Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to use, leaving many non-trivial, error-prone tasks to the user.

Animal domestication was a major step forward in human prehistory, contributing to the emergence of more complex societies. At the time of the Neolithic transition, zebu cattle (Bos indicus) were probably the most abundant and important domestic livestock species in Southern Asia. Although archaeological evidence points toward the domestication of zebu cattle within the Indian subcontinent, the exact geographic origins and phylogenetic history of zebu cattle remains uncertain. Here, we report evidence from 844 zebu mitochondrial DNA (mtDNA) sequences surveyed from 19 Asiatic countries comprising 8 regional groups, which identify 2 distinct mitochondrial haplogroups, termed I1 and I2. The marked increase in nucleotide diversity (P < 0.001) for both the I1 and I2 haplogroups within the northern part of the Indian subcontinent is consistent with an origin for all domestic zebu in this area. For haplogroup I1, genetic diversity was highest within the Indus Valley among the three hypothesized domestication centers (Indus Valley, Ganges, and South India). These data support the Indus Valley as the most likely center of origin for the I1 haplogroup and a primary center of zebu domestication. However, for the I2 haplogroup, a complex pattern of diversity is detected, preventing the unambiguous pinpointing of the exact place of origin for this zebu maternal lineage. Our findings are discussed with respect to the archaeological record for zebu domestication within the Indian subcontinent.

The application of DNA metabarcoding to dietary analysis of trophic generalists requires using multiple markers in order to overcome problems of primer specificity and bias. However, limited attention has been given to the integration of information from multiple markers, particularly when they partly overlap in the taxa amplified, and vary in taxonomic resolution and biases. Here, we test the use of a mix of universal and specific markers, provide criteria to integrate multi‐marker metabarcoding data and a python script to implement such criteria and produce a single list of taxa ingested per sample. We then compare the results of dietary analysis based on morphological methods, single markers, and the proposed combination of multiple markers. The study was based on the analysis of 115 faeces from a small passerine, the Black Wheatears (Oenanthe leucura). Morphological analysis detected far fewer plant taxa (12) than either a universal 18S marker (57) or the plant trnL marker (124). This may partly reflect the detection of secondary ingestion by molecular methods. Morphological identification also detected far fewer taxa (23) than when using 18S (91) or the arthropod markers IN16STK (244) and ZBJ (231), though each method missed or underestimated some prey items. Integration of multi‐marker data provided far more detailed dietary information than any single marker and estimated higher frequencies of occurrence of all taxa. Overall, our results show the value of integrating data from multiple, taxonomically overlapping markers in an example dietary data set.

Significance: The yellow, orange, and red colors of birds are produced through the deposition of carotenoid pigments into feathers and skin, and often function as signals in aggressive interactions and mate choice. These colors are hypothesized to communicate information about individual quality because their expression is linked to vital cellular processes through the mechanisms of carotenoid metabolism. To elucidate these mechanisms, we carried out genomic and biochemical analyses of the white recessive canary breed, which carries a heritable defect in carotenoid uptake. We identified a mutation in theSCARB1gene in this breed that disrupts carotenoid transport function. Our study implicates SCARB1 as a key mediator of carotenoid-based coloration and suggests a link between carotenoid coloration and lipid metabolism.