the wheat Cadenza TILLING population (Lyra et al. under development), and 4) integration of genomic and metagenomic data (e.g. rhizosphere microbiomes) for trait dissection. Danilo also has experience in teaching undergraduate courses as a tutor and has also taught biology in public high schools. (Fonte: Currículo Lattes)